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CLEER - AN AI-system DEVELOPED TO ASSIST EQUIPMENT ARRANGEMENTS ON WARSHIPS

NAVAL ENGINEERS JOURNAL 1989年第3期101卷 127-137页

作者： ZHOU, HH SILVERMAN, BG SIMKOL, J Dr. H. Harry Zhou:is a research professor at the Institute for Artificial Intelligence of The George Washington University. Dr. Zhou received his master's degree and Ph.D. in computer science from Vanderbilt University in 1984 and 1987 respectively. He did his dissertation in the fields of artificial intelligence analogical reasoning and machine learning. His research interests include: classifier systems genetic algorithms learning by analogy inductive learning adaptive expert systems automated knowledge acquisition and adaption. He is also interested in data base design programming languages mental modeling and software engineering. Dr. Barry G. Silverman:is director of the Institute for Artificial Intelligence and a professor at the Engineering Administration Department of The George Washington University. He is also president of IntelliTek Inc. an AI consulting firm. Dr. Silverman received the B.S.E. M.S.E. and Ph.D. degrees from the University of Pennsylvania. He has been a principal developer of four generic AI products as well as eight AI applications. Since 1979 he has written over 100 papers and reports on these AI efforts. Joel Simkol:is a research scientist currently engaged in designing expert system architectures to support electronic warfare vulnerability analyses threat assessments shipboard topside antenna arrangements and C3countermeasures employment. Mr. Simkol's work in applying expert systems technology to electromagnetic interference and to spectrum management has generated increased interest and participation from all branches of government agencies.

This paper describes a modularized AI system being built to help improve electromagnetic compatibility (EMC) among shipboard topside equipment and their associated systems. CLEER is intended to act as an easy to use integrator of existing expert knowledge and pre-existing data bases and large scale analytical models. Due to these interfaces; to the need for portability of the software; and to artificial intelligence related design requirements (such as the need for spatial reasoning, expert data base management, model base management, track-based reasoning, and analogical (similar ship) reasoning) it was realized that traditional expert system shells would be inappropriate, although relatively off-the-shelf AI technology could be incorporated. In the same vein, the rapid prototyping approach to expert system design and knowledge engineering was not pursued in favor of a rigorous systems engineering methodology. The critical design decisions affecting CLEER's development are summarized in this paper along with lessons learned to date all in terms of “how,” “why,” and “when” specific features are being developed.

关键词： Artificial Intelligence

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ROLE OF SIMULATION IN RAPID PROTOTYPING FOR CONCEPT DEVELOPMENT

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NAVAL ENGINEERS JOURNAL 1991年第3期103卷 204-211页

作者： KING, JF BARTON, DE J. Fred King:is the manager of the Advanced Technology Department for Unisys in Reston Virginia. He earned his Ph.D. in mathematics from the University of Houston in 1977. He has been principal investigator of research projects in knowledge engineering pattern recognition and heuristic problem-solving. Efforts include the development of a multi-temporal multispectral classifier for identifying graincrops using LANDSAT satellite imagery data for NASA. Also as a member of the research team for a NCI study with Baylor College of Medicine and NASA he helped develop techniques for detection of carcinoma using multispectral microphotometer scans of lung tissue. He established and became technical director of the AI Laboratory for Ford Aerospace where he developed expert scheduling modeling and knowledge acquisition systems for NASA. Since joining Unisys in 1985 he has led the development of object-oriented programming environments blackboard architectures data fusion techniques using neural networks and intelligent data base systems. Douglas E. Barton:is manager of Logistics Information Systems for Unisys in Reston Virginia. He earned his B.A. degree in computer science from the College of William and Mary in 1978 and did postgraduate work in London as a Drapers Company scholar. Since joining Unisys in 1981 his work has concentrated on program management and software engineering of large scale data base management systems and design and implementation of knowledge-based systems in planning and logistics. As chairman of the Logistics Data Subcommittee of the National Security Industrial Association (NSIA) he led an industry initiative which examined concepts in knowledge-based systems in military logistics. His responsibilities also include evaluation development and tailoring of software engineering standards and procedures for data base and knowledge-based systems. He is currently program manager of the Navigation Information Management System which provides support to the Fleet Ballistic Missile Progr

A valuable technique during concept development is rapid prototyping of software for key design components. This approach is particularly useful when the optimum design approach is not readily apparent or several known alternatives need to be rapidly evaluated. A problem inherent in rapid prototyping is the lack of a "target system" with which to interface. Some alternatives are to develop test driver libraries, integrate the prototype with an existing working simulator, or build one for the specific problem. This paper presents a unique approach to concept development using rapid prototyping for concept development and scenario-based simulation for concept verification. The rapid prototyping environment, derived from artificial intelligence technology, is based on a blackboard architecture. The rapid prototype simulation capability is provided through an object-oriented modeling environment. It is shown how both simulation and blackboard technologies are used collectively to rapidly gain insight into a tenacious problem. A specific example will be discussed where this approach was used to evolve the logic of a mission controller for an autonomous underwater vehicle.

关键词： Military Engineering

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Preface

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CEUR Workshop Proceedings 2019年 2514卷 1-2页

作者： Avetisyan, Arutyun Ivar, Jacobson Pozin, Boris A. Petrenko, Alexander K. Pozin, Boris A. Petrenko, Alexander K. Cavalli, Ana Rosa Petrenko, Alexander K. Avetisyan, Arutyun Arlazarov, Vladimir Avdoshin, Sergey Batovrin, Victor K. Bershadsky, Alexander M. Boichenko, Alexander Juris, Borzovs Vasenin, Valery A. Schlingloff, Holger Kalyanov, Georgy Kantorovich, Georgy G. Korolev, Anton Kosolapov, Mikhail S. Kostogryzov, Andrey I. Koznov, Dmitry V. Kuznetsov, Sergey Prokhorov, Sergei Soyfer, Victor A. Starykh, Vladimir A. Stolyarov, Gennady K. Stupnikov, Sergey A. Telnov, Yury Ph. Shmid, Alexander Mira, Kajko-Mattssen Miroslawa Wentzl, Wilfried Mayer, Walter H. Yevtushenko, Nina Zakharov, Victor Zmeev, Oleg Cavalli, Ana Rosa Petrenko, Alexander K. Pozin, Boris A. RAS ISP Russia Ivar Jacobson International Switzerland NRU HSE «-leasing» Co Russia NRU HSE ISP RAS Russia Information and Analytical Systems «-leasing» Co Russia Department of Network Software TELECOM and Management SudParis France NRU HSE Russia Software Engineering of Ivannikov Institute for System Programming RAS Russia RAS System Analysis Institute of Federal Research Centre Informatics and Management Russia Russia Penza State University Russia Federal State Educational Centre of Higher Learning «Plekhanov Russian University of Economics» Russia CISA Academy of Sciences of Latvia State University of Latvia Latvia MSU Institut für Offene Kommunikationssysteme FOKUS Germany Verifikation und Testtheorie an der Humboldt-Universität zu Berlin Germany Institute of Control Sciences RAS Russia Institute of Sociology RAS NRU HSE Russia ISO IEEC Institute of Informatics Problems Federal Research Centre IM RAS Russia St. Petersburg State University Russia Institute for System Programming RAS Moscow State University Russia SRI Korolev Samara State Aerospace University Russia Belarus FRC IM RAS Russia FSEC «Plekhanov Russian University of Economics» Russia KTH School of Information and Communication Technology Sweden Governmental Agricultural Analyst Austria Austria Ivannikov Institute for System Programming RAS Russia Institute of Informatics Problems Federal Research Centre IM RAS Russia Tomsk State University Russia

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Correction to: A new cognitive clock matching phenotypic and epigenetic ages

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Translational psychiatry 2022年第1期12卷 452页

作者： M I Krivonosov E V Kondakova N A Bulanov S A Polevaya C Franceschi M V Ivanchenko M V Vedunova Institute of Biology and Biomedicine Department of Neurotechnology N. I. Lobachevsky State University Nizhny Novgorod Russia. krivonosov@itmm.unn.ru. Institute of Information Technology Mathematics and Mechanics Department of Applied Mathematics N. I. Lobachevsky State University Nizhny Novgorod Russia. krivonosov@itmm.unn.ru. Research Center for Trusted Artificial Intelligence The Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow 109004 Russia. krivonosov@itmm.unn.ru. Research Center for Trusted Artificial Intelligence The Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow 109004 Russia. Institute of Biology and Biomedicine Department of Basic and Medical Genetics N. I. Lobachevsky State University Nizhny Novgorod Russia. Faculty of Computer Science School of Data Analysis and Artificial Intelligence HSE University Moscow Russia. Faculty of Social Sciences Department of Psychophysiology N. I. Lobachevsky State University Nizhny Novgorod Russia. Institute of Information Technology Mathematics and Mechanics Department of Applied Mathematics N. I. Lobachevsky State University Nizhny Novgorod Russia. Department of Experimental Diagnostic and Specialty Medicine (DIMES) University of Bologna Bologna Italy.

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Simulation of transonic low-Reynolds jets using quasi-gas dynamics equations

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Journal of Physics: Conference Series 2019年第1期1382卷

作者： M V Kraposhin A S Epikhin T G Elizarova K A Vatutin Ivannikov Institute for System Programming of the RAS Russia Moscow Solzhenitsyna str. 25 The Department of Aeromechanics and Flight Engineering Moscow Institute of Physics and Technology Russia Moscow Region Jukovskiy Gagarin str. 16 Keldysh Institute of Applied Mathematics of the RAS Russia Moscow Miusskaya Sqr. 4 Bauman Moscow State Technical University Russia Moscow 2nd Baumanskay str. 5 building 1 Faculty of Mechanics and Mathematics Lomonosov Moscow State University Russia Moscow GSP-1 Leninskiye gory 1

In this paper application of the OpenFOAM solver QGDFoam for numerical simulation of transonic viscous flows is considered. The developed solver, which implements regularized or quasi- gas dynamics (QGD) algorithms, is validated using the transonic low-Re jet flow case (Ma=0.9, Re=3600). The conducted numerical simulations allow the assessing applicability of the solver for modelling hydrodynamic instabilities and their interaction with transonic flow. Results of the numerical simulations are compared with experimental observations and Navier-Stokes-based code simulation. Results of the present study formulate a guideline for choosing (values of) QGD-algorithm tuning parameters.

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Scientific Data Lake for High Luminosity LHC project and other data-intensive particle and astro-particle physics experiments

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Journal of Physics: Conference Series 2020年第1期1690卷

作者： A Alekseev A Kiryanov A Klimentov T Korchuganova V Mitsyn D Oleynik A Smirnov S Smirnov A Zarochentsev Compiler Technology Department Ivannikov Institute for System Programming of the RAS Moscow 109004 Russia Cloud technologies and Big Data analytics laboratory Plekhanov Russian University of Economics Moscow 117997 Russia ATLAS group Universidad Andres Bello Santiago 7550196 Chile Department of computing resources and technologies NRC 'Kurchatov Institute' - PNPI 188300 Gatchina Russia Physics Department Brookhaven National Laboratory Upton NY 11973 USA Laboratory of Information Technologies Joint Institute for Nuclear Research Dubna 141980 Russia Institute of Nuclear Physics and Engineering National Research Nuclear University MEPhI Moscow 115409 Russia Laboratory of Ultra-High Energy Physics Saint Petersburg State University Saint Petersburg 198504 Russia

The next phase of LHC Operations – High Luminosity LHC (HL-LHC), which is aimed at ten-fold increase in the luminosity of proton-proton collisions at the energy of 14 TeV, is expected to start operation in 2027-2028 and will deliver an unprecedented scientific data volume of multi-exabyte scale. This amount of data has to be stored and the corresponding storage system should ensure fast and reliable data delivery for processing by scientific groups distributed all over the world. The present LHC computing and data processing model will not be able to provide the required infrastructure growth even taking into account the expected hardware technology evolution. To address this challenge the new state-of-the-art computing infrastructure technologies are now being developed and are presented here. The possibilities of application of the HL-LHC distributed data handling technique for other particle and astro-particle physics experiments dealing with large-scale data volumes like DUNE, LSST, Belle-II, JUNO, SKAO etc. are also discussed.

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THE AN/UYK‐502(V) MICROCOMPUTER

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Naval Engineers Journal 1979年第2期91卷 173-178页

作者： WILLIAMS, PAUL F. ANDERSON, JOHN M. Mr. Paul F. Williams:received his BS degree in Electrical Engineering from the University of Minnesota in December 1965. He joined SPERRY UNIVAC Defense Systems Division in January 1966 where he is now the Manager of the Computer Product Planning Group in the Marketing Department. He has been active in the development of new computer system architectures and new computer development including the AN/UYK-20 and AN/UYK-23. In addition he has worked with a number of Navies in the development of shipboard and landbased systems and has participated in the development of NATO Shipboard Standard Interfaces. Mr. John M. Anderson:received his BS degree in Electrical Engineering from the University of Washington in June 1969. He joined SPERRY UNIVAC in July 1970 where he is now a Senior Design Engineer in the Product Development Group. He is currently active in the development of the AN/UYK-520 Microcomputer and additionally has been active in the fields of digital logic design programming and computer testing.

The AN/UYK‐502 Microcomputer is a full‐scale, general‐purpose 16‐bit militarized computer designed to emmulate the AN/UYK‐20 and AN/AYK‐14, and to be implemented in a shipboard system employing distributed system architecture. Ship system Data Busses require microcomputers to be located near or within ship subsystems, with system interconnection being made through a common data bus. To implement this type of system architecture, a low cost, modular microcomputer capable of handling the bus “handshake” through a standard interface is required. The AN/UYK‐502(V) uses software common to minicomputers which allows different computer configurations to be implemented with bus architecture. The resulting system can then be maintained with a single set of support software programs thus significantly lowering system life cycle costs. The computer is offered in three physical packages: the Card Kit, Chassis Assembly, and Cabinet Assembly. Flexible options of the AN/UYK‐502(V) allow the user to tailor the system to the application needs. These options include the Central Processing Expansion Unit;main memory up to 2S6K (where K = 1024);memory parity;choice of 1 to 64 input/output (I/O) channels;parallel and/or serial I/O;and power supply selection. © 1979 American Society of Naval Engineers

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CONTROL system DESIGN CONSIDERING A TRADEOFF BETWEEN EVALUATED UNCERTAINTY RANGES AND CONTROL PERFORMANCE

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Asian Journal of Control 2008年第1期1卷

作者： Y. Wakasa Y. Yamamoto Dept. of Applied Analysis and Complex Dynamical Systems Graduate School of Informatics Kyoto University Kyoto Japan. Yuji Wakasa was born in Okayama Japan in 1968. He received the B.S. and M.S. degrees in engineering from Kyoto university Japan in 1992 and 1994 respectively. From 1994 to 1998 he was a Research Associate in the Department of Information Technology Okayama University. Since April 1998 he has been a Research Associate in the Graduate School of Informatics Kyoto University. His current research interests include robust control and control system design via mathematical programming. Yutaka Yamamoto received his B.S. and M.S. degrees in engineering from Kyoto University Kyoto Japan in 1972 and 1974 respectively and the M.S. and Ph.D. degree in mathematics from the University of Florida in 1976 and 1978 respectively. From 1978 to 1987 he was with Department of Applied Mathematics and Physics Kyoto University and from 1987 to 1997 with Department of Applied System Science. Since 1998 he is a professor at the current position. His current research interests include realization and robust control of distributed parameter systems learning control sampled-data systems and digital signal processing. Dr. Yamamoto is a receipient of the Sawaragi memorial paper award (1985) the Outstanding Paper Award of SICE (1987) Best Author Award of SICE (1990) the George Axelby Outstanding Paper Award of IEEE CSS in 1996 Takeda Paper Prize of SICE in 1997. He is a Fellow of IEEE. He was an associate editor of Automatica. He is currently an associate editor of IEEE Transactions on Automatic Control Systems and Control Letters and Mathematics of Control Signals and Systems. He is a member of the IEEE the Society of Instrument and Control Engineers (SICE) and the Institute of Systems Control and Information Engineers.

This paper presents a design method of control systems such that a designer can flexibly take account of tradeoffs between evaluated uncertainty ranges and the level of control performance. The problem is reduced to a BMI problem and approximately solved by LMIs. The convergence of the proposed approximation is proved in a modified sense. A numerical example shows the effectiveness of the proposed method in comparison with the standard robust control.

关键词： Control system design LMI BMI tradeoff curves

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OREGON'S GET TOUGH SENTENCING REFORM: A LESSON IN JUSTICE system ADAPTATION

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Criminology & Public Policy 2006年第1期5卷

作者： NANCY MERRITT TERRY FAIN SUSAN TURNER Extensive experience conducting justice system policy studies at the state and local level. As a Policy Analyst with the RAND Corporation and government agencies she designed and directed studies focused on the development implementation and evaluation of sentencing policy as well as juvenile and adult correctional programs. Her current work focuses on the implementation and impact of mandatory sentencing laws cross-jurisdictional variations in their application and the effects of prosecutorial discretion. Additional areas of interest include the development implementation and evaluation of juvenile justice programming. Ms. Merritt received her M.S. from the Pennsylvania State University University Park and is a Ph.D. candidate with the Rutgers University School of Criminal Justice. M.A. M.S. is a Senior project associate in the Behavioral Sciences Department at RAND Corporation. He has extensive research experience in criminal justice and substance abuse. He is expert in computer statistical techniques as well as in managing large datasets. He has conducted analysis for many RAND projects and is author or co-author of numerous publications both from RAND and in peer-reviewed journals. His research interests include alternatives to incarceration substance abuse and treatment racial disparities in prison admissions and research collaborations with state and local justice agencies. Professor in the Department of Criminology Law and Society at the University of California's Irvine campus. She received her Ph.D. in Social Psychology from the University of North Carolina at Chapel Hill. She has led a variety of research projects including studies on racial disparity field experiments of private sector alternatives for serious juvenile offenders work release day fines and a 14–site evaluation of intensive supervision probation. Dr. Turner's areas of expertise include the design and implementation of randomized field experiments and research collaborations with state and local justice agencies. He

Research Summary: Oregon's Measure 11, a mandatory minimum sentencing policy passed in 1994, had fewer negative system impacts than had been anticipated by many state and local criminal justice administrators, due largely to the fact that prosecutors exercised the discretion provided them under the law to selectively prosecute cases. Consequently, fewer Measure 11-eligible cases were sentenced under the relevant statues than before passage of the measure, and more were sentenced to lesser related offenses. At the same time, incarceration rates and sentence lengths increased for both Measure 11 and lesser related offenses. Trial rates increased for two years after Measure 11 took effect before reverting to previous levels. Policy Implications: The “unintended consequences” that Measure 11 produced should not have been unexpected. Our research indicates that the entire system will quickly adapt to mitigate the more draconian outcomes predicted by those who assume a simplistic implementation, which underscores the importance of understanding system dynamics and inter-relationships before implementing reform, as well as the pitfalls of designing legislation for either symbolic appeal or formal logic rather than for actual effect.

关键词： Sentencing Reform Mandatory Minimums Prosecutorial Discretion “Get Tough” Sentencing

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