WorldWideScience

Sample records for technology artificial intelligence

  1. Intelligent library systems: artificial intelligence technology and library automation systems

    OpenAIRE

    Bailey, Jr., Charles W.

    1991-01-01

    Artificial Intelligence (AI) encompasses the following general areas of research: (1) automatic programming, (2) computer vision, (3) expert systems, (4) intelligent computer-assisted instruction, (5) natural language processing, (6) planning and decision support, (7) robotics, and (8) speech recognition. Intelligent library systems utilize artificial intelligence technologies to provide knowledge-based services to library patrons and staff. This paper examines certain key aspects of AI th...

  2. Artificial Intelligence Applications to Videodisc Technology

    Science.gov (United States)

    Vries, John K.; Banks, Gordon; McLinden, Sean; Moossy, John; Brown, Melanie

    1985-01-01

    Much of medical information is visual in nature. Since it is not easy to describe pictorial information in linguistic terms, it has been difficult to store and retrieve this type of information. Coupling videodisc technology with artificial intelligence programming techniques may provide a means for solving this problem.

  3. Artificial Intelligence Applications to High-Technology Training.

    Science.gov (United States)

    Dede, Christopher

    1987-01-01

    Discusses the use of artificial intelligence to improve occupational instruction in complex subjects with high performance goals, such as those required for high-technology jobs. Highlights include intelligent computer assisted instruction, examples in space technology training, intelligent simulation environments, and the need for adult training…

  4. Demonstration of artificial intelligence technology for transit railcar diagnostics

    Science.gov (United States)

    1999-01-01

    This report will be of interest to railcar maintenance professionals concerned with improving railcar maintenance fault-diagnostic capabilities through the use of artificial intelligence (AI) technologies. It documents the results of a demonstration ...

  5. Artificial intelligence applications in information and communication technologies

    CERN Document Server

    Bouguila, Nizar

    2015-01-01

    This book presents various recent applications of Artificial Intelligence in Information and Communication Technologies such as Search and Optimization methods, Machine Learning, Data Representation and Ontologies, and Multi-agent Systems. The main aim of this book is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems.  .

  6. The Role of Artificial Intelligence Technologies in Crisis Response

    OpenAIRE

    Khalil, Khaled M.; Abdel-Aziz, M.; Nazmy, Taymour T.; Salem, Abdel-Badeeh M.

    2008-01-01

    Crisis response poses many of the most difficult information technology in crisis management. It requires information and communication-intensive efforts, utilized for reducing uncertainty, calculating and comparing costs and benefits, and managing resources in a fashion beyond those regularly available to handle routine problems. In this paper, we explore the benefits of artificial intelligence technologies in crisis response. This paper discusses the role of artificial intelligence technolo...

  7. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

    if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

  8. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

    Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

  9. The Potential Role of Artificial Intelligence Technology in Education.

    Science.gov (United States)

    Salem, Abdel-Badeeh M.

    The field of Artificial Intelligence (AI) and Education has traditionally a technology-based focus, looking at the ways in which AI can be used in building intelligent educational software. In addition AI can also provide an excellent methodology for learning and reasoning from the human experiences. This paper presents the potential role of AI in…

  10. Artificial Intelligence and Educational Technology: A Natural Synergy. Extended Abstract.

    Science.gov (United States)

    McCalla, Gordon I.

    Educational technology and artificial intelligence (AI) are natural partners in the development of environments to support human learning. Designing systems with the characteristics of a rich learning environment is the long term goal of research in intelligent tutoring systems (ITS). Building these characteristics into a system is extremely…

  11. Artificial Intelligence In Automatic Target Recognizers: Technology And Timelines

    Science.gov (United States)

    Gilmore, John F.

    1984-12-01

    The recognition of targets in thermal imagery has been a problem exhaustively analyzed in its current localized dimension. This paper discusses the application of artificial intelligence (AI) technology to automatic target recognition, a concept capable of expanding current ATR efforts into a new globalized dimension. Deficiencies of current automatic target recognition systems are reviewed in terms of system shortcomings. Areas of artificial intelligence which show the most promise in improving ATR performance are analyzed, and a timeline is formed in light of how near (as well as far) term artificial intelligence applications may exist. Current research in the area of high level expert vision systems is reviewed and the possible utilization of artificial intelligence architectures to improve low level image processing functions is also discussed. Additional application areas of relevance to solving the problem of automatic target recognition utilizing both high and low level processing are also explored.

  12. Artificial intelligence

    International Nuclear Information System (INIS)

    Perret-Galix, D.

    1992-01-01

    A vivid example of the growing need for frontier physics experiments to make use of frontier technology is in the field of artificial intelligence and related themes. This was reflected in the second international workshop on 'Software Engineering, Artificial Intelligence and Expert Systems in High Energy and Nuclear Physics' which took place from 13-18 January at France Telecom's Agelonde site at La Londe des Maures, Provence. It was the second in a series, the first having been held at Lyon in 1990

  13. Artificial intelligence and nuclear power. Report by the Technology Transfer Artificial Intelligence Task Team

    International Nuclear Information System (INIS)

    1985-06-01

    The Artificial Intelligence Task Team was organized to review the status of Artificial Intelligence (AI) technology, identify guidelines for AI work, and to identify work required to allow the nuclear industry to realize maximum benefit from this technology. The state of the nuclear industry was analyzed to determine where the application of AI technology could be of greatest benefit. Guidelines and criteria were established to focus on those particular problem areas where AI could provide the highest possible payoff to the industry. Information was collected from government, academic, and private organizations. Very little AI work is now being done to specifically support the nuclear industry. The AI Task Team determined that the establishment of a Strategic Automation Initiative (SAI) and the expansion of the DOE Technology Transfer program would ensure that AI technology could be used to develop software for the nuclear industry that would have substantial financial payoff to the industry. The SAI includes both long and short term phases. The short-term phase includes projects which would demonstrate that AI can be applied to the nuclear industry safely, and with substantial financial benefit. The long term phase includes projects which would develop AI technologies with specific applicability to the nuclear industry that would not be developed by people working in any other industry

  14. Artificial intelligence technologies for power system operations. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Talukdar, S.N.; Cardozo, E.

    1986-01-01

    Researchers in this study examined the potential of artificial intelligence (AI) technologies for improving problem-solving strategies in 16 power system operations. To demonstrate the use of AI in the area they considered most promising, contingency selection-security assessment, they also developed two programs - one to simulate network protection schemes, the other to diagnose faults.

  15. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

    Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

  16. Natural language processing in psychiatry. Artificial intelligence technology and psychopathology.

    Science.gov (United States)

    Garfield, D A; Rapp, C; Evens, M

    1992-04-01

    The potential benefit of artificial intelligence (AI) technology as a tool of psychiatry has not been well defined. In this essay, the technology of natural language processing and its position with regard to the two main schools of AI is clearly outlined. Past experiments utilizing AI techniques in understanding psychopathology are reviewed. Natural language processing can automate the analysis of transcripts and can be used in modeling theories of language comprehension. In these ways, it can serve as a tool in testing psychological theories of psychopathology and can be used as an effective tool in empirical research on verbal behavior in psychopathology.

  17. Artificial Intelligence.

    Science.gov (United States)

    Wash, Darrel Patrick

    1989-01-01

    Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

  18. Intelligence in Artificial Intelligence

    OpenAIRE

    Datta, Shoumen Palit Austin

    2016-01-01

    The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

  19. The application of artificial intelligence technology to aeronautical system design

    Science.gov (United States)

    Bouchard, E. E.; Kidwell, G. H.; Rogan, J. E.

    1988-01-01

    This paper describes the automation of one class of aeronautical design activity using artificial intelligence and advanced software techniques. Its purpose is to suggest concepts, terminology, and approaches that may be useful in enhancing design automation. By understanding the basic concepts and tasks in design, and the technologies that are available, it will be possible to produce, in the future, systems whose capabilities far exceed those of today's methods. Some of the tasks that will be discussed have already been automated and are in production use, resulting in significant productivity benefits. The concepts and techniques discussed are applicable to all design activity, though aeronautical applications are specifically presented.

  20. Quo Vadis, Artificial Intelligence?

    OpenAIRE

    Berrar, Daniel; Sato, Naoyuki; Schuster, Alfons

    2010-01-01

    Since its conception in the mid 1950s, artificial intelligence with its great ambition to understand and emulate intelligence in natural and artificial environments alike is now a truly multidisciplinary field that reaches out and is inspired by a great diversity of other fields. Rapid advances in research and technology in various fields have created environments into which artificial intelligence could embed itself naturally and comfortably. Neuroscience with its desire to understand nervou...

  1. Analysis of Computer-Aided and Artificial Intelligence Technologies and Solutions in Service Industries in Russia

    OpenAIRE

    Rezanov, Vladislav

    2013-01-01

    The primary objective of this research study was to investigate the relationship between Computer-Aided and Artificial Intelligence Technologies and customer satisfaction in the context of businesses in Russia. The research focuses on methods of Artificial Intelligence technology application in business and its effect on customer satisfaction. The researcher introduces Artificial Intelligence and studies the forecasting approaches in relation to business operations. The rese...

  2. ARTIFICIAL INTELLIGENCE CAPABILITIES FOR INCREASING ORGANIZATIONAL-TECHNOLOGICAL RELIABILITY OF CONSTRUCTION

    OpenAIRE

    Ginzburg Alexander Vital`evich; Ryzhkova Anastasiya Igorevna

    2018-01-01

    The technology of artificial intelligence is actively being mastered in the world but there is not much talk about the capabilities of artificial intelligence in construction industry and this issue requires additional elaboration. As a rule, the decision to invest in a particular construction project is made on the basis of an assessment of the organizational and technological reliability of the construction process. Artificial intelligence can be a convenient quality tool for identifying, a...

  3. Artificial Intelligence.

    Science.gov (United States)

    Lawrence, David R; Palacios-González, César; Harris, John

    2016-04-01

    It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries-namely, with regard to artificially (super)intelligent persons-but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve.

  4. Artificial Intelligence in Astronomy

    Science.gov (United States)

    Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

    2010-12-01

    From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

  5. Automatic food detection in egocentric images using artificial intelligence technology

    Science.gov (United States)

    Our objective was to develop an artificial intelligence (AI)-based algorithm which can automatically detect food items from images acquired by an egocentric wearable camera for dietary assessment. To study human diet and lifestyle, large sets of egocentric images were acquired using a wearable devic...

  6. Artificial Consciousness or Artificial Intelligence

    OpenAIRE

    Spanache Florin

    2017-01-01

    Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus a...

  7. Quo Vadis, Artificial Intelligence?

    Directory of Open Access Journals (Sweden)

    Daniel Berrar

    2010-01-01

    Full Text Available Since its conception in the mid 1950s, artificial intelligence with its great ambition to understand and emulate intelligence in natural and artificial environments alike is now a truly multidisciplinary field that reaches out and is inspired by a great diversity of other fields. Rapid advances in research and technology in various fields have created environments into which artificial intelligence could embed itself naturally and comfortably. Neuroscience with its desire to understand nervous systems of biological organisms and systems biology with its longing to comprehend, holistically, the multitude of complex interactions in biological systems are two such fields. They target ideals artificial intelligence has dreamt about for a long time including the computer simulation of an entire biological brain or the creation of new life forms from manipulations of cellular and genetic information in the laboratory. The scope for artificial intelligence in neuroscience and systems biology is extremely wide. This article investigates the standing of artificial intelligence in relation to neuroscience and systems biology and provides an outlook at new and exciting challenges for artificial intelligence in these fields. These challenges include, but are not necessarily limited to, the ability to learn from other projects and to be inventive, to understand the potential and exploit novel computing paradigms and environments, to specify and adhere to stringent standards and robust statistical frameworks, to be integrative, and to embrace openness principles.

  8. Web Intelligence and Artificial Intelligence in Education

    Science.gov (United States)

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  9. ARTIFICIAL INTELLIGENCE CAPABILITIES FOR INCREASING ORGANIZATIONAL-TECHNOLOGICAL RELIABILITY OF CONSTRUCTION

    Directory of Open Access Journals (Sweden)

    Ginzburg Alexander Vital`evich

    2018-02-01

    Full Text Available The technology of artificial intelligence is actively being mastered in the world but there is not much talk about the capabilities of artificial intelligence in construction industry and this issue requires additional elaboration. As a rule, the decision to invest in a particular construction project is made on the basis of an assessment of the organizational and technological reliability of the construction process. Artificial intelligence can be a convenient quality tool for identifying, analyzing and subsequent control of the “pure” risks of the construction project, which not only will significantly reduce the financial and time expenditures for the investor’s decision-making process but also improve the organizational-technological reliability of the construction process as a whole. Subject: the algorithm of creation of artificial intelligence in the field of identification and analysis of potential risk events is presented, which will facilitate the creation of an independent analytical system for different stages of construction production: from the sketch to the working documentation and conduction of works directly on the construction site. Research objectives: the study of the possibility, methods and planning of the algorithm of works for creation of artificial intelligence technology in order to improve the organizational-technological reliability of the construction process. Materials and methods: the developments in the field of improving the organizational and technological reliability of construction were studied through the analysis and control of potential “pure” risks of the construction project, and the work was also carried out to integrate the technology of artificial intelligence into the area being studied. Results: An algorithm for creating artificial intelligence in the field of identification of potential “pure” risks of construction projects was presented. Conclusions: the obtained results are useful

  10. Imagining the thinking machine: technological myths and the rise of Artificial Intelligence

    OpenAIRE

    Natale, Simone; Ballatore, Andrea

    2017-01-01

    This article discusses the role of technological myths in the development of Artificial Intelligence (AI) technologies from 1950s to the early 1970s. It shows how the rise of AI was accompanied by the construction of a powerful cultural myth: the creation of a thinking machine, which would be able to perfectly simulate the cognitive faculties of the human mind. Based on a content analysis of articles on Artificial Intelligence published in two magazines, the Scientific American and the New Sc...

  11. Automatic food detection in egocentric images using artificial intelligence technology.

    Science.gov (United States)

    Jia, Wenyan; Li, Yuecheng; Qu, Ruowei; Baranowski, Thomas; Burke, Lora E; Zhang, Hong; Bai, Yicheng; Mancino, Juliet M; Xu, Guizhi; Mao, Zhi-Hong; Sun, Mingui

    2018-03-26

    To develop an artificial intelligence (AI)-based algorithm which can automatically detect food items from images acquired by an egocentric wearable camera for dietary assessment. To study human diet and lifestyle, large sets of egocentric images were acquired using a wearable device, called eButton, from free-living individuals. Three thousand nine hundred images containing real-world activities, which formed eButton data set 1, were manually selected from thirty subjects. eButton data set 2 contained 29 515 images acquired from a research participant in a week-long unrestricted recording. They included both food- and non-food-related real-life activities, such as dining at both home and restaurants, cooking, shopping, gardening, housekeeping chores, taking classes, gym exercise, etc. All images in these data sets were classified as food/non-food images based on their tags generated by a convolutional neural network. A cross data-set test was conducted on eButton data set 1. The overall accuracy of food detection was 91·5 and 86·4 %, respectively, when one-half of data set 1 was used for training and the other half for testing. For eButton data set 2, 74·0 % sensitivity and 87·0 % specificity were obtained if both 'food' and 'drink' were considered as food images. Alternatively, if only 'food' items were considered, the sensitivity and specificity reached 85·0 and 85·8 %, respectively. The AI technology can automatically detect foods from low-quality, wearable camera-acquired real-world egocentric images with reasonable accuracy, reducing both the burden of data processing and privacy concerns.

  12. Applying artificial intelligence to astronomical databases - a surveyof applicable technology.

    Science.gov (United States)

    Rosenthal, D. A.

    This paper surveys several emerging technologies which are relevant to astronomical database issues such as interface technology, internal database representation, and intelligent data reduction aids. Among the technologies discussed are natural language understanding, frame and object representations, planning, pattern analysis, machine learning and the nascent study of simulated neural nets. These techniques will become increasingly important for astronomical research, and in particular, for applications with large databases.

  13. The 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies

    Science.gov (United States)

    Hostetter, Carl F. (Editor)

    1995-01-01

    This publication comprises the papers presented at the 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland, on May 9-11, 1995. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  14. Trends in Artificial Intelligence.

    Science.gov (United States)

    Hayes, Patrick

    1978-01-01

    Discusses the foundations of artificial intelligence as a science and the types of answers that may be given to the question, "What is intelligence?" The paradigms of artificial intelligence and general systems theory are compared. (Author/VT)

  15. Artificial Intelligence Information Sources for the Beginner and Expert

    Science.gov (United States)

    1991-05-01

    Electronics Engineers) sponsors a number of artificial intelli- gence conferences, including the Conference on Artificial Intelligence Applications and the...Artificial Intelligence and Legal Reasoning Intelligent Tutoring Systems Artificial Intelligence Applications for Nil- Technologies itary Logistics

  16. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2003-01-01

    As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.

  17. Artificial intelligence in nanotechnology

    International Nuclear Information System (INIS)

    Sacha, G M; Varona, P

    2013-01-01

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines. (topical review)

  18. Artificial intelligence in nanotechnology.

    Science.gov (United States)

    Sacha, G M; Varona, P

    2013-11-15

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  19. Artificial intelligence executive summary

    International Nuclear Information System (INIS)

    Wamsley, S.J.; Purvis, E.E. III

    1984-01-01

    Artificial intelligence (AI) is a high technology field that can be used to provide problem solving diagnosis, guidance and for support resolution of problems. It is not a stand alone discipline, but can also be applied to develop data bases for retention of the expertise that is required for its own knowledge base. This provides a way to retain knowledge that otherwise may be lost. Artificial Intelligence Methodology can provide an automated construction management decision support system, thereby restoring the manager's emphasis to project management

  20. Artificial intelligence within AFSC

    Science.gov (United States)

    Gersh, Mark A.

    1990-01-01

    Information on artificial intelligence research in the Air Force Systems Command is given in viewgraph form. Specific research that is being conducted at the Rome Air Development Center, the Space Technology Center, the Human Resources Laboratory, the Armstrong Aerospace Medical Research Laboratory, the Armamant Laboratory, and the Wright Research and Development Center is noted.

  1. Using Computer-Based Artificial Intelligence Technology to Help ESL Students.

    Science.gov (United States)

    Adams, Dennis M.

    This paper discusses ways in which artificial intelligence (AI) technologies may be used to aid students for whom English is a second language in the development of language and reading skills, and asserts that the coupling of technology with close adult-teacher contacts within a context of cultural precedents and social rewards is an important…

  2. Soft computing in artificial intelligence

    CERN Document Server

    Matson, Eric

    2014-01-01

    This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, ind...

  3. Electron beam lithographic modeling assisted by artificial intelligence technology

    Science.gov (United States)

    Nakayamada, Noriaki; Nishimura, Rieko; Miura, Satoru; Nomura, Haruyuki; Kamikubo, Takashi

    2017-07-01

    We propose a new concept of tuning a point-spread function (a "kernel" function) in the modeling of electron beam lithography using the machine learning scheme. Normally in the work of artificial intelligence, the researchers focus on the output results from a neural network, such as success ratio in image recognition or improved production yield, etc. In this work, we put more focus on the weights connecting the nodes in a convolutional neural network, which are naturally the fractions of a point-spread function, and take out those weighted fractions after learning to be utilized as a tuned kernel. Proof-of-concept of the kernel tuning has been demonstrated using the examples of proximity effect correction with 2-layer network, and charging effect correction with 3-layer network. This type of new tuning method can be beneficial to give researchers more insights to come up with a better model, yet it might be too early to be deployed to production to give better critical dimension (CD) and positional accuracy almost instantly.

  4. Intelligence, Artificial and Otherwise

    OpenAIRE

    Chace, William M.

    1984-01-01

    I rise now to speak with the assumption that all of you know very well what I am going to say. I am the humanist here, the professor of English. We humanists, when asked to speak on questions of science and technology, are notorious for offering an embarrassed and ignorant respect toward those matters, a respect, however, which can all too quickly degenerate into insolent condescension. Face to face with the reality of computer technology, say, or with "artificial intelligence," we humanists ...

  5. Artificial intelligence

    OpenAIRE

    Duda, Antonín

    2009-01-01

    Abstract : Issue of this work is to acquaint the reader with the history of artificial inteligence, esspecialy branch of chess computing. Main attention is given to progress from fifties to the present. The work also deals with fighting chess programs against each other, and against human opponents. The greatest attention is focused on 1997 and duel Garry Kasparov against chess program Deep Blue. The work is divided into chapters according to chronological order.

  6. Prediction of shipboard electromagnetic interference (EMI) problems using artificial intelligence (AI) technology

    Science.gov (United States)

    Swanson, David J.

    1990-08-01

    The electromagnetic interference prediction problem is characteristically ill-defined and complicated. Severe EMI problems are prevalent throughout the U.S. Navy, causing both expected and unexpected impacts on the operational performance of electronic combat systems onboard ships. This paper focuses on applying artificial intelligence (AI) technology to the prediction of ship related electromagnetic interference (EMI) problems.

  7. Artificial intelligence to maximise contributions of nondestructive evaluation to materials science and technology

    International Nuclear Information System (INIS)

    Baldev Raj; Rajagopalan, C.

    1996-01-01

    The paper reviews the current status of Nondestructive Testing and Evaluation (NDT and E), in relation to materials science and technology. It suggests a path of growth for Nondestructive Testing and Evaluation, taking into account the increase in data and knowledge. We recommend Artificial Intelligence (AI) concepts for maximising the contributions of and benefits from, Nondestructive Testing and Evaluation. (author)

  8. Installation and evaluation of a nuclear power plant operator advisor based on artificial intelligence technology

    International Nuclear Information System (INIS)

    Hajek, B.K.; Miller, D.W.

    1989-01-01

    This report discusses the following topics on a Nuclear Power Plant operator advisor based on artificial Intelligence Technology; Workstation conversion; Software Conversion; V ampersand V Program Development Development; Simulator Interface Development; Knowledge Base Expansion; Dynamic Testing; Database Conversion; Installation at the Perry Simulator; Evaluation of Operator Interaction; Design of Man-Machine Interface; and Design of Maintenance Facility

  9. Prediction of shipboard electromagnetic interference (EMI) problems using artificial intelligence (AI) technology

    Science.gov (United States)

    Swanson, David J.

    1990-01-01

    The electromagnetic interference prediction problem is characteristically ill-defined and complicated. Severe EMI problems are prevalent throughout the U.S. Navy, causing both expected and unexpected impacts on the operational performance of electronic combat systems onboard ships. This paper focuses on applying artificial intelligence (AI) technology to the prediction of ship related electromagnetic interference (EMI) problems.

  10. Artificial intelligence and exponential technologies business models evolution and new investment opportunities

    CERN Document Server

    Corea, Francesco

    2017-01-01

    Artificial Intelligence is a huge breakthrough technology that is changing our world. It requires some degrees of technical skills to be developed and understood, so in this book we are going to first of all define AI and categorize it with a non-technical language. We will explain how we reached this phase and what historically happened to artificial intelligence in the last century. Recent advancements in machine learning, neuroscience, and artificial intelligence technology will be addressed, and new business models introduced for and by artificial intelligence research will be analyzed. Finally, we will describe the investment landscape, through the quite comprehensive study of almost 14,000 AI companies and we will discuss important features and characteristics of both AI investors as well as investments. This is the “Internet of Thinks” era. AI is revolutionizing the world we live in. It is augmenting the human experiences, and it targets to amplify human intelligence in a future not so distant from...

  11. Protein subcellular localization prediction using artificial intelligence technology.

    Science.gov (United States)

    Nair, Rajesh; Rost, Burkhard

    2008-01-01

    Proteins perform many important tasks in living organisms, such as catalysis of biochemical reactions, transport of nutrients, and recognition and transmission of signals. The plethora of aspects of the role of any particular protein is referred to as its "function." One aspect of protein function that has been the target of intensive research by computational biologists is its subcellular localization. Proteins must be localized in the same subcellular compartment to cooperate toward a common physiological function. Aberrant subcellular localization of proteins can result in several diseases, including kidney stones, cancer, and Alzheimer's disease. To date, sequence homology remains the most widely used method for inferring the function of a protein. However, the application of advanced artificial intelligence (AI)-based techniques in recent years has resulted in significant improvements in our ability to predict the subcellular localization of a protein. The prediction accuracy has risen steadily over the years, in large part due to the application of AI-based methods such as hidden Markov models (HMMs), neural networks (NNs), and support vector machines (SVMs), although the availability of larger experimental datasets has also played a role. Automatic methods that mine textual information from the biological literature and molecular biology databases have considerably sped up the process of annotation for proteins for which some information regarding function is available in the literature. State-of-the-art methods based on NNs and HMMs can predict the presence of N-terminal sorting signals extremely accurately. Ab initio methods that predict subcellular localization for any protein sequence using only the native amino acid sequence and features predicted from the native sequence have shown the most remarkable improvements. The prediction accuracy of these methods has increased by over 30% in the past decade. The accuracy of these methods is now on par with

  12. Intelligence: Real or artificial?

    OpenAIRE

    Schlinger, Henry D.

    1992-01-01

    Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally r...

  13. Brain Intelligence: Go Beyond Artificial Intelligence

    OpenAIRE

    Lu, Huimin; Li, Yujie; Chen, Min; Kim, Hyoungseop; Serikawa, Seiichi

    2017-01-01

    Artificial intelligence (AI) is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan's economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India. The attention has been focused mainly on developing new artificial intelligence information communication ...

  14. Intelligence: Real or artificial?

    Science.gov (United States)

    Schlinger, Henry D.

    1992-01-01

    Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally referred to behavior-environment relations and not to inferred internal structures and processes. It is concluded that if workers in artificial intelligence are to succeed in their general goal, then they must design machines that are adaptive, that is, that can learn. Thus, artificial intelligence researchers must discard their essentialist model of natural intelligence and adopt a selectionist model instead. Such a strategic change should lead them to the science of behavior analysis. PMID:22477051

  15. Medical applications of artificial intelligence

    CERN Document Server

    Agah, Arvin

    2013-01-01

    Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Ap

  16. Application of Artificial Intelligence technology to the analysis and synthesis of reliable software systems

    Science.gov (United States)

    Wild, Christian; Eckhardt, Dave

    1987-01-01

    The development of a methodology for the production of highly reliable software is one of the greatest challenges facing the computer industry. Meeting this challenge will undoubtably involve the integration of many technologies. This paper describes the use of Artificial Intelligence technologies in the automated analysis of the formal algebraic specifications of abstract data types. These technologies include symbolic execution of specifications using techniques of automated deduction and machine learning through the use of examples. On-going research into the role of knowledge representation and problem solving in the process of developing software is also discussed.

  17. Principles of artificial intelligence

    CERN Document Server

    Nilsson, Nils J

    1980-01-01

    A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of th

  18. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2010-01-01

    Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.New to the Second EditionNew chapter on Bayesian network classifiersNew section on object-oriente

  19. Applying artificial intelligence technology to support decision-making in nursing: A case study in Taiwan.

    Science.gov (United States)

    Liao, Pei-Hung; Hsu, Pei-Ti; Chu, William; Chu, Woei-Chyn

    2015-06-01

    This study applied artificial intelligence to help nurses address problems and receive instructions through information technology. Nurses make diagnoses according to professional knowledge, clinical experience, and even instinct. Without comprehensive knowledge and thinking, diagnostic accuracy can be compromised and decisions may be delayed. We used a back-propagation neural network and other tools for data mining and statistical analysis. We further compared the prediction accuracy of the previous methods with an adaptive-network-based fuzzy inference system and the back-propagation neural network, identifying differences in the questions and in nurse satisfaction levels before and after using the nursing information system. This study investigated the use of artificial intelligence to generate nursing diagnoses. The percentage of agreement between diagnoses suggested by the information system and those made by nurses was as much as 87 percent. When patients are hospitalized, we can calculate the probability of various nursing diagnoses based on certain characteristics. © The Author(s) 2013.

  20. How People Interact with Technology based on Natural and Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Vasile MAZILESCU

    2017-04-01

    Full Text Available This paper aims to analyse the different forms of intelligence within organizations in a systemic and inclusive vision, in order to design an integrated environment based on Artificial Intelligence (AI and Collective Intelligence (CI. This way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow, of connecting people with a series of content management knowledge (taxonomies and documents classification, ontologies or thesauri, search engines, portals, to the current approaches of connecting people on the use (automatic of operational knowledge to solve problems and make decisions based on intellectual cooperation. Few technologies have the big potential to review how we live, move, and work. Artificial intelligence (AI is nowdays equivalent of electricity and the Internet. AI is expected to bring massive shifts in how people perceive and interact with technology, with machines performing a wider range of tasks, in many cases doing a better job than humans.

  1. Artificial intelligence in medicine.

    Science.gov (United States)

    Ramesh, A N; Kambhampati, C; Monson, J R T; Drew, P J

    2004-09-01

    Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting.

  2. Artificial intelligence in medicine.

    Science.gov (United States)

    Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

    2004-01-01

    INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. RESULTS: The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. DISCUSSION: Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting. PMID:15333167

  3. Artificial intelligence in cardiology

    OpenAIRE

    Bonderman, Diana

    2017-01-01

    Summary Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiol...

  4. Artificial intelligence in medicine.

    OpenAIRE

    Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

    2004-01-01

    INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of ...

  5. Sustainable Technology Analysis of Artificial Intelligence Using Bayesian and Social Network Models

    Directory of Open Access Journals (Sweden)

    Juhwan Kim

    2018-01-01

    Full Text Available Recent developments in artificial intelligence (AI have led to a significant increase in the use of AI technologies. Many experts are researching and developing AI technologies in their respective fields, often submitting papers and patent applications as a result. In particular, owing to the characteristics of the patent system that is used to protect the exclusive rights to registered technology, patent documents contain detailed information on the developed technology. Therefore, in this study, we propose a statistical method for analyzing patent data on AI technology to improve our understanding of sustainable technology in the field of AI. We collect patent documents that are related to AI technology, and then analyze the patent data to identify sustainable AI technology. In our analysis, we develop a statistical method that combines social network analysis and Bayesian modeling. Based on the results of the proposed method, we provide a technological structure that can be applied to understand the sustainability of AI technology. To show how the proposed method can be applied to a practical problem, we apply the technological structure to a case study in order to analyze sustainable AI technology.

  6. Artificial Intelligence and brain.

    Science.gov (United States)

    Shapshak, Paul

    2018-01-01

    From the start, Kurt Godel observed that computer and brain paradigms were considered on a par by researchers and that researchers had misunderstood his theorems. He hailed with displeasure that the brain transcends computers. In this brief article, we point out that Artificial Intelligence (AI) comprises multitudes of human-made methodologies, systems, and languages, and implemented with computer technology. These advances enhance development in the electron and quantum realms. In the biological realm, animal neurons function, also utilizing electron flow, and are products of evolution. Mirror neurons are an important paradigm in neuroscience research. Moreover, the paradigm shift proposed here - 'hall of mirror neurons' - is a potentially further productive research tactic. These concepts further expand AI and brain research.

  7. Artificial intelligence in hematology.

    Science.gov (United States)

    Zini, Gina

    2005-10-01

    Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

  8. Artificial intelligence in cardiology.

    Science.gov (United States)

    Bonderman, Diana

    2017-12-01

    Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiology are reviewed. The text also touches on the ethical issues and speculates on the future roles of automated algorithms versus clinicians in cardiology and medicine in general.

  9. How People Interact with Technology based on Natural and Artificial Intelligence

    OpenAIRE

    Vasile MAZILESCU

    2017-01-01

    This paper aims to analyse the different forms of intelligence within organizations in a systemic and inclusive vision, in order to design an integrated environment based on Artificial Intelligence (AI) and Collective Intelligence (CI). This way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow), of connecting people with...

  10. Artificial Intelligence and Information Retrieval.

    Science.gov (United States)

    Teodorescu, Ioana

    1987-01-01

    Compares artificial intelligence and information retrieval paradigms for natural language understanding, reviews progress to date, and outlines the applicability of artificial intelligence to question answering systems. A list of principal artificial intelligence software for database front end systems is appended. (CLB)

  11. Generality in Artificial Intelligence

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 3. Generality in Artificial Intelligence. John McCarthy. Classics Volume 19 Issue 3 March 2014 pp 283-296. Fulltext. Click here to view fulltext PDF. Permanent link: http://www.ias.ac.in/article/fulltext/reso/019/03/0283-0296. Author Affiliations.

  12. Artificial Intelligence and CALL.

    Science.gov (United States)

    Underwood, John H.

    The potential application of artificial intelligence (AI) to computer-assisted language learning (CALL) is explored. Two areas of AI that hold particular interest to those who deal with language meaning--knowledge representation and expert systems, and natural-language processing--are described and examples of each are presented. AI contribution…

  13. Generality in Artificial Intelligence

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 3. Generality in Artificial Intelligence. John McCarthy. Classics Volume 19 Issue 3 March 2014 pp 283-296. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/019/03/0283-0296. Author Affiliations.

  14. The Artificial Intelligence Applications to Learning Programme.

    Science.gov (United States)

    Williams, Noel

    1992-01-01

    Explains the Artificial Intelligence Applications to Learning Programme, which was developed in the United Kingdom to explore and accelerate the use of artificial intelligence (AI) technologies in learning in both the educational and industrial sectors. Highlights include program evaluation, marketing, ownership of information, consortia, and cost…

  15. Artificial intelligence technology assessment for the US Army Depot System Command

    Energy Technology Data Exchange (ETDEWEB)

    Pennock, K A

    1991-07-01

    This assessment of artificial intelligence (AI) has been prepared for the US Army's Depot System Command (DESCOM) by Pacific Northwest Laboratory. The report describes several of the more promising AI technologies, focusing primarily on knowledge-based systems because they have been more successful in commercial applications than any other AI technique. The report also identifies potential Depot applications in the areas of procedural support, scheduling and planning, automated inspection, training, diagnostics, and robotic systems. One of the principal objectives of the report is to help decisionmakers within DESCOM to evaluate AI as a possible tool for solving individual depot problems. The report identifies a number of factors that should be considered in such evaluations. 22 refs.

  16. Rapid and accurate intraoperative pathological diagnosis by artificial intelligence with deep learning technology.

    Science.gov (United States)

    Zhang, Jing; Song, Yanlin; Xia, Fan; Zhu, Chenjing; Zhang, Yingying; Song, Wenpeng; Xu, Jianguo; Ma, Xuelei

    2017-09-01

    Frozen section is widely used for intraoperative pathological diagnosis (IOPD), which is essential for intraoperative decision making. However, frozen section suffers from some drawbacks, such as time consuming and high misdiagnosis rate. Recently, artificial intelligence (AI) with deep learning technology has shown bright future in medicine. We hypothesize that AI with deep learning technology could help IOPD, with a computer trained by a dataset of intraoperative lesion images. Evidences supporting our hypothesis included the successful use of AI with deep learning technology in diagnosing skin cancer, and the developed method of deep-learning algorithm. Large size of the training dataset is critical to increase the diagnostic accuracy. The performance of the trained machine could be tested by new images before clinical use. Real-time diagnosis, easy to use and potential high accuracy were the advantages of AI for IOPD. In sum, AI with deep learning technology is a promising method to help rapid and accurate IOPD. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Artificial Intelligence and Economic Theories

    OpenAIRE

    Marwala, Tshilidzi; Hurwitz, Evan

    2017-01-01

    The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence such as the swarming of birds, the working of the brain and the pathfinding of the ants. These techniques have impact on economic theories. This book studies the impact of artificial intelligence on economic theories, a subject that has not been extensively studied. The theories that...

  18. Artificial intelligence and the future.

    Science.gov (United States)

    Clocksin, William F

    2003-08-15

    We consider some of the ideas influencing current artificial-intelligence research and outline an alternative conceptual framework that gives priority to social relationships as a key component and constructor of intelligent behaviour. The framework starts from Weizenbaum's observation that intelligence manifests itself only relative to specific social and cultural contexts. This is in contrast to a prevailing view, which sees intelligence as an abstract capability of the individual mind based on a mechanism for rational thought. The new approach is not based on the conventional idea that the mind is a rational processor of symbolic information, nor does it require the idea that thought is a kind of abstract problem solving with a semantics that is independent of its embodiment. Instead, priority is given to affective and social responses that serve to engage the whole agent in the life of the communities in which it participates. Intelligence is seen not as the deployment of capabilities for problem solving, but as constructed by the continual, ever-changing and unfinished engagement with the social group within the environment. The construction of the identity of the intelligent agent involves the appropriation or 'taking up' of positions within the conversations and narratives in which it participates. Thus, the new approach argues that the intelligent agent is shaped by the meaning ascribed to experience, by its situation in the social matrix, and by practices of self and of relationship into which intelligent life is recruited. This has implications for the technology of the future, as, for example, classic artificial intelligence models such as goal-directed problem solving are seen as special cases of narrative practices instead of as ontological foundations.

  19. The Nexus between Artificial Intelligence and Economics

    OpenAIRE

    van de Gevel, A.J.W.; Noussair, C.N.

    2012-01-01

    This book is organized as follows. Section 2 introduces the notion of the Singularity, a stage in development in which technological progress and economic growth increase at a near-infinite rate. Section 3 describes what artificial intelligence is and how it has been applied. Section 4 considers artificial happiness and the likelihood that artificial intelligence might increase human happiness. Section 5 discusses some prominent related concepts and issues. Section 6 describes the use of arti...

  20. Essentials of artificial intelligence

    CERN Document Server

    Ginsberg, Matt

    1993-01-01

    Since its publication, Essentials of Artificial Intelligence has beenadopted at numerous universities and colleges offering introductory AIcourses at the graduate and undergraduate levels. Based on the author'scourse at Stanford University, the book is an integrated, cohesiveintroduction to the field. The author has a fresh, entertaining writingstyle that combines clear presentations with humor and AI anecdotes. At thesame time, as an active AI researcher, he presents the materialauthoritatively and with insight that reflects a contemporary, first hand

  1. Impacts of Artificial Intelligence

    OpenAIRE

    Trappl, R.

    1986-01-01

    This book, which is intended to serve as the first stage in an iterative process of detecting, predicting, and assessing the impacts of Artificial Intelligence opens with a short "one-hour course" in AI, which is intended to provide a nontechnical informative introduction to the material which follows. Next comes an overview chapter which is based on an extensive literature search, the position papers, and discussions. The next section of the book contains position papers whose richness...

  2. Ethical Artificial Intelligence

    OpenAIRE

    Hibbard, Bill

    2014-01-01

    This book-length article combines several peer reviewed papers and new material to analyze the issues of ethical artificial intelligence (AI). The behavior of future AI systems can be described by mathematical equations, which are adapted to analyze possible unintended AI behaviors and ways that AI designs can avoid them. This article makes the case for utility-maximizing agents and for avoiding infinite sets in agent definitions. It shows how to avoid agent self-delusion using model-based ut...

  3. Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction.

    Science.gov (United States)

    Park, Seong Ho; Han, Kyunghwa

    2018-03-01

    The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical images. Adoption of an artificial intelligence tool in clinical practice requires careful confirmation of its clinical utility. Herein, the authors explain key methodology points involved in a clinical evaluation of artificial intelligence technology for use in medicine, especially high-dimensional or overparameterized diagnostic or predictive models in which artificial deep neural networks are used, mainly from the standpoints of clinical epidemiology and biostatistics. First, statistical methods for assessing the discrimination and calibration performances of a diagnostic or predictive model are summarized. Next, the effects of disease manifestation spectrum and disease prevalence on the performance results are explained, followed by a discussion of the difference between evaluating the performance with use of internal and external datasets, the importance of using an adequate external dataset obtained from a well-defined clinical cohort to avoid overestimating the clinical performance as a result of overfitting in high-dimensional or overparameterized classification model and spectrum bias, and the essentials for achieving a more robust clinical evaluation. Finally, the authors review the role of clinical trials and observational outcome studies for ultimate clinical verification of diagnostic or predictive artificial intelligence tools through patient outcomes, beyond performance metrics, and how to design such studies. © RSNA, 2018.

  4. Instructional Applications of Artificial Intelligence.

    Science.gov (United States)

    Halff, Henry M.

    1986-01-01

    Surveys artificial intelligence and the development of computer-based tutors and speculates on the future of artificial intelligence in education. Includes discussion of the definitions of knowledge, expert systems (computer systems that solve tough technical problems), intelligent tutoring systems (ITS), and specific ITSs such as GUIDON, MYCIN,…

  5. Artificial Intelligence in Maintenance: Synthesis of Technical Issues.

    Science.gov (United States)

    1985-10-01

    Marrone, M. P., & Gaynor M. W. (1984). IN-ATE/2: Interpretating high-level fault modes. In Proceedings of the First Conference on Artificial Intelligence Applications . IEEE...York: Springer-Verlag. Coppola, A. (1984). Artificial intelligence applications to maintenance. In Artificial Intelligence in Maintenance: Proceedings...Army Research and Technology Laboratories, Applied Technology Laboratory. Dallman, B. (1984). AFHRL program for artificial intelligence applications to

  6. Artificial Intelligence and Public Healthcare Service Innovation

    DEFF Research Database (Denmark)

    Sun, Tara Qian; Medaglia, Rony

    Public healthcare ecosystems are complex networks of diverse actors that are subject to pressures to innovate, also a result of technological advancements. Artificial Intelligence (AI), in particular, has the potential to transform the way hospitals, doctors, patients, government agencies...

  7. Uncertainty in artificial intelligence

    CERN Document Server

    Kanal, LN

    1986-01-01

    How to deal with uncertainty is a subject of much controversy in Artificial Intelligence. This volume brings together a wide range of perspectives on uncertainty, many of the contributors being the principal proponents in the controversy.Some of the notable issues which emerge from these papers revolve around an interval-based calculus of uncertainty, the Dempster-Shafer Theory, and probability as the best numeric model for uncertainty. There remain strong dissenting opinions not only about probability but even about the utility of any numeric method in this context.

  8. Artificial intelligence in cardiology

    Directory of Open Access Journals (Sweden)

    Srishti Sharma

    2017-01-01

    Full Text Available Artificial intelligence (AI provides machines with the ability to learn and respond the way humans do and is also referred to as machine learning. The step to building an AI system is to provide the data to learn from so that it can map relations between inputs and outputs and set up parameters such as “weights”/decision boundaries to predict responses for inputs in the future. Then, the model is tested on a second data set. This article outlines the promise this analytic approach has in medicine and cardiology.

  9. Generative Artificial Intelligence : Philosophy and Theory of Artificial Intelligence

    NARCIS (Netherlands)

    van der Zant, Tijn; Kouw, Matthijs; Schomaker, Lambertus; Mueller, Vincent C.

    2013-01-01

    The closed systems of contemporary Artificial Intelligence do not seem to lead to intelligent machines in the near future. What is needed are open-ended systems with non-linear properties in order to create interesting properties for the scaffolding of an artificial mind. Using post-structuralistic

  10. Artificial Intelligence Applications for Education: Promise, ...Promises.

    Science.gov (United States)

    Adams, Dennis M.; Hamm, Mary

    1988-01-01

    Surveys the current status of artificial intelligence (AI) technology. Discusses intelligent tutoring systems, robotics, and applications for educators. Likens the status of AI at present to that of aviation in the very early 1900s. States that educators need to be involved in future debates concerning AI. (CW)

  11. Artificial intelligence in medicine.

    Science.gov (United States)

    Hamet, Pavel; Tremblay, Johanne

    2017-04-01

    Artificial Intelligence (AI) is a general term that implies the use of a computer to model intelligent behavior with minimal human intervention. AI is generally accepted as having started with the invention of robots. The term derives from the Czech word robota, meaning biosynthetic machines used as forced labor. In this field, Leonardo Da Vinci's lasting heritage is today's burgeoning use of robotic-assisted surgery, named after him, for complex urologic and gynecologic procedures. Da Vinci's sketchbooks of robots helped set the stage for this innovation. AI, described as the science and engineering of making intelligent machines, was officially born in 1956. The term is applicable to a broad range of items in medicine such as robotics, medical diagnosis, medical statistics, and human biology-up to and including today's "omics". AI in medicine, which is the focus of this review, has two main branches: virtual and physical. The virtual branch includes informatics approaches from deep learning information management to control of health management systems, including electronic health records, and active guidance of physicians in their treatment decisions. The physical branch is best represented by robots used to assist the elderly patient or the attending surgeon. Also embodied in this branch are targeted nanorobots, a unique new drug delivery system. The societal and ethical complexities of these applications require further reflection, proof of their medical utility, economic value, and development of interdisciplinary strategies for their wider application. Copyright © 2017. Published by Elsevier Inc.

  12. In Pursuit of Artificial Intelligence.

    Science.gov (United States)

    Watstein, Sarah; Kesselman, Martin

    1986-01-01

    Defines artificial intelligence and reviews current research in natural language processing, expert systems, and robotics and sensory systems. Discussion covers current commercial applications of artificial intelligence and projections of uses and limitations in library technical and public services, e.g., in cataloging and online information and…

  13. Artificial Intelligence and Language Comprehension.

    Science.gov (United States)

    National Inst. of Education (DHEW), Washington, DC. Basic Skills Group. Learning Div.

    The three papers in this volume concerning artificial intelligence and language comprehension were commissioned by the National Institute of Education to further the understanding of the cognitive processes that enable people to comprehend what they read. The first paper, "Artificial Intelligence and Language Comprehension," by Terry Winograd,…

  14. Artificial intelligence approaches to astronomical observation scheduling

    Science.gov (United States)

    Johnston, Mark D.; Miller, Glenn

    1988-01-01

    Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.

  15. Exploring Artificial Intelligence Utilizing BioArt

    OpenAIRE

    Simou , Panagiota; Tiligadis , Konstantinos; Alexiou , Athanasios

    2013-01-01

    Part 15: First Workshop on Ethics and Philosophy in Artificial Intelligence (EPAI 2013); International audience; While artificial intelligence combined with Bioinformatics and Nanotechnology offers a variety of improvements and a technological and healthcare revolution, Bioartists attempt to replace the traditional artistic medium with biological materials, bio-imaging techniques, bioreactors and several times to treat their own body as an alive canvas. BioArt seems to play the role of a new ...

  16. Why general purpose technologies matter in innovation systems : The case of artificial intelligence in the mining and metal producing industry of Sweden

    OpenAIRE

    Karakaya, Emrah

    2017-01-01

    There are many signs indicating that artificial intelligence – reproduction of the cognitive functions that humans have such as learning and problem solving by machines– has been spreading among various industries. The rise of artificial intelligence – as this article conceptualize as a general purpose technology –   is affecting not only the cognitive dimension of technological innovation systems but also the organizational, institutional and economic dimensions. However, from a technologica...

  17. What Is Artificial Intelligence Anyway?

    Science.gov (United States)

    Kurzweil, Raymond

    1985-01-01

    Examines the past, present, and future status of Artificial Intelligence (AI). Acknowledges the limitations of AI but proposes possible areas of application and further development. Urges a concentration on the unique strengths of machine intelligence rather than a copying of human intelligence. (ML)

  18. The handbook of artificial intelligence

    CERN Document Server

    Barr, Avron

    1982-01-01

    The Handbook of Artificial Intelligence, Volume II focuses on the improvements in artificial intelligence (AI) and its increasing applications, including programming languages, intelligent CAI systems, and the employment of AI in medicine, science, and education. The book first elaborates on programming languages for AI research and applications-oriented AI research. Discussions cover scientific applications, teiresias, applications in chemistry, dependencies and assumptions, AI programming-language features, and LISP. The manuscript then examines applications-oriented AI research in medicine

  19. Artificial Intelligence in Civil Engineering

    OpenAIRE

    Lu, Pengzhen; Chen, Shengyong; Zheng, Yujun

    2012-01-01

    Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applicati...

  20. Improving designer productivity. [artificial intelligence

    Science.gov (United States)

    Hill, Gary C.

    1992-01-01

    Designer and design team productivity improves with skill, experience, and the tools available. The design process involves numerous trials and errors, analyses, refinements, and addition of details. Computerized tools have greatly speeded the analysis, and now new theories and methods, emerging under the label Artificial Intelligence (AI), are being used to automate skill and experience. These tools improve designer productivity by capturing experience, emulating recognized skillful designers, and making the essence of complex programs easier to grasp. This paper outlines the aircraft design process in today's technology and business climate, presenting some of the challenges ahead and some of the promising AI methods for meeting these challenges.

  1. Artificial Intelligence in Space Platforms.

    Science.gov (United States)

    1984-12-01

    computer algorithms, there still appears to be a need for Artificial Inteligence techniques in the navigation area. The reason is that navigaion, in...RD-RI32 679 ARTIFICIAL INTELLIGENCE IN SPACE PLRTFORNSMU AIR FORCE 1/𔃼 INST OF TECH WRIGHT-PRTTERSON AFB OH SCHOOL OF ENGINEERING M A WRIGHT DEC 94...i4 Preface The purpose of this study was to analyze the feasibility of implementing Artificial Intelligence techniques to increase autonomy for

  2. Innovative applications of artificial intelligence

    Science.gov (United States)

    Schorr, Herbert; Rappaport, Alain

    Papers concerning applications of artificial intelligence are presented, covering applications in aerospace technology, banking and finance, biotechnology, emergency services, law, media planning, music, the military, operations management, personnel management, retail packaging, and manufacturing assembly and design. Specific topics include Space Shuttle telemetry monitoring, an intelligent training system for Space Shuttle flight controllers, an expert system for the diagnostics of manufacturing equipment, a logistics management system, a cooling systems design assistant, and a knowledge-based integrated circuit design critic. Additional topics include a hydraulic circuit design assistant, the use of a connector assembly specification expert system to harness detailed assembly process knowledge, a mixed initiative approach to airlift planning, naval battle management decision aids, an inventory simulation tool, a peptide synthesis expert system, and a system for planning the discharging and loading of container ships.

  3. Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

    Science.gov (United States)

    Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

    2012-01-01

    In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

  4. Artificial Intelligence in Civil Engineering

    Directory of Open Access Journals (Sweden)

    Pengzhen Lu

    2012-01-01

    Full Text Available Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering.

  5. Knowledge Based Artificial Augmentation Intelligence Technology: Next Step in Academic Instructional Tools for Distance Learning

    Science.gov (United States)

    Crowe, Dale; LaPierre, Martin; Kebritchi, Mansureh

    2017-01-01

    With augmented intelligence/knowledge based system (KBS) it is now possible to develop distance learning applications to support both curriculum and administrative tasks. Instructional designers and information technology (IT) professionals are now moving from the programmable systems era that started in the 1950s to the cognitive computing era.…

  6. [Artificial Intelligence in Drug Discovery].

    Science.gov (United States)

    Fujiwara, Takeshi; Kamada, Mayumi; Okuno, Yasushi

    2018-04-01

    According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI. In addition, with the aim of creating new therapeutic targets in genomic drug discovery, we have been also working on the development of a binding affinity prediction system for mutated proteins and drugs by molecular dynamics simulation using supercomputer "Kei". We also have tackled for problems in a drug virtual screening. Our developed AI technology has successfully generated virtual compound library, and deep learning method has enabled us to predict interaction between compound and target protein.

  7. Investigation of an artificial intelligence technology--Model trees. Novel applications for an immediate release tablet formulation database.

    Science.gov (United States)

    Shao, Q; Rowe, R C; York, P

    2007-06-01

    This study has investigated an artificial intelligence technology - model trees - as a modelling tool applied to an immediate release tablet formulation database. The modelling performance was compared with artificial neural networks that have been well established and widely applied in the pharmaceutical product formulation fields. The predictability of generated models was validated on unseen data and judged by correlation coefficient R(2). Output from the model tree analyses produced multivariate linear equations which predicted tablet tensile strength, disintegration time, and drug dissolution profiles of similar quality to neural network models. However, additional and valuable knowledge hidden in the formulation database was extracted from these equations. It is concluded that, as a transparent technology, model trees are useful tools to formulators.

  8. Accounting Practice and Intelligent Technologies

    Directory of Open Access Journals (Sweden)

    Daniela Postolache (Males

    2012-12-01

    Full Text Available was to determine how intelligent technologies can support accounting practice. Our research allowed for establishment of accounting information intelligent systems typology and for placement of these solutions in the sphere of artificial intelligence applications. It is underlined the intelligent technologies contribution to improve accounting processes and activities, in a qualitative approach, from the hermeneutic perspective. The results of our research are useful for researchers in the fields of applied accounting, intelligent systems for accounting, information technology management. Also, our study is useful in the activity of accounting experts, given the presentation of new technologies used in their area of interest.

  9. Artificial Intelligence and Expert Systems.

    Science.gov (United States)

    Wilson, Harold O.; Burford, Anna Marie

    1990-01-01

    Delineates artificial intelligence/expert systems (AI/ES) concepts; provides an exposition of some business application areas; relates progress; and creates an awareness of the benefits, limitations, and reservations of AI/ES. (Author)

  10. Artificial Intelligence and School Library Media Centers.

    Science.gov (United States)

    Young, Robert J.

    1990-01-01

    Discusses developments in artificial intelligence in terms of their impact on school library media centers and the role of media specialists. Possible uses of expert systems, hypertext, and CD-ROM technologies in school media centers are examined and the challenges presented by these technologies are discussed. Fourteen sources of additional…

  11. Artificial Intelligence and Science Education.

    Science.gov (United States)

    Good, Ron

    1987-01-01

    Defines artificial intelligence (AI) in relation to intelligent computer-assisted instruction (ICAI) and science education. Provides a brief background of AI work, examples of expert systems, examples of ICAI work, and addresses problems facing AI workers that have implications for science education. Proposes a revised model of the Karplus/Renner…

  12. Artificial intelligence approaches in statistics

    International Nuclear Information System (INIS)

    Phelps, R.I.; Musgrove, P.B.

    1986-01-01

    The role of pattern recognition and knowledge representation methods from Artificial Intelligence within statistics is considered. Two areas of potential use are identified and one, data exploration, is used to illustrate the possibilities. A method is presented to identify and separate overlapping groups within cluster analysis, using an AI approach. The potential of such ''intelligent'' approaches is stressed

  13. Computer automation and artificial intelligence

    International Nuclear Information System (INIS)

    Hasnain, S.B.

    1992-01-01

    Rapid advances in computing, resulting from micro chip revolution has increased its application manifold particularly for computer automation. Yet the level of automation available, has limited its application to more complex and dynamic systems which require an intelligent computer control. In this paper a review of Artificial intelligence techniques used to augment automation is presented. The current sequential processing approach usually adopted in artificial intelligence has succeeded in emulating the symbolic processing part of intelligence, but the processing power required to get more elusive aspects of intelligence leads towards parallel processing. An overview of parallel processing with emphasis on transputer is also provided. A Fuzzy knowledge based controller for amination drug delivery in muscle relaxant anesthesia on transputer is described. 4 figs. (author)

  14. Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare.

    Science.gov (United States)

    Mamoshina, Polina; Ojomoko, Lucy; Yanovich, Yury; Ostrovski, Alex; Botezatu, Alex; Prikhodko, Pavel; Izumchenko, Eugene; Aliper, Alexander; Romantsov, Konstantin; Zhebrak, Alexander; Ogu, Iraneus Obioma; Zhavoronkov, Alex

    2018-01-19

    The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major challenges for the patients, developers, providers and regulators. The novel deep learning and transfer learning techniques are turning any data about the person into medical data transforming simple facial pictures and videos into powerful sources of data for predictive analytics. Presently, the patients do not have control over the access privileges to their medical records and remain unaware of the true value of the data they have. In this paper, we provide an overview of the next-generation artificial intelligence and blockchain technologies and present innovative solutions that may be used to accelerate the biomedical research and enable patients with new tools to control and profit from their personal data as well with the incentives to undergo constant health monitoring. We introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship-value of the data. We also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control over personal data including medical records back to the individuals.

  15. Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare

    Science.gov (United States)

    Mamoshina, Polina; Ojomoko, Lucy; Yanovich, Yury; Ostrovski, Alex; Botezatu, Alex; Prikhodko, Pavel; Izumchenko, Eugene; Aliper, Alexander; Romantsov, Konstantin; Zhebrak, Alexander; Ogu, Iraneus Obioma; Zhavoronkov, Alex

    2018-01-01

    The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major challenges for the patients, developers, providers and regulators. The novel deep learning and transfer learning techniques are turning any data about the person into medical data transforming simple facial pictures and videos into powerful sources of data for predictive analytics. Presently, the patients do not have control over the access privileges to their medical records and remain unaware of the true value of the data they have. In this paper, we provide an overview of the next-generation artificial intelligence and blockchain technologies and present innovative solutions that may be used to accelerate the biomedical research and enable patients with new tools to control and profit from their personal data as well with the incentives to undergo constant health monitoring. We introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship-value of the data. We also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control over personal data including medical records back to the individuals. PMID:29464026

  16. Artificial Intelligence and Information Management

    Science.gov (United States)

    Fukumura, Teruo

    After reviewing the recent popularization of the information transmission and processing technologies, which are supported by the progress of electronics, the authors describe that by the introduction of the opto-electronics into the information technology, the possibility of applying the artificial intelligence (AI) technique to the mechanization of the information management has emerged. It is pointed out that althuogh AI deals with problems in the mental world, its basic methodology relies upon the verification by evidence, so the experiment on computers become indispensable for the study of AI. The authors also describe that as computers operate by the program, the basic intelligence which is concerned in AI is that expressed by languages. This results in the fact that the main tool of AI is the logical proof and it involves an intrinsic limitation. To answer a question “Why do you employ AI in your problem solving”, one must have ill-structured problems and intend to conduct deep studies on the thinking and the inference, and the memory and the knowledge-representation. Finally the authors discuss the application of AI technique to the information management. The possibility of the expert-system, processing of the query, and the necessity of document knowledge-base are stated.

  17. Northeast Artificial Intelligence Consortium Annual Report. 1988 Artificial Intelligence Applications to Speech Recognition. Volume 8

    Science.gov (United States)

    1989-10-01

    1988 Artificial Intelligence Applications to Speech Recognition Syracuse University Harvey E. Rhody, Thomas R. Ridley, John A. ,les DTIC S ELECTE FEB...Include Security Oiewftction) NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT - 1988 Artificial Intelligence Applications to Speech...Intelligence Consortium 1988 Annual Report Volume 8 Artificial Intelligence Applications to Speech Recognition Harvey E. Rhody Thomas R. Ridley John A

  18. Artificial Intelligence and Its Importance in Education.

    Science.gov (United States)

    Tilmann, Martha J.

    Artificial intelligence, or the study of ideas that enable computers to be intelligent, is discussed in terms of what it is, what it has done, what it can do, and how it may affect the teaching of tomorrow. An extensive overview of artificial intelligence examines its goals and applications and types of artificial intelligence including (1) expert…

  19. Artificial intelligence and process management

    International Nuclear Information System (INIS)

    Epton, J.B.A.

    1989-01-01

    Techniques derived from work in artificial intelligence over the past few decades are beginning to change the approach in applying computers to process management. To explore this new approach and gain real practical experience of its potential a programme of experimental applications was initiated by Sira in collaboration with the process industry. This programme encompassed a family of experimental applications ranging from process monitoring, through supervisory control and troubleshooting to planning and scheduling. The experience gained has led to a number of conclusions regarding the present level of maturity of the technology, the potential for further developments and the measures required to secure the levels of system integrity necessary in on-line applications to critical processes. (author)

  20. A Research Program on Artificial Intelligence in Process Engineering.

    Science.gov (United States)

    Stephanopoulos, George

    1986-01-01

    Discusses the use of artificial intelligence systems in process engineering. Describes a new program at the Massachusetts Institute of Technology which attempts to advance process engineering through technological advances in the areas of artificial intelligence and computers. Identifies the program's hardware facilities, software support,…

  1. Integrated Artificial Intelligence Approaches for Disease Diagnostics.

    Science.gov (United States)

    Vashistha, Rajat; Chhabra, Deepak; Shukla, Pratyoosh

    2018-06-01

    Mechanocomputational techniques in conjunction with artificial intelligence (AI) are revolutionizing the interpretations of the crucial information from the medical data and converting it into optimized and organized information for diagnostics. It is possible due to valuable perfection in artificial intelligence, computer aided diagnostics, virtual assistant, robotic surgery, augmented reality and genome editing (based on AI) technologies. Such techniques are serving as the products for diagnosing emerging microbial or non microbial diseases. This article represents a combinatory approach of using such approaches and providing therapeutic solutions towards utilizing these techniques in disease diagnostics.

  2. Artificial Intelligence Applications to Fire Management

    Science.gov (United States)

    Don J. Latham

    1987-01-01

    Artificial intelligence could be used in Forest Service fire management and land-use planning to a larger degree than is now done. Robots, for example, could be programmed to monitor for fire and insect activity, to keep track of wildlife, and to do elementary thinking about the environment. Catching up with the fast-changing technology is imperative.

  3. The Nexus between Artificial Intelligence and Economics

    NARCIS (Netherlands)

    van de Gevel, A.J.W.; Noussair, C.N.

    2012-01-01

    This book is organized as follows. Section 2 introduces the notion of the Singularity, a stage in development in which technological progress and economic growth increase at a near-infinite rate. Section 3 describes what artificial intelligence is and how it has been applied. Section 4 considers

  4. Computational aerodynamics and artificial intelligence

    Science.gov (United States)

    Kutler, P.; Mehta, U. B.

    1984-01-01

    Some aspects of artificial intelligence are considered and questions are speculated on, including 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. The anatomy of an idealized expert system called AERODYNAMICIST is discussed. Resource requirements are examined for using artificial intelligence in computational fluid dynamics and aerodynamics. Considering two of the essentials of computational aerodynamics - reasoniing and calculating - it is believed that a substantial part of the reasoning can be achieved with artificial intelligence, with computers being used as reasoning machines to set the stage for calculating. Expert systems will probably be new assets of institutions involved in aeronautics for various tasks of computational aerodynamics.

  5. Installation and evaluation of a nuclear power plant Operator Advisor based on artificial intelligence technology

    International Nuclear Information System (INIS)

    Hajek, B.K.; Miller, D.W.

    1993-02-01

    The Artificial Intelligence Group in the Nuclear Engineering Program has designed and built an Operator Advisor (OA), an AI system to monitor nuclear power plant parameters, detect component and system malfunctions, dispose their causes, and provide the plant operators with the correct procedures for mitigating the consequences of the malfunctions. It then monitors performance of the procedures, and provides backup steps when specific operator actions fail. The OA has been implemented on Sun 4 workstations in Common Lisp, and has been interfaced to run in real time on the Perry Nuclear Power Plant full-function simulator in the plant training department. The eventual goal for a fully functioning Operator Advisor would be to have reactor operators receive direction for all plant operations. Such a goal requires considerable testing of the system within limited malfunction boundaries, an extensive Verification ampersand Validation (V ampersand V) effort, a large knowledge base development effort, and development of tools as part of the system to automate its maintenance. Clearly, these efforts are beyond the scope of the feasibility effort expended during this project period. However, as a result of this project, we have an AI based platform upon which a complete system can be built

  6. Engaging older adults with dementia in creative occupations using artificially intelligent assistive technology.

    Science.gov (United States)

    Leuty, Valerie; Boger, Jennifer; Young, Laurel; Hoey, Jesse; Mihailidis, Alex

    2013-01-01

    Engagement in creative occupations has been shown to promote well-being for older adults with dementia. Providing access to such occupations is often difficult, as successful participation requires face-time with a person who is knowledgeable in facilitating engagement as well as access to any required resources, such as an arts studio. In response, a computer-based device, the Engaging Platform for Art Development (ePAD), was created to with the aim of enabling more independent access to art creation, ePAD is a an artificially intelligent touch-screen device that estimates a client's level of engagement and provides prompts to encourage engagement if the client becomes disengaged. ePAD is customizable such that an art therapist can choose themes and tools that they feel reflect their client's needs and preferences. This article presents a mixed-methods study that evaluated ePAD's usability by six older adult (with mild-to-moderate dementia) and art therapist dyads. Usability measures suggest that all participants found ePAD engaging but did not find prompts effective. Future development of ePAD includes improving the prompts, implementing the recommendations made by participants in this research, and long-term testing in more naturalistic art therapy contexts.

  7. The role of automation and artificial intelligence

    Science.gov (United States)

    Schappell, R. T.

    1983-07-01

    Consideration is given to emerging technologies that are not currently in common use, yet will be mature enough for implementation in a space station. Artificial intelligence (AI) will permit more autonomous operation and improve the man-machine interfaces. Technology goals include the development of expert systems, a natural language query system, automated planning systems, and AI image understanding systems. Intelligent robots and teleoperators will be needed, together with improved sensory systems for the robotics, housekeeping, vehicle control, and spacecraft housekeeping systems. Finally, NASA is developing the ROBSIM computer program to evaluate level of automation, perform parametric studies and error analyses, optimize trajectories and control systems, and assess AI technology.

  8. Artificial intelligence techniques in Prolog

    CERN Document Server

    Shoham, Yoav

    1993-01-01

    Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed.Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prol

  9. Artificial Intelligence and Urbanization: The Rise of the Elysium City

    OpenAIRE

    MUNOZ, J. Mark; NAQVI, Al

    2017-01-01

    Abstract. From ancient times, Greek religion introduced Elysium as a heavenly place to which admission was exclusively reserved for mortals related to gods, heroes, and those blessed by gods. We argue that the rise of artificial intelligence technology will lead to the creation of Elysium cities. Elysium cities agents will be technologists, technocrats, intelligent machines, and wealthy capitalists. These cities will be the first embracers of the artificial intelligence technology and will do...

  10. Impact of Artificial Intelligence on Economic Theory

    OpenAIRE

    Marwala, Tshilidzi

    2015-01-01

    Artificial intelligence has impacted many aspects of human life. This paper studies the impact of artificial intelligence on economic theory. In particular we study the impact of artificial intelligence on the theory of bounded rationality, efficient market hypothesis and prospect theory.

  11. Assistive Technology as an artificial intelligence opportunity: Case study of letter-based, head movement driven communication.

    Science.gov (United States)

    Miksztai-Réthey, Brigitta; Faragó, Kinga Bettina

    2015-01-01

    We studied an artificial intelligent assisted interaction between a computer and a human with severe speech and physical impairments (SSPI). In order to speed up AAC, we extended a former study of typing performance optimization using a framework that included head movement controlled assistive technology and an onscreen writing device. Quantitative and qualitative data were collected and analysed with mathematical methods, manual interpretation and semi-supervised machine video annotation. As the result of our research, in contrast to the former experiment's conclusions, we found that our participant had at least two different typing strategies. To maximize his communication efficiency, a more complex assistive tool is suggested, which takes the different methods into consideration.

  12. CLASSICS Generality in Artificial Intelligence

    Indian Academy of Sciences (India)

    IAS Admin

    My 1971 Turing Award Lecture was entitled “Generality in Artificial Intelligence.” The topic turned out to have been overambitious in that I discovered I was unable to put my thoughts on the subject in a satisfactory written form at that time. It would have been better to have reviewed my previous work rather than attempt ...

  13. Artificial Intelligence and Authority Control.

    Science.gov (United States)

    Burger, Robert H.

    1984-01-01

    Four artificial intelligence (AI) concepts that have relevance for information retrieval systems are discussed and applied to area of authority control in automated catalogs--pattern recognition, representation, problem solving, learning. Existing automated authority control systems are analyzed using two other AI concepts, augmentation and…

  14. Artificial Intelligence and Expert Systems.

    Science.gov (United States)

    Lawlor, Joseph

    Artificial intelligence (AI) is the field of scientific inquiry concerned with designing machine systems that can simulate human mental processes. The field draws upon theoretical constructs from a wide variety of disciplines, including mathematics, psychology, linguistics, neurophysiology, computer science, and electronic engineering. Some of the…

  15. Hybrid Applications Of Artificial Intelligence

    Science.gov (United States)

    Borchardt, Gary C.

    1988-01-01

    STAR, Simple Tool for Automated Reasoning, is interactive, interpreted programming language for development and operation of artificial-intelligence application systems. Couples symbolic processing with compiled-language functions and data structures. Written in C language and currently available in UNIX version (NPO-16832), and VMS version (NPO-16965).

  16. Artificial Intelligence: Applications in Education.

    Science.gov (United States)

    Thorkildsen, Ron J.; And Others

    1986-01-01

    Artificial intelligence techniques are used in computer programs to search out rapidly and retrieve information from very large databases. Programing advances have also led to the development of systems that provide expert consultation (expert systems). These systems, as applied to education, are the primary emphasis of this article. (LMO)

  17. Artificial Intelligence Assists Ultrasonic Inspection

    Science.gov (United States)

    Schaefer, Lloyd A.; Willenberg, James D.

    1992-01-01

    Subtle indications of flaws extracted from ultrasonic waveforms. Ultrasonic-inspection system uses artificial intelligence to help in identification of hidden flaws in electron-beam-welded castings. System involves application of flaw-classification logic to analysis of ultrasonic waveforms.

  18. Artificial Intelligence in Education.

    Science.gov (United States)

    Ruyle, Kim E.

    Expert systems have made remarkable progress in areas where the knowledge of an expert can be codified and represented, and these systems have many potentially useful applications in education. Expert systems seem "intelligent" because they do not simply repeat a set of predetermined questions during a consultation session, but will have…

  19. The National Artificial Intelligence Research And Development Strategic Plan

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — Executive Summary: Artificial intelligence (AI) is a transformative technology that holds promise for tremendous societal and economic benefit. AI has the potential...

  20. The potential of artificial intelligence toys

    DEFF Research Database (Denmark)

    Dai, Zheng

    2008-01-01

    Artificial intelligence is moving to a next step of development and application areas. From electronic games to human-like robots, AI toy is a good choice for next step during this process. Technology-based design is fit to the development of AI toy. It can exert the advantages and explore more...... value for existing resources. It combines AI programs and common sensors to realize the function of intelligence input and output. Designers can use technology-based criteria to design and need to consider the possible issues in this new field. All of these aspects can be referenced from electronic game...

  1. TECHNOLOGIES OF ARTIFICIAL INTELLIGENCE AS THE FACTOR OF DIGITALIZATION OF ECONOMY IN RUSSIA AND IN THE WORLD

    Directory of Open Access Journals (Sweden)

    L. A. Tsvetkova

    2017-01-01

    Full Text Available The growth rates of the market for high-tech goods and services based on deep learning technologies are estimated. Key investors and beneficiaries in the development of deep learning technologies were identified. The patent activity in the world is analyzed and the place of Russia in the patent landscape in the field of deep learning is determined. It is shown that most of the patent documents are concentrated in the portfolios of major US corporations, which are headed by Microsoft, IBM, Google, Yahoo. Among the leaders of the rating of patent holders are also the corporations of Japan and the Republic of Korea. High rates of growth of patent activity in China are noted. The prospects of the development of artificial intelligence technologies and deep learning in Russia are estimated. Special attention is paid to the fact that most of the research and development in this area is carried out in public research institutes and universities, while in the countries – technological leaders the driver of development of the direction is the business sector.

  2. Uncertainty in artificial intelligence

    CERN Document Server

    Levitt, TS; Lemmer, JF; Shachter, RD

    1990-01-01

    Clearly illustrated in this volume is the current relationship between Uncertainty and AI.It has been said that research in AI revolves around five basic questions asked relative to some particular domain: What knowledge is required? How can this knowledge be acquired? How can it be represented in a system? How should this knowledge be manipulated in order to provide intelligent behavior? How can the behavior be explained? In this volume, all of these questions are addressed. From the perspective of the relationship of uncertainty to the basic questions of AI, the book divides naturally i

  3. Intelligence Quotient and Intelligence Grade of Artificial Intelligence

    OpenAIRE

    Liu, Feng; Shi, Yong; Liu, Ying

    2017-01-01

    Although artificial intelligence is currently one of the most interesting areas in scientific research, the potential threats posed by emerging AI systems remain a source of persistent controversy. To address the issue of AI threat, this study proposes a standard intelligence model that unifies AI and human characteristics in terms of four aspects of knowledge, i.e., input, output, mastery, and creation. Using this model, we observe three challenges, namely, expanding of the von Neumann archi...

  4. Neuroscience-Inspired Artificial Intelligence.

    Science.gov (United States)

    Hassabis, Demis; Kumaran, Dharshan; Summerfield, Christopher; Botvinick, Matthew

    2017-07-19

    The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history. In more recent times, however, communication and collaboration between the two fields has become less commonplace. In this article, we argue that better understanding biological brains could play a vital role in building intelligent machines. We survey historical interactions between the AI and neuroscience fields and emphasize current advances in AI that have been inspired by the study of neural computation in humans and other animals. We conclude by highlighting shared themes that may be key for advancing future research in both fields. Copyright © 2017. Published by Elsevier Inc.

  5. The application and development of artificial intelligence in smart clothing

    Science.gov (United States)

    Wei, Xiong

    2018-03-01

    This paper mainly introduces the application of artificial intelligence in intelligent clothing. Starting from the development trend of artificial intelligence, analysis the prospects for development in smart clothing with artificial intelligence. Summarize the design key of artificial intelligence in smart clothing. Analysis the feasibility of artificial intelligence in smart clothing.

  6. Introducing artificial intelligence into structural optimization programs

    International Nuclear Information System (INIS)

    Jozwiak, S.F.

    1987-01-01

    Artificial Intelligence /AI/ is defined as the branch of the computer science concerned with the study of the ideas that enable computers to be intelligent. The main purpose of the application of AI in engineering is to develop computer programs which function better as tools for engineers and designers. Many computer programs today have properties which make them inconvenient to their final users and the research carried within the field of AI provides tools and techniques so that these restriction can be removed. The continuous progress in computer technology has lead to developing efficient computer systems which can be applied to more than simple solving sets of equations. (orig.)

  7. Seventh Scandinavian Conference on Artificial Intelligence

    DEFF Research Database (Denmark)

    Lund, Henrik Hautop; Mayoh, Brian Henry; Perram, John

    2001-01-01

    The book covers the seventh Scandinavian Conference on Artificial Intelligence, held at the Maersk Mc-Kinney Moller Institute for Production Technology at the University of Southern Denmark during the period 20-21 February, 2001. It continues the tradition established by SCAI of being one...... of the most important regional AI conferences in Europe, attracting high quality submissions from Scandinavia and the rest of the world, including the Baltic countries. The contents include robotics, sensor/motor intelligence, evolutionary robotics, behaviour-based systems, multi-agent systems, applications...

  8. Important Themas in Artificial Intelligence

    OpenAIRE

    Šudoma, Petr

    2013-01-01

    The paper studies description logics as a method of field of artificial intelligence, describes history of knowledge representation as series of events leading to founding of description logics. Furthermore the paper compares description logics with their predecessor, the frame systems. Syntax, semantics and description logics naming convention is also presented and algorithms solving common knowledge representation tasks with usage of description logics are described. Paper compares computat...

  9. Anesthesiology, automation, and artificial intelligence.

    Science.gov (United States)

    Alexander, John C; Joshi, Girish P

    2018-01-01

    There have been many attempts to incorporate automation into the practice of anesthesiology, though none have been successful. Fundamentally, these failures are due to the underlying complexity of anesthesia practice and the inability of rule-based feedback loops to fully master it. Recent innovations in artificial intelligence, especially machine learning, may usher in a new era of automation across many industries, including anesthesiology. It would be wise to consider the implications of such potential changes before they have been fully realized.

  10. Artificial Intelligence, Employment, and Income

    OpenAIRE

    Nilsson, Nils J.

    1984-01-01

    Artificial intelligence (AI) will have profound societal effects. It promises potential benefits (and may also pose risks) in education, defense, business, law and science. In this article we explore how AI is likely to affect employment and the distribution of income. We argue that AI will indeed reduce drastically the need of human toil. We also note that some people fear the automation of work by machines and the resulting of unemployment. Yet, since the majority of us probably would rathe...

  11. Automated Scheduling Via Artificial Intelligence

    Science.gov (United States)

    Biefeld, Eric W.; Cooper, Lynne P.

    1991-01-01

    Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.

  12. Artificial intelligence and computer vision

    CERN Document Server

    Li, Yujie

    2017-01-01

    This edited book presents essential findings in the research fields of artificial intelligence and computer vision, with a primary focus on new research ideas and results for mathematical problems involved in computer vision systems. The book provides an international forum for researchers to summarize the most recent developments and ideas in the field, with a special emphasis on the technical and observational results obtained in the past few years.

  13. Application of artificial intelligence to the management of urological cancer.

    Science.gov (United States)

    Abbod, Maysam F; Catto, James W F; Linkens, Derek A; Hamdy, Freddie C

    2007-10-01

    Artificial intelligence techniques, such as artificial neural networks, Bayesian belief networks and neuro-fuzzy modeling systems, are complex mathematical models based on the human neuronal structure and thinking. Such tools are capable of generating data driven models of biological systems without making assumptions based on statistical distributions. A large amount of study has been reported of the use of artificial intelligence in urology. We reviewed the basic concepts behind artificial intelligence techniques and explored the applications of this new dynamic technology in various aspects of urological cancer management. A detailed and systematic review of the literature was performed using the MEDLINE and Inspec databases to discover reports using artificial intelligence in urological cancer. The characteristics of machine learning and their implementation were described and reports of artificial intelligence use in urological cancer were reviewed. While most researchers in this field were found to focus on artificial neural networks to improve the diagnosis, staging and prognostic prediction of urological cancers, some groups are exploring other techniques, such as expert systems and neuro-fuzzy modeling systems. Compared to traditional regression statistics artificial intelligence methods appear to be accurate and more explorative for analyzing large data cohorts. Furthermore, they allow individualized prediction of disease behavior. Each artificial intelligence method has characteristics that make it suitable for different tasks. The lack of transparency of artificial neural networks hinders global scientific community acceptance of this method but this can be overcome by neuro-fuzzy modeling systems.

  14. Artificial Intelligence and Virology - quo vadis.

    Science.gov (United States)

    Shapshak, Paul; Somboonwit, Charurut; Sinnott, John T

    2017-01-01

    Artificial Intelligence (AI), robotics, co-robotics (cobots), quantum computers (QC), include surges of scientific endeavor to produce machines (mechanical and software) among numerous types and constructions that are accelerating progress to defeat infectious diseases. There is a plethora of additional applications and uses of these methodologies and technologies for the understanding of biomedicine through bioinformation discovery. Therefore, we briefly outline the use of such techniques in virology.

  15. Artificial Intelligence and Virology - quo vadis

    Science.gov (United States)

    Shapshak, Paul; Somboonwit, Charurut; Sinnott, John T.

    2017-01-01

    Artificial Intelligence (AI), robotics, co-robotics (cobots), quantum computers (QC), include surges of scientific endeavor to produce machines (mechanical and software) among numerous types and constructions that are accelerating progress to defeat infectious diseases. There is a plethora of additional applications and uses of these methodologies and technologies for the understanding of biomedicine through bioinformation discovery. Therefore, we briefly outline the use of such techniques in virology. PMID:29379259

  16. Beyond AI: Multi-Intelligence (MI) Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

    OpenAIRE

    Stephen Fox

    2017-01-01

    Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI) are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, t...

  17. Artificial Intelligence: An Analysis of the Technology for Training. Training and Development Research Center Project Number Fourteen.

    Science.gov (United States)

    Sayre, Scott Alan

    The ultimate goal of the science of artificial intelligence (AI) is to establish programs that will use algorithmic computer techniques to imitate the heuristic thought processes of humans. Most AI programs, especially expert systems, organize their knowledge into three specific areas: data storage, a rule set, and a control structure. Limitations…

  18. Artificial Intelligence--Applications in Education.

    Science.gov (United States)

    Poirot, James L.; Norris, Cathleen A.

    1987-01-01

    This first in a projected series of five articles discusses artificial intelligence and its impact on education. Highlights include the history of artificial intelligence and the impact of microcomputers; learning processes; human factors and interfaces; computer assisted instruction and intelligent tutoring systems; logic programing; and expert…

  19. A Progress Report on Artificial Intelligence: Hospital Applications and a Review of the Artificial Intelligence Marketplace

    Science.gov (United States)

    Brenkus, Lawrence M.

    1984-01-01

    Artificial intelligence applications are finally beginning to move from the university research laboratory into commercial use. Before the end of the century, this new computer technology will have profound effects on our work, economy, and lives. At present, relatively few products have appeared in the hospital, but we can anticipate significant product offerings in instrumentation and affecting hospital administration within 5 years.

  20. Implications of VISIDEPtm For Artificial Intelligence Applications

    Science.gov (United States)

    McLaurin, A. P.; Jones, Edwin R.; Cathey, LeConte

    1987-04-01

    VISIDF is a system for generating true three-dimensional displays on flat-screened devices. Hodges and McAllister, in their article, state clearly that this system is the autostereoscopic alternative to PLZT shutter systems for computer-generated graphic appli-cations. This opens the door to consideration of the system as a component of vision for artificial intelligence applications. In order to understand the potentials of VISIDEP one must, in fact, accept several fundamental assumptions. These are: 1. Perception is an intelligent activity rather than purely stimulus/response. 2. Binocular depth cues are of greater importance to accurate depth interpretation than monocular cues. 3. Depth perception does not require object identification. Each of these assumptions is essential to the application of VISIDEP research in practical operations requiring depth interpretation. The relationships between human vision and perception and the parallax induction generated by VISIDEP technology offer depth in real time to artificial intelligence. Through machine operations on incoming data, the perception of depth is generated in much the same way as the stereoptic data enter the human being, thus providing rapidly quantifiable depth interpretation which is very accurate, perhaps more accurate that human perception of depth. The analysis of a mechanical system in relationship to human approaches to depth perceptions offers the potential of many applications of visually competent artificial intelligence. An additional factor is that the system under discussion is user friendly for human operators as well as requiring minimal reconfiguration of existing equipment and relatively simple software.

  1. Third Conference on Artificial Intelligence for Space Applications, part 2

    Science.gov (United States)

    Denton, Judith S. (Compiler); Freeman, Michael S. (Compiler); Vereen, Mary (Compiler)

    1988-01-01

    Topics relative to the application of artificial intelligence to space operations are discussed. New technologies for space station automation, design data capture, computer vision, neural nets, automatic programming, and real time applications are discussed.

  2. Intelligent Tutoring System: A Tool for Testing the Research Curiosities of Artificial Intelligence Researchers

    Science.gov (United States)

    Yaratan, Huseyin

    2003-01-01

    An ITS (Intelligent Tutoring System) is a teaching-learning medium that uses artificial intelligence (AI) technology for instruction. Roberts and Park (1983) defines AI as the attempt to get computers to perform tasks that if performed by a human-being, intelligence would be required to perform the task. The design of an ITS comprises two distinct…

  3. Readings in artificial intelligence and software engineering

    CERN Document Server

    Rich, Charles

    1986-01-01

    Readings in Artificial Intelligence and Software Engineering covers the main techniques and application of artificial intelligence and software engineering. The ultimate goal of artificial intelligence applied to software engineering is automatic programming. Automatic programming would allow a user to simply say what is wanted and have a program produced completely automatically. This book is organized into 11 parts encompassing 34 chapters that specifically tackle the topics of deductive synthesis, program transformations, program verification, and programming tutors. The opening parts p

  4. Ethical Considerations in Artificial Intelligence Courses

    OpenAIRE

    Burton, Emanuelle; Goldsmith, Judy; Koenig, Sven; Kuipers, Benjamin; Mattei, Nicholas; Walsh, Toby

    2017-01-01

    The recent surge in interest in ethics in artificial intelligence may leave many educators wondering how to address moral, ethical, and philosophical issues in their AI courses. As instructors we want to develop curriculum that not only prepares students to be artificial intelligence practitioners, but also to understand the moral, ethical, and philosophical impacts that artificial intelligence will have on society. In this article we provide practical case studies and links to resources for ...

  5. Of Artificial Intelligence and Legal Reasoning

    OpenAIRE

    Sunstein, Cass Robert

    2014-01-01

    Can computers, or artificial intelligence, reason by analogy? This essay urges that they cannot, because they are unable to engage in the crucial task of identifying the normative principle that links or separates cases. Current claims, about the ability of artificial intelligence to reason analogically, rest on an inadequate picture of what legal reasoning actually is. For the most part, artificial intelligence now operates as a kind of advanced version of LEXIS, offering research assistance...

  6. Northeast Artificial Intelligence Consortium Annual Report 1987. Volume 6. Artificial Intelligence Applications to Speech Recognition

    Science.gov (United States)

    1989-03-01

    ARTIFICIAL INTELLIGENCE’CONSORTIUM ANNUAL REPORT 1987 Artificial Intelligence Applications to Speech Recognition 12. PERSONAL AUTHOR(S) H. E. Rhody, J. A...obsolete. SECURITY CLASSIFICATION OF THIS PAGE UNCLASSIFIED 6 ARTIFICIAL INTELLIGENCE APPLICATIONS TO SPEECH RECOGNITION Report submitted by: Harvey E

  7. Artificial intelligence a beginner's guide

    CERN Document Server

    Whitby, Blay

    2012-01-01

    Tomorrow begins right here as we embark on an enthralling and jargon-free journey into the world of computers and the inner recesses of the human mind. Readers encounter everything from the nanotechnology used to make insect-like robots, to computers that perform surgery, in addition to discovering the biggest controversies to dog the field of AI. Blay Whitby is a Lecturer on Cognitive Science and Artificial Intelligence at the University of Sussex UK. He is the author of two books and numerous papers.

  8. Logical Foundations Of Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-04-01

    Full Text Available The procedures of searching solutions to problems, in Artificial Intelligence, can be brought about, in many occasions, without knowledge of the Domain, and in other situations, with knowledge of it. This last procedure is usually called Heuristic Search. In such methods the matrix techniques reveal themselves as essential. Their introduction can give us an easy and precise way in the search of solution. Our paper explains how the matrix theory appears and fruitfully participates in A I, with feasible applications to Game Theory.

  9. Artificial intelligence methods for diagnostic

    International Nuclear Information System (INIS)

    Dourgnon-Hanoune, A.; Porcheron, M.; Ricard, B.

    1996-01-01

    To assist in diagnosis of its nuclear power plants, the Research and Development Division of Electricite de France has been developing skills in Artificial Intelligence for about a decade. Different diagnostic expert systems have been designed. Among them, SILEX for control rods cabinet troubleshooting, DIVA for turbine generator diagnosis, DIAPO for reactor coolant pump diagnosis. This know how in expert knowledge modeling and acquisition is direct result of experience gained during developments and of a more general reflection on knowledge based system development. We have been able to reuse this results for other developments such as a guide for auxiliary rotating machines diagnosis. (authors)

  10. An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part A: The core ingredients

    Science.gov (United States)

    Gevarter, W. B.

    1983-01-01

    Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. The goal of Artificial Intelligence is focused on developing computational approaches to intelligent behavior. This goal is so broad - covering virtually all aspects of human cognitive activity - that substantial confusion has arisen as to the actual nature of AI, its current status and its future capability. This volume, the first in a series of NBS/NASA reports on the subject, attempts to address these concerns. Thus, this report endeavors to clarify what AI is, the foundations on which it rests, the techniques utilized, applications, the participants and, finally, AI's state-of-the-art and future trends. It is anticipated that this report will prove useful to government and private engineering and research managers, potential users, and others who will be affected by this field as it unfolds.

  11. Application of artificial intelligence in coal preparation

    Energy Technology Data Exchange (ETDEWEB)

    Kuang, Y.; Deng, J.; Liu, H. [China University of Mining and Technology, Xuzhou (China). School of Chemical Engineering and Technology

    2001-11-01

    The general situation of using AI (Artificial intelligence) technology in coal preparation was introduced. The expert systems of coal preparation plant design, the expert management system of coal preparation plant, and the intelligent data-drawing bank were discussed. Some opinions about their foundation and method of knowledge expressing, inference, knowledge discovery of databases were presented. It is pointed out that an industrial system such as coal preparation is big and complex, so it is necessary and also difficult to use AI technology in these systems. Because the types of knowledge are different, there are various knowledge expressions and model of knowledge inference, hence only comprehensive methods suitable for the characters of the system may be used. 14 refs., 5 figs.

  12. Trends in telemedicine utilizing artificial intelligence

    Science.gov (United States)

    Pacis, Danica Mitch M.; Subido, Edwin D. C.; Bugtai, Nilo T.

    2018-02-01

    With the growth and popularity of the utilization of artificial intelligence (AI) in several fields and industries, studies in the field of medicine have begun to implement its capabilities in handling and analyzing data to telemedicine. With the challenges in the implementation of telemedicine, there has been a need to expand its capabilities and improve procedures to be specialized to solve specific problems. The versatility and flexibility of both AI and telemedicine gave the endless possibilities for development and these can be seen in the literature reviewed in this paper. The trends in the development of the utilization of this technology can be classified in to four: patient monitoring, healthcare information technology, intelligent assistance diagnosis, and information analysis collaboration. Each trend will be discussed and presented with examples of recent literature and the problems they aim to address. Related references will also be tabulated and categorized to see the future and potential of this current trend in telemedicine.

  13. Interactive Video and Artificial Intelligence: A Convenient Marriage.

    Science.gov (United States)

    Midoro, V.; And Others

    1988-01-01

    Describes the theoretical framework of a research project aimed at exploring the new potentials for instructional systems offered by videodisc technology and artificial intelligence. A prototype of an intelligent tutoring system, "Earth," is described, and types of interactions in instructional systems are discussed as they relate to the…

  14. Artificial Intelligence Applications for Nuclear Survivability Validation

    Science.gov (United States)

    1992-11-01

    AD-A259 394 IIIIIt~l111 11 11 11 1 1hIf L- E, Defense Nuclear Agency Alexandria, VA 22310-3398 DNA-TR-92-82 Artificial Intelligence Applications for...TYPE AND DATES COVERED 921101 Technical 920101 -920408 4. TITLE AND SUBTITLE 5, FUNDING NUMBERS Artificial Intelligence Applications for Nuclear

  15. A Hierarchical Artificial Intelligence Maintenance Advisor

    Science.gov (United States)

    1991-07-08

    Lee Kline, and Mr. Thomas Gattis for their enthusiasm for the project. 7 Appendix ARTIFICIAL INTELLIGENCE APPLICATIONS FOR MILITARY LOGISTICS This...Appendix contains the visuals and summarizes commentary presented at the Defense Preparedness Association conference on " Artificial Intelligence Applications for

  16. Contribution of artificial intelligence to operation

    International Nuclear Information System (INIS)

    Malvache, P.; Mourlevat, J.L.

    1993-01-01

    Artificial Intelligence techniques are already used in nuclear plants for assistance to operation: synthesis from numerous information sources may be then derived, based on expert knowledge. Artificial intelligence may be used also for quality and reliability assessment of software-based control-command systems. Various expert systems developed by CEA, EDF and Framatome are presented

  17. Tissue engineering scheming by artificial intelligence.

    Science.gov (United States)

    Xu, J; Ge, H; Zhou, X; Yang, D

    2005-01-01

    Tissue engineers are often confused when seeking the most effective, economical and secure scheme for tissue engineering. The aim of this study is to generate tissue engineering schemes with artificial intelligence instead of human intelligence. The experimental data of tissue engineered cartilage were integrated and standardized with a centralized database, and a scheme engine was developed using artificial intelligent methods (artificial neural networks and decision trees). The scheme engine was trained with existing cases in the database, and then was used to generate tissue engineering schemes for new experimental animals. Following the schemes generated by the artificial intelligent system, we cured 18 of the 20 experimental animals. In conclusion, artificial intelligence is a powerful method for decision making in the tissue engineering realm.

  18. A DISTRIBUTED SMART HOME ARTIFICIAL INTELLIGENCE SYSTEM

    DEFF Research Database (Denmark)

    Lynggaard, Per

    2013-01-01

    A majority of the research performed today explore artificial intelligence in smart homes by using a centralized approach where a smart home server performs the necessary calculations. This approach has some disadvantages that can be overcome by shifting focus to a distributed approach where...... the artificial intelligence system is implemented as distributed as agents running parts of the artificial intelligence system. This paper presents a distributed smart home architecture that distributes artificial intelligence in smart homes and discusses the pros and cons of such a concept. The presented...... distributed model is a layered model. Each layer offers a different complexity level of the embedded distributed artificial intelligence. At the lowest layer smart objects exists, they are small cheap embedded microcontroller based smart devices that are powered by batteries. The next layer contains a more...

  19. Artificial intelligence in a technological production system of the set quality

    Directory of Open Access Journals (Sweden)

    V. I. Karpov

    2017-01-01

    Full Text Available This  article considers the expert system (ES as a subsystem of management information system technology of sausage products of a given quality. Given the typical structure of an automated expert system, upgraded under a set of interrelated operations of the technological process of production of cooked sausages. Describes the development of two main blocks of this expert system – a database and knowledge base, creating an information space. The work of ES is a sequence of steps, each of which is selected from the database for a rule that applies to the current contents of the working set. The cycle ends when withdrawn or denied the target claim. In our case, the system is designed as a system with direct output, in which the known facts is found the conclusion which from these facts follows. If such a conclusion is found, it is entered into working memory. The knowledge base of an expert system is created as a set of separate entities. The set of these entities allows you to generate objects of study, rules that they can conform, and recommendations for meeting these rules. A set of such entities with their attributes and relationships can be represented as a set of tuples. For the implementation of this approach developed an automated expert system of control of technological process of production of meat and sausage products – the program complex (PC “MulTimit Expert”. The effectiveness of using the developed expert system to control the technology of sausage products of a given quality are considered in one of the examples of the identification of technology defects in the formulation of cooked sausages "Capital", containing large amounts of fatty raw materials. The results of the research as a whole showed that the recommendations of the developed expert system make it possible to improve the quality of the ready-to-eat meat product, increase the water retention coefficient characterizing the moisture retention capacity of the

  20. Artificial Intelligence Implications for Information Retrieval.

    Science.gov (United States)

    1983-04-01

    data entry, and (4) active memory techniques. In the remainder of this section we will describe each of these areas briefly. Artificial Intelligence applications In... Intelligence applications to information retrieval fall into four broad categories: (1) human-database interfaces, (2) conceptual Indexing, (3) automatic...the fact that some of the most difficult of intelligent behavior (i.e. common sense) seems intuitively easy. z. =2atgarIa at Al AiA1AnA Artificial

  1. Parallel processing for artificial intelligence 2

    CERN Document Server

    Kumar, V; Suttner, CB

    1994-01-01

    With the increasing availability of parallel machines and the raising of interest in large scale and real world applications, research on parallel processing for Artificial Intelligence (AI) is gaining greater importance in the computer science environment. Many applications have been implemented and delivered but the field is still considered to be in its infancy. This book assembles diverse aspects of research in the area, providing an overview of the current state of technology. It also aims to promote further growth across the discipline. Contributions have been grouped according to their

  2. Perspectives on artificial intelligence programming.

    Science.gov (United States)

    Bobrow, D G; Stefik, M J

    1986-02-28

    Programs are judged not only by whether they faithfully carry out the intended processing but also by whether they are understandable and easily changed. Programming systems for artificial intelligence applications use specialized languages, environments, and knowledge-based tools to reduce the complexity of the programming task. Language styles based on procedures, objects, logic, rules, and constraints reflect different models for organizing programs and facilitate program evolution and understandability. To make programming easier, multiple styles can be integrated as sublanguages in a programming environment. Programming environments provide tools that analyze programs and create informative displays of their structure. Programs can be modified by direct interaction with these displays. These tools and languages are helping computer scientists to regain a sense of control over systems that have become increasingly complex.

  3. An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part B: Applications

    Science.gov (United States)

    Gevarter, W. B.

    1983-01-01

    Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. This report, Part B of a three part report on AI, presents overviews of the key application areas: Expert Systems, Computer Vision, Natural Language Processing, Speech Interfaces, and Problem Solving and Planning. The basic approaches to such systems, the state-of-the-art, existing systems and future trends and expectations are covered.

  4. Robotics, Artificial Intelligence, Computer Simulation: Future Applications in Special Education.

    Science.gov (United States)

    Moore, Gwendolyn B.; And Others

    The report describes three advanced technologies--robotics, artificial intelligence, and computer simulation--and identifies the ways in which they might contribute to special education. A hybrid methodology was employed to identify existing technology and forecast future needs. Following this framework, each of the technologies is defined,…

  5. Economic reasoning and artificial intelligence.

    Science.gov (United States)

    Parkes, David C; Wellman, Michael P

    2015-07-17

    The field of artificial intelligence (AI) strives to build rational agents capable of perceiving the world around them and taking actions to advance specified goals. Put another way, AI researchers aim to construct a synthetic homo economicus, the mythical perfectly rational agent of neoclassical economics. We review progress toward creating this new species of machine, machina economicus, and discuss some challenges in designing AIs that can reason effectively in economic contexts. Supposing that AI succeeds in this quest, or at least comes close enough that it is useful to think about AIs in rationalistic terms, we ask how to design the rules of interaction in multi-agent systems that come to represent an economy of AIs. Theories of normative design from economics may prove more relevant for artificial agents than human agents, with AIs that better respect idealized assumptions of rationality than people, interacting through novel rules and incentive systems quite distinct from those tailored for people. Copyright © 2015, American Association for the Advancement of Science.

  6. A Case Study of the Link between Artificial Intelligence and Knowledge Creation in Emerging Technology in China

    DEFF Research Database (Denmark)

    Søberg, Peder Veng

    2017-01-01

    in much knowledge creation research, the empirical insights come from a case study in a Chinese startup SME (small and medium-sized enterprise) within the emerging industry of visual intelligence/surveillance systems. The findings, extracted from semi-structured interviews as well as observations, suggest...... of consent requirements when collecting information and a willing population makes China an ideal test bed for visual intelligence technologies. The chapter exposes the shortcomings of the existing knowledge creation theory and bridges these with insights on how to overcome them in different contexts...

  7. Artificial intelligence in power system optimization

    CERN Document Server

    Ongsakul, Weerakorn

    2013-01-01

    With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also be useful for those who are interested in using artificial intelligence in power system optimization.

  8. BWR shutdown analyzer using artificial intelligence (AI) techniques

    International Nuclear Information System (INIS)

    Cain, D.G.

    1986-01-01

    A prototype alarm system for detecting abnormal reactor shutdowns based on artificial intelligence technology is described. The system incorporates knowledge about Boiling Water Reactor (BWR) plant design and component behavior, as well as knowledge required to distinguish normal, abnormal, and ATWS accident conditions. The system was developed using a software tool environment for creating knowledge-based applications on a LISP machine. To facilitate prototype implementation and evaluation, a casual simulation of BWR shutdown sequences was developed and interfaced with the alarm system. An intelligent graphics interface for execution and control is described. System performance considerations and general observations relating to artificial intelligence application to nuclear power plant problems are provided

  9. Artificial intelligence for analyzing orthopedic trauma radiographs.

    Science.gov (United States)

    Olczak, Jakub; Fahlberg, Niklas; Maki, Atsuto; Razavian, Ali Sharif; Jilert, Anthony; Stark, André; Sköldenberg, Olof; Gordon, Max

    2017-12-01

    Background and purpose - Recent advances in artificial intelligence (deep learning) have shown remarkable performance in classifying non-medical images, and the technology is believed to be the next technological revolution. So far it has never been applied in an orthopedic setting, and in this study we sought to determine the feasibility of using deep learning for skeletal radiographs. Methods - We extracted 256,000 wrist, hand, and ankle radiographs from Danderyd's Hospital and identified 4 classes: fracture, laterality, body part, and exam view. We then selected 5 openly available deep learning networks that were adapted for these images. The most accurate network was benchmarked against a gold standard for fractures. We furthermore compared the network's performance with 2 senior orthopedic surgeons who reviewed images at the same resolution as the network. Results - All networks exhibited an accuracy of at least 90% when identifying laterality, body part, and exam view. The final accuracy for fractures was estimated at 83% for the best performing network. The network performed similarly to senior orthopedic surgeons when presented with images at the same resolution as the network. The 2 reviewer Cohen's kappa under these conditions was 0.76. Interpretation - This study supports the use for orthopedic radiographs of artificial intelligence, which can perform at a human level. While current implementation lacks important features that surgeons require, e.g. risk of dislocation, classifications, measurements, and combining multiple exam views, these problems have technical solutions that are waiting to be implemented for orthopedics.

  10. Robotics and artificial intelligence: Jewish ethical perspectives.

    Science.gov (United States)

    Rappaport, Z H

    2006-01-01

    In 16th Century Prague, Rabbi Loew created a Golem, a humanoid made of clay, to protect his community. When the Golem became too dangerous to his surroundings, he was dismantled. This Jewish theme illustrates some of the guiding principles in its approach to the moral dilemmas inherent in future technologies, such as artificial intelligence and robotics. Man is viewed as having received the power to improve upon creation and develop technologies to achieve them, with the proviso that appropriate safeguards are taken. Ethically, not-harming is viewed as taking precedence over promoting good. Jewish ethical thinking approaches these novel technological possibilities with a cautious optimism that mankind will derive their benefits without coming to harm.

  11. Detection of Terrorist Preparations by an Artificial Intelligence Expert System Employing Fuzzy Signal Detection Theory

    National Research Council Canada - National Science Library

    Koltko-Rivera, Mark E

    2004-01-01

    ...). As the name suggests, FUSEDOT applies artificial intelligence expert system technology to the fuzzy signals presented by certain anomalous data, such as interpersonal relationships, financial...

  12. Machine learning \\& artificial intelligence in the quantum domain

    OpenAIRE

    Dunjko, Vedran; Briegel, Hans J.

    2017-01-01

    Quantum information technologies, and intelligent learning systems, are both emergent technologies that will likely have a transforming impact on our society. The respective underlying fields of research -- quantum information (QI) versus machine learning (ML) and artificial intelligence (AI) -- have their own specific challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question to what extent th...

  13. The present status of artificial intelligence for nuclear power plants

    International Nuclear Information System (INIS)

    Suda, Kazunori; Yonekawa, Tuyoshi; Yoshikawa, Shinji; Hasegawa, Makoto

    1999-03-01

    JNC researches the development of distributed intelligence systems at autonomous plants and intelligent support system at nuclear power plant. This report describes the present status of artificial intelligence (AI) technologies for this research. The following are represented in this report: present research study for AI, Implementation of AI system and application of AI technologies in the field of industries, requirement for AI by industries, problems of social acceptance for AI. A development of AI systems has to be motivated both by current status of AI and requirement for AI. Furthermore a problem of social acceptance for AI technologies has to be solved for using AI systems in society. (author)

  14. Artificial Intelligence, Robots and Education: Selected Sources.

    Science.gov (United States)

    Kissinger, Pat

    1987-01-01

    This annotated bibliography describes 12 books, 10 ERIC publications, and 7 periodical articles about artificial intelligence and robotics that were selected by the author as resources for educators. (CLB)

  15. What Artificial Intelligence Is Doing for Training.

    Science.gov (United States)

    Kirrane, Peter R.; Kirrane, Diane E.

    1989-01-01

    Discusses the three areas of research and application of artificial intelligence: (1) robotics, (2) natural language processing, and (3) knowledge-based or expert systems. Focuses on what expert systems can do, especially in the area of training. (JOW)

  16. Artificial intelligence tool development and applications to nuclear power

    International Nuclear Information System (INIS)

    Naser, J.A.

    1987-01-01

    Two parallel efforts are being performed at the Electric Power Research Institute (EPRI) to help the electric utility industry take advantage of the expert system technology. The first effort is the development of expert system building tools, which are tailored to electric utility industry applications. The second effort is the development of expert system applications. These two efforts complement each other. The application development tests the tools and identifies additional tool capabilities that are required. The tool development helps define the applications that can be successfully developed. Artificial intelligence, as demonstrated by the developments described is being established as a credible technological tool for the electric utility industry. The challenge to transferring artificial intelligence technology and an understanding of its potential to the electric utility industry is to gain an understanding of the problems that reduce power plant performance and identify which can be successfully addressed using artificial intelligence

  17. Artificial Intelligence and Spacecraft Power Systems

    Science.gov (United States)

    Dugel-Whitehead, Norma R.

    1997-01-01

    This talk will present the work which has been done at NASA Marshall Space Flight Center involving the use of Artificial Intelligence to control the power system in a spacecraft. The presentation will include a brief history of power system automation, and some basic definitions of the types of artificial intelligence which have been investigated at MSFC for power system automation. A video tape of one of our autonomous power systems using co-operating expert systems, and advanced hardware will be presented.

  18. The 2002 Starting Artificial Intelligence Researchers Symposium

    OpenAIRE

    Vidal, Thierry

    2003-01-01

    During the 2002 European Conference on Artificial Intelligence (ECAI-02) was introduced the Starting Artificial Intelligence Researchers Symposium STAIRS), the first-ever international symposium specifically aimed at Ph.D. students in AI. The outcome was a thorough, high-quality, and successful event, with all the features one usually finds in the best international conferences: large international committees, comprehensive coverage, published proceedings, renowned speakers and panelists, sub...

  19. ARTIFICIAL INTELLIGENCE- BENEFITS, CHALLENGES AND ETHICAL ISSUES

    OpenAIRE

    Elena Juganaru Andreou

    2017-01-01

    Nowadays, all big companies and most of small businesses are focused on increasing profitability and improving competitiveness. With this goal in mind, many of them turned to replace many tasks performed by humans with Artificial Intelligence. Artificial Intelligence (AI) is receiving an increasing attention lately and the debate is fiercely growing with a question not being answered yet: will it change the world for the better or for worse?

  20. Artificial Intelligence: Realizing the Ultimate Promises of Computing

    OpenAIRE

    Waltz, David L.

    1997-01-01

    Artificial intelligence (AI) is the key technology in many of today's novel applications, ranging from banking systems that detect attempted credit card fraud, to telephone systems that understand speech, to software systems that notice when you're having problems and offer appropriate advice. These technologies would not exist today without the sustained federal support of fundamental AI research over the past three decades.

  1. Robotics, Artificial Intelligence, Computer Simulation: Future Applications in Special Education.

    Science.gov (United States)

    Moore, Gwendolyn B.; And Others

    1986-01-01

    Describes possible applications of new technologies to special education. Discusses results of a study designed to explore the use of robotics, artificial intelligence, and computer simulations to aid people with handicapping conditions. Presents several scenarios in which specific technological advances may contribute to special education…

  2. The future of artificial intelligence in nuclear plant maintenance

    International Nuclear Information System (INIS)

    Norgate, G.

    1984-01-01

    Robots with vision and force sensing capability, performing tasks under computer control, will offer new opportunities to reduce human exposure to radiation. Such machines do not yet exist and even simple maintenance tasks challenge current robot technology. Recently increased priority for research on artificial intelligence and fifth generation computer technology is likely to bring useful maintenance robots closer to reality

  3. Artificial Intelligence for Controlling Robotic Aircraft

    Science.gov (United States)

    Krishnakumar, Kalmanje

    2005-01-01

    A document consisting mostly of lecture slides presents overviews of artificial-intelligence-based control methods now under development for application to robotic aircraft [called Unmanned Aerial Vehicles (UAVs) in the paper] and spacecraft and to the next generation of flight controllers for piloted aircraft. Following brief introductory remarks, the paper presents background information on intelligent control, including basic characteristics defining intelligent systems and intelligent control and the concept of levels of intelligent control. Next, the paper addresses several concepts in intelligent flight control. The document ends with some concluding remarks, including statements to the effect that (1) intelligent control architectures can guarantee stability of inner control loops and (2) for UAVs, intelligent control provides a robust way to accommodate an outer-loop control architecture for planning and/or related purposes.

  4. Improving Tools in Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-01-01

    Full Text Available The historical origin of the Artificial Intelligence (AI is usually established in the Dartmouth Conference, of 1956. But we can find many more arcane origins [1]. Also, we can consider, in more recent times, very great thinkers, as Janos Neumann (then, John von Neumann, arrived in USA, Norbert Wiener, Alan Mathison Turing, or Lofti Zadeh, for instance [12, 14]. Frequently AI requires Logic. But its Classical version shows too many insufficiencies. So, it was necessary to introduce more sophisticated tools, as Fuzzy Logic, Modal Logic, Non-Monotonic Logic and so on [1, 2]. Among the things that AI needs to represent are categories, objects, properties, relations between objects, situations, states, time, events, causes and effects, knowledge about knowledge, and so on. The problems in AI can be classified in two general types [3, 5], search problems and representation problems. On this last "peak", there exist different ways to reach their summit. So, we have [4] Logics, Rules, Frames, Associative Nets, Scripts, and so on, many times connected among them. We attempt, in this paper, a panoramic vision of the scope of application of such representation methods in AI. The two more disputable questions of both modern philosophy of mind and AI will be perhaps the Turing Test and the Chinese Room Argument. To elucidate these very difficult questions, see our final note.

  5. Artificial Intelligence in planetary spectroscopy

    Science.gov (United States)

    Waldmann, Ingo

    2017-10-01

    The field of exoplanetary spectroscopy is as fast moving as it is new. Analysing currently available observations of exoplanetary atmospheres often invoke large and correlated parameter spaces that can be difficult to map or constrain. This is true for both: the data analysis of observations as well as the theoretical modelling of their atmospheres.Issues of low signal-to-noise data and large, non-linear parameter spaces are nothing new and commonly found in many fields of engineering and the physical sciences. Recent years have seen vast improvements in statistical data analysis and machine learning that have revolutionised fields as diverse as telecommunication, pattern recognition, medical physics and cosmology.In many aspects, data mining and non-linearity challenges encountered in other data intensive fields are directly transferable to the field of extrasolar planets. In this conference, I will discuss how deep neural networks can be designed to facilitate solving said issues both in exoplanet atmospheres as well as for atmospheres in our own solar system. I will present a deep belief network, RobERt (Robotic Exoplanet Recognition), able to learn to recognise exoplanetary spectra and provide artificial intelligences to state-of-the-art atmospheric retrieval algorithms. Furthermore, I will present a new deep convolutional network that is able to map planetary surface compositions using hyper-spectral imaging and demonstrate its uses on Cassini-VIMS data of Saturn.

  6. An artificial intelligence approach towards disturbance analysis

    International Nuclear Information System (INIS)

    Fiedler, U.; Lindner, A.; Baldeweg, F.; Klebau, J.

    1986-01-01

    Scale and degree of sophistication of technological plants, e.g. nuclear power plants, have been essentially increased during the last decades. Conventional disturbance analysis systems have proved to work successfully in well-known situations. But in cases of emergencies, the operator needs more advanced assistance in realizing diagnosis and therapy control. The significance of introducing artificial intelligence (AI) methods in nuclear power technology is emphasized. Main features of the on-line disturbance analysis system SAAP-2 are reported about. It is being developed for application to nuclear power plants. Problems related to man-machine communication will be gone into more detail, because their solution will influence end-user acceptance considerably. (author)

  7. Artificial intelligence approaches to software engineering

    Science.gov (United States)

    Johannes, James D.; Macdonald, James R.

    1988-01-01

    Artificial intelligence approaches to software engineering are examined. The software development life cycle is a sequence of not so well-defined phases. Improved techniques for developing systems have been formulated over the past 15 years, but pressure continues to attempt to reduce current costs. Software development technology seems to be standing still. The primary objective of the knowledge-based approach to software development presented in this paper is to avoid problem areas that lead to schedule slippages, cost overruns, or software products that fall short of their desired goals. Identifying and resolving software problems early, often in the phase in which they first occur, has been shown to contribute significantly to reducing risks in software development. Software development is not a mechanical process but a basic human activity. It requires clear thinking, work, and rework to be successful. The artificial intelligence approaches to software engineering presented support the software development life cycle through the use of software development techniques and methodologies in terms of changing current practices and methods. These should be replaced by better techniques that that improve the process of of software development and the quality of the resulting products. The software development process can be structured into well-defined steps, of which the interfaces are standardized, supported and checked by automated procedures that provide error detection, production of the documentation and ultimately support the actual design of complex programs.

  8. Artificial intelligence what everyone needs to know

    CERN Document Server

    Kaplan, Jerry

    2016-01-01

    Over the coming decades, Artificial Intelligence will profoundly impact the way we work and live. Whose interests should such systems serve? What limits should we place on their use? This book is a succinct introduction to the complex social, ethical, legal, and economic issues raised by the emergence of intelligent machines.

  9. Advanced solutions in power systems HVDC, facts, and artificial intelligence

    CERN Document Server

    Liu, Chen-Ching; Edris, Abdel-Aty

    2016-01-01

    Provides insight on both classical means and new trends in the application of power electronic and artificial intelligence techniques in power system operation and control This book presents advanced solutions for power system controllability improvement, transmission capability enhancement and operation planning. The book is organized into three parts. The first part describes the CSC-HVDC and VSC-HVDC technologies, the second part presents the FACTS devices, and the third part refers to the artificial intelligence techniques. All technologies and tools approached in this book are essential for power system development to comply with the smart grid requirements.

  10. Artificial Intelligence Approaches To UCAV Autonomy

    OpenAIRE

    Husain, Amir; Porter, Bruce

    2017-01-01

    This paper covers a number of approaches that leverage Artificial Intelligence algorithms and techniques to aid Unmanned Combat Aerial Vehicle (UCAV) autonomy. An analysis of current approaches to autonomous control is provided followed by an exploration of how these techniques can be extended and enriched with AI techniques including Artificial Neural Networks (ANN), Ensembling and Reinforcement Learning (RL) to evolve control strategies for UCAVs.

  11. PLANNING IN ARTIFICIAL INTELLIGENCE AND ROBOTICS (PAIR

    Directory of Open Access Journals (Sweden)

    Editorial, Foreword

    2016-11-01

    Full Text Available September 18th, 2016Deggendorf, Germanyhttp://robotics.fel.cvut.cz/pair16/Organized by: Artificial Intelligence Center Department of Computer Science Faculty of Electrical Engineering Czech Technical University in PragueTechnicka 2, Prague 6, 166 27, Czech RepublicGuest editors:Jan Faigl (Artificial Intelligence Center, Department of Computer Science, Faculty of Electrical Engineering, Czech Technical University in PragueJiří Vokřínek (Artificial Intelligence Center, Department of Computer Science, Faculty of Electrical Engineering, Czech Technical University in PragueScientific comittee:D. Belter (Poznań University of Technology, PolandW. Dorner (Technische Hochschule Deggendorf, GermanyJ. Faigl (Czech Technical University in PragueT. Krajník (University of Lincoln, United KingdomA. Komenda (Czech Technical University in PragueG. Kupris (Technische Hochschule Deggendorf, GermanyM. Rollo (Czech Technical University in PragueM. Saska (Czech Technical University in PragueJ. Vokřínek (Czech Technical University in PragueV. Vonásek (Czech Technical University in PragueK. Walas (Poznań University of Technology, Poland Foreword:The third year of the student conference on “Planning in Artificial Intelligence and Robotics” (PAIR continues in joining young researchers and students interested in robotics and artificial intelligence. In 2016, we follow the schema of the last year as a joint event with the RoboTour competition in Deggendorf, Germany. Thanks to the great collaboration with Gerald Kupris and Wolfgang Donner from Technische Hochschule Deggendorf and support from Czech Technical University under project No. SVK 26/16/F3 and Bayerisches Staatsministerium der Finanzen, für Landesentwicklung und Heimat, we have been able to provide accommodations and travel support to participants and an invited speaker. Fourteen papers have accepted and listed in the conference program. The papers have been authored by students from Central Europe

  12. A review of European applications of artificial intelligence to space

    Science.gov (United States)

    Drummond, Mark (Editor); Stewart, Helen (Editor)

    1993-01-01

    The purpose is to describe the applications of Artificial Intelligence (AI) to the European Space program that are being developed or have been developed. The results of a study sponsored by the Artificial Intelligence Research and Development program of NASA's Office of Advanced Concepts and Technology (OACT) are described. The report is divided into two sections. The first consists of site reports, which are descriptions of the AI applications seen at each place visited. The second section consists of two summaries which synthesize the information in the site reports by organizing this information in two different ways. The first organizes the material in terms of the type of application, e.g., data analysis, planning and scheduling, and procedure management. The second organizes the material in terms of the component technologies of Artificial Intelligence which the applications used, e.g., knowledge based systems, model based reasoning, procedural reasoning, etc.

  13. Research on artificial intelligence systems for nuclear installations

    International Nuclear Information System (INIS)

    Sakuma, Minoru

    1992-01-01

    The development and utilization of atomic energy in Japan has be advanced in conformity with the long term plan of atomic energy development and utilization decided in 1987. As one of the basic targets, the upbringing of creative and innovative science and technology is put up. Artificial intelligence technology has been positioned as one of the important basic technologies for promoting future atomic energy development. The research and development of artificial intelligence technology have been advanced aiming at making nuclear power stations autonomous, by the guidance of Science and Technology Agency and the cooperation of several research institutes. The upbringing of creative science and technology, the preponderant development of basic technology, the concept of developing the basic technology for atomic energy, the concept of autonomous plants, the standard for autonomy, the approach to autonomous plants, the present state of the researches in respective research institutes on autonomous operation and autonomous maintenance are described. (K.I.)

  14. Artificial intelligence in radiology: decision support systems.

    Science.gov (United States)

    Kahn, C E

    1994-07-01

    Computer-based systems that incorporate artificial intelligence techniques can help physicians make decisions about their patients' care. In radiology, systems have been developed to help physicians choose appropriate radiologic procedures and to formulate accurate diagnoses. These decision support systems use techniques such as rule-based reasoning, artificial neural networks, hypertext, Bayesian networks, and case-based reasoning. This article reviews these artificial intelligence techniques, describes their application in radiology, and discusses the role that decision support systems may play in radiology's future.

  15. Northeast Artificial Intelligence Consortium (NAIC). Volume 8. Artificial Intelligence Applications to Speech Recognition

    Science.gov (United States)

    1990-12-01

    AD-A234 887 RADC-TR-90-404, Vol VIII (of 18) Final Technical Report December 1990 ARTIFICIAL INTELLIGENCE APPLICATIONS TO SPEECH RECOGNITION...AND SUBl7TLE 5. FUNIOING NUMBERS ARTIFICIAL INTELLIGENCE APPLICATIONS TO SPEECH C - F30602-85-C-0008 RECOGNITION eE - b2702F AUTHOR(S) PR - 5581 TA - 27

  16. Artificial Intelligence as a Means to Moral Enhancement

    Directory of Open Access Journals (Sweden)

    Klincewicz Michał

    2016-12-01

    Full Text Available This paper critically assesses the possibility of moral enhancement with ambient intelligence technologies and artificial intelligence presented in Savulescu and Maslen (2015. The main problem with their proposal is that it is not robust enough to play a normative role in users’ behavior. A more promising approach, and the one presented in the paper, relies on an artificial moral reasoning engine, which is designed to present its users with moral arguments grounded in first-order normative theories, such as Kantianism or utilitarianism, that reason-responsive people can be persuaded by. This proposal can play a normative role and it is also a more promising avenue towards moral enhancement. It is more promising because such a system can be designed to take advantage of the sometimes undue trust that people put in automated technologies. We could therefore expect a well-designed moral reasoner system to be able to persuade people that may not be persuaded by similar arguments from other people. So, all things considered, there is hope in artificial intelligence for moral enhancement, but not in artificial intelligence that relies solely on ambient intelligence technologies.

  17. Clinical Note Creation, Binning, and Artificial Intelligence.

    Science.gov (United States)

    Deliberato, Rodrigo Octávio; Celi, Leo Anthony; Stone, David J

    2017-08-03

    The creation of medical notes in software applications poses an intrinsic problem in workflow as the technology inherently intervenes in the processes of collecting and assembling information, as well as the production of a data-driven note that meets both individual and healthcare system requirements. In addition, the note writing applications in currently available electronic health records (EHRs) do not function to support decision making to any substantial degree. We suggest that artificial intelligence (AI) could be utilized to facilitate the workflows of the data collection and assembly processes, as well as to support the development of personalized, yet data-driven assessments and plans. ©Rodrigo Octávio Deliberato, Leo Anthony Celi, David J Stone. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 03.08.2017.

  18. Artificial intelligence in process design and operation

    International Nuclear Information System (INIS)

    Sudduth, A.L.

    1988-01-01

    Artificial Intelligence (AI) has recently become prominent in the discussion of computer applications in the utility business. In order to assess this technology, a research project was performed to determine whether software development techniques based on AI could be used to facilitate management of information associated with the design of a generating station. The approach taken was the development of an expert system, using a relatively simple set of rules acting on a more complex knowledge base. A successful prototype for the application was developed and its potential extension to a production environment demonstrated. During the course of prototype development, other possible applications of AI in design engineering were discovered, and areas of particular interest selected for further investigation. A plan for AI R and D was formulated. That plan and other possible future work in AI are discussed

  19. Heading toward Artificial Intelligence 2.0

    Directory of Open Access Journals (Sweden)

    Yunhe Pan

    2016-12-01

    Full Text Available With the popularization of the Internet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society, physical space, and cyberspace, the information environment related to the current development of artificial intelligence (AI has profoundly changed. AI faces important adjustments, and scientific foundations are confronted with new breakthroughs, as AI enters a new stage: AI 2.0. This paper briefly reviews the 60-year developmental history of AI, analyzes the external environment promoting the formation of AI 2.0 along with changes in goals, and describes both the beginning of the technology and the core idea behind AI 2.0 development. Furthermore, based on combined social demands and the information environment that exists in relation to Chinese development, suggestions on the development of AI 2.0 are given.

  20. Northeast Artificial Intelligence Consortium Annual Report 1986: Artificial Intelligence Applications to Speech Recognition. Volume 7

    Science.gov (United States)

    1988-06-01

    CONSORTIUM ANNUAL REPORT 1986 Artificial Intelligence Applications to Speech Recognition 12- PERSONAL AUTHOR(S) H. E. Rhody, J. Hillenbrand, J. A. Biles...funded partially by the Laboratory Directors’ Fund. By.... Dit: ;b! A!- UNCLASSIFIED %%v IZ. 7 ARTIFICIAL INTELLIGENCE APPLICATIONS TO SPEECH... Intelligence Applications to Speech Recognition Syracuse University ’ II. E. Rhody, J. Hillenbrand and J. A. Bites rT~s effort was funded partially by tho

  1. Artificial intelligence for analyzing orthopedic trauma radiographs

    Science.gov (United States)

    Olczak, Jakub; Fahlberg, Niklas; Maki, Atsuto; Razavian, Ali Sharif; Jilert, Anthony; Stark, André; Sköldenberg, Olof

    2017-01-01

    Background and purpose — Recent advances in artificial intelligence (deep learning) have shown remarkable performance in classifying non-medical images, and the technology is believed to be the next technological revolution. So far it has never been applied in an orthopedic setting, and in this study we sought to determine the feasibility of using deep learning for skeletal radiographs. Methods — We extracted 256,000 wrist, hand, and ankle radiographs from Danderyd’s Hospital and identified 4 classes: fracture, laterality, body part, and exam view. We then selected 5 openly available deep learning networks that were adapted for these images. The most accurate network was benchmarked against a gold standard for fractures. We furthermore compared the network’s performance with 2 senior orthopedic surgeons who reviewed images at the same resolution as the network. Results — All networks exhibited an accuracy of at least 90% when identifying laterality, body part, and exam view. The final accuracy for fractures was estimated at 83% for the best performing network. The network performed similarly to senior orthopedic surgeons when presented with images at the same resolution as the network. The 2 reviewer Cohen’s kappa under these conditions was 0.76. Interpretation — This study supports the use for orthopedic radiographs of artificial intelligence, which can perform at a human level. While current implementation lacks important features that surgeons require, e.g. risk of dislocation, classifications, measurements, and combining multiple exam views, these problems have technical solutions that are waiting to be implemented for orthopedics. PMID:28681679

  2. Artificial intelligence in a mission operations and satellite test environment

    Science.gov (United States)

    Busse, Carl

    1988-01-01

    A Generic Mission Operations System using Expert System technology to demonstrate the potential of Artificial Intelligence (AI) automated monitor and control functions in a Mission Operations and Satellite Test environment will be developed at the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Expert system techniques in a real time operation environment are being studied and applied to science and engineering data processing. Advanced decommutation schemes and intelligent display technology will be examined to develop imaginative improvements in rapid interpretation and distribution of information. The Generic Payload Operations Control Center (GPOCC) will demonstrate improved data handling accuracy, flexibility, and responsiveness in a complex mission environment. The ultimate goal is to automate repetitious mission operations, instrument, and satellite test functions by the applications of expert system technology and artificial intelligence resources and to enhance the level of man-machine sophistication.

  3. Distributed Computing and Artificial Intelligence, 12th International Conference

    CERN Document Server

    Malluhi, Qutaibah; Gonzalez, Sara; Bocewicz, Grzegorz; Bucciarelli, Edgardo; Giulioni, Gianfranco; Iqba, Farkhund

    2015-01-01

    The 12th International Symposium on Distributed Computing and Artificial Intelligence 2015 (DCAI 2015) is a forum to present applications of innovative techniques for studying and solving complex problems. The exchange of ideas between scientists and technicians from both the academic and industrial sector is essential to facilitate the development of systems that can meet the ever-increasing demands of today’s society. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This symposium is organized by the Osaka Institute of Technology, Qatar University and the University of Salamanca.

  4. [Advances in the research of application of artificial intelligence in burn field].

    Science.gov (United States)

    Li, H H; Bao, Z X; Liu, X B; Zhu, S H

    2018-04-20

    Artificial intelligence has been able to automatically learn and judge large-scale data to some extent. Based on database of a large amount of burn data and in-depth learning, artificial intelligence can assist burn surgeons to evaluate burn surface, diagnose burn depth, guide fluid supply during shock stage, and predict prognosis, with high accuracy. With the development of technology, artificial intelligence can provide more accurate information for burn surgeons to make clinical diagnosis and treatment strategies.

  5. Distributed computing and artificial intelligence : 10th International Conference

    CERN Document Server

    Neves, José; Rodriguez, Juan; Santana, Juan; Gonzalez, Sara

    2013-01-01

    The International Symposium on Distributed Computing and Artificial Intelligence 2013 (DCAI 2013) is a forum in which applications of innovative techniques for solving complex problems are presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. This conference is a stimulating and productive forum where the scientific community can work towards future cooperation in Distributed Computing and Artificial Intelligence areas. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both the academic and industry se...

  6. Artificial intelligence and robot responsibilities: innovating beyond rights.

    Science.gov (United States)

    Ashrafian, Hutan

    2015-04-01

    The enduring innovations in artificial intelligence and robotics offer the promised capacity of computer consciousness, sentience and rationality. The development of these advanced technologies have been considered to merit rights, however these can only be ascribed in the context of commensurate responsibilities and duties. This represents the discernable next-step for evolution in this field. Addressing these needs requires attention to the philosophical perspectives of moral responsibility for artificial intelligence and robotics. A contrast to the moral status of animals may be considered. At a practical level, the attainment of responsibilities by artificial intelligence and robots can benefit from the established responsibilities and duties of human society, as their subsistence exists within this domain. These responsibilities can be further interpreted and crystalized through legal principles, many of which have been conserved from ancient Roman law. The ultimate and unified goal of stipulating these responsibilities resides through the advancement of mankind and the enduring preservation of the core tenets of humanity.

  7. Tuberculosis control, and the where and why of artificial intelligence

    Science.gov (United States)

    Falzon, Dennis; Thomas, Bruce V.; Temesgen, Zelalem; Sadasivan, Lal; Raviglione, Mario

    2017-01-01

    Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB. PMID:28656130

  8. Tuberculosis control, and the where and why of artificial intelligence

    Directory of Open Access Journals (Sweden)

    Riddhi Doshi

    2017-06-01

    Full Text Available Countries aiming to reduce their tuberculosis (TB burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

  9. Tuberculosis control, and the where and why of artificial intelligence.

    Science.gov (United States)

    Doshi, Riddhi; Falzon, Dennis; Thomas, Bruce V; Temesgen, Zelalem; Sadasivan, Lal; Migliori, Giovanni Battista; Raviglione, Mario

    2017-04-01

    Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

  10. 9th International conference on distributed computing and artificial intelligence

    CERN Document Server

    Santana, Juan; González, Sara; Molina, Jose; Bernardos, Ana; Rodríguez, Juan; DCAI 2012; International Symposium on Distributed Computing and Artificial Intelligence 2012

    2012-01-01

    The International Symposium on Distributed Computing and Artificial Intelligence 2012 (DCAI 2012) is a stimulating and productive forum where the scientific community can work towards future cooperation in Distributed Computing and Artificial Intelligence areas. This conference is a forum in which  applications of innovative techniques for solving complex problems will be presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both the academic and indus...

  11. Putting artificial intelligence to work: Evaluating and implementing business applications

    Energy Technology Data Exchange (ETDEWEB)

    Schoen, S.; Sykes, W.; Little, A.D.

    1987-01-01

    This is a guide on applying the emerging technology of artificial intelligence and expert systems to the corporate environment. The authors focus on specific, practical applications and provide ways to set them in motion, including advice on determining realistic applications, evaluating costs, getting authorization for a purchase, and implementing AI and expert systems.

  12. Beyond AI: Multi-Intelligence (MI Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

    Directory of Open Access Journals (Sweden)

    Stephen Fox

    2017-06-01

    Full Text Available Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, the extensive post-anthropocentric research into intelligence is not given sufficient consideration. Third, AI is discussed often in reductionist mechanistic terms. Rather than in organicist emergentist terms as a contributor to multi-intelligence (MI hybrid beings and/or systems. Thus, current framing of AI can be a self-validating reduction within which AI development is focused upon AI becoming the single-variable mechanism causing future effects. In this paper, AI is reframed as a contributor to MI.

  13. Modeling the effects of light and sucrose on in vitro propagated plants: a multiscale system analysis using artificial intelligence technology.

    Directory of Open Access Journals (Sweden)

    Jorge Gago

    Full Text Available Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale. Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology.In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122-130 µmol m(-2 s(-1.Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work.

  14. Artificial intelligence: contemporary applications and future compass.

    Science.gov (United States)

    Khanna, Sunali

    2010-08-01

    The clinical use of information technology in the dental profession has increased substantially in the past 10 to 20 years. In most developing countries an insufficiency of medical and dental specialists has increased the mortality of patients suffering from various diseases. Employing technology, especially artificial intelligence technology, in medical and dental application could reduce cost, time, human expertise and medical error. This approach has the potential to revolutionise the dental public health scenario in developing countries. Clinical decision support systems (CDSS) are computer programs that are designed to provide expert support for health professionals. The applications in dental sciences vary from dental emergencies to differential diagnosis of orofacial pain, radiographic interpretations, analysis of facial growth in orthodontia to prosthetic dentistry. However, despite the recognised need for CDSS, the implementation of these systems has been limited and slow. This can be attributed to lack of formal evaluation of the systems, challenges in developing standard representations, cost and practitioner scepticism about the value and feasibility of CDSS. Increasing public awareness of safety and quality has accelerated the adoption of generic knowledge based CDSS. Information technology applications for dental practice continue to develop rapidly and will hopefully contribute to reduce the morbidity and mortality of oral and maxillofacial diseases and in turn impact patient care.

  15. Human-in-the-loop Artificial Intelligence

    OpenAIRE

    Zanzotto, Fabio Massimo

    2017-01-01

    Little by little, newspapers are revealing the bright future that Artificial Intelligence (AI) is building. Intelligent machines will help everywhere. However, this bright future has a dark side: a dramatic job market contraction before its unpredictable transformation. Hence, in a near future, large numbers of job seekers will need financial support while catching up with these novel unpredictable jobs. This possible job market crisis has an antidote inside. In fact, the rise of AI is sustai...

  16. Algorithms and architectures of artificial intelligence

    CERN Document Server

    Tyugu, E

    2007-01-01

    This book gives an overview of methods developed in artificial intelligence for search, learning, problem solving and decision-making. It gives an overview of algorithms and architectures of artificial intelligence that have reached the degree of maturity when a method can be presented as an algorithm, or when a well-defined architecture is known, e.g. in neural nets and intelligent agents. It can be used as a handbook for a wide audience of application developers who are interested in using artificial intelligence methods in their software products. Parts of the text are rather independent, so that one can look into the index and go directly to a description of a method presented in the form of an abstract algorithm or an architectural solution. The book can be used also as a textbook for a course in applied artificial intelligence. Exercises on the subject are added at the end of each chapter. Neither programming skills nor specific knowledge in computer science are expected from the reader. However, some p...

  17. Knowledge representation an approach to artificial intelligence

    CERN Document Server

    Bench-Capon, TJM

    1990-01-01

    Although many texts exist offering an introduction to artificial intelligence (AI), this book is unique in that it places an emphasis on knowledge representation (KR) concepts. It includes small-scale implementations in PROLOG to illustrate the major KR paradigms and their developments.****back cover copy:**Knowledge representation is at the heart of the artificial intelligence enterprise: anyone writing a program which seeks to work by encoding and manipulating knowledge needs to pay attention to the scheme whereby he will represent the knowledge, and to be aware of the consequences of the ch

  18. A Transitive Model For Artificial Intelligence Applications

    Science.gov (United States)

    Dwyer, John

    1986-03-01

    A wide range of mathematical techniques have been applied to artificial intelligence problems and some techniques have proved more suitable than others for certain types of problem. We formally define a mathematical model which incorporates some of these successful techniques and we discuss its intrinsic properties. Universal applicability of the model is demonstrated through specific applications to problems drawn from rule-based systems, digital hardware design and constraint satisfaction networks. We also give indications of potential applications to other artificial intelligence problems, including knowledge engineering.

  19. Application Of Artificial Intelligence To Wind Tunnels

    Science.gov (United States)

    Lo, Ching F.; Steinle, Frank W., Jr.

    1989-01-01

    Report discusses potential use of artificial-intelligence systems to manage wind-tunnel test facilities at Ames Research Center. One of goals of program to obtain experimental data of better quality and otherwise generally increase productivity of facilities. Another goal to increase efficiency and expertise of current personnel and to retain expertise of former personnel. Third goal to increase effectiveness of management through more efficient use of accumulated data. System used to improve schedules of operation and maintenance of tunnels and other equipment, assignment of personnel, distribution of electrical power, and analysis of costs and productivity. Several commercial artificial-intelligence computer programs discussed as possible candidates for use.

  20. Machine learning an artificial intelligence approach

    CERN Document Server

    Banerjee, R; Bradshaw, Gary; Carbonell, Jaime Guillermo; Mitchell, Tom Michael; Michalski, Ryszard Spencer

    1983-01-01

    Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV a

  1. Beyond AI: Interdisciplinary Aspects of Artificial Intelligence

    CERN Document Server

    Romportl, Jan; Zackova, Eva; Beyond Artificial Intelligence : Contemplations, Expectations, Applications

    2013-01-01

    Products of modern artificial intelligence (AI) have mostly been formed by the views, opinions and goals of the “insiders”, i.e. people usually with engineering background who are driven by the force that can be metaphorically described as the pursuit of the craft of Hephaestus. However, since the present-day technology allows for tighter and tighter mergence of the “natural” everyday human life with machines of immense complexity, the responsible reaction of the scientific community should be based on cautious reflection of what really lies beyond AI, i.e. on the frontiers where the tumultuous ever-growing and ever-changing cloud of AI touches the rest of the world.   The chapters of this boo are based on the selected subset of the presentations that were delivered by their respective authors at the conference “Beyond AI: Interdisciplinary Aspects of Artificial Intelligence” held in Pilsen in December 2011.   From its very definition, the reflection of the phenomena that lie beyond AI must be i...

  2. Artificial Intelligence in Surgery: Promises and Perils.

    Science.gov (United States)

    Hashimoto, Daniel A; Rosman, Guy; Rus, Daniela; Meireles, Ozanan R

    2018-01-31

    The aim of this review was to summarize major topics in artificial intelligence (AI), including their applications and limitations in surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new developments. AI is composed of various subfields that each provide potential solutions to clinical problems. Each of the core subfields of AI reviewed in this piece has also been used in other industries such as the autonomous car, social networks, and deep learning computers. A review of AI papers across computer science, statistics, and medical sources was conducted to identify key concepts and techniques within AI that are driving innovation across industries, including surgery. Limitations and challenges of working with AI were also reviewed. Four main subfields of AI were defined: (1) machine learning, (2) artificial neural networks, (3) natural language processing, and (4) computer vision. Their current and future applications to surgical practice were introduced, including big data analytics and clinical decision support systems. The implications of AI for surgeons and the role of surgeons in advancing the technology to optimize clinical effectiveness were discussed. Surgeons are well positioned to help integrate AI into modern practice. Surgeons should partner with data scientists to capture data across phases of care and to provide clinical context, for AI has the potential to revolutionize the way surgery is taught and practiced with the promise of a future optimized for the highest quality patient care.

  3. Statistical Software and Artificial Intelligence: A Watershed in Applications Programming.

    Science.gov (United States)

    Pickett, John C.

    1984-01-01

    AUTOBJ and AUTOBOX are revolutionary software programs which contain the first application of artificial intelligence to statistical procedures used in analysis of time series data. The artificial intelligence included in the programs and program features are discussed. (JN)

  4. An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

    Science.gov (United States)

    1996-01-01

    An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems appli...

  5. Abstraction in artificial intelligence and complex systems

    CERN Document Server

    Saitta, Lorenza

    2013-01-01

    Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences.  After discussing the characterizing properties of abstraction, a formal model, the K

  6. Solving Complex Logistics Problems with Multi-Artificial Intelligent System

    Directory of Open Access Journals (Sweden)

    Y.K. Tse

    2009-10-01

    Full Text Available The economy, which has become more information intensive, more global and more technologically dependent, is undergoing dramatic changes. The role of logistics is also becoming more and more important. In logistics, the objective of service providers is to fulfill all customers? demands while adapting to the dynamic changes of logistics networks so as to achieve a higher degree of customer satisfaction and therefore a higher return on investment. In order to provide high quality service, knowledge and information sharing among departments becomes a must in this fast changing market environment. In particular, artificial intelligence (AI technologies have achieved significant attention for enhancing the agility of supply chain management, as well as logistics operations. In this research, a multi-artificial intelligence system, named Integrated Intelligent Logistics System (IILS is proposed. The objective of IILS is to provide quality logistics solutions to achieve high levels of service performance in the logistics industry. The new feature of this agile intelligence system is characterized by the incorporation of intelligence modules through the capabilities of the case-based reasoning, multi-agent, fuzzy logic and artificial neural networks, achieving the optimization of the performance of organizations.

  7. Artificial Intelligence, Computational Thinking, and Mathematics Education

    Science.gov (United States)

    Gadanidis, George

    2017-01-01

    Purpose: The purpose of this paper is to examine the intersection of artificial intelligence (AI), computational thinking (CT), and mathematics education (ME) for young students (K-8). Specifically, it focuses on three key elements that are common to AI, CT and ME: agency, modeling of phenomena and abstracting concepts beyond specific instances.…

  8. Artificial Intelligence. LC Science Tracer Bullet.

    Science.gov (United States)

    Rodgers, Kay, Comp.

    Desgined to serve as a guide to resources on artificial intelligence (AI) and expert systems, this Library of Congress bulletin is divided into 18 sections that contain lists of books, journal articles, periodicals, associations, and other sources of information. A brief statement of the scope of the guide introduces the sections, which are listed…

  9. Artificial Intelligence, Counseling, and Cognitive Psychology.

    Science.gov (United States)

    Brack, Greg; And Others

    With the exception of a few key writers, counselors largely ignore the benefits that Artificial Intelligence (AI) and Cognitive Psychology (CP) can bring to counseling. It is demonstrated that AI and CP can be integrated into the counseling literature. How AI and CP can offer new perspectives on information processing, cognition, and helping is…

  10. Artificial Intelligence Techniques: Applications for Courseware Development.

    Science.gov (United States)

    Dear, Brian L.

    1986-01-01

    Introduces some general concepts and techniques of artificial intelligence (natural language interfaces, expert systems, knowledge bases and knowledge representation, heuristics, user-interface metaphors, and object-based environments) and investigates ways these techniques might be applied to analysis, design, development, implementation, and…

  11. Yale Artificial Intelligence Project (Research in Progress)

    OpenAIRE

    Collins, Gregg

    1981-01-01

    The Yale Artificial Intelligence Project, under the direction of Professor Roger C. Schank, supports a number of research projects. Most of this research is in the02-02 area of attempting to model the processes involved in human understanding, with a current emphasis on memory models and the processes involved in learning.

  12. Event tree analysis using artificial intelligence techniques

    International Nuclear Information System (INIS)

    Dixon, B.W.; Hinton, M.F.

    1985-01-01

    Artificial Intelligence (AI) techniques used in Expert Systems and Object Oriented Programming are discussed as they apply to Event Tree Analysis. A SeQUence IMPortance calculator, SQUIMP, is presented to demonstrate the implementation of these techniques. Benefits of using AI methods include ease of programming, efficiency of execution, and flexibility of application. The importance of an appropriate user interface is stressed. 5 figs

  13. Employing Artificial Intelligence To Minimise Internet Fraud

    Directory of Open Access Journals (Sweden)

    Edward Wong Sek Khin

    2009-12-01

    Full Text Available Internet fraud is increasing on a daily basis with new methods for extracting funds from government, corporations, businesses in general, and persons appearing almost hourly. The increases in on-line purchasing and the constant vigilance of both seller and buyer have meant that the criminal seems to be one-step ahead at all times. To pre-empt or to stop fraud before it can happen occurs in the non-computer based daily transactions of today because of the natural intelligence of the players, both seller and buyer. Currently, even with advances in computing techniques, intelligence is not the current strength of any computing system of today, yet techniques are available which may reduce the occurrences of fraud, and are usually referred to as artificial intelligence systems.This paper provides an overview of the use of current artificial intelligence (AI techniques as a means of combating fraud.Initially the paper describes how artificial intelligence techniques are employed in systems for detecting credit card fraud (online and offline fraud and insider trading.Following this, an attempt is made to propose the using of MonITARS (Monitoring Insider Trading and Regulatory Surveillance Systems framework which use a combination of genetic algorithms, neural nets and statistical analysis in detecting insider dealing. Finally, the paper discusses future research agenda to the role of using MonITARS system.

  14. An introduction to artificial intelligence and its potential use in space systems.

    OpenAIRE

    McDonald, Gary Wayne

    1986-01-01

    Approved for public release; distribution is unlimited This thesis provides an introduction to Artificial Intelligence and Space Systems, with comments regarding their integration. The survey of Artificial Intelligence (AI) is based upon a review of its history, its philosophical development, and subcategories of its current technologies. These subcategories are Expert Systems (ES), Natural Language Processing (NLP), Computer Vision and Pattern Recognition, and Robotic...

  15. Artificial Intelligence in Information Services: Revolution or Survival?

    OpenAIRE

    Mess, John A

    2012-01-01

    The evolution of society places a growing demand on access to information. Libraries have been pivotal in shaping society by providing this access, but now that role has been altered by information dynamics and knowledge economics. The rapid advances in computer technology and software design, especially in artificial intelligence, have shifted libraries to a "demand" economy. Unless libraries begin exploiting the technologies and innovate manage information and knowledge, they may face obsol...

  16. Artificial intelligence and information-control systems of robots - 87

    International Nuclear Information System (INIS)

    Plander, I.

    1987-01-01

    Independent research areas of artificial intelligence represent the following problems: automatic problem solving and new knowledge discovering, automatic program synthesis, natural language, picture and scene recognition and understanding, intelligent control systems of robots equipped with sensoric subsystems, dialogue of two knowledge systems, as well as studying and modelling higher artificial intelligence attributes, such as emotionality and personality. The 4th Conference draws on the problems treated at the preceding Conferences, and presents the most recent knowledge on the following topics: theoretical problems of artificial intelligence, knowledge-based systems, expert systems, perception and pattern recognition, robotics, intelligent computer-aided design, special-purpose computer systems for artificial intelligence and robotics

  17. 2nd International Conference on Robot Intelligence Technology and Applications

    CERN Document Server

    Matson, Eric; Myung, Hyun; Xu, Peter; Karray, Fakhri

    2014-01-01

    We are facing a new technological challenge on how to store and retrieve knowledge and manipulate intelligence for autonomous services by intelligent systems which should be capable of carrying out real world tasks autonomously. To address this issue, robot researchers have been developing intelligence technology (InT) for “robots that think” which is in the focus of this book. The book covers all aspects of intelligence from perception at sensor level and reasoning at cognitive level to behavior planning at execution level for each low level segment of the machine. It also presents the technologies for cognitive reasoning, social interaction with humans, behavior generation, ability to cooperate with other robots, ambience awareness, and an artificial genome that can be passed on to other robots. These technologies are to materialize cognitive intelligence, social intelligence, behavioral intelligence, collective intelligence, ambient intelligence and genetic intelligence. The book aims at serving resear...

  18. Application of artificial intelligence in process control

    CERN Document Server

    Krijgsman, A

    1993-01-01

    This book is the result of a united effort of six European universities to create an overall course on the appplication of artificial intelligence (AI) in process control. The book includes an introduction to key areas including; knowledge representation, expert, logic, fuzzy logic, neural network, and object oriented-based approaches in AI. Part two covers the application to control engineering, part three: Real-Time Issues, part four: CAD Systems and Expert Systems, part five: Intelligent Control and part six: Supervisory Control, Monitoring and Optimization.

  19. Artificial intelligence applications to nuclear reactor diagnostics

    International Nuclear Information System (INIS)

    Lee, J.C.; Hassberger, J.A.; Wehe, D.K.

    1987-01-01

    The authors research into applications of artificial intelligence to nuclear reactor diagnostics involves three main areas. In the first area, the authors combine reactor simulation models and expert systems to diagnose the state of the plant. The second area examines ways in which the rule or knowledge base of an intelligent controller can be generated systematically from either fault trees or acquired plant data. Third, efforts are described to develop the capabilities to validate these techniques in a realistic reactor setting. The techniques are applicable to all reactor types, including fast reactors

  20. Using artificial intelligence to automate remittance processing.

    Science.gov (United States)

    Adams, W T; Snow, G M; Helmick, P M

    1998-06-01

    The consolidated business office of the Allegheny Health Education Research Foundation (AHERF), a large integrated healthcare system based in Pittsburgh, Pennsylvania, sought to improve its cash-related business office activities by implementing an automated remittance processing system that uses artificial intelligence. The goal was to create a completely automated system whereby all monies it processed would be tracked, automatically posted, analyzed, monitored, controlled, and reconciled through a central database. Using a phased approach, the automated payment system has become the central repository for all of the remittances for seven of the hospitals in the AHERF system and has allowed for the complete integration of these hospitals' existing billing systems, document imaging system, and intranet, as well as the new automated payment posting, and electronic cash tracking and reconciling systems. For such new technology, which is designed to bring about major change, factors contributing to the project's success were adequate planning, clearly articulated objectives, marketing, end-user acceptance, and post-implementation plan revision.

  1. Distributed artificial intelligence, diversity and information literacy

    Directory of Open Access Journals (Sweden)

    Peter Kåhre

    2010-09-01

    Full Text Available My proposal is based on my doctoral dissertation On the Shoulders of AI-technology : Sociology of Knowledge and Strong Artificial Intelligence which I succesfully defended on May 29th 2009. E-published http://www.lu.se/o.o.i.s?id=12588&postid=1389611 The dissertation is concerned with Sociology’s stance in the debate on Strong Artificial Intelligence,.i.e. AI-systems that is able to shape knowledge on their own. There is a need for sociologists to realize the difference between two approaches to constructing AI systems: Symbolic AI (or Classic AI and Connectionistic AI in a distributed model – DAI. Sociological literature shows a largely critical attitude towards Symbolic AI, an attitude that is justified. The main theme of the dissertation is that DAI is not only compatible with Sociology’s approach to what is social, but also constitutes an apt model of how a social system functions. This is consolidated with help from german sociologist Niklas Luhmann’s social systems theory. A lot of sociologists criticize AI because they think that diversity is important and can only be comprehended in informal circumstances that only humans interacting together can handle. They mean that social intelligence is needed to make something out of diversity and informalism. Luhmann´s systems theory gives the opposite perspective. It tells us that it is social systems that communicate and produce new knowledge structures out of contincency. Psychological systems, i.e. humans, can only think within the circumstances the social system offer. In that way human thoughts are bound by formalism. Diversity is constructed when the social systems interact with complexity in their environments. They reduce the complexity and try to present it as meaningful diversity. Today when most of academic literature is electronically stored and is accessible through the Internet from al over the world, DAI can help social systems to observe and reduce complexity in this

  2. International Conference on Intelligent Technologies and Engineering System (ICITES 2012)

    CERN Document Server

    Huang, Yi-Cheng; Intelligent Technologies and Engineering Systems

    2013-01-01

    This book concentrates on intelligent technologies as it relates to engineering systems. The book covers the following topics: networking, signal processing, artificial intelligence, control and software engineering, intelligent electronic circuits and systems, communications, and materials and mechanical engineering. The book is a collection of original papers that have been reviewed by technical editors. These papers were presented at the International Conference on Intelligent Technologies and Engineering Systems, held Dec. 13-15, 2012.

  3. Projective simulation for artificial intelligence

    Science.gov (United States)

    Briegel, Hans J.; de Las Cuevas, Gemma

    2012-05-01

    We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.

  4. The role of artificial intelligence and expert systems in increasing STS operations productivity

    Science.gov (United States)

    Culbert, C.

    1985-01-01

    Artificial Intelligence (AI) is discussed. A number of the computer technologies pioneered in the AI world can make significant contributions to increasing STS operations productivity. Application of expert systems, natural language, speech recognition, and other key technologies can reduce manpower while raising productivity. Many aspects of STS support lend themselves to this type of automation. The artificial intelligence section of the mission planning and analysis division has developed a number of functioning prototype systems which demonstrate the potential gains of applying AI technology.

  5. Artificial intelligence as a diagnostic adjunct in cardiovascular nuclear imaging

    International Nuclear Information System (INIS)

    Duncan, J.S.

    1988-01-01

    The radiologist and/or nuclear medicine physician is literally bombarded with information from today's diagnostic imaging technologies. As a consequence of this, whereas a decade ago the emphasis in medical image analysis was on improving the extraction of diagnostic information by developing and using more sophisticated imaging modalities, today those working on the development of medical imaging technology are struggling to find ways to handle all gathered information effectively. This chapter gives an introduction to the area of artificial intelligence, with an emphasis on the research ongoing in cardiovascular nuclear imaging. This chapter has reviewed the place of artificial intelligence in cardiovascular nuclear imaging. It is intended to provide a general sense of this new and emerging field, an insight into some of its specific methodologies and applications, and a closer look at the several AI approaches currently being applied in cardiovascular nuclear imaging

  6. Artificial intelligence in nuclear power plants

    International Nuclear Information System (INIS)

    Haapanen, P.J.

    1990-01-01

    The IAEA Specialists' Meeting on Artificial Intelligence in Nuclear Power Plants was arranged in Helsink/Vantaa, Finland, on October 10-12, 1989, under auspices of the International Working Group of Nuclear Power Plant Control and Instrumentation of the International Atomic Energy Agency (IAEA/IWG NPPCI). Technical Research Centre of Finland together with Imatran Voima Oy and Teollisuuden Voima Oy answered for the practical arrangements of the meeting. 105 participants from 17 countries and 2 international organizations took part in the meeting and 58 papers were submitted for presentation. These papers gave a comprehensive picture of the recent status and further trends in applying the rapidly developing techniques of artificial intelligence and expert systems to improve the quality and safety in designing and using of nuclear power worldwide

  7. Artificial intelligence - NASA. [robotics for Space Station

    Science.gov (United States)

    Erickson, J. D.

    1985-01-01

    Artificial Intelligence (AI) represents a vital common space support element needed to enable the civil space program and commercial space program to perform their missions successfully. It is pointed out that advances in AI stimulated by the Space Station Program could benefit the U.S. in many ways. A fundamental challenge for the civil space program is to meet the needs of the customers and users of space with facilities enabling maximum productivity and having low start-up costs, and low annual operating costs. An effective way to meet this challenge may involve a man-machine system in which artificial intelligence, robotics, and advanced automation are integrated into high reliability organizations. Attention is given to the benefits, NASA strategy for AI, candidate space station systems, the Space Station as a stepping stone, and the commercialization of space.

  8. Artificial intelligence in medicine: the challenges ahead.

    Science.gov (United States)

    Coiera, E W

    1996-01-01

    The modern study of artificial intelligence in medicine (AIM) is 25 years old. Throughout this period, the field has attracted many of the best computer scientists, and their work represents a remarkable achievement. However, AIM has not been successful-if success is judged as making an impact on the practice of medicine. Much recent work in AIM has been focused inward, addressing problems that are at the crossroads of the parent disciplines of medicine and artificial intelligence. Now, AIM must move forward with the insights that it has gained and focus on finding solutions for problems at the heart of medical practice. The growing emphasis within medicine on evidence-based practice should provide the right environment for that change. PMID:8930853

  9. Artificial intelligence applications for operation and maintenance

    International Nuclear Information System (INIS)

    Itoh, M.; Tai, I.; Monta, K.; Sekimizu, K.

    1987-01-01

    A nuclear power plant as a typical man-machine system of the modern industry needs an efficient human window through which operators can observe every necessary detail of the plant for its safe and reliable operation. Much efforts have been devoted to the development of the computerized operator support systems (COSS). Recent development of artificial intelligence (AI) seems to offer new possibility to strengthen the performance of the COSS such as more powerful diagnosis and procedure synthesis and user friendly man-machine interfaces. From this point of view, a national project of Advanced Man-Machine System Development for Nuclear Power Plants has been carried out. Artificial intelligence application to nuclear power plant operation and maintenance is also selected as a major theme for the promotion of research and development on frontiers in the recently revised long term national program for development and utilization of nuclear energy in JAPAN

  10. Intelligent Decision Technologies : Proceedings of the 4th International Conference on Intelligent Decision Technologies

    CERN Document Server

    Watanabe, Toyohide; Phillips-Wren, Gloria; Howlett, Robert; Jain, Lakhmi

    2012-01-01

    The Intelligent Decision Technologies (IDT) International Conference encourages an interchange of research on intelligent systems and intelligent technologies that enhance or improve decision making. The focus of IDT is interdisciplinary and includes research on all aspects of intelligent decision technologies, from fundamental development to real applications. IDT has the potential to expand their support of decision making in such areas as finance, accounting, marketing, healthcare, medical and diagnostic systems, military decisions, production and operation, networks, traffic management, crisis response, human-machine interfaces, financial and stock market monitoring and prediction, and robotics. Intelligent decision systems implement advances in intelligent agents, fuzzy logic, multi-agent systems, artificial neural networks, and genetic algorithms, among others.  Emerging areas of active research include virtual decision environments, social networking, 3D human-machine interfaces, cognitive interfaces,...

  11. Rural architecture between artificial intelligence and natural intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Cennamo, M.; Palma, P. di; Ricciardelli, A. [University of Naples Frederico II (Italy). Dept. of Configurazione e Attuazione dell Architettra

    2000-02-01

    Following the field of research carried out and reported in the Second International Conference for Teachers of Architecture held in Florence on October 16, 17 and 18, 1997, which stated the central position of Architectural project in relation to Human Intelligence, Natural Intelligence and Artificial Intelligence, the present paper suggests a phase of application of the theoretical assumptions to spacial models paradigmatic of the complexity of projects and building technique, as well as of the relationship between man-made environment and natural one. Among the different typologies in architecture, this research focuses on the rural buildings in Campania, mainly on the ones in the Vesuvius area, as those are the most suitable to be studied and salvaged with the help of biology, mathematics and high engineering. (author)

  12. Artificial Intelligence techniques for big data analysis

    OpenAIRE

    Aditya Khatri

    2017-01-01

    During my stay in Salamanca (Spain), I was fortunate enough to participate in the BISITE Research Group of the University of Salamanca. The University of Salamanca is the oldest university in Spain and in 2018 it celebrates its 8th centenary. As a computer science researcher, I participated in one of the many international projects that the research group has active, especially in big data analysis using Artificial Intelligence (AI) techniques. AI is one of BISITE's main lines of rese...

  13. The Artificial Intelligence Workbench: a retrospective review

    OpenAIRE

    López-Fernández, Hugo; Reboiro-Jato, Miguel; Pérez Rodríguez, José A.; Fdez-Riverola, Florentino; Glez-Peña, Daniel

    2016-01-01

    Last decade, biomedical and bioinformatics researchers have been demanding advanced and user-friendly applications for real use in practice. In this context, the Artificial Intelligence Workbench, an open-source Java desktop application framework for scientific software development, emerged with the goal of provid-ing support to both fundamental and applied research in the domain of transla-tional biomedicine and bioinformatics. AIBench automatically provides function-alities that are common ...

  14. Artificial Intelligence in Mitral Valve Analysis

    OpenAIRE

    Jeganathan, Jelliffe; Knio, Ziyad; Amador, Yannis; Hai, Ting; Khamooshian, Arash; Matyal, Robina; Khabbaz, Kamal R; Mahmood, Feroze

    2017-01-01

    Background: Echocardiographic analysis of mitral valve (MV) has become essential for diagnosis and management of patients with MV disease. Currently, the various software used for MV analysis require manual input and are prone to interobserver variability in the measurements. Aim: The aim of this study is to determine the interobserver variability in an automated software that uses artificial intelligence for MV analysis. Settings and Design: Retrospective analysis of intraoperative three-dim...

  15. Artificial Intelligence Research in Australia -- A Profile

    OpenAIRE

    Smith, Elizabeth; Whitelaw, John

    1987-01-01

    Does the United States have a 51st state called Australia? A superficial look at the artificial intelligence (AI) research being done here could give that impression. A look beneath the surface, though, indicates some fundamental differences and reveals a dynamic and rapidly expanding AI community. General awareness of the Australian AI research community has been growing slowly for some time. AI was once considered a bit esoteric -- the domain of an almost lunatic fringe- but the large gover...

  16. Parallel processing for artificial intelligence 1

    CERN Document Server

    Kanal, LN; Kumar, V; Suttner, CB

    1994-01-01

    Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discus

  17. Artificial Intelligence Research at General Electric

    OpenAIRE

    Sweet, Larry

    1985-01-01

    General Electric is engaged in a broad range of research and development activities in artificial intelligence, with the dual objectives of improving the productivity of its internal operations and of enhancing future products and services in its aerospace, industrial, aircraft engine, commercial, and service sectors. Many of the applications projected for AI within GE will require significant advances in the state of the art in advanced inference, formal logic, and architectures for real-tim...

  18. A Plan for the Application of Artificial Intelligence to DoD Logistics

    Science.gov (United States)

    1989-10-01

    an annual Symposium and Workshop on Artificial Intelligence Applications for Military Logistics at Williamsburg, Virginia. The conference allows the...Staff (GM) AFB = Air Force Base AFLC = Air Force Logistics Command AI = Artificial Intelligence AIAG = Artificial Intelligence Applications Group (DEC...AIASC = Artificial Intelligence Applications Support Center (AFLC) AIBOD = Artificial Intelligence Board of Directors (DEC) AIC = Artificial

  19. Third International Conference on Artificial Intelligence Planning Systems

    OpenAIRE

    Drabble, Brian

    1997-01-01

    The Third International Conference on Artificial Intelligence Planning Systems (AIPS-96) was held in Edinburgh, Scotland, from 29 to 31 May 1996. The main gathering of researchers in AI and planning and scheduling, the conference promoted the practical applications of planning technologies. Details of the conference papers and sessions are provided as well as information on the Defense Advanced Research Projects Agency -- Rome Laboratory Planning Initiative.

  20. Artificial Intelligence Research at GTE Laboratories (Research in Progress)

    OpenAIRE

    Frawley, William; Goyal, Shri

    1984-01-01

    GTE Laboratories is the central corporate research and development facility for the sixty subsidiaries of the worldwide GTE corporation. Located in the Massachusetts Route 128 high technology area, the five laboratories that comprise GTE Laboratories generate the ideas, products, systems, and services that provide technical leadership for GTE. The two laboratories which conduct artificial intelligence research are the Computer Science Laboratory (CSL) and the Fundamental Research Laboratory (...

  1. A STUDY ON ARTIFICIAL INTELLIGENCE IN E-COMMERCE

    OpenAIRE

    Shyna Kakkar

    2017-01-01

    Artificial intelligence has the powerful ability to acquire and analyze large volumes of data and provide decisions for action. E-commerce is now adopting this technology to identify patterns based on browsing, purchase history, credit checks, account information etc. This data collected then form the basis of creating customized recommendations for each customer. Google and Microsoft are already investing into new AI initiatives. Many e-commerce businesses have started implementing different...

  2. Applications of artificial intelligence to scientific research

    Science.gov (United States)

    Prince, Mary Ellen

    1986-01-01

    Artificial intelligence (AI) is a growing field which is just beginning to make an impact on disciplines other than computer science. While a number of military and commercial applications were undertaken in recent years, few attempts were made to apply AI techniques to basic scientific research. There is no inherent reason for the discrepancy. The characteristics of the problem, rather than its domain, determines whether or not it is suitable for an AI approach. Expert system, intelligent tutoring systems, and learning programs are examples of theoretical topics which can be applied to certain areas of scientific research. Further research and experimentation should eventurally make it possible for computers to act as intelligent assistants to scientists.

  3. Artificial intelligence approach to legal reasoning

    International Nuclear Information System (INIS)

    Gardner, A.V.D.L.

    1984-01-01

    For artificial intelligence, understanding the forms of human reasoning is a central goal. Legal reasoning is a form that makes a new set of demands on artificial intelligence methods. Most importantly, a computer program that reasons about legal problems must be able to distinguish between questions it is competent to answer and questions that human lawyers could seriously argue either way. In addition, a program for analyzing legal problems should be able to use both general legal rules and decisions in past cases; and it should be able to work with technical concepts that are only partly defined and subject to shifts of meaning. Each of these requirements has wider applications in artificial intelligence, beyond the legal domain. This dissertation presents a computational framework for legal reasoning, within which such requirements can be accommodated. The development of the framework draws significantly on the philosophy of law, in which the elucidation of legal reasoning is an important topic. A key element of the framework is the legal distinction between hard cases and clear cases. In legal writing, this distinction has been taken for granted more often than it has been explored. Here, some initial heuristics are proposed by which a program might make the distinction

  4. Artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

    Schultz, D.E.; Hurd, J.W.; Brown, S.K.

    1987-01-01

    An experiment was recently started at LAMPF to evaluate the power and limitations of using artificial intelligence techniques to solve problems in accelerator control and operation. A knowledge base was developed to describe the characteristics and the relationships of the first 30 devices in the LAMPF H+ beam line. Each device was categorized and pertinent attributes for each category defined. Specific values were assigned in the knowledge base to represent each actual device. Relationships between devices are modeled using the artificial intelligence techniques of rules, active values, and object-oriented methods. This symbolic model, built using the Knowledge Engineering Environment (KEE) system, provides a framework for analyzing faults, tutoring trainee operators, and offering suggestions to assist in beam tuning. Based on information provided by the domain expert responsible for tuning this portion of the beam line, additional rules were written to describe how he tunes, how he analyzes what is actually happening, and how he deals with failures. Initial results have shown that artificial intelligence techniques can be a useful adjunct to traditional methods of numerical simulation. Successful and efficient operation of future accelerators may depend on the proper merging of symbolic reasoning and conventional numerical control algorithms

  5. Artificial intelligence research in anesthesia and intensive care.

    Science.gov (United States)

    Rennels, G D; Miller, P L

    1988-10-01

    This article describes several research directions exploring the application of artificial intelligence techniques in anesthesia and intensive care. Artificial intelligence can be loosely defined as the discipline of designing computer systems that exhibit "intelligent" behavior. This article first introduces artificial intelligence and computer science research and discusses why medicine has proved to be a challenging domain for applying artificial intelligence techniques. A discussion of the central research themes that arise in medical artificial intelligence, many of which are common to different projects and to different medical settings, is followed by a description of specific research projects that apply artificial intelligence techniques in anesthesiology, ventilatory management, and cardiovascular management. Finally, further comments are made on the current state of the field.

  6. A psychoanalyst artificial intelligence model in a computer game

    OpenAIRE

    Muñoz Fernández, Enrique

    2012-01-01

    Projecte realitzat en el marc d'un programa de mobilitat amb la Vienna University of Technology. [ANGLÈS] Implementation of an artificial intelligence model based on the psychoanalytic theory of the ID-Ego-SuperEgo of Sigmund Freud into the computer game Unreal Tournament 2004. [CASTELLÀ] Implementación de un modelo de inteligencia artificial basado en la teoría psicoanalítica del ID-Ego-SuperEgo de Sigmund Freud en el videojuego Unreal Tournament 2004. [CATALÀ] Implementació d'un mo...

  7. Expertik: Experience with Artificial Intelligence and Mobile Computing

    Directory of Open Access Journals (Sweden)

    José Edward Beltrán Lozano

    2013-06-01

    Full Text Available This article presents the experience in the development of services based in Artificial Intelligence, Service Oriented Architecture, mobile computing. It aims to combine technology offered by mobile computing provides techniques and artificial intelligence through a service provide diagnostic solutions to problems in industrial maintenance. It aims to combine technology offered by mobile computing and the techniques artificial intelligence through a service to provide diagnostic solutions to problems in industrial maintenance. For service creation are identified the elements of an expert system, the knowledge base, the inference engine and knowledge acquisition interfaces and their consultation. The applications were developed in ASP.NET under architecture three layers. The data layer was developed conjunction in SQL Server with data management classes; business layer in VB.NET and the presentation layer in ASP.NET with XHTML. Web interfaces for knowledge acquisition and query developed in Web and Mobile Web. The inference engine was conducted in web service developed for the fuzzy logic model to resolve requests from applications consulting knowledge (initially an exact rule-based logic within this experience to resolve requests from applications consulting knowledge. This experience seeks to strengthen a technology-based company to offer services based on AI for service companies Colombia.

  8. 4th International Conference on Robot Intelligence Technology and Applications

    CERN Document Server

    Karray, Fakhri; Jo, Jun; Sincak, Peter; Myung, Hyun

    2017-01-01

    This book covers all aspects of robot intelligence from perception at sensor level and reasoning at cognitive level to behavior planning at execution level for each low level segment of the machine. It also presents the technologies for cognitive reasoning, social interaction with humans, behavior generation, ability to cooperate with other robots, ambience awareness, and an artificial genome that can be passed on to other robots. These technologies are to materialize cognitive intelligence, social intelligence, behavioral intelligence, collective intelligence, ambient intelligence and genetic intelligence. The book aims at serving researchers and practitioners with a timely dissemination of the recent progress on robot intelligence technology and its applications, based on a collection of papers presented at the 4th International Conference on Robot Intelligence Technology and Applications (RiTA), held in Bucheon, Korea, December 14 - 16, 2015. For better readability, this edition has the total of 49 article...

  9. 3rd International Conference on Robot Intelligence Technology and Applications

    CERN Document Server

    Yang, Weimin; Jo, Jun; Sincak, Peter; Myung, Hyun

    2015-01-01

    This book covers all aspects of robot intelligence from perception at sensor level and reasoning at cognitive level to behavior planning at execution level for each low level segment of the machine. It also presents the technologies for cognitive reasoning, social interaction with humans, behavior generation, ability to cooperate with other robots, ambience awareness, and an artificial genome that can be passed on to other robots. These technologies are to materialize cognitive intelligence, social intelligence, behavioral intelligence, collective intelligence, ambient intelligence and genetic intelligence. The book aims at serving researchers and practitioners with a timely dissemination of the recent progress on robot intelligence technology and its applications, based on a collection of papers presented at the 3rd International Conference on Robot Intelligence Technology and Applications (RiTA), held in Beijing, China, November 6 - 8, 2014. For better readability, this edition has the total 74 papers group...

  10. Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

    Science.gov (United States)

    Mishra, D.; Goyal, P.

    2014-12-01

    Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

  11. QUESTION ANSWERING SYSTEM BERBASIS ARTIFICIAL INTELLIGENCE MARKUP LANGUAGE SEBAGAI MEDIA INFORMASI

    Directory of Open Access Journals (Sweden)

    Fajrin Azwary

    2016-04-01

    Full Text Available Artificial intelligence technology nowadays, can be processed with a variety of forms, such as chatbot, and the various methods, one of them using Artificial Intelligence Markup Language (AIML. AIML using template matching, by comparing the specific patterns in the database. AIML template design process begins with determining the necessary information, then formed into questions, these questions adapted to AIML pattern. From the results of the study, can be known that the Question-Answering System in the chatbot using Artificial Intelligence Markup Language are able to communicate and deliver information. Keywords: Artificial Intelligence, Template Matching, Artificial Intelligence Markup Language, AIML Teknologi kecerdasan buatan saat ini dapat diolah dengan berbagai macam bentuk, seperti ChatBot, dan berbagai macam metode, salah satunya menggunakan Artificial Intelligence Markup Language (AIML. AIML menggunakan metode template matching yaitu dengan membandingkan pola-pola tertentu pada database. Proses perancangan template AIML diawali dengan menentukan informasi yang diperlukan, kemudian dibentuk menjadi pertanyaan, pertanyaan tersebut disesuaikan dengan bentuk pattern AIML. Hasil penelitian dapat diperoleh bahwa Question-Answering System dalam bentuk ChatBot menggunakan Artificial Intelligence Markup Language dapat berkomunikasi dan menyampaikan informasi. Kata kunci : Kecerdasan Buatan, Pencocokan Pola, Artificial Intelligence Markup Language, AIML

  12. Enhancing nuclear power plant performance through the use of artificial intelligence

    International Nuclear Information System (INIS)

    Maren, A.J.; Miller, L.F.; Tsoukalas, L.H.; Uhrig, R.E.; Upadhyaya, B.R.

    1992-01-01

    The objective of this research was to advance the state-of-the-art of applying artificial intelligence technology (both expert systems and neural networks) to enhancing the performance (safety, efficiency, control and management) of nuclear power plants. A second, but equally important objective, was to build a broadly based critical mass of expertise in the artificial intelligence field that can be brought to bear on the technology of nuclear power plants

  13. Artificial Intelligence, DNA Mimicry, and Human Health

    Science.gov (United States)

    Stefano, George B.; Kream, Richard M.

    2017-01-01

    The molecular evolution of genomic DNA across diverse plant and animal phyla involved dynamic registrations of sequence modifications to maintain existential homeostasis to increasingly complex patterns of environmental stressors. As an essential corollary, driver effects of positive evolutionary pressure are hypothesized to effect concerted modifications of genomic DNA sequences to meet expanded platforms of regulatory controls for successful implementation of advanced physiological requirements. It is also clearly apparent that preservation of updated registries of advantageous modifications of genomic DNA sequences requires coordinate expansion of convergent cellular proofreading/error correction mechanisms that are encoded by reciprocally modified genomic DNA. Computational expansion of operationally defined DNA memory extends to coordinate modification of coding and previously under-emphasized noncoding regions that now appear to represent essential reservoirs of untapped genetic information amenable to evolutionary driven recruitment into the realm of biologically active domains. Additionally, expansion of DNA memory potential via chemical modification and activation of noncoding sequences is targeted to vertical augmentation and integration of an expanded cadre of transcriptional and epigenetic regulatory factors affecting linear coding of protein amino acid sequences within open reading frames. The burgeoning Artificial Intelligence (AI) discipline of biomolecular and DNA computing incorporates core operational machinery that includes input and output devices, memory, and biomolecular logic gates in order to utilize the potentially inexhaustible information technology (IT) capacity of genomic DNA [1]. Contextually, the dual application of DNA/RNA/protein complexed microcircuits to model AI deep learning and recurrent neural network paradigms carries the potential to significantly expand IT based strategies to effectively address a broad array of

  14. EU copyright protection of works created by artificial intelligence systems

    OpenAIRE

    Bøhler, Helene Margrethe

    2017-01-01

    This thesis is concerned with copyright regulation of works created by artificial intelligence systems. The rapid advances in artificial intelligence are calling into question some of the fundamental assumptions upon which intellectual property law rests. Currently, the European framework of copyright law does not take non-human innovation into account. Meanwhile, advances in artificial intelligence are quickly making machine-generation of creative works a reality. Institutions of the Europea...

  15. Design Issues in Parallel Architectures for Artificial Intelligence.

    Science.gov (United States)

    1983-11-01

    Empirical computations require dynamic allocation because it is impossible to plan in advance which procedures will need to be run. Artificial intelligence applications require...consider particular limitations of previously proposed architectures in the context of large-scale parallel artificial intelligence applications . Most of...the limitations stem from the fact that previous architectures were not designed for highly parallel artificial intelligence applications in open

  16. A Methodology for Screening Potential Artificial Intelligence Applications

    Science.gov (United States)

    1988-07-01

    trryv’ rr P ’r ( l Ft COPY ..10 nr MEcp AFWAL-TR-.8-1083 I I A METHODOLOGY FOR SCREENING POTENTIAL ARTIFICIAL ~ INTELLIGENCE APPLICATIONS S Lt Eric N...Hanson Artificial Intelligence Applications Office JULY 1088 PROCEEDINGS APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED (, ELECTC-, NOV 2...BEEN REVIEWED AND IS APPROVED FOR PUBLICATION. ERIC N. HANSO’, lT, USAF WILLIAM R. BAKER Technical Director Chief, Artificial Intelligence Applications Office

  17. On the Suitability of ADA for Artificial Intelligence Applications

    Science.gov (United States)

    1980-07-01

    ON THE SUITABILITY OF ADA FOR ARTIFICIAL INTELLIGENCE APPLICATIONS July 1980 0By: Richard L. Schwartz P. M. Melliar-Smith Project Scientists Computer... ARTIFICIAL INTELLIGENCE APPLICATIONS July 1980 By: Richard L. Schwartz, Computer Scientist P. M. Melliar-Smith, Senior Computer Scientist Computer Science...Research The following papers have been prepared during this project: 0"The Suitability of Ada for Artificial Intelligence Applications ". Final

  18. The impact of artificial intelligence on the world economy

    OpenAIRE

    Kuprevich, T. S.

    2017-01-01

    In the article the potential benefits and opportunities offered by AI in the world economy are considered. In the course of the research benefits and tendencies of artificial intelligence in the world economy were revealed, the main directions of development and barriers of artificial intelligence adoption are analyzed and revealed. Nowadays artificial intelligence (AI) is going mainstream, driven by machine learning, big data and cloud computing.

  19. A development framework for distributed artificial intelligence

    Science.gov (United States)

    Adler, Richard M.; Cottman, Bruce H.

    1989-01-01

    The authors describe distributed artificial intelligence (DAI) applications in which multiple organizations of agents solve multiple domain problems. They then describe work in progress on a DAI system development environment, called SOCIAL, which consists of three primary language-based components. The Knowledge Object Language defines models of knowledge representation and reasoning. The metaCourier language supplies the underlying functionality for interprocess communication and control access across heterogeneous computing environments. The metaAgents language defines models for agent organization coordination, control, and resource management. Application agents and agent organizations will be constructed by combining metaAgents and metaCourier building blocks with task-specific functionality such as diagnostic or planning reasoning. This architecture hides implementation details of communications, control, and integration in distributed processing environments, enabling application developers to concentrate on the design and functionality of the intelligent agents and agent networks themselves.

  20. Worldwide Intelligent Systems: Approaches to Telecommunications and Network Management. Frontiers in Artificial Intelligence and Applications, Volume 24.

    Science.gov (United States)

    Liebowitz, Jay, Ed.; Prerau, David S., Ed.

    This is an international collection of 12 papers addressing artificial intelligence (AI) and knowledge technology applications in telecommunications and network management. It covers the latest and emerging AI technologies as applied to the telecommunications field. The papers are: "The Potential for Knowledge Technology in…

  1. Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy.

    Science.gov (United States)

    Hueso, Miguel; Vellido, Alfredo; Montero, Nuria; Barbieri, Carlo; Ramos, Rosa; Angoso, Manuel; Cruzado, Josep Maria; Jonsson, Anders

    2018-02-01

    Current dialysis devices are not able to react when unexpected changes occur during dialysis treatment or to learn about experience for therapy personalization. Furthermore, great efforts are dedicated to develop miniaturized artificial kidneys to achieve a continuous and personalized dialysis therapy, in order to improve the patient's quality of life. These innovative dialysis devices will require a real-time monitoring of equipment alarms, dialysis parameters, and patient-related data to ensure patient safety and to allow instantaneous changes of the dialysis prescription for the assessment of their adequacy. The analysis and evaluation of the resulting large-scale data sets enters the realm of "big data" and will require real-time predictive models. These may come from the fields of machine learning and computational intelligence, both included in artificial intelligence, a branch of engineering involved with the creation of devices that simulate intelligent behavior. The incorporation of artificial intelligence should provide a fully new approach to data analysis, enabling future advances in personalized dialysis therapies. With the purpose to learn about the present and potential future impact on medicine from experts in artificial intelligence and machine learning, a scientific meeting was organized in the Hospital Universitari Bellvitge (L'Hospitalet, Barcelona). As an outcome of that meeting, the aim of this review is to investigate artificial intel ligence experiences on dialysis, with a focus on potential barriers, challenges, and prospects for future applications of these technologies. Artificial intelligence research on dialysis is still in an early stage, and the main challenge relies on interpretability and/or comprehensibility of data models when applied to decision making. Artificial neural networks and medical decision support systems have been used to make predictions about anemia, total body water, or intradialysis hypotension and are promising

  2. AIonAI: a humanitarian law of artificial intelligence and robotics.

    Science.gov (United States)

    Ashrafian, Hutan

    2015-02-01

    The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across these categories, the robotics laws first proposed by Isaac Asimov in the twentieth century remain well-recognised and esteemed due to their specification of preventing human harm, stipulating obedience to humans and incorporating robotic self-protection. However the overwhelming predominance in the study of this field has focussed on human-robot interactions without fully considering the ethical inevitability of future artificial intelligences communicating together and has not addressed the moral nature of robot-robot interactions. A new robotic law is proposed and termed AIonAI or artificial intelligence-on-artificial intelligence. This law tackles the overlooked area where future artificial intelligences will likely interact amongst themselves, potentially leading to exploitation. As such, they would benefit from adopting a universal law of rights to recognise inherent dignity and the inalienable rights of artificial intelligences. Such a consideration can help prevent exploitation and abuse of rational and sentient beings, but would also importantly reflect on our moral code of ethics and the humanity of our civilisation.

  3. Probabilistic machine learning and artificial intelligence

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-01

    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

  4. Optimizing radiologic workup: An artificial intelligence approach

    International Nuclear Information System (INIS)

    Swett, H.A.; Rothschild, M.; Weltin, G.G.; Fisher, P.R.; Miller, P.L.

    1987-01-01

    The increasing complexity of diagnostic imaging is presenting an ever-expanding variety of radiologic test options to referring clinicians, making it more difficult for them to plan efficient workup. Diagnosis-oriented reimbursement systems are providing new incentives for hospitals and radiologists to use imaging modalities judiciously. This paper describes DxCON, a developmental artificial intelligence-based computer system, which gives advice to physicians about the optimum sequencing of radiologic tests. DxCON analyzes a physician's proposed workup plan and discusses its strengths and weaknesses. The domain chosen for this research is the imaging workup of obstructive jaundice

  5. Human-Level Artificial Intelligence? Be Serious!

    OpenAIRE

    Nilsson, Nils J.

    2005-01-01

    I claim that achieving real human-level artificial intelligence would necessarily imply that most of the tasks that humans perform for pay could be automated. Rather than work toward this goal of automation by building special-purpose systems, I argue for the development of general-purpose, educable systems that can learn and be taught to perform any of the thousands of jobs that humans can perform. Joining others who have made similar proposals, I advocate beginning with a system that has mi...

  6. The Third Age of Artificial Intelligence

    OpenAIRE

    Miailhe, Nicolas; Hodes, Cyrus

    2018-01-01

    If the definitional boundaries of Artificial Intelligence (AI) remains contested, experts agree that we are witnessing a revolution. “Is this time different?” is the question that they worryingly argue over when they analyze the socio-economic impact of the AI revolution as compared with the other industrial revolutions of the 19th and 20th centuries. This Schumpeterian wave may prove to be a creative destruction raising incomes, enhancing quality of life for all and generating previously uni...

  7. Quantum neuromorphic hardware for quantum artificial intelligence

    Science.gov (United States)

    Prati, Enrico

    2017-08-01

    The development of machine learning methods based on deep learning boosted the field of artificial intelligence towards unprecedented achievements and application in several fields. Such prominent results were made in parallel with the first successful demonstrations of fault tolerant hardware for quantum information processing. To which extent deep learning can take advantage of the existence of a hardware based on qubits behaving as a universal quantum computer is an open question under investigation. Here I review the convergence between the two fields towards implementation of advanced quantum algorithms, including quantum deep learning.

  8. Markov decision processes in artificial intelligence

    CERN Document Server

    Sigaud, Olivier

    2013-01-01

    Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as Reinforcement Learning problems. Written by experts in the field, this book provides a global view of current research using MDPs in Artificial Intelligence. It starts with an introductory presentation of the fundamental aspects of MDPs (planning in MDPs, Reinforcement Learning, Partially Observable MDPs, Markov games and the use of non-classical criteria). Then it presents more advanced research trends in the domain and gives some concrete examples using illustr

  9. Artificial intelligence and the business manager

    Energy Technology Data Exchange (ETDEWEB)

    Hertz, D.R.

    1983-10-24

    The Fortune 1000 executive may have too much data too soon. His problem lies in turning it into usable information. Artificial intelligence (AI) may promise one resolution of the executive's dilemma. Knowledge resides in the facts; mining that knowledge for more effective competition, smoother operations and better planning is a major goal of ai knowledge scientists and engineers. They believe the right kind of computer programs will turn the tide of data from an uncontrollable flood to an orderly, productive stream.

  10. Probabilistic machine learning and artificial intelligence.

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-28

    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

  11. Artificial intelligence applied to process signal analysis

    Science.gov (United States)

    Corsberg, Dan

    1988-01-01

    Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.

  12. A Characterization of the Utility of Using Artificial Intelligence to Test Two Artificial Intelligence Systems

    Directory of Open Access Journals (Sweden)

    Jeremy Straub

    2013-05-01

    Full Text Available An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (perhaps ensuring that a set of foreseeable conditions trigger an appropriate response, this may be insufficient to fully characterize and validate safe system performance. An approach to validating the performance of an artificial intelligence system using a simple artificial intelligence test case producer (AITCP is presented. The AITCP allows the creation and simulation of prospective operating scenarios at a rate far exceeding that possible by human testers. Four scenarios for testing an autonomous navigation control system are presented: single actor in two-dimensional space, multiple actors in two-dimensional space, single actor in three-dimensional space, and multiple actors in three-dimensional space. The utility of using the AITCP is compared to that of human testers in each of these scenarios.

  13. Artificial intelligence model for sustain ability measurement

    International Nuclear Information System (INIS)

    Navickiene, R.; Navickas, K.

    2012-01-01

    The article analyses the main dimensions of organizational sustain ability, their possible integrations into artificial neural network. In this article authors performing analyses of organizational internal and external environments, their possible correlations with 4 components of sustain ability, and the principal determination models for sustain ability of organizations. Based on the general principles of sustainable development organizations, a artificial intelligence model for the determination of organizational sustain ability has been developed. The use of self-organizing neural networks allows the identification of the organizational sustain ability and the endeavour to explore vital, social, antropogenical and economical efficiency. The determination of the forest enterprise sustain ability is expected to help better manage the sustain ability. (Authors)

  14. Accelerating artificial intelligence with reconfigurable computing

    Science.gov (United States)

    Cieszewski, Radoslaw

    Reconfigurable computing is emerging as an important area of research in computer architectures and software systems. Many algorithms can be greatly accelerated by placing the computationally intense portions of an algorithm into reconfigurable hardware. Reconfigurable computing combines many benefits of both software and ASIC implementations. Like software, the mapped circuit is flexible, and can be changed over the lifetime of the system. Similar to an ASIC, reconfigurable systems provide a method to map circuits into hardware. Reconfigurable systems therefore have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. Such a field, where there is many different algorithms which can be accelerated, is an artificial intelligence. This paper presents example hardware implementations of Artificial Neural Networks, Genetic Algorithms and Expert Systems.

  15. Artificial intelligence and expert systems in-flight software testing

    Science.gov (United States)

    Demasie, M. P.; Muratore, J. F.

    1991-01-01

    The authors discuss the introduction of advanced information systems technologies such as artificial intelligence, expert systems, and advanced human-computer interfaces directly into Space Shuttle software engineering. The reconfiguration automation project (RAP) was initiated to coordinate this move towards 1990s software technology. The idea behind RAP is to automate several phases of the flight software testing procedure and to introduce AI and ES into space shuttle flight software testing. In the first phase of RAP, conventional tools to automate regression testing have already been developed or acquired. There are currently three tools in use.

  16. TECHNOLOGIES OF ARTIFICIAL INTELLIGENCE AS THE FACTOR OF DIGITALIZATION OF ECONOMY IN RUSSIA AND IN THE WORLD

    OpenAIRE

    L. A. Tsvetkova

    2017-01-01

    The growth rates of the market for high-tech goods and services based on deep learning technologies are estimated. Key investors and beneficiaries in the development of deep learning technologies were identified. The patent activity in the world is analyzed and the place of Russia in the patent landscape in the field of deep learning is determined. It is shown that most of the patent documents are concentrated in the portfolios of major US corporations, which are headed by Microsoft, IBM, Goo...

  17. Birth of Industry 5.0: Making Sense of Big Data with Artificial Intelligence, "The Internet of Things" and Next-Generation Technology Policy.

    Science.gov (United States)

    Özdemir, Vural; Hekim, Nezih

    2018-01-01

    Driverless cars with artificial intelligence (AI) and automated supermarkets run by collaborative robots (cobots) working without human supervision have sparked off new debates: what will be the impacts of extreme automation, turbocharged by the Internet of Things (IoT), AI, and the Industry 4.0, on Big Data and omics implementation science? The IoT builds on (1) broadband wireless internet connectivity, (2) miniaturized sensors embedded in animate and inanimate objects ranging from the house cat to the milk carton in your smart fridge, and (3) AI and cobots making sense of Big Data collected by sensors. Industry 4.0 is a high-tech strategy for manufacturing automation that employs the IoT, thus creating the Smart Factory. Extreme automation until "everything is connected to everything else" poses, however, vulnerabilities that have been little considered to date. First, highly integrated systems are vulnerable to systemic risks such as total network collapse in the event of failure of one of its parts, for example, by hacking or Internet viruses that can fully invade integrated systems. Second, extreme connectivity creates new social and political power structures. If left unchecked, they might lead to authoritarian governance by one person in total control of network power, directly or through her/his connected surrogates. We propose Industry 5.0 that can democratize knowledge coproduction from Big Data, building on the new concept of symmetrical innovation. Industry 5.0 utilizes IoT, but differs from predecessor automation systems by having three-dimensional (3D) symmetry in innovation ecosystem design: (1) a built-in safe exit strategy in case of demise of hyperconnected entrenched digital knowledge networks. Importantly, such safe exists are orthogonal-in that they allow "digital detox" by employing pathways unrelated/unaffected by automated networks, for example, electronic patient records versus material/article trails on vital medical information; (2) equal

  18. Artificial intelligence analysis of paraspinal power spectra.

    Science.gov (United States)

    Oliver, C W; Atsma, W J

    1996-10-01

    OBJECTIVE: As an aid to discrimination of sufferers with back pain an artificial intelligence neural network was constructed to differentiate paraspinal power spectra. DESIGN: Clinical investigation using surface electromyography. METHOD: The surface electromyogram power spectra from 60 subjects, 33 non-back-pain sufferers and 27 chronic back pain sufferers were used to construct a back propagation neural network that was then tested. Subjects were placed on a test frame in 30 degrees of lumbar forward flexion. An isometric load of two-thirds maximum voluntary contraction was held constant for 30 s whilst surface electromyograms were recorded at the level of the L(4-5). Paraspinal power spectra were calculated and loaded into the input layer of a three-layer back propagation network. The neural network classified the spectra into normal or back pain type. RESULTS: The back propagation neural was shown to have satisfactory convergence with a specificity of 79% and a sensitivity of 80%. CONCLUSIONS: Artificial intelligence neural networks appear to be a useful method of differentiating paraspinal power spectra in back-pain sufferers.

  19. Marine litter prediction by artificial intelligence

    International Nuclear Information System (INIS)

    Balas, Can Elmar; Ergin, Aysen; Williams, Allan T.; Koc, Levent

    2004-01-01

    Artificial intelligence techniques of neural network and fuzzy systems were applied as alternative methods to determine beach litter grading, based on litter surveys of the Antalya coastline (the Turkish Riviera). Litter measurements were categorized and assessed by artificial intelligence techniques, which lead to a new litter categorization system. The constructed neural network satisfactorily predicted the grading of the Antalya beaches and litter categories based on the number of litter items in the general litter category. It has been concluded that, neural networks could be used for high-speed predictions of litter items and beach grading, when the characteristics of the main litter category was determined by field studies. This can save on field effort when fast and reliable estimations of litter categories are required for management or research studies of beaches--especially those concerned with health and safety, and it has economic implications. The main advantages in using fuzzy systems are that they consider linguistic adjectival definitions, e.g. many/few, etc. As a result, additional information inherent in linguistic comments/refinements and judgments made during field studies can be incorporated in grading systems

  20. Predicting asthma exacerbations using artificial intelligence.

    Science.gov (United States)

    Finkelstein, Joseph; Wood, Jeffrey

    2013-01-01

    Modern telemonitoring systems identify a serious patient deterioration when it already occurred. It would be much more beneficial if the upcoming clinical deterioration were identified ahead of time even before a patient actually experiences it. The goal of this study was to assess artificial intelligence approaches which potentially can be used in telemonitoring systems for advance prediction of changes in disease severity before they actually occur. The study dataset was based on daily self-reports submitted by 26 adult asthma patients during home telemonitoring consisting of 7001 records. Two classification algorithms were employed for building predictive models: naïve Bayesian classifier and support vector machines. Using a 7-day window, a support vector machine was able to predict asthma exacerbation to occur on the day 8 with the accuracy of 0.80, sensitivity of 0.84 and specificity of 0.80. Our study showed that methods of artificial intelligence have significant potential in developing individualized decision support for chronic disease telemonitoring systems.

  1. Artificial intelligence. Fears of an AI pioneer.

    Science.gov (United States)

    Russell, Stuart; Bohannon, John

    2015-07-17

    From the enraged robots in the 1920 play R.U.R. to the homicidal computer H.A.L. in 2001: A Space Odyssey, science fiction writers have embraced the dark side of artificial intelligence (AI) ever since the concept entered our collective imagination. Sluggish progress in AI research, especially during the “AI winter” of the 1970s and 1980s, made such worries seem far-fetched. But recent breakthroughs in machine learning and vast improvements in computational power have brought a flood of research funding— and fresh concerns about where AI may lead us. One researcher now speaking up is Stuart Russell, a computer scientist at the University of California, Berkeley, who with Peter Norvig, director of research at Google, wrote the premier AI textbook, Artificial Intelligence: A Modern Approach, now in its third edition. Last year, Russell joined the Centre for the Study of Existential Risk at Cambridge University in the United Kingdom as an AI expert focusing on “risks that could lead to human extinction.” Among his chief concerns, which he aired at an April meeting in Geneva, Switzerland, run by the United Nations, is the danger of putting military drones and weaponry under the full control of AI systems. This interview has been edited for clarity and brevity.

  2. Research in artificial intelligence for nuclear facilities

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1990-01-01

    The application of artificial intelligence, in the form of expert systems and neural networks, to the control room activities in a nuclear power plant has the potential to reduce operator error and increase plant safety, reliability, and efficiency. Furthermore, artificial intelligence can increase efficiency and effectiveness in a large number of nonoperating activities (testing, routine maintenance, outage planning, equipment diagnostics, and fuel management) and in research facility experiments. Recent work at the University of Tennessee has demonstrated the feasibility of using neural networks to identify six different transients introduced into the simulation of a steam generator of a nuclear power plant. This work is now being extended to utilize data from a nuclear power plant training simulator. In one configuration, the inputs to the neural network are a subset of the quantities that are typical of those available from the safety parameter display system. The outputs of the network represent the various states of the plant (e.g., normal operation, coolant leakage, inadequate core flow, excessive peak fuel temperature, etc.). Training of the neural network is performed by introducing various faults or conditions to be diagnosed into the simulator. The goal of this work is to demonstrate a neural network diagnostic system that could provide advice to the operators in accordance with the emergency operating procedures

  3. Marine litter prediction by artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Balas, Can Elmar; Ergin, Aysen; Williams, Allan T.; Koc, Levent

    2004-03-01

    Artificial intelligence techniques of neural network and fuzzy systems were applied as alternative methods to determine beach litter grading, based on litter surveys of the Antalya coastline (the Turkish Riviera). Litter measurements were categorized and assessed by artificial intelligence techniques, which lead to a new litter categorization system. The constructed neural network satisfactorily predicted the grading of the Antalya beaches and litter categories based on the number of litter items in the general litter category. It has been concluded that, neural networks could be used for high-speed predictions of litter items and beach grading, when the characteristics of the main litter category was determined by field studies. This can save on field effort when fast and reliable estimations of litter categories are required for management or research studies of beaches--especially those concerned with health and safety, and it has economic implications. The main advantages in using fuzzy systems are that they consider linguistic adjectival definitions, e.g. many/few, etc. As a result, additional information inherent in linguistic comments/refinements and judgments made during field studies can be incorporated in grading systems.

  4. Artificial Intelligence Research Branch future plans

    Science.gov (United States)

    Stewart, Helen (Editor)

    1992-01-01

    This report contains information on the activities of the Artificial Intelligence Research Branch (FIA) at NASA Ames Research Center (ARC) in 1992, as well as planned work in 1993. These activities span a range from basic scientific research through engineering development to fielded NASA applications, particularly those applications that are enabled by basic research carried out in FIA. Work is conducted in-house and through collaborative partners in academia and industry. All of our work has research themes with a dual commitment to technical excellence and applicability to NASA short, medium, and long-term problems. FIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at the Jet Propulsion Laboratory (JPL) and AI applications groups throughout all NASA centers. This report is organized along three major research themes: (1) Planning and Scheduling: deciding on a sequence of actions to achieve a set of complex goals and determining when to execute those actions and how to allocate resources to carry them out; (2) Machine Learning: techniques for forming theories about natural and man-made phenomena; and for improving the problem-solving performance of computational systems over time; and (3) Research on the acquisition, representation, and utilization of knowledge in support of diagnosis design of engineered systems and analysis of actual systems.

  5. Artificial intelligence applications in offshore oil and gas production

    Energy Technology Data Exchange (ETDEWEB)

    Attia, F.G. [Univ. of Houston, TX (United States). Dept. of Mechanical Technology; Tawfik, A.S. [Brown and Root, Inc., Houston, TX (United States)

    1994-12-31

    The field of Artificial Intelligence (AI) has gained considerable acceptance in virtually all fields, of engineering applications. Artificial intelligence is now being applied in several areas of offshore oil and gas operations, such as drilling, well testing, well logging and interpretation, reservoir engineering, planning and economic evaluation, process control, and risk analysis. Current AI techniques offer a new and exciting technology for solving problems in the oil and gas industry. Expert systems, fuzzy logic systems, neural networks and genetic algorithms are major AI technologies which have made an impact on the petroleum industry. Presently, these technologies are at different stages of maturity with expert systems being the most mature and genetic algorithms the least. However, all four technologies have evolved such that practical applications were produced. This paper describes the four major Al techniques and their many applications in offshore oil and gas production operations. A summary description of future developments in Al technology that will affect the execution and productivity of offshore operations will be also provided.

  6. Artificial intelligence applications in offshore oil and gas production

    International Nuclear Information System (INIS)

    Attia, F.G.

    1994-01-01

    The field of Artificial Intelligence (AI) has gained considerable acceptance in virtually all fields, of engineering applications. Artificial intelligence is now being applied in several areas of offshore oil and gas operations, such as drilling, well testing, well logging and interpretation, reservoir engineering, planning and economic evaluation, process control, and risk analysis. Current AI techniques offer a new and exciting technology for solving problems in the oil and gas industry. Expert systems, fuzzy logic systems, neural networks and genetic algorithms are major AI technologies which have made an impact on the petroleum industry. Presently, these technologies are at different stages of maturity with expert systems being the most mature and genetic algorithms the least. However, all four technologies have evolved such that practical applications were produced. This paper describes the four major Al techniques and their many applications in offshore oil and gas production operations. A summary description of future developments in Al technology that will affect the execution and productivity of offshore operations will be also provided

  7. Applications of artificial intelligence, including expert systems

    International Nuclear Information System (INIS)

    Abbott, M.B.

    1989-01-01

    When Artificial Intelligence is applied to a complex physical system like a nuclear plant it is useful to distinguish between two rather distinct and different intelligent views of such a plant. The first view may be characterised as ''the designer's view''. This is the view of the plant as it was originally conceived and designed; it is essentially a once-and-for-all static view, corresponding to the implicit assumption of an ''ageless plant'', or at most a plant which ages in a preconceived, preset manner. The second view, which may be characterised as ''the operators view'', has to do more with a real-world, ageing plant. It is a more dynamic view, which sees the ageing process as one in which unforeseen, and possibly unforeseeable events may occur at equally unforeseen, and possibly unforeseeable times. The first view is predominantly a way of thinking about the plant, while the second is very often more a way of feeling about it. It should be emphasized that both ways are ways of intelligence. (author)

  8. Expertise, Task Complexity, and Artificial Intelligence: A Conceptual Framework.

    Science.gov (United States)

    Buckland, Michael K.; Florian, Doris

    1991-01-01

    Examines the relationship between users' expertise, task complexity of information system use, and artificial intelligence to provide the basis for a conceptual framework for considering the role that artificial intelligence might play in information systems. Cognitive and conceptual models are discussed, and cost effectiveness is considered. (27…

  9. The coming of age of artificial intelligence in medicine

    NARCIS (Netherlands)

    Patel, Vimla L.; Shortliffe, Edward H.; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R.; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2009-01-01

    This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in

  10. The 1993 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Hostetter, Carl F. (Editor)

    1993-01-01

    This publication comprises the papers presented at the 1993 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, MD on May 10-13, 1993. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  11. The 1994 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Hostetter, Carl F. (Editor)

    1994-01-01

    This publication comprises the papers presented at the 1994 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/GSFC, Greenbelt, Maryland, on 10-12 May 1994. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  12. The Potential of Artificial Intelligence in Aids for the Disabled.

    Science.gov (United States)

    Boyer, John J.

    The paper explores the possibilities for applying the knowledge of artificial intelligence (AI) research to aids for the disabled. Following a definition of artificial intelligence, the paper reviews areas of basic AI research, such as computer vision, machine learning, and planning and problem solving. Among application areas relevant to the…

  13. Ethico-epistemological implications of artificial intelligence for ...

    African Journals Online (AJOL)

    We argued for a re-direction of AI. research and suggested a humanization of Artificial Intelligence that cloaks technoscientific innovations with humanistic life jackets for man‟s preservation. The textual analysis method is adopted for this research. Key words: Ethics, Epistemology, Artificial Intelligence, Humanity.

  14. Concerns Over the Expansion of Artificial Intelligence in the Legal Field

    OpenAIRE

    Einhouse, Ben

    2018-01-01

    Cornell Law School J.D. Student Research Papers. 38 Advances in technology have surely made the practice of law more efficient, but looming advances in artificial intelligence should raise some concern about the price of this efficiency. Artificial intelligence programs already exhibit the capacity to replace the daily activities of some lawyers, which should raise some concern in the legal community, especially regarding legal ethics. Despite these concerns, the access to knowledge that arti...

  15. Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET)

    Science.gov (United States)

    Shahidi, Anoosh K.; Schlegelmilch, Richard F.; Petrik, Edward J.; Walters, Jerry L.

    1992-01-01

    A software application to assist end-users of the high burst rate (HBR) link evaluation terminal (LET) for satellite communications is being developed. The HBR LET system developed at NASA Lewis Research Center is an element of the Advanced Communications Technology Satellite (ACTS) Project. The HBR LET is divided into seven major subsystems, each with its own expert. Programming scripts, test procedures defined by design engineers, set up the HBR LET system. These programming scripts are cryptic, hard to maintain and require a steep learning curve. These scripts were developed by the system engineers who will not be available for the end-users of the system. To increase end-user productivity a friendly interface needs to be added to the system. One possible solution is to provide the user with adequate documentation to perform the needed tasks. With the complexity of this system the vast amount of documentation needed would be overwhelming and the information would be hard to retrieve. With limited resources, maintenance is another reason for not using this form of documentation. An advanced form of interaction is being explored using current computer techniques. This application, which incorporates a combination of multimedia and artificial intelligence (AI) techniques to provided end-users with an intelligent interface to the HBR LET system, is comprised of an intelligent assistant, intelligent tutoring, and hypermedia documentation. The intelligent assistant and tutoring systems address the critical programming needs of the end-user.

  16. The impact of artificial intelligence on airborne maritime reconnaissance

    Science.gov (United States)

    Shepard, J.; Scott-Wilson, R. J.

    1985-08-01

    Some of the problems arising out of the introduction of VHPIC to the sensor and data processing systems of Maritime Reconnaissance aircraft are susceptible to solution by conventional computing techniques within mission time constraints. Some may be more susceptible to the use of artificial intelligence techniques. This paper identifies those aspects of artificial intelligence relevant to the Airborne Maritime Reconnaissance task and the areas of the current task where artificial intelligence can be usefully applied. It reviews the current state of the art in the relevant aspects of artificial intelligence and indicates how they might be employed in the near, medium and long term. It indicates some future applications and concludes that, artificial intelligence will play an important role in the future Maritime Reconnaissance aircraft.

  17. What can the brain teach us about building artificial intelligence?

    Science.gov (United States)

    George, Dileep

    2017-01-01

    Lake et al. offer a timely critique on the recent accomplishments in artificial intelligence from the vantage point of human intelligence and provide insightful suggestions about research directions for building more human-like intelligence. Because we agree with most of the points they raised, here we offer a few points that are complementary.

  18. A critique of artificial intelligence | Airoboman | Sophia: An African ...

    African Journals Online (AJOL)

    The question concerning machines‟ intelligence or mindedness has become topical issue in some disciplines. The focus in this research is on philosophic inquiry into the claim widely current in our time that machines are intelligent. The study introduces the debate and presents some definitions of artificial intelligence as a ...

  19. The 1990 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Rash, James L. (Editor)

    1990-01-01

    The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

  20. Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

    Science.gov (United States)

    Cipresso, Pietro; Riva, Giuseppe

    2015-01-01

    There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society.

  1. Artificial intelligence techniques for embryo and oocyte classification.

    Science.gov (United States)

    Manna, Claudio; Nanni, Loris; Lumini, Alessandra; Pappalardo, Sebastiana

    2013-01-01

    One of the most relevant aspects in assisted reproduction technology is the possibility of characterizing and identifying the most viable oocytes or embryos. In most cases, embryologists select them by visual examination and their evaluation is totally subjective. Recently, due to the rapid growth in the capacity to extract texture descriptors from a given image, a growing interest has been shown in the use of artificial intelligence methods for embryo or oocyte scoring/selection in IVF programmes. This work concentrates the efforts on the possible prediction of the quality of embryos and oocytes in order to improve the performance of assisted reproduction technology, starting from their images. The artificial intelligence system proposed in this work is based on a set of Levenberg-Marquardt neural networks trained using textural descriptors (the local binary patterns). The proposed system was tested on two data sets of 269 oocytes and 269 corresponding embryos from 104 women and compared with other machine learning methods already proposed in the past for similar classification problems. Although the results are only preliminary, they show an interesting classification performance. This technique may be of particular interest in those countries where legislation restricts embryo selection. One of the most relevant aspects in assisted reproduction technology is the possibility of characterizing and identifying the most viable oocytes or embryos. In most cases, embryologists select them by visual examination and their evaluation is totally subjective. Recently, due to the rapid growth in our capacity to extract texture descriptors from a given image, a growing interest has been shown in the use of artificial intelligence methods for embryo or oocyte scoring/selection in IVF programmes. In this work, we concentrate our efforts on the possible prediction of the quality of embryos and oocytes in order to improve the performance of assisted reproduction technology

  2. Westinghouse use of artificial intelligence in signal interpretation

    International Nuclear Information System (INIS)

    Mark, R.H.

    1984-01-01

    This paper discusses Westinghouse's use of artificial intelligence to assist inspectors who routinely monitor the thousands of tubes in nuclear steam generators. Using the AI technology has made the inspection process easier to learn and to apply. The system uses pattern recognition to identify off-normal conditions. As part of the in-service inspection program for nuclear power reactors, utilities make a practice of inspecting the condition of the large heat exchangers that produce the steam that turns the electric turbine generator. The same data are presented for inspection using form, motion, and color to call attention to off-normal signal patterns

  3. Multisensor system and artificial intelligence in housing for the elderly.

    Science.gov (United States)

    Chan, M; Bocquet, H; Campo, E; Val, T; Estève, D; Pous, J

    1998-01-01

    To improve the safety of a growing proportion of elderly and disabled people in the developed countries, a multisensor system based on Artificial Intelligence (AI), Advanced Telecommunications (AT) and Information Technology (IT) has been devised and fabricated. Thus, the habits and behaviours of these populations will be recorded without disturbing their daily activities. AI will diagnose any abnormal behavior or change and the system will warn the professionals. Gerontology issues are presented together with the multisensor system, the AI-based learning and diagnosis methodology and the main functionalities.

  4. Chemogenomics: a discipline at the crossroad of high throughput technologies, biomarker research, combinatorial chemistry, genomics, cheminformatics, bioinformatics and artificial intelligence.

    Science.gov (United States)

    Maréchal, Eric

    2008-09-01

    Chemogenomics is the study of the interaction of functional biological systems with exogenous small molecules, or in broader sense the study of the intersection of biological and chemical spaces. Chemogenomics requires expertises in biology, chemistry and computational sciences (bioinformatics, cheminformatics, large scale statistics and machine learning methods) but it is more than the simple apposition of each of these disciplines. Biological entities interacting with small molecules can be isolated proteins or more elaborate systems, from single cells to complete organisms. The biological space is therefore analyzed at various postgenomic levels (genomic, transcriptomic, proteomic or any phenotypic level). The space of small molecules is partially real, corresponding to commercial and academic collections of compounds, and partially virtual, corresponding to the chemical space possibly synthesizable. Synthetic chemistry has developed novel strategies allowing a physical exploration of this universe of possibilities. A major challenge of cheminformatics is to charter the virtual space of small molecules using realistic biological constraints (bioavailability, druggability, structural biological information). Chemogenomics is a descendent of conventional pharmaceutical approaches, since it involves the screening of chemolibraries for their effect on biological targets, and benefits from the advances in the corresponding enabling technologies and the introduction of new biological markers. Screening was originally motivated by the rigorous discovery of new drugs, neglecting and throwing away any molecule that would fail to meet the standards required for a therapeutic treatment. It is now the basis for the discovery of small molecules that might or might not be directly used as drugs, but which have an immense potential for basic research, as probes to explore an increasing number of biological phenomena. Concerns about the environmental impact of chemical industry

  5. Automated information-analytical system for thunderstorm monitoring and early warning alarms using modern physical sensors and information technologies with elements of artificial intelligence

    Science.gov (United States)

    Boldyreff, Anton S.; Bespalov, Dmitry A.; Adzhiev, Anatoly Kh.

    2017-05-01

    Methods of artificial intelligence are a good solution for weather phenomena forecasting. They allow to process a large amount of diverse data. Recirculation Neural Networks is implemented in the paper for the system of thunderstorm events prediction. Large amounts of experimental data from lightning sensors and electric field mills networks are received and analyzed. The average recognition accuracy of sensor signals is calculated. It is shown that Recirculation Neural Networks is a promising solution in the forecasting of thunderstorms and weather phenomena, characterized by the high efficiency of the recognition elements of the sensor signals, allows to compress images and highlight their characteristic features for subsequent recognition.

  6. Artificial intelligence in the materials processing laboratory

    Science.gov (United States)

    Workman, Gary L.; Kaukler, William F.

    1990-01-01

    Materials science and engineering provides a vast arena for applications of artificial intelligence. Advanced materials research is an area in which challenging requirements confront the researcher, from the drawing board through production and into service. Advanced techniques results in the development of new materials for specialized applications. Hand-in-hand with these new materials are also requirements for state-of-the-art inspection methods to determine the integrity or fitness for service of structures fabricated from these materials. Two problems of current interest to the Materials Processing Laboratory at UAH are an expert system to assist in eddy current inspection of graphite epoxy components for aerospace and an expert system to assist in the design of superalloys for high temperature applications. Each project requires a different approach to reach the defined goals. Results to date are described for the eddy current analysis, but only the original concepts and approaches considered are given for the expert system to design superalloys.

  7. Artificial Intelligence Software Engineering (AISE) model

    Science.gov (United States)

    Kiss, Peter A.

    1990-01-01

    The American Institute of Aeronautics and Astronautics has initiated a committee on standards for Artificial Intelligence. Presented are the initial efforts of one of the working groups of that committee. A candidate model is presented for the development life cycle of knowledge based systems (KBSs). The intent is for the model to be used by the aerospace community and eventually be evolved into a standard. The model is rooted in the evolutionary model, borrows from the spiral model, and is embedded in the standard Waterfall model for software development. Its intent is to satisfy the development of both stand-alone and embedded KBSs. The phases of the life cycle are shown and detailed as are the review points that constitute the key milestones throughout the development process. The applicability and strengths of the model are discussed along with areas needing further development and refinement by the aerospace community.

  8. Artificial Intelligence In Computational Fluid Dynamics

    Science.gov (United States)

    Vogel, Alison Andrews

    1991-01-01

    Paper compares four first-generation artificial-intelligence (Al) software systems for computational fluid dynamics. Includes: Expert Cooling Fan Design System (EXFAN), PAN AIR Knowledge System (PAKS), grid-adaptation program MITOSIS, and Expert Zonal Grid Generation (EZGrid). Focuses on knowledge-based ("expert") software systems. Analyzes intended tasks, kinds of knowledge possessed, magnitude of effort required to codify knowledge, how quickly constructed, performances, and return on investment. On basis of comparison, concludes Al most successful when applied to well-formulated problems solved by classifying or selecting preenumerated solutions. In contrast, application of Al to poorly understood or poorly formulated problems generally results in long development time and large investment of effort, with no guarantee of success.

  9. Issues and challenges in artificial intelligence

    CERN Document Server

    Kulikowski, Juliusz; Mroczek, Teresa; Wtorek, Jerzy

    2014-01-01

    The importance of human-computer system interaction problems is increasing due to the growing expectations of users on general computer systems capabilities in human work and life facilitation. Users expect system which is not only a passive tool in human hands but rather an active partner equipped with a sort of artificial intelligence, having access to large information resources, being able to adapt its behavior to the human requirements and to collaborate with the human users.   This book collects examples of recent human-computer system solutions. The content of the book is divided into three parts. Part I is devoted to detection, recognition and reasoning in different circumstances and applications. Problems associated with data modeling, acquisition and mining are presented by papers collected in part II and part III is devoted to Optimization.

  10. Minimum DNBR Prediction Using Artificial Intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Dong Su; Kim, Ju Hyun; Na, Man Gyun [Chosun University, Gwangju (Korea, Republic of)

    2011-05-15

    The minimum DNBR (MDNBR) for prevention of the boiling crisis and the fuel clad melting is very important factor that should be consistently monitored in safety aspects. Artificial intelligence methods have been extensively and successfully applied to nonlinear function approximation such as the problem in question for predicting DNBR values. In this paper, support vector regression (SVR) model and fuzzy neural network (FNN) model are developed to predict the MDNBR using a number of measured signals from the reactor coolant system. Also, two models are trained using a training data set and verified against test data set, which does not include training data. The proposed MDNBR estimation algorithms were verified by using nuclear and thermal data acquired from many numerical simulations of the Yonggwang Nuclear Power Plant Unit 3 (YGN-3)

  11. Artificial intelligence approach to interwell log correlation

    Energy Technology Data Exchange (ETDEWEB)

    Lim, Jong-Se [Korea Maritime University, Pusan(Korea); Kang, Joo Myung [Seoul National University, Seoul(Korea); Kim, Jung Whan [Korea National Oil Corp., Anyang(Korea)

    2000-04-30

    This paper describes a new approach to automated interwell log correlation using artificial intelligence and principal component analysis. The approach to correlate wire line logging data is on the basis of a large set of subjective rules that are intended to represent human logical processes. The data processed are mainly the qualitative information such as the characteristics of the shapes extracted along log traces. The apparent geologic zones are identified by pattern recognition for the specific characteristics of log trace collected as a set of objects by object oriented programming. The correlation of zones between wells is made by rule-based inference program. The reliable correlation can be established from the first principal component logs derived from both the important information around well bore and the largest common part of variances of all available well log data. Correlation with field log data shows that this approach can make interwell log correlation more reliable and accurate. (author). 6 refs., 7 figs.

  12. Discrete PID Tuning Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Petr DOLEŽEL

    2009-06-01

    Full Text Available PID controllers are widely used in industry these days due to their useful properties such as simple tuning or robustness. While they are applicable to many control problems, they can perform poorly in some applications. Highly nonlinear system control with constrained manipulated variable can be mentioned as an example. The point of the paper is to string together convenient qualities of conventional PID control and progressive techniques based on Artificial Intelligence. Proposed control method should deal with even highly nonlinear systems. To be more specific, there is described new method of discrete PID controller tuning in this paper. This method tunes discrete PID controller parameters online through the use of genetic algorithm and neural model of controlled system in order to control successfully even highly nonlinear systems. After method description and some discussion, there is performed control simulation and comparison to one chosen conventional control method.

  13. Amplify scientific discovery with artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Gil, Yolanda; Greaves, Mark T.; Hendler, James; Hirsch, Hyam

    2014-10-10

    Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automated language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.

  14. Clinical Note Creation, Binning, and Artificial Intelligence

    OpenAIRE

    Deliberato, Rodrigo Oct?vio; Celi, Leo Anthony; Stone, David J

    2017-01-01

    The creation of medical notes in software applications poses an intrinsic problem in workflow as the technology inherently intervenes in the processes of collecting and assembling information, as well as the production of a data-driven note that meets both individual and healthcare system requirements. In addition, the note writing applications in currently available electronic health records (EHRs) do not function to support decision making to any substantial degree. We suggest that artifici...

  15. 2nd International Symposium on Intelligent Systems Technologies and Applications

    CERN Document Server

    Mitra, Sushmita; Thampi, Sabu; El-Alfy, El-Sayed

    2016-01-01

    This book constitutes the thoroughly refereed proceedings of the second International Symposium on Intelligent Systems Technologies and Applications (ISTA’16), held on September 21–24, 2016 in Jaipur, India. The 80 revised papers presented were carefully reviewed and selected from 210 initial submissions and are organized in topical sections on image processing and artificial vision, computer networks and distributed systems, intelligent tools and techniques and applications using intelligent techniques.

  16. Artificial intelligence in molecular biology: a review and assessment.

    Science.gov (United States)

    Rawlings, C J; Fox, J P

    1994-06-29

    Over the past ten years, molecular biologists and computer scientists have experimented with various computational methods developed in artificial intelligence (AI). AI research has yielded a number of novel technologies, which are typified by an emphasis on symbolic (non-numerical) programming methods aimed at problems which are not amenable to classical algorithmic solutions. Prominent examples include knowledge-based and expert systems, qualitative simulation and artificial neural networks and other automated learning techniques. These methods have been applied to problems in data analysis, construction of advanced databases and modelling of biological systems. Practical results are now being obtained, notably in the recognition of active genes in genomic sequences, the assembly of physical and genetic maps and protein structure prediction. This paper outlines the principal methods, surveys the findings to date, and identifies the promising trends and current limitations.

  17. Using Artificial Intelligence Techniques to Implement a Multifactor Authentication System

    Directory of Open Access Journals (Sweden)

    Jackson Phiri

    2011-08-01

    Full Text Available The recent years have seen a rise in the number of cases of cyber-crime committed through identity theft and fraud. To address this problem, this paper uses adaptive neural-fuzzy inference system, fuzzy logic and artificial neural network to implement a multifactor authentication system through a technique of information fusion. To begin with, the identity attributes are mined using the three corpora from three major sources namely the social networks, a set of questionnaires and application forms from the various services offered both in the real and cyberspace. The statistical information generated by the corpora is then used to compose an identity attribute metric model. The composed identity attributes metrics values classified as biometrics, device metrics and pseudo metrics are then fused at the score level through a technique of information fusion in a multifactor authentication system by using each of the above artificial intelligence technologies and the results compared.

  18. Present situation and trend of precision guidance technology and its intelligence

    Science.gov (United States)

    Shang, Zhengguo; Liu, Tiandong

    2017-11-01

    This paper first introduces the basic concepts of precision guidance technology and artificial intelligence technology. Then gives a brief introduction of intelligent precision guidance technology, and with the help of development of intelligent weapon based on deep learning project in foreign: LRASM missile project, TRACE project, and BLADE project, this paper gives an overview of the current foreign precision guidance technology. Finally, the future development trend of intelligent precision guidance technology is summarized, mainly concentrated in the multi objectives, intelligent classification, weak target detection and recognition, intelligent between complex environment intelligent jamming and multi-source, multi missile cooperative fighting and other aspects.

  19. The Coming of Age of Artificial Intelligence in Medicine*

    OpenAIRE

    Patel, Vimla L.; Shortliffe, Edward H.; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R.; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2008-01-01

    This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its “adolescence” (Shortliffe EH. The adolescence of AI in medicine: Will the field come of age in the ‘90s? Artificial Intelligence in Medicine 1993; 5:93–106). In this article, the ...

  20. The Effects O Artificial Intelligence And Robotic Systems On Librarianship

    Directory of Open Access Journals (Sweden)

    Müslüm Yıldız

    2018-03-01

    Full Text Available With Industry 4.0, smart robots will be involved in all areas of our lives, and systems using technology control instead of work force will dominate. In this way, there will be a more qualified workforce with a high level of education, rather than workers with low-skilled jobs. According to recent studies, librarianship has been identified as one of the professions that could disappear in the near future due to this rapidly advancing technology. In this study, the possible effects of artificial intelligence and robotic systems on the profession of librarianship/information and document management were evaluated considering the findings of research conducted at Oxford University in 2017 and it was emphasized that in the near future, the only way to continue in this profession would be to keep the professional knowledge up to date as well as to follow the technological developments in areas such as computers, communication, and the internet.

  1. Artificial intelligence in nuclear reactor operation

    International Nuclear Information System (INIS)

    Da Ruan; Benitez-Read, J.S.

    2005-01-01

    Assessment of four real fuzzy control applications at the MIT research reactor in the US, the FUGEN heavy water reactor in Japan, the BR1 research reactor in Belgium, and a TRIGA Mark III reactor in Mexico will be examined through a SWOT analysis (strengths, weakness, opportunities, and threats). Special attention will be paid to the current cooperation between the Belgian Nuclear Research Centre (SCK·CEN) and the Mexican Nuclear Centre (ININ) on AI-based intelligent control for nuclear reactor operation under the partial support of the National Council for Science and Technology of Mexico (CONACYT). (authors)

  2. Toward Intelligent Assessment: An Integration of Constructed Response Testing, Artificial Intelligence, and Model-Based Measurement.

    Science.gov (United States)

    Bennett, Randy Elliot

    A new assessment conception is described that integrates constructed-response testing, artificial intelligence, and model-based measurement. The conception incorporates complex constructed-response items for their potential to increase the validity, instructional utility, and credibility of standardized tests. Artificial intelligence methods are…

  3. Artificial intelligence and bladder cancer arrays.

    Science.gov (United States)

    Wild, P J; Catto, J W F; Abbod, M F; Linkens, D A; Herr, A; Pilarsky, C; Wissmann, C; Stoehr, R; Denzinger, S; Knuechel, R; Hamdy, F C; Hartmann, A

    2007-01-01

    Non-muscle invasive bladder cancer is a heterogenous disease whose management is dependent upon the risk of progression to muscle invasion. Although the recurrence rate is high, the majority of tumors are indolent and can be managed by endoscopic means alone. The prognosis of muscle invasion is poor and radical treatment is required if cure is to be obtained. Progression risk in non-invasive tumors is hard to determine at tumor diagnosis using current clinicopathological means. To improve the accuracy of progression prediction various biomarkers have been evaluated. To discover novel biomarkers several authors have used gene expression microarrays. Various statistical methods have been described to interpret array data, but to date no biomarkers have entered clinical practice. Here, we describe a new method of microarray analysis using neurofuzzy modeling (NFM), a form of artificial intelligence, and integrate it with artificial neural networks (ANN) to investigate non-muscle invasive bladder cancer array data (n=66 tumors). We develop a predictive panel of 11 genes, from 2800 expressed genes, that can significantly identify tumor progression (average Logrank p = 0.0288) in the analyzed cancers. In comparison, this panel appears superior to those genes chosen using traditional analyses (average Logrank p = 0.3455) and tumor grade (Logrank, p = 0.2475) in this non-muscle invasive cohort. We then analyze panel members in a new non-muscle invasive bladder cancer cohort (n=199) using immunohistochemistry with six commercially available antibodies. The combination of 6 genes (LIG3, TNFRSF6, KRT18, ICAM1, DSG2 and BRCA2) significantly stratifies tumor progression (Logrank p = 0.0096) in the new cohort. We discuss the benefits of the transparent NFM approach with respect to other reported methods.

  4. Use of artificial intelligence in nuclear power plants

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1990-01-01

    The application of artificial intelligence, in the form of expert systems and neural networks, to the control room activities in a nuclear power plant has the potential to reduce operator error and increase plant safety, reliability, and efficiency. Furthermore, there are a large number of non-operating activities (testing, routine maintenance, outage planning, equipment diagnostics, and fuel management) in which artificial intelligence can increase the efficiency and effectiveness of overall plant and corporate operations. This paper reviews the state-of-the-art of artificial intelligence techniques, specifically, expert systems and neural networks, to nuclear power plants. This paper has reviewed the state-of-the-art of artificial intelligence, specifically expert systems and neural networks that are applied to problems in nuclear power plants

  5. Artificial intelligence in NMR imaging and image processing

    International Nuclear Information System (INIS)

    Kuhn, M.H.

    1988-01-01

    NMR tomography offers a wealth of information and data acquisition variants. Artificial intelligence is able to efficiently support the selection of measuring parameters and the evaluation of results. (orig.) [de

  6. Artificial intelligence - applications in high energy and nuclear physics

    Energy Technology Data Exchange (ETDEWEB)

    Mueller, U. E-mail: mueller@whep.uni-wuppertal.de

    2003-04-21

    In the parallel sessions at ACAT2002 different artificial intelligence applications in high energy and nuclear physics were presented. I will briefly summarize these presentations. Further details can be found in the relevant section of these proceedings.

  7. Artificial intelligence, quantum mechanics, neuroscience, and the philosophy of mind

    OpenAIRE

    Mainzer, Klaus

    1998-01-01

    Artificial intelligence, quantum mechanics, neuroscience, and the philosophy of mind. - In: Philosophy and the many faces of science / ed. by Dionysios Anapolitanos ... - Lanham u.a. : Rowman & Littlefield, 1998. - S. 235-251. - (CPS Publications in the philosophy of science)

  8. Researches in Artificial Intelligence in Republic of Moldova

    Directory of Open Access Journals (Sweden)

    Yu. Pechersky

    1994-11-01

    Full Text Available The article presents a review of researches in the field of Artificial Intelligence in Republic of Moldova concerning pattern recognition and also theory and applications of intellectual knowledge based systems.

  9. Third Conference on Artificial Intelligence for Space Applications, part 1

    Science.gov (United States)

    Denton, Judith S. (Compiler); Freeman, Michael S. (Compiler); Vereen, Mary (Compiler)

    1987-01-01

    The application of artificial intelligence to spacecraft and aerospace systems is discussed. Expert systems, robotics, space station automation, fault diagnostics, parallel processing, knowledge representation, scheduling, man-machine interfaces and neural nets are among the topics discussed.

  10. Software Reviews. PC Software for Artificial Intelligence Applications.

    Science.gov (United States)

    Epp, Helmut; And Others

    1988-01-01

    Contrasts artificial intelligence and conventional programming languages. Reviews Personal Consultant Plus, Smalltalk/V, and Nexpert Object, which are PC-based products inspired by problem-solving paradigms. Provides information on background and operation of each. (RT)

  11. Utilising artificial intelligence in software defined wireless sensor network

    CSIR Research Space (South Africa)

    Matlou, OG

    2017-10-01

    Full Text Available Software Defined Wireless Sensor Network (SDWSN) is realised by infusing Software Defined Network (SDN) model in Wireless Sensor Network (WSN), Reason for that is to overcome the challenges of WSN. Artificial Intelligence (AI) and machine learning...

  12. Automation of neutral beam source conditioning with artificial intelligence techniques

    International Nuclear Information System (INIS)

    Johnson, R.R.; Canales, T.; Lager, D.

    1986-01-01

    This paper describes a system that automates neutral beam source conditioning. The system achieves this with artificial intelligence techniques. The architecture of the system is presented followed by a description of its performance

  13. Artificial intelligence and applications relevant to nuclear industries

    International Nuclear Information System (INIS)

    Haridasan, G.; Das, Debashis

    1987-01-01

    Possible areas of application of artificial intelligence systems such as machine vision systems and expert systems are indicated. The work underway in this field at the Bhabha Atomic Research Centre, Bombay is briefly mentioned. (M.G.B.)

  14. Artificial intelligence: Learning to play Go from scratch

    Science.gov (United States)

    Singh, Satinder; Okun, Andy; Jackson, Andrew

    2017-10-01

    An artificial-intelligence program called AlphaGo Zero has mastered the game of Go without any human data or guidance. A computer scientist and two members of the American Go Association discuss the implications. See Article p.354

  15. Automated Machinery Health Monitoring Using Stress Wave Analysis & Artificial Intelligence

    National Research Council Canada - National Science Library

    Board, David

    1998-01-01

    .... Army, for application to helicopter drive train components. The system will detect structure borne, high frequency acoustic data, and process it with feature extraction and polynomial network artificial intelligence software...

  16. Automation of neutral beam source conditioning with artificial intelligence techniques

    International Nuclear Information System (INIS)

    Johnson, R.R.; Canales, T.W.; Lager, D.L.

    1985-01-01

    This paper describes a system that automates neutral beam source conditioning. The system achieves this with artificial intelligence techniques. The architecture of the system is presented followed by a description of its performance

  17. Knowledge in Artificial Intelligence Systems: Searching the Strategies for Application

    OpenAIRE

    Kornienko, Alla A.; Kornienko, Anatoly V.; Fofanov, Oleg B.; Chubik, Maxim P.

    2015-01-01

    The studies based on auto-epistemic logic are pointed out as an advanced direction for development of artificial intelligence (AI). Artificial intelligence is taken as a system that imitates the solution of complicated problems by human during the course of life. The structure of symbols and operations, by which intellectual solution is performed, as well as searching the strategic reference points for those solutions, which are caused by certain structures of symbols and operations, – are co...

  18. Semantic Network and Frame Knowledge Representation Formalisms in Artificial Intelligence

    OpenAIRE

    Rashid, Pshtiwan Qader

    2015-01-01

    ABSTRACT: Choosing a suitable method to represent the knowledge concerning the real world is one of the major issues involved in Artificial Intelligence. The purpose of this research is to consider the important beneficial roles of semantic network and frame formalisms for knowledge representation in Artificial Intelligence. The basic properties of the above methods for appropriate structuring and arranging the knowledge are presented. Some types of relationships, the conceptual graph...

  19. An Artificial Intelligence-Based Environment Quality Analysis System

    OpenAIRE

    Oprea , Mihaela; Iliadis , Lazaros

    2011-01-01

    Part 20: Informatics and Intelligent Systems Applications for Quality of Life information Services (ISQLIS) Workshop; International audience; The paper describes an environment quality analysis system based on a combination of some artificial intelligence techniques, artificial neural networks and rule-based expert systems. Two case studies of the system use are discussed: air pollution analysis and flood forecasting with their impact on the environment and on the population health. The syste...

  20. Artificial Intelligence: Threat or Boon to Radiologists?

    Science.gov (United States)

    Recht, Michael; Bryan, R Nick

    2017-11-01

    The development and integration of machine learning/artificial intelligence into routine clinical practice will significantly alter the current practice of radiology. Changes in reimbursement and practice patterns will also continue to affect radiology. But rather than being a significant threat to radiologists, we believe these changes, particularly machine learning/artificial intelligence, will be a boon to radiologists by increasing their value, efficiency, accuracy, and personal satisfaction. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  1. Human Brain inspired Artificial Intelligence & Developmental Robotics: A Review

    Directory of Open Access Journals (Sweden)

    Suresh Kumar

    2017-06-01

    Full Text Available Along with the developments in the field of the robotics, fascinating contributions and developments can be seen in the field of Artificial intelligence (AI. In this paper we will discuss about the developments is the field of artificial intelligence focusing learning algorithms inspired from the field of Biology, particularly large scale brain simulations, and developmental Psychology. We will focus on the emergence of the Developmental robotics and its significance in the field of AI.

  2. A Python Engine for Teaching Artificial Intelligence in Games

    OpenAIRE

    Riedl, Mark O.

    2015-01-01

    Computer games play an important role in our society and motivate people to learn computer science. Since artificial intelligence is integral to most games, they can also be used to teach artificial intelligence. We introduce the Game AI Game Engine (GAIGE), a Python game engine specifically designed to teach about how AI is used in computer games. A progression of seven assignments builds toward a complete, working Multi-User Battle Arena (MOBA) game. We describe the engine, the assignments,...

  3. Modelling fuel cell performance using artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Ogaji, S.O.T.; Singh, R.; Pilidis, P.; Diacakis, M. [Power Propulsion and Aerospace Engineering Department, Centre for Diagnostics and Life Cycle Costs, Cranfield University (United Kingdom)

    2006-03-09

    Over the last few years, fuel cell technology has been increasing promisingly its share in the generation of stationary power. Numerous pilot projects are operating worldwide, continuously increasing the amount of operating hours either as stand-alone devices or as part of gas turbine combined cycles. An essential tool for the adequate and dynamic analysis of such systems is a software model that enables the user to assess a large number of alternative options in the least possible time. On the other hand, the sphere of application of artificial neural networks has widened covering such endeavours of life such as medicine, finance and unsurprisingly engineering (diagnostics of faults in machines). Artificial neural networks have been described as diagrammatic representation of a mathematical equation that receives values (inputs) and gives out results (outputs). Artificial neural networks systems have the capacity to recognise and associate patterns and because of their inherent design features, they can be applied to linear and non-linear problem domains. In this paper, the performance of the fuel cell is modelled using artificial neural networks. The inputs to the network are variables that are critical to the performance of the fuel cell while the outputs are the result of changes in any one or all of the fuel cell design variables, on its performance. Critical parameters for the cell include the geometrical configuration as well as the operating conditions. For the neural network, various network design parameters such as the network size, training algorithm, activation functions and their causes on the effectiveness of the performance modelling are discussed. Results from the analysis as well as the limitations of the approach are presented and discussed. (author)

  4. Modelling fuel cell performance using artificial intelligence

    Science.gov (United States)

    Ogaji, S. O. T.; Singh, R.; Pilidis, P.; Diacakis, M.

    Over the last few years, fuel cell technology has been increasing promisingly its share in the generation of stationary power. Numerous pilot projects are operating worldwide, continuously increasing the amount of operating hours either as stand-alone devices or as part of gas turbine combined cycles. An essential tool for the adequate and dynamic analysis of such systems is a software model that enables the user to assess a large number of alternative options in the least possible time. On the other hand, the sphere of application of artificial neural networks has widened covering such endeavours of life such as medicine, finance and unsurprisingly engineering (diagnostics of faults in machines). Artificial neural networks have been described as diagrammatic representation of a mathematical equation that receives values (inputs) and gives out results (outputs). Artificial neural networks systems have the capacity to recognise and associate patterns and because of their inherent design features, they can be applied to linear and non-linear problem domains. In this paper, the performance of the fuel cell is modelled using artificial neural networks. The inputs to the network are variables that are critical to the performance of the fuel cell while the outputs are the result of changes in any one or all of the fuel cell design variables, on its performance. Critical parameters for the cell include the geometrical configuration as well as the operating conditions. For the neural network, various network design parameters such as the network size, training algorithm, activation functions and their causes on the effectiveness of the performance modelling are discussed. Results from the analysis as well as the limitations of the approach are presented and discussed.

  5. Artificial intelligence and Internet of Things in a “smart home” context

    DEFF Research Database (Denmark)

    Lynggaard, Per

    We are currently witnessing an evolution from building and home automation to smart homes, driven by progressing maturity of the Internet of Things and the use of artificial intelligence. However, significant technological challenges such as immature home intelligence, huge network and central...... with autonomous behavior, parallel processing, context awareness, and node communication. In particular, it introduces a novel approach to adapt and distribute the artificial intelligence to match the distributed system architecture in the smart home. The proposed solution addresses important issues such as real......-time learning, temporal detection with a high probability, battery lifetime, network communication, integration with smart objects, and embedded processing power. A multi-agent smart object model is provided to support the artificial intelligence framework with a new distributed architecture. This model focuses...

  6. Computational neuroscience for advancing artificial intelligence

    Directory of Open Access Journals (Sweden)

    Fernando P. Ponce

    2011-07-01

    Full Text Available resumen del libro de Alonso, E. y Mondragón, E. (2011. Hershey, NY: Medical Information Science Reference. La neurociencia como disciplinapersigue el entendimiento del cerebro y su relación con el funcionamiento de la mente a través del análisis de la comprensión de la interacción de diversos procesos físicos, químicos y biológicos (Bassett & Gazzaniga, 2011. Por otra parte, numerosas disciplinasprogresivamente han realizado significativas contribuciones en esta empresa tales como la matemática, la psicología o la filosofía, entre otras. Producto de este esfuerzo, es que junto con la neurociencia tradicional han aparecido disciplinas complementarias como la neurociencia cognitiva, la neuropsicología o la neurocienciacomputacional (Bengio, 2007; Dayan & Abbott, 2005. En el contexto de la neurociencia computacional como disciplina complementaria a laneurociencia tradicional. Alonso y Mondragón (2011 editan el libroComputacional Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications.

  7. [Artificial intelligence in medicine: limits and obstacles.

    Science.gov (United States)

    Santoro, Eugenio

    2017-12-01

    Data scientists and physicians are starting to use artificial intelligence (AI) even in the medical field in order to better understand the relationships among the huge amount of data coming from the great number of sources today available. Through the data interpretation methods made available by the recent AI tools, researchers and AI companies have focused on the development of models allowing to predict the risk of suffering from a specific disease, to make a diagnosis, and to recommend a treatment that is based on the best and most updated scientific evidence. Even if AI is used to perform unimaginable tasks until a few years ago, the awareness about the ongoing revolution has not yet spread through the medical community for several reasons including the lack of evidence about safety, reliability and effectiveness of these tools, the lack of regulation accompanying hospitals in the use of AI by health care providers, the difficult attribution of liability in case of errors and malfunctions of these systems, and the ethical and privacy questions that they raise and that, as of today, are still unanswered.

  8. [Artificial intelligence applied to radiation oncology].

    Science.gov (United States)

    Bibault, J-E; Burgun, A; Giraud, P

    2017-05-01

    Performing randomised comparative clinical trials in radiation oncology remains a challenge when new treatment modalities become available. One of the most recent examples is the lack of phase III trials demonstrating the superiority of intensity-modulated radiation therapy in most of its current indications. A new paradigm is developing that consists in the mining of large databases to answer clinical or translational issues. Beyond national databases (such as SEER or NCDB), that often lack the necessary level of details on the population studied or the treatments performed, electronic health records can be used to create detailed phenotypic profiles of any patients. In parallel, the Record-and-Verify Systems used in radiation oncology precisely document the planned and performed treatments. Artificial Intelligence and machine learning algorithms can be used to incrementally analyse these data in order to generate hypothesis to better personalize treatments. This review discusses how these methods have already been used in previous studies. Copyright © 2017 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

  9. Artificial intelligence, physiological genomics, and precision medicine.

    Science.gov (United States)

    Williams, Anna Marie; Liu, Yong; Regner, Kevin R; Jotterand, Fabrice; Liu, Pengyuan; Liang, Mingyu

    2018-04-01

    Big data are a major driver in the development of precision medicine. Efficient analysis methods are needed to transform big data into clinically-actionable knowledge. To accomplish this, many researchers are turning toward machine learning (ML), an approach of artificial intelligence (AI) that utilizes modern algorithms to give computers the ability to learn. Much of the effort to advance ML for precision medicine has been focused on the development and implementation of algorithms and the generation of ever larger quantities of genomic sequence data and electronic health records. However, relevance and accuracy of the data are as important as quantity of data in the advancement of ML for precision medicine. For common diseases, physiological genomic readouts in disease-applicable tissues may be an effective surrogate to measure the effect of genetic and environmental factors and their interactions that underlie disease development and progression. Disease-applicable tissue may be difficult to obtain, but there are important exceptions such as kidney needle biopsy specimens. As AI continues to advance, new analytical approaches, including those that go beyond data correlation, need to be developed and ethical issues of AI need to be addressed. Physiological genomic readouts in disease-relevant tissues, combined with advanced AI, can be a powerful approach for precision medicine for common diseases.

  10. Artificial intelligence aid to efficient plant operations

    International Nuclear Information System (INIS)

    Wildberger, A.M.; Pack, R.W.

    1987-01-01

    As the nuclear power industry matures, it is becoming more and more important that plants be operated in an efficient, cost-effective manner, without, of course, any decrease in the essential margins of safety. Indeed, most opportunities for improved efficiency have little or no relation to nuclear safety, but are based on trade-offs among operator controllable parameters both within and external to the reactor itself. While these trade-offs are describable in terms of basic physical theory, thermodynamics, and the mathematics of control systems, their actual application is highly plant specific and influenced even by the day-to-day condition of the various plant components. This paper proposes the use of artificial intelligence techniques to construct a computer-based expert assistant to the plant operator for the purpose of aiding him in improving the efficiency of plant operation on a routine basis. The proposed system, which only advises the human operator, seems more amenable to the current regulatory approach than a truly automated control system even if the latter provides for manual override

  11. The Artificial Intelligence Workbench: a retrospective review

    Directory of Open Access Journals (Sweden)

    Hugo LÓPEZ-FERNÁNDEZ

    2016-10-01

    Full Text Available Last decade, biomedical and bioinformatics researchers have been demanding advanced and user-friendly applications for real use in practice. In this context, the Artificial Intelligence Workbench, an open-source Java desktop application framework for scientific software development, emerged with the goal of provid-ing support to both fundamental and applied research in the domain of transla-tional biomedicine and bioinformatics. AIBench automatically provides function-alities that are common to scientific applications, such as user parameter defini-tion, logging facilities, multi-threading execution, experiment repeatability, work-flow management, and fast user interface development, among others. Moreover, AIBench promotes a reusable component based architecture, which also allows assembling new applications by the reuse of libraries from existing projects or third-party software. Ten years have passed since the first release of AIBench, so it is time to look back and check if it has fulfilled the purposes for which it was conceived to and how it evolved over time.

  12. Artificial intelligence in mitral valve analysis.

    Science.gov (United States)

    Jeganathan, Jelliffe; Knio, Ziyad; Amador, Yannis; Hai, Ting; Khamooshian, Arash; Matyal, Robina; Khabbaz, Kamal R; Mahmood, Feroze

    2017-01-01

    Echocardiographic analysis of mitral valve (MV) has become essential for diagnosis and management of patients with MV disease. Currently, the various software used for MV analysis require manual input and are prone to interobserver variability in the measurements. The aim of this study is to determine the interobserver variability in an automated software that uses artificial intelligence for MV analysis. Retrospective analysis of intraoperative three-dimensional transesophageal echocardiography data acquired from four patients with normal MV undergoing coronary artery bypass graft surgery in a tertiary hospital. Echocardiographic data were analyzed using the eSie Valve Software (Siemens Healthcare, Mountain View, CA, USA). Three examiners analyzed three end-systolic (ES) frames from each of the four patients. A total of 36 ES frames were analyzed and included in the study. A multiple mixed-effects ANOVA model was constructed to determine if the examiner, the patient, and the loop had a significant effect on the average value of each parameter. A Bonferroni correction was used to correct for multiple comparisons, and P = 0.0083 was considered to be significant. Examiners did not have an effect on any of the six parameters tested. Patient and loop had an effect on the average parameter value for each of the six parameters as expected (P < 0.0083 for both). We were able to conclude that using automated analysis, it is possible to obtain results with good reproducibility, which only requires minimal user intervention.

  13. Applications of artificial intelligence to mission planning

    Science.gov (United States)

    Ford, Donnie R.; Rogers, John S.; Floyd, Stephen A.

    1990-01-01

    The scheduling problem facing NASA-Marshall mission planning is extremely difficult for several reasons. The most critical factor is the computational complexity involved in developing a schedule. The size of the search space is large along some dimensions and infinite along others. It is because of this and other difficulties that many of the conventional operation research techniques are not feasible or inadequate to solve the problems by themselves. Therefore, the purpose is to examine various artificial intelligence (AI) techniques to assist conventional techniques or to replace them. The specific tasks performed were as follows: (1) to identify mission planning applications for object oriented and rule based programming; (2) to investigate interfacing AI dedicated hardware (Lisp machines) to VAX hardware; (3) to demonstrate how Lisp may be called from within FORTRAN programs; (4) to investigate and report on programming techniques used in some commercial AI shells, such as Knowledge Engineering Environment (KEE); and (5) to study and report on algorithmic methods to reduce complexity as related to AI techniques.

  14. Implementing Artificial Intelligence Behaviors in a Virtual World

    Science.gov (United States)

    Krisler, Brian; Thome, Michael

    2012-01-01

    In this paper, we will present a look at the current state of the art in human-computer interface technologies, including intelligent interactive agents, natural speech interaction and gestural based interfaces. We describe our use of these technologies to implement a cost effective, immersive experience on a public region in Second Life. We provision our Artificial Agents as a German Shepherd Dog avatar with an external rules engine controlling the behavior and movement. To interact with the avatar, we implemented a natural language and gesture system allowing the human avatars to use speech and physical gestures rather than interacting via a keyboard and mouse. The result is a system that allows multiple humans to interact naturally with AI avatars by playing games such as fetch with a flying disk and even practicing obedience exercises using voice and gesture, a natural seeming day in the park.

  15. Computer Aided Automatic Control - CAAC artificial intelligence block

    Energy Technology Data Exchange (ETDEWEB)

    Balate, J.; Chramcov, B.; Princ, M. [Brno Univ. of Technology (Czech Republic). Faculty of Technology in Zlin

    2000-07-01

    The aim of the plan to build up the system CAAC - Computer Aided Automatic Control is to create modular setup of partial computing programs including theory of automatic control, algorithms of programs for processing signals and programs of control algorithms. To approach its informative contents to students and professional public the CAAC system utilizes Internet services http in the form of WWW pages. The CAAC system is being processed at the Institute of Automation and Control Technique of the Faculty of Technology in Zlin of the Brno University of Technology and is determined particularly for pedagogic purposes. Recently also the methods of artificial intelligence have been included to the open CAAC system and that is comprised in this article. (orig.)

  16. Applications of Artificial Intelligence in Education--A Personal View.

    Science.gov (United States)

    Richer, Mark H.

    1985-01-01

    Discusses: how artificial intelligence (AI) can advance education; if the future of software lies in AI; the roots of intelligent computer-assisted instruction; protocol analysis; reactive environments; LOGO programming language; student modeling and coaching; and knowledge-based instructional programs. Numerous examples of AI programs are cited.…

  17. Computational Narrative Intelligence: A Human-Centered Goal for Artificial Intelligence

    OpenAIRE

    Riedl, Mark O.

    2016-01-01

    Narrative intelligence is the ability to craft, tell, understand, and respond affectively to stories. We argue that instilling artificial intelligences with computational narrative intelligence affords a number of applications beneficial to humans. We lay out some of the machine learning challenges necessary to solve to achieve computational narrative intelligence. Finally, we argue that computational narrative is a practical step towards machine enculturation, the teaching of sociocultural v...

  18. An application of artificial intelligence for rainfall–runoff modeling

    Indian Academy of Sciences (India)

    This study proposes an application of two techniques of artificial intelligence (AI) for rainfall–runoff modeling: the artificial neural networks (ANN) and .... conventional mathematical analysis does not, or cannot, provide analytical solutions, .... very simple where there exist one-to-one relation- ships between the symbols of the ...

  19. An application of artificial intelligence for rainfall–runoff modeling

    Indian Academy of Sciences (India)

    This study proposes an application of two techniques of artificial intelligence (AI) for rainfall–runoff modeling: the artificial neural networks (ANN) and the evolutionary computation (EC). Two diff- erent ANN techniques, the feed forward back propagation (FFBP) and generalized regression neural network (GRNN) methods ...

  20. DEALING MEDICAL DATA WITH FUNDAMENTALS OF NEW ARTIFICIAL INTELLIGENCE

    OpenAIRE

    ALI SAKR,; DIANA MOSA

    2010-01-01

    This work applies rough sets and artificial intelligent to analyze and reduce medical data without affecting the information to construct an expert system. The ROSETTA software is applied for analyzing some medical data and deducing rules. This paper discusses fundamentals of Rough Set Theory (RST); uses this theorem to extract decision rules for medical data and drive results by Artificial Neural Network (ANN).

  1. Application of artificial intelligence in load frequency control of ...

    African Journals Online (AJOL)

    This paper presents the use of artificial intelligence to study the load frequency control of interconnected power system. In the proposed scheme, a control methodology is developed using Artificial Neural Network (ANN) and Fuzzy Logic controller (FLC) for interconnected hydro-thermal power system. The control strategies ...

  2. Artificial versus Natural Intelligence: An Adendum to the Philosophy ...

    African Journals Online (AJOL)

    in modern science that is causing waves in the philosophy of mind. Can there be artificial minds? Can machines be made to think? Can machines be conscious? Is it possible for artificial intelligence to replace the human brain? These and similar questions pervade most discussions and philosophical polemics on the issue ...

  3. Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  4. Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  5. Artificial intelligence in drug combination therapy.

    Science.gov (United States)

    Tsigelny, Igor F

    2018-02-09

    Currently, the development of medicines for complex diseases requires the development of combination drug therapies. It is necessary because in many cases, one drug cannot target all necessary points of intervention. For example, in cancer therapy, a physician often meets a patient having a genomic profile including more than five molecular aberrations. Drug combination therapy has been an area of interest for a while, for example the classical work of Loewe devoted to the synergism of drugs was published in 1928-and it is still used in calculations for optimal drug combinations. More recently, over the past several years, there has been an explosion in the available information related to the properties of drugs and the biomedical parameters of patients. For the drugs, hundreds of 2D and 3D molecular descriptors for medicines are now available, while for patients, large data sets related to genetic/proteomic and metabolomics profiles of the patients are now available, as well as the more traditional data relating to the histology, history of treatments, pretreatment state of the organism, etc. Moreover, during disease progression, the genetic profile can change. Thus, the ability to optimize drug combinations for each patient is rapidly moving beyond the comprehension and capabilities of an individual physician. This is the reason, that biomedical informatics methods have been developed and one of the more promising directions in this field is the application of artificial intelligence (AI). In this review, we discuss several AI methods that have been successfully implemented in several instances of combination drug therapy from HIV, hypertension, infectious diseases to cancer. The data clearly show that the combination of rule-based expert systems with machine learning algorithms may be promising direction in this field. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  6. Artificial intelligence in mitral valve analysis

    Directory of Open Access Journals (Sweden)

    Jelliffe Jeganathan

    2017-01-01

    Full Text Available Background: Echocardiographic analysis of mitral valve (MV has become essential for diagnosis and management of patients with MV disease. Currently, the various software used for MV analysis require manual input and are prone to interobserver variability in the measurements. Aim: The aim of this study is to determine the interobserver variability in an automated software that uses artificial intelligence for MV analysis. Settings and Design: Retrospective analysis of intraoperative three-dimensional transesophageal echocardiography data acquired from four patients with normal MV undergoing coronary artery bypass graft surgery in a tertiary hospital. Materials and Methods: Echocardiographic data were analyzed using the eSie Valve Software (Siemens Healthcare, Mountain View, CA, USA. Three examiners analyzed three end-systolic (ES frames from each of the four patients. A total of 36 ES frames were analyzed and included in the study. Statistical Analysis: A multiple mixed-effects ANOVA model was constructed to determine if the examiner, the patient, and the loop had a significant effect on the average value of each parameter. A Bonferroni correction was used to correct for multiple comparisons, and P = 0.0083 was considered to be significant. Results: Examiners did not have an effect on any of the six parameters tested. Patient and loop had an effect on the average parameter value for each of the six parameters as expected (P < 0.0083 for both. Conclusion: We were able to conclude that using automated analysis, it is possible to obtain results with good reproducibility, which only requires minimal user intervention.

  7. Artificial Intelligence in Mitral Valve Analysis

    Science.gov (United States)

    Jeganathan, Jelliffe; Knio, Ziyad; Amador, Yannis; Hai, Ting; Khamooshian, Arash; Matyal, Robina; Khabbaz, Kamal R; Mahmood, Feroze

    2017-01-01

    Background: Echocardiographic analysis of mitral valve (MV) has become essential for diagnosis and management of patients with MV disease. Currently, the various software used for MV analysis require manual input and are prone to interobserver variability in the measurements. Aim: The aim of this study is to determine the interobserver variability in an automated software that uses artificial intelligence for MV analysis. Settings and Design: Retrospective analysis of intraoperative three-dimensional transesophageal echocardiography data acquired from four patients with normal MV undergoing coronary artery bypass graft surgery in a tertiary hospital. Materials and Methods: Echocardiographic data were analyzed using the eSie Valve Software (Siemens Healthcare, Mountain View, CA, USA). Three examiners analyzed three end-systolic (ES) frames from each of the four patients. A total of 36 ES frames were analyzed and included in the study. Statistical Analysis: A multiple mixed-effects ANOVA model was constructed to determine if the examiner, the patient, and the loop had a significant effect on the average value of each parameter. A Bonferroni correction was used to correct for multiple comparisons, and P = 0.0083 was considered to be significant. Results: Examiners did not have an effect on any of the six parameters tested. Patient and loop had an effect on the average parameter value for each of the six parameters as expected (P < 0.0083 for both). Conclusion: We were able to conclude that using automated analysis, it is possible to obtain results with good reproducibility, which only requires minimal user intervention. PMID:28393769

  8. Artificial-intelligence methods in decision and control systems

    Energy Technology Data Exchange (ETDEWEB)

    Lirov, Y.V.

    1987-01-01

    Artificial-intelligence methods were applied to the design and implementation of some decision and control systems. A so-called semantic approach to control and decisions was developed and artificial-intelligence methods were used to provide a realizable implementation. These concepts were tested using applications from robust identification and control of time-varying systems, intelligent navigation, and intelligent simulation of differential games. An aspect of a generalized traveling-salesman problem was solved, and intelligent simulation of differential games was implemented in Prolog using an example system for automated learning by tactical decision systems in air combat. These implementations were successful and provide several advantages over traditional approaches. The limitations of these concepts were identified and suggestions for future work are made.

  9. Artificial intelligence for multi-mission planetary operations

    Science.gov (United States)

    Atkinson, David J.; Lawson, Denise L.; James, Mark L.

    1990-01-01

    A brief introduction is given to an automated system called the Spacecraft Health Automated Reasoning Prototype (SHARP). SHARP is designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for evaluation of the prototype in a real-time operations setting during the Voyager spacecraft encounter with Neptune in August, 1989. The preliminary results of the SHARP project and plans for future application of the technology are discussed.

  10. Enabling Autonomous Space Mission Operations with Artificial Intelligence

    Science.gov (United States)

    Frank, Jeremy

    2017-01-01

    For over 50 years, NASA's crewed missions have been confined to the Earth-Moon system, where speed-of-light communications delays between crew and ground are practically nonexistent. This ground-centered mode of operations, with a large, ground-based support team, is not sustainable for NASAs future human exploration missions to Mars. Future astronauts will need smarter tools employing Artificial Intelligence (AI) techniques make decisions without inefficient communication back and forth with ground-based mission control. In this talk we will describe several demonstrations of astronaut decision support tools using AI techniques as a foundation. These demonstrations show that astronauts tasks ranging from living and working to piloting can benefit from AI technology development.

  11. The Application of Artificial Intelligence to Astronomical Scheduling Problems

    Science.gov (United States)

    Johnston, Mark D.

    1993-01-01

    As artificial intelligence (AI) technology has moved from the research laboratory into more and more widespread use, one of the leading applications in astronomy has been to high-profile observation scheduling. The Spike scheduling system was developed by the Space Telescope Science Institute (STScI) for the purpose of long-range scheduling of Hubble Space Telescope (HST). Spike has been in daily operational use at STScI since well before HST launch in April 1990. The system has also been adapted to schedule other missions: one of these missions (EUVE) is currently operational, while another (ASTRO-D) will be launched in February 1993. Some other future space astronomy missions (XTE, SWAS, and AXAF) are making tentative plans to use Spike. Spike has proven to be a powerful and flexible scheduling framework with applicability to a wide variety of problems.

  12. Experimental Autonomous Road Vehicle with Logical Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Sergey Sergeevich Shadrin

    2017-01-01

    Full Text Available This article describes some technical issues regarding the adaptation of a production car to a platform for the development and testing of autonomous driving technologies. A universal approach to performing the reverse engineering of electric power steering (EPS for the purpose of external control is also presented. The primary objective of the related study was to solve the problem associated with the precise prediction of the dynamic trajectory of an autonomous vehicle. This was accomplished by deriving a new equation for determining the lateral tire forces and adjusting some of the vehicle parameters under road test conductions. A Mivar expert system was also integrated into the control system of the experimental autonomous vehicle. The expert system was made more flexible and effective for the present application by the introduction of hybrid artificial intelligence with logical reasoning. The innovation offers a solution to the major problem of liability in the event of an autonomous transport vehicle being involved in a collision.

  13. Medical image diagnosis of liver cancer using artificial intelligence

    International Nuclear Information System (INIS)

    Kondo, Tadashi; Ueno, Junji; Takao, Shoichiro

    2010-01-01

    A revised Group Method of Data Handling (GMDH)-type neural network algorithm using artificial intelligence technology for medical image diagnosis is proposed and is applied to medical image diagnosis of liver cancer. In this algorithm, the knowledge base for medical image diagnosis are used for organizing the neural network architecture for medical image diagnosis. Furthermore, the revised GMDH-type neural network algorithm has a feedback loop and can identify the characteristics of the medical images accurately using feedback loop calculations. The optimum neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion defined as Prediction Sum of Squares (PSS). It is shown that the revised GMDH-type neural network can be easily applied to the medical image diagnosis. (author)

  14. Research on architecture of intelligent design platform for artificial neural network expert system

    Science.gov (United States)

    Gu, Honghong

    2017-09-01

    Based on the review of the development and current situation of CAD technology, the necessity of combination of artificial neural network and expert system, and then present an intelligent design system based on artificial neural network. Moreover, it discussed the feasibility of realization of a design-oriented expert system development tools on the basis of above combination. In addition, knowledge representation strategy and method and the solving process are given in this paper.

  15. Intelligent Technologies for Interactive Entertainment

    NARCIS (Netherlands)

    Nijholt, Antinus; Reidsma, Dennis; Hondorp, G.H.W.; Unknown, [Unknown

    2009-01-01

    These are the proceedings of the 3rd International Conference on Intelligent Technologies for Interactive Entertainment (INTETAIN 09). The first edition of this conference, organised in Madonna di Campiglio, saw the gathering of a diverse audience with broad and varied interests. With presentations

  16. Space Communications Artificial Intelligence for Link Evaluation Terminal (SCAILET)

    Science.gov (United States)

    Shahidi, Anoosh

    1991-01-01

    A software application to assis end-users of the Link Evaluation Terminal (LET) for satellite communication is being developed. This software application incorporates artificial intelligence (AI) techniques and will be deployed as an interface to LET. The high burst rate (HBR) LET provides 30 GHz transmitting/20 GHz receiving, 220/110 Mbps capability for wideband communications technology experiments with the Advanced Communications Technology Satellite (ACTS). The HBR LET and ACTS are being developed at the NASA Lewis Research Center. The HBR LET can monitor and evaluate the integrity of the HBR communications uplink and downlink to the ACTS satellite. The uplink HBR transmission is performed by bursting the bit-pattern as a modulated signal to the satellite. By comparing the transmitted bit pattern with the received bit pattern, HBR LET can determine the bit error rate BER) under various atmospheric conditions. An algorithm for power augmentation is applied to enhance the system's BER performance at reduced signal strength caused by adverse conditions. Programming scripts, defined by the design engineer, set up the HBR LET terminal by programming subsystem devices through IEEE488 interfaces. However, the scripts are difficult to use, require a steep learning curve, are cryptic, and are hard to maintain. The combination of the learning curve and the complexities involved with editing the script files may discourage end-users from utilizing the full capabilities of the HBR LET system. An intelligent assistant component of SCAILET that addresses critical end-user needs in the programming of the HBR LET system as anticipated by its developers is described. A close look is taken at the various steps involved in writing ECM software for a C&P, computer and at how the intelligent assistant improves the HBR LET system and enhances the end-user's ability to perform the experiments.

  17. The future of radiology augmented with Artificial Intelligence: A strategy for success.

    Science.gov (United States)

    Liew, Charlene

    2018-05-01

    The rapid development of Artificial Intelligence/deep learning technology and its implementation into routine clinical imaging will cause a major transformation to the practice of radiology. Strategic positioning will ensure the successful transition of radiologists into their new roles as augmented clinicians. This paper describes an overall vision on how to achieve a smooth transition through the practice of augmented radiology where radiologists-in-the-loop ensure the safe implementation of Artificial Intelligence systems. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems

    CERN Document Server

    Dash, Subhransu; Panigrahi, Bijaya

    2015-01-01

      The book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the broad area of use of artificial intelligence and evolutionary algorithms in engineering systems. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.

  19. Artificial intelligence for the CTA Observatory scheduler

    Science.gov (United States)

    Colomé, Josep; Colomer, Pau; Campreciós, Jordi; Coiffard, Thierry; de Oña, Emma; Pedaletti, Giovanna; Torres, Diego F.; Garcia-Piquer, Alvaro

    2014-08-01

    The Cherenkov Telescope Array (CTA) project will be the next generation ground-based very high energy gamma-ray instrument. The success of the precursor projects (i.e., HESS, MAGIC, VERITAS) motivated the construction of this large infrastructure that is included in the roadmap of the ESFRI projects since 2008. CTA is planned to start the construction phase in 2015 and will consist of two arrays of Cherenkov telescopes operated as a proposal-driven open observatory. Two sites are foreseen at the southern and northern hemispheres. The CTA observatory will handle several observation modes and will have to operate tens of telescopes with a highly efficient and reliable control. Thus, the CTA planning tool is a key element in the control layer for the optimization of the observatory time. The main purpose of the scheduler for CTA is the allocation of multiple tasks to one single array or to multiple sub-arrays of telescopes, while maximizing the scientific return of the facility and minimizing the operational costs. The scheduler considers long- and short-term varying conditions to optimize the prioritization of tasks. A short-term scheduler provides the system with the capability to adapt, in almost real-time, the selected task to the varying execution constraints (i.e., Targets of Opportunity, health or status of the system components, environment conditions). The scheduling procedure ensures that long-term planning decisions are correctly transferred to the short-term prioritization process for a suitable selection of the next task to execute on the array. In this contribution we present the constraints to CTA task scheduling that helped classifying it as a Flexible Job-Shop Problem case and finding its optimal solution based on Artificial Intelligence techniques. We describe the scheduler prototype that uses a Guarded Discrete Stochastic Neural Network (GDSN), for an easy representation of the possible long- and short-term planning solutions, and Constraint

  20. Artificial intelligence and other innovative computer applications in the nuclear industry

    International Nuclear Information System (INIS)

    Majumdar, M.C.; Majumdar, D.; Sackett, J.I.

    1987-01-01

    This book reviews the applications of artificial intelligence and computers in the nuclear industry and chemical plants. The topics discussed are: Robots applications and reliability in maintenance of nuclear power plants; Advanced information technology and expert systems; Knowledge base alarm systems; Emergency planning and response of accidents; and reactor safety assessment

  1. LOGO Progress Report 1973-1975. Artificial Intelligence Memo Number 356. Revised.

    Science.gov (United States)

    Abelson, H.; And Others

    This report outlines the accomplishments of the LOGO project of the Massachusetts Institute of Technology's Artificial Intelligence Laboratory during the period 1973-1975. Three major areas of work are listed: (1) building learning environments, (2) the theory behind the environments, and (3) experimenting with learning environments. Advances in…

  2. A Framework for Intelligent Instructional Systems: An Artificial Intelligence Machine Learning Approach.

    Science.gov (United States)

    Becker, Lee A.

    1987-01-01

    Presents and develops a general model of the nature of a learning system and a classification for learning systems. Highlights include the relationship between artificial intelligence and cognitive psychology; computer-based instructional systems; intelligent instructional systems; and the role of the learner's knowledge base in an intelligent…

  3. The Coming of Age of Artificial Intelligence in Medicine*

    Science.gov (United States)

    Patel, Vimla L.; Shortliffe, Edward H.; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R.; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2009-01-01

    Summary This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its “adolescence” (Shortliffe EH. The adolescence of AI in medicine: Will the field come of age in the ‘90s? Artificial Intelligence in Medicine 1993; 5:93–106). In this article, the discussants reflect on medical AI research during the subsequent years and attempt to characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems. PMID:18790621

  4. A PHILOSOPHICAL APPROACH TO ARTIFICIAL INTELLIGENCE AND ISLAMIC VALUES

    Directory of Open Access Journals (Sweden)

    Ali Akbar Ziaee

    2012-02-01

    Full Text Available Artificial Intelligence has the potential to empower humans through enhanced learning and performance. But if this potential is to be realized and accepted, the ethical aspects as well as the technical must be addressed. Many engineers claim that AI will be smarter than human brains, including scientific creativity, general wisdom and social skills, so we must consider it an important factor for making decisions in our social life and especially in our Islamic societies. The most important challenges will be the quality of representing the Islamic values like piety, obedience, Halal and Haram, and etc in the form of semantics. In this paper, I want to emphasize on the role of Divine Islamic values in the application of AI and discuss it according to philosophy of AI and Islamic perspective.Keywords- Value, expert, Community Development, Artificial Intelligence, Superintelligence, Friendly Artificial Intelligence

  5. [Artificial intelligence--the knowledge base applied to nephrology].

    Science.gov (United States)

    Sancipriano, G P

    2005-01-01

    The idea that efficacy efficiency, and quality in medicine could not be reached without sorting the huge knowledge of medical and nursing science is very common. Engineers and computer scientists have developed medical software with great prospects for success, but currently these software applications are not so useful in clinical practice. The medical doctor and the trained nurse live the 'information age' in many daily activities, but the main benefits are not so widespread in working activities. Artificial intelligence and, particularly, export systems charm health staff because of their potential. The first part of this paper summarizes the characteristics of 'weak artificial intelligence' and of expert systems important in clinical practice. The second part discusses medical doctors' requirements and the current nephrologic knowledge bases available for artificial intelligence development.

  6. The coming of age of artificial intelligence in medicine.

    Science.gov (United States)

    Patel, Vimla L; Shortliffe, Edward H; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2009-05-01

    This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its "adolescence" (Shortliffe EH. The adolescence of AI in medicine: will the field come of age in the '90s? Artificial Intelligence in Medicine 1993;5:93-106). In this article, the discussants reflect on medical AI research during the subsequent years and characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision-making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems.

  7. Artificial intelligence and its impact on combat aircraft

    Science.gov (United States)

    Ott, Lawrence M.; Abbot, Kathy; Kleider, Alfred; Moon, D.; Retelle, John

    1987-01-01

    As the threat becomes more sophisticated and weapon systems more complex to meet the threat, the need for machines to assist the pilot in the assessment of information becomes paramount. This is particularly true in real-time, high stress situations. The advent of artificial intelligence (AI) technology offers the opportunity to make quantum advances in the application of machine technology. However, if AI systems are to find their way into combat aircraft, they must meet certain criteria. The systems must be responsive, reliable, easy to use, flexible, and understandable. These criteria are compared with the current status used in a combat airborne application. Current AI systems deal with nonreal time applications and require significant user interaction. On the other hand, aircraft applications require real time, minimum human interaction systems. In order to fill the gap between where technology is now and where it must be for aircraft applications, considerable government research is ongoing in NASA, DARPA, and three services. The ongoing research is briefly summarized. Finally, recognizing that AI technology is in its embryonic stage, and the aircraft needs are very demanding, a number of issues arise. These issues are delineated and findings are provided where appropriate.

  8. Training Software in Artificial-Intelligence Computing Techniques

    Science.gov (United States)

    Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

    2005-01-01

    The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

  9. Artificial intelligence (AI) systems for interpreting complex medical datasets.

    Science.gov (United States)

    Altman, R B

    2017-05-01

    Advances in machine intelligence have created powerful capabilities in algorithms that find hidden patterns in data, classify objects based on their measured characteristics, and associate similar patients/diseases/drugs based on common features. However, artificial intelligence (AI) applications in medical data have several technical challenges: complex and heterogeneous datasets, noisy medical datasets, and explaining their output to users. There are also social challenges related to intellectual property, data provenance, regulatory issues, economics, and liability. © 2017 ASCPT.

  10. Artificial and Computational Intelligence for Games on Mobile Platforms

    OpenAIRE

    Congdon, Clare Bates; Hingston, Philip; Kendall, Graham

    2013-01-01

    In this chapter, we consider the possibilities of creating new and innovative games that are targeted for mobile devices, such as smart phones and tablets, and that showcase AI (Artificial Intelligence) and CI (Computational Intelligence) approaches. Such games might take advantage of the sensors and facilities that are not available on other platforms, or might simply rely on the "app culture" to facilitate getting the games into users' hands. While these games might be profitable in themsel...

  11. Fifth Conference on Artificial Intelligence for Space Applications

    Science.gov (United States)

    Odell, Steve L. (Compiler)

    1990-01-01

    The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration.

  12. Artificial intelligence and pediatrics: A synthetic mini review

    OpenAIRE

    Kokol, Peter; Završnik, Jernej; Vošner, Helena Blažun

    2018-01-01

    The use of artificial intelligence intelligencein medicine can be traced back to 1968 when Paycha published his paper Le diagnostic a l'aide d'intelligences artificielle, presentation de la premiere machine diagnostri. Few years later Shortliffe et al. presented an expert system named Mycin which was able to identify bacteria causing severe blood infections and to recommend antibiotics. Despite the fact that Mycin outperformed members of the Stanford medical school in the reliability of diagn...

  13. Bionics: A Step toward Artificial Intelligence Systems

    Science.gov (United States)

    Dutton, Robert E.

    1970-01-01

    Recent developments and future prospects in the borrowing of biological principles to build problem solving relationships between human intelligence and the information storage and manipulation capacities of computers. Twenty-one references. (LY)

  14. Systems with artificial intelligence in nuclear power plant operation

    International Nuclear Information System (INIS)

    Bastl, W.; Felkel, L.

    1989-01-01

    The authors first summarize some developments made by GRS teams which can be regarded as the precursors of systems with artificial intelligence, and explain the basic characteristics of artificial intelligence, referring in particular to possible applications in nuclear engineering. The systems described are arranged in four groups according to applicability as follows: plant diagnosis and failure analysis, information systems and operating systems, control systems, assessment and decision aids. The working principle of the systems is explained by some examples giving details of the database and the interference processes. (orig./DG) [de

  15. Solving Systems of Equations with Techniques from Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Irina Maria Terfaloaga

    2015-07-01

    Full Text Available A frequent problem in numerical analysis is solving the systems of equations. That problem has generated in time a great interest among mathematicians and computer scientists, as evidenced by the large number of numerical methods developed. Besides the classical numerical methods, in the last years were proposed methods inspired by techniques from artificial intelligence. Hybrid methods have been also proposed along the time [15, 19]. The goal of this study is to make a survey of methods inspired from artificial intelligence for solving systems of equations

  16. The 1988 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Rash, James (Editor); Hughes, Peter (Editor)

    1988-01-01

    This publication comprises the papers presented at the 1988 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland on May 24, 1988. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in these proceedings fall into the following areas: mission operations support, planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; modeling and simulation; and development tools/methodologies.

  17. Artificial Intelligence Applied to Project Success: A Literature Review

    Directory of Open Access Journals (Sweden)

    Daniel Magaña Martínez

    2015-12-01

    Full Text Available Project control and monitoring tools are based on expert judgement and parametric tools. Projects are the means by which companies implement their strategies. However project success rates are still very low. This is a worrying situation that has a great economic impact so alternative tools for project success prediction must be proposed in order to estimate project success or identify critical factors of success. Some of these tools are based on Artificial Intelligence. In this paper we will carry out a literature review of those papers that use Artificial Intelligence as a tool for project success estimation or critical success factor identification.

  18. APPLYING ARTIFICIAL INTELLIGENCE TECHNIQUES TO HUMAN-COMPUTER INTERFACES

    DEFF Research Database (Denmark)

    Sonnenwald, Diane H.

    1988-01-01

    A description is given of UIMS (User Interface Management System), a system using a variety of artificial intelligence techniques to build knowledge-based user interfaces combining functionality and information from a variety of computer systems that maintain, test, and configure customer telephone...... and data networks. Three artificial intelligence (AI) techniques used in UIMS are discussed, namely, frame representation, object-oriented programming languages, and rule-based systems. The UIMS architecture is presented, and the structure of the UIMS is explained in terms of the AI techniques....

  19. Artificial intelligence and synthetic biology: A tri-temporal contribution.

    Science.gov (United States)

    Bianchini, Francesco

    2016-10-01

    Artificial intelligence can make numerous contributions to synthetic biology. I would like to suggest three that are related to the past, present and future of artificial intelligence. From the past, works in biology and artificial systems by Turing and von Neumann prove highly interesting to explore within the new framework of synthetic biology, especially with regard to the notions of self-modification and self-replication and their links to emergence and the bottom-up approach. The current epistemological inquiry into emergence and research on swarm intelligence, superorganisms and biologically inspired cognitive architecture may lead to new achievements on the possibilities of synthetic biology in explaining cognitive processes. Finally, the present-day discussion on the future of artificial intelligence and the rise of superintelligence may point to some research trends for the future of synthetic biology and help to better define the boundary of notions such as "life", "cognition", "artificial" and "natural", as well as their interconnections in theoretical synthetic biology. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  20. SOME PARADIGMS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL COMPUTER SYSTEMS

    OpenAIRE

    Jerzy Balicki

    2015-01-01

    The article discusses some paradigms of artificial intelligence in the context of their applications in computer financial systems. The proposed approach has a significant po-tential to increase the competitiveness of enterprises, including financial institutions. However, it requires the effective use of supercomputers, grids and cloud computing. A reference is made to the computing environment for Bitcoin. In addition, we characterized genetic programming and artificial neural networks to p...

  1. SOME PARADIGMS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL COMPUTER SYSTEMS

    Directory of Open Access Journals (Sweden)

    Jerzy Balicki

    2015-12-01

    Full Text Available The article discusses some paradigms of artificial intelligence in the context of their applications in computer financial systems. The proposed approach has a significant po-tential to increase the competitiveness of enterprises, including financial institutions. However, it requires the effective use of supercomputers, grids and cloud computing. A reference is made to the computing environment for Bitcoin. In addition, we characterized genetic programming and artificial neural networks to prepare investment strategies on the stock exchange market.

  2. Artificial intelligence in the diagnosis of low back pain.

    Science.gov (United States)

    Mann, N H; Brown, M D

    1991-04-01

    Computerized methods are used to recognize the characteristics of patient pain drawings. Artificial neural network (ANN) models are compared with expert predictions and traditional statistical classification methods when placing the pain drawings of low back pain patients into one of five clinically significant categories. A discussion is undertaken outlining the differences in these classifiers and the potential benefits of the ANN model as an artificial intelligence technique.

  3. Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

    Science.gov (United States)

    1994-01-01

    The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments.

  4. The Construction of Intelligent English Teaching Model Based on Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Xiaoguang Li

    2017-12-01

    Full Text Available In order to build a modernized tool platform that can help students improve their English learning efficiency according to their mastery of knowledge and personality, this paper develops an online intelligent English learning system that uses Java and artificial intelligence language Prolog as the software system. This system is a creative reflection of the thoughts of expert system in artificial intelligence. Established on the Struts Spring Hibernate lightweight JavaEE framework, the system modules are coupled with each other in a much lower degree, which is convenient to future function extension. Combined with the idea of expert system in artificial intelligence, the system developed appropriate learning strategies to help students double the learning effect with half the effort; Finally, the system takes into account the forgetting curve of memory, on which basis the knowledge that has been learned will be tested periodically, intending to spare students’ efforts to do a sea of exercises and obtain better learning results.

  5. The deep learning AI playbook strategy for disruptive artificial intelligence

    CERN Document Server

    Perez, Carlos E

    2017-01-01

    Deep Learning Artificial Intelligence involves the interplay of Computer Science, Physics, Biology, Linguistics and Psychology. In addition to that, it is technology that can be extremely disruptive. The ramifications to society and even our own humanity will be profound. There are few subjects that are as captivating and as consequential as this. Surprisingly, there is very little that is written about this new technology in a more comprehensive and cohesive way. This book is an opinionated take on the developments of Deep Learning AI. One question many have will be "how to apply Deep Learning AI in a business context?" Technology that is disruptive does not automatically imply that its application to valuable use cases will be apparent. For years, many people could not figure out how to monetize the World Wide Web. We are in a similar situation with Deep Learning AI. The developments may be mind-boggling but its monetization is far from being obvious. This book presents a framework to address this shortcomi...

  6. Use of artificial intelligence in supervisory control

    Science.gov (United States)

    Cohen, Aaron; Erickson, Jon D.

    1989-01-01

    Viewgraphs describing the design and testing of an intelligent decision support system called OFMspert are presented. In this expert system, knowledge about the human operator is represented through an operator/system model referred to as the OFM (Operator Function Model). OFMspert uses the blackboard model of problem solving to maintain a dynamic representation of operator goals, plans, tasks, and actions given previous operator actions and current system state. Results of an experiment to assess OFMspert's intent inferencing capability are outlined. Finally, the overall design philosophy for an intelligent tutoring system (OFMTutor) for operators of complex dynamic systems is summarized.

  7. A novel modification of the Turing test for artificial intelligence and robotics in healthcare.

    Science.gov (United States)

    Ashrafian, Hutan; Darzi, Ara; Athanasiou, Thanos

    2015-03-01

    The increasing demands of delivering higher quality global healthcare has resulted in a corresponding expansion in the development of computer-based and robotic healthcare tools that rely on artificially intelligent technologies. The Turing test was designed to assess artificial intelligence (AI) in computer technology. It remains an important qualitative tool for testing the next generation of medical diagnostics and medical robotics. Development of quantifiable diagnostic accuracy meta-analytical evaluative techniques for the Turing test paradigm. Modification of the Turing test to offer quantifiable diagnostic precision and statistical effect-size robustness in the assessment of AI for computer-based and robotic healthcare technologies. Modification of the Turing test to offer robust diagnostic scores for AI can contribute to enhancing and refining the next generation of digital diagnostic technologies and healthcare robotics. Copyright © 2014 John Wiley & Sons, Ltd.

  8. Northeast Artificial Intelligence Consortium Annual Report. 1988 Executive Summary. Volume 1

    Science.gov (United States)

    1989-10-01

    Automatic Photointerpretation (RPI): Vol. 7 ............................ 12 1.3.7 Artificial Intelligence Applications to Speech Recognition (RIT...PHOTOINTERPRETATION PIs: James W. Modestino, Arthur C. Sanderson Rensselaer Polytechnic Institute (Volume 7) ARTIFICIAL INTELLIGENCE APPLICATIONS TO SPEECH...Workstation. The RPI volume for FY88 documents this progress. 1.3.7 Artificial Intelligence Applications to Speech Recognition (RIT): Vol. 8 The RIT NAIC

  9. Concepts for Army Use of Robotic-Artificial Intelligence in the 21st Century,

    Science.gov (United States)

    1982-06-01

    considering robotic- artificial intelligence applications , consideration was not constrained only to that concept’s environment. Other future force...robotic- artificial intelligence applications which meet one or more of five criteria: o Cost effectiveness of the application surpasses traditional way of...considers potential robotic- artificial intelligence applications within the functional areas of the Airland Battle 2000 concept. These applications go

  10. Artificial Intelligence: Is the Future Now for A.I.?

    Science.gov (United States)

    Ramaswami, Rama

    2009-01-01

    In education, artificial intelligence (AI) has not made much headway. In the one area where it would seem poised to lend the most benefit--assessment--the reliance on standardized tests, intensified by the demands of the No Child Left Behind Act of 2001, which holds schools accountable for whether students pass statewide exams, precludes its use.…

  11. Evolution and Revolution in Artificial Intelligence in Education

    Science.gov (United States)

    Roll, Ido; Wylie, Ruth

    2016-01-01

    The field of Artificial Intelligence in Education (AIED) has undergone significant developments over the last twenty-five years. As we reflect on our past and shape our future, we ask two main questions: What are our major strengths? And, what new opportunities lay on the horizon? We analyse 47 papers from three years in the history of the…

  12. An Artificial Intelligence-Based Distance Education System: Artimat

    Science.gov (United States)

    Nabiyev, Vasif; Karal, Hasan; Arslan, Selahattin; Erumit, Ali Kursat; Cebi, Ayca

    2013-01-01

    The purpose of this study is to evaluate the artificial intelligence-based distance education system called ARTIMAT, which has been prepared in order to improve mathematical problem solving skills of the students, in terms of conceptual proficiency and ease of use with the opinions of teachers and students. The implementation has been performed…

  13. Express: the reliability of complex systems and artificial intelligence techniques

    International Nuclear Information System (INIS)

    Ancelin, C.; Le, P.; Saint-Quentin, S. de

    1987-01-01

    The probabilistic safety study for the Paluel nuclear power station, commissioned by EDF in 1986, involved development of data processing methods and equipment which was to be given an entirely new impetus by the use of artificial intelligence techniques. The authors describe the salient features of the approach which was adopted and the lessons learnt from the way it was applied in practice [fr

  14. Teaching Artificial Intelligence and Expert Systems: Concepts in Library Curricula.

    Science.gov (United States)

    Kranch, Douglas A.

    1992-01-01

    Survey of institutions offering a bachelor's or higher degree in library science showed that the higher the level of the program, the more likely that artificial intelligence/expert systems (AI/ES) courses would be offered. Study concludes that all master's and doctoral level programs should include AI/ES units, and that greater emphasis should be…

  15. Artificial Intelligence Applications in Special Education: How Feasible? Final Report.

    Science.gov (United States)

    Hofmeister, Alan M.; Ferrara, Joseph M.

    The research project investigated whether expert system tools have become sophisticated enough to be applied efficiently to problems in special education. (Expert systems are a development of artificial intelligence that combines the computer's capacity for storing specialized knowledge with a general set of rules intended to replicate the…

  16. VAR control in distribution systems by using artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Golkar, M.A. [Curtin Univ. of Technology, Sarawak (Malaysia). School of Engineering and Science

    2005-07-01

    This paper reviewed artificial intelligence techniques used in VAR control systems. Reactive power controls in distribution systems were also reviewed. While artificial intelligence methods are widely used in power control systems, the techniques require extensive human knowledge bases and experiences in order to operate correctly. Expert systems use knowledge and interface procedures to solve problems that often require human expertise. Expert systems often cause knowledge bottlenecks as they are unable to learn or adopt to new situations. While neural networks possess learning ability, they are computationally expensive. However, test results in recent neural network studies have demonstrated that they work well in a variety of loading conditions. Fuzzy logic techniques are used to accurately represent the operational constraints of power systems. Fuzzy logic has an advantage over other artificial intelligence techniques as it is able to remedy uncertainties in data. Evolutionary computing algorithms use probabilistic transition rules which can search complicated data to determine optimal constraints and parameters. Over 95 per cent of all papers published on power systems use genetic algorithms. It was concluded that hybrid systems using various artificial intelligence techniques are now being used by researchers. 69 refs.

  17. A Course in Artificial Intelligence in Process Engineering.

    Science.gov (United States)

    Venkatasubramanian, V.

    1986-01-01

    Describes a course on artificial intelligence (AI) in process engineering taught at Columbia University to chemical engineering students, using an AI methodology known as Knowledge-Based Expert Systems (KBES). Provides a description of the course, the lecture topics, and a synopsis of some of the student projects. (TW)

  18. Ethical Implications of an Experiment in Artificial Intelligence.

    Science.gov (United States)

    Levinson, Stephen E.

    2003-01-01

    Revisits the classic debate on whether there can be an artificial creation that behaves and uses language with intelligence and agency. Argues that many moral and spiritual objections to this notion are not grounded either ethically or empirically. (Author/VWL)

  19. Research Priorities for Robust and Beneficial Artificial Intelligence

    OpenAIRE

    Russell, Stuart; Dewey, Daniel; Tegmark, Max

    2015-01-01

    Success in the quest for artificial intelligence has the potential to bring unprecedented benefits to humanity, and it is therefore worthwhile to investigate how to maximize these benefits while avoiding potential pitfalls. This article gives numerous examples (which should by no means be construed as an exhaustive list) of such worthwhile research aimed at ensuring that AI remains robust and beneficial.

  20. Magical Stories: Blending Virtual Reality and Artificial Intelligence.

    Science.gov (United States)

    McLellan, Hilary

    Artificial intelligence (AI) techniques and virtual reality (VR) make possible powerful interactive stories, and this paper focuses on examples of virtual characters in three dimensional (3-D) worlds. Waldern, a virtual reality game designer, has theorized about and implemented software design of virtual teammates and opponents that incorporate AI…

  1. The 1992 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Rash, James L. (Editor)

    1992-01-01

    The purpose of this conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers fall into the following areas: planning and scheduling, control, fault monitoring/diagnosis and recovery, information management, tools, neural networks, and miscellaneous applications.

  2. Second Conference on Artificial Intelligence for Space Applications

    Science.gov (United States)

    Dollman, Thomas (Compiler)

    1988-01-01

    The proceedings of the conference are presented. This second conference on Artificial Intelligence for Space Applications brings together a diversity of scientific and engineering work and is intended to provide an opportunity for those who employ AI methods in space applications to identify common goals and to discuss issues of general interest in the AI community.

  3. Artificial Intelligence in Business: Technocrat Jargon or Quantum Leap?

    Science.gov (United States)

    Burford, Anna M.; Wilson, Harold O.

    This paper addresses the characteristics and applications of artificial intelligence (AI) as a subsection of computer science, and briefly describes the most common types of AI programs: expert systems, natural language, and neural networks. Following a brief presentation of the historical background, the discussion turns to an explanation of how…

  4. Artificial Intelligence in ADA: Pattern-Directed Processing. Final Report.

    Science.gov (United States)

    Reeker, Larry H.; And Others

    To demonstrate to computer programmers that the programming language Ada provides superior facilities for use in artificial intelligence applications, the three papers included in this report investigate the capabilities that exist within Ada for "pattern-directed" programming. The first paper (Larry H. Reeker, Tulane University) is…

  5. Body, thought, being-human and artificial intelligence: Merleau ...

    African Journals Online (AJOL)

    The focus then shifts to Merleau-Ponty in order to demonstrate the remarkable extent to which his understanding of human embodiment and related issues such as perception and creativity, paved the way for the work of, among others, Lyotard, and anticipated the critique of artificial intelligence on the part of the latter.

  6. Social Studies and Emerging Paradigms: Artificial Intelligence and Consciousness Education.

    Science.gov (United States)

    Braun, Joseph A., Jr.

    1987-01-01

    Asks three questions: (1) Are machines capable of thinking as people do? (2) How is the thinking of computers similar and different from human thinking? and (3) What exactly is thinking? Examines research in artificial intelligence. Describes the theory and research of consciousness education and discusses an emerging paradigm for human thinking…

  7. John McCarthy–Father of Artificial Intelligence

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 3. John McCarthy – Father of Artificial Intelligence. V Rajaraman. General Article Volume 19 Issue 3 March 2014 pp 198-207. Fulltext. Click here to view fulltext PDF. Permanent link: http://www.ias.ac.in/article/fulltext/reso/019/03/0198-0207 ...

  8. Reflections on the relationship between artificial intelligence and operations research

    Science.gov (United States)

    Fox, Mark S.

    1989-01-01

    Historically, part of Artificial Intelligence's (AI's) roots lie in Operations Research (OR). How AI has extended the problem solving paradigm developed in OR is explored. In particular, by examining how scheduling problems are solved using OR and AI, it is demonstrated that AI extends OR's model of problem solving through the opportunistic use of knowledge, problem reformulation and learning.

  9. Some Notes About Artificial Intelligence as New Mathematical Tool

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-04-01

    Full Text Available Mathematics is a mere instance of First-Order Predicate Calculus. Therefore it belongs to applied Monotonic Logic. So, we found the limitations of classical logic reasoning and the clear advantages of Fuzzy Logic and many other new interesting tools. We present here some of the more usefulness tools of this new field of Mathematics so-called Artificial Intelligence.

  10. The Third International Conference on Artificial Intelligence and Education

    OpenAIRE

    Liffick, Blaise W.

    1987-01-01

    The Third International Conference on Artificial Intelligence and Education attracted over 400 participants from all over the world who gathered to present projects reports, exchange views, discuss common problems, and establish contacts concerning AI and education. This article presents a synopsis of the major presentations and an overview of the conference as a whole.

  11. The Seeds of Artificial Intelligence. SUMEX-AIM.

    Science.gov (United States)

    Research Resources Information Center, Rockville, MD.

    Written to provide an understanding of the broad base of information on which the artificial intelligence (AI) branch of computer science rests, this publication presents a general view of AI, the concepts from which it evolved, its current abilities, and its promise for research. The focus is on a community of projects that use the SUMEX-AIM…

  12. RICIS research review of artificial intelligence and expert systems

    Science.gov (United States)

    Feagin, Terry

    1988-01-01

    The paper summarizes the research accomplishments of the past year for the artificial intelligence and expert systems areas. Most projects have been underway for only a short time; however, overall progress within the areas has been steady and worthwhile. Several projects have already attained their major objectives.

  13. An Artificial Intelligence Course for Liberal Arts Students.

    Science.gov (United States)

    Skala, Helen

    1988-01-01

    Outlines a course in artificial intelligence for liberal arts students that has no programing prerequisites. Topics and projects included in the course are described, including problem solving; natural language; expert systems; image understanding, or character recognition; and robotic systems. (28 references) (Author/LRW)

  14. Application of artificial intelligence to risk analysis for forested ecosystems

    Science.gov (United States)

    Daniel L. Schmoldt

    2001-01-01

    Forest ecosystems are subject to a variety of natural and anthropogenic disturbances that extract a penalty from human population values. Such value losses (undesirable effects) combined with their likelihoods of occurrence constitute risk. Assessment or prediction of risk for various events is an important aid to forest management. Artificial intelligence (AI)...

  15. Artificial intelligence applications in the intensive care unit.

    Science.gov (United States)

    Hanson, C W; Marshall, B E

    2001-02-01

    To review the history and current applications of artificial intelligence in the intensive care unit. The MEDLINE database, bibliographies of selected articles, and current texts on the subject. The studies that were selected for review used artificial intelligence tools for a variety of intensive care applications, including direct patient care and retrospective database analysis. All literature relevant to the topic was reviewed. Although some of the earliest artificial intelligence (AI) applications were medically oriented, AI has not been widely accepted in medicine. Despite this, patient demographic, clinical, and billing data are increasingly available in an electronic format and therefore susceptible to analysis by intelligent software. Individual AI tools are specifically suited to different tasks, such as waveform analysis or device control. The intensive care environment is particularly suited to the implementation of AI tools because of the wealth of available data and the inherent opportunities for increased efficiency in inpatient care. A variety of new AI tools have become available in recent years that can function as intelligent assistants to clinicians, constantly monitoring electronic data streams for important trends, or adjusting the settings of bedside devices. The integration of these tools into the intensive care unit can be expected to reduce costs and improve patient outcomes.

  16. Artificial intelligent e-learning architecture

    Science.gov (United States)

    Alharbi, Mafawez; Jemmali, Mahdi

    2017-03-01

    Many institutions and university has forced to use e learning, due to its ability to provide additional and flexible solutions for students and researchers. E-learning In the last decade have transported about the extreme changes in the distribution of education allowing learners to access multimedia course material at any time, from anywhere to suit their specific needs. In the form of e learning, instructors and learners live in different places and they do not engage in a classroom environment, but within virtual universe. Many researches have defined e learning based on their objectives. Therefore, there are small number of e-learning architecture have proposed in the literature. However, the proposed architecture has lack of embedding intelligent system in the architecture of e learning. This research argues that unexplored potential remains, as there is scope for e learning to be intelligent system. This research proposes e-learning architecture that incorporates intelligent system. There are intelligence components, which built into the architecture.

  17. The Emperor of Strong AI Has No Clothes: Limits to Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Adriana Braga

    2017-11-01

    Full Text Available Making use of the techniques of media ecology we argue that the premise of the technological Singularity based on the notion computers will one day be smarter that their human creators is false. We also analyze the comments of other critics of the Singularity, as well supporters of this notion. The notion of intelligence that advocates of the technological singularity promote does not take into account the full dimension of human intelligence. They treat artificial intelligence as a figure without a ground. Human intelligence as we will show is not based solely on logical operations and computation, but also includes a long list of other characteristics that are unique to humans, which is the ground that supporters of the Singularity ignore. The list includes curiosity, imagination, intuition, emotions, passion, desires, pleasure, aesthetics, joy, purpose, objectives, goals, telos, values, morality, experience, wisdom, judgment, and even humor.

  18. Artificial intelligence - New tools for aerospace project managers

    Science.gov (United States)

    Moja, D. C.

    1985-01-01

    Artificial Intelligence (AI) is currently being used for business-oriented, money-making applications, such as medical diagnosis, computer system configuration, and geological exploration. The present paper has the objective to assess new AI tools and techniques which will be available to assist aerospace managers in the accomplishment of their tasks. A study conducted by Brown and Cheeseman (1983) indicates that AI will be employed in all traditional management areas, taking into account goal setting, decision making, policy formulation, evaluation, planning, budgeting, auditing, personnel management, training, legal affairs, and procurement. Artificial intelligence/expert systems are discussed, giving attention to the three primary areas concerned with intelligent robots, natural language interfaces, and expert systems. Aspects of information retrieval are also considered along with the decision support system, and expert systems for project planning and scheduling.

  19. Towards an unanimous international regulatory body for responsible use of Artificial Intelligence [UIRB-AI

    OpenAIRE

    Chidambaram, Rajesh

    2017-01-01

    Artificial Intelligence (AI), is once again in the phase of drastic advancements. Unarguably, the technology itself can revolutionize the way we live our everyday life. But the exponential growth of technology poses a daunting task for policy researchers and law makers in making amendments to the existing norms. In addition, not everyone in the society is studying the potential socio-economic intricacies and cultural drifts that AI can bring about. It is prudence to reflect from our historica...

  20. The Bright, Artificial Intelligence-Augmented Future of Neuroimaging Reading.

    Science.gov (United States)

    Hainc, Nicolin; Federau, Christian; Stieltjes, Bram; Blatow, Maria; Bink, Andrea; Stippich, Christoph

    2017-01-01

    Radiologists are among the first physicians to be directly affected by advances in computer technology. Computers are already capable of analyzing medical imaging data, and with decades worth of digital information available for training, will an artificial intelligence (AI) one day signal the end of the human radiologist? With the ever increasing work load combined with the looming doctor shortage, radiologists will be pushed far beyond their current estimated 3 s allotted time-of-analysis per image; an AI with super-human capabilities might seem like a logical replacement. We feel, however, that AI will lead to an augmentation rather than a replacement of the radiologist. The AI will be relied upon to handle the tedious, time-consuming tasks of detecting and segmenting outliers while possibly generating new, unanticipated results that can then be used as sources of medical discovery. This will affect not only radiologists but all physicians and also researchers dealing with medical imaging. Therefore, we must embrace future technology and collaborate interdisciplinary to spearhead the next revolution in medicine.

  1. The Bright, Artificial Intelligence-Augmented Future of Neuroimaging Reading

    Directory of Open Access Journals (Sweden)

    Nicolin Hainc

    2017-09-01

    Full Text Available Radiologists are among the first physicians to be directly affected by advances in computer technology. Computers are already capable of analyzing medical imaging data, and with decades worth of digital information available for training, will an artificial intelligence (AI one day signal the end of the human radiologist? With the ever increasing work load combined with the looming doctor shortage, radiologists will be pushed far beyond their current estimated 3 s allotted time-of-analysis per image; an AI with super-human capabilities might seem like a logical replacement. We feel, however, that AI will lead to an augmentation rather than a replacement of the radiologist. The AI will be relied upon to handle the tedious, time-consuming tasks of detecting and segmenting outliers while possibly generating new, unanticipated results that can then be used as sources of medical discovery. This will affect not only radiologists but all physicians and also researchers dealing with medical imaging. Therefore, we must embrace future technology and collaborate interdisciplinary to spearhead the next revolution in medicine.

  2. Forecasting daily lake levels using artificial intelligence approaches

    Science.gov (United States)

    Kisi, Ozgur; Shiri, Jalal; Nikoofar, Bagher

    2012-04-01

    Accurate prediction of lake-level variations is important for planning, design, construction, and operation of lakeshore structures and also in the management of freshwater lakes for water supply purposes. In the present paper, three artificial intelligence approaches, namely artificial neural networks (ANNs), adaptive-neuro-fuzzy inference system (ANFIS), and gene expression programming (GEP), were applied to forecast daily lake-level variations up to 3-day ahead time intervals. The measurements at the Lake Iznik in Western Turkey, for the period of January 1961-December 1982, were used for training, testing, and validating the employed models. The results obtained by the GEP approach indicated that it performs better than ANFIS and ANNs in predicting lake-level variations. A comparison was also made between these artificial intelligence approaches and convenient autoregressive moving average (ARMA) models, which demonstrated the superiority of GEP, ANFIS, and ANN models over ARMA models.

  3. Aerobic Bioprocess Control Using Artificial Intelligence Techniques

    OpenAIRE

    M. Caramihai; Irina Severin

    2017-01-01

    This paper deals with the design of an intelligent control structure for a bioprocess of Hansenula polymorpha yeast cultivation. The objective of the process control is to produce biomass in a desired physiological state. The work demonstrates that the designed Hybrid Control Techniques (HCT) are able to recognize specific evolution bioprocess trajectories using neural networks trained specifically for this purpose, in order to estimate the model parameters and to adjust the overall bioproces...

  4. Methodology Investigation of AI(Artificial Intelligence) Test Officer Support Tool. Volume 1

    Science.gov (United States)

    1989-03-01

    American Association for Artificial inteligence A! ............. Artificial inteliigence AMC ............ Unt:ed States Army Maeriel Comand ASL...block number) FIELD GROUP SUB-GROUP Artificial Intelligence, Expert Systems Automated Aids to Testing 9. ABSTRACT (Continue on reverse if necessary and...identify by block number) This report covers the application of Artificial Intelligence-Techniques to the problem of creating automated tools to

  5. Artificial Intelligence Applied to the Command, Control, Communications, and Intelligence of the U.S. Central Command.

    Science.gov (United States)

    1983-06-06

    these components will be presented. 4.17 °°,. CHAPTER III FOOTNOTES 1. Arron Barr and Edward A. Feigenbaum, eds., Te Handbook gf Artificial Inteligence ol...RD-R137 205 ARTIFICIAL INTELLIGENCE APPLIED TO THE COMIMAND CONTROL i/i COMMUNICATIONS RND..(U) ARMY WAR COLL CARLISLE BARRACKS U PA J N ENVART 06...appropriate mlitary servic or *swesmment aency. ARTIFICIAL INTELLIGENCE APPLIED TO THE COMMAND, CONTROL, COMMUNICATIONS, AND INTELLIGENCE OF THE U.S. CENTRAL

  6. Teaching artificial intelligence to read electropherograms.

    Science.gov (United States)

    Taylor, Duncan; Powers, David

    2016-11-01

    Electropherograms are produced in great numbers in forensic DNA laboratories as part of everyday criminal casework. Before the results of these electropherograms can be used they must be scrutinised by analysts to determine what the identified data tells us about the underlying DNA sequences and what is purely an artefact of the DNA profiling process. A technique that lends itself well to such a task of classification in the face of vast amounts of data is the use of artificial neural networks. These networks, inspired by the workings of the human brain, have been increasingly successful in analysing large datasets, performing medical diagnoses, identifying handwriting, playing games, or recognising images. In this work we demonstrate the use of an artificial neural network which we train to 'read' electropherograms and show that it can generalise to unseen profiles. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  7. Artificial organic networks artificial intelligence based on carbon networks

    CERN Document Server

    Ponce-Espinosa, Hiram; Molina, Arturo

    2014-01-01

    This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: ·        approximation; ·        inference; ·        clustering; ·        control; ·        class...

  8. Intelligent process control operator aid -- An artificial intelligence approach

    International Nuclear Information System (INIS)

    Sharma, D.D.; Miller, D.D.; Hajek, B.; Chandrasekaran, B.

    1986-01-01

    This paper describes an approach for designing intelligent process and power plant control operator aids. It is argued that one of the key aspects of an intelligent operator aid is the capability for dynamic procedure synthesis with incomplete definition of initial state, unknown goal states, and the dynamic world situation. The dynamic world state is used to determine the goal, select appropriate plan steps from prespecified procedures to achieve the goal, control the execution of the synthesized plan, and provide for dynamic recovery from failure often using a goal hierarchy. The dynamic synthesis of a plan requires integration of various problems solving capabilities such as plan generation, plan synthesis, plan modification, and failure recovery from a plan. The programming language for implementing the DPS framework provides a convenient tool for developing applications. An application of the DPS approach to a Nuclear Power Plant emergency procedure synthesis is also described. Initial test results indicate that the approach is successful in dynamically synthesizing the procedures. The authors realize that the DPS framework is not a solution for all control tasks. However, many existing process and plant control problems satisfy the requirements discussed in the paper and should be able to benefit from the framework described

  9. Space Environment Modelling with the Use of Artificial Intelligence Methods

    Science.gov (United States)

    Lundstedt, H.; Wintoft, P.; Wu, J.-G.; Gleisner, H.; Dovheden, V.

    1996-12-01

    Space based technological systems are affected by the space weather in many ways. Several severe failures of satellites have been reported at times of space storms. Our society also increasingly depends on satellites for communication, navigation, exploration, and research. Predictions of the conditions in the satellite environment have therefore become very important. We will here present predictions made with the use of artificial intelligence (AI) techniques, such as artificial neural networks (ANN) and hybrids of AT methods. We are developing a space weather model based on intelligence hybrid systems (IHS). The model consists of different forecast modules, each module predicts the space weather on a specific time-scale. The time-scales range from minutes to months with the fundamental time-scale of 1-5 minutes, 1-3 hours, 1-3 days, and 27 days. Solar and solar wind data are used as input data. From solar magnetic field measurements, either made on the ground at Wilcox Solar Observatory (WSO) at Stanford, or made from space by the satellite SOHO, solar wind parameters can be predicted and modelled with ANN and MHD models. Magnetograms from WSO are available on a daily basis. However, from SOHO magnetograms will be available every 90 minutes. SOHO magnetograms as input to ANNs will therefore make it possible to even predict solar transient events. Geomagnetic storm activity can today be predicted with very high accuracy by means of ANN methods using solar wind input data. However, at present real-time solar wind data are only available during part of the day from the satellite WIND. With the launch of ACE in 1997, solar wind data will on the other hand be available during 24 hours per day. The conditions of the satellite environment are not only disturbed at times of geomagnetic storms but also at times of intense solar radiation and highly energetic particles. These events are associated with increased solar activity. Predictions of these events are therefore

  10. Philosophy and Theory of Artificial Intelligence

    CERN Document Server

    2013-01-01

    Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we s...

  11. Learning comunication strategies for distributed artificial intelligence

    Science.gov (United States)

    Kinney, Michael; Tsatsoulis, Costas

    1992-08-01

    We present a methodology that allows collections of intelligent system to automatically learn communication strategies, so that they can exchange information and coordinate their problem solving activity. In our methodology communication between agents is determined by the agents themselves, which consider the progress of their individual problem solving activities compared to the communication needs of their surrounding agents. Through learning, communication lines between agents might be established or disconnected, communication frequencies modified, and the system can also react to dynamic changes in the environment that might force agents to cease to exist or to be added. We have established dynamic, quantitative measures of the usefulness of a fact, the cost of a fact, the work load of an agent, and the selfishness of an agent (a measure indicating an agent's preference between transmitting information versus performing individual problem solving), and use these values to adapt the communication between intelligent agents. In this paper we present the theoretical foundations of our work together with experimental results and performance statistics of networks of agents involved in cooperative problem solving activities.

  12. An application of artificial intelligence theory to reconfigurable flight control

    Science.gov (United States)

    Handelman, David A.

    1987-01-01

    Artificial intelligence techniques were used along with statistical hpyothesis testing and modern control theory, to help the pilot cope with the issues of information, knowledge, and capability in the event of a failure. An intelligent flight control system is being developed which utilizes knowledge of cause and effect relationships between all aircraft components. It will screen the information available to the pilots, supplement his knowledge, and most importantly, utilize the remaining flight capability of the aircraft following a failure. The list of failure types the control system will accommodate includes sensor failures, actuator failures, and structural failures.

  13. Artificial intelligence: the future in nuclear plant maintenance

    International Nuclear Information System (INIS)

    Norgate, G.

    1984-01-01

    The role of robotics and remote handling equipment in future nuclear power plant maintenance activities is discussed in the context of artificial intelligence applications. Special requirements manipulators, control systems, and man-machine interfaces for nuclear applications are noted. Tasks might include inspection with cameras, eddy current probes, and leak detectors; the collection of material samples; radiation monitoring; and the disassembly, repair and reassembly of a variety of system components. A robot with vision and force sensing and an intelligent control system that can access a knowledge base is schematically described. Recent advances in image interpretation systems are also discussed

  14. Anti-fatigue optimization design by artificial intelligence strategy

    Science.gov (United States)

    Xing, Bin; Yang, Qingxiong

    1991-11-01

    The artificial intelligence strategy is applied to the optimum antifatigue design of structural details. A set of approaches quite different from the traditional mathematical programming method is put forward. By setting up a state space of discrete design variables to which the intelligence search strategy is applied, the integralization of discrete variables can be avoided. An example of optimum antifatigue design for a typical structure detail of aircraft is worked out using the present method. Comparison between the results obtained by this method and those obtained by the mathematical programming method shows that the present method is better. Verification experiments conducted by the author show that the method proposed is feasible and reliable.

  15. Integrating artificial and human intelligence into tablet production process.

    Science.gov (United States)

    Gams, Matjaž; Horvat, Matej; Ožek, Matej; Luštrek, Mitja; Gradišek, Anton

    2014-12-01

    We developed a new machine learning-based method in order to facilitate the manufacturing processes of pharmaceutical products, such as tablets, in accordance with the Process Analytical Technology (PAT) and Quality by Design (QbD) initiatives. Our approach combines the data, available from prior production runs, with machine learning algorithms that are assisted by a human operator with expert knowledge of the production process. The process parameters encompass those that relate to the attributes of the precursor raw materials and those that relate to the manufacturing process itself. During manufacturing, our method allows production operator to inspect the impacts of various settings of process parameters within their proven acceptable range with the purpose of choosing the most promising values in advance of the actual batch manufacture. The interaction between the human operator and the artificial intelligence system provides improved performance and quality. We successfully implemented the method on data provided by a pharmaceutical company for a particular product, a tablet, under development. We tested the accuracy of the method in comparison with some other machine learning approaches. The method is especially suitable for analyzing manufacturing processes characterized by a limited amount of data.

  16. Artificial intelligence applications to design validation and sneak function analysis

    International Nuclear Information System (INIS)

    Stratton, R.C.

    1985-01-01

    An objective of the US space reactor program is to design systems with high reliability and safety of control over long operating lifetimes. Argonne National Laboratory (ANL) is a participant in the National Man-Machine Integration (MMI) program for Liquid Metal Fast Breeder Reactors (LMFBR). A purpose of this program is to promote the development of concepts and technologies that enhance the operational safety and reliability of fast-breeder reactors. Much of the work is directly applicable to the space reactor program. This paper reports on one of the MMI projects being developed by ANL. The project reported pertains to an automated system that demonstrates the use of artificial intelligence (AI) for design validation (DA) and sneak function analysis (SFA). The AI system models the design specification and the physical design of the cooling process assigned to the Argon Cooling System (ACS) at Experimental Breeder Reactor II (EBR-II). The models are developed using heuristic knowledge and natural laws. 13 refs

  17. Operation optimization of distributed generation using artificial intelligent techniques

    Directory of Open Access Journals (Sweden)

    Mahmoud H. Elkazaz

    2016-06-01

    Full Text Available Future smart grids will require an observable, controllable and flexible network architecture for reliable and efficient energy delivery. The use of artificial intelligence and advanced communication technologies is essential in building a fully automated system. This paper introduces a new technique for online optimal operation of distributed generation (DG resources, i.e. a hybrid fuel cell (FC and photovoltaic (PV system for residential applications. The proposed technique aims to minimize the total daily operating cost of a group of residential homes by managing the operation of embedded DG units remotely from a control centre. The target is formed as an objective function that is solved using genetic algorithm (GA optimization technique. The optimal settings of the DG units obtained from the optimization process are sent to each DG unit through a fully automated system. The results show that the proposed technique succeeded in defining the optimal operating points of the DGs that affect directly the total operating cost of the entire system.

  18. Providing Language Instructor with Artificial Intelligence Assistant

    Directory of Open Access Journals (Sweden)

    K. Pietroszek

    2007-12-01

    Full Text Available Abstract—This paper presents the preliminary results ofdeveloping HAL for CALL, an artificial intelligenceassistant for language instructor. The assistant consists of achatbot, an avatar (a three-dimensional visualization of thechatbot, a voice (text-to-speech engine interface andinterfaces to external sources of language knowledge. Sometechniques used in adapting freely available chatbot for theneed of a language learning system are presented.Integration of HAL with Second Life virtual world isproposed. We will discuss technical challenges and possiblefuture work directions.

  19. ARTIFICIAL INTELLIGENCE EFFECTIVENESS IN JOB SHOP ENVIRONMENTS

    Directory of Open Access Journals (Sweden)

    OMAR CASTRILLON

    2011-01-01

    Full Text Available El objetivo del presente trabajo, es definir una nueva metodología la cual permita comparar la efectividad de algunas de las principales técnicas de inteligencia artificial (aleatorias, búsqueda tabú, minería de datos, algoritmos evolutivos. Esta metodología es aplicada en los procesos de secuenciación de la producción en ambientes job shop, en un problema con N pedidos y M máquinas, donde cada uno de los pedidos debe pasar por todas las máquinas sin importar el orden. Estas técnicas son medidas en las variables tiempo total de proceso, tiempo total muerto y porcentaje de utilización de las máquinas. Inicialmente, una revisión teórica fue realizada, esta muestra la utilidad y efectividad de la inteligencia artificial en los procesos de secuenciación de la producción. Posteriormente y con base en la experimentación planteada, los resultados obtenidos, muestran que estas técnicas presentan una efectividad superior al 95%, con un intervalo de confiabilidad del 99.5% medido en las variables objeto de estudio.

  20. Artificial Intelligence based technique for BTS placement

    International Nuclear Information System (INIS)

    Alenoghena, C O; Emagbetere, J O; 1 Minna (Nigeria))" data-affiliation=" (Department of Telecommunications Engineering, Federal University of Techn.1 Minna (Nigeria))" >Aibinu, A M

    2013-01-01

    The increase of the base transceiver station (BTS) in most urban areas can be traced to the drive by network providers to meet demand for coverage and capacity. In traditional network planning, the final decision of BTS placement is taken by a team of radio planners, this decision is not fool proof against regulatory requirements. In this paper, an intelligent based algorithm for optimal BTS site placement has been proposed. The proposed technique takes into consideration neighbour and regulation considerations objectively while determining cell site. The application will lead to a quantitatively unbiased evaluated decision making process in BTS placement. An experimental data of a 2km by 3km territory was simulated for testing the new algorithm, results obtained show a 100% performance of the neighbour constrained algorithm in BTS placement optimization. Results on the application of GA with neighbourhood constraint indicate that the choices of location can be unbiased and optimization of facility placement for network design can be carried out