Digital Enterprise and Information Systems

This work aims to exploit a distinguished method of the public key cryptography which is known as Identity-Based Cryptography (IBC) to solve the usability problem of secure e-mail systems. The public key is taken from general information (such as e-mail address) of the recipient and thus does not require access to any certificate to validate the key. To increase the system strength, the identity-based cryptography is combined with mediated cryptography to enable the cancelation of any key that is being exposed or suspicious. In addition, all the operations of decryption and signature are controlled (without the ability to fraud or detect secret) by the authorized person to prevent hackers and non-authorized parties from using or manipulating of the system. This proposal includes the deployment of the combined method for Mediated Identity-Based Cryptography.

E-mail brings us lots of conveniences. Especially with help of PGP and S/MIME, it gives both confidentiality and message/origin authentication. However, in some cases for strong privacy, a message sender will not want to let others know even the fact that he sent a message to a recipient. Very recently, Harn and Ren proposed a fully deniable authentication scheme for E-mail where a sender can repudiate his or her signature. In this paper, however, their deniable authentication scheme is proved not to be fully deniable. To resolve this deniability problem, we suggest a designated verifier signature scheme to support strong privacy, and construct a privacy-enhanced deniable authentication E-mail scheme using the designated verifier signature scheme. Compared with the Harn and Ren’s scheme, the proposed scheme has a simple cryptographic structure and can be easily realized with the existing secure E-mail systems.

In this paper, an extended sequence using chaotic map and Bernstein form Bézier curve to improve the chaotic key sequence is presented. Based on this sequence, we perform the scrambling in DCT domain with variable control parameters. To further enforce the security, the gray values of image pixels are diffused using keystream extracted from the extended key sequence of the chaotic map and the plainimage. As a result, the algorithm resists the chosen-plaintext/chosen-ciphertext/known-plaintext attacks, as diffusion depends on the plainimage. Moreover, experimental results and analysis confirm a high security level using the proposed scheme.

There exists a big demand for secure electronic communications while the expertise level of attackers increases rapidly and that causes even bigger demands and needs for an extreme secure connection. An ideal security protocol should always be protecting the security of connections in many aspects, and leaves no trapdoor for the attackers. Nowadays, one of the popular cryptography protocols is hybrid cryptosystem that uses symmetric and public key cryptography to change secret message. In available cryptography protocol attackers are always aware of transmission of sensitive data. Even noninterested attackers can get interested to break the ciphertext out of curiosity and challenge, when suddenly catches some scrambled data over the network. In this paper we discuss about the disadvantages of asymmetric algorithms in cryptography protocol. Furthermore, this paper proposes new cryptography protocol based on DNA steganography to reduce the usage of public cryptography to exchange session key. In this protocol session key between sender and receiver is hidden by DNA data hiding technique. Therefore, the attackers are not aware of transmission of session key through unsecure channel. Finally, the strength point of the DNA steganography is discussed.

The main target of this paper is to propose an algorithm to implement data hiding in DNA sequences to increase the complexity by using software point of view. By utilizing some interesting features of DNA sequences, the implementation of a data hiding is applied. The algorithm which has been proposed here is based on binary coding and the complementary pair rules. Therefore, DNA reference sequence is chosen and also a secret message M is hidden into it. After applying three steps, M’” is come out. Finally, M’” is sent to the receiver. When the receiver takes the M’”, the process of identifying and extracting the original message M, which has been hidden in DNA reference sequence, begins. In addition, security issues are demonstrated to inspect the complexity of the algorithm.

NAND flash memory lacks an over-write operation, and NAND-based storage deploys flash translation layer (FTL), which emulates the over-write with out-of-place updates. The performance of NAND-based storage is mainly determined by the performance of the FTL, which significantly varies according to access pattern. The present work aims to identify key attributes of access pattern which favors for the FTL. If the key attributes are identified, file systems can be modified to generate NAND-friendly access pattern. The performance evaluation results through trace-driven simulations shows that the request size is the most critical factor that impacts on the performance.

Until now, most service annotation has been added the semantics to WSDL, that is a description of SOAP based web services. But REST services have been widely used because of simplicity and usability. In order to discover the most suitable services among various web services and compose them, the integrated service annotation of SOAP and REST web services is necessary. In this paper, we present semantic service framework which is designed for user’s goal based service discovery and composition. And we present the semi-automatic service annotation for SOAP and REST web services. The proposed annotation approach deals with functional semantics, non-functional semantics, and data semantics from web service description and web service portal. Based on this service annotation, it is useful to discover and compose services that satisfy the user’s goal.

E-commerce, the buying and selling of goods and services over the Internet and other digital technologies has attracted much research especially in developing countries within the last two decades. Findings from such researches focused more on the barriers to e-commerce with very little on the extent of adoption. This paper utilized the findings from past studies and the explanatory case study methodology to describe the extent of e-commerce adoption in Nigeria. Recent attempts to transcend known e-commerce barriers and the role of banks and available ICT technologies are also discussed.

Over the last decade, enrollment in information systems (IS) related programs has plummeted worldwide and still remains low despite positive job market predictions. Given the significant negative consequences of low enrollments on both academia and industry, the IS community has focused its efforts on mechanisms to increase enrollments. This study investigates how such a mechanism – social support – influences students’ aspirations to pursue an IS degree. More specifically, the study suggests that social support, self-efficacy, outcome expectations, and interests are expected to independently and cumulatively affect students’ choice of IS.

The definitive classification of scientific journals depends on their aims and scopes details. In this paper, we present an approach to facilitate the journals classification of the DBLP datasets. For the analysis, the DBLP data sets were pre-processed by assigning each journal attributes defined by its topics and then the theory of formal concept analysis is introduced. It is subsequently shown how this theory can be applied to analyze the relations between journals and the extracted topics from their aims and scopes. The result is a concept lattice that contains information on journal-topic relational context depending on how they are associated. It is shown how this approach can be used to facilitate the classifications of scientific journals.

In this work is presented the total least squares algorithm and its application in the economic field, whose calculation can be performed using certain software packages. This approach can be also used to analyze the dependence between various economic indicators, especially for the situation in which the direction of the causality between the model variables is unknown. The model is employed for studying the relation between wheat market prices for three Romanian historical regions, which are some of the most important cereal producers for Romania. The final result consists in a unified formula, which provides a global pattern of the national wheat market as a whole.

Optimal selection of interdependent IT projects for funding in multi period has been challenging in the framework of Real Option analysis. This paper presents a mathematical model to optimize the fuzzy Option value for multi-stage portfolio of IT projects. A fuzzy Option model is used to maximize the Option value of each IT project. The IT portfolio selection problem is formulated as a fuzzy zero-one integer programming model that can handle both uncertain and flexible parameters to determine the optimal project portfolio. The idea of optimizing the fuzzy real option value of the portfolio is to maximize the overall value and to minimize the downside risk of the selected portfolio for funding. A transformation method based on qualitative possibility theory is developed to convert the fuzzy portfolio selection model into a crisp mathematical model from the risk-averse perspective. The transformed model can be solved by an optimization technique .The optimization model and solution approach can help IT managers in optimal funding decision making for projects prioritization.

The power of IT and business alignment that has the use of a communication model of the IT value should be based on the ability to engage IT governance models and IT management models, respectively. This engagement should provide a clear view both board members, users and IT staff. Thus, our research provides this communication model that explains explicitly how IT projects, the board’s strategy and business units should go together and in the same direction. In addition, our implementation of this model alerts the CIO when IT assets are not really aligned to the principles and objectives of the board or the budget is spent on just technology, not investing it in valued solutions. Our research methodology is based on the ISO/IEC 38500 standard model, although important features have been added based on our IT governance experience and the use of a tool that implement the model itself.

The growing interest in Peer-to-Peer systems (such as Gnutella) has inspired numerous research activities. The problem in a schema-based Peer-to-Peer (P2P) system is how to locate Peers relevant to a given query. Different methods proposed routing strategies of queries taking into account the P2P network at hand. In this paper, we propose an architecture, based on (Super-) Peers, and we focus on query routing. Our approach considers that (Super-) Peers having similar interests are grouped together for an efficient query routing method. In such groups, called Super-Super-Peers (SSP), Super-Peers submit queries that are often processed by members of this group. A SSP is a specific Super-Peer that contains knowledge about: 1. its Super-Peers and 2. The other SSP. Knowledge is extracted by using data mining techniques (e.g. decision tree algorithms) starting from queries of Peers that transit on the network. The advantage of this distributed knowledge is that, it avoids making semantic mapping, between heterogeneous data sources owned by (Super-)Peers, each time the system decides to route query to other (Super-)Peers. The set of SSP improves the robustness in queries routing mechanism and scalability in P2P Network. Compared with a baseline approach, our proposed architecture shows that data mining technique increase performance with respect to response time and precision.

This study examines why consumers accept and continue to use e-payment for online purchase, specifically, the relationship between their perceived benefits, legal protection, risk avoidance, and satisfaction with prior experiences. The analytical results presented in this study indicate that beliefs (benefits, legal protection and risk allocation) differentially affect e-payment use behavior. Notably, consumer beliefs and confirmation affect satisfaction with e-payment use and continuance intention. Finally the practical and theoretical implications of this study are discussed.

Identity Federations are increasingly being used to establish convenient and secure attribute-based authentication and authorization systems. During the last few years, a third aspect has become important within these federations: i.e., payment. Thus, several payment approaches have been designed and used in Identity Federations. However, when more than one federation is being combined into an inter-federation association, federation bridges have to be established to translate messages between the participating federations. Whilst the problem of bridging identity information between federations has already been considered in many research activities, the problem of how to bridge payment data still remains unsolved. Therefore, this paper presents a solution to bridge between a SAML-based payment enabled Identity Federation and four other kinds of payment solutions used by Identity Federations.

The main objective of this paper is to present the ERP implementation’s risk factors in state owned company in post-socialist transitioning country as Bosnia and Herzegovina is. Paper will treat selected risks factors according to their impact on implementation process. This study presents observations/remarks based on experience of authors in ERP implementation projects in public sector in Bosnia and Herzegovina. This paper aims to generate list of ERP implementation factors that will provide structural knowledge for all stakeholders involved in the process of ERP implementation in public sector. Also it could be approached as a ground base for professionals to foster its implementation practices and focus on critical factors.

This research investigates the Factors influencing Enterprise Resource Planning implementations in Australia. It is accomplished through five case studies conducted in five companies in Australia. Five senior managers were interviewed, each of whom was involved in ERP implementation in their respecting companies. Some of the findings of this research show that business factors are the most important cause in initiating ERP implementations within business organisations, followed with personnel and technology factors. The research has also indicated that the user engagement is very important to the success of ERP implementation, and it can have an effect on the success and failure of ERP projects.

In this research, we focus on software namely Building Submission Checklist System (BuSCLIS) that has been developed to be use in construction industry. An objective of developing BuSCLI is to simplify the management of submission data of building plan approval through online system for the Local Authority (LA) or State Town and Country Planning in Malaysia. We presents the data management of the system through the data dictionary include login, user, contractor, consultant, checklist, location and project. BuSCLI facilitates user by computerized the forms and provide fast, efficient, transparent, effective service to the engineer, architect and contractor. Relevant and timely information managed by sophisticated BuSCLI with the database management system, MySQL.

Recently, fuel price becomes as hot topic and never ending issue especially the demand of fuel is very high. Malaysia Government has stood up in helping citizens by giving certain amount of money per vehicle owner to reduce their burden. However, the solution of reducing the total amount of fuel cost and consumption seems to be more helpful if the citizens can plan their fuel expenditure efficiently without unnecessary spend. Therefore, new software namely Online Fuel Consumption Cost Calculator (OFCCC) has been developed to help user plan and calculates the total amount of fuel cost for a car to travel based on the distance given, driving speed, weight capacity and current market fuel price cost. This software has been developed by using Microsoft Web Expression 2 and SQL Server database system. The result shows that the users can obtain a minimum cost towards the desired destination by using OFCCC.

In recent years, Internet auctions have become increasingly widespread. The Independent Private Values (IPV) model is widely used in the studying of auction behaviour and plays a fundamental role in many analyses of Internet auction performance. This model assumes privacy and independence, meaning that the private values of buyers are drawn from a common distribution, or in probabilistic terms, the series of values are independent and identically distributed. Since a general stochastic analysis is intractable, the IPV model has a significant impact on auction behaviour. In this paper, we study auction performance using an auction process simulator, considering both the hard close and soft close types of Internet auctions. From our experimental findings, we are able to establish quantitative relationships between the different auction process parameters, and also to deploy suitable IPV distributions in modelling the characteristics of different communities of bidders.

Cloud computing is fundamentally altering the expectations for how and when computing, storage and networking resources should be allocated, managed, consume and allow users to utilize services globally. Due to the powerful computing and storage, high availability and security, easy accessibility and adaptability, reliable scalability and interoperability, cost and time effective cloud computing is the top needed for current fast growing business world. A client, organization or a trade that adopting emerging cloud environment can choose a well suitable infrastructure, platform, software and a network resource, for any business, where each one has some exclusive features. In this paper, we managed a comprehensive classification for describing cloud computing architecture. After this classification, easy to choose a specific cloud service out of several existing cloud computing services developed by various projects globally such as Amazon, Google, Microsoft, Sun, force.com etc. Using this survey results not only to identify similarities and differences of the various aspects of cloud computing, but also identifying some areas for further research.

Owing to their ability to easily organize and update heterogeneous knowledge, Decision-Support Systems form a promising approach for the optimization of logistics businesses. The management and visualization of the knowledge base of these systems are in this regard crucial to ensure a proper functioning and to keep an intuitive view of their expected behavior. This paper introduces Atlas, a customizable automated tool for assisting / improving the supply chain with respect to miscellaneous aspects such as secure collaboration, traceability, or multimodality. The operational knowledge of Atlas is accessed through 2 different views. In an analytical view, the knowledge is modeled on elementary if-then rules, which are processed by a resolution engine written in the Soar architecture. A synthetic view offers a pictorial representation of all the knowledge, and in particular, shows the inter-dependence of the rules and their procedural references. In addition to allowing an efficient processing, the system checks the coherence of the knowledge and produces a justification of the decision with respect to relevant operational procedures.

In a competitive environment, those enterprises that always look forward and implement customer-winning supply chain competencies are more profitable than those that do not have such. Existing approaches have not considered customers’ needs in the supplier selection and negotiation processes. This paper aims to present a systematic agent-based framework for supplier selection based on the case-based reasoning approach to evaluate material offers, and negotiate with the suppliers and customers on the price, volume, quality grade, and delivery date of supply materials. The main objective of this research is to take the customers’ needs into consideration and provide them with alternative products which are closest to their first order if their first order was out of stock or they couldn’t get supply from the suppliers. Based on the proposed framework, a numerical example of the known case study is illustrated for highlighting the effectiveness of the approach.

The recent financial crisis that has devastated many nations of the world has made it imperative that nations upgrade their credit scoring methods. Although statistical methods have been the preferred method for decades, soft computing techniques are becoming increasingly popular due to their efficient and accurate nature and relative simplicity. In this paper a comparison is made between two prominent soft computing schemes namely Support Vector Machines and Artificial Neural Networks. Although a comparison can be made along various criteria, this study attempts to compare both techniques when applied to credit scoring in terms of accuracy, computational complexity and processing times. In order to assure meaningful comparisons, a real world dataset precisely the Australian Credit Scoring data set available online was used for this task. Experimental results obtained indicate that although both soft computing schemes are highly efficient, Artificial Neural Networks obtain slightly better results and in relatively shorter times.

Recent studies on social networks are based on a characteristic which includes assortative mixing, high clustering, short average path lengths, broad degree distributions and the existence of community structure. Here, a model has been developed in the domain of ‘formation of relationships’ which satisfies all the above characteristics, based on some existing social network models. In addition, this model facilitates interaction between various family groups. This model gives very high clustering coefficient by retaining the asymptotically scale-free degree distribution. Here the community structure is raised from a mixture of random attachment and implicit preferential attachment. In addition to earlier works which only considered Neighbor of Initial Contact (NIC) as implicit preferential contact, we have considered Neighbor of Neighbor of Initial Contact (NNIC) also. This model supports the occurrence of a contact between two initial contacts if the new vertex chooses more than one initial contacts. This ultimately will develop a complex social network rather than the one that was taken as basic reference.

Persuasive technology is a recent research field that combines the computing and human psychology aspects. The target is to develop persuasive systems that are able to change or reshape human behavior. Persuasive technology has quickly found a wide range of applications in many fields of research and development like marketing, health, safety and environment. Persuasive systems may also be used in other domains like religion, politics, diplomacy, military training, management, and education. Improving the persuasion process is a key element in the success of persuasive systems. The user experience is an important factor that should be included in the persuasion process. This paper reviews the current trends of persuasive technology and shows some example of the available persuasive systems. It then contributes by proposing a new and promising research direction for designing persuasive systems that take the user feedback as a main element in the persuasion process. Some of the systems that follow this approach have been proposed and illustrated.

The current trend of computer hardware declining and the speed of personal computer increasing had lead to opportunity of parallel programming. This paper presents the implementation of parallel Laplacian edge detection on cluster of four used personal computers. The algorithm was developed using C# language and had utilized the Message Passing Interface (MPI) library for parallel implementation. Comparison between sequential versus parallel implementation had been made based on sequential time taken for varies of images sizes. Results show significant time improvement as well as performance efficiency earned using parallel computing platform focusing on image processing Laplacian edge detection algorithm.

An important challenge in peer-to-peer (P2P) networks is locating the peers that can provide the answer for user query. To cope with this challenge, the proposed mechanisms have their own weaknesses to be a successful solution. In this paper, we propose a new query routing mechanism to improve the search performance in such networks. The mechanism consists of domain based architecture for grouping peers in the network into domains based on their contents. In each domain, interconnected groups of peers are constructed based on attributes analysis process. The mechanism provides the required methods for specifying the interaction between the peers in the same or different groups. A comparative analysis is performed to compare the proposed mechanism with two representative baseline routing approaches. To validate this analysis; an experimental study is conducted. The results show that the proposed mechanism achieves better performance with respect to the reduction of average number of messages, the average search path length, and response time.

Wireless Sensor Networks have many real world applications. Accordingly, researchers and entrepreneurs are looking for a reliable, real time, and energy-efficient network structures. Traditional techniques of flooding the network with information have proved inept in all of the latter criteria. Others have made specific assumptions of how the network is used and thus make intelligent choices on data dissemination. This paper proposes a non-data centric and thus highly adaptable information dissemination protocol called the Irrigation Algorithm to efficiently route packet to base stations. To evaluate its performance this algorithm is compared with the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol.

Data replication is one of the mechanisms in data grid architecture since it improves data access and reliability. Therefore, the storage, availability, and consistency are important issues to be addressed in order to allow distributed users efficiently and safely access data from many different sites. This paper propose a new algorithm namely Binary Vote Assignment on Grid Quorum (BVAGQ) in order to handle data replication and transaction management. We address how to build reliable system by using the proposed BVAGQ algorithm for distributed database fragmentation. The result show that managing replication and transaction through proposed BVAGQ able to prepare data consistency.

Data grid is a distributed computing architecture that integrates a large number of data and computing resources into a single virtual data management system. It coordinated the data from several of resources and enables the sharing of the data. In handling and managing data grid some of problems must be considered such as reliability and availability of the data to the user access, network latency, failures or malicious attacks during execution and etc. These problems can overcome by using replication technique. The data will replicate into several sites. If one of the sites has fail, it will fail independently and not affect to others node. The deadlock is the most important problem that must be manages when sharing any data in data grids. Furthermore, it can reduce the throughput by minimizing the available resources, so it becomes an important resource management problem in distributed systems. In this paper, we propose Neighbour Replication Grid Deadlock Detection (NRGDD) framework to detect the deadlock during transaction occur in Neighbour Replication on Grid replication model. Based on this framework it shows how the deadlock can be detected.

Historically, Enterprise Resource Planning (ERP) systems were initially destined to large companies in order to standardize and streamline their key business processes. Recently, they have been increasingly adopted by Small and Medium Enterprises (SMEs). However, making strategic tradeoffs among the various marketplace solutions is a troublesome balance task for SMEs without the rescue of systematic decision approaches. This paper addresses the question of how to choose an ERP solution that best suits a given SME. It serves twofold objectives; firstly it defines a set of selection criteria related to SMEs’ context. Secondly, it presents a selection methodology based on the construction of an induced decision model through capturing the decision maker’s preferences. The key contribution of this paper is the introduction of a new iterative learning based approach destined to make enlightened decisions through the consideration of interdependencies among the adopted selection criteria thanks to the Choquet integral.

To ensure the crucial integrity and confidentiality of patients’ information, this paper proposes a novel support vector machine (SVM) cum spread spectrum (SS) watermarking model to watermark medical images. In applying watermarking to secure medical images, there are generally three key stages, namely classifying the medical images into Region of Interest (ROI) and Region of Non-Interest (RONI), embedding the patients’ information and other relevant information into the image, and lastly extracting that information from the watermark images. The classifying and embedding stages require specific techniques tailored to their different requirements while the third is usually done using symmetric algorithms applied in the embedding stage. Among the soft computing techniques, SVM excels in classification including image classification and has a high potential to be used in the watermarking to improve its performance. However, based on current works reviewed in medical image watermarking, none has applied SVM yet. Similarly, SS is robust to the most common of signal processing and geometric distortions have been successfully applied in image watermarking. Therefore, in our novel model, SVM will be applied in the first stage while SS will be applied in the second and third stages. Significantly, the model aims to secure medical images to resist distortion as well as to avoid medical images quality degradation. The patient confidential data will be embedded into the RONI of their medical images using grayscale JPEG format using the SS symmetric algorithm. The watermark images will be evaluated on robustness and imperceptibility. Experiments will be conducted to measure the similarity ratio (SR) to test the robustness and Peak Signal to Noise Ratio (PSNR) to test the imperceptibility. The results show a high quality robust and imperceptible watermarking has been achieved with SR of more than 0.98 and PSNR of more than 40dB.

The purpose of this study is to better understand the current dynamics of the Malaysian market for mobile content and applications. This paper presents the result of a survey on the trend of smartphone from the perspective of end consumers. The data was collected from 1814 respondents across major cities in Malaysia. This study has looked into the familiarity of users towards smartphones, choices of smartphone brand and service providers, and most importantly the determinants that influence their purchasing decision. Additionally, the consumers’ preferences on smartphone specifications such as design, computing power, operating platform, and price are investigated. The statistics presented is to provide fundamental information regarding the status and trends in the smartphone market in Malaysia. Such information is useful for academics to the development of future works in the field, and for smartphone manufacturers, application developers and other stakeholders to plan their direction in the Malaysian smartphone market.

In the digital economy, every enterprise has the tendency of becoming an intelligent enterprise and, through the means of innovational information technology solutions, of gaining competition advantage on the market. At the same time, management and service-oriented technology and principles caught the attention of researchers with the purpose of finding new methods to increase the enterprise agility. At present there are some problems regarding the transition to service-oriented architecture and the management of service-oriented enterprise. The study analyses the impact of service-oriented architecture on enterprise and some aspects regarding agile architecture for the service-oriented enterprise as an important factor in the economic development of enterprises within the knowledge-based society.

In service-oriented architectures the management of services is a crucial task during all stages of IT operations. Based on a case study performed for a group of finance companies the different aspects of service management are presented. First, the paper discusses how services must be described for management purposes. In particular, a special emphasis is placed on the integration of legacy/non web services. Secondly, the service lifecycle that underlies service management is presented. Especially, the relation to SOA governance and an appropriate tool support by registry repositories is outlined.

Corporate wikis are increasingly being adopted by enterprises as a solution to various organizational processes. Subsequently a significant number of research works have started focusing on providing results on both successful and unsuccessful corporate wiki implementations. Nevertheless, the scope of these studies is usually limited on a specific organizational case or focuses on a limited set of aspects of the wiki adoption, e.g. either the technological or the cultural one. Our objective in this work is to provide an overview of the key factors affecting the successful implementation of an organizational wiki, by analyzing thirty case studies reported in the research literature. The result of this analysis is the identification of a core set of common best practices to be taken into account by stakeholders when planning the integration of a wiki within a corporate context. In this way, the study aims at contributing to the planning and the realization of more successful corporate wiki implementations with enterprise environments.

Internet phenomena like Facebook or Twitter hold great potential for companies. The 21st century’s social networks are platforms for the (semi) public exchange of information. For an organisation, taking an active part in these conversations means gaining more trust, co-shaping its own image and obtaining knowledge from user-generated content. User-generated content can help optimise processes and act as a testimonial for the organisation’s services and products. This paper offers a conceptional process model facilitating external knowledge management within organisational communication measures in Social Media.

There have been few investigations into the amount of relevant information that can be recovered from the physical memory of Windows applications. Extraction of user information is vital in today’s digital investigation and forensic investigators find it helpful to gain access to dispersal evidence stored over time in the physical memory of these applications. In this research, we present the quantitative and qualitative results of experiments carried out on the extraction of forensically relevant information from Windows computer systems. This process involves a pattern matching techniques of the original user input and the extracted memory dump strings processes. In conducting this research; we have identified the most commonly used applications on Windows systems, designed a methodology to capture data and processed that data. This research will report the amount of evidence dispersed over time in the physical memory when the application was running and user is not interacting with the system.

XML query processing based on labeling schemes has been proposed in the past several years. Based on labeling schemes, the structural relationships between XML nodes can be directly determined without the need of accessing the XML document. However, the existing labeling schemes have to re-label the pre-existing XML nodes or re-calculate the label values when a new node is inserted into the XML tree during an updating process. EXEL as a bit string based encoding and labeling scheme is able to remove the process of re-labeling for the pre-existing XML nodes efficiently. However, EXEL is unable to reuse the deleted labels for future node insertions. Also, another problem of EXEL is in the frequent skewed insertions where nodes always are inserted at a fixed place of an XML tree. In this case, the label size increases significantly. In this paper, we propose an algorithm to reuse the deleted labels for future node insertions and propose a strategy to solve the problem of frequent skewed insertion. The experimental results show that the proposed algorithm can reuse all the deleted labels for future insertions. Also, the proposed strategy can reduce the increment of label size in the case of frequent skewed insertions efficiently.

This article proposes to include an in-air signature biometric technique in mobile e-commerce applications in order to increase the security of passwords and authenticate users directly from their mobile phones. Five architectures have been proposed to implement this technique as a complement of current authentication methods. Moreover, the opinion of end users has been considered assessed by a survey of 24 people. From the results of this survey it has been deducted that this authentication method seems useful, necessary and comfortable to complement the password authentication methods and increase the global security of e-commerce applications.

Virtual heritage is a computer-based interactive technology that provides formative stages of the educational experience of cultural heritage such as virtual tour of museums. With the fast growing technological advancement in mobile phone technology, it has become possible to create a virtual heritage application for edutainment for general public on mobile platform. In this paper, we present a virtual heritage application called M-Heritage Hunt that provides a technology-integrated environment that allows users to gain knowledge of heritage on mobile platform through panoramic views of the heritage sites and a game that combines the traditional games of Monopoly and Treasure Hunt. Based on the comparison and preliminary evaluation, the system has been found to be interesting, attractive and successful in delivering the heritage contents.

Nowadays, with rapid advancement of technology, people can roam around the virtual world through the aid of the Internet. One of these advances is a photographic technique called panoramic view where images are captured with elongated field of view using specialized software or equipments. However, the computational cost of generating a panoramic view is high. One of the popular software for generating panoramic views is Apple Inc.’s QuickTime VR (QTVR). Nevertheless, iPhone Operating System (iOS) does not support the existing QTVR software. Therefore, in this paper, a low-cost method for generating panoramic views on mobile platform is proposed by storing finite images in an array in order to generate a 360o panoramic view. This method can be supported by all kinds of platform and therefore can be installed in any mobile devices without having to use any intermediate software to convert the format of the images. The outcome is a cylindrical panoramic view that allows the user to gain a 360o clear vision around historical monuments in a mobile virtual heritage exploration using lower computational cost but with similar quality of production.

In this paper we present a formal definition of the basic concepts and notations of Object Role Modeling (ORM) using the Z formal specification language. Most of ORM concepts such as object and relationship types, value types, objectification, reference schemes, sub-types, roles and constraints such as uniqueness, mandatory, cardinality, subset, equality, exclusive and ring constraints are specified formally. Population is specified as objects, relationships and roles instances. These are specified using Z axioms and diagram instances are specified using Z schemas. This would enable validation and reasoning on the formal properties of ORM diagrams such as detecting constraint contradictions and implications. All the specifications are validated and type-checked using Z/EVES.

In this study, considering different perspectives and concepts about customer relationship management (CRM), we try to investigate the significance of the correlation between each of the customer retention programs of CRM (loyalty programs, customer service, customization, and community) and customer retention. Data from 286 top bank managers of two governmental and two private Iranian bank branches were gathered in a field survey. The results of data analysis show the positive and significant correlation between each of the customer retention programs of CRM and customer retention. The study also finds the most significant correlation between customer service and customer retention.

This article describes the theoretical foundations and key elements of the dynamic geometry approach – an approach to high school geometry that utilizes dynamic geometry software and supporting instructional materials to help students construct mathematical ideas through active explorations and investigations. Due to its benefits to students’ learning, this instructional approach should be implemented in as many classrooms as possible. The focus of the article is hence on how this approach will be operationalized in the classrooms.

This paper describes a new method for automatic classification of scientific literature archived in digital libraries and repositories according to a standard library classification scheme. The method is based on identifying all the references cited in the document to be classified and, using the subject classification metadata of extracted references as catalogued in existing conventional libraries, inferring the most probable class for the document itself with the help of a weighting mechanism. We have demonstrated the application of the proposed method and assessed its performance by developing a prototype software system for automatic classification of scientific documents according to the Dewey Decimal Classification (DDC) scheme. A dataset of one thousand research articles, papers, and reports from a well-known scientific digital library, CiteSeer, were used to evaluate the classification performance of the system. Detailed results of this experiment are presented and discussed.

In this paper we introduce two e-learning systems, namely eLogika and (LMS) ORGANON. Both systems are apt for teaching logic and should improve the quality of the teaching. The ORGANON system is primarily aimed at solving tasks and practicing logical formalisms by means of interactive exercises. The eLogika system is intended to support effective automated testing of students’ knowledge together with automatic generation of suitable exam tests. We also describe the application of data-mining methods which can contribute to the improvement of e-learning systems by adjusting particular tests in accordance with students’ capabilities and needs.

The impact of packet reordering on the performance of TCP flavours is presented in this paper by analyzing four TCP flavours that are TCP-Reno, TCP-Newreo, TCP-SACK, and TCP-Linux. Thus, to do so an experiment is conducted based on simulation environment using Network simulator NS-2 version 2.33. The simulation results show that sending rate is decreased as a result of packet reordering phenomena; however, TCP-Linux performs better than other TCP flavours when there is more than one flow due to the large initial value of TCP-Linux slow-start threshold (ssthresh). These results demonstrate that packet reordering negatively affect the performance of TCP flavours. The finding of this paper can be summarized in that packet reordering may have a catastrophic effect on the performance of the TCP flavours, and the expected throughput from using these TCP flavours might not be achieved.

Business Intelligence (BI) refers to skills, processes, technologies, applications and practices used to support decision making. BI technologies provide historical, current, and predictive views of business operations which are normally used to analyze business data. Online Analytical Processing (OLAP) is one of the common BI approaches in quickly answering multidimensional analytical queries for analytical purpose. In this paper, we have proposed OLAP technique to be implemented in Academic area. Through this technique, UniSZA students’ academic pattern behaviors can be analyzed. A set of data from students’ examination results in relational DB is extracted into multi-dimensional model to support OLAP query processing. The results are grouped into several subject areas. Then, the analysis to recognize students’ academic pattern behaviors is conducted. From the analysis, the groups of students who have the excellent skills or vice versa can be identified. It also optimizes the time dimension to perform current and historical data analysis. The weaknesses and strengths of the student can also be obtained. Finally, students’ future potential areas can be predicted for the next level of educations.

The developments in computer networks in recent days such as the internet have increased rapidly. Connections of these networks necessitate resources in order to send their data to their prospective destinations. Further, the connections require high speed router buffers which they route data in high speed. Congestion is one of the main issues that occur at the router buffer cause deterioration of the network performance, i.e. increasing average waiting time, decreasing throughput, etc. Gentle Random Early Detection (GRED) is one of the known congestion control algorithms proposed to detect congestion before the router buffer overflows. In fact, GRED improves the setting of the parameters for the maximum threshold position (max

threshold

) at the router buffer and the maximum value for the packet dropping probability (

D

max

). This paper proposes an Adaptive GRED algorithm that detects congestion at router buffers in an preliminary stage, and enhances the parameters setting of the max

threshold

and the

D

max

. During congestion, the simulation results reveal that the Adaptive GRED drops fewer packets than GRED, and it marginally offers better performance results than that of GRED.

Supplier selection is a multi-criteria decision making problem which includes both qualitative and quantitative factors. In order to select the best suppliers it is necessary to make a trade-off between these tangible and intangible factors some of which may conflict. Buyer should decide about two problems: which suppliers are the best and how much should be purchased from each selected supplier. The majority of previous supplier selection techniques do not consider strategic perspective. Besides, uncertainty is one of the most important obstacles in supplier selection. For the first time, in this paper, the idea of the algorithm ”Knapsack” is used to select suppliers. Moreover, an attempt has to be made to take the advantage of a simple numerical method for solving model. This is an innovation to resolve any ambiguity in choosing suppliers. This model has been tried in the suppliers selected in a competitive environment and according to all desired standards of quality and quantity. To show the efficiency of the model, an industry sample has been uses.

This study presents an approach for determining optimal locations of oil wells in an oil field such that a predetermined production policy can be achieved. In the first step, Dynamic Fuzzy Neural Network (DFNN) is employed to generate an analytical and dynamic model of the reservoir. The model would be updated during the process due to current reservoir information. In order to determine optimal weights for DFNN, Orthogonal Least Square method is modified and applied. It will be shown that the method has more computational efficiency in comparison with other approaches. In the second stage, gradient-based approaches as one of the most common methods in control field are employed to determine well locations based on the generated model. The method can perform search without being obliged to use the simulator several times. Finally, simulation results show the abilities of the proposed procedure in both modeling and tracking control.

The electricity distribution regulation and efficiency benchmarking practice in Finland has drawn attention because of its controversial regulatory scheme and arguably efficient electricity distribution sector. This study uses a computational intelligence tool, i.e., Self-Organizing Map (SOM), in the context of electricity distribution efficiency performance visualization. A SOMmodel has been built based on collected data for 2001-2004. It allows the reader to discriminate between the Finnish DSOs’ differing operating circumstances. Through clustering and visualization, an overall perspective of the efficiency performance of the DSOs in 2001-2004 is rendered. In addition, such a visualization approach connects the DSO’s efficiency performance to its respective operating characteristics, which is otherwise not straightforwardly indicated by only studying efficiency scores. This application provides evidence that visual data mining with the SOM as a complementary approach in electricity distribution regulation and efficiency benchmarking has the potential to be expended to other regulatory practices (e.g., yardstick regulation).

Although many researchers have studied different factors which affect E-Learning performance, there is little research on assessment of the intervening role of infrastructures in E-Learning performance. This study proposes a conceptual model to determine the role of infrastructures in the relationship between E-Learning factors and performance. A questionnaire was completed by 96 respondents. This sample consists of teachers at Tehran high schools who are utilizing a technology-based educating method. Hierarchical regression analysis is done and its results strongly support the appropriateness of the proposed model and prove that infrastructure plays a moderating role in the relationship between E-Learning factors and performance. Also latent moderated structuring (LMS) technique and MPLUS3 software are used to determine each variable’s ranking. Results show that organizational infrastructure has the most important effect on E-Learning performance and teacher is the most important factor in E-Learning.

The existing theories in the technology acceptance and Internet adoption fields could be classified to technological and behavioral approaches. In this paper, we propose an integrated household Internet adoption model combining both perspectives, so as the three primal models of technology acceptance model (TAM), theory of planned behavior (TPB) and uses and gratifications theory (U&G) are selected to construct the integrated model. The relations between the proposed model’s constructs are then hypothesized based on the literature findings, and examined in a case study of Internet adoption among Iranian household users.

In this paper, we present an engineered sorting algorithm, named NQQuicksort, which is efficient and non quadratic. To avoid the quadratic worst case, and degenerate partitioning performance, NQQuicksort adopts two pivot computations only. The first is the same as the pivot computation in median of three quicksort and the second is similar to that in binary quicksort (radix exchange). The pivot computations applied are quite different and non-related, such that when one pivot computation fails, it gives no indication to whether the second pivot computation step will, or will not succeed (fail). When the first pivot selected results in unbalanced partitioning, the second pivot computation is immediately applied in the next recursive call. NQQuickSort is faster than the tuned quicksort implementation of the Java class library engineered by Bentley and McIlroy [3]. The algorithm and its runtime behavior are discussed in detail. The performance of NQQuicksort is faster than quicksort as well as the fastest variant of radix sorting algorithms; the Least Significant Digit (LSD) radix sort [15].

Currently, metadata are being democratized and used for various purposes. We present a novel metadata-based mechanism to help making weak links between digital identity documents based on distance score that is generated by a distance function and performance. We identify two parameters of the distance function: elapsed time t and a random vector, which is defined by joint probability density for forgetting between two documents. The more the distance score is high the more the link established between parent and child document becomes weaker, therefore the child document becomes less visible. This would provide user more control over his identity and promote forgiveness in the digital age. We provided also an XRD implementation of the parent and child DigIdMeta documents.

Cloud Security is one of the biggest challenges that currently this technology is facing. Based on cryptography and keys used to protect information, this paper proposes the integration of key management model in the cloud KMIP with the cryptographic standard protocol PKCS11, responding to the problem of key management, no doubt, one of the main problems to solve when a model of this nature is thought in the cloud. The inclusion of cryptographic hardware reinforces this proposal, which is based in interoperable models that are compatible with high level of security devices like Hardware Security Modules.

With the growth of World Wide Web and increasing human demand on trading, e-commerce becomes an inseparable part of business. In the past decade a huge number of researches have been done in order to develop optimal negotiation agent systems in e-commerce. However, existing models are weak in supporting real world e-market conditions since most of them assume static conditions for environment and complete information about opponent agent’s preferences. As a result, this work proposes an adaptive one-to-many negotiation model called Aspiration negotiation model. This model is proposed in order to assist agents to adapt to the dynamicity of opponent agent’s preferences and environmental conditions. Proposed model is employed in order to optimize the negotiation outcome in terms of utility gained by agents. Experimental studies have been done to evaluate the performance of proposed model. Finally Aspiration model was able to outperform previous models in terms of seller, buyer and joint utility value.

This paper proposes a new method for syntheses DC–DC converters by using Main Topological Matrix MTM. The properties of MTM are described. The common properties for single-switch DC-DC converters are also given. The proposed method has a lot of advantages as opposed to other methods. This method is fully algorithmic and takes into account the design by pats. It is also shown by examples how this method is used for generating all sub-class (sub-family) of DC-DC converters with predetermined characteristics.

Business/IT alignment means the degree to which the information technology mission, objectives, and plans are supported by the business mission, objectives, and plans. The aim of this research is the maturity assessment of Business/IT alignment by an intelligent system. Here, a Fuzzy Expert System has been designed in which main effective variables on Business and IT alignment have been considered as Inputs and level of maturity as output. Then, system rules have been extracted by the IT experts and the system has been developed with the use of FIS tool of MATLAB software. Finally, the presented steps have been run in an Iranian Bank as empirical study.

Rigid and strictly defined business models do not support changes required to meet today’s competitive business needs and demands. The business model must be adaptable and should have the agility needed to remain in such an environment. This implies that systems on which companies rely must therefore also be flexible and agile. However, in the case of Online Airline Reservation Systems (OARS), flexibility is undeterminable without accounting for traveler’s flexible travelling behavior. In this paper we investigate and explore the concept of users’ perception on factors influencing flexible traveling behavior and flexible OARS. A qualitative approach using grounded theory was conducted. Our findings show that users travelling behavior is molded by a number of important personality relevant determinants, both internal and external in characteristics. We conclude that flexibility of users and system are independent but still very much dependent on one another.