ISSN: 1998-4308


Year 2009

All papers of the journal were peer reviewed by two independent reviewers. Acceptance was granted when both reviewers' recommendations were positive.

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    Paper Title, Authors, Abstract (Issue 1, Volume 3, 2009)


The Role of Avatars with Facial Expressions to Communicate Customer Knowledge
Mutlaq B. Alotaibi, Dimitrios I. Rigas

Abstract: This paper describes a comparative evaluation study conducted to examine the impact of incorporating avatars with facial expressions into Electronic Customer Knowledge Management Systems (E-CKMS) on usability of E-CKMS, and the user’s attitudes and knowledge. Although the implementation of E-CKMS encounters several challenges, such as lack of trust and information overload, few empirical studies were devoted to examine the role of metaphors of audio-visual nature. As a result, an empirical investigation was carried out by implementing avatars-enhanced multimodal E-CKMS (ACKMS), and comparing it with text with graphics E-CKMS (VCKMS), and another multimodal E-CKMS (MCKMS) that utilises speech, earcons and auditory icons. The three experimental systems were evaluated by three independent groups of twenty users each (n=60) performed eight common tasks, increasing in complexity and designed based on three different styles of Customer Knowledge Management (CKM). Results and analysis revealed that ACKMS outperform MCKMS and VCKMS with regard to the user’s attitudes and knowledge.


Implementation of a USN-based Disaster Prevention System in Korea
Dae-Hyun Ryu, Ho-Jun Na, Seung-Hoon Nam

Abstract: The rapid economic rise of Korea has also led to the rapid development of infrastructure. As this infrastructure becomes more complex, it is becoming more and more of a challenge to appropriately monitor. As a result, there have been several occurrences of preventable disasters taking place and, if nothing is done, the frequency of such disasters is likely to increase. With wireless communication, sensor networks, and standards such as Zigbee becoming mainstream, it is now possible to implement disaster prevention systems for many applications. This paper suggests and designs an efficient ubiquitous sensor network-based disaster prevention system that monitors gas lines for leaks. Using our system, it's possible to monitor and control relevant facilities in real-time. This near-immediate reaction time will allow for the evacuation of affected people and rapid emergency response in the event of a leak, thereby saving lives and preventing a disaster from occurring. This system may be a key component of new government policy that holds the safety of citizens in the highest regard.


Eigenface-Gabor Algorithm for Features Extraction in Face Recognition
Gualberto Aguilar-Torres, Karina Toscano-Medina, Gabriel Sanchez-Perez, Mariko Nakano-Miyatake, Hector Perez-Meana

Abstract: This paper provides a study on Face Recognition Algorithms; several methods are used to extract image face features vector, which presents small inter-person variation. This feature vector is feed to a multilayer perceptron to carry out the face recognition or identity verification tasks. Proposed system consists in a combination of Gabor and Eigenfaces to obtain the feature vector. Evaluation results show that proposed system provides robustness against changes in illumination, wardrobe, facial expressions, scale, and position inside the captured image, as well as inclination, noise contamination and filtering. Proposed scheme also provides some tolerance to changes on the age of the person under analysis. Evaluation results using the proposed scheme with identification and verification configurations are given and compared with other feature extraction methods to show the desirable features of proposed algorithm.


License Plate Recognition Using a Novel Fuzzy Multilayer Neural Network
Osslan Osiris Vergara Villegas, Daniel Gonzalez Balderrama, Humberto de Jesus Ochoa Dominguez, Vianey Guadalupe Cruz Sanchez

Abstract: In this paper we present a proposal to solve the problem of license plate recognition using a three layer fuzzy neural network. In the first stage the plate is detected inside the digital image using rectangular perimeter detection and the finding of a pattern by pattern matching, after that, the characters are extracted from the plate by means of horizontal and vertical projections. Finally, a fuzzy neural network is used to recognize the license plate. The tests were made in an uncontrolled environment in a parking lot and using Mexican and American plates. The results show that the system is robust as compare to those systems reported in the literature.


Buffer Caching Algorithms for Storage Class RAMs
Junseok Park, Hyunkyoung Choi, Hyokyung Bahn, Kern Koh

Abstract: Due to recent advances in semiconductor technologies, storage class RAMs (SCRAMs) such as FRAM and PRAM are emerging rapidly. Since SCRAMs are nonvolatile and byte-accessible, there are attempts to use these SCRAMs as part of nonvolatile buffer caches. A nonvolatile buffer cache provides improved consistency of file systems by absorbing write I/Os as well as improved performance. In this paper, we discuss the optimality of cache replacement algorithms in nonvolatile buffer caches and present a new algorithm called NBM (Nonvolatile-RAM-aware Buffer cache Management). NBM has three salient features. First, it separately exploits read and write histories of block references, and thus it estimates future references of each operation more precisely. Second, NBM guarantees the complete consistency of write I/Os since all dirty data are cached in nonvolatile buffer caches. Third, metadata lists are maintained separately from cached blocks. This allows more efficient management of volatile and nonvolatile buffer caches based on read and write histories, respectively. Trace-driven simulations show that NBM improves the I/O performance of file systems significantly compared to the NVLRU algorithm that is a modified version of LRU to hold dirty blocks in nonvolatile buffer caches.


Web Page Information Architecture Formalization Method and It's an Example
Yorinori Kishimoto

Abstract: This paper proposed a formalization method of Web page information architecture by regular expression for checking its structure. This method classifies structure elements of a Web page in attributes on the basis of an idea of the Web information architecture, and it’s expressed by two types of equations on the basis of the F-Shaped reading pattern. This method can verify structure of the information architecture of a Web page. As a result, this method was able to analyze about structure elements of lack point and a redundant point in Web page information architecture.


Increasing Level of Correctness in Correlation with McCabe Complexity
Nicolae-Iulian Enescu, Dan Mancas, Ecaterina-Irina Manole, Stefan Udristoiu

Abstract: The scope of our research is finding a correlation between the correctness indicator and the McCabe complexity indicator for software programs. For this, the correctness and McCabe complexity indicators will be calculated for a simple program, written in C programming language. The computations will be made for each program version obtained by correcting different error type found in the testing process. Will be observed there is a closed correlation between correctness and McCabe complexity in the way that for an increasing of the correctness level there will also be a significant increase of the complexity level.


Adaptation of Satellite Navigation for Pedestrians with Electronic Compass
Krzysztof Tokarz, Michal Dzik

Abstract: Despite constantly improving medical techniques it is still impossible to cure many severe vision defects which causes great demand for developing new techniques that could help visually impaired persons to get through chores of everyday life. GPS navigation is the most valuable technology but currently available consumer GPS receivers do not offer good accuracy. At the Silesian University of Technology the research was done for improving the functionality and accuracy of navigation for blind persons. The GPS navigation device has been developed equipped additionally with electronic compass and accelerometer for improving accuracy of determining the azimuth.


Word Co-occurrence Matrix and Context Dependent Class in LSA based Language Model for Speech Recognition
Welly Naptali, Masatoshi Tsuchiya, Seiichi Nakagawa

Abstract: A data sparseness problem for modeling a language often occurs in many language models (LMs). This problem is caused by the insufficiency of training data, which in turn, makes the infrequent words have unreliable probability. Mapping from words into classes gives the infrequent words more confident probability, because they can rely on other more frequent words in the same class. In this research, we investigates a class LM based on a latent semantic analysis (LSA). A word-document matrix is commonly used to represent a collection of text (corpus) in LSA framework. This matrix tells how many times a word occurs in a certain document. In other words, this matrix ignores the word order in the sentence. We propose several word co-occurrence matrices that keep the word order. By applying LSA to these matrices, words in the vocabulary are projected to a continues vector space according to their position in the sentences. To support this matrices, we also define a context dependent class (CDC) LM. Unlike traditional class LM, CDC LM distinguishes classes according to their context in the sentences. Experiments on Wall Street Journal (WSJ) corpus show that the word co-occurrence matrix works 3.62%-12.72 better than worddocument matrix. Furthermore, the CDC improves the performance and achieves better perplexity than the traditional class LM based on LSA. When the model is linearly interpolated with the word-based trigram, it gives improvements about 2.01% for trigram model and 9.47% for fourgram model on relative perplexity against a standard word-based trigram LM.


Design and Development of a Qualitative Simulator for Learning Organic Reactions
Y. C. Alicia Tang, S. M. Zain, N. A. Rahman

Abstract: Our work features an ontology-supported framework for developing a qualitative simulator for explaining the behaviors of selected sample of organic chemistry reactions. The design of the simulator uses Qualitative Reasoning (QR), and in particular, Qualitative Process Theory (QPT) for constructing qualitative models and the simulation of basic steps in the chemical reactions such as creating and deleting bonds. The qualitative simulator allows learners to access notions of how the behavior of chemical systems evolves in time. Students would benefit from it in terms of improving their reasoning skills and enhancing their understanding in organic processes. The roles of each functional component of the qualitative simulator will first be introduced. Then, we move on to discuss the qualitative modeling and simulation design for reproducing the chemical behaviors of organic reactions. Finally, a discussion on the simulation results and explanation generation capability are presented.


Validation Methods of Suspicious Network Flows for Unknown Attack Detection
Ikkyun Kim, Daewon Kim, Yangseo Choi, Koohong Kang, Jintae Oh, Jongsoo Jang

Abstract: The false rate of the detection methods which are based on abnormal traffic behavior is a little high and the accuracy of the signature generation is relatively low. Moreover, it is not suitable to detect exploits and generate its signature. In this paper, we have presented ZASMIN (Zeroday-Attack Signature Management Infrastructure) system, which is developed for novel network attack detection. This system provides early warning at the moment the attacks start to spread on the network and to block the spread of the cyber attacks by automatically generating a signature that could be used by the network security appliance such as IPS. This system have adopted various technologies — suspicious traffic monitoring, attack validation, polymorphic worm recognition, signature generation — for unknown network attack detection. Especially, the validation functions in ZASMIN have to able to cover 1) polymorphism, which is an encrypted attack code at the penetration and operation step, 2) executables, which are any binary functions at each step, and 3) malicious string. And also, we introduce two concepts to validate the preprocessing of the suspicious traffic. The one is attack-based validation and the other is signature-based validation. These validation functions can reduce the false rate of the unknown attack detection. In order to check the feasibility of the validation functions in ZASMIN, we have installed it on real honeynet environment, then we have analyzed the result about detection of unknown attack. Even though short–period analysis is not enough long to detect various unknown attacks, we confirmed that ZASMIN can detect some attacks without any well-known signature.


Multi-Hash based Pattern Matching Mechanism for High-Performance Intrusion Detection
Byoungkoo Kim, Seungyong Yoon, Jintae Oh

Abstract: Many Network-based Intrusion Detection Systems (NIDSs) are developed till now to respond these network attacks. As network technology presses forward, Gigabit Ethernet has become the actual standard for large network installations. Therefore, software solutions in developing high-speed NIDSs are increasingly impractical. It thus appears well motivated to investigate the hardware-based solutions. Although several solutions have been proposed recently, finding an efficient solution is considered as a difficult problem due to the limitations in resources such as a small memory size, as well as the growing link speed. Therefore, we propose the FPGA-based intrusion detection technique to detect and respond variant attacks on high-speed links. It was designed to fully exploit hardware parallelism to achieve real-time packet inspection, to require a small memory for storing signature. The technique is a part of our system, called ATPS (Adaptive Threat Prevention System) recently developed. Most of all, the proposed system has a novel content filtering technique called Table-driven Bottom-up Tree (TBT) for exact string matching. However, as the number of signatures to be compared is growing rapidly, the improved mechanism is required. In this paper, we present the multi-hash based TBT technique with memory-efficiency. Simulation based performance evaluations showed that the proposed technique used on-chip SRAM less than 20% of the one-hash based TBT technique. Finally, experimental results about our system show a consistent performance in traffic level and had nothing to do with increasing number of signatures applied.


A Proposed Model for Individualized Learning through Mobile Technologies
Farhan Obisat, Ezz Hattab

Abstract: Mobile Learning (mLearning) describes a new trend of learning that uses innovations like wireless communication, personal digital assistants, digital content from traditional textbooks, and other sources to provide a dynamic learning environment.
With the facility of connecting people and information world-widely, the Internet has a major impact on the traditional education. Currently, students can easily access online courses at anytime anywhere in the globe. Since the Internet has been adopted by students, traditional pedagogical models are no more appropriate models. Consequently, new pedagogical models are required. Such models should be student-centric that based on individual student’s learning expectation, styles, interests and abilities. In this paper, first we discuss these four dimensions and then we introduce an individualized learning model that takes these dimensions into account. It discusses 1) student learning styles, 2) student learning interests and 3) student devices, such as personal profiles. The main objective is to help understanding the behaviors of the students and to materialize the concept of personalization.


A Fast Geometric Rectification of Remote Sensing Imagery Based on Feature Ground Control Point Database
Jian Yang, Zhongming Zhao

Abstract: This paper, on the basis of the traditional design of database for ground control point, tries to founded a fast auto-correction method of satellite remote sensing imagery based on feature ground control point database which brings local feature points as the effective supplement and aims to achieve the automatic matching between feature ground control points and original images that need geometric correction and improve the rectified process utilizing random sample consensus (RANSAC algorithm). In this method, the author realize the auto-extraction of feature ground control points for ensuring speed and precise geometric correction of a high volume of satellite remote sensing images by means of analyzing feature ground control point database algorithm.


Hierarchical Denormalizing: A Possibility to Optimize the Data Warehouse Design
Morteza Zaker, Somnuk Phon-Amnuaisuk, Su-Cheng Haw

Abstract: Two of the most common processes in database design community include data normalization and denormalization which play pivotal roles in the underlying performance. Today data warehouse queries comprise a group of aggregations and joining operations. As a result, normalization process does not seem to be an adequate option since several relations must combine to provide answers for queries that involve aggregation. Further, denormalization process engages a wealth of administrative tasks, which include the documentation structure of the denormalization assessments, data validation, and data migration schedule, among others. It is the objective of the present paper to investigate the possibility that, under certain circumstances, the above-mentioned justifications cannot provide justifiable reasons to ignore the effects of denormalization. To date, denormalization techniques have been applied in several database designs one of which is hierarchical denormalization. The findings provide empirical data that show the query response time is remarkably minimized once the schema is deployed by hierarchical denormalization on a large dataset with multi-billion records. It is, thus, recommended that hierarchical denormalization be considered a more preferable method to improve query processing performance.


A Study on Industrial Customers Loyalty to Application Service Providers – The Case of Logistics Information Services
Cheng-Kiang Farn, Li Ting Huang

Abstract: The growth of application service providers has been phenomenal in application service industry worldwide. Application service providers usually provide service which is comprised with modularized and standard components. Customers can easily switch to another supplier based on the comparison between cost and benefit if their service is comprised with modularized and standard components. So, keeping a long-term relationship with industrial customers is getting an imperative strategy for application service providers in order to pursue more predictable source of revenues and successive income streams. Yet, cost-effective feature of ASPs is not the sufficient condition for ensuring business success. Cultivating relationship management whose core concept is to enhance loyalty of existing customers gradually becomes a critical issue for application service providers. This study investigates economic and psychological factors simultaneously and compares subtle difference between influences of economic and psychological factors on customer loyalty. Empirical result from a questionnaire survey leads to several findings. The importance of psychological factors is relative importance to loyalty formation in comparison with economic factors. Service quality both directly and indirectly affects customer loyalty. Trust affects loyalty mediated by affective commitment. Switching barrier affects continuous commitment, while it positively moderates the relationship of service quality and loyalty. This finding is contrary to literature. Moreover, influences of affective and continuous commitment are distinct by business types. Findings reveal that psychological factors are also important to loyalty formation in B2B environment. Firms could pay more attention on commitment. Implications and limitations are discussed.


Digital Steganalysis: Computational Intelligence Approach
Roshidi Din, Azman Samsudin

Abstract: In this paper, we present a consolidated view of digital media steganalysis from the perspective of computational intelligence. In our analysis the digital media steganalysis is divided into three domains which are image steganalysis, audio steganalysis, and video steganalysis. Three major computational intelligence methods have also been identified in the steganalysis domains which are bayesian, neural network, and genetic algorithm. Each of these methods has its own pros and cons.


An Empirical Analysis of Relationship Commitment and Trust in Virtual Programmer Community
Yu-Ren Yen

Abstract: Virtual Communities (VCs) have become a forum for programmer seeking knowledge to resolve problems and communicate with each other. The Internet makes participant relatively easy to switch for one VC to another VC that provides similar content or services. However, many VCs have failed due to the reluctance of members to continue their participation in these VCs. In volatile cyberspaces, VCs without specific domain knowledge may face challenges such as large populations, unstable memberships, and imperfect information and memory, which also affect knowledge flows within members. The most important aspect of VCs from the members’ perspective is the increase satisfaction, and engage behavioral intention to use VCs, but satisfaction does not always predict continuous usage. This study proposes a conceptual model based on commitment-trust theory (CTT) and investigates the continuance intention in VC. It seeks to theorize the antecedents and consequence of relationship commitment in the VCs and identify how CTT can be adapted in a knowledge sharing environment. The members of Programmer Club, a representative professional community in Taiwan, were chosen to participate in the survey, and 488 usable responses were collected in three months. Structural Equation Model (SEM) was used to test the model, the findings show that relationship commitment and trust is the strongest predictor of members’ continuance intention. Implications are proposed in the final section.


Why Focal Firms Share Information? A Relational Perspective
Chia-Chen Wang, Chun-Der Chen, Yu-Fen Chen, Cheng-Kiang Farn

Abstract: Supply chain management has become an important issue for Taiwan’s manufacturing industry due to escalating global competition. Virtual vertical integration is an important issue in supply chain management. Because organizations only have limited resources, they pursue long-term partnership with specific transaction partners. They share information to improve visibility, speed responses to markets, and reduce costs from information distortion or information asymmetry. This study empirically explores the factors affecting inter-organizational information sharing from the perspective of focal firms. 1,000 questionnaires were administered to top 1,000 manufacturing companies in Taiwan, with 139 valid responses. The results show that partner’s power, trust, and relation-specific asset investments positively affect inter-organizational information sharing. On the other hand, the partner’s power does not significantly affect the organization’s relation-specific investments. This study further investigates the moderating role of information technology competence and trust. The result indicates that when an organization has lower information technology competence, the relationship between the partner’s power and relation-specific investments is significant. In addition, when the focal firm has lower trust in the customer, there is significant relationship between relation-specific investments and information sharing. Implications and discussion are then provided.


DEA-RTA: A Dynamic Encryption Algorithm for the Real-Time Applications
Ahmad H. Omari, Basil M. Al-Kasasbeh, Rafa E. Al-Qutaish, Mohammad I. Muhairat

Abstract: The Internet and it is applications are hungry for high level of Quality of Service (QoS), and most of the Internet applications seek to minimize packets delay, especially, the Real-Time Applications (RTA). QoS is considered as a major issue in the Internet, where RTA services like IPTelephony and XoIP become a successful business in the world, call distribution may result in big money loss, for this reason researchers put their efforts to build applications that can deal with different levels of QoS. In addition to the basic QoS some customers ask to preserve confidentiality which makes it more complicated and may result in higher delay time.
Delay is very complex issue specially in RTA, and it consists of many types of delays, such as, Packetization delay (sampling, coder-decoder (codec),compression and encryption), and end-to-end delay (processing, queuing, serialization and propagation delays), our research try to achieve better encryption delay at the user machine CPU level while maintain confidentiality. The proposed algorithm is a new symmetric encryption technique that allows users to choose using new different key for each single packet if they wish. The encryption key is flexible in length, the plain text is flexible in size, the encryption process is very simple, the transposition table is simple too, the shifted transposition table is easy to initiate and complex to regenerate. These properties results in better encryption delay while maintaining confidentiality, the algorithm is 15 times faster and 10 times faster than AES algorithm.


    Paper Title, Authors, Abstract (Issue 2, Volume 3, 2009)


The Integration of Seafood Traceability System for Shrimp Value Chain Systems
Echo Huang, Juh-Cheng Yang

Abstract: The impact of information systems on productivity is wide ranging and potentially affects all other activities of a company. This trend extends beyond high-tech companies in Taiwan. The aquacultural industry is finding they can substantially increase productivity and reduce costs by moving process tracking, management and reverse tracking functions online. This paper presents a new radio frequency identification (RFID) and quick response code-based (QR codes) system for managing in-house seafood cultivation, inspection, distribution and retailing and its impact on productivity and costs. The value chain system was tested in a white shrimp cultivation factory which provides live-shrimp offerings, and demonstrated efficiency, effectiveness, and better customer services from the model. The traceability is mainly the standard that guarantees the food security of consumer, is a system that improves a risk management and promotes to produce effect and industry level. Integrate RFID and the technique of QR CODE, combine entity logistics and information process, record product all messages inside the life cycle in detail, increase information visibility, change traditional farming supply chain homework mode, will effectively raise the additional value of whole supply chain system.


Integration of Variance Analysis and Multi Attribute Methods of Decision in Application of Optimal Factor Combination Choice in One Experiment
Dragan Randjelovic

Abstract: Beside one affirmation their hypothesis scientists make experiments to choose the optimal from available possibilities in one experiment. It is known that on the results of one experiment make influnce treatments and other uncontrolled factors called experimental error which must be smaller and for this reason scientists make different statistical plans. Mathematical apparatus for experiment organization are possible to search on the basis of total random distribution, random block distribution and special organized block distribution while they can most effectively represent complex most often multifactor even multivariate experiments. It is very dificult to make analysis of results and especially determine the optimal factor combination choice in these experiments with respondable apparatus of multiple regression analysis, or canonical analysis in multivarite case, and at any rate with help of variance analysis. Because of that for optimal factor combination choice in one experiment authors propose procedure based on integration of analysis of variance and multi attribute methods of decision. In the end of this paper are given three examples on which are demonstrated proposed procedure.


A Compact Colored Petri Net Model for Fault Diagnosis and Recovery in Embedded and Control Systems
A. Spiteri Staines

Abstract: This paper describes the modeling and use of a reduced Colored Petri net for fault diagnosis and recovery in embedded and control systems. The reduced or compact Colored Petri net modeling approach can be extended to other classes of real time systems, real time hardware, etc. A reduced colored Petri net is a compact form of a Colored Petri net having complex token types based on sets or complex sets containing the structured information for error handling. The approach presented here will reduce the size of the Colored Petri net because information is put in the token instead of having many additional places and transitions as is typically done. This approach is illustrated with a comprehensive example of a computerized fuel control system for a combustion turbine. The Colored Petri net is an executable model. It is analyzed structurally and results are shown and interpreted.


A Fuzzy Model to Evaluate the Motivation to Quality Programs
Denise Dumke de Medeiros

Abstract: This article emphasizes motivation and competence as basic factors needed to optimize human action with regard to quality. To evaluate the motivation to quality, a model with objective characteristics is proposed, using Herzberg’s Two Factor Theory, and Fuzzy Set Theory. As this is a difficult area to measure, the model proposes an objective methodology that makes it possible to detect the motivational strategies that make employees more susceptible to the reality of the enterprise. This can help managers choose the best model to motivate the employees. An application of the methodology is also presented.


Email Threads: A Comparative Evaluation of Textual, Graphical and Multimodal Approaches
Saad Alharbi, Dimitrios Rigas

Abstract: Email threads were implemented by enormous number of studies in order to improve the efficiency of email clients. Nevertheless, contextual information about messages in the threads was somewhat neglected by most of these studies. This paper describes an empirical study carried out to investigate into how extent can such information be implemented in email threads. Furthermore, this study aimed to investigate various ways of communicating this type of information. Therefore, three email threads approaches that presented various types of information in different ways were developed. Textual approach, which presented related messages with chronological and contextual information in the main view of the email client. Graphical approach, which presented related messages with chronological, relationships and contextual information in a temporal view. Multimodal approach, where threads presented in a similar way of the previous approach with some contextual information communicated aurally (i.e. non-speech sound). These approaches were tested comparatively with three independent groups of users. The results were analysed based on effectiveness (i.e. tasks completion rate and identification of threads information) and efficiency (i.e. tasks accomplishment time and errors rate). The results indicated that multimodal threads approach was more effective and efficient than the textual approach. The results also highlighted that the large scale of graphically presented information in the graphical approach has negatively affected its effectiveness when compared to the textual approach especially with complex email threads. However, communicating messages information through two channels (i.e. visual and auditory channels) in the multimodal approach helped to reduce the graphical overload and hence significantly improved the usability when compared to the graphical approach.


Using Assembler Encoding to Solve Predator-Prey Problem
Tomasz Praczyk

Abstract: The paper presents a neuro-evolutionary method called Assembler Encoding. The method was tested in the predator-prey problem. To compare Assembler Encoding with another neuro-evolutionary method, in the experiments, a co-evolutionary version of simple connectivity matrix was also applied.


Solving Traveling Salesman Problem on Cluster Compute Nodes
Izzatdin A. Aziz, Nazleeni Haron, Mazlina Mehat, Low Tan Jung, Aisyah Nabilah Mustapa, Emelia Akashah P.Akhir

Abstract: In this paper, we present a parallel implementation of a solution for the Traveling Salesman Problem (TSP). TSP is the problem of finding the shortest path from point A to point B, given a set of points and passing through each point exactly once. Initially a sequential algorithm is fabricated from scratch and written in C language. The sequential algorithm is then converted into a parallel algorithm by integrating it with the Message Passing Interface (MPI) libraries so that it can be executed on a cluster computer. Our main aim by creating the parallel algorithm is to accelerate the execution time of solving TSP. Experimental results conducted on Beowulf cluster are presented to demonstrate the viability of our work as well as the efficiency of the parallel algorithm.


Emotional Agents in Computer Games
Khalil Shihab

Abstract: In this paper, we consider emotion as a factor in the decision-making process and actions taken by an agent can be represented by a model, called “emotional model” created with specific focus on computer games development. It is designed to explore people’s behavior in certain circumstances, while under specified emotional states. Special attention was given to the thought process and actions displayed in the hypothetical scenarios. We characterized thoughts and actions associated with each scenario and emotional state. Each particular action or proof of steps taken in the thought process was given a percentage value directly proportional to answers given by the test population. Finally, we developed an experimental game program for the evaluation of our emotional decision making model. The aim of the evaluation was to find out how real life agents reacted in certain situations and what processes the human mind runs through when thinking and acting upon certain situations.


    Paper Title, Authors, Abstract (Issue 3, Volume 3, 2009)


A Contribution to the Application of Autonomous Control in Manufacturing
B. Scholz-Reiter, St. Sowade, D. Rippel, M. Teucke, M. Ozsahin, T. Hildebrandt

Abstract: The apparel industry is a prime example for the field of manual manufacture. Problems in manufacturing control are caused by manual handling of garments and influence the availability and correctness of information. This bad information quality leads to problems along the supply chain from production to disposition. Automated data management based on radio frequency identification technology is proposed to solve these problems. Autonomous control can be established on top to increase the system robustness and flexibility and to enable smaller manufacturing batch sizes. Although autonomous control is easily applicable in highly automated systems its application in manual processes is generally difficult. Three different system architectures are discussed, diverse technical approaches are analyzed and decision is made for one approach based on radio frequency identification and manufacturing batches that suits the apparel scenario well.


An Action Decision Model for Emotions based on Transactional Analysis
H. Fujita, N. Sawai, J. Hakura, M. Kurematsu

Abstract: Human computer Interaction based on emotional modeling has been investigated and reported in this paper. Human personality has been analyzed based on ego-gram analysis and accordingly human "SELF" emotional model has been created. We have created as one part a computerized model which reflects a human user (in this paper Miyzawa Kenji model) impeded as a computer model and through it, an emotional interaction between that model and the real human user is established. The interaction scenarios and reasoning are based on transactional analysis. We have implemented the system and empirically, examined it, as experiment in public space for revision and evaluation.


Generic Interactive Natural Language Interface to Databases (GINLIDB)
Faraj A. El-Mouadib, Zakaria S. Zubi, Ahmed A. Almagrous, Irdess S. El-Feghi

Abstract: To override the complexity of SQL, and to facilitate the manipulation of data in databases for common people (not SQL professionals), many researches have turned out to use natural language instead of SQL. The idea of using natural language instead of SQL has prompted the development of new type of processing method called Natural Language Interface to Database systems (NLIDB). The NLIDB system is actually a branch of more comprehensive method called Natural Language Processing (NLP). In general, the main objective of NLP research is to create an easy and friendly environment to interact with computers in the sense that computer usage does not require any programming language skills to access the data; only natural language (i.e. English) is required. Many systems have been developed to use the concept of NLP in different varieties of domains, for example the system LUNAR [19] and the system LADDER [8]. One drawback of previous systems is that the grammar must be tailor-made for each given database. Another drawback is that many NLP systems cover only a small domain of the English language questions. In this paper we present the design and implementation of a natural language interface to a database system. The system is called Generic Interactive Natural Language Interface to Databases (GINLIDB). It is designed by the use of UML and developed using Visual Basic.NET-2005. Our system is generic in nature given the appropriate database and knowledge base. This feature makes our system distinguishable.


Estimation Model of Labor Time at the Information Security Audit and Standardization of Audit Work by Probabilistic Risk Assessment
Naoki Satoh, Hiromitsu Kumamoto

Abstract: Based on the factors that are available at the initial phase of the audit task, this paper proposes a labor time estimation method for the information security audit in the form of formula, statistically analyzing the data of the past 20 cases. Initially, audit mode, operation mode, penetration degree, and company size are considered to be the factors that could influence the labor time, and thus the “quantitative analysis I” is conducted with these factors. However the results were not sufficiently positive. As a result, by dividing audit mode into regular and emergency audit and by using company size as the factor, labor time estimation formula has been established by means of the regression analysis. Compared to regular audit, it is found that emergency audit takes more labor time at information security audit. We try to investigate this factor by probabilistic risk assessment.


Secret Image Recovery based on Search Order Coding
Wei-Kai Su, Lee Shu-Teng Chen, Shang-Kuan Chen, Ja-Chen Lin

Abstract: In this paper, we propose an image recovery method based on search order coding (SOC). By using SOC technique, we can generate a SOC image for an input secret image. If the secret image is damaged, by referring to its SOC image, the damaged image can be repaired to a better one. In addition to the proposed basic version of the SOC recovery technique, we also modify it to an advanced one. The advanced version provides a more flexible method that repairs the damaged image by two different ways according to the availability of the mapping table. The secret image can still be recovered even when it is seriously damaged. Besides, the proposed SOC recovery technique can be applied to not only the gray values of the secret image but also the VQ indices. Experiments show that the recovery ability of the VQ indices is better than that of pixel values. Moreover, the SOC image alone reveals nothing about the secret image. Therefore, the SOC image is safer than directly duplicating the secret image.


Efficient Biometric Watermark Embedding by Flipping on Binary Text Documents
Chi-Man Pun, Ioi-Tun Lam

Abstract: In respect to the issues on privacy, security and legal significance of a document, some sorts of security protections should be put on a document to ensure its genuineness and integrity. In this paper, signatories’ encrypted digital biometric fingerprint in binary format will be embedded into a binary text document by Flipping – one of the methods in spatial domain. During the embedding process, document will be adaptively partitioned into blocks with fixed size of pixels according to the number of bits in the watermark message. Each watermark bit is embedded into each block by Flipping. Based on the odd or even number of pixels in each block on the embedded document, the fingerprint watermark message is extracted after decryption. Experimental results from our prototype system show that the proposed method is successfully tested for embedding and extracting a fingerprint watermark message in a document no matter it is written in hieroglyph or in alphabetic character.


Analysis of Information Security Problem by Probabilistic Risk Assessment
Naoki Satoh, Hiromitsu Kumamoto

Abstract: The information security risk assessment is investigated from perspectives of most advanced probabilistic risk assessment (PRA) for nuclear power plants. Accident scenario enumeration by initiating events, mitigation systems and event trees are first described and demonstrated. Assets, confidentiality, integrity, availability, threats, vulnerabilities, impacts, likelihoods, and safeguards are reformulated by the PRA. Two illustrative examples are given: network access attacker and physical access attacker. Defenseless time spans and their frequencies are introduced to cope with non-rare initiating events of information security problems. A common event tree structure may apply to variety of security problems, thus facilitating the risk assessment.


    Paper Title, Authors, Abstract (Issue 4, Volume 3, 2009)


Customers Satisfaction in Shipping Companies under Artificial Intelligence and Multicriteria Decision Analysis
Nikolaos Loukeris

Abstract: Strategic Planning is formed considering customers satisfaction to maximise the market share. In shipping companies, the identification of satisfaction within clients is very difficult, thus satisfaction’s prediction provides valuable information. Previous research in the field used techniques of multicriteria analysis, data mining and analytical-synthetical preference models. This research paper aims to define the most effective method to predict satisfaction, between techniques of data mining, rough sets, neural networks and multcriteria decision analysis.


Improvement of Rule Based Morphological Analysis and POS Tagging in Tamil Language via Projection and Induction Techniques
M. Selvam, A. M. Natarajan

Abstract: Morphological analysis and part of speech (POS) tagging are very essential for natural language processes like generation of Treebanks, training of parsing models and parsing. Rule based approach is applicable to the languages which have well defined set of rules to accommodate most of the words with inflectional and derivational morphology. Rule based morphological analysis and POS tagging are very difficult and cannot accommodate all combinations through the rules due to inflections and exceptions especially in languages like Tamil. Statistical methods are very important which in turn need large volume of electronic corpus and automated tools which are very rare in Tamil. Since English is very rich in all aspects, POS tags can be projected to Tamil through alignment and projection techniques. Rule based morphological analyzer and POS tagger can be built from well defined morphological rules of Tamil. They can be further improved by the root words induced from English to Tamil through the sequence of processes like alignment, lemmatization and induction with the help of sentence aligned corpora like Bible corpora, TV news, newspaper articles since finding the root in the inflected words is very difficult and leads to ambiguity. In our experiments, rule based morphological analyzer and POS tagger were built with 85.56% accuracy. POS tagged sentences in Tamil were obtained for the Bible corpus through alignment and projection techniques and categorical information had been obtained. Root words were induced from English to Tamil through alignment, lemmatization and induction processes. Further 7% improvement was made in rule based morphological analyzer and POS tagger using categorical information and root words obtained from POS projection and morphological induction respectively via sentence aligned corpora.


Viewpoint of Probabilistic Risk Assessment in Information Security Audit
Naoki Satoh, Hiromitsu Kumamoto

Abstract: After the information security audit, the auditor commonly points out the importance of information assets, the vulnerability of the audited information system, and the need of countermeasures. On such an occasion, the audited often ask the auditor for the quantitative assessment of the risk so that they can take specific measures. Nevertheless, in reality, the auditor can hardly meet this requirement because they do not have any appropriate methods to assess the risk quantitatively and systematically. Therefore, this paper proposes the approach that makes it possible to identify the scenarios of information security accidents systematically, to assess the risk of the occurrence of the scenario quantitatively, and to point out the importance of taking countermeasures by incorporating Probabilistic Risk Assessment in information security audit. For the concrete description and explanation of this approach, this paper takes the case of the audit of password management as an example. By enumerating the possible scenarios that indicate how initiating events, the vulnerability of mitigation systems, and the failures of operations can allow illegal accesses to the information assets, this paper shows that it is possible to assess the security risks by the pair of defenseless time span and its occurrence frequency of each scenario. Finally, since the parameters necessary for risk quantification such as the occurrence frequency of password theft, the probability of theft detection, and the probability of taking countermeasure after the theft have uncertainty, the uncertainty of the occurrence of the scenario itself is assessed by propagating the incompleteness of the knowledge of these parameters with random digits.




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