Many software reliability growth models (SRGMs) have been analyzed for measuring the growth of software reliability. Selection of optimal SRGMs for use in a particular case has been an area of interest for researchers in the field of software reliability. All existing methodologies use same weight for each comparison criterion. But in reality, it is the fact that all the parameters do not have the same priority in reliability measurement. Keeping this point in mind, in this paper, a computational methodology based on weighted criteria is presented to the problem of performance analysis of various non-homogenous Poisson process (NHPP) models. It is relatively simple and requires less calculation. A set of twelve comparison criteria has been formulated and each criterion has been assigned different weight to rank the software reliability growth models proposed during the past 30 years. Case study results show that the weighted criteria value method offers a very promising technique in software reliability growth models comparison.

In this work we present an approach and a tool for transforming business patterns to labelled Petri nets. This transformation is justified by the fact that Petri nets have efficient analysis techniques. We specify first, business patterns and labelled Petri nets Meta-Models in UML Class Diagram formalism with the Meta-Modelling tool Atom3, and then we generate visual modelling tools according to the proposed Meta-Models. Finally, we define a graph grammar which transforms Business Patterns models to Labelled Petri Nets model for analysis purposes. The approach is illustrated with examples.

Organizational decisions involve with unusually vague and conflicting criteria. This controversy increases empirical uncertainties, disputes, and the resulting consequences of these decisions. One possible method in subduing this problem is to apply quantitative approaches to provide a transparent process for resolute conclusions which enables decision makers to formulate accurate and decisive on time decisions. Although numerous methods are presented in the literature, the majority of them aim to develop theoretical models. However, this article aims to develop and implement an integrated fuzzy virtual MCDM model based on fuzzy AHP and fuzzy TOPSIS as a decision support system (DDS). Preventing disadvantageous face-to-face decision-making by achieving positive benefit from virtual decision making causes the proposed DDS to be suitable for making crucial decisions such as supplier selection, employee selection, employee appraisal, R&D project selection, etc. The proposed DDS has been implemented in an optical company in Iran.

Processing of meteorological satellite image data provides a wealth of information useful in earth surface and environmental applications. Particularly, it is important for the estimation of different parameters of surface energy budget. In this work, a method has been developed to estimation of hourly incoming solar radiation on the surface of Bangladesh using NOAA-AVHRR satellite digital images. The model is based on the statistical regressions between the ground truth and satellite estimated values. Hundreds of full resolution images (1.1 km) for two months of the year have been processed using ERDAS IMAGINE software. Ground solar global irradiation for one place has been estimated for two months through this application. The efficiency of this method for calculating surface insolation has been checked by estimating the relative deviation between the estimated Irradiation and measured Irradiation. The method can be used for calculation of hourly irradiation over areas in a tropical environment.

Electronic Commerce (E-Commerce) has a growing potential in Saudi Arabia, due to widespread use of the internet and the maturity of the Information Technology (IT) infrastructure. The purpose of this paper is to assess the quality of E-Commerce websites in Saudi Arabia, using a proposed evaluation instrument. To achieve this aim, six E-Commerce websites were selected for evaluation and then categorized into three categories: domestic, regional and international. Each category consisted of two E-Commerce websites, with the international website category considered as a benchmark. The six websites were evaluated by sixty participants (n=60) with good web design experience, following a set of guidelines offered by the evaluation instrument. The evaluation instrument described six key evaluation factors: appearance, content, organization, interaction, customer-focus and assurance. Each factor was evaluated by several indicators using a five-point scale ranging from not applicable (0) to very strong (4). To unify the views of all evaluators, a technique was introduced which would show the way in which each indicator was assessed based on several checklists (questions). The results therein revealed that international websites were of higher quality than regional and domestic websites with regard to all aspects of web evaluation. In addition, the quality of regional websites outweighed that of domestic websites with regard to appearance, content, organization, customer-focus and assurance, but not interaction.

Classification of regional territories and countries related to endangered species has been investigated by data mining techniques and graphical modeling using an extensive data set of species. We developed the graphical models (hereafter referred to as ‘ESDI’) using cosine, jaccard similarity, K Mean clustering and cliques in graph modeling for a large number of countries. Environmental variables associated with species records were identified in context of their diversification to integration with our proposed prototype. We have shown that the problem of finding the most coherent clusters is reducible to finding maximum clique. Key findings include the urge to ameliorate communication about the loss and protection of endangered species and their concerned projects. The proposed framework is presented to serves a portal to knowledge discovery. We have concluded that the proposed framework model and its associated data mining similarity measures can be useful for investigating various scientific and management oriented questions related to protection of endangered species with emphasis on collaboration among regional countries. The rationale behind the proposed approach is that the countries which have been grouped into same clique inherit a lot of argues illustrating common reasons of their struggles towards ecological safety with minimization of perils for endangered species. The development and implementation of a regional approach based on this similar grouping address the actions that could offer significant benefits in achieving their goal for ecological policies. Other critical actions at this clique level include fortifying and elevating harmonization of legal frameworks with emphasis on prevention procedural issues; awareness realizations of endangered species issues and its priority. Such actions will eventually lead towards implementation of essential plans fulfilling co-operative expertise and common endeavors.

Wireless and Mobile Network Infrastructure services generally examine how different infrastructure providers are positioning themselves to compete in wireless services. These services analyze the opportunities and challenges facing by the infrastructure providers selling to wireless and mobile network operators worldwide. The opportunities and challenges are the review of strategies, market positioning, and future direction in the market for wireless and mobile network infrastructure. The service covers all generations of wireless and mobile network infrastructure: 2G, 2.5G, 3G, and 4G so on global in scope. Majority of the users are mobile while availing these services. Mobility is the most important feature of any wireless and mobile network. Usually, continuous service is achieved by supporting handoff from one cell to another. Poorly designed handoff schemes tend to generate very heavy signaling traffic and, thereby, lead to a dramatic decrease in quality of service. In this paper we make a comparison study on some selective traffic models with priority handoff scheme. The study shows how a handoff procedure has a significant impact on wireless mobile network performance on the basis of two primary criteria – Blocking probability of originating calls and the forced termination probability of ongoing calls. In addition to this the study shows arrival rate of handoff calls, and approximate number of mobile users that get serviced by underlying base station.

Digital watermarking can be used as an important tool for the security and copyright protection of digital multimedia content. The present paper explores its applications as a quality indicator of a watermarked medical image when subjected to intentional (noise, cropping, alteration) or unintentional (compression, transmission or filtering) operations. The watermark also carries EPR data along with a binary mark (used for quality assessment). The binary mark is used as a No-Reference (NR) quality metrics that blindly estimates the quality of an image without the need of original image. It is a semi-fragile watermark which degrades at around the same rate as the original image and thus gives an indication of the quality degradation of the host image at the receiving end. In the proposed method, the original image is divided into two parts- ROI and non-ROI. ROI is an area that contains diagnostically important information and must be processed without any distortion. The binary mark and EPR are embedded into the DCT domain of Non-ROI. Embedding EPR within a medical image reduces storage and transmission overheads and no additional file has to be sent along with an image. The watermark (binary mark and EPR) is extracted from non-ROI part at the receiving end and a measure of degradation of binary mark is used to estimate the quality of the original image. The performance of the proposed method is evaluated by calculating MSE and PSNR of original and extracted mark.

Multistate operations within a network result in high-dimensional, multivariate temporal data, and are useful for systems, which monitor access to network entities like resources, objects, etc. Efficient self organization of such multistate network operations stored in databases with respect to relationships amongst users or between a user and a data object is an important and a challenging problem. In this work, a layer is proposed where discovered relationship patterns amongst users are classified as clusters. This information along with attributes of involved users is used to monitor and extract existing and growing relationships. The correlation is used to help generate alerts in advance due to internal user-object interactions or collaboration of internal as well as external entities. Using an experimental setup, the evolving relationships are monitored, and clustered in the database.

Biometric systems are alternates to the traditional identification systems. This paper provides an overview of single feature and multiple features based biometric systems, including the performance of physiological characteristics (such as fingerprint, hand geometry, head recognition, iris, retina, face recognition, DNA recognition, palm prints, heartbeat, finger veins, palates etc) and behavioral characteristics (such as body language, facial expression, signature verification, speech recognition, Gait Signature etc.).
The fingerprints, iris image, and DNA features based multimodal systems and their performances are analyzed in terms of security, reliability, accuracy, and long-term stability. The strengths and weaknesses of various multiple features based biometric approaches published so far are analyzed. The directions of future research work for robust personal identification is outlined.