Topic
Applied science
About: Applied science is a research topic. Over the lifetime, 1178 publications have been published within this topic receiving 19920 citations. The topic is also known as: applied sciences.
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Book•
01 Jan 1915
TL;DR: In this article, a course for beginning level students who have been identified as SLIFE (Students with Interrupted or Limited Education) and who have acquired few or no English language skills is presented.
Abstract: Course Title : Introduction to Science #303 Course Description: This course is for beginning level students who have been identified as SLIFE (Students with Interrupted or Limited Education) and who have acquired few or no English language skills. Students will study the major systems of the human body and how they interrelate, diseases and prevention, and issues related to mental and emotional health. This course will also emphasize the development of English language and literacy skills as well as content and academic vocabulary. Native language support is provided.
12 citations
Journal Article•
12 citations
01 Dec 2012
TL;DR: In this article, the authors discuss the importance of reference collections in academic and research library reference collections and provide a crucial tool for academicians, researchers, and practitioners and is ideal forclassroom use.
Abstract: Market: This premier publication is essential for all academic and research library reference collections. It is a crucial tool for academicians, researchers, and practitioners and is ideal forclassroom use. Khairiyah Mohd Yusof (Universiti Teknologi Malaysia, Malaysia), Naziha Ahmad Azli (Universiti Teknologi Malaysia, Malaysia), Azlina Mohd Kosnin (Universiti Teknologi Malaysia, Malaysia), Sharifah Kamilah (Universiti Teknologi Malaysia, Malaysia), Syed Yusof (Universiti Teknologi Malaysia, Malaysia), & Yudariah Mohammad Yusof (Universiti Teknologi Malaysia, Malaysia)
12 citations
TL;DR: It is recognized by several experts in the field, during panel discussions conducted during recent conferences, that the focus of effort needs to shift from the implementation aspects to the conceptual aspects of modelling and simulation as well.
Abstract: Two emerging trends in modelling and simulation (M&S) are beginning to dovetail in a potentially highly productive manner, namely conceptual modelling and semantic modelling. Conceptual modelling has existed for several decades, but its importance has risen to the forefront in the last decade (Taylor and Robinson, 2006; Robinson, 2007). Also, during the last decade, progress on the Semantic Web has begun to influence M&S, with the development of general modelling ontologies (Miller et al, 2004), as well as ontologies for modelling particular domains (Durak et al, 2006). An ontology, which is a formal specification of a conceptualization (Gruber, 1993), can be used to rigorously define a domain of discourse in terms of classes/concepts, properties/relationships and instances/individuals. For the Semantic Web, ontologies are typically specified using the Web Ontology Language (OWL). Although, conceptual modelling is broader than just semantics (it includes additional issues such as pragmatics (Tolk et al, 2008)), progress in the Semantic Web and ontologies is certainly beneficial to conceptual modelling. Benefits are accrued in many ways including the large knowledge bases being placed on the Web in numerous fields in which simulation studies are conducted and the powerful reasoning algorithms based on description logic being developed that allow the consistency of large specifications to be checked. Conceptual and semantic models are useful for developing executable simulations in general, but are particularly helpful in supporting composability and interoperability. Interoperability of simulation systems is concerned with the correctness of interactions among components in the simulation environment and builds on the composability of their underlying models. In order to fully utilize and share the underlying models, the interactions have to be made explicit, which requires well-documented conceptual models as well as their implementations. Several best practices and even standardized methods exist supporting integration of two or more simulations in order to provide a broader basis for M&S-based research, as envisioned in the 1996 National Science Foundation (NSF) Report on ‘Simulation-based Engineering Science’ showing the potential of using simulation technology and methods to revolutionize engineering science. In addition, it is recognized by several experts in the field, during panel discussions conducted during recent conferences, that the focus of effort needs to shift from the implementation aspects to the conceptual aspects of modelling and simulation as well. In all these discussions, the value and necessity of simulation integration efforts was recognized as a necessary part of interoperability and composability, but it was also recognized that these efforts are not sufficient. While the community agrees on the necessity of unambiguous and machine readable documentation of the conceptual component of M&S in principle, the details of different approaches are currently not well aligned (Balci et al, 2010). However, one discussion topic is most often observed when it comes to conceptual modelling: the increased use of ontological means supporting precisely defined formal models that capture semantics, yet afford more flexibility in syntax. In particular, the experts of several related panels expressed their conviction that ontologies offer a means for enhancing composability and interoperability among models and simulations developed independently. The rationale for supporting this belief that emerges from these discussions is that an ontology is a formal specification of a conceptualization, which fulfills the requirements for a conceptual model:
12 citations
12 citations