26,995 research outputs found

    CORPORATE INFRASTRUCTURE FOR FIFTH GENERATION COMPUTERS

    Get PDF
    Arithmetically each level of human generation contributes to 6.72 generations of Computer upgrading. But, this effect could pay back to the human society only by tuning the corporate infrastructure to utilise these computer innovations optimally. The future computer electronics works towards drastic cost reduction and process speed optimization. Pre-fifth generation computer environment in late 1980s and early 1990s will be dominated by a circularly integrated general purpose computer network, and the organisation will be vertically integration in the hierarchical administration, and horizontal interaction at implementation levels. The Fifth generation architecture with its innovative techniques will be tuned to accept keyed, voice, picture inputs and process towards decision and action guidelines, using a knowledge based management and problem solving and inference modules. The machine is also expected to become more intelligent with the passage of time. The proposed Fifth Generation organisational structure is hence designed with the maintenance of 1990s hierarchical and machine interfaces, circularly integrated policy, management work flow, intensified problem-solution, knowledge/intelligence orientation, integrated human-machine interface and mutual training setup. Based on a survey of Hardware and Software development in USA and Japan by the author in 1984. The paper is supported with 4 Schematic Diagrams and a Post-Publication Appraisal. Published in Indian Management, Journal of the All India Management Association, New Delhi. India. June 1985, Pages 19 to 28.Computers, Computer Architecture, Computer Generations, Computer Network, Corporate Infra-structure, Circular Integration, Fifth Generation Computers, Group Work, Horizontal Inter-action, Human Machine Interface, Mutual Training, Infra-structure, Intelligent Machine, Knowledge base, Problem Solving, Vertically Integrated Administration

    Computational aerodynamics and artificial intelligence

    Get PDF
    The general principles of artificial intelligence are reviewed and speculations are made concerning how knowledge based systems can accelerate the process of acquiring new knowledge in aerodynamics, how computational fluid dynamics may use expert systems, and how expert systems may speed the design and development process. In addition, the anatomy of an idealized expert system called AERODYNAMICIST is discussed. Resource requirements for using artificial intelligence in computational fluid dynamics and aerodynamics are examined. Three main conclusions are presented. First, there are two related aspects of computational aerodynamics: reasoning and calculating. Second, a substantial portion of reasoning can be achieved with artificial intelligence. It offers the opportunity of using computers as reasoning machines to set the stage for efficient calculating. Third, expert systems are likely to be new assets of institutions involved in aeronautics for various tasks of computational aerodynamics

    Parallel processing and expert systems

    Get PDF
    Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 90's cannot enjoy an increased level of autonomy without the efficient use of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real time demands are met for large expert systems. Speed-up via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial labs in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems was surveyed. The survey is divided into three major sections: (1) multiprocessors for parallel expert systems; (2) parallel languages for symbolic computations; and (3) measurements of parallelism of expert system. Results to date indicate that the parallelism achieved for these systems is small. In order to obtain greater speed-ups, data parallelism and application parallelism must be exploited

    Parallel processing and expert systems

    Get PDF
    Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 1990s cannot enjoy an increased level of autonomy without the efficient implementation of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real-time demands are met for larger systems. Speedup via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial laboratories in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems is surveyed. The survey discusses multiprocessors for expert systems, parallel languages for symbolic computations, and mapping expert systems to multiprocessors. Results to date indicate that the parallelism achieved for these systems is small. The main reasons are (1) the body of knowledge applicable in any given situation and the amount of computation executed by each rule firing are small, (2) dividing the problem solving process into relatively independent partitions is difficult, and (3) implementation decisions that enable expert systems to be incrementally refined hamper compile-time optimization. In order to obtain greater speedups, data parallelism and application parallelism must be exploited

    Technology assessment of advanced automation for space missions

    Get PDF
    Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis formation, natural language and other man-machine communication, space manufacturing, teleoperators and robot systems, and computer science and technology

    Style Transfer and Extraction for the Handwritten Letters Using Deep Learning

    Full text link
    How can we learn, transfer and extract handwriting styles using deep neural networks? This paper explores these questions using a deep conditioned autoencoder on the IRON-OFF handwriting data-set. We perform three experiments that systematically explore the quality of our style extraction procedure. First, We compare our model to handwriting benchmarks using multidimensional performance metrics. Second, we explore the quality of style transfer, i.e. how the model performs on new, unseen writers. In both experiments, we improve the metrics of state of the art methods by a large margin. Lastly, we analyze the latent space of our model, and we see that it separates consistently writing styles.Comment: Accepted in ICAART 201

    Japanese cooperative R&D projects in software technology

    Get PDF
    Includes bibliographical references (leaves 50-55).Michael A. Cusumano

    An architecture for rule based system explanation

    Get PDF
    A system architecture is presented which incorporate both graphics and text into explanations provided by rule based expert systems. This architecture facilitates explanation of the knowledge base content, the control strategies employed by the system, and the conclusions made by the system. The suggested approach combines hypermedia and inference engine capabilities. Advantages include: closer integration of user interface, explanation system, and knowledge base; the ability to embed links to deeper knowledge underlying the compiled knowledge used in the knowledge base; and allowing for more direct control of explanation depth and duration by the user. User models are suggested to control the type, amount, and order of information presented
    • …
    corecore