Parallelization of Goal-Driven, Production Systems on Hypercube Machines in a C Environment.

Production systems are widely used in artificial intelligence to capture the notion of expertise in modeling expert systems. Production systems are computationally intensive programs spending most of the execution time in their MATCH or recognise phase. Efforts have been made by the research in this dissertation to minimize the production system\u27s execution time by optimizing the MATCH phase. Goal oriented deterministic production systems are commonly used for robotics applications and formed the main class of production systems that were studied in this dissertation. The main motivation for the research was to provide a better MATCH algorithm and use the multiprocessing capabilities of existing parallel computer hardware. The dissertation realizes these goals by transforming a traditional production system\u27s scalar equivalence operations into C arithmetic hashing function to generate an indexing variable for the switch-case construct of the C language. Partitioning of the working memory into homogeneous blocks and distributing production memory over the multiprocessors enhanced the MIMD operation of the production system. A scheme is formulated and implemented to identify a few key condition elements that may be used as an indexing variable and reduce the number of condition elements used in the MATCH phase. The complete translation from OPS5 code to C and the implementation scheme is presented in this dissertation. Various issues regarding the distribution of the inference engine over the multiprocessor environment and other related synchronization topics for distributed systems are covered in the dissertation. A detailed description of the parallel computer\u27s simulator is also provided in the dissertation. The dissertation identifies other research topics and problems related to parallelization of production systems, the most significant being the ability to incorporate LEARNING in production systems by using one or all of the idle processors that are waiting for the active processor to complete it\u27s activities

On Fixed Point Theorem in Fuzzy Metric Spaces

Abstract: - The Purpose of this paper, we prove common fixed point theorem using new continuity condition in fuzzy metric spaces. Keywords: - Compatible maps, R-weakly commuting maps, reciprocal continuity. Mathematics subject classification: - 47H10, 54H25

Some Common Fixed Point Theorems in Generalized Vector Metric Spaces

In this paper we give some theorems on point of coincidence and common fixed point for two self mappings satisfying some general contractive conditions in generalized vector spaces. Our results generalize some well-known recent results in this direction

Abstracts of National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020

This book presents the abstracts of the papers presented to the Online National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020 (RDMPMC-2020) held on 26th and 27th August 2020 organized by the Department of Metallurgical and Materials Science in Association with the Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, India. Conference Title: National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020Conference Acronym: RDMPMC-2020Conference Date: 26–27 August 2020Conference Location: Online (Virtual Mode)Conference Organizer: Department of Metallurgical and Materials Engineering, National Institute of Technology JamshedpurCo-organizer: Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, IndiaConference Sponsor: TEQIP-

Challenges to effective cancer control in China, India, and Russia

Cancer is one of the major non-communicable diseases posing a threat to world health. Unfortunately, improvements in socioeconomic conditions are usually associated with increased cancer incidence. In this Commission, we focus on China, India, and Russia, which share rapidly rising cancer incidence and have cancer mortality rates that are nearly twice as high as in the UK or the USA, vast geographies, growing economies, ageing populations, increasingly westernised lifestyles, relatively disenfranchised subpopulations, serious contamination of the environment, and uncontrolled cancer-causing communicable infections. We describe the overall state of health and cancer control in each country and additional specific issues for consideration: for China, access to care, contamination of the environment, and cancer fatalism and traditional medicine; for India, affordability of care, provision of adequate health personnel, and sociocultural barriers to cancer control; and for Russia, monitoring of the burden of cancer, societal attitudes towards cancer prevention, effects of inequitable treatment and access to medicine, and a need for improved international engagement