International Journal of Circuits, Systems and Signal Processing

E-ISSN: 1998-4464
Volume 12, 2018

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of NAUN Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

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Volume 12, 2018

Title of the Paper: Physical Property Characterization of Cux(1,2)O Nanofilms Grown on (100) Silicon by Thermal Copper Oxidation


Authors: Joel Díaz-Reyes, José Eladio Flores-Mena, Roberto Saúl Castillo-Ojeda, José M. Gutiérrez-Arias, María Montserrat Morín-Castillo

Pages: 742-746

Abstract: Cuprous oxide (Cu2O) and cupric oxide (CuO) films of nanometric thicknesses on monocrystalline (100) silicon were grown by thermal cupper oxidation technique. The copper nanofilms were deposited on crystalline (100) silicon by autocatalysis using watery solutions based on copper sulphate (CuSO4) and hydrofluoric acid (HF). The Cu2O was obtained at an annealing temperature of 200ºC, whereas for the CuO was necessary to use a higher oxidation temperature, 600ºC for 3 h. The thicknesses of the copper oxide layers were ranged from 30 to 150 nm obtained by ellipsometry. For the characterization of the oxidized copper layers, cuprous and cupric of oxides, were used different techniques. In order to examine the surface morphology of the films atomic force microscopy (AFM) was used and for the identification of the different oxides crystalline phases was used X-ray diffraction. By means of the Debye-Scherrer equation the nanocrystal size that forms the copper-based nanofilms was estimated. For the Cu nanofilm in the diffraction peak (111), a crystal size of 16.82 nm is obtained. Similarly, for Cu2O, the nanocrystal size is 8.11 nm and for the CuO, the size is 6.66 nm, which indicates that crystal size depends of the annealing temperature. The refractive indexes measured for the nanofilms oxidized at 200ºC was from 2.2-2.3 and for the obtained ones at 600ºC was from 2.7-2.9.

Title of the Paper: The Comparative Analysis of Information, Communication and Warning Systems


Authors: Katerina Vichova, Martin Hromada

Pages: 736-741

Abstract: This paper describes the information, communication and warning systems, which are using in the area of crisis management. For the purpose of this paper we selected system for crisis management to the three areas. Each states use different types of these systems for crisis management. The aim of this article is to describe these systems, and gives information about the using in the selected states. For each area of these systems we choose two or three state and describe them. There was used the heuristic analysis of usability, which was used for the systems in the Czech Republic.

Title of the Paper: Iterative Mining Algorithm based on Overlapping Communities in Social Networks


Authors: Jiayin Feng, Jinling Song, Dongyan Jia, Limin Shen

Pages: 730-735

Abstract: Social networks with complex structure and large scale emerged with the development of social network sites. Various network communities gradually form complex structural pattern in the production and living of people. The competitive advantages and community distribution in networks can be obtained through analyzing the structure of community. Therefore the research key point of the current data mining field is how to find out the potential structure of such large-scale social networks. Currently, most of real networks have overlapping communities. All the users can be allocated to different communities according to different allocation rules. But the complex structure of network and mass node information are difficulties for mining large-scale social network communities. Based on the discussion of relevant theories of complex network and mining algorithm, this study summarized and analyzed several algorithms for mining overlapping communities and put forward a high-efficient and effective overlapping community iterative mining algorithms. Moreover, experiments were carried out to verify its effectiveness and high efficiency. This work provides an improvement direction of relevant technologies for researchers who engage in network community data mining.

Title of the Paper: Recursive Fuzzy Operator for Contrast Enhancement of Digital Color Images


Authors: Fabrizio Russo

Pages: 721-729

Abstract: A new method for contrast enhancement of RGB color images is presented in this paper. The approach is based on a three-output recursive operator that adopts fuzzy relations in order to perform detail sharpening and noise reduction as well. The optimal amounts of sharpening and smoothing can be easily achieved by choosing a set of parameter values. Results of computer simulations dealing with color pictures corrupted by Gaussian noise show that the proposed method is very effective. It can sharpen the details of a color image and reduce the noise.

Title of the Paper: Art Animation Control based on Maya Embedded Language


Authors: Yan Yan

Pages: 713-720

Abstract: More and more industries tend to integrate with the computer industry for its rapid development; as a result, the digital media industry is born. This study adopted Maya embedded language (MEL) to control art animation, which overcame the problem of manual control and also accelerated the generation of three-dimensional animation. At first, the operation mode, modeling and technological content of Maya embedded language were introduced; then a three-dimensional tree animation generation experiment was carried out based on inverse kinematics (IK). The results demonstrated that, the method could skillfully manifest the actions of tree branches such as defoliation, fracture and swinging. Therefore, the technology is proved to be feasible, and it can be applied in the animation for trees and other aspects, thus to provide more technological supports for art animation control and offer assistance for people who begin to learn the production of three-dimensional art animation.

Title of the Paper: High Dimensional Video-based Face Recognition


Authors: Shailaja A. Patil, Pramod J. Deore

Pages: 704-712

Abstract: High dimensional data is the challenging task in Video-based Face Recognition system. Due to the curse of dimensionality, it needs a more memory space and more processing time (training or testing time). We propose a novel approach of concatenation of Graph Wavelet (GW) and Multi-radius Local Binary Pattern (MRLBP) to Video-based Face Recognition. After pre-processing step, the combination of Graph Wavelet (GW) and Multi-radius Local Binary Pattern (MRLBP) provide a flexible model to extract the data features of video and image face database. Independent component Analysis (ICA) is used to reduce these data features. Euclidean distance (ED) is used for matching the data features. Different experiments has been done with different face databases (Casia database for image to image recognition and NRC-IIT & HONDA-UCSD for video to video recognition). Experimental results show that the system achieves better performance, more accuracy, less processing time and less memory space than other video-based face recognition (VFR) algorithms on challenging, high dimensional video face databases and thus advancing the state-of-the-art.

Title of the Paper: Research on the Classification and Selection of Archive Texts with the Improved C4.5 Algorithm


Authors: Xianbin Lv

Pages: 698-703

Abstract: In the age of information explosion, how to get the information we need from mass information has always been a problem for us. Hence, many data mining techniques have been developed. In this paper, the scope of data mining was further narrowed based on a data model constructed from text categorization. Logarithmic calculation was converted to a simpler arithmetic hybrid operation, which reduced the time overhead of generating decision trees by the algorithm through eliminating the procedure to call the library function, thus reducing the time overhead of the entire text classification process, with the Fayyad and Irani Boundary Theorems as well as the decision tree C4.5 algorithm introduced. The experimental results showed that the improved algorithm in this paper had a classification time of 2 minutes and 44 seconds, which was shorter than the original C4.5 algorithm and its average classification accuracy of 92.91% was close to that of the original C4.5 algorithm. Therefore, the improved C4.5 algorithm could be well applied to the calculation of the file classification and had good results.

Title of the Paper: New Model of a Separately Excited D.C. Motor


Authors: Jozef Duda

Pages: 690-697

Abstract: In the paper a new model of a separately excited D.C. motor is presented. It is assumed that the mechanical torque do not cause the motion of the motor. This condition implies the model is nonlinear. The non-linearity of the model is reshaped to the linear model with time delay. The value of time delay depends on the value of mechanical torque which loads the motor. The parametric optimization problem for a new model of a separately existed D.C. motor with a P-controller is considered. The general quadratic performance index is used. The value of the quadratic performance index is equal to the value of the Lyapunov functional at initial function of time delay system. In the paper Repin’s method is used to determine the Lyapunov functional coefficients. The parametric optimization results for the separately excited D.C. motor Siemens 1GH6 size 225, the catalog number: 1GH6 226-ONA40-1VV3 are presented.

Title of the Paper: Software IMS Core Network under SIP Load Evaluation


Authors: Matej Kavacký

Pages: 684-689

Abstract: The aim of the paper is to present evaluation of software open-source IMS network under the load of SIP messages. The OpenIMS Core platform in virtualized environment were selected for evaluation. Then the performance tests based on the ETSI standard and its metrics are evaluated. The paper also presents some limitations and solutions for this platform which were encountered during our testing.

Title of the Paper: High Dimensional Video-based Face Recognition


Authors: Shailaja Arjun Patil, Pramod Jagan Deore

Pages: 674-683

Abstract: High dimensional data is the challenging task in Videobased Face Recognition system. Due to the curse of dimensionality, it needs a more memory space and more processing time (training or testing time). We have proposed a novel approach of concatenation of Graph Wavelet (GW) and Multi-Radius Local Binary Pattern (MRLBP) to VFR. After pre-processing step, the combination of GW and MRLBP provide a flexible model to extract the data features of video and image face database. Independent component Analysis (ICA) is used to reduce these data features. Euclidean distance (ED) is used for matching the data features. The experiments has been done with different face databases (Casia database for image to image recognition and NRC-IIT & HONDA-UCSD for video to video recognition). Experimental results show that, our system achieves better performance, more accuracy, less processing time and less memory space than other VFR algorithms on challenging, high dimensional video face databases and thus advancing the state-of-the-art.

Title of the Paper: Exclude: A New Heuristics Based Algorithm for Excluding Irrelevant Features in Inductive Learning


Authors: Saleh M. Abu-Soud

Pages: 661-673

Abstract: In this paper, a new algorithm, called Exclude, for excluding irrelevant features has been suggested. This algorithm is stand-alone which means that it can be applied by any inductive learning algorithm. It increases the efficiency of the inductive algorithm which is applied by, reduces number of rules, and simplifies the resulted rules (fewer conditions in their LHS). All this happens with maintaining the accuracy at acceptable levels. In Exclude algorithm, a new heuristic function has been suggested and tested with hundreds of experiments on many datasets with several known inductive algorithms. These experiments are categorized into three categories: the first set of experiments test the suggested approach on induction without feature subset selection, while the second set tests this approach on several decision tree and non-decision tree inductive learning algorithms as ILA, ID3, and AQ. The third set compares the results of this approach with the results of some other feature selection methods as Wrapper, PSORSFS and Relief-F. The results obtained are encouraging and showed that the suggested approach is powerful and comparable with other methods.

Title of the Paper: Face Classification Based on PCA by Using the Center and Foci of an Ellipse


Authors: W. Ieosanurak, S. Sakha, W. Klongdee

Pages: 653-660

Abstract: We introduce an improved method for face classification based on the nearest and the center of ellipse (NCE). The NCE is a method for face classification by using an ellipse. Before face classification, we use two-dimensional principal component analysis (PCA) for feature extraction, then a three points from the same class produce an ellipse together with inside three points, the foci and the center. The classification rules are as follows: 1) if the tested image is inside the ellipse, we calculate the average distance between the tested image and each of the inside three points; 2) otherwise, we find the minimum distance. The distance between the tested image and each of the three points which produce the ellipse. From both cases, we obtain the distance corresponding to the ellipse. Then we conclude that the tested image is in the same class with the ellipse which gives the minimum distance. A large number of experiments were investigated on the Faces94 and the Grimace database. Meanwhile, we compare our method with the shortest feature line segment (SFLS), the nearest and the center of ellipse (NCE). The proposed algorithm shows high performance and it has the average recognition rate over 96.88 %.

Title of the Paper: Forecasting Time Series for Power Consumption Data in Different Buildings Using the Fractional Brownian Motion


Authors: Valeria Bondarenko, Simona Filipova-Petrakieva, Ina Taralova, Desislav Andreev

Pages: 646-652

Abstract: In the present paper will be discussed the problem related to the individual household electric power consumption of objects in different areas – industry, farmers, banks, hospitals, theaters, hostels, supermarkets, universities. The main goal of the directed research is to estimate the active P and full S power consumptions for all studied buildings. The defined goal is achieved by solving of the following three problems. The first problem studies which buildings increase their power consumption. The second one finds which objects have the greatest increase of power consumption. And the third problem regards if it is possible to make a short-term forecast, based on the solutions of previous two problems. The present research and solving of the aforementioned problems is conducted using fractional Brownian motion theory. The applicability of this approach is illustrated on the example with 20 real objects in different areas. The paper ends with conclusion notes about possibilities to make short-term forecasts about power consumption of the considered buildings.

Title of the Paper: A Novel Hybrid Approach for Sentiment Classification of Turkish Tweets for GSM Operators


Authors: Ilkay Yelmen, Metin Zontul, Oguz Kaynar, Ferdi Sonmez

Pages: 637-645

Abstract: The increase in the amount of content shared on social media makes it difficult to extract meaningful information from scientific studies. Accordingly, in recent years, researchers have been working extensively on sentiment analysis studies for the automatic evaluation of social media data. One of the focuses of these studies is sentiment analysis on tweets. The more tweets are available, the more features in terms of words exist. This leads to the curse of dimensionality and sparsity, resulting in a decrease in the success of the classification. In this study, Gini Index, Information Gain and Genetic Algorithm (GA) are used for feature selection and Support Vector Machines (SVMs), Artificial Neural Networks (ANN) and Centroid Based classification algorithms are used for the classification of Turkish tweets obtained from 3 different GSM operators. The feature selection methods are combined with the classification methods to investigate the effect on the success rate of analysis. Especially, when the SVMs are used with the GA as a hybrid, 96.8% success has been achieved for the classification of the tweets as positive or negative.

Title of the Paper: Study of Electrical Switching Processes with NI USB Data Acquisition Systems and MATLAB-SIMULINK Environment


Authors: Titu Niculescu, Florin Gabriel Popescu, Marius Marcu, Ioan Razvan Slusariuc

Pages: 629-636

Abstract: For the study, the evaluation and visualization of switching processes, modern computer-aided measurement elements associated with high-speed data acquisition systems are used. In the paper is presented a method of study of switching phenomena using a NI USB data acquisition system produced by National Instruments. It is well known that the acquisition software provided by the manufacturing company is LabView. In the paper is presented a more efficient alternative method, based on the use of MATLAB software, and a design interface circuit attached to the NI USB system. In industrial electrical installations frequently occur situations where inductive circuits are connected to alternating current sources. The operation is accompanied by the emergence of transient modes characterized by the presence of surges and high instantaneous power for very short duration at the terminals of the inductive circuit. They can endanger the circuit elements. For two values of the connected circuit inductance, the voltage variation diagrams on the coil and the instantaneous power dissipated on them are plotted. Two methods of data acquisition are presented in the paper. The first method to study this, is the acquisition of data using a MATLAB program designed for the interface circuit presented in the paper and the NI USB data acquisition system. The second method of measurement is based on the use of the Simulink program package. Because there is no support software for data acquisition in Simulink in 64-bit systems, the paper presents a method that does this. The measurement method highlights its superiority compared to the use of LabView software. In the paper, both aspects of the switching are addressed, both by connecting an inductive circuit to an alternative voltage source and by disconnecting it from the source. Because in the introduction of the paper the theoretical phenomenon is presented both during connection and disconnection, in the conclusions are explained the differences that occur between the theoretical situation and the experimental results obtained from the measurement process with the help of the described method.

Title of the Paper: A Quasi-Alternating Markov-Modulated Linear Regression: Model Implementation Using Data about Coaches’ Delay Time


Authors: Nadezda Spiridovska

Pages: 617-628

Abstract: This research presents a case-study of quasi-alternating Markov-modulated linear regression application for analysis of delays of coaches (regional buses) on the route Ventspils-Riga in Latvia. Markov-modulated linear regression suggests that the parameters of regression model vary randomly in accordance with external environment which is described as a continuous-time homogeneous irreducible Markov chain with known parameters. Markov-modulated linear regression model differs from other switching models by a new analytical approach. For each state of the environment the regression model parameters are estimated. External environment has only two states in this research that is why model is called quasi-alternating. Data on weather conditions provided by the Latvian Environment, Geology and Meteorology Centre and is free downloaded from its database. Data on weather conditions in the Ventspils city are used for the environment description: two alternate states are assumed: “no precipitation” and “precipitation”. The model of the external environment is tested for the markovian properties using inferential statistics. Actual data on coaches’ trip times is provided by the Riga International Coach Terminal. Data are analysed by means of descriptive statistics. Different experiments are carried out and the application of Markov-modulated linear regression model on given sample showed adequate results indicating the validity of the model

Title of the Paper: Methods of Reducing the Distorting Regime Using Parallel Active Filters


Authors: M. Marcu, F. G. Popescu, T. Niculescu, I. R. Slusariuc

Pages: 604-616

Abstract: Given the nature of voltages and currents in nonlinear electrical networks with fast and random variation, it is understood that the power measurement methods cannot be based on averages or quadratic mean values, and it is necessary to offset the negative effects due to the presence of certain loads. In order to compensate the distorting regime, it is necessary to use active filters. The paper presents the structure of an active power filter to compensate higher order harmonics. Active Power Filter Control is performed using three theories (instantaneous reactive power, generalized power, and synchronous reference theories). In each of the three theories there is an analysis of the functioning of the system for loads balanced and unbalanced. The authors present the parallel active power filter based on these theories, and the results were simulated in MATLAB-Simulink. With the aims of these simulations, the authors made a comparative analysis in order to reduce the harmonic pollution to obtain conclusions about their efficiency.

Title of the Paper: Classes of Ordinary Differential Equations Obtained for the Probability Functions of Linear Failure Rate and Generalized Linear Failure Rate Distributions


Authors: Hilary I. Okagbue, Pelumi E. Oguntunde, Abiodun A. Opanuga, Patience I. Adamu

Pages: 596-603

Abstract: The linear failure rate (hazard) and generalized linear failure rate (hazard) distributions are uniquely identified by their linear hazard functions. In this paper, homogenous ordinary differential equations (ODES) of different orders were obtained for the probability functions of linear failure rate and generalized linear failure rate distributions. This is possible since the aforementioned probability functions of the distributions are differentiable and the former distribution is a particular case of the later. Differentiation and modified product rule were used to derive the required ODEs, whose solutions are the respective probability functions. The different conditions necessary for the existence of the ODEs were obtained and it is in consistent with the support that defined the various probability functions considered. The parameters that defined each distribution greatly affect the nature of the ODEs obtained. This method provides new ways of classifying and approximating other probability distributions apart from one considered in this research. Algorithms for implementation can be helpful in improving the results.

Title of the Paper: Design of Low Complexity Low Delay Short Length Code Based on Convolutional Encoder and LDPC Decoder


Authors: Bashar M. Mansoor, Tarik Z. Ismaeel

Pages: 587-595

Abstract: Due to their low delay and complexity, short length codes are attractive for use in wireless communication systems. Turbo and Low-Density Parity Check (LDPC) codes achieve excellent error correction capability and good performance at large block lengths, while the complexity and delay increase exponentially with block length. The main contribution of this work is to design a code with low time delay and low computation complexity, while having a improved BER performance. The proposed code is based on convolutional encoding and LDPC decoding, and can support variable block sizes and multiple code rates. The architecture of this code is investigated for short block length, which aims at optimizing performance by growing the generator and parity-check matrices. The proposed codes are evaluated and simulated over additive white Gaussian noise (AWGN) channel and Quadrature Phase Shift Keying (QPSK) modulation scheme, and then compared with irregular LDPC and turbo codes using a range of rates and block lengths. Theoretical analysis denotes that the structure of this code offers advantages in terms of latency and complexity, while simulation results show that the proposed code outperforms the irregular LDPC code by 0.4 dB and outperforms the turbo code (used in LTE) by 0.2 dB in terms of BER performance.

Title of the Paper: Recommended Items Rating Prediction Based on RBF Neural Network Optimized by PSO Algorithm


Authors: Chengfang Tan, Caiyin Wang, Yulin Li, Xixi Qi

Pages: 580-586

Abstract: In order to mitigate the data sparsity and cold-start problems of recommendation item ratings and more accurately predict the ratings of recommended items, according to the characteristics of the non-linearity and randomness in recommendation content changes, recommended items ratings prediction model based on RBF neural network optimized by PSO algorithm is proposed and the parameters of RBF neural network are globally optimized by using the proposed PSO algorithm. Experimental results show that, compared with the state-of-the-art models including the traditional user-based collaborating filtering method, the traditional item-based collaborating filtering method and RBF neural network model, the proposed RBF neural network optimized by PSO algorithm can more accurately predict the recommendation item ratings, which has higher prediction accuracy and much lower prediction error measured by Root Mean Square Error (RMSE), Precision@N and Recall@N.

Title of the Paper: Pyramid Loss for Person Re-identification


Authors: Yuanyuan Wang, Zhijian Wang, Mingxin Jiang

Pages: 573-579

Abstract: Person re-identification (ReID) is an important task in computer vision, meanwhile attracted the attention of industry. Person ReID focuses on identifying person among multiple different cameras. A key under-addressed problem is to learn a good metric for measuring the similarity among images. Recently, deep learning networks with metric learning loss has become a common framework for person ReID, such as triplet loss and its variants. However, the previous method mainly uses the distance to measure the similarity, and the distance measure is more sensitive when the scale changes. In this paper, we propose pyramid loss to learn better similarity metric for the person ReID. Our approach uses the angular relationship in triangles as a measure of similarity, minimizing the angle at the negative point of the triangle. Pyramid loss can learn better similarity metric and can achieve a higher performance on the person ReID benchmark datasets. The experimental results show that, our method yields competitive accuracy with the state-of-the-art methods.

Title of the Paper: The Most Significant MOSFET Parameters Impact in CMOS Inverter Switching Characteristics


Authors: Milaim Zabeli, Nebi Caka, Myzafere Limani, Qamil Kabashi

Pages: 565-572

Abstract: The objective of this paper is to research the impact of electrical and physical parameters that characterize the complementary MOSFETs (NMOS and PMOS transistors) in the dynamic behaviour (time-domain) of the CMOS inverter. In addition to this, the paper also aims at exploring the directives that are to be followed during the design phase of the CMOS inverters that enable designers to design the CMOS inverters with the best possible dynamic performance, depending on operation conditions. The CMOS inverter designed with the best possible dynamic features also enables the designing of the CMOS logic circuits with the best possible dynamic performance, according to the operation conditions and designers’ requirements.

Title of the Paper: Object Detection Based on RGB and Depth Information


Authors: Kangri Wang, Xiaolin Zhang

Pages: 559-564

Abstract: Object detection technology is an important technology for intelligent robot to understand the scene and conduct human-computer interaction. There are important applications in motion control. In this paper, the object detection technology based on RGB and depth information based on optimal dynamic programming algorithm is analyzed. Firstly, the related technology of robot object detection is introduced. On the basis of the discussion of object segmentation algorithm in RBG-D scene, the feasibility of optimizing dynamic programming algorithm for RGB and depth information object detection is studied.

Title of the Paper: A Random Zero Vector Strategy Based on Markov Chain for Induction Motor Drive


Authors: Xie Fang, Hang Bing, Kangkang Liang, Wenming Wu

Pages: 552-558

Abstract: Higher-order harmonics can affect the running performance of induction motor. For the problem, the change should be done from the harmonic spectrum distribution to proceed so that the output of the inverter harmonic components relatively evenly distributed in a wide band, so as to minimize noise. In this paper, based on the volt-second balance equation of traditional algorithm, the linear equations of the pulse time of switching devices in 3-phase upper arms are set up and solved, thus a simplified algorithm for SVPWM without coordinate transformation and sector judgment is proposed. Then, Markov chain algorithm is used to determine the zero vector distribution coefficient for the simplified algorithm. The simulation and experimental results verify the effectiveness of the proposed strategy on induction motor under different load.

Title of the Paper: Computer Aided Software for No-limit Texas Hold’em Poker


Authors: Wen-Hsing Lai, Zi-Hao Huang

Pages: 540-551

Abstract: No-limit Texas Hold’em Poker, with the features of multiple players, imperfect knowledge, risk and deception management, is a very important platform for implementing complex topics for machine intelligence, and developing computer programs that play poker at human level is considered to be a big challenge. Our goal is to establish a No-limit Texas Hold’em aided software to help players make decisions and gain steady profit. The aided software we built is based on expert rules, which are designed basically on simulated/enumerated win rate. First, we simulated/enumerated the win rate. Based on the win rate, we sort the strength of drawing hands and made hands in every round and build betting strategy rules by an expert from expert experience. The test experiments are performed on three world-renowned online poker games. The result shows that our aided software is very profitable. In 100 hands, averagely, our profit is 3.65 times in no-limit 2 and 3.95 times in no-limit 5 of the money we buy-in.

Title of the Paper: Model and Analysis of Multitasking Testing System Based on Network


Authors: Jin Guo, Qinkun Xiao, Zheng Qiu

Pages: 532-539

Abstract: To improve the system performance of multitasking testing system based on network, builds the model of multitasking testing system based on network by using TrueTime toolbox and Simulink module of the Matlab, simulates the different network types, gets data transmission rate and packet loss rate by the TrueTime Network, analyzes the performance of multitasking testing system respectively based on CAN bus and Ethernet, discusses the performance of network control multitasking testing system with the different data transmission rate. The calculation result shows that the multitasking testing system output curve with CAN bus has the small overshoot, short adjustment time, and quickly reach stability; the data transmission rate is 800kbits/s, the multitasking testing system has better performance than the data transmission rate is 80kbits/s according to the multitasking testing system output curve, improves the data transmission rate can effectively reduce the time delay.

Title of the Paper: Face Classification Based on PCA by Using the Centroid of a Triangle


Authors: W. Klongdee, W. Ieosanurak

Pages: 526-531

Abstract: This paper focuses centroid of a triangle for a face classification. We propose a simple, fast, uncomplicated and effective classification method for a face grayscale image based on principal component analysis (PCA) in grayscale of face images. Any triangle is generated from three points, which are obtained from the combination of m (a number of image per class) distinct points taken from the same class. The classification criteria is minimum the distance between the tested image and the centroid of the triangle. The proposed method tests on the Grimace and faces94 databases. The recognition rate is compared with the nearest neighbor (NN), the nearest feature line (NFL), the shortest feature line segment (SFLS), the restricted nearest feature line with ellipse (RNFL), and the nearest and the center of ellipse (NCE). The proposed algorithm shows high performance and it has recognition rate over 90%. Moreover, we compare time spent on the experiment of the proposed algorithm and other algorithms. We found that the time of the proposed algorithm is less than other algorithms.

Title of the Paper: Algorithms for Approximations in MGRSM Based on Maximal Compatible Granules


Authors: Chen Wu, Bingying Xia, Dandan Li, Ronghua Yang, Lijuan Wang, Xibei Yang

Pages: 520-525

Abstract: This paper emphasizes studying on the properties of approximations in rough set and multi-granulation rough set models based on maximal compatible classes as primitive ones in which any two objects are mutually compatible, obtains several theorem results, proposes and designs the upper and lower approximation computation algorithms in multi-granulation rough set model. It verifies the correctness of algorithms by examples and experiments.

Title of the Paper: Private Partner Selection of PPP Model for Rural Infrastructure Based on Grey Cluster Theory


Authors: Limei Liang, Lin Shen, Yabei Cui, Hongjie Liu

Pages: 514-519

Abstract: To overcome the shortcoming of analytic hierarchy process (AHP) and fuzzy theory in the private partner selection of public-private-partnership (PPP) model for rural infrastructure, a private partner selection method is presented based on grey cluster theory. The method can reflect the ability of private partners in an objective manner, which make the decision more objectively and accuracy. At first, this paper constructed evaluation index system of private partners of PPP model for rural infrastructure and built a selection model combined AHP and gray clustering method. Then this paper took water supply project in H city as the example to verify the applicability and feasibility of the model. The results showed that the critical factors were relevant experience and fund position of private enterprises, then the technological and managerial levels of the private enterprises. In view of analysis results, this paper offered suggestions such as innovation of financing channels, completion of rural financial system and supervisory system to secure the interests of farmers.

Title of the Paper: Tracking Control for an Autonomous Airship Based on Neural Dynamics Model with the Basktepping Technique and a Robust Sliding Mode Control


Authors: Tami Y., Melbous A., Guessoum A.

Pages: 505-513

Abstract: This paper presents a control approach hybrid for trajectory tracking of an autonomous airship. An integrated backstepping and sliding mode tracking control algorithm is developed for four dimensional tracking controls of an autonomous airship vehicles (AAV). First, a kinematic controller based on Neural Dynamics model with the Basktepping technique is integrated together with the dynamic controller uses a sliding mode control. In the traditional Backstepping method, speed jump occurs if the tracking error changes suddenly. The application of the biologically inspired model is designed to smooth the virtual velocity controller output, avoid speed jumps of autonomous airship vehicles in the large initial errors. Computer simulation results illustrate the effectiveness and efficiency of the control strategy proposed controller.

Title of the Paper: Image Feature Matching Based on Improved SIFT Algorithm


Authors: Jing Li

Pages: 500-504

Abstract: Image matching is a very important technology in the field of computer vision and image processing. SIFT algorithm can process feature matching issues between two images such as translation, rotation, scale change and illumination changes, and can have stable feature matching ability for perspective changes and affine changes to a certain extent. But SIFT feature matching also faces some problems, such as: more extracted image feature points, matching point redundancy, easiness to mismatch, large storage space and time-consuming matching etc. Therefore, this paper studies and improves SIFT algorithm to put forward an image feature matching by improved SIFT algorithm, and improves SIFT algorithm by combining the region extraction method to eliminate some unstable feature points beforehand, and extract the same target areas of two images before the matching, and then the area matching, and then match such region to reduce the SIFT feature points and increase the matching efficiency. Experiments show that such algorithm, based on the unchanged SIFT algorithm basic characteristics, has such advantages as large amount of matching points, no repeating point and higher matching efficiency, thus providing precise matching point for the image follow-up processing.

Title of the Paper: Personalized Recommendation System Based on Cloud Computing


Authors: Weiwei Jiao, Xin Li, Jingji Li

Pages: 494-499

Abstract: With the advent of cloud computing applications, the amount of data increases rapidly, personalized recommendation technology is becoming more and more important, however, because of the characteristics of cloud computing and large scale distributed processing architecture, the traditional recommendation techniques are applied directly to the cloud computing environment, will be faced with the recommended efficiency, accuracy and low personal problems, aiming at these problems, an improved method is proposed. This method combine’s user’s implicit query and context search query when users create interest models, so as to generate user personalized interest models, achieve immediate updating and accurately reflect user interest. In this paper, the principles and advantages of the improved method are analyzed in detail, and the flow chart of its recommendation steps is given.

Title of the Paper: Complex Mathematical Model of the Contact Center with Determining of the Optimal Number of Agents


Authors: Erik Chromy, Ivan Baronak

Pages: 488-493

Abstract: The paper deals with the contact center modeling with emphasis on the optimal number of agents. The mathematical model of the contact center can be described by various quality of service parameters. Suitable tool for contact center modeling is Erlang C formula. The contact center consist of IVR system and service groups. The IVR systen can be desribed by graph theory and with Markov model M/M/infinity/infinity. In our paper we propose also two new parameters – downtime and administrative task duration. These parameters are useful for better determination of the optimal number of contact center agents. Based on these parameters we propose a mathematical model for contact centers. At the end of the paper, we also propose a model with repeated calls in thr contact center. We have used the theory of extended Erlang B formula.

Title of the Paper: Part-of-Speech Tagging Based on Maximum Entropy


Authors: Hongdan Zhao, Jiangde Yu

Pages: 483-487

Abstract: Part-of-speech is a fundamental step in natural language processing. This paper presents a part-of speech tagging method base on Maximum entropy. The proposed method is made up of three steps, that is, (1) Designing the context feature. (2)Training process and (3) Tagging process. Maximum Entropy estimation is able to compute Probability Density Function of the random variables, and in this paper, we solve the problem of tagging part of speech by tackling an optimization problem using maximum entropy. Closed evaluations were performed on PKU, NCC and CTB corpus from Bakeoff 2007. Experimental results showed that the context feature window including 3 words was better, and using single-word feature set were appropriate for Chinese part of speech tagging.

Title of the Paper: Localization Algorithm Based on Classification for Wireless Sensor Networks


Authors: Keyu Zhuang

Pages: 477-482

Abstract: Node localization in wireless sensor networks is one of the key technologies as it plays a critical role in many applications. By the analysis of localization algorithm based on support vector machine, and using the classification function of SVM and combined with the RSSI(Received Signal Strength Indicator) location algorithm, a new localization algorithm based classification is proposed in the paper. The location area is firstly divided into densely populated regions and sparse regions by SVM, and then different algorithms are used to realize the localization, this can save computation and improve the accuracy. Simulation results show that the algorithm works well, and the algorithm ensures the algorithm complexity in the case of increased positioning accuracy.

Title of the Paper: Pseudo Measurements Based on Smart Meters Prosumer’s Characterization for Distribution System State Estimation


Authors: Ales Svigelj

Pages: 466-476

Abstract: Growing complexity of conventional distribution systems due to increasing penetration of the distributed generation such as wind and solar plants, calls for better observability or monitoring capabilities in order to allow higher and higher levels of penetration of distributed energy resources such as electric vehicles and batteries. The distribution system state estimation is seen as the key technology for providing the full observability of distribution grid. The most important input parameters into distribution system state estimation are topology parameters, phasor measurements and pseudo measurements. To this end, in this paper we are focusing on calculation of pseudo measurements, based on real prosumers characterization. More precisely, we are proposing clustering based pseudo measurements calculation based on real smart meters data. The results show that proposed method can improve the estimated values of pseudo measurements.

Title of the Paper: Knowledge Dependency Degree in TRSM and its Application to Robot Rod Catching Control


Authors: Chen Wu, Wei Zhu, Lijuan Wang

Pages: 458-465

Abstract: Through extending the related concept from complete decision table to incomplete one, the present paper first defines the concept of complete knowledge dependency and discusses relationships between tolerance class and indispensable attribute and knowledge dependency. It proves that reflectivity, transitivity, augmentation, decomposition rule and merge rule are valid for complete knowledge dependency. Secondly, it newly defines dependency degree and partial dependency degree in incomplete decision table with respect to whether or not decision attribute exist missing decision value. By finding that partial dependency degrees after transferring, augmenting and decomposing are not always kept in the same, it reveals several laws with proved theorems. Finally, it uses the knowledge dependency and dependency degree to design an algorithm to solve attribute reduction of incomplete decision table and apply the algorithm to realize robot rod catching control problem solving.

Title of the Paper: Color Correction for Panorama Video Surveillance


Authors: Jun Cheng, Wei Dai, Tianyin Liu

Pages: 452-457

Abstract: In panorama surveillance video, color inconsistency among different cameras always exists because of imperfect camera calibration, different reflection functions, CCD noise, etc. Since color inconsistency greatly reduces rendering quality of panorama surveillance video, a hybrid color correction method by combining the region matching with the gamma correction and the linear correction is proposed in this paper. Firstly, two frames from two adjacent cam-eras are matched using point feature correspondences and the overlapping areas are located by the homography. Secondly, the images in the overlapping areas are segmented into regions by marker-controlled watershed transformation and regions are matched using point feature correspondences. Finally, the color-corrected frame is generated from the combination of gamma correction for the luminance component and linear correction for the chrominance components of corresponding regions in the YUV color space. Experimental results show that the performance of color correction for panorama video is visually acceptable. This method can be improved the market competitiveness of panoramic video surveillance products.

Title of the Paper: Multitask Machine Learning for Financial Forecasting


Authors: Luca Di Persio, Oleksandr Honchar

Pages: 444-451

Abstract: In this paper we propose a new neural networks based regularization method requiring only 4 additional yperparameter and that can be easily injected in any machine learning architecture. It is based on the use of auxiliary loss functions designed to appropriately learn data momenta. Our approach can be used both for classification and regression problems. A comparative analysis with real time series will be provided concerning cryptocurrency data, showing improvements in accuracy of about 5% with respect to existing approaches, without requiring additional training data or further parameters. The presented approach constitutes an innovative, new step towards the statistical moments oriented regularization scheme for statistical forecasting.

Title of the Paper: Structure Design and Accuracy Analysis of High Precision Single Valve Spool Grinder


Authors: Kai Wang, Wanchen Sun, Qingtang Wu, Dongyan Wang

Pages: 438-443

Abstract: Aiming at the structure and accuracy of the single pump valve core grinder, the working process and structural characteristics of the core of the single pump were analyzed in this paper. The general structural design scheme of the grinder with the "L" type lathe bed and the high-precision motorized spindle as the sand wheel shaft and the CBN grinding wheel was put forward. Through the analysis of the grinding error, determine the error distribution principle. According to the characteristics of valve structure, characteristics and precision grinding, the errors are decomposed. And then, ultimately determine the range of error, to ensure that the total error can meet the processing requirements of grinder, laid the foundation for the following detailed design.

Title of the Paper: A New Method for Purification of Rayleigh Wave Signal Based on GSTTF-MT


Authors: Kunnan Qiu, Feimin Shen

Pages: 432-437

Abstract: It is a difficult problem to purify the Leibo signal from the seismic record. In order to purify the Rayleigh wave signal from seismic records, a new method for purification of Rayleigh wave exploration signal is proposed, which is based on the combination of multiple-filter technique and time-frequency filtering of generalized S transform (GSTTF-MT). GSTTF-MT calculation is described in this paper. It illustrates that the GSTTF-MT can be effectively applied to the Rayleigh wave purification through the simulation experiments and engineering examples. After analyzed and compared the advantages and disadvantages of GSTTF-MT and other methods. In conclusion, the method of GSTTF-MT is reliable and stable, and the experience and conclusions can be for reference to extraction of Rayleigh wave dispersion Curve in practical engineering.

Title of the Paper: Neuro-Fuzzy Control of Vehicle Active Suspension System


Authors: Haifa Souilem, Nabil Derbel

Pages: 423-431

Abstract: Adaptative Neuro-fuzzy controller (ANFIS) is applied in order to control vibration of vehicle’s suspensions for full suspension system which comes from road roughness. Moreover, the full vehicle system has seven degrees of freedom on the vertical direction of vehicle’s chassis, on the angular variation around X- axis and on the angular variation around Y- axis. The approach of the proposed controller is to minimize vibrations which are made on the road roughness. On the other hand, standard PID controller is also used to control whole vehicle’s suspension system for comparison. Consequently, random road roughnesses are used as disturbance of control system. Simulation results show that this control exhibited an improved ride comfort and good road holding ability and indicated that the proposed control system has superior performance at adapting random road disturbance for vehicle’s suspension.

Title of the Paper: Influence of Transient Recovery Voltage from the Parasitic Inductance in Grading Capacitors of Vacuum Circuit Breaker with Triple-interrupters


Authors: Xianghao Zeng, Haichuan Zhang, Jiyan Zou, Zhihui Huang

Pages: 416-422

Abstract: Under the condition of power frequency, the influence of the parasitic inductance in grading capacitor which connects with multi-vacuum interrupters in parallel is negligible, but when the breakers are opened by power grid break down, the TRV (Transient Recovery Voltage) will appear in high frequency, and the influence of the parasitic inductance on TRV will occur. In this paper, the model of post arc resistance will be established within the research of VCB (Vacuum Circuit Breaker) with triple-interrupters as background, then do simulation on the effect on TRV with different parasitic inductance value by ATP DRAW. When the inductance value is lower than 13μH, the wave form of TRV can be seen as sinusoidal variation, and when the inductance value is higher than 13μH, it can be seen as linear variation with the increase of inductance. As the inductance increased, the influence of voltage sharing is not obvious, but because of the existence of the parasitic inductance, there are inhibitory effects for the rate of TRV in 4μs after the interrupter breaking. At last, the module of VCB with triple interrupters is established, and the correctness of simulation results is proved by experiments.

Title of the Paper: A Constrained ILC Method for Signal Intersection’s Green Ratio in Fixed Cycle


Authors: Taiyuan Ruan, Hao Zhou, Zhiyong Liu

Pages: 412-415

Abstract: Under the urban arterial traffic coordination control, in order to ensure the formation of phase difference between the road intersections, the signal cycle of each intersection must be same. The vehicle queue length in the intersections is determined by the green time of each phase when the cycle is fixed. However, to optimize the green ratio quickly and effectively in each cycle is difficult. In this paper, we proposed a constrained Iterative Learning Control(ILC) method to solve this problem.In order to verify its effectivenes, six experiments are carried out to investigate the efficiency of ILC and constrained ILC for differernt traffic load under the arterial coordination control. The simulation results show: the control efficiency is higher under the constrained ILC than that under the ILC. In each cycle, the constrained ILC can calculate the optimum green ratio according to the vehicle queue length in the last cycle.So the constrained ILC presented in this paper,can optimize the green ratio effectively for different traffic load in a fixed cycle, it can minimize the vehicle queue length.

Title of the Paper: Enhancement of Bandwidth Efficiency for SLM SC-FDMA MIMO with Side Information


Authors: A. Khelil, D. Slimani, L. Talbi, J. LeBel

Pages: 405-411

Abstract: This paper presents a modified selective mapping (MSLM) based on the peak-to-average power ratio (PAPR) reduction technique for the single carrier frequency division multiple access with multiple input multiple output uplink system (SC-FDMA MIMO). The main idea of the proposed scheme is to use the same phase vectors for all antennas unlike the conventional scheme when each antenna has its own phase vectors. The branches of the same rang of all NT transmitting antennas are then multiplied point to point by the same phase vector. Then, the signal with minimum PAPR of each antenna is chosen to be transmitted. Simulation results show that the proposed scheme can achieve the same PAPR reduction performance as that of the conventional SLM SC-FDMA MIMO technique with 50% reduction on terms of number of side information bits and bandwidth degradation. Hence, it improves the bandwidth efficiency of the system. However, no improvement of the computational complexity is achieved over the conventional SLM SC-FDMA MIMO.

Title of the Paper: Prediction Model of Nonlinear Combination Based on Support Vector Machine


Authors: Yuping Yuan, Zenglong An, Yanting Sun

Pages: 399-404

Abstract: Grain yield prediction is a kind of randomness and complexity and has a strong nonlinear prediction problem. Adopting an intelligent optimization algorithm for support vector machines and combined forecasting technology. First, using the SOM method of self -organizing neural network to discretization attribute in order to establish information systems and decision table. Second, Transform determining weight coefficient into the evaluation of attribute significance among standard rough set theory, work out weight coefficient of single model amid combination prediction model. Use constructed combination prediction model, predict the historical data of grain gross output. At last, in order to reduce the risk of declining grain production, increase punish to the risk of grain production. The prediction model of support vector regression machine based on Ramp controlled asymmetric loss function is established. It shows the high accuracy of constructed combination prediction model in predicting the grain output.

Title of the Paper: Attack Probability Controllability Analysis Model Based on Attack Graph


Authors: Yan Li, Chunzi Wang, Jingfeng Shao, Bin Zhang

Pages: 387-398

Abstract: How to improve the accuracy of network security evaluation and promote its practicability under large-scale network is the focus of the research in the field of network security. This paper detailed summary the research status and progress in network security situational awareness. After that, provides a new model which refines the attack graph node to component level and describes the interaction process between the components in the attack step in the form of a directed weighted graph to improve coarse grain size and limitations of the current attack graph; At the same time, Through mathematical calculation, come out the standard condition of probability controllability or partial probability controllability for complex attack network, and proved the relationship between the probability controllability and the traditional controllability, besides give out the concrete method for controlling network and defense node selection; The analysis results and the examples show that, if valid defense existed, the complex networks can still provide normal service function in the case of attack and damage, the method proposed in this paper can greatly improve the precision of network security defense.

Title of the Paper: Improving Continuous Arabic Speech Recognition over Mobile Networks DSR and NSR Using MFCCs Features Transformed


Authors: L. Bouchakour, M. Debyeche

Pages: 379-386

Abstract: In this paper, we argue that the improved the performance of speech recognition in mobiles communication system, in order to improve the performance of Automatic Speech Recognition (ASR) systems, we have achieved by two modules Front-End or feature extractor used and a Back-End or recognizer. The Front-End we have used MFCC-MT (Multitaper Frequency Cepstral Coefficients features) and Gabor features GF-MFCC, are the result of their ability to extract discriminative internal representations that are robust to the many sources of variability in speech signals so to reduce spectral variations and correlations. In the back-end we have investigated different systems of classification in the field of speech using three systems: CHMM (Continues Hidden Markov Models), DNN (Deep Neural Network) and HMM-DNN hybrid. We have examined the DNN, which is usually used to reduce spectral variations and the spectral correlations that exist in model signals. Furthermore, we focused particularly on HMM-DNN in continuous speech recognition tasks of the large Arabic vocabulary, and we gave more emphasis to the optimal number of the hidden units and the best feature of input for DNN as well. Our findings show that HMM-DNN can achieve consistently almost 8% of clean speech, 13% of AMR-NB coder and 8.5% of DSR coders. The system was trained using the 3hour training set 440 sentences with 20 speakers with labels generated by Viterbi alignment from a maximum likelihood ML trained CHMM system using the HTK toolkits.

Title of the Paper: The Composite Control Method for Piston Stop Position of the GDI Engine


Authors: Honghui Mu, Xuejun Li, Jun Tang

Pages: 372-378

Abstract: The instantaneous reverse starting technique can restart engine quietly and quickly, the crucial problem of this technique is the piston stop position. In this paper, the piston stop position is converted to the electric throttle control technique, the dynamical model of electric throttle is designed, and the composite controller is proposed to control the throttle opening, then the amount of air inflow cylinder is crucial for the piston stop position. The feed-forward nonlinear compensation controller is designed to compensate the friction force and spring torque, then the electric throttle system is described as nonlinear SISO system. The feedback controller is an adaptive fuzzy sliding-mode controller which is based on equivalent control and switching control, and combined with fuzzy logic and sliding mode control, that not only retain the rapidity and robustness of sliding mode control, but also reduce the buffeting. The simulation results show that the composite controller can enable the throttle opening track the input quickly and accurately.

Title of the Paper: User Sensitive Data Identification Method Based on Constraint Gaussian Mixture-Probability Hypothesis Density Filter


Authors: Zhengqiu Lu, Shengjun Xue, Chunliang Zhou, Quanping Hua, Defa Hu, Weijin Jiang

Pages: 367-371

Abstract: In order to identify the sensitive data of users in Internet, a sensitive data identification method is proposed by weight constraint Gaussian Mixture-Probability Hypothesis Density (GM-PHD) filter and Restricted Boltzmann Machines (RBM) in this thesis. At first, the data is normalized with weight constraint in this method, and the random network is formed by the definition of the collected characteristic simulation energy function of RBM. Then, the sensitive feature weight of sensitive data is generated in GM-PHD filter. Finally, the simulation experiments are conducted to study this method performance compared with GM-PGD filter, Gaussian filter by MATLAB, including filtering and tracking performance, relevancy degree, sensitive words weight, cluster mapping and high frequency approximation. The results show that, compared with other methods, this method has better performance.

Title of the Paper: An Efficient Communication Protocol for Wireless Sensor Network Using Differential Encoding Based Compressed Sensing Technique


Authors: A. Parnasree Chakraborty, B. Tharini Prasad

Pages: 356-366

Abstract: Wireless sensor networks (WSNs) are typically resource constrained network due to restricted parameters like power supply, processing speed, memory requirement and bandwidth required for communication. Energy consumption is a key issue in the design of protocols and algorithms for WSNs due to their limited power supply. WSN operations involve sensing of data, computation, switching from node to node, transmission etc. In all these operations, energy efficiency is very essential. It is found in literature that, most of the energy is consumed in WSNs is due to the radio communications. In radio communication if the number of bits of data to be transmitted is reduced by some amount then it is possible to reduce the energy consumption. Hence it is essential to use data compression to reduce the number of bits to be transmitted. Researchers have investigated many energy efficient light weight compression algorithms suitable for WSN data. Still there is a requirement for efficient compression algorithms for WSN which minimizes the mean square error (MSE) of received data and hence in this paper differential encoding based compressed sensing (CS) algorithm is suggested. A CODEC design is suggested for improving the reconstruction quality. Simulation results show improvement in reconstruction quality and reduction in MSE value compared to standard compressed sensing technique.

Title of the Paper: Dynamic Security Authentication Protocol Based on Hash Function for RFID System


Authors: Baolong Liu, Bing Yang

Pages: 349-355

Abstract: In order to ensure the information security of the RFID system, this paper proposes a dynamic security authentication protocol based on hash function to prevent asynchronous attack within RFID system. The proposed protocol uses the tag key and the tag ID updating method to ensure the two-way authentication between the tag and the reader to avoid asynchronous attack. The correctness of the protocol is proved by using BAN logic analysis. The experimental results show that the protocol proposed can satisfy the security requirement of RFID system. Compared to existing security protocols, the presented protocol has improved the security level of RFID system. The solution can be implemented in the hardware environment, which provides a reliable approach for RFID system application in practical.

Title of the Paper: Segmentation of Gray Scale Images of Dropwise Condensation on Textured Surfaces


Authors: Helene Martin, Solmaz Boroomandi Barati, Nicolas Pionnier, Jean-Charles Pinoli, Stephane Valette, Yann Gavet

Pages: 339-348

Abstract: In the present work we developed an image processing algorithm to measure water droplets characteristics during dropwise condensation on pillared surfaces. The main problem in this process is the similarity between shape and size of water droplets and the pillars. The developed method divides droplets into four main groups based on their size and applies the corresponding algorithm to segment each group. These algorithms generate binary images of droplets based on both their geometrical and intensity properties. The information related to droplets evolution during time including mean radius and drops number per unit area are then extracted from the binary images. The developed image processing algorithm is verified using manual detection and applied to two different sets of images corresponding to two kinds of pillared surfaces.

Title of the Paper: Analysis on Motor Control System Based on DSP


Authors: Jie Luo, Wenchang Li, Huaxiang Lu

Pages: 333-338

Abstract: DSP is a microprocessor commonly used in the design of motor control system, which is characterized by the advantages of strong data processing ability and fast running speed. This paper analyzes the design of motor control system based on DPS, including hardware design and software design. Hardware system structure, DPS main controller application, motor driver selection and communication circuit design are all analyzed; wherefrom the software design scheme, motor speed regulation method, the method of rotational speed measurement and the design method of SCI serial communication module are put forward, and finally the experimental verification to the system is conducted.

Title of the Paper: Fuzzy Numerical Solution to Horizontal Infiltration


Authors: N. Samarinas, C. Tzimopoulos, C. Evangelides

Pages: 325-332

Abstract: In this paper we examine the fuzzy numerical solution to a second order partial differential equation, called absorption equation, which in general describes the water movement. The uncertainties that appear, from either human or machine errors, in this equation greatly affect the results and for this reason they should be taken into account. The solution in this problem is to use the fuzzy set theory. Here, we present an implicit finite difference scheme in combination with fuzzy logic. Since the problem refers to a partial differential equation, the Generalized Hukuhara (gH) derivative was used in order to find the correct form of the linear system of equations.

Title of the Paper: Research on the Risk Crisis Prediction of Enterprise Finance by Genetic Algorithm


Authors: Tingting Ye

Pages: 319-324

Abstract: With the development of the global economy, the competition between enterprises is getting fiercer and enterprises are facing increasing crises and challenges As a result, the prediction of risk crisis of enterprises becomes very important. The growing numbers of data within enterprises have caused great inconvenience to the risk crisis forecasts. In this paper, the genetic algorithm is analyzed. With this algorithm, a large number of high-latitude data are reduced in dimension. The genetic algorithm is also used to optimize the neural network. A genetic algorithm model is established by MATLAB. The experiment proves that this algorithm can effectively optimize the BP neural network, and has an obvious early warning effect on the financial risk crisis with high accuracy, which provides a reference for the application of the algorithm in the prediction of the financial risk crisis.

Title of the Paper: Reachability Analysis of Nonlinear Hybrid Systems with Mixed Contacting


Authors: Ren Shengbing, Liu Yuan, Huang Fei, Jia Mengyu

Pages: 312-318

Abstract: How to calculate the intersection set of flows and guards quickly and accurately is at the core of nonlinear hybrid systems reachability analysis. The continuous flow condition of dynamic system of nonlinear hybrid systems are usually expressed by the implicit differential equations. Interval Taylor method with QR decomposition method is adopted in this paper that can explicitly express the boundaries of flows. Then the flows and guards can be expressed as Constraint Satisfaction Problem (CSP for short). At this moment, using the mixed contracting algorithms to solve the CSP that can calculate the intersection set of flows and guards. In the mixed contracting algorithm, when contracting the domain, single contractor is no longer used, but according to the use cycle to select the corresponding contractor. In the contraction domain, the strong but time-cost contractor and the weak but time-save contractor will be used interchangeably, that can improve the computing accuracy and reduce the time-consuming. The experimental results show that this method can quickly and accurately solve the intersection set of flows and guards.

Title of the Paper: Peculiarities of the Electric Field Calculation of the Artificial Thunderstorm Cells


Authors: Alexander G. Temnikov, Leonid L. Chernensky, Alexander A. Orlov, Tatiana K. Kivshar, Nikolay Y. Lysov, Olga S. Belova, Daria S. Zhuravkova

Pages: 305-311

Abstract: Method of the calculation of the formation dynamics of the electric fields of a single and a system of two artificial thunderstorm cells is considered in paper. Method of the electric field calculation of the fully developed charged aerosol flow is based on the theoretical and experimentally measured parameters of a turbulent jets. Method of the calculation of the dynamics of the electric field formation of the turbulent charged submerged aerosol flow is based on the method of “big particles”. Application of these methods for calculation of the electric fields of single artificial thunderstorm cell and for the system of two vertically disposed artificial thunderstorm cells has been considered in paper. It was established that near the second is required for the creation of the fully charged artificial thunderstorm cell. It is shown that the maximal electric field strength will achieve in the space between the artificial thunderstorm cells of the different polarity. It is found that the maximal electric field strength will be above upper and beneath bottom unipolar artificial thunderstorm cells. It was experimentally shown that the model hydrometeor arrays posed in these places could initiate intensive discharge phenomena (from powerful streamers to clear observed return strokes) between the charged clouds and between the artificial thunderstorm cells and the ground. Received results could help to find the methods of the artificial lightning initiation in thunderclouds.

Title of the Paper: Numerical Optimization Solution of System of Non-Linear Equations Based on Interval Algorithm


Authors: Guobing Fan, Chen Guo, Sha Fu

Pages: 298-304

Abstract: Non-linear problem extensively exists in our life; however the solution algorithm for system of non-linear equations is always not perfect enough because of local optimum and low numerical calculation preciseness. This study aims to solve the numerical solution optimization of system of non-linear equations through algorithm. Based on traditional interval algorithm, this study put forward optimized interval algorithm which had improved Krawczyk iterative operator and combined it with genetic algorithm to compose genetic-optimization interval algorithm to perform optimization solution on system of non-linear equations. Then it was tested using several numerical examples. Finally the results suggested that the genetic-optimization interval solution algorithm could precisely calculate the solution of system of non-linear equations in shorter time, which achieved the research purpose of numerical optimization solution of system of non-linear equations.

Title of the Paper: Reichenbach and f-Generated Implications in Fuzzy Database Relations


Authors: Nedžad Dukić, Dženan Gušić, Nermana Kajmović

Pages: 285-297

Abstract: Applying a definition of attribute conformance based on a similarity relation, we introduce an interpretation as a function associated to some fuzzy relation instance and defined on the universal set of attributes. As a consequence, the attributes become fuzzy formulas. Conjunctions, disjunctions and implications between the attributes become fuzzy formulas as well in view of the requirement that the interpretation has to agree with the minimum t-norm, the maximum t-conorm and appropriately chosen fuzzy implication. The purpose of this paper is to derive a number of results related to these fuzzy formulas if the fuzzy implication is selected so to be either Reichenbach or some f-generated fuzzy implication.

Title of the Paper: Design of 24GHz Frequency Source Based on Phase Noise Analysis


Authors: Bo Yin, Shuai Zhang, Shiwei Zhao, Wei Luo, Wen Huang

Pages: 279-284

Abstract: A 24 GHz Phase-Locked Loop (PLL) frequency source based on the analysis of the phase noise of the system is presented. Instead of using Direct Digital Synthesizer (DDS) and the combination of DDS and PLL, the design method of a single PLL circuit is adopted in this paper. Based on the phase noise model of the PLL system, it is concluded that the selection of loop bandwidth determines the phase noise performance of the frequency source by analyzing the characteristics of the phase noise transfer function of each noise source. ADIsimPLL4.10 software is used to adjust the bandwidth of the Loop Filter, so that the designed Loop Filter meets the design requirements of the 24GHz microwave frequency source. The test results show that output frequency of the frequency source is at 24.17GHz, and its phase noise is -102.48dBc/Hz@10kHz. Compared with the frequency source designed by other methods, this design has the advantage of low phase noise.

Title of the Paper: Integration of Hash -Crypto- Steganography for Efficient Security Technique


Authors: Saleh Saraireh, Jaafer Al-Saraireh, Mohammad Saraireh

Pages: 274-278

Abstract: The exchange of data over wired and wireless communication networks is influenced by various security attacks and threats. This issue requires the implementation of secure system to provide confidentiality and data integrity to ensure secure data exchange. In this paper integration between different security algorithms is proposed to satisfy confidentiality and data integrity of the transmitted data. Data encryption, hashing algorithm and steganography technique are used to protect data transmission over communication channels. The proposed approach combines these techniques together to obtain a secure and strong communication system. The proposed technique provides confidentiality, data integrity; scalability, low complexity and high speed by using a symmetric cryptographic technique namely, filter bank block cipher. DWT based steganography, and MD5 hashing algorithm. The propose algorithm performance is evaluated and analyzed using different images. Simulation results show that confidentiality and integrity are achieved as reflected from the obtained high peak signal to noise ratio (PSNR) and high perceptual quality of the histogram analysis.

Title of the Paper: Adaptive Subspace Predictive Control and its Application in 2-CSTR System


Authors: Baoshan Cao, Xiaosuo Luo

Pages: 268-273

Abstract: A new adaptive subspace predictive control method is proposed for the problem that the control performance is ineffective when conventional control methods are applied in the processes of complex chemical production, and the chemical processes have the nonlinear and time-varying characteristics. We get the subspace predictors through input and output data by the subspace identification method. The subspace predictors are used as the prediction model to design the predictive controller directly. The predictive controller is to get the control sequence which can be obtained by minimizing the cost function and the control input is calculated from the control sequence. Based on the advantages of the integrated rolling window and the recursive identification method, the adaptive strategy of updating the subspace predictors is given. Furthermore, the decision coefficient is introduced to filter the bad data and the problem of data inaccuracy is well solved in the proposed method. The effectiveness of the proposed control method is verified by the simulation test of 2-CSTR process control system.

Title of the Paper: DFIG Stator Reactive and Active Power Control Based Fuzzy Logic


Authors: W. Ayrir, M. Ourahou, A. Haddi

Pages: 262-267

Abstract: The stator reactive and active power control of a variable speed doubly fed induction generator (DFIG) based wind generation system is proposed in this paper. The proposed control aims to generate a suitable referential rotor voltage to control the rotor side converter. The generator mechanical speed is controlled using the MPPT based TSR technique, then the fuzzy logic control is used to control the rotor direct and quadratic currents so that they match their references gotten from the reactive and active power references respectively. The referential active power is gotten from the MPPT control, while the referential reactive power is set to 0 Vars in order to obtain a unit power factor at the stator terminals. The proposed control technique was simulated in MATLAB/SIMULINK. The results show the effectiveness of the fuzzy control strategy.

Title of the Paper: Beamforming Based on Suppression Transforming Error for Array Interpolation


Authors: Shexiang Ma, Fei Pan, Xin Meng

Pages: 256-261

Abstract: Aiming at the inherently problems that interpolated transformation technique can not work effectively over a large transformation area, and when the burst interference occurs to the out of transformation area, it can not be suppressed. In this paper, we propose an improved algorithm by designing the weights of interpolated array to reduce the influence of transformation errors. The key feature of this algorithm is that minimizes the error of output signal power which is caused by transforming errors and guarantees the weight is orthogonal to the transforming errors of the desired signal direction. Numerical simulations confirm the validity of the proposed algorithm. In comparing with the existing algorithms, the proposed interpolated array beamforming algorithm can suppress interference signal accurately, prevent the main lobe from shifting effectively and make the null deeper in the large transformation area. Besides, it also increases the output signal to interference plus noise ratio (SINR), and has lower complexity.

Title of the Paper: Comparative Analysis of Conventional and Multi-Rotor Wind Turbines


Authors: N. S. Sandhu, S. Chanana

Pages: 246-255

Abstract: Due to continuous increase of power demand and on the other hand shortage of fossil fuels have diverted the focus of scientists towards alternate energy resources. Out of these, wind energy is emerging as a potential renewable energy resource and at present acquired the substantial share. Conventional wind turbines are used to extract the energy associated with moving wind. However the rotor size of such turbines increases with their rating. Increased rotor size results in to many problems such as its weight, complicated design, increased noise pollution & cost etc. Large rotor size and turbine cost have diverted the attention of scientists from single-rotor to multi-rotor wind turbines. Aim of this paper is to find out the most suitable power curve model for the analysis of multi-rotor wind turbines. New models have been developed for the energy estimation of a three rotor wind turbine. Simulation results as presented in the paper are helpful to decide the best suitable power curve model for single-rotor as well as for multi-rotor wind turbine. Further as observed, three-rotor wind turbine yields more energy in contrast to single rotor configuration. This increase is 6.34% with mean wind speed of 8m/s & 4.76% with mean wind speed of 12m/s. Analysis, as reported, shows that an equivalent three rotor configuration results into higher annual energy yield with low installation cost.

Title of the Paper: Landing Position Prediction Model for Hydraulic Monitors Based on the Genetic BP Neural Network


Authors: Ning Li, Wenrui Hao, Jiangming Kan

Pages: 240-245

Abstract: Automatic-orientating fire extinguishing is significant to the development of fire-fighting equipment, and the key issue is to accurately predict the landing position of the water jet. The landing positions of water jet are affected by multiple factors. A hydraulic jet experimental system was established to measure the landing positions under different conditions by changing the height of the hydraulic monitor, pitch angle, horizontal angle and hydraulic pressure. Meanwhile, data about the effect factors are collected, including the real-time flow, wind speed, wind direction and temperature. The BP neural network is widely used in prediction, which is good at addressing the non-linear data relationship. However, it has drawbacks such as the low convergence speed and the flaw of entering a local optimum. The genetic algorithm has a strong global searching ability, which is commonly used to optimize the weights and thresholds of BP neural networks. Therefore, the prediction model is proposed based on BP neural network, which was optimized by genetic algorithm. The simulation results demonstrate that the prediction model of GA-BP neural networks improve the prediction accuracy. The correlation coefficient between the output of GA-BP network and the target value was 0.97. Consequently, the prediction model well reflects the nonlinear relationship between the input factors and the landing position and is an effective method to predict the landing position of the water jets of hydraulic monitors.

Title of the Paper: Forecasting Temperature Profile Based on Blending of Measurement Data and Numerical Prediction Models


Authors: Nikolay A. Baranov, Ekaterina V. Lemishchenko

Pages: 235-239

Abstract: The work is devoted to the presentation of the approach to the construction of a short-term forecast of the dynamics of the atmospheric surface temperature profile. The forecast is based on the correction of the results of a numerical global forecast issued from temperature profile measurement data with the use of remote temperature sensing means. The data from the microwave temperature profiler MTP-5 applied for Pulkovo Airport (ICAO ULLI code) was used as the source of the measurement data. The relevance of this study is determined by the high requirements to the accuracy of the short-term forecast of weather hazards, for example, for the terminal area control. This approach provides the possibility of correcting the short-term forecast of weather hazards carried out by the data from real-time observations and does not require significant computational resources.

Title of the Paper: Mathematical Methods to Locate Touch Points Using Laser Optic Modules


Authors: Sang-Young Cho

Pages: 229-234

Abstract: An interactive whiteboards are used in a variety of settings, including in classrooms, in corporate board rooms, in training rooms, in broadcasting studios, and others. Interactive whiteboard implementation is heavily dependent on touchscreen technologies. Existing technologies are suffering from high manufacturing cost, low resolution, screen size scalability when the display screen size is over 100 inches. In this paper, we introduce a new interactive whiteboard system that uses laser modules. The operational principal of the system is similar to that of the camera-based optic system. However, our system positions touches more accurately by using laser emitter and detector, and its operation is simpler due to the absence of image processing. We derived several expressions based on trigonometry calculation to operate the whiteboard including locating laser sensors, screen positioning, calibration, distortion detection, and point locating. With the simplest form of expressions, the operating hardware has little burden to consume software time.

Title of the Paper: Combined Continuous Nonlinear Mathematical and Computer Models of the Information Warfare


Authors: Nugzar Kereselidze

Pages: 220-228

Abstract: In this paper, the first attempt is made to combine existing approaches of mathematical and computer modeling of information warfare. As a result, integration mathematical and computer models of information warfare were created. Until now, in the mathematical modeling of the information warfare, issues of information flows and information dissemination were considered separately. The first direction was initiated by the idea of Professor T. Chilachava, to study the distribution of information flows of the two opposite and third peacekeeping sides by mathematical models. The second direction was laid by Academician A.A. Samarskiy and Professor A.P. Mikhailov, who proposed a mathematical model for the dissemination of information among the population. Both these directions have been intensively developed and many scientific studies have been devoted to them. Several dozens of interesting models were created, which reflect the various nuances of the problem. But it is natural that the information and the information for which it is intended should be studied together. During the implementation of this idea, integrated mathematical and computer models of information warfare were created. Integrated common linear and nonlinear mathematical and computer models of information warfare were created. In this paper, integrated general and particular mathematical and computer models for ignoring the enemy are presented. With the help of computer research, a numerical experiment, the question of the existence of a solution to the problem of the Chilker range is studied, which is equivalent to the task of completing information warfare.

Title of the Paper: A Two-Stage Fraud Detection Method


Authors: Yuanyuan Zhou, Wei Liu, Zhigang Hu, Feng He

Pages: 215-219

Abstract: With the economic development, more and more people participate in medical insurance and enjoy the benefits of medical insurance. However, medical insurance fraud has brought tremendous losses to the medical insurance fund. This paper presents a two-stage outlier detection method for medical insurance fraud detection. In the first stage, weighted k-means algorithm is used to cluster the data set and prune the result set, where the weight w is calculated by using the particle swarm optimization algorithm to minimize the evaluation function of the weight index. The second stage adopts the improved outlier detection method to process the result set. Experiments show that the accuracy of this method is higher than that of using K-means algorithm or LOF algorithm alone. Moreover, it can avoid the influence of subjective factors on the detection results.

Title of the Paper: An Initiation of Forest Fires as a Result of Gas Pipeline Accidents


Authors: Valeriy A. Perminov, Elina Soprunenko

Pages: 210-214

Abstract: Accidents occurring at the sites of pipelines are accompanied by environmental damage, economic loss, and sometimes loss of life. In some cases, the pipelines transporting fuel are ruptured as a result of accidents. The resulting gas cloud expands over nearby forests or homes and ignited, creating a large fireball. As a result of this processes heat radiation is emitted, it heats and ignites the forest combustible materials in the forest. The paper gives a new mathematical setting and method of numerical solution of a problem of a forest fire initiation as a result of accident. The boundary-value problem is solved numerically using the finite volume method and method of splitting according to physical processes. The dependence of the sizes of forest fire zones for different amounts of leaked flammable substances and moisture content, bulk and type of vegetation were studied. In this paper, we calculated the sizes of the possible ignition zones in emergency situations on pipelines located close to the forest, accompanied by the appearance of fireballs. The paper suggested in the context of the general mathematical model of forest fires is given a new mathematical setting, method and results of numerical solution.

Title of the Paper: Scattered Pilot Detection of CMMB Signals based on Data Smoothing in Cognitive Radio Networks


Authors: Huiheng Liu, Zhengqiang Wang, Weijin Jiang

Pages: 204-209

Abstract: This paper investigates the cyclostationarity of China multimedia mobile broadcasting (CMMB) signals. A scattered pilot detection algorithm with lower complexity of CMMB signals based on data smoothing for cognitive radio networks is proposed. First, the received data in secondary user is smoothed by the first order lag filter. Then the cyclic autocorrelation functions (CAFs) of the odd and even orthogonal frequency division multiplexing (OFDM) symbols in CMMB signals, as the decision statistics are calculated. According to the signature of CMMB signals, appearing some peaks of scattered pilots for the cycle frequency around the delay lags , as dominant peaks of CAF is used to detect the CMMB primary user. We derive and simplify expressions of these two decision statistics, and we use the OR rule to decide whether the CMMB primary user is present or not. Simulation results show that by using longer sensing time, the detection performance of the proposed algorithm is significantly improved.

Title of the Paper: Model and Analysis of Target Detection Probability under Strong Background Light


Authors: Xiaoli Wang

Pages: 200-203

Abstract: In order to improve the target detection performance of the photoelectric imaging system under strong background light, it is necessary to establish the probabilistic assessment model of the photoelectric imaging system. According to the target surface luminous flux function, obtains the target radiation illumination, in accordance with the formula of Purcell, calculates the brightness of the background radiation, according to the relationship among the signal to noise ratio of the detector, the false alarm probability and the detection probability, deduces the target detection calculation model of the photoelectric imaging system under strong background light. Through the calculation and analysis, gives the functional relationship of the target’s radiation illumination and working distance at different angles of incidence, gets the curves of signal to noise ratio and the time of signal stranded detector in a certain false alarm probability, verifies the computational model of the target detection probability of the photoelectric imaging system under strong background illumination.

Title of the Paper: Analytical Performance Evaluation of Relay Assisted OFDMA Cellular Systems with Various Frequency Reuse Schemes Under Different Propagation Impacts


Authors: Osama H. Elgazzar, Imbaby I. Mahmoud, Sherief Hashima, H. A. Konber

Pages: 190-199

Abstract: This paper addresses the Co-Channel Interference (CCI) mitigation in Relay-Assisted (R-A) cellular systems to improve Cell Edge User’s (CEU's) performance. Analytical treatments are conducted. The network performance improvement through reducing CCI effects are evaluated using two proposed interference mitigation models. These models denote the R-A sectored Fractional Frequency Reuse (FFR) and R-A Soft Frequency Reuse (SFR). Each model contains two different scenarios for further network performance improvement. The first scenario considers three Relay Stations (RSs) per cell while the other one proposes six RSs in each cell. The best RS placement is proposed. Moreover, closed form expressions for worst cases CEU's SIR, Cell Centre User's (CCU's) SIR and inner radius are implemented. These expressions are used to compare between the considered models using different performance evaluation metrics. The work outcomes enable the system designer to characterize and optimize the multi-cell network performance without a need to execute complex calculations. Also the obtained results contributes to achieve much higher network performance improvement with a lower cost.

Title of the Paper: Coupling Dynamics Analysis of the Flying Cable Driven Parallel Robot


Authors: Qin Wang, Hua Chen, Yu Su, Lu Qiao

Pages: 181-189

Abstract: Flying cable driven parallel robots consist of two subsystems, i.e. four-rotor unmanned aerial vehicle (QUV) and cable driven parallel robot (CDPR), which cooperate each other to complete various operations. Due to the cable flexibility, wind disturbance and base motion of QUV, the dynamics coupling exists between the two subsystems, leading to the imprecise dynamics modeling and cable tension determination. To describe the dynamics coupling, base motions of QUV can be viewed as the external disturbance and the motion of the cable can be decomposed of two categories: steady winding motion and vibration with small amplitude. Based on the space discretization of the cable, cable tension increment caused by vibration with small amplitude can be applied to describe the dynamics coupling. Thus, the cable tension can be determined precisely. Simulation results show that the cable vibration with small amplitude and base motion of QUV can affect the cable tension determination apparently, which should be take into account fully, thus providing the theoretical foundation for controlling the CDPR more accurately.

Title of the Paper: Image Blind Deblurring Based on Laplacian Gradients


Authors: Yue Han, Jiangming Kan

Pages: 173-180

Abstract: Image blind deblurring is an ill-posed inverse problem, in which the blurring kernel is unknown. In this paper, we propose a new image blind deblurring method. We introduce Laplacian operator to extract the gradients of the image instead of first- and second-order gradients, which simply the solving process. In the estimation framework, blurring kernel and image are alternately obtained. Compared with the state-of-the-art image deblurring methods, the image deblurred by the proposed method is more clearly and have higher fidelity, and the ringing artifacts are reduced effectively. From the image deblurring results, the kernel similarity of estimated blurring kernel is higher, the indices of image deblurring result are dominant as well.

Title of the Paper: HADOOP Based Image Compression and Amassed Approach for Lossless Images


Authors: Ruhiat Sultana, Nisar Ahmed, Syed Abdul Sattar

Pages: 163-172

Abstract: This paper develops Hadoop based image compression approach, to solve the problem of low image quality, low compression ratio and high time that occurs during lossless image compression. Lossless image is considered in this paper because in case of lossy compression it leads to information loss which cannot retrieve anymore. By the employment of Hadoop based technique this paper proposes a novel image compression for lossless images. This method makes use of Weiner filter for the cancellation of noise and image blurring. Followed by this, hybrid concepts are employed to perform segmentation and feature extraction. Finally, compression is done with the help of Hadoop map reduce concept. Our proposed technique is implemented in MATLAB and therefore the experimental results proved the effectiveness of proposed image compression technique in terms of high compression ratio and low noise ratio when compared with existing techniques.

Title of the Paper: Simulation Analysis of Dough Wrapper Rolling Device for Large-scale Production of Alkaline Noodle


Authors: Qiang Yin, Feiyu Zhao, Guoquan Zhang

Pages: 158-162

Abstract: At present, the process of large-scale production of alkaline noodles is very complex, and more often depends on manual production, which greatly reduces the production efficiency and scale. Therefore, the development of automation equipment surface is necessary. As the key Components of the large-scale production of alkaline noodles, the paper has designed the dough wrapper rolling device in detail. The structure and principle of the dough packing rolling device are introduced. On the basis of determining the main technical parameters, the face press is emphatically studied. The model analysis theory is used to model the coiling device, and then the modal analysis is carried out by the ANSYS analysis software. According to the simulation results, there is no resonance phenomenon in the normal operation of the roller, which indicates that the design is reasonable and reliable.

Title of the Paper: Fuzzy Detection of Digital Forgery Using Mathematical Morphology


Authors: Yonghui He, Huifen Huang

Pages: 154-157

Abstract: According to the fuzzy operation commonly used in image tampering detection scheme, a new fuzzy edge preservation studies using smoothing filter and mathematical morphology method, make full use of these two kinds of methods to determine and indicate possible tampering and positioning of tampering without the need for embeded information such as watermark. The scheme not only can judge whether an image is blurred, it can also detect the image blur. Digital tampering may affect image characteristics from multiple levels. Experimental results confirm the effectiveness of the scheme, the edge reservation is used to process the image using the smoothing filter method, and then the artificial fuzzy edge is detected by mathematical morphology, which can accurately identify the digital forensics, and accurately locate the tampering region.

Title of the Paper: A Numerical Algorithm and Visualization Software for Flood Simulation in Urban Area: A Case Study of West Jakarta, Indonesia


Authors: Saeful Bahtiar, Somporn Chuai-Aree, Anurak Busaman

Pages: 147-153

Abstract: Flood is an overflow of a large amount of water beyond its normal limits, especially in the area of normally dry land which can cause many losses. To minimize those effects and to predict flood occurrence, simulation and mathematical models are required. The purpose of this paper is to develop a numerical algorithm for flood simulation and visualization in West Jakarta, Indonesia. The numerical algorithm was constructed based on shallow water equations (SWEs) that were solved by using finite volume method (FVM) and first order well-balanced scheme equipped with the dynamic domain defining method. The numerical algorithm was validated in the scenario of Kleefsman’s dam breaking test case. The result of validation shows that experiments have good agreement with the simulation data. The numerical algorithm and investigated software were applied to terrain data of West Jakarta, Indonesia. The simulated results were compared for two cases by involving with buildings and without buildings. The comparison shows that the algorithm with buildings can reduce the number of computational grid cells since the buildings grid cells were ignored. This algorithm and the software can be applied for other regions.

Title of the Paper: An Improved SIFT Image Tamper Forensics Method


Authors: Huifen Huang, Yonghui He, Qingmin Liu

Pages: 143-146

Abstract: In view of copy and paste, the most frequent operation in digital image tampering, an improved SIFT algorithm for forensics of image tampering was put forward. The algorithm sees to copy and paste forensics based on the SIFT circular descriptor operator, extracts the circular descriptor eigenvectors of the detected images, and conducts detection and location for the image copy and paste area by using eigenvector match-up. Experiments show that this method is robust to image processing operations, such as image rotation, zoom, blurring, noising and so on. It can detect the trace of copy and paste operation in digital image tampering quickly and effectively. Furthermore, it can accurately locate the area where copy and paste occurred.

Title of the Paper: A Quadratic Optimization Model for Dynamic Intensity Modulated Radiotherapy and Volumetric Modulated Arc Therapy with Tongue and Groove Constraints


Authors: Yihua Lan, Jinjiang Liu, Yang Wang, Xiao Song, Chih-Cheng Hung

Pages: 135-142

Abstract: The paper provides an improved model for quadratic programming for dynamic intensity modulated radiotherapy (dIMRT) and volumetric modulated arc therapy (VMAT) schemes. This improved model suppresses the total beam-on-time as well as tongue and groove chamfer effects. First, we model the goal of clinical dose with the traditional quadratic programming technique. Then, we describe leaf-moving trajectory matrices and obtain the relationship between trajectory matrices and the fluence map matrix. We establish convex constraints for the leaf collision and tongue and groove chamfer effects based on the relationship. Furthermore, by analyzing the relationship between the leaf movement speed and leaf moving trajectory matrix as well as the relationship between the beam-on time and leaf moving trajectory matrix, we establish the convex constraint of the leaf moving maximum speed and the convex constraint of the total number of monitor units (the beam-on time). Finally, considering the limitation for the unidirectional leaf-moving pattern, we form the bidirectional leaf-moving pattern and embed it into the model. This paper proposes a theoretical model which can meet the majority of the clinical demand. It is also easy for the implementation of hardware and software aspects of constraints by multi-leaf collimator.

Title of the Paper: Software for Modeling Estimated Respiratory Waveform


Authors: Aleksei E. Zhdanov, Leonid G. Dorosinsky

Pages: 129-134

Abstract: In the imaging of chest or abdomen, motion artifact is an unavoidable problem. In the radiation treatment, organ movement caused by respiratory motion is a problem unavoidable also to realizing safe and effective cancer treatment preserving healthy tissue. In this article, we compare two modalities 3D CT and 4D CT and present the main difference between them, which is compensating the breathing motion. However, we record a real breathing signal using ANZAI belt, analyze the resulting signal and simulate the estimated respiratory waveform based on three different models.

Title of the Paper: Peak Field Approximation of Shock Wave Overpressure Based on Sparse Data


Authors: Yongli Zhang, Tailin Han, Yuqun Chen, Enkui Zhang, Xuan Liu

Pages: 123-128

Abstract: To obtain the shock wave field distribution, two kinds of caliber weapons shock wave overpressure by the electric measuring method are analyzed, and the attenuation formula in far field is corrected, and the approximation method of overpressure peak field with cubic spline interpolation is put forward. The sparse array data of small caliber muzzle shock wave field measured by sensor array is first analyzed and the curve fitting was carried out by using the correction formula in the radial direction; secondly, cubic spline interpolation was used in the circumferential direction; and lastly, Delaunay triangulation method was used to divide the mesh to approximate the overpressure peak surface. Compared with the cubic spline interpolation results obtained by this method, the approximate isobars showed obvious advantages. Further, the large-diameter muzzle shock wave using polar coordinate sensors were tested, and the approximate method of sparse matrix overpressure data processing field effect is good. The approximate method provides reference for the drawing of the shock wave field by polar coordinate.

Title of the Paper: Behavior Prediction of Mobile User Based on Context Similarity


Authors: Chengfang Tan, Qixiang Song, Xiaoyin Wu

Pages: 118-122

Abstract: Contextual information of users in mobile environment is diverse. Contextual factors have different importance to users in choosing resources. This paper presents a context-based mobile user behavior analysis model. Firstly, by using the context information entropy to calculate the importance of different context attributes, context similarity can be calculated. Then, combining with the traditional collaborative filtering recommendation algorithm, the target user's nearest neighbor set is obtained based on user similarity. Finally, the behavior preference of the target user can be predicted, and a target user's recommended list of projects also generate under the current context environment. Experimental study is carried out and the results show that the proposed prediction method have a better performance in a specific context.

Title of the Paper: Adaptive Sliding Mode Controller with Single Parameter Approximation for Four-wheel Omnidirectional Mobile Robots


Authors: Jianbin Wang, Jianping Chen, Sijie Ouyang

Pages: 112-117

Abstract: Due to the parametric uncertainties and the disturbances in dynamic model, the traditional control methods are not suit for the motion control of four-wheel omnidirectional mobile robot. An adaptive sliding mode controller is presented, the RBF neural network is applied to estimate the function of the parameter uncertainty and the disturbance. To suit the real-time control demand, single parameter estimation is used instead of the weights of RBF neural network, and then a Lyapunov function is exploited to prove the stability of the improved closed-loop system. The numerical simulations results show that the controlled system has better robust stability and ability of restraining disturbance.

Title of the Paper: 1-Point RANSAC Application: an Independent Positioning Method for Crawler Mobile Robots Based on Binocular Stereo Vision


Authors: Xixuan Zhao, Jiangming Kan, Chuandong Zhan

Pages: 105-111

Abstract: Independent positioning is a basic problem for realizing the autonomous navigation of a mobile robot in an unknown environment. In this paper, an independent positioning method based on binocular stereo vision is examined. This method includes two steps: extracting and matching point features based on binocular stereo vision and estimating the motion model of the crawler mobile robot. In the first step, point features are detected using a FAST algorithm and matched according to the Hamming distance. In the second step, the motion model of the crawler mobile robot is estimated by points that are matched using the visual odometry method which is based on 1-Point RANSAC (random sample consensus) framework and Kalman filter. The results of indoor and outdoor practical experiments illustrated that the proposed method can achieve the goal of real-time independent positioning and obtain accurate and robust results.

Title of the Paper: A Convex Cauchy-Schwarz Divergence Measure for Blind Source Separation


Authors: Zaid Albataineh, Fathi M. Salem

Pages: 94-104

Abstract: We propose a new class of divergence measures for Independent Component Analysis (ICA) for the de-mixing of multiple source mixtures. We call it the Convex Cauchy-Schwarz Divergence (CCS-DIV), and it is formed by integrating convex functions into the Cauchy-Schwarz inequality. The new measure is symmetric and the degree of its curvature with respect to the joint-distribution can be tuned by a (convexity) parameter. The CCS-DIV is able to speed-up the search process in the parameter space and produces improved de-mixing performance. An algorithm, generated from the proposed divergence, is developed which is employing the non-paramteric Parzen window-based distribution. Simulation evidence is presented to verify and quantify its superior performance in comparison to state-of-the-art approaches.

Title of the Paper: Differential Ant-Stigmergy Algorithm Based Parameters Estimation of Sum of Exponentials Model


Authors: Jianfeng Liu, Jiawen Bian, Hongwei Li

Pages: 85-93

Abstract: Exponentials sum model is an important model in time series analysis and has applications in modeling various physical phenomena of real life. The estimation of the parameters of the model is a necessary and fundamental task for the application of the model. In this paper, we propose a differential ant-stigmergy algorithm (DASA) based iterative procedure to estimate the parameters of the considered model where two different criterions which are least squares and least absolute errors are considered. The estimators of the parameters for the considered model by the two criterions are compared with the existing estimators by genetic algorithm based least squares (GA-LS). Simulation experiments and real data fitting are presented to inspect the performance of the proposed algorithm. It can be observed that better results can be obtained by DASA based LS (DASA-LS) than by GA-LS in terms of mean squares errors (MSEs) and robustness. Although a higher dimensional optimization is needed for DASA based least absolute errors (DASA-LAE) than that for the other two methods, DASA-LAE providers better results than DASA-LS in outliers condition. Finally, simulation results also show that DASA has better global searching ability than that for GA.

Title of the Paper: New Design Methodology for Adaptive 2-D (Two-Dimensional) IIR Notch filters


Authors: Nikos E. Mastorakis, Dimitris Tseles, Lazaros Vryzides

Pages: 80-84

Abstract: A new method for the design of 2-D (Two-Dimensional) notch filters is proposed. We discuss the advantages of our methods in comparison with previously published methods in the 2-D (Two-Dimensional) Systems literature. An appropriate transformation is considered. Numerical examples illustrate the validity and the efficiency of the method.

Title of the Paper: A Compact and High Isolation Dual Polarization Antenna for Micro-base Station


Authors: Bo Yin, Xingxing Feng, Shenwei Mao, Lijun Sun

Pages: 74-79

Abstract: A compact, low-profile and high isolation dual-polarized patch antenna with good radiation pattern is proposed for micro-base station (operating in 2.5-2.7GHz). This antenna consists of two horizontal substrates and two vertical substrates, both placed orthographically. Low-profile is achieved by employing electromagnetic feed and Γ shape feed line. Hybrid feed structure is used to obtain the high port isolation. The differential feed network in port 2 enhances the port isolation and suppresses the cross polarization level. A metal wall is loaded to improve the radiation pattern. For demonstration, the proposed antenna is fabricated and measured. The operation frequency of port 1 and port 2 which can be observed in the measured results are both around 2.6GHz. The desired isolation and radiation characteristics are achieved.

Title of the Paper: Comparing Threshold Based Denoising Methods in Wavelet Transform Domain


Authors: A. Mohammad Zaki, S. Ghofrani

Pages: 65-73

Abstract: In this paper, the principal concept of image denoising in wavelet domain is discussed. For this purpose, three thresholding approaches known as VisuShrink, SureShrink and NeighBlock are employed, three noise power estimators named Median absolute deviation, Quantile median and Marginal variance are used and four thresholding rules called hard, soft, Exp. and Garrot are applied. All methods take effort for denoising in transform domain. As a matter of fact, sparsity of coefficients, in addition to the noise power estimator efficiency, are the key roles for every thresholding method. So, we focus on the capability for noise power estimation to discover the most optimal method for image denoising in wavelet domain. Being consistent in estimating the noise power in every wavelet decomposition level, it was believed that Median absolute deviation was the best method. To challenge this idea, outcome of mentioned method and other noise power estimators is to be compared. Finally, some packages will be proposed that each of them introduce methods and algorithms that act together optimally. The performance evaluation is via two points of view, Speckle noise reduction and image quality preservation. The most optimal package which outperforms others is using Garrot thresholding rule and Median absolute deviation in VisuSrink denoising method.

Title of the Paper: On Quadrature Formulas for Oscillatory Evolutionary Problems


Authors: Angelamaria Cardone, Dajana Conte, Raffaele D’Ambrosio, Beatrice Paternoster

Pages: 58-64

Abstract: Gaussian-type quadrature rules for oscillatory integrand functions are presented. The weights and nodes depend on the frequency of the problem and they are constructed by following the exponential fitting theory. The error analysis proves that the exponentially fitted Gaussian rules are more accurate than the classical Gaussian rules when oscillatory functions are treated. The numerical approximation to Volterra integral equations with oscillatory solution through these formulas is presented. Some numerical tests are reported.

Title of the Paper: Application Support for Topographical-Geodetic Issues for Tactical and Technical Control of Artillery Fire


Authors: Martin Blaha, Karel Šilinger

Pages: 48-57

Abstract: This paper is focused on suggestions and recommendations for suitable guidelines for fulfilling of The sketch of topographical-geodetic connection and aiming guns through line rod in the prepared firing positions. This method belongs to the fast and accurate Aiming works into the main firing direction, and consequently the target. This paper contains table of contents and method of “The sketch of topographical-geodetic connection” fulfilling. Moreover, this article aims to clarify the issue Aiming guns through line rod and show new possibilities for their placement. Stakes are still standard placed before or after the cannon in the main direction of fire. In case it is not possible in this way to place stakes can be positioned also in another direction as described in the article. With the change in tactics deployment works in firing positions, the guns are no longer on the linear line and therefore can deploy stakes in direction and eventually left to right cannon. The paper gives the instructions for the respective commanders also use those spaces that are not typically used to Aiming guns into the line of fire through line rod. Paper explains the general principle of targeting guns by line rod, particularly for 152 mm ShKH vz.77. The paper presents problems of current Artillery communication and information system and suggests requirements of the future system.

Title of the Paper: Effect of the FWM Influence on the CWDM Signal Transmission in the Optical Transmission Media


Authors: Rastislav Róka, Martin Mokráň

Pages: 42-47

Abstract: This paper deals with analysis of negative influences on the optical signal transmitted in the environment of optical transmission media and is focused especially on the Four Wave Mixing (FWM) effect. The FWM is one of nonlinear effects in the optical transmission media with the strongest impact on transmitted signals utilizing a wavelength division multiplexing. Consequently, a simulation model for the appropriate CWDM optical transmission path is introduced with short descriptions of functional blocks representing technologies utilized in this specific environment. The created Simulink modeling scheme of real environmental conditions at the signal transmission using the Coarse Wavelength Division Multiplexing (CWDM) allows executing different requested analyses for advanced optical signal processing techniques. Finally, some results from the CWDM simulation are introduced for the signal transmission influenced by different negative effects in the optical transmission medium. Using the presented simulation model, it is possible analyzing transmitted optical signals with eye diagrams and determined the impact of negative influences on the optical frequency spectrum.

Title of the Paper: A Performance Evaluation of Color Constancy Methods Based on Illumination Estimation


Authors: Chunxiao Li, Jiangming Kan

Pages: 35-41

Abstract: There are many color constancy methods based on illumination estimation and their error metrics, but it is unclear how they perform or which method is more appropriate in a particular scene. We chose Reproduction Angular Error (RAE) as the error measure to compare the performance of twenty-two illumination estimation methods in four different scenes (Open Country, City, Indoor, Lab), and present the best method choice to be used with each scene type.

Title of the Paper: Coupled Method for Solving Time-Fractional Navier-Stokes Equation


Authors: S. O. Edeki, G. O. Akinlabi

Pages: 27-34

Abstract: This paper witnesses the coupling of two basic transforms: the He-Laplace transform (HLT) which is a blend of Laplace transformation and Homotopy perturbation methods and the fractional complex transform (FCT). This coupling technique is applied for the solutions of the time-fractional Navier-Stokes model equation. Two examples are considered in demonstrating the effectiveness of the coupled technique. The exact solutions of the solved problems are obtained with less computational work, while still maintaining high level of accuracy with little knowledge of fractional calculus being required. Thus, the proposed method is recommended for handling linear and nonlinear fractional models arising in pure and applied sciences.

Title of the Paper: Simulation Research of Extra-Vehicular Activity Based on Virtual Reality Technology


Authors: Weilin Li, Jian Wen, Zeyu Hu, Wenkai Ma

Pages: 21-26

Abstract: In order to solve the problem that six degree of freedom movement and automatic attitude holding of the simplified aid for extravehicular activity rescue (SAFER) on the ground simulation of astronaut's operation cannot be achieved accurately due to the influence of gravity, friction and other conditions. The dynamic simulation model of the device is established by using virtual reality technology. And in the MATLAB/Simulink environment to establish a hybrid control system model, its core concept is based on the Bang-bang control. Under different conditions, the SAFER attitude control process is simulated, and then the scene simulation animation and control process curves are obtained. The simulation results verify the accuracy of the mathematical model and control strategy. Application of virtual prototyping technology model simulation method can describe the device control process accurately and make the design process more efficient. And provide certain theoretical basis and guiding significance to the practical application of SAFER.

Title of the Paper: Effect of Multirate and Suppression Filter in the Performance of Wavelet Packet Multicarrier Multicode CDMA System


Authors: Maryam M. Akho-Zahieh

Pages: 12-20

Abstract: Many ways can be considered to improve the performance of Multicarrier Multicode Code-Division Multiple Access (MC\MCD-CDMA) systems. Some of them are to use: Multirates services, suppression filters, wavelet packets, diversity and others. Multirates (MR) services can be provided in MC\MCDCDMA system by varying the number of multicodes for each user according to his data rate but the processing gain of all users must be fixed. Suppression filter (SF) can improve the performance for the system by rejecting the narrow-band jammer interference. Since wavelet packets (WPs) have lower sidelobes compared with sinusoidal carriers, then systems which use WPs as subcarriers are very effective in reducing the problem of intercarrier interference Also, to reduce multiple access interference diversity techniques can be used. In this paper, the effects of MR , WPs and SF on the performance of MC\MCD-CDMA system that uses WPs as subcarrier were investigated. The system is denoted as WP-MC\MCD-CDMA system, and the study includes the effects of number of the rates, SF and its number of taps, WP family type and filter length.

Title of the Paper: Computation of the Electric Fields of System of the Artificial Thunderstorm Cells


Authors: Alexander G. Temnikov, Leonid L. Chernensky, Alexander A. Orlov, Tatiana K. Kivshar, Nikolay Y. Lysov, Olga S. Belova, Daria S. Zhuravkova

Pages: 7-11

Abstract: Method of the computation of the electric fields of a system of the artificial thunderstorm cells is considered in paper. It is based on the theoretical and experimentally measured parameters of a turbulent charged aerosol flows. Approaches for calculation of the electric field characteristics of the separate charged aerosol flow have been analyzed for the case of an aerosol chamber. Application of this method for computation of the electric fields of two unipolar or differently charged artificial thunderstorm cells has been considered in paper. It is shown that the maximal electric field strength will achieve in the gap between the positively and negatively charged artificial thunderstorm cells, and above upper and beneath bottom unipolar artificial thunderstorm cells. It was experimentally shown that the model hydrometeor arrays posed in these places could initiate intensive discharge phenomena (powerful streamer and leader discharges) between the charged clouds and between the artificial thunderstorm cells and the ground.

Title of the Paper: The Solution of Boundary Value Problems with Mixed Boundary Conditions via Boundary Value Methods


Authors: Grace O. Akinlabi, Raphael B. Adeniyi, Enahoro A. Owoloko

Pages: 1-6

Abstract: Boundary Value Methods (BVMs) are methods based on Linear Multistep Methods (LMMs), which are used for the numerical approximation of Differential Equations (DEs). These methods were introduced to overcome the weaknesses of the LMMs. In this paper, we introduce a new class of BVMs – Hybrid Boundary Value Methods (HBVMs) and used them to solve first order systems BVPs with mixed boundary conditions by using the specific cases: 2, 4 and 6. These methods are also based on LMMs where data are used at both step and off-step points. The maximum errors and rate of convergence (ROC) of the solutions are reported for these cases to illustrate the effectiveness of these new class of methods.