SPSM and SPC for Software Process and Project Management

Software process simulation modeling (SPSM) provides a platform for process and project management. On the other hand, statistical process control (SPC) provides the means to assess a process for stability and capability through visualization. This paper provides a framework for integrating SPSM and SPC. The framework realizes their synergy by leveraging the investment in supporting software measurement processes, ensuring the stability of the underlying development process, and enhancing simulation output using visualization techniques made possible through SPC. The paper illustrates the framework by integrating SPC to an existing SPSM. The integrated model is then used to evaluate the underlying process with respect to capability

Decision Support for Software Projects: The Role of SPC and Simulation Metamodeling

While many researchers have attempted to directly apply statistical process control (SPC) to the software domain, several difficulties in applying SPC to software development, in particular, the inability to compute meaningful control limits for the process. In this research, we propose a framework for applying SPC to software projects. The framework integrates SPC concepts and simulation metamodeling to create meaningful control limits on process and project inputs. The framework is demonstrated using a case study

Application of fuzzy logic to multiple criteria decision making in aquacultural planning

The field of regional planning is characterized by the large number of issues and attributes involved, and regional planning for aquaculture development is no exception. Moreover, aquacultural plans do not have clearly defined objectives and require information that, if exist, is often imprecise and uncertain.This paper applies fuzzy set theory to multiple criteria decision making (MCDM) in aquaculture planning. In effect, the paper demonstrates how fuzzy set theory can be used to explicitly account for the inherent uncertainty encountered when planning for aquaculture development in a given region. A case study for regional aquaculture planning in Northern Egypt demonstrates the proposed fuzzy MCDM framework

The use of information technology in aquaculture management

The recent advances in information technology (IT) have had profound impacts on all walks of life and aquaculture is no exception. The growing importance of aquaculture as an alternative source of protein has further emphasized the need to adapt and develop advanced IT for the better management of aquaculture facilities as well as the regional planning for aquaculture development. It is the objective of this paper to review the use and potential prospects of IT in aquaculture management. The information technologies considered are instrumentation and process control, data management, computerized models, decision support systems, artificial intelligence and expert systems, image processing and pattern recognition, geographical information systems, and information centres and networks. The review includes a brief introduction of each of the aforementioned technologies, followed by a survey of their current application as well as their potential use in aquaculture management. Abstract The recent advances in information technology (IT) have had profound impacts on all walks of life and aquaculture is no exception. The growing importance of aquaculture as an alternative source of protein has further emphasized the need to adapt and develop advanced IT for the better management of aquaculture facilities as well as the regional planning for aquaculture development. It is the objective of this paper to review the use and potential prospects of IT in aquaculture management. The information technologies considered are instrumentation and process control, data management, computerized models, decision support systems, artificial intelligence and expert systems, image processing and pattern recognition, geographical information systems, and information centres and networks. The review includes a brief introduction of each of the aforementioned technologies, followed by a survey of their current application as well as their potential use in aquaculture management

Aquaculture in Egypt and Issues for Sustainable Development

Although aquaculture in Egypt has the potential for satisfying the increased demand for protein and has been experiencing unprecedented growth during the last decade, questions remain regarding the sustainable development of the industry. It is thus the objective of this article to review the current status and practices of the aquaculture industry in Egypt, highlighting the major issues confronting the sustainable development of the aquaculture industry. Several issues are identified as limitations to future sustainable development, namely, production technology, fry supply, a feed industry sufficient to meet the demands of a growing aquaculture industry, and marketing and distribution systems necessary to accommodate the strong seasonal supply pattern. The article then concludes with a discussion of recommendations for alleviating these limitations

Designing information systems doctoral programs: Issues and challenges

Doctoral programs aim at preparing students for stewardship in their discipline with particular emphasis on training for research. While doctoral programs have been conventionally offered by research institutions, market demands, changing needs, and other factors are driving traditionally teaching institutions to explore opportunities for implementing information systems (IS) doctoral programs. In this paper we present some of the issues and challenges involved in designing and implementing IS doctoral programs. The emphasis is on traditionally teaching institutions. The paper concludes with a set of recommendations and directions for future research on doctoral programs in information systems

An XML Based Architecture for Sharing Heterogeneous Models in Web and Distributed Computing Environments

Model management emerged in the mid-seventies in the context of managing models in decision support systems (DSS). With the recent advances in computer and telecommunication technologies, organizations are ever increasingly dependent on management models for data analysis and decision support. Accordingly, the number and complexity of management models and of modeling platforms dramatically increased rendering such models a corporate (and national) resource. With the advent of the Web and distributed computing environments, there is also an increasing demand to share these often heterogeneous models over corporate intranets as well as the Web. To this end, this paper presents an XML-based architecture for sharing heterogeneous models in Web and distributed computing environments. The architecture includes an XML schema for representing models. The schema is based on the structured modeling paradigm as a formal mathematical environment for conceiving, representing and manipulating a wide variety of models. The architecture allows different types of models, developed in a variety of modeling platform to be represented in a standardized format and shared over the Web. The paper demonstrates the proposed architecture through a case study

The Role of the Privacy Calculus and the Privacy Paradox in the Acceptance of Wearables for Health and Wellbeing

The Internet along with innovations in technology have inspired an industry focused on designing portable devices, known as wearables that can track users’ personal activities and wellbeing. While such technologies have many benefits, they also have risks (especially regarding information privacy and security). These concerns become even more pronounced with healthcare-related wearables. Consequently, users must consider the benefits given the risks (privacy calculus); however, users often opt for wearables despite their disclosure concerns (privacy paradox). In this study, we investigate the multidimensional role that privacy (and, in particular, the privacy calculus and the privacy paradox) plays in consumers’ intention to disclose their personal information, whether health status has a moderating effect on the relationship, and the influence of privacy on acceptance. To do so, we evaluated a research model that explicitly focused on the privacy calculus and the privacy paradox in the healthcare wearables acceptance domain. We used a survey-oriented approach to collect data from 225 users and examined relationships among privacy, health, and acceptance constructs. In that regard, our research confirmed significant evidence of the influence of the privacy calculus on disclosure and acceptance as well as evidence of the privacy paradox when considering health status. We found that consumers felt less inclined to disclose their personal information when the risks to privacy outweighed benefits; however, health status moderated this behavior such that people with worse health tipped the scale towards disclosure. This study expands our previous knowledge about healthcare wearables’ privacy/acceptance paradigm and, thus, the influences that affect healthcare wearables’ acceptance in the privacy context

Bayesian Social Subgraph Generative Models: Social Network Twins using Belief Networks and Ego Behavior Models

A key assumption of a Subgraph Generative Model (SUGM) for sparse networks is that a subgraph is independent of lower order subgraphs in a sparse network. This is not entirely true especially for non-sparse networks. Additionally, the generated networks lack the typical properties of a social network because of an assumption of random growth for nodes and edges. Finally, there is no concept for explicit ego choice or bias when connecting to dyadic or triadic relationships. We develop a novel graph generative model referred to as the Bayesian Social Subgraph Generative Model (BASSUGM). We ground the BASSUGM in a proposed sociological model and leverage Bayesian tools like belief networks. We introduce novel concepts like the networks’ macro theme when combines with an ego’s individuality realizes the ego’s intent. We also demonstrate how the social network twin generated with BASSUGM outperforms SUGM for non-sparse, small, social, networks