Simulation in manufacturing and business: A review

Copyright @ 2009 Elsevier B.V.This paper reports the results of a review of simulation applications published within peer-reviewed literature between 1997 and 2006 to provide an up-to-date picture of the role of simulation techniques within manufacturing and business. The review is characterised by three factors: wide coverage, broad scope of the simulation techniques, and a focus on real-world applications. A structured methodology was followed to narrow down the search from around 20,000 papers to 281. Results include interesting trends and patterns. For instance, although discrete event simulation is the most popular technique, it has lower stakeholder engagement than other techniques, such as system dynamics or gaming. This is highly correlated with modelling lead time and purpose. Considering application areas, modelling is mostly used in scheduling. Finally, this review shows an increasing interest in hybrid modelling as an approach to cope with complex enterprise-wide systems

Citation Counts and Evaluation of Researchers in the Internet Age

Bibliometric measures derived from citation counts are increasingly being used as a research evaluation tool. Their strengths and weaknesses have been widely analyzed in the literature and are often subject of vigorous debate. We believe there are a few fundamental issues related to the impact of the web that are not taken into account with the importance they deserve. We focus on evaluation of researchers, but several of our arguments may be applied also to evaluation of research institutions as well as of journals and conferences.Comment: 4 pages, 2 figures, 3 table

Open Science in Software Engineering

Open science describes the movement of making any research artefact available to the public and includes, but is not limited to, open access, open data, and open source. While open science is becoming generally accepted as a norm in other scientific disciplines, in software engineering, we are still struggling in adapting open science to the particularities of our discipline, rendering progress in our scientific community cumbersome. In this chapter, we reflect upon the essentials in open science for software engineering including what open science is, why we should engage in it, and how we should do it. We particularly draw from our experiences made as conference chairs implementing open science initiatives and as researchers actively engaging in open science to critically discuss challenges and pitfalls, and to address more advanced topics such as how and under which conditions to share preprints, what infrastructure and licence model to cover, or how do it within the limitations of different reviewing models, such as double-blind reviewing. Our hope is to help establishing a common ground and to contribute to make open science a norm also in software engineering.Comment: Camera-Ready Version of a Chapter published in the book on Contemporary Empirical Methods in Software Engineering; fixed layout issue with side-note

Open source repositories: Implications for libraries

Software that is accepted as “Open source” should comply with 10 conditions which are itinerated in the paper. The paper subsequently describes the application of open source initiatives in the digital library context. Three open source digital library initiatives developed by the Digital Library Research Group at the Faculty of Computer Science and information Technology, University of Malaya are highlighted. These are; (a) MyManuskrip: digital library of Malay manuscripts; (b) MyAIS : Digital library of Malaysian scholarly journals and conference proceedings; and (d) DSpace@Um: a digital library of dissertations, theses and final year project reports. Other “free” systems such as EJUM: electronic journal of university of Malaya is also described to highlight the slight difference between open source and being free. The paper also describes the libraries involved in the initiatives and the changing eco-system which libraries must accept to embrace the open source culture

Optimization of stand-alone photovoltaic system by implementing fuzzy logic MPPT controller

A photovoltaic (PV) generator is a nonlinear device having insolation-dependent volt-ampere characteristics. Since the maximum-power point varies with solar insolation, it is difficult to achieve an optimum matching that is valid for all insolation levels. Thus, Maximum power point tracking (MPPT) plays an important roles in photovoltaic (PV) power systems because it maximize the power output from a PV system for a given set of condition, and therefore maximize their array efficiency. This project presents a maximum power point tracker (MPPT) using Fuzzy Logic theory for a PV system. The work is focused on a comparative study between most conventional controller namely Perturb and Observe (P&O) algorithm and is compared to a design fuzzy logic controller (FLC). The introduction of fuzzy controller has given very good performance on whatever the parametric variation of the system

Ontology (Science)

Increasingly, in data-intensive areas of the life sciences, experimental results are being described in algorithmically useful ways with the help of ontologies. Such ontologies are authored and maintained by scientists to support the retrieval, integration and analysis of their data. The proposition to be defended here is that ontologies of this type – the Gene Ontology (GO) being the most conspicuous example – are a _part of science_. Initial evidence for the truth of this proposition (which some will find self-evident) is the increasing recognition of the importance of empirically-based methods of evaluation to the ontology develop¬ment work being undertaken in support of scientific research. Ontologies created by scientists must, of course, be associated with implementations satisfying the requirements of software engineering. But the ontologies are not themselves engineering artifacts, and to conceive them as such brings grievous consequences. Rather, ontologies such as the GO are in different respects comparable to scientific theories, to scientific databases, and to scientific journal publications. Such a view implies a new conception of what is involved in the author¬ing, maintenance and application of ontologies in scientific contexts, and therewith also a new approach to the evaluation of ontologies and to the training of ontologists