International Journal of Computers
E-ISSN: 1998-4308
Volume 14, 2020
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 14, 2020
Title of the Paper: PID Controller Gains Tuning Using Metaheuristic Optimization Methods: A survey
Authors: Abdallah Abushawish, Mohammed Hamadeh, Ali Bou Nassif
Pages: 87-95
http://doi.org/10.46300/9108.2020.14.14
Abstract: In nowadays industry, most processes are controlled and automated. Interestingly, PID controllers are major contributors to the control process since they were invented and become quite practical. PID controllers are vital component in the industry and enhancing the component will show an echo effect in today’s technology. Their drawbacks are tuning them for an application, and this provides inspiration to develop advanced optimization methods in tuning PID controllers. This survey aims to review metaheuristic optimization methods of PID controller tuning that were published between 2010 and 2018. The paper was constructed based on 22 research papers and found that 8 metaheuristics optimization methods were used with PID tuning on 5 industrial applications. The papers also extensively provided answers to 3 research questions and assessing the quality of the papers based on 6 parameters.
Title of the Paper: Classifications of Breast Cancer Diagnosis using Machine Learning
Authors: Hajra Naveed Iqbal, Ali Bou Nassif, Ismail Shahin
Pages: 81-86
http://doi.org/10.46300/9108.2020.14.13
Abstract: Breast Cancer (BC) is amongst the most common and leading causes of deaths in women throughout the world. Recently, classification and data analysis tools are being widely used in the medical field for diagnosis, prognosis and decision making to help lower down the risks of people dying or suffering from diseases. Advanced machine learning methods have proven to give hope for patients as this has helped the doctors in early detection of diseases like Breast Cancer that can be fatal, in support with providing accurate outcomes. However, the results highly depend on the techniques used for feature selection and classification which will produce a strong machine learning model. In this paper, a performance comparison is conducted using four classifiers which are Multilayer Perceptron (MLP), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Random Forest on the Wisconsin Breast Cancer dataset to spot the most effective predictors. The main goal is to apply best machine learning classification methods to predict the Breast Cancer as benign or malignant using terms such as accuracy, f-measure, precision and recall. Experimental results show that Random forest is proven to achieve the highest accuracy of 99.26% on this dataset and features, while SVMand KNN show 97.78% and 97.04% accuracy respectively. MLP shows the least accuracy of 94.07%. All the experiments are conducted using RStudio as the data mining tool platform.
Title of the Paper: Approach for a Safe-SoC for Cyber-physical Application according to IEC 61508
Authors: Josef Börcsök, Michael Schwarz, Waldemar Müller, Mohamed Abdelawwad, Eike Hahn
Pages: 77-80
http://doi.org/10.46300/9108.2020.14.12
Abstract: Using electronic systems to control complex applications has found its way into nearly all technical and industrial areas during the last four decades. Today, in addition to system size, reduced system costs, optimized energy consumption and high reliability or safety, the aspects of functional safety are increasingly in the focus of many applications. Especially concerning safe embedded cyber-physical systems, which is favored by increasing integration of components, these aspects are of central importance. This article describes a consistently safety 1oo2 SoC architecture model (a miniaturized safety system on a chip) based on a modified software comparator architecture. The design and realization of the safety SoC, according to IEC 61508, are also presented.
Title of the Paper: Reliability Monitoring of Laser Scanner Based Navigation
Authors: Richard Thum, Josef Borcsok
Pages: 73-76
http://doi.org/10.46300/9108.2020.14.11
Abstract: Autonomous guided vehicles have great advantages over rigidly track-guided conveyor technology, as they can react flexibly to changes in the application area. Temporary obstacles can be easily avoided. The vehicles can circumnavigate bottlenecks and areas at risk of congestion switch to alternative routes. To avoid accidents, safety-relevant position detection is necessary in many areas. The current speed is derived from this driven trajectory and this is safely reduced in the working areas. Minimum distances can also be safely maintained. Therefore it is necessary to permanently control the measured position with regard to disturbance variables and to monitor the reliability of the position detection in real time.
Title of the Paper: Soc-approach for Safety-oriented Multi-channel Communication in Industrial Application of Human-robot-collaboration (HRC)
Authors: Mohamed Abdelawwad, Michael Schwarz, Malte Drabesch, Josef Börcsök, Christian Voss
Pages: 69-72
http://doi.org/10.46300/9108.2020.14.10
Abstract: The importance of human-robot collaboration systems in industrial applications has increased due to the orientation towards the smart factory approach. To ensure the safety of such systems, collision avoidance techniques based on millimeter-wave radar sensors are used. Safe communication between the robot and the radar sensor is ensured by using the safety system on a chip based on 1oo2D architecture. The design and prototyping of a multi-channel communication FPGA-based development board is presented. Furthermore, the FPGA implementation of SoC with multiple Ethernet MAC interfaces based on various soft cores is demonstrated.
Title of the Paper: Enlightening and Predicting the Correlation Around Deep Neural Nets and Cognitive Perceptions
Authors: Chandra Bhim Bhan Singh
Pages: 61-68
http://doi.org/10.46300/9108.2020.14.9
Abstract: Recently, psychologist has experienced drastic development using statistical methods to analyze the interactions of humans. The intention of past decades of psychological studies is to model how individuals learn elements and types. The scientific validation of such studies is often based on straightforward illustrations of artificial stimuli. Recently, in activities such as recognizing items in natural pictures, strong neural networks have reached or exceeded human precision. In this paper, we present Relevance Networks (RNs) as a basic plug-and-play application with Covolutionary Neural Network (CNN) to address issues that are essentially related to reasoning. Thus our proposed network performs visual answering the questions, super-human performance and text based answering. All of these have been accomplished by complex reasoning on diverse physical systems. Thus, by simply increasing convolutions, (Long Short Term Memory) LSTMs, and (Multi-Layer Perceptron) MLPs with RNs, we can remove the computational burden from network components that are unsuitable for handling relational reasoning, reduce the overall complexity of the network, and gain a general ability to reason about the relationships between entities and their properties.
Title of the Paper: Cognitive Inductive Prejudice For Corporal Edifice In Hominids And Contraption
Authors: Chandra Bhim Bhan Singh
Pages: 53-60
http://doi.org/10.46300/9108.2020.14.8
Abstract: A strong and insightful interpretation of scientific knowledge and practice must take into consideration how human cognitive skills and constraints enable as well restrict the scientific enterprise's activities and products. While existing deep learning systems are outstanding in functions such as object classification, language processing, and gameplay but few can create or transform a complex system like a Frame Pyramid. Assume that what these systems lack is a "Cognitive Inductive Prejudice": an ability to justify inter-object relationships and make decisions about an organized description of the incident. In order to assess this premise, this paper concentrated on a work involving stapling together stacks of frames to balance a castle and quantify how well hominids are doing. Then for analyzing contraption capability, our work introduce the Significant Stimulus Learning Tool that utilizes object-and interaction-centered scene and policy representations, these apply to the task. Our results shows that these structural portrayals enable the tool to perform both hominids and contraption for more naive methods, indicating that cognitive inductive effect is a significant element in solving structured reasoning issues and building more intelligent also flexible for machines.
Title of the Paper: A New Core Level Utilization Algorithm for Energy-Efficient Multicore Systems
Authors: Samar Nour, Sameh A.Salem, Shahira M.Habashy
Pages: 45-52
http://doi.org/10.46300/9108.2020.14.7
Abstract: The energy consumption is becoming a constraint on all computer devices, from smartphones to supercomputers. Consequently, the focus has moved from performance to energy and power consumption. Design metrics are not only based solely on performance, as the energy performance of application executions is becoming the main aspect of architecture. Also, Design metrics depend on, the manufacturers of semiconductor chips which, have implemented multicore processors to boost the level of energy efficiency by using verified techniques for voltage and frequency scaling. To utilize the maximum potential of such architectures, we need to make the right decisions because parameters such as core type, frequency, and utilization typically affect power dissipation and performance. This paper proposes a new algorithm to achieve energy-efficient by monitoring core energy and level utilization control such as: Increasing the number of cores to execute the task, scaling voltage, and frequency. Based on the built model, we analyze the energy efficiency variations for different platform configurations providing the same level of performance. We show that trading the number and type of core with frequency and voltage level and core utilization rate can lead to substantial energy efficiency gains.
Title of the Paper: A Soft Target Threat and Risk Methodology Application
Authors: N.Cajkova
Pages: 40-44
http://doi.org/10.46300/9108.2020.14.6
Abstract: This article is focused on a Soft Target Risk application and Threat Analysis Methodology at the Faculty of Applied Informatics in Zlin. The terrorist attacks are one of the biggest security problems in the modern world. Attacks are often against Soft Targets which are places, that are typical of a high concentration of people and in the same time a low level of security. As a Soft Target we can imagine shopping centers, airport terminals, sporting arenas, airport terminals, public meetings, schools, cinemas, religious events, etc. This paper focuses of the security analysis of the Faculty of Applied Informatics (Soft Target) and its preventive safety measures.
Title of the Paper: Smart Homes: Security Challenges and Privacy Concerns
Authors: Fraser Hall, Leandros Maglaras, Theodoros Aivaliotis, Loukas Xagoraris, Ioanna Kantzavelou
Pages: 34-39
http://doi.org/10.46300/9108.2020.14.5
Abstract: Development and growth of Internet of Things (IoT) technology has exponentially increased over the course of the last 10 years since its inception, and as a result has directly influenced the popularity and size of smart homes. In this article we present the main technologies and applications that constitute a smart home, we identify the main security and privacy challenges that smart home face and we provide good practices to mitigate those threats.
Title of the Paper: Optimum Risk Engineering Tools Depend on Technical Facility Complexity
Authors: Dana Prochazkova, Jan Prochazka
Pages: 26-33
http://doi.org/10.46300/9108.2020.14.4
Abstract: The study of accidents and failures of complex technical facilities has shown that in many cases, these phenomena occur when the technical facility integral risk exceeds the certain criticality rate, i.e. also if larger number of small risk sources executes in technical facility in a short period of time and their impacts are specially interconnected. The present risk engineering tools are diverse and have different requirements for data, knowledge, processing time, i.e. finance, and practice is of course interested in the least demanding tools. The article shows optimum risk engineering tools working with risks for achievement of main three targets of technical facility (reliability; security; safety), which depend on the technical facilities´ complexity rate
Title of the Paper: One Approach to Conducting the Hierarchical Structuring of Various Systems
Authors: Teimuraz Tsabadze, Archil Prangishvili
Pages: 17-25
http://doi.org/10.46300/9108.2020.14.3
Abstract: This paper is intended to present a new approach to the hierarchical structuring of various systems.An approach is thoroughly discussed and its theoretical justification is given, in particular, a theorem is proved that gives formalisms for constructing hierarchical structuring.The paper includes a detailed practical exampleof application of the introduced method. Further ways of development of the presented work are also outlined.
Title of the Paper: Block Based Motion Estimation Algorithms: Analysis
Authors: Kiran Kumar Vemula, S. Neeraja
Pages: 9-16
http://doi.org/10.46300/9108.2020.14.2
Title of the Paper: Lossless Compression of Medical Images based on the Differential Probability of Images
Authors: Cheng Yao, Shuchao Chen, Jiawen Fu, Shuai Ren, Lizhi Liu, Hongbo Chen
Pages: 1-8
http://doi.org/10.46300/9108.2020.14.1
Abstract: Lossless compression is crucial in the remote transmission of large-scale medical image and the retainment of complete medical diagnostic information. The lossless compression method of medical image based on differential probability of image is proposed in this study. The medical image with DICOM format was decorrelated by the differential method, and the difference matrix was optimally coded by the Huffman coding method to obtain the optimal compression effect. Experimental results obtained using the new method were compared with those using Lempel–Ziv–Welch, modified run–length encoding, and block–bit allocation methods to verify its effectiveness. For 2-D medical images, the lossless compression effect of the proposed method is the best when the object region is more than 20% of the image. For 3-D medical images, the proposed method has the highest compression ratio among the control methods. The proposed method can be directly used for lossless compression of DICOM images.
