CORRELATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES WITH SOFT COMPUTING IN VARIOUS AREAS

Artificial Intelligence (AI) is a part of computer science concerned with designing intelligent computer systems that exhibit the characteristics used to associate with intelligence in human behavior. Basically, it define as a field that study and design of intelligent agents. Traditional AI approach deals with cognitive and biological models that imitate and describe human information processing skills. This processing skills help to perceive and interact with their environment. But in modern era developers can build system that assemble superior information processing needs of government and industry by choosing from large areas of mature technologies. Soft Computing (SC) is an added area of AI. It focused on the design of intelligent systems that process uncertain, imprecise and incomplete information. It applied in real world problems frequently to offer more robust, tractable and less costly solutions than those obtained by more conventional mathematical techniques. This paper reviews correlation of artificial intelligence techniques with soft computing in various areas

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 341)

This bibliography lists 133 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during September 1990. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

NFC based service innovation in retail: An explorative study

Enterprises are facing a challenging dilemma. In order to be able to accommodate peak loads on their IT systems, they must maintain large computing clusters, which lie idle most of the time. At the same time, IT departments are under constant pressure to cut down on hard- and software expenses. Grid technology offers a promising way out of this dilemma by allowing the dynamic sharing both within enterprises as well as across organizational boundaries. This sharing approach, however, requires proper economic incentives. This paper is concerned with the determination of dynamic market-based prices. Due to their simplicity, so-called pay-as-bid mechanisms have become popular. This paper is novel as we provide an in-depth analysis of two such pay-as-bid mechanisms – Proportional Share and a discriminatory pay-as-bid mechanism – for the case of three users, thus extending previous work by Sanghavi and Hajek (2004) and Stößer et al. (2008). This analysis is important as we show that the nice results for two users cannot be retained once three or more users are present. Even worse, we show that these results can even be reversed if we move to games with more than two player

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 118

This special bibliography lists 338 reports, articles, and other documents introduced into the NASA scientific and technical information system in July 1973

Performance management system enhancement and maintenance

The research described in this report concludes a two-year effort to develop a Performance Management System (PMS) for the NCC computers. PMS provides semi-automated monthly reports to NASA and contractor management on the status and performance of the NCC computers in the TDRSS program. Throughout 1984, PMS was tested, debugged, extended, and enhanced. Regular PMS monthly reports were produced and distributed. PMS continues to operate at the NCC under control of Bendix Corp. personnel

A Hybrid Modelling Framework for Real-time Decision-support for Urgent and Emergency Healthcare

In healthcare, opportunities to use real-time data to support quick and effective decision-making are expanding rapidly, as data increases in volume, velocity and variety. In parallel, the need for short-term decision-support to improve system resilience is increasingly relevant, with the recent COVID-19 crisis underlining the pressure that our healthcare services are under to deliver safe, effective, quality care in the face of rapidly-shifting parameters. A real-time hybrid model (HM) which combines real-time data, predictions, and simulation, has the potential to support short-term decision-making in healthcare. Considering decision-making as a consequence of situation awareness focuses the HM on what information is needed where, when, how, and by whom with a view toward sustained implementation. However the articulation between real-time decision-support tools and a sociotechnical approach to their development and implementation is currently lacking in the literature. Having identified the need for a conceptual framework to support the development of real-time HMs for short-term decision-support, this research proposed and tested the Integrated Hybrid Analytics Framework (IHAF) through an examination of the stages of a Design Science methodology and insights from the literature examining decision-making in dynamic, sociotechnical systems, data analytics, and simulation. Informed by IHAF, a HM was developed using real-time Emergency Department data, time-series forecasting, and discrete-event simulation. The application started with patient questionnaires to support problem definition and to act as a formative evaluation, and was subsequently evaluated using staff interviews. Evaluation of the application found multiple examples where the objectives of people or sub-systems are not aligned, resulting in inefficiencies and other quality problems, which are characteristic of complex adaptive sociotechnical systems. Synthesis of the literature, the formative evaluation, and the final evaluation found significant themes which can act as antecedents or evaluation criteria for future real-time HM studies in sociotechnical systems, in particular in healthcare. The generic utility of IHAF is emphasised for supporting future applications in similar domains

Air Force Institute of Technology Research Report 2017

This Research Report presents the FY18 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs)