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Nathoo F.S.,University of Victoria | Ghosh P.,Information Systems Management Institute
Statistics in Medicine | Year: 2013

Mixed models incorporating spatially correlated random effects are often used for the analysis of areal data. In this setting, spatial smoothing is introduced at the second stage of a hierarchical framework, and this smoothing is often based on a latent Gaussian Markov random field. The Markov random field provides a computationally convenient framework for modeling spatial dependence; however, the Gaussian assumption underlying commonly used models can be overly restrictive in some applications. This can be a problem in the presence of outliers or discontinuities in the underlying spatial surface, and in such settings, models based on non-Gaussian spatial random effects are useful. Motivated by a study examining geographic variation in the treatment of acute coronary syndrome, we develop a robust model for smoothing small-area health service utilization rates. The model incorporates non-Gaussian spatial random effects, and we develop a formulation for skew-elliptical areal spatial models. We generalize the Gaussian conditional autoregressive model to the non-Gaussian case, allowing for asymmetric skew-elliptical marginal distributions having flexible tail behavior. The resulting new models are flexible, computationally manageable, and can be implemented in the standard Bayesian software WinBUGS. We demonstrate performance of the proposed methods and comparisons with other commonly used Gaussian and non-Gaussian spatial prior formulations through simulation and analysis in our motivating application, mapping rates of revascularization for patients diagnosed with acute coronary syndrome in Quebec, Canada. © 2012 John Wiley & Sons, Ltd.


Terrovitis M.,Information Systems Management Institute | Mamoulis N.,University of Hong Kong | Kalnis P.,King Abdullah University of Science and Technology
VLDB Journal | Year: 2011

In this paper, we study the problem of protecting privacy in the publication of set-valued data. Consider a collection of supermarket transactions that contains detailed information about items bought together by individuals. Even after removing all personal characteristics of the buyer, which can serve as links to his identity, the publication of such data is still subject to privacy attacks from adversaries who have partial knowledge about the set. Unlike most previous works, we do not distinguish data as sensitive and non-sensitive, but we consider them both as potential quasi-identifiers and potential sensitive data, depending on the knowledge of the adversary. We define a new version of the k-anonymity guarantee, the k m-anonymity, to limit the effects of the data dimensionality, and we propose efficient algorithms to transform the database. Our anonymization model relies on generalization instead of suppression, which is the most common practice in related works on such data. We develop an algorithm that finds the optimal solution, however, at a high cost that makes it inapplicable for large, realistic problems. Then, we propose a greedy heuristic, which performs generalizations in an Apriori, level-wise fashion. The heuristic scales much better and in most of the cases finds a solution close to the optimal. Finally, we investigate the application of techniques that partition the database and perform anonymization locally, aiming at the reduction of the memory consumption and further scalability. A thorough experimental evaluation with real datasets shows that a vertical partitioning approach achieves excellent results in practice. © 2010 Springer-Verlag.


Srivastava P.R.,Information Systems Management Institute
International Journal of Bio-Inspired Computation | Year: 2016

Software testing is prime concern for the software industry and researchers. In the software testing process test cases play an important and significant role. Optimisations of test cases are essential to test the software effectively. Finding maximum number of faults and rectifying them before actual software release is most complex and critical during software development process. This paper deals with software test case optimisation using bacteriologic algorithm (BA) and requirement mapping-based approach. Test case optimisation deals with selecting effective test cases having maximum code coverage and fault detection capability, consequently minimising and prioritising the test cases. Copyright © 2016 Inderscience Enterprises Ltd.


Panigrahi P.K.,Information Systems Management Institute
Proceedings - 4th International Conference on Computational Intelligence and Communication Networks, CICN 2012 | Year: 2012

Unsolicited e-mail (Spam) has become a major issue for each e-mail user. In recent days it is very difficult to filter spam emails as these emails are written or generated in a very special way so that anti-spam filters cannot detect such emails. This Paper compares and discusses performance measures of certain categories of supervised machine learning techniques such as Bayes algorithms, lazy algorithms, tree algorithms, neural network, and support vector machines for classifying a spam e-mail corpus maintained by UCI Machine Learning Repository. The objective of this study is to consider the content of the emails, learn a finite dataset available and to develop a classification model that will able to predict whether an e-mail is spam or not. © 2012 IEEE.


Thakurta R.,Information Systems Management Institute
Software Quality Journal | Year: 2013

Non-functional requirements (NFRs) determine the characteristics of a software product or service as a whole. The research described in this paper presents a quantitative framework involving respondents of both the project and the business organization, in order to determine the priority of a list of NFRs to be considered for implementation during a software development. The framework also provides a quantitative basis for evaluating the extent of value addition that can be achieved while deciding upon whether or not to consider a particular non-functional requirement for inclusion to the project's requirement set. The assessment process also indicates the extent to which different business values are perceived important by representatives of business organizations, and their perception of the importance of the different NFRs. The work distinguishes from others by explicitly considering dependencies among NFRs in the evaluation process. The final results are expected to be beneficial to both the business and the project organization by identifying and implementing the desired NFRs that contribute to business value in a cost-effective manner. © 2012 Springer Science+Business Media New York.


Biradar R.C.,Information Systems Management Institute | Manvi S.S.,Information Systems Management Institute
Journal of Network and Computer Applications | Year: 2012

Frequent interactions among the group members of distributed wireless network environment may be facilitated with the help of Mobile Ad Hoc NETworks (MANETs). Some of the group-oriented applications include disaster management, battlefields, audio/video conferencing, e-commerce, e-education, etc. Group communication demands dynamic construction of efficient and reliable multicast routes under user mobility and varying channel conditions. Multicast routing mechanisms in MANETs have been consistently improved by researchers considering various performance measures such as energy efficient route establishment, packet delivery ratio, quicker and faster proactive route recovery, network life time, reliability, Quality of Service (QoS) based on bandwidth, delays, jitters, and security. The paper focuses on most recent reliable and QoS based multicast routing mechanisms that helps in multimedia communication over MANETs. The mechanisms are considered under different topological routing categories such as mesh, tree, zone and hybrid. We provide an overview of existing multicast routing mechanisms based on routing categories and point to directions for future research and development. © 2011 Published by Elsevier Ltd. All rights reserved.


Biradar R.C.,Information Systems Management Institute | Manvi S.S.,Information Systems Management Institute
Journal of Network and Computer Applications | Year: 2012

The limited battery power, unpredictable mobility and large variation of received signal strength in nodes of Mobile Ad Hoc Networks (MANETs) create link and node vulnerability and instability. Multicast routing in MANETs for group communication requires the establishment of reliable links between neighboring nodes called as reliability pair beginning from the source and extending such reliability pairs enroute to the destination. We propose a scheme for Multipath Multicast Routing in MANETs using reliable Neighbor Selection (MMRNS) mechanism. A mesh of multipath routes are established from source to multicast destinations using neighbors that have high reliability pair factor. MMRNS operates in the following phases. (1) Computation of reliability pair factor based on node power level, received differential signal strength between the nodes and mobility. (2) Pruning neighbor nodes that have reliability pair factor smaller than a threshold. (3) Discovery of multipath multicast mesh routes with the help of request and reply packets. (4) Multipath priority assignment based on minimum value of reliability pair factor of a path and information transfer from source to the multicast destinations and (5) route maintenance against link/node failures. The scheme is simulated to evaluate the performance parameters like packet delivery ratio, memory overhead, message overhead, control overhead and packet delays in comparison to the mesh based multicast routing protocols such as On-demand Multicast Routing Protocol (ODMRP) and Enhanced ODMRP (EODMRP). MMRNS performs better than ODMRP and EODMRP as observed from the simulation results. © 2011 Elsevier Ltd. All rights reserved.


Wittstruck D.,Information Systems Management Institute | Teuteberg F.,Information Systems Management Institute
Corporate Social Responsibility and Environmental Management | Year: 2012

Recent studies have reported that organizations are often unable to identify the key success factors of Sustainable Supply Chain Management (SSCM) and to understand their implications for management practice. For this reason, the implementation of SSCM often does not result in noticeable benefits. So far, research has failed to offer any explanations for this discrepancy. In view of this fact, our study aims at identifying and analyzing the factors that underlie successful SSCM. Success factors are identified by means of a systematic literature review and are then integrated into an explanatory model. Consequently, the proposed success factor model is tested on the basis of an empirical study focusing on recycling networks of the electrics and electronics industry. We found that signaling, information provision and the adoption of standards are crucial preconditions for strategy commitment, mutual learning, the establishment of ecological cycles and hence for the overall success of SSCM. © 2011 John Wiley & Sons, Ltd and ERP Environment.


Krishnan S.,Information Systems Management Institute
Computers in Human Behavior | Year: 2016

Cyber incivility is defined as communicative behavior exhibited in computer mediated interactions that violate workplace norms of mutual respect. This study examines the impact of personality traits on cyber incivility via work email. Specifically, by drawing on the abridged big-five dimensional circumplex (AB5C) model of personality and the extant literature on cyber incivility, this study proposes a personality model of cyber incivility and posits that the personality traits of extraversion and emotional stability can be linked to cyber incivility more closely when each of them is accompanied by the personality trait of conscientiousness than when without it. We test our model by conducting a two-phased online survey of 265 full-time employees in the country of India. Results indicate that the relationships of extraversion and emotional stability with cyber incivility are negatively moderated by conscientiousness. Our findings contribute to the knowledge base of both personality and cyber incivility by understanding their linkages. © 2016 Elsevier Ltd


Karagiorgou S.,Information Systems Management Institute | Pfoser D.,Information Systems Management Institute
GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems | Year: 2012

Road networks are important datasets for an increasing number of applications. However, the creation and maintenance of such datasets pose interesting research challenges. This work proposes an automatic road network generation algorithm that takes vehicle tracking data in the form of trajectories as input and produces a road network graph. This effort addresses the challenges of evolving map data sets, specifically by focusing on (i) automatic map-attribute generation (weights), (ii) automatic road network generation, and (iii) by providing a quality assessment. An experimental study assesses the quality of the algorithms by generating a part of the road network of Athens, Greece, using trajectories derived from GPS tracking a school bus fleet. © 2012 ACM.

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