WorldWideScience

Sample records for intelligence ai methods

  1. Artificial Intelligence Study (AIS).

    Science.gov (United States)

    1987-02-01

    ARTIFICIAL INTELLIGNECE HARDWARE ....... 2-50 AI Architecture ................................... 2-49 AI Hardware ....................................... 2...ftf1 829 ARTIFICIAL INTELLIGENCE STUDY (RIS)(U) MAY CONCEPTS 1/3 A~NLYSIS AGENCY BETHESA RD R B NOJESKI FED 6? CM-RP-97-1 NCASIFIED /01/6 M |K 1.0...p/ - - ., e -- CAA- RP- 87-1 SAOFŔ)11 I ARTIFICIAL INTELLIGENCE STUDY (AIS) tNo DTICFEBRUARY 1987 LECT 00 I PREPARED BY RESEARCH AND ANALYSIS

  2. Application of artificial intelligence (AI) methods for designing and analysis of reconfigurable cellular manufacturing system (RCMS)

    CSIR Research Space (South Africa)

    Xing, B

    2009-12-01

    Full Text Available This work focuses on the design and control of a novel hybrid manufacturing system: Reconfigurable Cellular Manufacturing System (RCMS) by using Artificial Intelligence (AI) approach. It is hybrid as it combines the advantages of Cellular...

  3. Organisational intelligence and distributed AI

    OpenAIRE

    Kirn, Stefan

    1995-01-01

    The analysis of this chapter starts from organisational theory, and from this it draws conclusions for the design, and possible organisational applications, of Distributed AI systems. We first review how the concept of organisations has emerged from non-organised black-box entities to so-called computerised organisations. Within this context, organisational researchers have started to redesign their models of intelligent organisations with respect to the availability of advanced computing tec...

  4. 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.

  5. 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...

  6. Artificial Intelligence Safety and Cybersecurity: a Timeline of AI Failures

    OpenAIRE

    Yampolskiy, Roman V.; Spellchecker, M. S.

    2016-01-01

    In this work, we present and analyze reported failures of artificially intelligent systems and extrapolate our analysis to future AIs. We suggest that both the frequency and the seriousness of future AI failures will steadily increase. AI Safety can be improved based on ideas developed by cybersecurity experts. For narrow AIs safety failures are at the same, moderate, level of criticality as in cybersecurity, however for general AI, failures have a fundamentally different impact. A single fai...

  7. 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.

  8. [Artificial intelligence] AI for protection systems

    Energy Technology Data Exchange (ETDEWEB)

    Aggarwal, R.; Johns, A.

    1997-12-31

    The reliable operation of large power systems with small stability margins is highly dependent on control systems and protection devices. Progress in the field of microprocessor systems and demanding requirements in respect of the performance of protective relays are the reasons for digital device applications to power system protection. The superiority of numeric protection over its analogue alternatives is attributed to such factors as accurate extraction of the fundamental voltage and current components through filtering, functional benefits resulting from multi-processor design and extensive self-monitoring, etc. However, all these reasons have not led to a major impact on speed, sensitivity and selectivity of primary protective relays, and the gains are only marginal; this is so because conventional digital relays still rely on deterministic signal models and a heuristic approach for decision making, so that only a fraction of the information contained within voltage and current signals as well as knowledge about the plant to be protected is used. The performance of digital relays may be substantially improved if the decision making is based on elements of artificial intelligence (AI). (Author)

  9. 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...

  10. Artificial Intelligence (AI) Based Tactical Guidance for Fighter Aircraft

    Science.gov (United States)

    McManus, John W.; Goodrich, Kenneth H.

    1990-01-01

    A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS), a second generation TDG, is presented. The Knowledge-Based Systems used by CLAWS to aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of CLAWS versus a baseline TDG developed in FORTRAN to run in real-time in the Langley Differential Maneuvering Simulator (DMS), are presented. To date, these test results have shown significant performance gains with respect to the TDG baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify and maintain than the baseline FORTRAN TDG programs. Alternate computing environments and programming approaches, including the use of parallel algorithms and heterogeneous computer networks are discussed, and the design and performance of a prototype concurrent TDG system are presented.

  11. Artificial Intelligence (AI) Studies in Water Resources

    OpenAIRE

    Ay, Murat; Özyıldırım, Serhat

    2018-01-01

    Artificial intelligence has been extensively used in many areas such as computer science,robotics, engineering, medicine, translation, economics, business, and psychology. Variousstudies in the literature show that the artificial intelligence in modeling approaches give closeresults to the real data for solution of linear, non-linear, and other systems. In this study, wereviewed the current state-of-the-art and progress on the modelling of artificial intelligence forwater variables: rainfall-...

  12. Human-Assisted AI: an Intelligence Augmentation Approach

    OpenAIRE

    Alicea, Bradly

    2018-01-01

    As a flavor of Human-Computer Interaction (HCI), Human-Assisted AI can serve to both augment both human performance and artificial systems. This talk will feature a discussion of Human-assisted AI as an instance of Intelligence Augmentation (IA). We will discuss instances of weak and strong IA, in addition to contemporary examples of and paths forward for such systems. In the variety of models presented, data plays a critical role in the structure of interactions between human and artificial ...

  13. 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.

  14. 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.…

  15. Application of AI methods to aircraft guidance and control

    Science.gov (United States)

    Hueschen, Richard M.; Mcmanus, John W.

    1988-01-01

    A research program for integrating artificial intelligence (AI) techniques with tools and methods used for aircraft flight control system design, development, and implementation is discussed. The application of the AI methods for the development and implementation of the logic software which operates with the control mode panel (CMP) of an aircraft is presented. The CMP is the pilot control panel for the automatic flight control system of a commercial-type research aircraft of Langley Research Center's Advanced Transport Operating Systems (ATOPS) program. A mouse-driven color-display emulation of the CMP, which was developed with AI methods and used to test the AI software logic implementation, is discussed. The operation of the CMP was enhanced with the addition of a display which was quickly developed with AI methods. The display advises the pilot of conditions not satisfied when a mode does not arm or engage. The implementation of the CMP software logic has shown that the time required to develop, implement, and modify software systems can be significantly reduced with the use of the AI methods.

  16. Quality measures and assurance for AI (Artificial Intelligence) software

    Science.gov (United States)

    Rushby, John

    1988-01-01

    This report is concerned with the application of software quality and evaluation measures to AI software and, more broadly, with the question of quality assurance for AI software. Considered are not only the metrics that attempt to measure some aspect of software quality, but also the methodologies and techniques (such as systematic testing) that attempt to improve some dimension of quality, without necessarily quantifying the extent of the improvement. The report is divided into three parts Part 1 reviews existing software quality measures, i.e., those that have been developed for, and applied to, conventional software. Part 2 considers the characteristics of AI software, the applicability and potential utility of measures and techniques identified in the first part, and reviews those few methods developed specifically for AI software. Part 3 presents an assessment and recommendations for the further exploration of this important area.

  17. 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...

  18. Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology.

    Science.gov (United States)

    VoPham, Trang; Hart, Jaime E; Laden, Francine; Chiang, Yao-Yi

    2018-04-17

    Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance computing to extract knowledge from spatial big data. In environmental epidemiology, exposure modeling is a commonly used approach to conduct exposure assessment to determine the distribution of exposures in study populations. geoAI technologies provide important advantages for exposure modeling in environmental epidemiology, including the ability to incorporate large amounts of big spatial and temporal data in a variety of formats; computational efficiency; flexibility in algorithms and workflows to accommodate relevant characteristics of spatial (environmental) processes including spatial nonstationarity; and scalability to model other environmental exposures across different geographic areas. The objectives of this commentary are to provide an overview of key concepts surrounding the evolving and interdisciplinary field of geoAI including spatial data science, machine learning, deep learning, and data mining; recent geoAI applications in research; and potential future directions for geoAI in environmental epidemiology.

  19. Past, present and prospect of an Artificial Intelligence (AI) based model for sediment transport prediction

    Science.gov (United States)

    Afan, Haitham Abdulmohsin; El-shafie, Ahmed; Mohtar, Wan Hanna Melini Wan; Yaseen, Zaher Mundher

    2016-10-01

    An accurate model for sediment prediction is a priority for all hydrological researchers. Many conventional methods have shown an inability to achieve an accurate prediction of suspended sediment. These methods are unable to understand the behaviour of sediment transport in rivers due to the complexity, noise, non-stationarity, and dynamism of the sediment pattern. In the past two decades, Artificial Intelligence (AI) and computational approaches have become a remarkable tool for developing an accurate model. These approaches are considered a powerful tool for solving any non-linear model, as they can deal easily with a large number of data and sophisticated models. This paper is a review of all AI approaches that have been applied in sediment modelling. The current research focuses on the development of AI application in sediment transport. In addition, the review identifies major challenges and opportunities for prospective research. Throughout the literature, complementary models superior to classical modelling.

  20. Computational intelligence from AI to BI to NI

    Science.gov (United States)

    Werbos, Paul J.

    2015-05-01

    This paper gives highlights of the history of the neural network field, stressing the fundamental ideas which have been in play. Early neural network research was motivated mainly by the goals of artificial intelligence (AI) and of functional neuroscience (biological intelligence, BI), but the field almost died due to frustrations articulated in the famous book Perceptrons by Minsky and Papert. When I found a way to overcome the difficulties by 1974, the community mindset was very resistant to change; it was not until 1987/1988 that the field was reborn in a spectacular way, leading to the organized communities now in place. Even then, it took many more years to establish crossdisciplinary research in the types of mathematical neural networks needed to really understand the kind of intelligence we see in the brain, and to address the most demanding engineering applications. Only through a new (albeit short-lived) funding initiative, funding crossdisciplinary teams of systems engineers and neuroscientists, were we able to fund the critical empirical demonstrations which put our old basic principle of "deep learning" firmly on the map in computer science. Progress has rightly been inhibited at times by legitimate concerns about the "Terminator threat" and other possible abuses of technology. This year, at SPIE, in the quantum computing track, we outline the next stage ahead of us in breaking out of the box, again and again, and rising to fundamental challenges and opportunities still ahead of us.

  1. Ai

    African Journals Online (AJOL)

    :=g=~!Ai~~~~~g~~ ~~~~~~. Jim Taylor, Rob O'Donoghue and Alistair Clacherty. INTRODUCTION. The Department of Environment Affairs, in cooperation with ...

  2. Three IQs of AI Systems and their Testing Methods

    OpenAIRE

    Liu, Feng; Shi, Yong; Liu, Ying

    2017-01-01

    The rapid development of artificial intelligence has brought the artificial intelligence threat theory as well as the problem about how to evaluate the intelligence level of intelligent products. Both need to find a quantitative method to evaluate the intelligence level of intelligence systems, including human intelligence. Based on the standard intelligence system and the extended Von Neumann architecture, this paper proposes General IQ, Service IQ and Value IQ evaluation methods for intelli...

  3. Application of Artificial Intelligence (AI) Programming Techniques to Tactical Guidance for Fighter Aircraft

    Science.gov (United States)

    McManus, John W.; Goodrich, Kenneth H.

    1989-01-01

    A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined in detail and example rules are presented. The results of tests to evaluate the performance of the TDG versus a version of AML and versus human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify than the updated FORTRAN AML programs.

  4. Intelligent structural optimization: Concept, Model and Methods

    International Nuclear Information System (INIS)

    Lu, Dagang; Wang, Guangyuan; Peng, Zhang

    2002-01-01

    Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented

  5. 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...

  6. Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS): A conceptual framework

    Science.gov (United States)

    Parnell, Gregory S.; Rowell, William F.; Valusek, John R.

    1987-01-01

    In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.

  7. AI Reloaded: Objectives, Potentials, and Challenges of the Novel Field of Brain-Like Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Rosemarie Velik

    2012-11-01

    Full Text Available The general objective of Artificial Intelligence (AI is to make machines – particularly computers – do things that require intelligence when done by humans. In the last 60 years, AI has significantly progressed and today forms an important part of industry and technology. However, despite the many successes, fundamental questions concerning the creation of human-level intelligence in machines still remain open and will probably not be answerable when continuing on the current, mainly mathematic-algorithmically-guided path of AI. With the novel discipline of
    Brain-Like Artificial Intelligence, one potential way out of this dilemma has been suggested. Brain-Like AI aims at analyzing and deciphering the working mechanisms of the brain and translating this knowledge into implementable AI architectures with the objective to develop in this way more efficient, flexible, and capable technical systems This article aims at giving a review about this young and still heterogeneous and dynamic research field.

  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. Intelligence Unleashed: An argument for AI in Education

    OpenAIRE

    Luckin, R.; Holmes, W.

    2016-01-01

    This paper on artificial intelligence in education (AIEd) has two aims. The first: to explain to a non-specialist, interested, reader what AIEd is: its goals, how it is built, and how it works. The second: to set out the argument for what AIEd can offer teaching and learning, both now and in the future, with an eye towards improving learning and life outcomes for all. Computer systems that are artificially intelligent interact with the world using capabilities (such as speech recognition) and...

  10. Infrastructural intelligence: Contemporary entanglements between neuroscience and AI.

    Science.gov (United States)

    Bruder, Johannes

    2017-01-01

    In this chapter, I reflect on contemporary entanglements between artificial intelligence and the neurosciences by tracing the development of Google's recent DeepMind algorithms back to their roots in neuroscientific studies of episodic memory and imagination. Google promotes a new form of "infrastructural intelligence," which excels by constantly reassessing its cognitive architecture in exchange with a cloud of data that surrounds it, and exhibits putatively human capacities such as intuition. I argue that such (re)alignments of biological and artificial intelligence have been enabled by a paradigmatic infrastructuralization of the brain in contemporary neuroscience. This infrastructuralization is based in methodologies that epistemically liken the brain to complex systems of an entirely different scale (i.e., global logistics) and has given rise to diverse research efforts that target the neuronal infrastructures of higher cognitive functions such as empathy and creativity. What is at stake in this process is no less than the shape of brains to come and a revised understanding of the intelligent and creative social subject. © 2017 Elsevier B.V. All rights reserved.

  11. 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.

  12. Artificial intelligence/expert (AI/EX) systems for steelworks pollution control

    Energy Technology Data Exchange (ETDEWEB)

    Schofield, N.; Le Louer, P.; Mirabile, D.; Hubner, R. [Corus UK Ltd., Rotherham (United Kingdom)

    2002-07-01

    The objectives of this project have been to develop and apply artificial intelligence and expert system (AI/EX) methods to improve the control and operational performance of steelworks' pollution control equipment and to assess the viability and benefits of using such systems in dynamic process plant applications. Four distinct sub-projects were carried out: an expert system incorporating knowledge-based rules and neural network simulations has been developed by Corus which provides plant personnel with a real-time condition monitoring tool for the plant. Abnormalities with plant operation are now instantly recognised and alarmed, allowing prioritised maintenance to increase plant availability. The LECES project focused on studies concerning three different sites in order to evaluate predictive emission monitoring systems using neural networks to replace conventional instrumental and controls in steelworks' combustion systems. VAI developed a software template for pollution control expert systems to demonstrate the transferability of AI/EX technology. This has been done through the development of a validated process database containing data from the Corus sub-project and the subsequent integration of this data with dynamic emission models to produce rules for input to an evaluation database. CSM developed a fuzzy logic controlled process management system applied to the biological treatment of coke-oven waste water. A pilot plant has been installed and results on simulations performed using the fuzzy logic system linked to a neural network simulator show that it is possible to obtain great advantages in the biological pilot plant performance.

  13. Representation Methods in AI. Searching by Graphs

    Directory of Open Access Journals (Sweden)

    Angel GARRIDO

    2012-12-01

    Full Text Available The historical origin of the Artificial Intelligence (A I is usually established in the Darmouth 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 Zadehfor instance [6, 7]. Frequently A I 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 [2]. Among the things that A I 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 A I can be classified in two general types [3, 4]: search problems and representation problems. In this last “mountain”, there exist different ways to reach their summit. So, we have [3]: logics, rules, frames, associative nets, scripts and so on, many times connectedamong them. We attempt, in this paper, a panoramic vision of the scope of application of such Representation Methods in A I. The two more disputable questions of both modern philosophy of mind and A I will be Turing Test and The Chinese Room Argument. To elucidate these very difficult questions, see both final Appendices.

  14. Man-machine communication in reactor control using AI methods

    International Nuclear Information System (INIS)

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

    1987-01-01

    In the last years the interest in process control has expecially focused on problems of man-machine communication. It depends on its great importance to process performance and user acceptance. Advanced computerized operator aids, e.g. in nuclear power plants, are as well as their man-machine interface. In the Central Institute for Nuclear Research in Rossendorf a computerized operator support system for nuclear power plants is designed, which is involved in a decentralized process automation system. A similar but simpler system, the Hierarchical Informational System (HIS) at the Rossendorf Research Reactor, works with a computer controlled man-machine interface, based on menu. In the special case of the disturbance analysis program SAAP-2, which is included in the HIS, the limits of menu techniques are obviously. Therefore it seems to be necessary and with extended hard- and software possible to realize an user controlled natural language interface using Artificial Intelligence (AI) methods. The draft of such a system is described. It should be able to learn during a teaching phase all phrases and their meanings. The system will work on the basis of a self-organizing, associative data structure. It is used to recognize a great amount of words which are used in language analysis. Error recognition and, if possible, correction is done by means of a distance function in the word set. Language analysis should be carried out with a simplified word class controlled functional analysis. With this interface it is supposed to get experience in intelligent man-machine communication to enhance operational safety in future. (author)

  15. 3rd Workshop on "Combinations of Intelligent Methods and Applications"

    CERN Document Server

    Palade, Vasile

    2013-01-01

    The combination of different intelligent methods is a very active research area in Artificial Intelligence (AI). The aim is to create integrated or hybrid methods that benefit from each of their components.  The 3rd Workshop on “Combinations of Intelligent Methods and Applications” (CIMA 2012) was intended to become a forum for exchanging experience and ideas among researchers and practitioners who are dealing with combining intelligent methods either based on first principles or in the context of specific applications. CIMA 2012 was held in conjunction with the 22nd European Conference on Artificial Intelligence (ECAI 2012).This volume includes revised versions of the papers presented at CIMA 2012.  .

  16. 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.

  17. Blue Sky Ideas in Artificial Intelligence Education from the EAAI 2017 New and Future AI Educator Program

    OpenAIRE

    Eaton, Eric; Koenig, Sven; Schulz, Claudia; Maurelli, Francesco; Lee, John; Eckroth, Joshua; Crowley, Mark; Freedman, Richard G.; Cardona-Rivera, Rogelio E.; Machado, Tiago; Williams, Tom

    2017-01-01

    The 7th Symposium on Educational Advances in Artificial Intelligence (EAAI'17, co-chaired by Sven Koenig and Eric Eaton) launched the EAAI New and Future AI Educator Program to support the training of early-career university faculty, secondary school faculty, and future educators (PhD candidates or postdocs who intend a career in academia). As part of the program, awardees were asked to address one of the following "blue sky" questions: * How could/should Artificial Intelligence (AI) courses ...

  18. Artificial Intelligence (AI techniques to analyze the determinants attributes in housing prices

    Directory of Open Access Journals (Sweden)

    Julia M. Núñez Tabale

    2016-12-01

    Full Text Available The econometric approach to obtain the value of a property began with hedonic modelling, which were based on a set of property attributes, internal or external, associated to each particular dwelling. The final sale value can be estimated, and also the marginal prices of each exogenous explanatory variable. A good alternative to the hedonic approach is based on several Artificial Intelligence (AI techniques, such as artificial neural networks (ANN, these tend to be more precise. Both methodologies are compared, and a case study is developed using data from Seville, the larger town in the South of Spain.

  19. An artificial intelligence (AI) NOx/heat rate optimization system for Ontario Hydro`s fossil generating stations

    Energy Technology Data Exchange (ETDEWEB)

    Luk, J.; Frank, A.; Bodach, P. [Ontario Hydro, Toronto, ON (Canada); Warriner, G. [Radian International, Tucker, GA (United States); Noblett, J. [Radian International, Austin, TX (United States); Slatsky, M. [Southern Company, Birmingham, AL (United States)

    1999-08-01

    Artificial intelligence (AI)-based software packages which can optimize power plant operations that improves heat rate and also reduces nitrogen oxide emissions are now commonly available for commercial use. This paper discusses the implementation of the AI-based NOx and Heat Rate Optimization System at Ontario Hydro`s generation stations, emphasizing the current AI Optimization Project at Units 5 and 6 of the Lakeview Generating Station. These demonstration programs are showing promising results in NOx reduction and plant performance improvement. The availability of the plant Digital Control System (DCS) in implementing AI optimization in a closed-loop system was shown to be an important criterion for success. Implementation of AI technology at other Ontario Hydro fossil generating units as part of the overall NOx emission reduction system is envisaged to coincide with the retrofit of the original plant control system with the latest DCS systems. 14 refs., 3 figs.

  20. Human-centered automation and AI - Ideas, insights, and issues from the Intelligent Cockpit Aids research effort

    Science.gov (United States)

    Abbott, Kathy H.; Schutte, Paul C.

    1989-01-01

    A development status evaluation is presented for the NASA-Langley Intelligent Cockpit Aids research program, which encompasses AI, human/machine interfaces, and conventional automation. Attention is being given to decision-aiding concepts for human-centered automation, with emphasis on inflight subsystem fault management, inflight mission replanning, and communications management. The cockpit envisioned is for advanced commercial transport aircraft.

  1. Enabling technologies and methods for the retro-fitting of AI software into NPPS

    International Nuclear Information System (INIS)

    Pymm, P.

    1994-01-01

    Scottish Nuclear have a number of plant monitoring and training applications at their operational nuclear power plant which could benefit from the introduction of artificial intelligence (AI) software. An outline of early work on two current AI developments in the areas of advanced operator aids and intelligent training is given. A generic workstation based engineering simulator (WES) which provides a prototyping environment for AI product application development and evaluation and development of human-computer interface (HCI) designs for plant installation is described. It is concluded that the WES architecture facilitates both migration of the prototype AI application to the plant and collaboration in the AI field between Scottish Nuclear and other organizations. (author). 1 ref., 6 figs

  2. Flood AI: An Intelligent Systems for Discovery and Communication of Disaster Knowledge

    Science.gov (United States)

    Demir, I.; Sermet, M. Y.

    2017-12-01

    Communities are not immune from extreme events or natural disasters that can lead to large-scale consequences for the nation and public. Improving resilience to better prepare, plan, recover, and adapt to disasters is critical to reduce the impacts of extreme events. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This project presents an intelligent system, Flood AI, for flooding to improve societal preparedness by providing a knowledge engine using voice recognition, artificial intelligence, and natural language processing based on a generalized ontology for disasters with a primary focus on flooding. The knowledge engine utilizes the flood ontology and concepts to connect user input to relevant knowledge discovery channels on flooding by developing a data acquisition and processing framework utilizing environmental observations, forecast models, and knowledge bases. Communication channels of the framework includes web-based systems, agent-based chat bots, smartphone applications, automated web workflows, and smart home devices, opening the knowledge discovery for flooding to many unique use cases.

  3. The Molecular Basis of Neural Memory. Part 7: Neural Intelligence (NI versus Artificial Intelligence (AI

    Directory of Open Access Journals (Sweden)

    Gerard Marx

    2017-07-01

    Full Text Available The link of memory to intelligence is incontestable, though the development of electronic artifacts with memory has confounded cognitive and computer scientists’ conception of memory and its relevance to “intelligence”. We propose two categories of “Intelligence”: (1 Logical (objective — mathematics, numbers, pattern recognition, games, programmable in binary format. (2 Emotive (subjective — sensations, feelings, perceptions, goals desires, sociability, sex, food, love. The 1st has been reduced to computational algorithms of which we are well versed, witness global technology and the internet. The 2nd relates to the mysterious process whereby (psychic emotive states are achieved by neural beings sensing, comprehending, remembering and dealing with their surroundings. Many theories and philosophies have been forwarded to rationalize this process, but as neuroscientists, we remain dissatisfied. Our own musings on universal neural memory, suggest a tripartite mechanism involving neurons interacting with their surroundings, notably the neural extracellular matrix (nECM with dopants [trace metals and neurotransmitters (NTs]. In particular, the NTs are the molecular encoders of emotive states. We have developed a chemographic representation of such a molecular code.To quote Longuet-Higgins, “Perhaps it is time for the term ‘artificial intelligence’ to be replaced by something more modest and less provisional”. We suggest “artifact intelligence” (ARTI or “machine intelligence” (MI, neither of which imply emulation of emotive neural processes, but simply refer to the ‘demotive’ (lacking emotive quality capability of electronic artifacts that employ a recall function, to calculate algorithms.

  4. AI (artificial intelligence) in histopathology--from image analysis to automated diagnosis.

    Science.gov (United States)

    Kayser, Klaus; Görtler, Jürgen; Bogovac, Milica; Bogovac, Aleksandar; Goldmann, Torsten; Vollmer, Ekkehard; Kayser, Gian

    2009-01-01

    The technological progress in digitalization of complete histological glass slides has opened a new door in tissue--based diagnosis. The presentation of microscopic images as a whole in a digital matrix is called virtual slide. A virtual slide allows calculation and related presentation of image information that otherwise can only be seen by individual human performance. The digital world permits attachments of several (if not all) fields of view and the contemporary visualization on a screen. The presentation of all microscopic magnifications is possible if the basic pixel resolution is less than 0.25 microns. To introduce digital tissue--based diagnosis into the daily routine work of a surgical pathologist requires a new setup of workflow arrangement and procedures. The quality of digitized images is sufficient for diagnostic purposes; however, the time needed for viewing virtual slides exceeds that of viewing original glass slides by far. The reason lies in a slower and more difficult sampling procedure, which is the selection of information containing fields of view. By application of artificial intelligence, tissue--based diagnosis in routine work can be managed automatically in steps as follows: 1. The individual image quality has to be measured, and corrected, if necessary. 2. A diagnostic algorithm has to be applied. An algorithm has be developed, that includes both object based (object features, structures) and pixel based (texture) measures. 3. These measures serve for diagnosis classification and feedback to order additional information, for example in virtual immunohistochemical slides. 4. The measures can serve for automated image classification and detection of relevant image information by themselves without any labeling. 5. The pathologists' duty will not be released by such a system; to the contrary, it will manage and supervise the system, i.e., just working at a "higher level". Virtual slides are already in use for teaching and continuous

  5. AI's Philosophical Underpinnings: A Thinking Person's Walk through the Twists and Turns of Artificial Intelligence's Meandering Path

    Science.gov (United States)

    Colombano, Silvano; Norvig, Peter (Technical Monitor)

    2000-01-01

    Few human endeavors can be viewed both as extremely successful and unsuccessful at the same time. This is typically the case when goals have not been well defined or have been shifting in time. This has certainly been true of Artificial Intelligence (AI). The nature of intelligence has been the object of much thought and speculation throughout the history of philosophy. It is in the nature of philosophy that real headway is sometimes made only when appropriate tools become available. Similarly the computer, coupled with the ability to program (at least in principle) any function, appeared to be the tool that could tackle the notion of intelligence. To suit the tool, the problem of the nature of intelligence was soon sidestepped in favor of this notion: If a probing conversation with a computer could not be distinguished from a conversation with a human, then AI had been achieved. This notion became known as the Turing test, after the mathematician Alan Turing who proposed it in 1950. Conceptually rich and interesting, these early efforts gave rise to a large portion of the field's framework. Key to AI, rather than the 'number crunching' typical of computers until then, was viewed as the ability to manipulate symbols and make logical inferences. To facilitate these tasks, AI languages such as LISP and Prolog were invented and used widely in the field. One idea that emerged and enabled some success with real world problems was the notion that 'most intelligence' really resided in knowledge. A phrase attributed to Feigenbaum, one of the pioneers, was 'knowledge is the power.' With this premise, the problem is shifted from 'how do we solve problems' to 'how do we represent knowledge.' A good knowledge representation scheme could allow one to draw conclusions from given premises. Such schemes took forms such as rules,frames and scripts. It allowed the building of what became known as expert systems or knowledge based systems (KBS).

  6. Continuous surveillance of transformers using artificial intelligence methods; Surveillance continue des transformateurs: application des methodes d'intelligence artificielle

    Energy Technology Data Exchange (ETDEWEB)

    Schenk, A.; Germond, A. [Ecole Polytechnique Federale de Lausanne, Lausanne (Switzerland); Boss, P.; Lorin, P. [ABB Secheron SA, Geneve (Switzerland)

    2000-07-01

    The article describes a new method for the continuous surveillance of power transformers based on the application of artificial intelligence (AI) techniques. An experimental pilot project on a specially equipped, strategically important power transformer is described. Traditional surveillance methods and the use of mathematical models for the prediction of faults are described. The article describes the monitoring equipment used in the pilot project and the AI principles such as self-organising maps that are applied. The results obtained from the pilot project and methods for their graphical representation are discussed.

  7. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

    Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

  8. 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

  9. Pathologies of AI: Responsible use of artificial intelligence in professional work

    NARCIS (Netherlands)

    Stamper, R.K.

    1988-01-01

    Although the AI paradigm is useful for building knowledge-based systems for the applied natural sciences, there are dangers when it is extended into the domains of business, law and other social systems. It is misleading to treat knowledge as a commodity that can be separated from the context in

  10. Squeeze Casting Method Of AI-Si Alloy For Piston Material

    International Nuclear Information System (INIS)

    Wagiyo, H.; Dani, Muhammad; Sulistioso, G.S.; Pardede, Elman; Handayani, Ari; Teguh, Yulius S.P.P.

    2001-01-01

    The AI-Si alloy is an alloy used as piston material. This alloys could be as AI-Si hypereutectic alloy (Si content more than 12.5 % wt.), as AI-Si eutectic alloy (Si cuntent 12.5 % wt, and as AI-Si hypoeutectic alloy (Si content less than 12.5 % wt.). The synthesize of AI-Si alloy piston generally using the technique of gravity casting in a dies. This method is causing high porousity. By using the squeeze technique, amount ofporousity in AI-Si alloy is possibly reduced and the density of this alloy should be higher. The other factors such as alloying elements of AI-Si alloy (Mg. Cu, Zn) would increase the mechanical properties especially the hardness. The focuses of this research are the microstructure and the maximum hardness during the heat treatment of AI-Si alloy which was added by alloying elments. The result of hardness at test shows the maximum hardness at 94.7 kg/mm 2 obtained at aging temperature of 210 o C for hours with homogenous dendritic microstructure

  11. Intelligent methods for cyber warfare

    CERN Document Server

    Reformat, Marek; Alajlan, Naif

    2015-01-01

    Cyberwarfare has become an important concern for governmental agencies as well businesses of various types.  This timely volume, with contributions from some of the internationally recognized, leaders in the field, gives readers a glimpse of the new and emerging ways that Computational Intelligence and Machine Learning methods can be applied to address problems related to cyberwarfare. The book includes a number of chapters that can be conceptually divided into three topics: chapters describing different data analysis methodologies with their applications to cyberwarfare, chapters presenting a number of intrusion detection approaches, and chapters dedicated to analysis of possible cyber attacks and their impact. The book provides the readers with a variety of methods and techniques, based on computational intelligence, which can be applied to the broad domain of cyberwarfare.

  12. 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.

  13. Investigating AI with Basic and Logo. Teaching Your Computer to Be Intelligent.

    Science.gov (United States)

    Mandell, Alan; Lucking, Robert

    1988-01-01

    Discusses artificial intelligence, its definitions, and potential applications. Provides listings of Logo and BASIC versions for programs along with REM statements needed to make modifications for use with Apple computers. (RT)

  14. Some applications of AI [Artificial Intelligence] to the problems of accelerator physics

    International Nuclear Information System (INIS)

    Higo, T.; Shoaee, H.; Spencer, J.E.

    1986-09-01

    Failure of orbit correction schemes to recognize betatron oscillation patterns obvious to any machine operator is a good problem with which to analyze the uses of Artificial Intelligence and the roles and relationships of operators, control systems and machines. Because such error modes are very common, their generalization could provide an efficient machine optimization and control strategy. A set of first-order, unitary transformations connecting canonical variables through measured results are defined which can either be compared to design for commissioning or to past results for 'golden orbit' operation. Because these relate directly to hardware variables, the method is simple, fast and direct. It has implications for machine design, controls, monitoring and feedback. Chronological analysis of such machine signatures can predict or provide a variety of information such as mean time to failure, failure modes and fast feedback or feedforward for optimizing figures of merit such as luminosity or current transmission. The use of theoretical and empirical scaling relations for such problems is discussed in terms of various figures of merit, the variables on which they depend as well as their functional dependences

  15. COMPETITIVE INTELLIGENCE ANALYSIS - SCENARIOS METHOD

    Directory of Open Access Journals (Sweden)

    Ivan Valeriu

    2014-07-01

    Full Text Available Keeping a company in the top performing players in the relevant market depends not only on its ability to develop continually, sustainably and balanced, to the standards set by the customer and competition, but also on the ability to protect its strategic information and to know in advance the strategic information of the competition. In addition, given that economic markets, regardless of their profile, enable interconnection not only among domestic companies, but also between domestic companies and foreign companies, the issue of economic competition moves from the national economies to the field of interest of regional and international economic organizations. The stakes for each economic player is to keep ahead of the competition and to be always prepared to face market challenges. Therefore, it needs to know as early as possible, how to react to others’ strategy in terms of research, production and sales. If a competitor is planning to produce more and cheaper, then it must be prepared to counteract quickly this movement. Competitive intelligence helps to evaluate the capabilities of competitors in the market, legally and ethically, and to develop response strategies. One of the main goals of the competitive intelligence is to acknowledge the role of early warning and prevention of surprises that could have a major impact on the market share, reputation, turnover and profitability in the medium and long term of a company. This paper presents some aspects of competitive intelligence, mainly in terms of information analysis and intelligence generation. Presentation is theoretical and addresses a structured method of information analysis - scenarios method – in a version that combines several types of analysis in order to reveal some interconnecting aspects of the factors governing the activity of a company.

  16. harnessing_ai_20180319.pptx

    OpenAIRE

    Johnson, Matthew

    2018-01-01

    There have been great strides made in Artificial Intelligence in recent years, but it is often not clear how to apply these recent advances to new problems. In this talk I propose one method of thinking about problems in the sciences and how to find the right AI techniques to aid in research.

  17. Rapid and simple colorimetric method for the quantification of AI-2 produced from Salmonella Typhimurium.

    Science.gov (United States)

    Wattanavanitchakorn, Siriluck; Prakitchaiwattana, Cheunjit; Thamyongkit, Patchanita

    2014-04-01

    The aim of this study was to evaluate the feasibility of Fe(III) ion reduction for the simple and rapid quantification of autoinducer-2 (AI-2) produced from bacteria using Salmonella Typhimurium as a model. Since the molecular structure of AI-2 is somewhat similar to ascorbic acid it was expected that AI-2 would also act as a reducing agent and reduce Fe(III) ions in the presence of 1,10-phenanthroline to form the colored [(o-phen)3 Fe(II)]SO4 ferroin complex that could be quantified colorimetrically. In support of this, colony rinses and cell free supernatants from cultures of all tested AI-2 producing strains, but not the AI-2 negative Sinorhizobium meliloti, formed a colored complex with a λmax of 510nm. The OD510 values of these culture supernatants or colony rinses were in broad agreement with the % activity observed in the same samples using the standard Vibrio harveyi bioluminescence assay for AI-2 detection, and with previously reported results. This methodology could potentially be developed as an alternative method for the simple and rapid quantification of AI-2 levels produced in bacterial cultures. Copyright © 2014 Elsevier B.V. All rights reserved.

  18. Reasoning methods in medical consultation systems: artificial intelligence approaches.

    Science.gov (United States)

    Shortliffe, E H

    1984-01-01

    It has been argued that the problem of medical diagnosis is fundamentally ill-structured, particularly during the early stages when the number of possible explanations for presenting complaints can be immense. This paper discusses the process of clinical hypothesis evocation, contrasts it with the structured decision making approaches used in traditional computer-based diagnostic systems, and briefly surveys the more open-ended reasoning methods that have been used in medical artificial intelligence (AI) programs. The additional complexity introduced when an advice system is designed to suggest management instead of (or in addition to) diagnosis is also emphasized. Example systems are discussed to illustrate the key concepts.

  19. Artificial Intelligence (AI) in Healthcare Market: Market Trend with Boom Opportunities in Upcoming Years

    OpenAIRE

    Rahul Gautam

    2018-01-01

    The global artificial intelligence in healthcare market is expected to observe an extensive growth in the coming years, led by growing need for precision medicine, increasing application of big data in healthcare industry, and rising need for coordination between healthcare workforce and patients. The products in the global market are categorized as hardware, software and services, with software being the largest contributor in 2016 and the category is also projected to witness significant gr...

  20. Application of artificial intelligence (AI) concepts to the development of space flight parts approval model

    Science.gov (United States)

    Krishnan, G. S.

    1997-01-01

    A cost effective model which uses the artificial intelligence techniques in the selection and approval of parts is presented. The knowledge which is acquired from the specialists for different part types are represented in a knowledge base in the form of rules and objects. The parts information is stored separately in a data base and is isolated from the knowledge base. Validation, verification and performance issues are highlighted.

  1. Combining AI Methods for Learning Bots in a Real-Time Strategy Game

    Directory of Open Access Journals (Sweden)

    Robin Baumgarten

    2009-01-01

    Full Text Available We describe an approach for simulating human game-play in strategy games using a variety of AI techniques, including simulated annealing, decision tree learning, and case-based reasoning. We have implemented an AI-bot that uses these techniques to form a novel approach for planning fleet movements and attacks in DEFCON, a nuclear war simulation strategy game released in 2006 by Introversion Software Ltd. The AI-bot retrieves plans from a case-base of recorded games, then uses these to generate a new plan using a method based on decision tree learning. In addition, we have implemented more sophisticated control over low-level actions that enable the AI-bot to synchronize bombing runs, and used a simulated annealing approach for assigning bombing targets to planes and opponent cities to missiles. We describe how our AI-bot operates, and the experimentation we have performed in order to determine an optimal configuration for it. With this configuration, our AI-bot beats Introversion's finite state machine automated player in 76.7% of 150 matches played. We briefly introduce the notion of ability versus enjoyability and discuss initial results of a survey we conducted with human players.

  2. Artificial intelligence (AI)-based relational matching and multimodal medical image fusion: generalized 3D approaches

    Science.gov (United States)

    Vajdic, Stevan M.; Katz, Henry E.; Downing, Andrew R.; Brooks, Michael J.

    1994-09-01

    A 3D relational image matching/fusion algorithm is introduced. It is implemented in the domain of medical imaging and is based on Artificial Intelligence paradigms--in particular, knowledge base representation and tree search. The 2D reference and target images are selected from 3D sets and segmented into non-touching and non-overlapping regions, using iterative thresholding and/or knowledge about the anatomical shapes of human organs. Selected image region attributes are calculated. Region matches are obtained using a tree search, and the error is minimized by evaluating a `goodness' of matching function based on similarities of region attributes. Once the matched regions are found and the spline geometric transform is applied to regional centers of gravity, images are ready for fusion and visualization into a single 3D image of higher clarity.

  3. Application of artificial intelligence (AI) concepts to the development of space flight parts approval model

    Science.gov (United States)

    Krishnan, Govindarajapuram Subramaniam

    1997-12-01

    The National Aeronautics & Space Administration (NASA), the European Space Agency (ESA), and the Canadian Space Agency (CSA) missions involve the performance of scientific experiments in Space. Instruments used in such experiments are fabricated using electronic parts such as microcircuits, inductors, capacitors, diodes, transistors, etc. For instruments to perform reliably the selection of commercial parts must be monitored and strictly controlled. The process used to achieve this goal is by a manual review and approval of every part used to build the instrument. The present system to select and approve parts for space applications is manual, inefficient, inconsistent, slow and tedious, and very costly. In this dissertation a computer based decision support model is developed for implementing this process using artificial intelligence concepts based on the current information (expert sources). Such a model would result in a greater consistency, accuracy, and timeliness of evaluation. This study presents the methodology of development and features of the model, and the analysis of the data pertaining to the performance of the model in the field. The model was evaluated for three different part types by experts from three different space agencies. The results show that the model was more consistent than the manual evaluation for all part types considered. The study concludes with the cost and benefits analysis of implementing the models and shows that implementation of the model will result in significant cost savings. Other implementation details are highlighted.

  4. General general game AI

    OpenAIRE

    Togelius, Julian; Yannakakis, Georgios N.; 2016 IEEE Conference on Computational Intelligence and Games (CIG)

    2016-01-01

    Arguably the grand goal of artificial intelligence research is to produce machines with general intelligence: the capacity to solve multiple problems, not just one. Artificial intelligence (AI) has investigated the general intelligence capacity of machines within the domain of games more than any other domain given the ideal properties of games for that purpose: controlled yet interesting and computationally hard problems. This line of research, however, has so far focuse...

  5. Tweeting AI: Perceptions of AI-Tweeters (AIT) vs Expert AI-Tweeters (EAIT)

    OpenAIRE

    Manikonda, Lydia; Dudley, Cameron; Kambhampati, Subbarao

    2017-01-01

    With the recent advancements in Artificial Intelligence (AI), various organizations and individuals started debating about the progress of AI as a blessing or a curse for the future of the society. This paper conducts an investigation on how the public perceives the progress of AI by utilizing the data shared on Twitter. Specifically, this paper performs a comparative analysis on the understanding of users from two categories -- general AI-Tweeters (AIT) and the expert AI-Tweeters (EAIT) who ...

  6. AI and health

    OpenAIRE

    Martin Anderson

    2018-01-01

    ntelligence refers to the ability of an individual to learn or understand something, or to deal with a new situation. When a machine or software exhibits such characteristics, it is referred to as artificial intelligence (AI). Artificial Intelligence is therefore defined as the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

  7. 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 ...

  8. 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)

  9. An analysis of the application of AI to the development of intelligent aids for flight crew tasks

    Science.gov (United States)

    Baron, S.; Feehrer, C.

    1985-01-01

    This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research.

  10. Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models.

    Science.gov (United States)

    Allawi, Mohammed Falah; Jaafar, Othman; Mohamad Hamzah, Firdaus; Abdullah, Sharifah Mastura Syed; El-Shafie, Ahmed

    2018-05-01

    Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research. During the last two decades, artificial intelligence (AI) techniques have been significantly utilized for attaining a robust modeling to handle different stochastic hydrological parameters. AI techniques have also shown considerable progress in finding optimal rules for reservoir operation. This review research explores the history of developing AI in reservoir inflow forecasting and prediction of evaporation from a reservoir as the major components of the reservoir simulation. In addition, critical assessment of the advantages and disadvantages of integrated AI simulation methods with optimization methods has been reported. Future research on the potential of utilizing new innovative methods based AI techniques for reservoir simulation and optimization models have also been discussed. Finally, proposal for the new mathematical procedure to accomplish the realistic evaluation of the whole optimization model performance (reliability, resilience, and vulnerability indices) has been recommended.

  11. Modeling Progress in AI

    OpenAIRE

    Brundage, Miles

    2015-01-01

    Participants in recent discussions of AI-related issues ranging from intelligence explosion to technological unemployment have made diverse claims about the nature, pace, and drivers of progress in AI. However, these theories are rarely specified in enough detail to enable systematic evaluation of their assumptions or to extrapolate progress quantitatively, as is often done with some success in other technological domains. After reviewing relevant literatures and justifying the need for more ...

  12. AI applications in sheet metal forming

    CERN Document Server

    Hussein, Hussein

    2017-01-01

    This book comprises chapters on research work done around the globe in the area of artificial intelligence (AI) applications in sheet metal forming. The first chapter offers an introduction to various AI techniques and sheet metal forming, while subsequent chapters describe traditional procedures/methods used in various sheet metal forming processes, and focus on the automation of those processes by means of AI techniques, such as KBS, ANN, GA, CBR, etc. Feature recognition and the manufacturability assessment of sheet metal parts, process planning, strip-layout design, selecting the type and size of die components, die modeling, and predicting die life are some of the most important aspects of sheet metal work. Traditionally, these activities are highly experience-based, tedious and time consuming. In response, researchers in several countries have applied various AI techniques to automate these activities, which are covered in this book. This book will be useful for engineers working in sheet metal industri...

  13. Beyond AI: Artificial Dreams Conference

    CERN Document Server

    Zackova, Eva; Kelemen, Jozef; Beyond Artificial Intelligence : The Disappearing Human-Machine Divide

    2015-01-01

    This book is an edited collection of chapters based on the papers presented at the conference “Beyond AI: Artificial Dreams” held in Pilsen in November 2012. The aim of the conference was to question deep-rooted ideas of artificial intelligence and cast critical reflection on methods standing at its foundations.  Artificial Dreams epitomize our controversial quest for non-biological intelligence, and therefore the contributors of this book tried to fully exploit such a controversy in their respective chapters, which resulted in an interdisciplinary dialogue between experts from engineering, natural sciences and humanities.   While pursuing the Artificial Dreams, it has become clear that it is still more and more difficult to draw a clear divide between human and machine. And therefore this book tries to portrait such an image of what lies beyond artificial intelligence: we can see the disappearing human-machine divide, a very important phenomenon of nowadays technological society, the phenomenon which i...

  14. Computing Nash equilibria through computational intelligence methods

    Science.gov (United States)

    Pavlidis, N. G.; Parsopoulos, K. E.; Vrahatis, M. N.

    2005-03-01

    Nash equilibrium constitutes a central solution concept in game theory. The task of detecting the Nash equilibria of a finite strategic game remains a challenging problem up-to-date. This paper investigates the effectiveness of three computational intelligence techniques, namely, covariance matrix adaptation evolution strategies, particle swarm optimization, as well as, differential evolution, to compute Nash equilibria of finite strategic games, as global minima of a real-valued, nonnegative function. An issue of particular interest is to detect more than one Nash equilibria of a game. The performance of the considered computational intelligence methods on this problem is investigated using multistart and deflection.

  15. Constructing an Intelligent Patent Network Analysis Method

    Directory of Open Access Journals (Sweden)

    Chao-Chan Wu

    2012-11-01

    Full Text Available Patent network analysis, an advanced method of patent analysis, is a useful tool for technology management. This method visually displays all the relationships among the patents and enables the analysts to intuitively comprehend the overview of a set of patents in the field of the technology being studied. Although patent network analysis possesses relative advantages different from traditional methods of patent analysis, it is subject to several crucial limitations. To overcome the drawbacks of the current method, this study proposes a novel patent analysis method, called the intelligent patent network analysis method, to make a visual network with great precision. Based on artificial intelligence techniques, the proposed method provides an automated procedure for searching patent documents, extracting patent keywords, and determining the weight of each patent keyword in order to generate a sophisticated visualization of the patent network. This study proposes a detailed procedure for generating an intelligent patent network that is helpful for improving the efficiency and quality of patent analysis. Furthermore, patents in the field of Carbon Nanotube Backlight Unit (CNT-BLU were analyzed to verify the utility of the proposed method.

  16. Introducing AI into MEMS can lead us to brain-computer interfaces and super-human intelligence

    OpenAIRE

    Sanders, David

    2009-01-01

    Last year, I spoke about the progress being made in machine intelligence (Sanders, 2008c) and with sensors and networks of sensors (Sanders, 2008b). Earlier this year (in this journal) I spoke about ambient-intelligence, rapid-prototyping and the role of humans in the factories of the future (Sanders, 2009a). I addressed new applications and technologies such as merging machines with human beings, micro-electromechanics, electro-mechanical systems that can be personalized, smarter than human ...

  17. AI 3D Cybug Gaming

    OpenAIRE

    Ahmed, Zeeshan

    2010-01-01

    In this short paper I briefly discuss 3D war Game based on artificial intelligence concepts called AI WAR. Going in to the details, I present the importance of CAICL language and how this language is used in AI WAR. Moreover I also present a designed and implemented 3D War Cybug for AI WAR using CAICL and discus the implemented strategy to defeat its enemies during the game life.

  18. Optimization of DRASTIC method by supervised committee machine artificial intelligence to assess groundwater vulnerability for Maragheh-Bonab plain aquifer, Iran

    Science.gov (United States)

    Fijani, Elham; Nadiri, Ata Allah; Asghari Moghaddam, Asghar; Tsai, Frank T.-C.; Dixon, Barnali

    2013-10-01

    Contamination of wells with nitrate-N (NO3-N) poses various threats to human health. Contamination of groundwater is a complex process and full of uncertainty in regional scale. Development of an integrative vulnerability assessment methodology can be useful to effectively manage (including prioritization of limited resource allocation to monitor high risk areas) and protect this valuable freshwater source. This study introduces a supervised committee machine with artificial intelligence (SCMAI) model to improve the DRASTIC method for groundwater vulnerability assessment for the Maragheh-Bonab plain aquifer in Iran. Four different AI models are considered in the SCMAI model, whose input is the DRASTIC parameters. The SCMAI model improves the committee machine artificial intelligence (CMAI) model by replacing the linear combination in the CMAI with a nonlinear supervised ANN framework. To calibrate the AI models, NO3-N concentration data are divided in two datasets for the training and validation purposes. The target value of the AI models in the training step is the corrected vulnerability indices that relate to the first NO3-N concentration dataset. After model training, the AI models are verified by the second NO3-N concentration dataset. The results show that the four AI models are able to improve the DRASTIC method. Since the best AI model performance is not dominant, the SCMAI model is considered to combine the advantages of individual AI models to achieve the optimal performance. The SCMAI method re-predicts the groundwater vulnerability based on the different AI model prediction values. The results show that the SCMAI outperforms individual AI models and committee machine with artificial intelligence (CMAI) model. The SCMAI model ensures that no water well with high NO3-N levels would be classified as low risk and vice versa. The study concludes that the SCMAI model is an effective model to improve the DRASTIC model and provides a confident estimate of the

  19. 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

  20. Classification of Children Intelligence with Fuzzy Logic Method

    Science.gov (United States)

    Syahminan; ika Hidayati, Permata

    2018-04-01

    Intelligence of children s An Important Thing To Know The Parents Early on. Typing Can be done With a Child’s intelligence Grouping Dominant Characteristics Of each Type of Intelligence. To Make it easier for Parents in Determining The type of Children’s intelligence And How to Overcome them, for It Created A Classification System Intelligence Grouping Children By Using Fuzzy logic method For determination Of a Child’s degree of intelligence type. From the analysis We concluded that The presence of Intelligence Classification systems Pendulum Children With Fuzzy Logic Method Of determining The type of The Child’s intelligence Can be Done in a way That is easier And The results More accurate Conclusions Than Manual tests.

  1. 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

  2. Combining AI Methods for Learning Bots in a Real-Time Strategy Game

    OpenAIRE

    Robin Baumgarten; Simon Colton; Mark Morris

    2009-01-01

    We describe an approach for simulating human game-play in strategy games using a variety of AI techniques, including simulated annealing, decision tree learning, and case-based reasoning. We have implemented an AI-bot that uses these techniques to form a novel approach for planning fleet movements and attacks in DEFCON, a nuclear war simulation strategy game released in 2006 by Introversion Software Ltd. The AI-bot retrieves plans from a case-base of recorded games, then uses these to generat...

  3. Hybrid Modeling and Optimization of Manufacturing Combining Artificial Intelligence and Finite Element Method

    CERN Document Server

    Quiza, Ramón; Davim, J Paulo

    2012-01-01

    Artificial intelligence (AI) techniques and the finite element method (FEM) are both powerful computing tools, which are extensively used for modeling and optimizing manufacturing processes. The combination of these tools has resulted in a new flexible and robust approach as several recent studies have shown. This book aims to review the work already done in this field as well as to expose the new possibilities and foreseen trends. The book is expected to be useful for postgraduate students and researchers, working in the area of modeling and optimization of manufacturing processes.

  4. AIS authentication

    CERN Multimedia

    2006-01-01

    Users are invited to use the NICE password for AIS authentication. As announced in CNL June-August 2006 (see http://www.cerncourier.com/articles/cnl/3/6/14/1) it is possible to use the NICE username and password to log on to AIS. The procedure is now fully operational and users can themselves reset the AIS password such that the NICE password will be used for authentication required by AIS applications. We strongly recommend CERN users who have a NICE account (this is the case of most users) to do this, with the objective to reduce the number of passwords they need to remember. This can be achieved very easily, directly from the Change Password option on the AIS login (https://aislogin.cern.ch/). Users should just select the '[Change Password]' option displayed at the bottom of the page, provide the 'Old Password' and then click on the button 'Use Nice password' followed by 'Submit'. Change Password option on the AIS login windowSetting the AIS password - Use Nice Password It should be noted that the proce...

  5. Exploring AI Language Assistants with Primary EFL Students

    Science.gov (United States)

    Underwood, Joshua

    2017-01-01

    The main objective of this study was to identify ways to incorporate voice-driven Artificial Intelligence (AI) effectively in classroom language learning. This nine month teacher-led design research study employed technology probes (Amazon's Alexa, Apple's Siri, Google voice search) and co-design methods with a class of primary age English as a…

  6. AI and Mathematical Education

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2012-01-01

    Full Text Available From ancient times, the history of human beings has developed by a succession of steps and sometimes jumps, until reaching the relative sophistication of the modern brain and culture. Researchers are attempting to create systems that mimic human thinking, understand speech, or beat the best human chess player. Understanding the mechanisms of intelligence, and creating intelligent artifacts are the twin goals of Artificial Intelligence (AI. Great mathematical minds have played a key role in AI in recent years; to name only a few: Janos Neumann (also known as John von Neumann, Konrad Zuse, Norbert Wiener, Claude E. Shannon, Alan M. Turing, Grigore Moisil, Lofti A. Zadeh, Ronald R. Yager, Michio Sugeno, Solomon Marcus, or Lászlo A. Barabási. Introducing the study of AI is not merely useful because of its capability for solving difficult problems, but also because of its mathematical nature. It prepares us to understand the current world, enabling us to act on the challenges of the future.

  7. 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

  8. Knowledge Discovery, Integration and Communication for Extreme Weather and Flood Resilience Using Artificial Intelligence: Flood AI Alpha

    Science.gov (United States)

    Demir, I.; Sermet, M. Y.

    2016-12-01

    Nobody is immune from extreme events or natural hazards that can lead to large-scale consequences for the nation and public. One of the solutions to reduce the impacts of extreme events is to invest in improving resilience with the ability to better prepare, plan, recover, and adapt to disasters. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This abstracts presents our project on developing a resilience framework for flooding to improve societal preparedness with objectives; (a) develop a generalized ontology for extreme events with primary focus on flooding; (b) develop a knowledge engine with voice recognition, artificial intelligence, natural language processing, and inference engine. The knowledge engine will utilize the flood ontology and concepts to connect user input to relevant knowledge discovery outputs on flooding; (c) develop a data acquisition and processing framework from existing environmental observations, forecast models, and social networks. The system will utilize the framework, capabilities and user base of the Iowa Flood Information System (IFIS) to populate and test the system; (d) develop a communication framework to support user interaction and delivery of information to users. The interaction and delivery channels will include voice and text input via web-based system (e.g. IFIS), agent-based bots (e.g. Microsoft Skype, Facebook Messenger), smartphone and augmented reality applications (e.g. smart assistant), and automated web workflows (e.g. IFTTT, CloudWork) to open the knowledge discovery for flooding to thousands of community extensible web workflows.

  9. The Multiple Intelligences Teaching Method and Mathematics ...

    African Journals Online (AJOL)

    The Multiple Intelligences teaching approach has evolved and been embraced widely especially in the United States. The approach has been found to be very effective in changing situations for the better, in the teaching and learning of any subject especially mathematics. Multiple Intelligences teaching approach proposes ...

  10. 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

  11. Citadels AI

    OpenAIRE

    Pekárek, Jakub

    2015-01-01

    The aim of this thesis is to implement a playable version of the game Citadels with console interface, and to use it for analysis of the game's properties and development of artificial intelligence. This thesis includes an analysis of strategies, a scheme for their design, an organization of turn processing, a model of intelligence implementation and testing tools. A number of approaches to specific moves have been developed, all of which achieved positive impact on overall intelligence perfo...

  12. Delamination detection using methods of computational intelligence

    Science.gov (United States)

    Ihesiulor, Obinna K.; Shankar, Krishna; Zhang, Zhifang; Ray, Tapabrata

    2012-11-01

    Abstract Reliable delamination prediction scheme is indispensable in order to prevent potential risks of catastrophic failures in composite structures. The existence of delaminations changes the vibration characteristics of composite laminates and hence such indicators can be used to quantify the health characteristics of laminates. An approach for online health monitoring of in-service composite laminates is presented in this paper that relies on methods based on computational intelligence. Typical changes in the observed vibration characteristics (i.e. change in natural frequencies) are considered as inputs to identify the existence, location and magnitude of delaminations. The performance of the proposed approach is demonstrated using numerical models of composite laminates. Since this identification problem essentially involves the solution of an optimization problem, the use of finite element (FE) methods as the underlying tool for analysis turns out to be computationally expensive. A surrogate assisted optimization approach is hence introduced to contain the computational time within affordable limits. An artificial neural network (ANN) model with Bayesian regularization is used as the underlying approximation scheme while an improved rate of convergence is achieved using a memetic algorithm. However, building of ANN surrogate models usually requires large training datasets. K-means clustering is effectively employed to reduce the size of datasets. ANN is also used via inverse modeling to determine the position, size and location of delaminations using changes in measured natural frequencies. The results clearly highlight the efficiency and the robustness of the approach.

  13. 4th Workshop on Combinations of Intelligent Methods and Applications

    CERN Document Server

    Palade, Vasile; Prentzas, Jim

    2016-01-01

    This volume includes extended and revised versions of the papers presented at the 4th Workshop on “Combinations of Intelligent Methods and Applications” (CIMA 2014) which was intended to become a forum for exchanging experience and ideas among researchers and practitioners dealing with combinations of different intelligent methods in Artificial Intelligence. The aim is to create integrated or hybrid methods that benefit from each of their components. Some of the existing presented efforts combine soft computing methods (fuzzy logic, neural networks and genetic algorithms). Another stream of efforts integrates case-based reasoning or machine learning with soft-computing methods. Some of the combinations have been more widely explored, like neuro-symbolic methods, neuro-fuzzy methods and methods combining rule-based and case-based reasoning. CIMA 2014 was held in conjunction with the 26th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2014). .

  14. Intelligent Lighting Control System

    OpenAIRE

    García, Elena; Rodríguez González, Sara; de Paz Santana, Juan F.; Bajo Pérez, Javier

    2014-01-01

    This paper presents an adaptive architecture that allows centralized control of public lighting and intelligent management, in order to economise on lighting and maintain maximum comfort status of the illuminated areas. To carry out this management, architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA and a Service Oriented Aproach (SOA). It performs optim...

  15. The Potential of AI Techniques for Remote Sensing

    Science.gov (United States)

    Estes, J. E.; Sailer, C. T. (Principal Investigator); Tinney, L. R.

    1984-01-01

    The current status of artificial intelligence AI technology is discussed along with imagery data management, database interrogation, and decision making. Techniques adapted from the field of artificial intelligence (AI) have significant, wide ranging impacts upon computer-assisted remote sensing analysis. AI based techniques offer a powerful and fundamentally different approach to many remote sensing tasks. In addition to computer assisted analysis, AI techniques can also aid onboard spacecraft data processing and analysis and database access and query.

  16. Managing bioengineering complexity with AI techniques.

    Science.gov (United States)

    Beal, Jacob; Adler, Aaron; Yaman, Fusun

    2016-10-01

    Our capabilities for systematic design and engineering of biological systems are rapidly increasing. Effectively engineering such systems, however, requires the synthesis of a rapidly expanding and changing complex body of knowledge, protocols, and methodologies. Many of the problems in managing this complexity, however, appear susceptible to being addressed by artificial intelligence (AI) techniques, i.e., methods enabling computers to represent, acquire, and employ knowledge. Such methods can be employed to automate physical and informational "routine" work and thus better allow humans to focus their attention on the deeper scientific and engineering issues. This paper examines the potential impact of AI on the engineering of biological organisms through the lens of a typical organism engineering workflow. We identify a number of key opportunities for significant impact, as well as challenges that must be overcome. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  17. Coupling artificial intelligence and numerical computation for engineering design (Invited paper)

    Science.gov (United States)

    Tong, S. S.

    1986-01-01

    The possibility of combining artificial intelligence (AI) systems and numerical computation methods for engineering designs is considered. Attention is given to three possible areas of application involving fan design, controlled vortex design of turbine stage blade angles, and preliminary design of turbine cascade profiles. Among the AI techniques discussed are: knowledge-based systems; intelligent search; and pattern recognition systems. The potential cost and performance advantages of an AI-based design-generation system are discussed in detail.

  18. Development of AI (Artificial Intelligence)-based simulation system for man-machine system behavior in accidental situations of nuclear power plant

    International Nuclear Information System (INIS)

    Yoshida, Kazuo; Yokobayashi, Masao; Tanabe, Fumiya; Kawase, Katumi.

    1996-01-01

    A prototype version of a computer simulation system named JACOS (JAeri COgnitive Simulation system) has been developed at JAERI (Japan Atomic Energy Research Institute) to simulate the man-machine system behavior in which both the cognitive behavior of a human operator and the plant behavior affect each other. The objectives of this system development is to provide man-machine system analysts with detailed information on the cognitive process of an operator and the plant behavior affected by operator's actions in accidental situations of an NPP (nuclear power plant). The simulation system consists of an operator model and a plant model which are coupled dynamically. The operator model simulates an operator's cognitive behavior in accidental situations based on the decision ladder model of Rasmussen, and is implemented using the AI-techniques of the distributed cooperative inference method with the so-called blackboard architecture. Rule-based behavior is simulated using knowledge representation with If-Then type of rules. Knowledge-based behavior is simulated using knowledge representation with MFM (Multilevel Flow Modeling) and qualitative reasoning method. Cognitive characteristics of attentional narrowing, limitation of short-term memory, and knowledge recalling from long-term memory are also modeled. The plant model of a 3-loop PWR is also developed using a best estimate thermal-hydraulic analysis code RELAP5/MOD2. Some simulations of incidents were performed to verify the human model. It was found that AI-techniques used in the human model are suitable to simulate the operator's cognitive behavior in an NPP accident. The models of cognitive characteristics were investigated in the effects on simulated results of cognitive behaviors. (author)

  19. Towards a science of integrated AI and Robotics

    OpenAIRE

    Rajan, Kanna; Saffiotti, Alessandro

    2017-01-01

    The early promise of the impact of machine intelligence did not involve the partitioning of the nascent field of Artificial Intelligence. The founders of AI envisioned the notion of embedded intelligence as being conjoined between perception, reasoning and actuation. Yet over the years the fields of AI and Robotics drifted apart. Practitioners of AI focused on problems and algorithms abstracted from the real world. Roboticists, generally with a background in mechanical and electrical engineer...

  20. Artificial Intelligence (AI) Flight Advisor

    Data.gov (United States)

    National Aeronautics and Space Administration — This research effort applies Deep Learning to contingency management.   Many historic aircraft accidents would have been avoidable if the pilot had better diagnosis...

  1. Tweeting AI: Perceptions of Lay vs Expert Twitterati

    OpenAIRE

    Manikonda, Lydia; Kambhampati, Subbarao

    2017-01-01

    With the recent advancements in Artificial Intelligence (AI), various organizations and individuals are debating about the progress of AI as a blessing or a curse for the future of the society. This paper conducts an investigation on how the public perceives the progress of AI by utilizing the data shared on Twitter. Specifically, this paper performs a comparative analysis on the understanding of users belonging to two categories -- general AI-Tweeters (AIT) and expert AI-Tweeters (EAIT) who ...

  2. Diapo, applying advanced AI methods to diagnosis of PWR reactor coolant pump

    International Nuclear Information System (INIS)

    Porcheron, M.; Ricard, B.

    1993-01-01

    Electricite de France has decided to increase the capabilities of its monitoring and diagnostic architecture with the development of an AI system for reactor coolant pump diagnostic support. This development is carried out with the cooperation of the equipment constructor Jeumont Schneider Industries. This diagnostic system will eventually be included in an integrated surveillance architecture. We present the architecture of the system and the basics of the knowledge model used. Main data for diagnosis are provided by sensor data issued by the pump monitoring system. Diagnostic reasoning is based on the cooperation of two main activities : a heuristic search among typical symptomatic situations that leads to the formulation of hypotheses and a ''deep'' causal analysis that consists in backtracking from identified situations up to initial faults or causes. This approach is well fitted to field expert reasoning, and provides powerful diagnostic capabilities that help to overcome conventional limitations of expert systems entirely based on heuristic knowledge. (authors). 9 figs., 11 refs

  3. Hybrid intelligent optimization methods for engineering problems

    Science.gov (United States)

    Pehlivanoglu, Yasin Volkan

    quantification studies, we improved new mutation strategies and operators to provide beneficial diversity within the population. We called this new approach as multi-frequency vibrational GA or PSO. They were applied to different aeronautical engineering problems in order to study the efficiency of these new approaches. These implementations were: applications to selected benchmark test functions, inverse design of two-dimensional (2D) airfoil in subsonic flow, optimization of 2D airfoil in transonic flow, path planning problems of autonomous unmanned aerial vehicle (UAV) over a 3D terrain environment, 3D radar cross section minimization problem for a 3D air vehicle, and active flow control over a 2D airfoil. As demonstrated by these test cases, we observed that new algorithms outperform the current popular algorithms. The principal role of this multi-frequency approach was to determine which individuals or particles should be mutated, when they should be mutated, and which ones should be merged into the population. The new mutation operators, when combined with a mutation strategy and an artificial intelligent method, such as, neural networks or fuzzy logic process, they provided local and global diversities during the reproduction phases of the generations. Additionally, the new approach also introduced random and controlled diversity. Due to still being population-based techniques, these methods were as robust as the plain GA or PSO algorithms. Based on the results obtained, it was concluded that the variants of the present multi-frequency vibrational GA and PSO were efficient algorithms, since they successfully avoided all local optima within relatively short optimization cycles.

  4. The Relevance of AI Research to CAI.

    Science.gov (United States)

    Kearsley, Greg P.

    This article provides a tutorial introduction to Artificial Intelligence (AI) research for those involved in Computer Assisted Instruction (CAI). The general theme is that much of the current work in AI, particularly in the areas of natural language understanding systems, rule induction, programming languages, and socratic systems, has important…

  5. Applying intelligent statistical methods on biometric systems

    OpenAIRE

    Betschart, Willie

    2005-01-01

    This master’s thesis work was performed at Optimum Biometric Labs, OBL, located in Karlskrona, Sweden. Optimum Biometric Labs perform independent scenario evaluations to companies who develop biometric devices. The company has a product Optimum preConTM which is surveillance and diagnosis tool for biometric systems. This thesis work’s objective was to develop a conceptual model and implement it as an additional layer above the biometric layer with intelligence about the biometric users. The l...

  6. Monitoring of operation with artificial intelligence methods; Betriebsueberwachung mit Verfahren der Kuenstlichen Intelligenz

    Energy Technology Data Exchange (ETDEWEB)

    Bruenninghaus, H. [DMT-Gesellschaft fuer Forschung und Pruefung mbH, Essen (Germany). Geschaeftsbereich Systemtechnik

    1999-03-11

    Taking the applications `early detection of fires` and `reduction of burst of messages` as an example, the usability of artificial intelligence (AI) methods in the monitoring of operation was checked in a R and D project. The contribution describes the concept, development and evaluation of solutions to the specified problems. A platform, which made it possible to investigate different AI methods (in particular artificial neuronal networks), had to be creaated as a basis for the project. At the same time ventilation data had to be acquired and processed by the networks for the classification. (orig.) [Deutsch] Am Beispiel der Anwendungsfaelle `Brandfrueherkennung` und `Meldungsschauerreduzierung` wurde im Rahmen eines F+E-Vorhabens die Einsetzbarkeit von Kuenstliche-Intelligenz-Methoden (KI) in der Betriebsueberwachung geprueft. Der Beitrag stellt Konzeption, Entwicklung und Bewertung von Loesungsansaetzen fuer die genannten Aufgabenstellungen vor. Als Grundlage fuer das Vorhaben wurden anhand KI-Methoden (speziell: Kuenstliche Neuronale Netze -KNN) auf der Grundlage gewonnener und aufbereiteter Wetterdaten die Beziehungen zwischen den Wettermessstellen im Laufe des Wetterwegs klassifiziert. (orig.)

  7. Artificial intelligence in healthcare: past, present and future.

    Science.gov (United States)

    Jiang, Fei; Jiang, Yong; Zhi, Hui; Dong, Yi; Li, Hao; Ma, Sufeng; Wang, Yilong; Dong, Qiang; Shen, Haipeng; Wang, Yongjun

    2017-12-01

    Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI.

  8. Artificial intelligence in healthcare: past, present and future

    Science.gov (United States)

    Jiang, Fei; Jiang, Yong; Zhi, Hui; Dong, Yi; Li, Hao; Ma, Sufeng; Wang, Yilong; Dong, Qiang; Shen, Haipeng; Wang, Yongjun

    2017-01-01

    Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI. PMID:29507784

  9. 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.

  10. Artificial Intelligence in Autonomous Telescopes

    Science.gov (United States)

    Mahoney, William; Thanjavur, Karun

    2011-03-01

    Artificial Intelligence (AI) is key to the natural evolution of today's automated telescopes to fully autonomous systems. Based on its rapid development over the past five decades, AI offers numerous, well-tested techniques for knowledge based decision making essential for real-time telescope monitoring and control, with minimal - and eventually no - human intervention. We present three applications of AI developed at CFHT for monitoring instantaneous sky conditions, assessing quality of imaging data, and a prototype for scheduling observations in real-time. Closely complementing the current remote operations at CFHT, we foresee further development of these methods and full integration in the near future.

  11. 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)

  12. A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

    Science.gov (United States)

    Wang, Wen-Chuan; Chau, Kwok-Wing; Cheng, Chun-Tian; Qiu, Lin

    2009-08-01

    SummaryDeveloping a hydrological forecasting model based on past records is crucial to effective hydropower reservoir management and scheduling. Traditionally, time series analysis and modeling is used for building mathematical models to generate hydrologic records in hydrology and water resources. Artificial intelligence (AI), as a branch of computer science, is capable of analyzing long-series and large-scale hydrological data. In recent years, it is one of front issues to apply AI technology to the hydrological forecasting modeling. In this paper, autoregressive moving-average (ARMA) models, artificial neural networks (ANNs) approaches, adaptive neural-based fuzzy inference system (ANFIS) techniques, genetic programming (GP) models and support vector machine (SVM) method are examined using the long-term observations of monthly river flow discharges. The four quantitative standard statistical performance evaluation measures, the coefficient of correlation ( R), Nash-Sutcliffe efficiency coefficient ( E), root mean squared error (RMSE), mean absolute percentage error (MAPE), are employed to evaluate the performances of various models developed. Two case study river sites are also provided to illustrate their respective performances. The results indicate that the best performance can be obtained by ANFIS, GP and SVM, in terms of different evaluation criteria during the training and validation phases.

  13. Intelligent methods for data retrieval in fusion databases

    International Nuclear Information System (INIS)

    Vega, J.

    2008-01-01

    The plasma behaviour is identified through the recognition of patterns inside signals. The search for patterns is usually a manual and tedious procedure in which signals need to be examined individually. A breakthrough in data retrieval for fusion databases is the development of intelligent methods to search for patterns. A pattern (in the broadest sense) could be a single segment of a waveform, a set of pixels within an image or even a heterogeneous set of features made up of waveforms, images and any kind of experimental data. Intelligent methods will allow searching for data according to technical, scientific and structural criteria instead of an identifiable time interval or pulse number. Such search algorithms should be intelligent enough to avoid passing over the entire database. Benefits of such access methods are discussed and several available techniques are reviewed. In addition, the applicability of the methods from general purpose searching systems to ad hoc developments is covered

  14. Os efeitos do método Ai Chi em pacientes portadoras da síndrome fibromiálgica The effect of Ai Chi method in fybromialgic patients

    Directory of Open Access Journals (Sweden)

    Jacqueline Soares de Santana

    2010-06-01

    Full Text Available O objetivo do estudo é demonstrar os efeitos do método Ai Chi como forma alternativa de abordagem hidroterapêutica em pacientes portadoras da síndrome fibromiálgica. Foram estudados dez pacientes; quatro fizeram parte do grupo experimento e cinco, do grupo controle, com uma desistência. As pacientes foram avaliadas através do Questionário de Impacto da Fibromialgia (QIF e da Escala de Intensidade e Índice de dor nos Pontos Sensíveis. Foram realizadas duas avaliações, uma antes e outra após o tratamento. As pacientes foram submetidas a dez sessões do método Ai Chi, com duração de quarenta minutos. Houve melhora na intensidade da dor, de acordo com a escala da intensidade de dor nos pontos sensíveis, após a intervenção; já a qualidade de vida manteve-se sem alteração. Na qualidade de vida, observou-se que os grupos obtiveram resultados semelhantes; isso se deve ao fato que as pacientes não apresentaram melhora no seu estado depressivo. No índice dos pontos sensíveis, verificou-se diferença entre os grupos. A explicação para essa diferença deve-se possivelmente aos benefícios da imersão em água aquecida e aos efeitos do método Ai Chi. Não houve diferença significativa entre os grupos, o que pode ser atribuído às limitações do estudo. Desta forma, torna-se relevante a realização de novos estudos referentes à aplicação do método Ai Chi em pacientes portadoras da síndrome fibromiálgica.The objective of this article is to show the effect of the Ai Chi method, as an alternative form of hydrotherapeutic approach in fibromyalgia syndrome patients. Ten patients were studied, four were part of the experiment group and five of the control group, with one desistance. The patients were evaluated through the Fibromyalgia Impact Questionnaire (QIF and Scale of Intensity and Index of pain in Sensible Points. Two evaluations were performed, before and after the treatment. The patients were submitted to ten sessions

  15. SMARTER THAN YOUR AVERAGE SENSOR: AIS SENSOR THAT INTELLIGENTLY RE-TRANSMITS MEANINGFUL INFORMATION DERIVED FROM RAWAIS DATA IN NETWORK LIMITED AREAS

    Directory of Open Access Journals (Sweden)

    R. G. V. Meyer

    2017-11-01

    Full Text Available AIS is a transponder based, anti-collision system used by the majority of ocean traffic. Ships regularly transmit their identity, position and speed. The information used to populate the AIS fields come from ship based sensors, such as GPS, and user populated fields, such as the vessels name and MMSI number. These fields are susceptible to spoofing and can be changed to hide the identity or location of a vessel. This is often done to disguise the vessel as a different class to avoid inspections or to enter a protected area without raising alarms. The AIS system has found great utility in monitoring global shipping trends and traffic but this was never intended when the protocol was designed. Docked vessels still transmit messages regularly that contain no new information. These, and other redundant messages, are still transmitted and stored. In situations where a sensor is remote and has limited access to the Internet this can become costly. The Smart-AIS sensor records all incoming messages locally and makes a decision on whether the message is of special interest or not. Messages of interest are re-transmitted to an external AIS database.

  16. 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.

  17. AI-guided parameter optimization in inverse treatment planning

    International Nuclear Information System (INIS)

    Yan Hui; Yin Fangfang; Guan Huaiqun; Kim, Jae Ho

    2003-01-01

    An artificial intelligence (AI)-guided inverse planning system was developed to optimize the combination of parameters in the objective function for intensity-modulated radiation therapy (IMRT). In this system, the empirical knowledge of inverse planning was formulated with fuzzy if-then rules, which then guide the parameter modification based on the on-line calculated dose. Three kinds of parameters (weighting factor, dose specification, and dose prescription) were automatically modified using the fuzzy inference system (FIS). The performance of the AI-guided inverse planning system (AIGIPS) was examined using the simulated and clinical examples. Preliminary results indicate that the expected dose distribution was automatically achieved using the AI-guided inverse planning system, with the complicated compromising between different parameters accomplished by the fuzzy inference technique. The AIGIPS provides a highly promising method to replace the current trial-and-error approach

  18. Artificial intelligence in radiology.

    Science.gov (United States)

    Hosny, Ahmed; Parmar, Chintan; Quackenbush, John; Schwartz, Lawrence H; Aerts, Hugo J W L

    2018-05-17

    Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Historically, in radiology practice, trained physicians visually assessed medical images for the detection, characterization and monitoring of diseases. AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics. In this Opinion article, we establish a general understanding of AI methods, particularly those pertaining to image-based tasks. We explore how these methods could impact multiple facets of radiology, with a general focus on applications in oncology, and demonstrate ways in which these methods are advancing the field. Finally, we discuss the challenges facing clinical implementation and provide our perspective on how the domain could be advanced.

  19. Artificial Intelligence Techniques and Methodology

    OpenAIRE

    Carbonell, Jaime G.; Sleeman, Derek

    1982-01-01

    Two closely related aspects of artificial intelligence that have received comparatively little attention in the recent literature are research methodology, and the analysis of computational techniques that span multiple application areas. We believe both issues to be increasingly significant as Artificial Intelligence matures into a science and spins off major application efforts. It is imperative to analyze the repertoire of AI methods with respect to past experience, utility in new domains,...

  20. Humans and Machines in the Evolution of AI in Korea

    OpenAIRE

    Zhang, Byoung-Tak

    2016-01-01

    Artificial intelligence in Korea is currently prospering. The media is regularly reporting AI-enabled products such as smart advisors, personal robots, autonomous cars, and human-level intelligence machines. The IT industry is investing in deep learning and AI to maintain the global competitive edge in their services and products. The Ministry of Science, ICT, and Future Planning (MSIP) has launched new funding programs in AI and cognitive science to implement the government’s newly adopted e...

  1. ORTHO IMAGE AND DTM GENERATION WITH INTELLIGENT METHODS

    Directory of Open Access Journals (Sweden)

    H. Bagheri

    2013-10-01

    Finally the artificial intelligence methods, like genetic algorithms as well as neural networks, were examined on sample data for optimizing interpolation and for generating Digital Terrain Models. The results then were compared with existing conventional methods and it appeared that these methods have a high capacity in heights interpolation and that using these networks for interpolating and optimizing the weighting methods based on inverse distance leads to a high accurate estimation of heights.

  2. Ortho Image and DTM Generation with Intelligent Methods

    Science.gov (United States)

    Bagheri, H.; Sadeghian, S.

    2013-10-01

    Nowadays the artificial intelligent algorithms has considered in GIS and remote sensing. Genetic algorithm and artificial neural network are two intelligent methods that are used for optimizing of image processing programs such as edge extraction and etc. these algorithms are very useful for solving of complex program. In this paper, the ability and application of genetic algorithm and artificial neural network in geospatial production process like geometric modelling of satellite images for ortho photo generation and height interpolation in raster Digital Terrain Model production process is discussed. In first, the geometric potential of Ikonos-2 and Worldview-2 with rational functions, 2D & 3D polynomials were tested. Also comprehensive experiments have been carried out to evaluate the viability of the genetic algorithm for optimization of rational function, 2D & 3D polynomials. Considering the quality of Ground Control Points, the accuracy (RMSE) with genetic algorithm and 3D polynomials method for Ikonos-2 Geo image was 0.508 pixel sizes and the accuracy (RMSE) with GA algorithm and rational function method for Worldview-2 image was 0.930 pixel sizes. For more another optimization artificial intelligent methods, neural networks were used. With the use of perceptron network in Worldview-2 image, a result of 0.84 pixel sizes with 4 neurons in middle layer was gained. The final conclusion was that with artificial intelligent algorithms it is possible to optimize the existing models and have better results than usual ones. Finally the artificial intelligence methods, like genetic algorithms as well as neural networks, were examined on sample data for optimizing interpolation and for generating Digital Terrain Models. The results then were compared with existing conventional methods and it appeared that these methods have a high capacity in heights interpolation and that using these networks for interpolating and optimizing the weighting methods based on inverse

  3. Monitoring severe accidents using AI techniques

    International Nuclear Information System (INIS)

    No, Young Gyu; Ahn, Kwang Il; Kim, Ju Hyun; Na, Man Gyun; Lim, Dong Hyuk

    2012-01-01

    After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.

  4. Monitoring severe accidents using AI techniques

    Energy Technology Data Exchange (ETDEWEB)

    No, Young Gyu; Ahn, Kwang Il [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Kim, Ju Hyun; Na, Man Gyun [Dept. of Nuclear Engineering, Chosun University, Gwangju (Korea, Republic of); Lim, Dong Hyuk [Korea Institute of Nuclear Nonproliferation and Control, Daejon (Korea, Republic of)

    2012-05-15

    After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.

  5. AI in space: Past, present, and possible futures

    Science.gov (United States)

    Rose, Donald D.; Post, Jonathan V.

    1992-01-01

    While artificial intelligence (AI) has become increasingly present in recent space applications, new missions being planned will require even more incorporation of AI techniques. In this paper, we survey some of the progress made to date in implementing such programs, some current directions and issues, and speculate about the future of AI in space scenarios. We also provide examples of how thinkers from the realm of science fiction have envisioned AI's role in various aspects of space exploration.

  6. Short-term electric load forecasting using computational intelligence methods

    OpenAIRE

    Jurado, Sergio; Peralta, J.; Nebot, Àngela; Mugica, Francisco; Cortez, Paulo

    2013-01-01

    Accurate time series forecasting is a key issue to support individual and organizational decision making. In this paper, we introduce several methods for short-term electric load forecasting. All the presented methods stem from computational intelligence techniques: Random Forest, Nonlinear Autoregressive Neural Networks, Evolutionary Support Vector Machines and Fuzzy Inductive Reasoning. The performance of the suggested methods is experimentally justified with several experiments carried out...

  7. AI/OR computational model for integrating qualitative and quantitative design methods

    Science.gov (United States)

    Agogino, Alice M.; Bradley, Stephen R.; Cagan, Jonathan; Jain, Pramod; Michelena, Nestor

    1990-01-01

    A theoretical framework for integrating qualitative and numerical computational methods for optimally-directed design is described. The theory is presented as a computational model and features of implementations are summarized where appropriate. To demonstrate the versatility of the methodology we focus on four seemingly disparate aspects of the design process and their interaction: (1) conceptual design, (2) qualitative optimal design, (3) design innovation, and (4) numerical global optimization.

  8. Present status of application of AI in nuclear industry

    International Nuclear Information System (INIS)

    Kitamura, Masaharu

    1989-01-01

    Artificial intelligence (AL) techniques have been introduced actively in the nuclear industry in pursuit of increased safety and efficiency. The present report outlines some AI techniques currently used in nuclear facilities. This type of techniques have increasingly been introduced to such areas as design, construction, operation, maintenance, quality control and analysis. Most of them use knowledge engineering techniques including expert systems. Positive efforts at research and application of various more advance AI techniaues have started recently. For application of AI techniques, activities in nuclear power plants can be divided into two groups. One includes 'analytical' activities such as operation, maintenance and analysis, while the other includes 'synthetic' activities such as design, construction and fuel control. The most important AI technology for the analytical activities is diagnosis. Thus the report outlines major processes to which diagnostic techniques are applicable, and knowledge description and inference methods used for diagnosis. For AI techniques for synthetic activities, some problems and possible solutions are addressed. Development efforts in and outside Japan are also outlined. (Nogami, K.)

  9. Discovering Knowledge from AIS Database for Application in VTS

    Science.gov (United States)

    Tsou, Ming-Cheng

    The widespread use of the Automatic Identification System (AIS) has had a significant impact on maritime technology. AIS enables the Vessel Traffic Service (VTS) not only to offer commonly known functions such as identification, tracking and monitoring of vessels, but also to provide rich real-time information that is useful for marine traffic investigation, statistical analysis and theoretical research. However, due to the rapid accumulation of AIS observation data, the VTS platform is often unable quickly and effectively to absorb and analyze it. Traditional observation and analysis methods are becoming less suitable for the modern AIS generation of VTS. In view of this, we applied the same data mining technique used for business intelligence discovery (in Customer Relation Management (CRM) business marketing) to the analysis of AIS observation data. This recasts the marine traffic problem as a business-marketing problem and integrates technologies such as Geographic Information Systems (GIS), database management systems, data warehousing and data mining to facilitate the discovery of hidden and valuable information in a huge amount of observation data. Consequently, this provides the marine traffic managers with a useful strategic planning resource.

  10. 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.

  11. Artificial neural network intelligent method for prediction

    Science.gov (United States)

    Trifonov, Roumen; Yoshinov, Radoslav; Pavlova, Galya; Tsochev, Georgi

    2017-09-01

    Accounting and financial classification and prediction problems are high challenge and researchers use different methods to solve them. Methods and instruments for short time prediction of financial operations using artificial neural network are considered. The methods, used for prediction of financial data as well as the developed forecasting system with neural network are described in the paper. The architecture of a neural network used four different technical indicators, which are based on the raw data and the current day of the week is presented. The network developed is used for forecasting movement of stock prices one day ahead and consists of an input layer, one hidden layer and an output layer. The training method is algorithm with back propagation of the error. The main advantage of the developed system is self-determination of the optimal topology of neural network, due to which it becomes flexible and more precise The proposed system with neural network is universal and can be applied to various financial instruments using only basic technical indicators as input data.

  12. 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.

  13. 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.

  14. 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…

  15. AI Based Personal Learning Environments: Directions for Long Term Research. AI Memo 384.

    Science.gov (United States)

    Goldstein, Ira P.; Miller, Mark L.

    The application of artificial intelligence (AI) techniques to the design of personal learning environments is an enterprise of both theoretical and practical interest. In the short term, the process of developing and testing intelligent tutoring programs serves as a new experimental vehicle for exploring alternative cognitive and pedagogical…

  16. Intelligent numerical methods applications to fractional calculus

    CERN Document Server

    Anastassiou, George A

    2016-01-01

    In this monograph the authors present Newton-type, Newton-like and other numerical methods, which involve fractional derivatives and fractional integral operators, for the first time studied in the literature. All for the purpose to solve numerically equations whose associated functions can be also non-differentiable in the ordinary sense. That is among others extending the classical Newton method theory which requires usual differentiability of function. Chapters are self-contained and can be read independently and several advanced courses can be taught out of this book. An extensive list of references is given per chapter. The book’s results are expected to find applications in many areas of applied mathematics, stochastics, computer science and engineering. As such this monograph is suitable for researchers, graduate students, and seminars of the above subjects, also to be in all science and engineering libraries.

  17. Comparison of methods for estimating premorbid intelligence

    OpenAIRE

    Bright, Peter; van der Linde, Ian

    2018-01-01

    To evaluate impact of neurological injury on cognitive performance it is typically necessary to derive a baseline (or ‘premorbid’) estimate of a patient’s general cognitive ability prior to the onset of impairment. In this paper, we consider a range of common methods for producing this estimate, including those based on current best performance, embedded ‘hold/no hold’ tests, demographic information, and word reading ability. Ninety-two neurologically healthy adult participants were assessed ...

  18. 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

  19. Method of dynamic fuzzy symptom vector in intelligent diagnosis

    International Nuclear Information System (INIS)

    Sun Hongyan; Jiang Xuefeng

    2010-01-01

    Aiming at the requirement of diagnostic symptom real-time updating brought from diagnostic knowledge accumulation and great gap in unit and value of diagnostic symptom in multi parameters intelligent diagnosis, the method of dynamic fuzzy symptom vector is proposed. The concept of dynamic fuzzy symptom vector is defined. Ontology is used to specify the vector elements, and the vector transmission method based on ontology is built. The changing law of symptom value is analyzed and fuzzy normalization method based on fuzzy membership functions is built. An instance proved method of dynamic fussy symptom vector is efficient to solve the problems of symptom updating and unify of symptom value and unit. (authors)

  20. Event classification and optimization methods using artificial intelligence and other relevant techniques: Sharing the experiences

    Science.gov (United States)

    Mohamed, Abdul Aziz; Hasan, Abu Bakar; Ghazali, Abu Bakar Mhd.

    2017-01-01

    Classification of large data into respected classes or groups could be carried out with the help of artificial intelligence (AI) tools readily available in the market. To get the optimum or best results, optimization tool could be applied on those data. Classification and optimization have been used by researchers throughout their works, and the outcomes were very encouraging indeed. Here, the authors are trying to share what they have experienced in three different areas of applied research.

  1. Deep into the Brain: Artificial Intelligence in Stroke Imaging.

    Science.gov (United States)

    Lee, Eun-Jae; Kim, Yong-Hwan; Kim, Namkug; Kang, Dong-Wha

    2017-09-01

    Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AI techniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives.

  2. AI Researchers, Video Games Are Your Friends!

    OpenAIRE

    Togelius, Julian

    2016-01-01

    If you are an artificial intelligence researcher, you should look to video games as ideal testbeds for the work you do. If you are a video game developer, you should look to AI for the technology that makes completely new types of games possible. This chapter lays out the case for both of these propositions. It asks the question "what can video games do for AI", and discusses how in particular general video game playing is the ideal testbed for artificial general intelligence research. It the...

  3. [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.

  4. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

  5. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-03-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

  6. 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)

  7. Advanced Applications of Neural Networks and Artificial Intelligence: A Review

    OpenAIRE

    Koushal Kumar; Gour Sundar Mitra Thakur

    2012-01-01

    Artificial Neural Network is a branch of Artificial intelligence and has been accepted as a new computing technology in computer science fields. This paper reviews the field of Artificial intelligence and focusing on recent applications which uses Artificial Neural Networks (ANN’s) and Artificial Intelligence (AI). It also considers the integration of neural networks with other computing methods Such as fuzzy logic to enhance the interpretation ability of data. Artificial Neural Networks is c...

  8. 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)

  9. 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.

  10. 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.

  11. 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…

  12. #%Applications of artificial intelligence in intelligent manufacturing: a review

    Institute of Scientific and Technical Information of China (English)

    #

    2017-01-01

    #%Based on research into the applications of artificial intelligence (AI) technology in the manufacturing industry in recent years, we analyze the rapid development of core technologies in the new era of 'Internet plus AI', which is triggering a great change in the models, means, and ecosystems of the manufacturing industry, as well as in the development of AI. We then propose new models, means, and forms of intelligent manufacturing, intelligent manufacturing system architecture, and intelligent man-ufacturing technology system, based on the integration of AI technology with information communications, manufacturing, and related product technology. Moreover, from the perspectives of intelligent manufacturing application technology, industry, and application demonstration, the current development in intelligent manufacturing is discussed. Finally, suggestions for the appli-cation of AI in intelligent manufacturing in China are presented.

  13. Monitoring Severe Accidents Using AI Techniques

    International Nuclear Information System (INIS)

    No, Young Gyu; Kim, Ju Hyun; Na, Man Gyun; Ahn, Kwang Il

    2011-01-01

    It is very difficult for nuclear power plant operators to monitor and identify the major severe accident scenarios following an initiating event by staring at temporal trends of important parameters. The objective of this study is to develop and verify the monitoring for severe accidents using artificial intelligence (AI) techniques such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH) and fuzzy neural network (FNN). The SVC and PNN are used for event classification among the severe accidents. Also, GMDH and FNN are used to monitor for severe accidents. The inputs to AI techniques are initial time-integrated values obtained by integrating measurement signals during a short time interval after reactor scram. In this study, 3 types of initiating events such as the hot-leg LOCA, the cold-leg LOCA and SGTR are considered and it is verified how well the proposed scenario identification algorithm using the GMDH and FNN models identifies the timings when the reactor core will be uncovered, when CET will exceed 1200 .deg. F and when the reactor vessel will fail. In cases that an initiating event develops into a severe accident, the proposed algorithm showed accurate classification of initiating events. Also, it well predicted timings for important occurrences during severe accident progression scenarios, which is very helpful for operators to perform severe accident management

  14. Subspace methods for pattern recognition in intelligent environment

    CERN Document Server

    Jain, Lakhmi

    2014-01-01

    This research book provides a comprehensive overview of the state-of-the-art subspace learning methods for pattern recognition in intelligent environment. With the fast development of internet and computer technologies, the amount of available data is rapidly increasing in our daily life. How to extract core information or useful features is an important issue. Subspace methods are widely used for dimension reduction and feature extraction in pattern recognition. They transform a high-dimensional data to a lower-dimensional space (subspace), where most information is retained. The book covers a broad spectrum of subspace methods including linear, nonlinear and multilinear subspace learning methods and applications. The applications include face alignment, face recognition, medical image analysis, remote sensing image classification, traffic sign recognition, image clustering, super resolution, edge detection, multi-view facial image synthesis.

  15. Discussion on AI Technology in Information Library Design

    OpenAIRE

    日比野, 省三; Shozo, HIBINO; 中京大学社会学部

    1987-01-01

    This paper deals with the discussion on the importance of AI (Artificial Intelligence) Technology in planning and designing a library information system in the near future. First of all, the history of Library and Information Science is reviewed and it is identified that the key technology in the future library will be AI as a mega-trend. After reviewing the concepts of AI technology, a model of a Knowledge-Base system is discussed as a case study, using micro-PROLOG.

  16. An Immune Agent for Web-Based AI Course

    Science.gov (United States)

    Gong, Tao; Cai, Zixing

    2006-01-01

    To overcome weakness and faults of a web-based e-learning course such as Artificial Intelligence (AI), an immune agent was proposed, simulating a natural immune mechanism against a virus. The immune agent was built on the multi-dimension education agent model and immune algorithm. The web-based AI course was comprised of many files, such as HTML…

  17. SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS

    Directory of Open Access Journals (Sweden)

    V. Panteleev Andrei

    2017-01-01

    Full Text Available An important stage in problem solving process for aerospace and aerostructures designing is calculating their main charac- teristics optimization. The results of the four constrained optimization problems related to the design of various technical systems: such as determining the best parameters of welded beams, pressure vessel, gear, spring are presented. The purpose of each task is to minimize the cost and weight of the construction. The object functions in optimization practical problem are nonlinear functions with a lot of variables and a complex layer surface indentations. That is why using classical approach for extremum seeking is not efficient. Here comes the necessity of using such methods of optimization that allow to find a near optimal solution in acceptable amount of time with the minimum waste of computer power. Such methods include the methods of Swarm Intelligence: spiral dy- namics algorithm, stochastic diffusion search, hybrid seeker optimization algorithm. The Swarm Intelligence methods are designed in such a way that a swarm consisting of agents carries out the search for extremum. In search for the point of extremum, the parti- cles exchange information and consider their experience as well as the experience of population leader and the neighbors in some area. To solve the listed problems there has been designed a program complex, which efficiency is illustrated by the solutions of four applied problems. Each of the considered applied optimization problems is solved with all the three chosen methods. The ob- tained numerical results can be compared with the ones found in a swarm with a particle method. The author gives recommenda- tions on how to choose methods parameters and penalty function value, which consider inequality constraints.

  18. AVID Students' Perceptions of Intelligence: A Mixed Methods Study

    Science.gov (United States)

    Becker, John Darrell

    2012-01-01

    Students' perceptions of intelligence have been shown to have an effect on learning. Students who see intelligence as something that can be developed, those with a growth mindset, often experience academic success, while those who perceive intelligence to be a fixed entity are typically less likely to take on challenging learning experiences and…

  19. Estimation of mechanical properties of nanomaterials using artificial intelligence methods

    Science.gov (United States)

    Vijayaraghavan, V.; Garg, A.; Wong, C. H.; Tai, K.

    2014-09-01

    Computational modeling tools such as molecular dynamics (MD), ab initio, finite element modeling or continuum mechanics models have been extensively applied to study the properties of carbon nanotubes (CNTs) based on given input variables such as temperature, geometry and defects. Artificial intelligence techniques can be used to further complement the application of numerical methods in characterizing the properties of CNTs. In this paper, we have introduced the application of multi-gene genetic programming (MGGP) and support vector regression to formulate the mathematical relationship between the compressive strength of CNTs and input variables such as temperature and diameter. The predictions of compressive strength of CNTs made by these models are compared to those generated using MD simulations. The results indicate that MGGP method can be deployed as a powerful method for predicting the compressive strength of the carbon nanotubes.

  20. 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…

  1. Artificial Intelligence Techniques Applications for Power Disturbances Classification

    OpenAIRE

    K.Manimala; Dr.K.Selvi; R.Ahila

    2008-01-01

    Artificial Intelligence (AI) methods are increasingly being used for problem solving. This paper concerns using AI-type learning machines for power quality problem, which is a problem of general interest to power system to provide quality power to all appliances. Electrical power of good quality is essential for proper operation of electronic equipments such as computers and PLCs. Malfunction of such equipment may lead to loss of production or disruption of critical services resulting in huge...

  2. 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)

  3. Reflection on robotic intelligence

    NARCIS (Netherlands)

    Bartneck, C.

    2006-01-01

    This paper reflects on the development or robots, both their physical shape as well as their intelligence. The later strongly depends on the progress made in the artificial intelligence (AI) community which does not yet provide the models and tools necessary to create intelligent robots. It is time

  4. 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 ...

  5. 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.

  6. AI, automation and the Flight Telerobotic Servicer

    Science.gov (United States)

    Goforth, Andre; Dominy, Robert

    1988-01-01

    A NASA study for the preliminary definition of a teleoperated robotic device has been recently completed. The Fligt Telerobotic Servicer (FTS) will be used to assist astronauts in many of the on-board tasks of assembly, maintenance, servicing, and inspection of the Space Station. The role of artificial intelligence (AI) in furthering the FTS automation capabilities and, hence, extending its capacity for growth and evolution is discussed. Relevant system engineering issues are identified, and an approach for insertion of AI technology is presented in terms of the NASA/NBS Standard Reference Model control architecture NASREM.

  7. Cyclotron operating mode determination based on intelligent methods

    International Nuclear Information System (INIS)

    Ouda, M.M.E.M.

    2011-01-01

    Particle accelerators are generators that produce beams of charged particles with energies depending on the accelerator type. The MGC-20 cyclotron is a cyclic particle accelerator used for accelerating protons, deuterons, alpha particles, and helium-3 to different energies. Main applications are isotopes production, nuclear reactions studies, and mass spectroscopy studies and other industrial applications. The cyclotron is a complicated machine depends on using a strong magnetic field and high frequency-high voltage electric field together to accelerate and bend charged particles inside the accelerating chamber. It consists of the following main parts, the radio frequency system, the main magnet with the auxiliary concentric and harmonic coils, the electrostatic deflector, and the ion source, the beam transport system, and high precision and high stability DC power supplies.To accelerate a particle to certain energy, one has to adjust the cyclotron operating parameters to be suitable to accelerate this particle to that energy. If the cyclotron operating parameters together are adjusted to accelerate a charged particle to certain energy, then these parameters together are named the operating mode to accelerate this particle to that energy. For example the operating mode to accelerate protons to 18 MeV is named the (18 MeV protons operating mode). The operating mode includes many parameters that must be adjusted together to be successful to accelerate, extract, focus, steer a particle from the ion source to the experiment. Due to the big number of parameters in the operating modes, 19 parameters have been selected in this thesis to be used in an intelligent system based on feed forward back propagation neural network to determine the parameters for new operating modes. The new intelligent system depends on the available information about the currently used operating modes.The classic way to determine a new operating mode was depending on trial and error method to

  8. New trends in computational collective intelligence

    CERN Document Server

    Kim, Sang-Wook; Trawiński, Bogdan

    2015-01-01

    This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods an...

  9. Artificial Intelligence: The Expert Way.

    Science.gov (United States)

    Bitter, Gary G.

    1989-01-01

    Discussion of artificial intelligence (AI) and expert systems focuses on their use in education. Characteristics of good expert systems are explained; computer software programs that contain applications of AI are described, highlighting one used to help educators identify learning-disabled students; and the future of AI is discussed. (LRW)

  10. 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.  .

  11. On how AI & Law can help autonomous systems obey the law: a position paper

    NARCIS (Netherlands)

    Prakken, Hendrik

    2016-01-01

    In this position paper I discuss to what extent current and past AI & law research is relevant for research on autonomous intelligent systems that exhibit legally relevant behaviour. After a brief review of the history of AI & law, I will compare the problems faced by autonomous intelligent systems

  12. Using design science and artificial intelligence to improve health communication: ChronologyMD case example.

    Science.gov (United States)

    Neuhauser, Linda; Kreps, Gary L; Morrison, Kathleen; Athanasoulis, Marcos; Kirienko, Nikolai; Van Brunt, Deryk

    2013-08-01

    This paper describes how design science theory and methods and use of artificial intelligence (AI) components can improve the effectiveness of health communication. We identified key weaknesses of traditional health communication and features of more successful eHealth/AI communication. We examined characteristics of the design science paradigm and the value of its user-centered methods to develop eHealth/AI communication. We analyzed a case example of the participatory design of AI components in the ChronologyMD project intended to improve management of Crohn's disease. eHealth/AI communication created with user-centered design shows improved relevance to users' needs for personalized, timely and interactive communication and is associated with better health outcomes than traditional approaches. Participatory design was essential to develop ChronologyMD system architecture and software applications that benefitted patients. AI components can greatly improve eHealth/AI communication, if designed with the intended audiences. Design science theory and its iterative, participatory methods linked with traditional health communication theory and methods can create effective AI health communication. eHealth/AI communication researchers, developers and practitioners can benefit from a holistic approach that draws from theory and methods in both design sciences and also human and social sciences to create successful AI health communication. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  13. Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

  14. Applications of artificial intelligence to reactor and plant control

    International Nuclear Information System (INIS)

    Bernard, J.A.

    1989-01-01

    Potential improvements in plant efficiency and reliability are often cited as reasons for developing and applying artificial intelligence (AI) techniques, principally expert systems, to the control and operation of nuclear reactors. Nevertheless, there have been few such applications and then mostly at the prototype level. Therefore, if AI techniques are to contribute to process control, methods must be identified by which rule-based and analytic approaches can be merged. This hypothesis is the basic premise of this article. Presented below are 1. a brief review of the human approach towards process control, 2. a discussion of the suitability of AI methodologies for the performance of control tasks, 3. examples of AI applications to both open- and closed-loop control, 4. an enumeration of unresolved issues associated with the use of AI for control, and 5. a discussion of the possible role of expert system techniques in process control. (orig./GL)

  15. Launch vehicle operations cost reduction through artificial intelligence techniques

    Science.gov (United States)

    Davis, Tom C., Jr.

    1988-01-01

    NASA's Kennedy Space Center has attempted to develop AI methods in order to reduce the cost of launch vehicle ground operations as well as to improve the reliability and safety of such operations. Attention is presently given to cost savings estimates for systems involving launch vehicle firing-room software and hardware real-time diagnostics, as well as the nature of configuration control and the real-time autonomous diagnostics of launch-processing systems by these means. Intelligent launch decisions and intelligent weather forecasting are additional applications of AI being considered.

  16. Intelligent Search Method Based ACO Techniques for a Multistage Decision Problem EDP/LFP

    Directory of Open Access Journals (Sweden)

    Mostefa RAHLI

    2006-07-01

    Full Text Available The implementation of a numerical library of calculation based optimization in electrical supply networks area is in the centre of the current research orientations, thus, our project in a form given is centred on the development of platform NMSS1. It's a software environment which will preserve many efforts as regards calculations of charge, smoothing curves, losses calculation and economic planning of the generated powers [23].The operational research [17] in a hand and the industrial practice in the other, prove that the means and processes of simulation reached a level of very appreciable reliability and mathematical confidence [4, 5, 14]. It is of this expert observation that many processes make confidence to the results of simulation.The handicaps of this approach or methodology are that it makes base its judgments and handling on simplified assumptions and constraints whose influence was deliberately neglected to be added to the cost to spend [14].By juxtaposing the methods of simulation with artificial intelligence techniques, gathering set of numerical methods acquires an optimal reliability whose assurance can not leave doubt.Software environment NMSS [23] can be a in the field of the rallying techniques of simulation and electric network calculation via a graphic interface. In the same software integrate an AI capability via a module expert system.Our problem is a multistage case where are completely dependant and can't be performed separately.For a multistage problem [21, 22], the results obtained from a credible (large size problem calculation, makes the following question: Could choice of numerical methods set make the calculation of a complete problem using more than two treatments levels, a total error which will be the weakest one possible? It is well-known according to algorithmic policy; each treatment can be characterized by a function called mathematical complexity. This complexity is in fact a coast (a weight overloading

  17. 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

  18. Elementary epistemological features of machine intelligence

    OpenAIRE

    Horvat, Marko

    2008-01-01

    Theoretical analysis of machine intelligence (MI) is useful for defining a common platform in both theoretical and applied artificial intelligence (AI). The goal of this paper is to set canonical definitions that can assist pragmatic research in both strong and weak AI. Described epistemological features of machine intelligence include relationship between intelligent behavior, intelligent and unintelligent machine characteristics, observable and unobservable entities and classification of in...

  19. Artificial Intelligence: Bayesian versus Heuristic Method for Diagnostic Decision Support.

    Science.gov (United States)

    Elkin, Peter L; Schlegel, Daniel R; Anderson, Michael; Komm, Jordan; Ficheur, Gregoire; Bisson, Leslie

    2018-04-01

    Evoking strength is one of the important contributions of the field of Biomedical Informatics to the discipline of Artificial Intelligence. The University at Buffalo's Orthopedics Department wanted to create an expert system to assist patients with self-diagnosis of knee problems and to thereby facilitate referral to the right orthopedic subspecialist. They had two independent sports medicine physicians review 469 cases. A board-certified orthopedic sports medicine practitioner, L.B., reviewed any disagreements until a gold standard diagnosis was reached. For each case, the patients entered 126 potential answers to 26 questions into a Web interface. These were modeled by an expert sports medicine physician and the answers were reviewed by L.B. For each finding, the clinician specified the sensitivity (term frequency) and both specificity (Sp) and the heuristic evoking strength (ES). Heuristics are methods of reasoning with only partial evidence. An expert system was constructed that reflected the posttest odds of disease-ranked list for each case. We compare the accuracy of using Sp to that of using ES (original model, p  < 0.0008; term importance * disease importance [DItimesTI] model, p  < 0.0001: Wilcoxon ranked sum test). For patient referral assignment, Sp in the DItimesTI model was superior to the use of ES. By the fifth diagnosis, the advantage was lost and so there is no difference between the techniques when serving as a reminder system. Schattauer GmbH Stuttgart.

  20. Using artificial intelligence methods to design new conducting polymers

    Directory of Open Access Journals (Sweden)

    Ronaldo Giro

    2003-12-01

    Full Text Available In the last years the possibility of creating new conducting polymers exploring the concept of copolymerization (different structural monomeric units has attracted much attention from experimental and theoretical points of view. Due to the rich carbon reactivity an almost infinite number of new structures is possible and the procedure of trial and error has been the rule. In this work we have used a methodology able of generating new structures with pre-specified properties. It combines the use of negative factor counting (NFC technique with artificial intelligence methods (genetic algorithms - GAs. We present the results for a case study for poly(phenylenesulfide phenyleneamine (PPSA, a copolymer formed by combination of homopolymers: polyaniline (PANI and polyphenylenesulfide (PPS. The methodology was successfully applied to the problem of obtaining binary up to quinternary disordered polymeric alloys with a pre-specific gap value or exhibiting metallic properties. It is completely general and can be in principle adapted to the design of new classes of materials with pre-specified properties.

  1. Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success.

    Science.gov (United States)

    Thrall, James H; Li, Xiang; Li, Quanzheng; Cruz, Cinthia; Do, Synho; Dreyer, Keith; Brink, James

    2018-03-01

    Worldwide interest in artificial intelligence (AI) applications, including imaging, is high and growing rapidly, fueled by availability of large datasets ("big data"), substantial advances in computing power, and new deep-learning algorithms. Apart from developing new AI methods per se, there are many opportunities and challenges for the imaging community, including the development of a common nomenclature, better ways to share image data, and standards for validating AI program use across different imaging platforms and patient populations. AI surveillance programs may help radiologists prioritize work lists by identifying suspicious or positive cases for early review. AI programs can be used to extract "radiomic" information from images not discernible by visual inspection, potentially increasing the diagnostic and prognostic value derived from image datasets. Predictions have been made that suggest AI will put radiologists out of business. This issue has been overstated, and it is much more likely that radiologists will beneficially incorporate AI methods into their practices. Current limitations in availability of technical expertise and even computing power will be resolved over time and can also be addressed by remote access solutions. Success for AI in imaging will be measured by value created: increased diagnostic certainty, faster turnaround, better outcomes for patients, and better quality of work life for radiologists. AI offers a new and promising set of methods for analyzing image data. Radiologists will explore these new pathways and are likely to play a leading role in medical applications of AI. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  2. T'ai Chi

    Science.gov (United States)

    ... are different styles of t'ai chi, including: Chen style Hao (or Wu Shi) style Hu Lei ... medical advice, diagnoses, and treatment, consult your doctor. © 1995- The Nemours Foundation. All rights reserved. Images provided ...

  3. Intelligent system for lighting control in smart cities

    OpenAIRE

    de Paz Santana, Juan F.; Bajo Pérez, Javier; Rodríguez González, Sara; Villarrubia González, Gabriel; Corchado Rodríguez, Juan M.

    2017-01-01

    This paper presents an adaptive architecture that centralizes the control of public lighting and intelligent management to economize lighting and maintain maximum visual comfort in illuminated areas. To carry out this management, the architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA, and a Service Oriented Approach (SOA). It achieves optimization in ter...

  4. A Survey of Formal Methods for Intelligent Swarms

    Science.gov (United States)

    Truszkowski, Walt; Rash, James; Hinchey, Mike; Rouff, Chrustopher A.

    2004-01-01

    Swarms of intelligent autonomous spacecraft, involving complex behaviors and interactions, are being proposed for future space exploration missions. Such missions provide greater flexibility and offer the possibility of gathering more science data than traditional single spacecraft missions. The emergent properties of swarms make these missions powerful, but simultaneously far more difficult to design, and to assure that the proper behaviors will emerge. These missions are also considerably more complex than previous types of missions, and NASA, like other organizations, has little experience in developing or in verifying and validating these types of missions. A significant challenge when verifying and validating swarms of intelligent interacting agents is how to determine that the possible exponential interactions and emergent behaviors are producing the desired results. Assuring correct behavior and interactions of swarms will be critical to mission success. The Autonomous Nano Technology Swarm (ANTS) mission is an example of one of the swarm types of missions NASA is considering. The ANTS mission will use a swarm of picospacecraft that will fly from Earth orbit to the Asteroid Belt. Using an insect colony analogy, ANTS will be composed of specialized workers for asteroid exploration. Exploration would consist of cataloguing the mass, density, morphology, and chemical composition of the asteroids, including any anomalous concentrations of specific minerals. To perform this task, ANTS would carry miniaturized instruments, such as imagers, spectrometers, and detectors. Since ANTS and other similar missions are going to consist of autonomous spacecraft that may be out of contact with the earth for extended periods of time, and have low bandwidths due to weight constraints, it will be difficult to observe improper behavior and to correct any errors after launch. Providing V&V (verification and validation) for this type of mission is new to NASA, and represents the

  5. Integration of artificial intelligence methods and life cycle assessment to predict energy output and environmental impacts of paddy production.

    Science.gov (United States)

    Nabavi-Pelesaraei, Ashkan; Rafiee, Shahin; Mohtasebi, Seyed Saeid; Hosseinzadeh-Bandbafha, Homa; Chau, Kwok-Wing

    2018-08-01

    Prediction of agricultural energy output and environmental impacts play important role in energy management and conservation of environment as it can help us to evaluate agricultural energy efficiency, conduct crops production system commissioning, and detect and diagnose faults of crop production system. Agricultural energy output and environmental impacts can be readily predicted by artificial intelligence (AI), owing to the ease of use and adaptability to seek optimal solutions in a rapid manner as well as the use of historical data to predict future agricultural energy use pattern under constraints. This paper conducts energy output and environmental impact prediction of paddy production in Guilan province, Iran based on two AI methods, artificial neural networks (ANNs), and adaptive neuro fuzzy inference system (ANFIS). The amounts of energy input and output are 51,585.61MJkg -1 and 66,112.94MJkg -1 , respectively, in paddy production. Life Cycle Assessment (LCA) is used to evaluate environmental impacts of paddy production. Results show that, in paddy production, in-farm emission is a hotspot in global warming, acidification and eutrophication impact categories. ANN model with 12-6-8-1 structure is selected as the best one for predicting energy output. The correlation coefficient (R) varies from 0.524 to 0.999 in training for energy input and environmental impacts in ANN models. ANFIS model is developed based on a hybrid learning algorithm, with R for predicting output energy being 0.860 and, for environmental impacts, varying from 0.944 to 0.997. Results indicate that the multi-level ANFIS is a useful tool to managers for large-scale planning in forecasting energy output and environmental indices of agricultural production systems owing to its higher speed of computation processes compared to ANN model, despite ANN's higher accuracy. Copyright © 2018 Elsevier B.V. All rights reserved.

  6. 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…

  7. The First Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI '06)

    OpenAIRE

    Augusto, Juan Carlos; Shapiro, Daniel

    2007-01-01

    The first annual workshop on the role of AI in ambient intelligence was held in Riva de Garda, Italy, on August 29, 2006. The workshop was colocated with the European Conference on Artificial Intelligence (ECAI 2006). It provided an opportunity for researchers in a variety of AI subfields together with representatives of commercial interests to explore ambient intelligence technology and applications.

  8. 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 ...

  9. Discrete simulation system based on artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Futo, I; Szeredi, J

    1982-01-01

    A discrete event simulation system based on the AI language Prolog is presented. The system called t-Prolog extends the traditional possibilities of simulation languages toward automatic problem solving by using backtrack in time and automatic model modification depending on logical deductions. As t-Prolog is an interactive tool, the user has the possibility to interrupt the simulation run to modify the model or to force it to return to a previous state for trying possible alternatives. It admits the construction of goal-oriented or goal-seeking models with variable structure. Models are defined in a restricted version of the first order predicate calculus using Horn clauses. 21 references.

  10. NASA space station automation: AI-based technology review

    Science.gov (United States)

    Firschein, O.; Georgeff, M. P.; Park, W.; Neumann, P.; Kautz, W. H.; Levitt, K. N.; Rom, R. J.; Poggio, A. A.

    1985-01-01

    Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures.

  11. It Takes Two to Tango: Towards Theory of AI's Mind

    OpenAIRE

    Chandrasekaran, Arjun; Yadav, Deshraj; Chattopadhyay, Prithvijit; Prabhu, Viraj; Parikh, Devi

    2017-01-01

    Theory of Mind is the ability to attribute mental states (beliefs, intents, knowledge, perspectives, etc.) to others and recognize that these mental states may differ from one's own. Theory of Mind is critical to effective communication and to teams demonstrating higher collective performance. To effectively leverage the progress in Artificial Intelligence (AI) to make our lives more productive, it is important for humans and AI to work well together in a team. Traditionally, there has been m...

  12. Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

  13. Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight

    Science.gov (United States)

    Bauer, Frank H. (Technical Monitor); Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's 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 AI 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. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.

  14. Areal Informations Systemet - AIS

    DEFF Research Database (Denmark)

    Nielsen, K.; Stjernholm, M.; Olsen, B. Ø.

    Forord: Denne rapport giver en kort beskrivelse af Areal Informations Systemet (AIS), som er et databasesystem med natur- og miljødata, som kan stedfæstes geografisk. Projektet er gennemført i perioden 1996-2000 som et samarbejdsprojekt mellem Danmarks Miljøundersøgelser (DMU), Danmarks og...... og enkeltpersoner med interesse for natur- og miljøforhold i Danmark. Yderligere oplysninger om Areal Informations Systemet, herunder adgangsforhold, kan fås på DMU's hjemmeside med følgende adresse: http://ais.dmu.dk/ Projektet er finansieret af Miljø- og Energiministeriet, mens en række...... (planlægning, beskyttelse), geologi (overfladegeologi og marin geologi), samt marin dybdemodel. # Etablering af dataadgang for Miljø- og Energiministeriets institutioner til AIS-data. # Afprøvning af systemet i forhold til konkrete projekter. # Formidling af produkterne til brugerkredsen....

  15. Intelligent Learning System using cognitive science theory and artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Cristensen, D.L.

    1986-01-01

    This dissertation is a presentation of a theoretical model of an intelligent Learning System (ILS). The approach view intelligent computer-based instruction on a curricular-level and educational-theory base, instead of the conventional instructional-only level. The ILS is divided into two components: (1) macro-level, curricular; and (2) micro-level (MAIS), instructional. The primary purpose of the ILS macro level is to establish the initial conditions of learning by considering individual difference variables within specification of the curriculum content domain. Second, the ILS macro-level will iteratively update the conditions of learning as the individual student progresses through the given curriculum. The term dynamic is used to describe the expert tutor that establishes and monitors the conditions of instruction between the ILS macro level and the micro level. As the student progresses through the instruction, appropriate information is sent back continuously to the macro level to constantly improve decision making for succeeding conditions of instruction.

  16. 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.

  17. MassAI

    DEFF Research Database (Denmark)

    2011-01-01

    A software tool for general analysis and data-mining of mass-spectrometric datasets. The program features a strong emphasis on scan-by-scan identification and results-transparency. MassAI also accommodates residue level analysis of labelled runs, e.g. HDX.......A software tool for general analysis and data-mining of mass-spectrometric datasets. The program features a strong emphasis on scan-by-scan identification and results-transparency. MassAI also accommodates residue level analysis of labelled runs, e.g. HDX....

  18. Intelligent methods for the process parameter determination of plastic injection molding

    Science.gov (United States)

    Gao, Huang; Zhang, Yun; Zhou, Xundao; Li, Dequn

    2018-03-01

    Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system- based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.

  19. Classical methods for interpreting objective function minimization as intelligent inference

    Energy Technology Data Exchange (ETDEWEB)

    Golden, R.M. [Univ. of Texas, Dallas, TX (United States)

    1996-12-31

    Most recognition algorithms and neural networks can be formally viewed as seeking a minimum value of an appropriate objective function during either classification or learning phases. The goal of this paper is to argue that in order to show a recognition algorithm is making intelligent inferences, it is not sufficient to show that the recognition algorithm is computing (or trying to compute) the global minimum of some objective function. One must explicitly define a {open_quotes}relational system{close_quotes} for the recognition algorithm or neural network which identifies the: (i) sample space, (ii) the relevant sigmafield of events generated by the sample space, and (iii) the {open_quotes}relation{close_quotes} for that relational system. Only when such a {open_quotes}relational system{close_quotes} is properly defined, is it possible to formally establish the sense in which computing the global minimum of an objective function is an intelligent, inference.

  20. ARTIFICIAL INTELLIGENCE: APPLICATIONS AND FUTURE

    OpenAIRE

    Ellur Anand; S. G. Varun Kumar

    2017-01-01

    Artificial Intelligence (AI) or Augmented Intelligence happens to be the most talked about technology that would have a major impact on the way the current day world functions. The next step in evolution of digital world is AI. The safety of the world with more and more use of AI also becomes necessity. Safety rules and regulations of the digital world need to be drafted and redrafted as AI evolves and becomes a new normal in every one’s life just as mobile phone has become in the current sce...

  1. 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.

  2. 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.…

  3. Research on intelligent machine self-perception method based on LSTM

    Science.gov (United States)

    Wang, Qiang; Cheng, Tao

    2018-05-01

    In this paper, we use the advantages of LSTM in feature extraction and processing high-dimensional and complex nonlinear data, and apply it to the autonomous perception of intelligent machines. Compared with the traditional multi-layer neural network, this model has memory, can handle time series information of any length. Since the multi-physical domain signals of processing machines have a certain timing relationship, and there is a contextual relationship between states and states, using this deep learning method to realize the self-perception of intelligent processing machines has strong versatility and adaptability. The experiment results show that the method proposed in this paper can obviously improve the sensing accuracy under various working conditions of the intelligent machine, and also shows that the algorithm can well support the intelligent processing machine to realize self-perception.

  4. 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.

  5. Quo vadis, Intelligent Machine?

    Directory of Open Access Journals (Sweden)

    Rosemarie Velik

    2010-09-01

    Full Text Available Artificial Intelligence (AI is a branch of computer science concerned with making computers behave like humans. At least this was the original idea. However, it turned out that this is no task easy to be solved. This article aims to give a comprehensible review on the last 60 years of artificial intelligence taking a philosophical viewpoint. It is outlined what happened so far in AI, what is currently going on in this research area, and what can be expected in future. The goal is to mediate an understanding for the developments and changes in thinking in course of time about how to achieve machine intelligence. The clear message is that AI has to join forces with neuroscience and other brain disciplines in order to make a step towards the development of truly intelligent machines.

  6. 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

  7. General Video Game AI: Learning from Screen Capture

    OpenAIRE

    Kunanusont, Kamolwan; Lucas, Simon M.; Perez-Liebana, Diego

    2017-01-01

    General Video Game Artificial Intelligence is a general game playing framework for Artificial General Intelligence research in the video-games domain. In this paper, we propose for the first time a screen capture learning agent for General Video Game AI framework. A Deep Q-Network algorithm was applied and improved to develop an agent capable of learning to play different games in the framework. After testing this algorithm using various games of different categories and difficulty levels, th...

  8. Launching AI in NASA ground systems

    Science.gov (United States)

    Perkins, Dorothy C.; Truszkowski, Walter F.

    1990-01-01

    This paper will discuss recent operational successes in implementing expert systems to support the complex functions of NASA mission control systems at the Goddard Space Flight Center, including fault detection and diagnosis for real time and engineering analysis functions in the Cosmic Background Explorer and Gamma Ray Observatory missions and automation of resource planning and scheduling functions for various missions. It will also discuss ongoing developments and prototypes that will lead to increasingly sophisticated applications of artificial intelligence. These include the use of neural networks to perform telemetry monitoring functions, the implementation of generic expert system shells that can be customized to telemetry handling functions specific to NASA control centers, the applications of AI in training and user support, the long-term potential of implementing systems based around distributed, cooperative problem solving, and the use of AI to control and assist system development activities.

  9. AI systems approach in particle accelerators

    International Nuclear Information System (INIS)

    Kataria, S.K.; Bhagwat, P.V.; Kori, S.A.

    1992-01-01

    The large particle accelerators machines like pelletron accelerator at Tata Institute of Fundamental Research (T.I.F.R) have several levels of controls with operators responsible for overall global control decisions and closed loop feedback controllers for relatively small subsystems of the machines. As the accelerator machines are becoming more complicated and the requirements more stringent, there is a need to provide the operators with an artificial intelligence (AI) system to aid in the tuning the machine and in failure diagnosis. There are few major areas in the pelletron operation, which can be done more efficiently using AI systems approach so that useful beam is available for much more time: 1) Accelerator Conditioning, 2) Accelerator Tuning, and 3) Maintaining the Tune beams. The feasibility study for using expert system for above areas and also for safety evaluation of the various subsystems is carried out. (author). 10 refs., 4 figs

  10. 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…

  11. Planning chemical syntheses with deep neural networks and symbolic AI

    Science.gov (United States)

    Segler, Marwin H. S.; Preuss, Mike; Waller, Mark P.

    2018-03-01

    To plan the syntheses of small organic molecules, chemists use retrosynthesis, a problem-solving technique in which target molecules are recursively transformed into increasingly simpler precursors. Computer-aided retrosynthesis would be a valuable tool but at present it is slow and provides results of unsatisfactory quality. Here we use Monte Carlo tree search and symbolic artificial intelligence (AI) to discover retrosynthetic routes. We combined Monte Carlo tree search with an expansion policy network that guides the search, and a filter network to pre-select the most promising retrosynthetic steps. These deep neural networks were trained on essentially all reactions ever published in organic chemistry. Our system solves for almost twice as many molecules, thirty times faster than the traditional computer-aided search method, which is based on extracted rules and hand-designed heuristics. In a double-blind AB test, chemists on average considered our computer-generated routes to be equivalent to reported literature routes.

  12. Orthogonally Evolved AI to Improve Difficulty Adjustment in Video Games

    DEFF Research Database (Denmark)

    Hintze, Arend; Olson, Randal; Lehman, Joel Anthony

    2016-01-01

    Computer games are most engaging when their difficulty is well matched to the player's ability, thereby providing an experience in which the player is neither overwhelmed nor bored. In games where the player interacts with computer-controlled opponents, the difficulty of the game can be adjusted...... not only by changing the distribution of opponents or game resources, but also through modifying the skill of the opponents. Applying evolutionary algorithms to evolve the artificial intelligence that controls opponent agents is one established method for adjusting opponent difficulty. Less-evolved agents...... (i.e. agents subject to fewer generations of evolution) make for easier opponents, while highly-evolved agents are more challenging to overcome. In this publication we test a new approach for difficulty adjustment in games: orthogonally evolved AI, where the player receives support from collaborating...

  13. Comparison of two solution ways of district heating control: Using analysis methods, using artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Balate, J.; Sysala, T. [Technical Univ., Zlin (Czech Republic). Dept. of Automation and Control Technology

    1997-12-31

    The District Heating Systems - DHS (Centralized Heat Supply Systems - CHSS) are being developed in large cities in accordance with their growth. The systems are formed by enlarging networks of heat distribution to consumers and at the same time they interconnect the heat sources gradually built. The heat is distributed to the consumers through the circular networks, that are supplied by several cooperating heat sources, that means by power and heating plants and heating plants. The complicated process of heat production technology and supply requires the system approach when solving the concept of automatized control. The paper deals with comparison of the solution way using the analysis methods and using the artificial intelligence methods. (orig.)

  14. Artificial intelligence: A joint narrative on potential use in pediatric stem and immune cell therapies and regenerative medicine.

    Science.gov (United States)

    Sniecinski, Irena; Seghatchian, Jerard

    2018-05-09

    by precise planning of treatments, predicting clinical outcomes, simplifying recruitment and retention of patients, learning from input data and applying to new data, thus lowering their complexity and costs. Complementing human intelligence with machine intelligence could have an exponentially high impact on continual progress in many fields of pediatrics. However how long before we could see the real impact still remains the big question. The most pertinent question that remains to be answered therefore, is can AI effectively and accurately predict properties of newer DDR strategies? The goal of this article is to review the use of AI method for cellular therapy and regenerative medicine and emphasize its potential to further the progress in these fields of medicine. Copyright © 2018. Published by Elsevier Ltd.

  15. Automatic detection of mycobacterium tuberculosis using artificial intelligence

    Science.gov (United States)

    Xiong, Yan; Ba, Xiaojun; Hou, Ao; Zhang, Kaiwen; Chen, Longsen

    2018-01-01

    Background Tuberculosis (TB) is a global issue that seriously endangers public health. Pathology is one of the most important means for diagnosing TB in clinical practice. To confirm TB as the diagnosis, finding specially stained TB bacilli under a microscope is critical. Because of the very small size and number of bacilli, it is a time-consuming and strenuous work even for experienced pathologists, and this strenuosity often leads to low detection rate and false diagnoses. We investigated the clinical efficacy of an artificial intelligence (AI)-assisted detection method for acid-fast stained TB bacillus. Methods We built a convolutional neural networks (CNN) model, named tuberculosis AI (TB-AI), specifically to recognize TB bacillus. The training set contains 45 samples, including 30 positive cases and 15 negative cases, where bacilli are labeled by human pathologists. Upon training the neural network model, 201 samples (108 positive cases and 93 negative cases) were collected as test set and used to examine TB-AI. We compared the diagnosis of TB-AI to the ground truth result provided by human pathologists, analyzed inconsistencies between AI and human, and adjusted the protocol accordingly. Trained TB-AI were run on the test data twice. Results Examined against the double confirmed diagnosis by pathologists both via microscopes and digital slides, TB-AI achieved 97.94% sensitivity and 83.65% specificity. Conclusions TB-AI can be a promising support system to detect stained TB bacilli and help make clinical decisions. It holds the potential to relieve the heavy workload of pathologists and decrease chances of missed diagnosis. Samples labeled as positive by TB-AI must be confirmed by pathologists, and those labeled as negative should be reviewed to make sure that the digital slides are qualified. PMID:29707349

  16. AIS ASM Operational Integration Plan

    Science.gov (United States)

    2013-08-01

    Rack mount computer AIS Radio Interface Ethernet Switch 192.168.0.x Firewall Cable Modem 192.168.0.1 VTS Accred. Boundary AIS ASM Operational... AIS ASM Operational Integration Plan Distribution Statement A: Approved for public release; distribution is unlimited. August 2013 Report No...CD-D-07-15 AIS ASM Operational Integration Plan ii UNCLAS//Public | CG-926 R&DC | I. Gonin, et al. | Public August 2013 N O T I C

  17. [Development and effects of emotional intelligence program for undergraduate nursing students: mixed methods research].

    Science.gov (United States)

    Lee, Oi Sun; Gu, Mee Ock

    2014-12-01

    This study was conducted to develop and test the effects of an emotional intelligence program for undergraduate nursing students. The study design was a mixed method research. Participants were 36 nursing students (intervention group: 17, control group: 19). The emotional intelligence program was provided for 4 weeks (8 sessions, 20 hours). Data were collected between August 6 and October 4, 2013. Quantitative data were analyzed using Chi-square, Fisher's exact test, t-test, repeated measure ANOVA, and paired t-test with SPSS/WIN 18.0. Qualitative data were analyzed using content analysis. Quantitative results showed that emotional intelligence, communication skills, resilience, stress coping strategy, and clinical competence were significantly better in the experimental group compared to the control group. According to the qualitative results, the nursing students experienced improvement in emotional intelligence, interpersonal relationships, and empowerment, as well as a reduction in clinical practice stress after participation in the emotional intelligence program. Study findings indicate that the emotional intelligence program for undergraduate nursing students is effective and can be recommended as an intervention for improving the clinical competence of undergraduate students in a nursing curriculum.

  18. 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...

  19. Strategic Team AI Path Plans: Probabilistic Pathfinding

    Directory of Open Access Journals (Sweden)

    Tng C. H. John

    2008-01-01

    Full Text Available This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002, in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006. We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans.

  20. AI/Simulation Fusion Project at Lawrence Livermore National Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Erickson, S.A.

    1984-04-25

    This presentation first discusses the motivation for the AI Simulation Fusion project. After discussing very briefly what expert systems are in general, what object oriented languages are in general, and some observed features of typical combat simulations, it discusses why putting together artificial intelligence and combat simulation makes sense. We then talk about the first demonstration goal for this fusion project.

  1. AI/Simulation Fusion Project at Lawrence Livermore National Laboratory

    International Nuclear Information System (INIS)

    Erickson, S.A.

    1984-01-01

    This presentation first discusses the motivation for the AI Simulation Fusion project. After discussing very briefly what expert systems are in general, what object oriented languages are in general, and some observed features of typical combat simulations, it discusses why putting together artificial intelligence and combat simulation makes sense. We then talk about the first demonstration goal for this fusion project

  2. AI AND SAR APPROACHES FOR PREDICTING CHEMICAL CARCINOGENICITY: SURVEY AND STATUS REPORT

    Science.gov (United States)

    A wide variety of artificial intelligence (AI) and structure-activity relationship (SAR approaches have been applied to tackling the general problem of predicting rodent chemical carcinogenicity. Given the diversity of chemical structures and mechanisms relative to this endpoin...

  3. Methods and models for quantative assessment of speech intelligibility in cross-language communication

    NARCIS (Netherlands)

    Wijngaarden, S.J. van; Steeneken, H.J.M.; Houtgast, T.

    2001-01-01

    To deal with the effects of nonnative speech communication on speech intelligibility, one must know the magnitude of these effects. To measure this magnitude, suitable test methods must be available. Many of the methods used in cross-language speech communication research are not very suitable for

  4. Automatic detection of mycobacterium tuberculosis using artificial intelligence.

    Science.gov (United States)

    Xiong, Yan; Ba, Xiaojun; Hou, Ao; Zhang, Kaiwen; Chen, Longsen; Li, Ting

    2018-03-01

    Tuberculosis (TB) is a global issue that seriously endangers public health. Pathology is one of the most important means for diagnosing TB in clinical practice. To confirm TB as the diagnosis, finding specially stained TB bacilli under a microscope is critical. Because of the very small size and number of bacilli, it is a time-consuming and strenuous work even for experienced pathologists, and this strenuosity often leads to low detection rate and false diagnoses. We investigated the clinical efficacy of an artificial intelligence (AI)-assisted detection method for acid-fast stained TB bacillus. We built a convolutional neural networks (CNN) model, named tuberculosis AI (TB-AI), specifically to recognize TB bacillus. The training set contains 45 samples, including 30 positive cases and 15 negative cases, where bacilli are labeled by human pathologists. Upon training the neural network model, 201 samples (108 positive cases and 93 negative cases) were collected as test set and used to examine TB-AI. We compared the diagnosis of TB-AI to the ground truth result provided by human pathologists, analyzed inconsistencies between AI and human, and adjusted the protocol accordingly. Trained TB-AI were run on the test data twice. Examined against the double confirmed diagnosis by pathologists both via microscopes and digital slides, TB-AI achieved 97.94% sensitivity and 83.65% specificity. TB-AI can be a promising support system to detect stained TB bacilli and help make clinical decisions. It holds the potential to relieve the heavy workload of pathologists and decrease chances of missed diagnosis. Samples labeled as positive by TB-AI must be confirmed by pathologists, and those labeled as negative should be reviewed to make sure that the digital slides are qualified.

  5. Building Explainable Artificial Intelligence Systems

    National Research Council Canada - National Science Library

    Core, Mark G; Lane, H. Chad; van Lent, Michael; Gomboc, Dave; Solomon, Steve; Rosenberg, Milton

    2006-01-01

    As artificial intelligence (AI) systems and behavior models in military simulations become increasingly complex, it has been difficult for users to understand the activities of computer-controlled entities...

  6. Bayesian Model Averaging of Artificial Intelligence Models for Hydraulic Conductivity Estimation

    Science.gov (United States)

    Nadiri, A.; Chitsazan, N.; Tsai, F. T.; Asghari Moghaddam, A.

    2012-12-01

    This research presents a Bayesian artificial intelligence model averaging (BAIMA) method that incorporates multiple artificial intelligence (AI) models to estimate hydraulic conductivity and evaluate estimation uncertainties. Uncertainty in the AI model outputs stems from error in model input as well as non-uniqueness in selecting different AI methods. Using one single AI model tends to bias the estimation and underestimate uncertainty. BAIMA employs Bayesian model averaging (BMA) technique to address the issue of using one single AI model for estimation. BAIMA estimates hydraulic conductivity by averaging the outputs of AI models according to their model weights. In this study, the model weights were determined using the Bayesian information criterion (BIC) that follows the parsimony principle. BAIMA calculates the within-model variances to account for uncertainty propagation from input data to AI model output. Between-model variances are evaluated to account for uncertainty due to model non-uniqueness. We employed Takagi-Sugeno fuzzy logic (TS-FL), artificial neural network (ANN) and neurofuzzy (NF) to estimate hydraulic conductivity for the Tasuj plain aquifer, Iran. BAIMA combined three AI models and produced better fitting than individual models. While NF was expected to be the best AI model owing to its utilization of both TS-FL and ANN models, the NF model is nearly discarded by the parsimony principle. The TS-FL model and the ANN model showed equal importance although their hydraulic conductivity estimates were quite different. This resulted in significant between-model variances that are normally ignored by using one AI model.

  7. 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...

  8. Explanation and trust: what to tell the user in security and AI?

    NARCIS (Netherlands)

    Pieters, Wolter

    2010-01-01

    There is a common problem in artificial intelligence (AI) and information security. In AI, an expert system needs to be able to justify and explain a decision to the user. In information security, experts need to be able to explain to the public why a system is secure. In both cases, the goal of

  9. Explanation and trust: what to tell the user in security and AI?

    NARCIS (Netherlands)

    Pieters, Wolter

    There is a common problem in artificial intelligence (AI) and information security. In AI, an expert system needs to be able to justify and explain a decision to the user. In information security, experts need to be able to explain to the public why a system is secure. In both cases, an important

  10. Development and application of AI technology to plant operation and support

    International Nuclear Information System (INIS)

    Sackett, J.I.; Mott, J.E.

    1989-01-01

    This paper discusses a framework for the development and application of artificial intelligence (AI) technology in existing nuclear facilities and reviews the status of development. We consider those areas best addressed by AI technology, e.g., equipment diagnostics, sensor validation, and expert systems for procedural response or planning. A brief discussion of work in computer displays is also given. (orig./GL)

  11. On construction method of shipborne and airborne radar intelligence and related equipment knowledge graph

    Science.gov (United States)

    Hao, Ruizhe; Huang, Jian

    2017-08-01

    Knowledge graph construction in military intelligence domain is sprouting but technically immature. This paper presents a method to construct the heterogeneous knowledge graph in the field of shipborne and airborne radar and equipment. Based on the expert knowledge and the up-to-date Internet open source information, we construct the knowledge graph of radar characteristic information and the equipment respectively, and establish relationships between two graphs, providing the pipeline and method for the intelligence organization and management in the context of the crowding battlefields big data.

  12. An Empirical Study of AI Population Dynamics with Million-agent Reinforcement Learning

    OpenAIRE

    Yang, Yaodong; Yu, Lantao; Bai, Yiwei; Wang, Jun; Zhang, Weinan; Wen, Ying; Yu, Yong

    2017-01-01

    In this paper, we conduct an empirical study on discovering the ordered collective dynamics obtained by a population of artificial intelligence (AI) agents. Our intention is to put AI agents into a simulated natural context, and then to understand their induced dynamics at the population level. In particular, we aim to verify if the principles developed in the real world could also be used in understanding an artificially-created intelligent population. To achieve this, we simulate a large-sc...

  13. Artificial Intelligence: A Selected Bibliography.

    Science.gov (United States)

    Smith, Linda C., Comp.

    1984-01-01

    This 19-item annotated bibliography introducing the literature of artificial intelligence (AI) is arranged by type of material--handbook, books (general interest, textbooks, collected readings), journals and newsletters, and conferences and workshops. The availability of technical reports from AI laboratories at universities and private companies…

  14. Pavlovian, Skinner, and Other Behaviourists' Contributions to AI. Chapter 9

    Science.gov (United States)

    Kosinski, Withold; Zaczek-Chrzanowska, Dominika

    2007-01-01

    A version of the definition of intelligent behaviour will be supplied in the context of real and artificial systems. Short presentation of principles of learning, starting with Pavlovian s classical conditioning through reinforced response and operant conditioning of Thorndike and Skinner and finishing with cognitive learning of Tolman and Bandura will be given. The most important figures within behaviourism, especially those with contribution to AI, will be described. Some tools of artificial intelligence that act according to those principles will be presented. An attempt will be made to show when some simple rules for behaviour modifications can lead to a complex intelligent behaviour.

  15. Artificial Intelligence for the Bang! Game

    OpenAIRE

    Daniláková, Monika

    2017-01-01

    This work explores artificial intelligence (AI) algorithms for the game Bang!, a Wild West-themed card game created by Italian game designer Emiliano Sciarra. The aim of this work was to design three different AIs for this game and to compare them theoretically and experimentally. First, we analyzed game Bang! with regards to game theory, and researched some of the AI algorithms used in similar games. We then designed three different AIs algorithms and compared their advantages and disadvanta...

  16. 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...

  17. An Intelligent Optical Dissolved Oxygen Measurement Method Based on a Fluorescent Quenching Mechanism.

    Science.gov (United States)

    Li, Fengmei; Wei, Yaoguang; Chen, Yingyi; Li, Daoliang; Zhang, Xu

    2015-12-09

    Dissolved oxygen (DO) is a key factor that influences the healthy growth of fishes in aquaculture. The DO content changes with the aquatic environment and should therefore be monitored online. However, traditional measurement methods, such as iodometry and other chemical analysis methods, are not suitable for online monitoring. The Clark method is not stable enough for extended periods of monitoring. To solve these problems, this paper proposes an intelligent DO measurement method based on the fluorescence quenching mechanism. The measurement system is composed of fluorescent quenching detection, signal conditioning, intelligent processing, and power supply modules. The optical probe adopts the fluorescent quenching mechanism to detect the DO content and solves the problem, whereas traditional chemical methods are easily influenced by the environment. The optical probe contains a thermistor and dual excitation sources to isolate visible parasitic light and execute a compensation strategy. The intelligent processing module adopts the IEEE 1451.2 standard and realizes intelligent compensation. Experimental results show that the optical measurement method is stable, accurate, and suitable for online DO monitoring in aquaculture applications.

  18. An Intelligent Optical Dissolved Oxygen Measurement Method Based on a Fluorescent Quenching Mechanism

    Directory of Open Access Journals (Sweden)

    Fengmei Li

    2015-12-01

    Full Text Available Dissolved oxygen (DO is a key factor that influences the healthy growth of fishes in aquaculture. The DO content changes with the aquatic environment and should therefore be monitored online. However, traditional measurement methods, such as iodometry and other chemical analysis methods, are not suitable for online monitoring. The Clark method is not stable enough for extended periods of monitoring. To solve these problems, this paper proposes an intelligent DO measurement method based on the fluorescence quenching mechanism. The measurement system is composed of fluorescent quenching detection, signal conditioning, intelligent processing, and power supply modules. The optical probe adopts the fluorescent quenching mechanism to detect the DO content and solves the problem, whereas traditional chemical methods are easily influenced by the environment. The optical probe contains a thermistor and dual excitation sources to isolate visible parasitic light and execute a compensation strategy. The intelligent processing module adopts the IEEE 1451.2 standard and realizes intelligent compensation. Experimental results show that the optical measurement method is stable, accurate, and suitable for online DO monitoring in aquaculture applications.

  19. Northeast Artificial Intelligence Consortium Annual Report 1986. Volume 4. Part A. Hierarchical Region-Based Approach to Automatic Photointerpretation. Part B. Application of AI Techniques to Image Segmentation and Region Identification

    Science.gov (United States)

    1988-01-01

    MONITORING ORGANIZATION Northeast Artificial (If applicaole)nelincCostum(AcRome Air Development Center (COCU) Inteligence Consortium (NAIC)I 6c. ADDRESS...f, Offell RADC-TR-88-1 1, Vol IV (of eight) Interim Technical ReportS June 1988 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT 1986...13441-5700 EMENT NO NO NO ACCESSION NO62702F 5 8 71 " " over) I 58 27 13 " ൓ TITLE (Include Security Classification) NORTHEAST ARTIFICIAL INTELLIGENCE

  20. Artificial intelligence in medicine

    OpenAIRE

    Scerri, Mariella; Grech, Victor E.

    2016-01-01

    Various types of artificial intelligence programs are already available as consultants to physicians, and these help in medical diagnostics and treatment. At the time of writing, extant programs constitute “weak” AI—lacking in consciousness and intentionality. With AI currently making rapid progress in all domains, including those of healthcare, physicians face possible competitors—or worse, claims that doctors may become obsolete. We will explore the development of AI and robotics in medicin...

  1. 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

  2. SDI satellite autonomy using AI and Ada

    Science.gov (United States)

    Fiala, Harvey E.

    1990-01-01

    The use of Artificial Intelligence (AI) and the programming language Ada to help a satellite recover from selected failures that could lead to mission failure are described. An unmanned satellite will have a separate AI subsystem running in parallel with the normal satellite subsystems. A satellite monitoring subsystem (SMS), under the control of a blackboard system, will continuously monitor selected satellite subsystems to become alert to any actual or potential problems. In the case of loss of communications with the earth or the home base, the satellite will go into a survival mode to reestablish communications with the earth. The use of an AI subsystem in this manner would have avoided the tragic loss of the two recent Soviet probes that were sent to investigate the planet Mars and its moons. The blackboard system works in conjunction with an SMS and a reconfiguration control subsystem (RCS). It can be shown to be an effective way for one central control subsystem to monitor and coordinate the activities and loads of many interacting subsystems that may or may not contain redundant and/or fault-tolerant elements. The blackboard system will be coded in Ada using tools such as the ABLE development system and the Ada Production system.

  3. Intelligent Evaluation Method of Tank Bottom Corrosion Status Based on Improved BP Artificial Neural Network

    Science.gov (United States)

    Qiu, Feng; Dai, Guang; Zhang, Ying

    According to the acoustic emission information and the appearance inspection information of tank bottom online testing, the external factors associated with tank bottom corrosion status are confirmed. Applying artificial neural network intelligent evaluation method, three tank bottom corrosion status evaluation models based on appearance inspection information, acoustic emission information, and online testing information are established. Comparing with the result of acoustic emission online testing through the evaluation of test sample, the accuracy of the evaluation model based on online testing information is 94 %. The evaluation model can evaluate tank bottom corrosion accurately and realize acoustic emission online testing intelligent evaluation of tank bottom.

  4. Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants

    International Nuclear Information System (INIS)

    Reifman, J.

    1997-01-01

    A comprehensive survey of computer-based systems that apply artificial intelligence methods to detect and identify component faults in nuclear power plants is presented. Classification criteria are established that categorize artificial intelligence diagnostic systems according to the types of computing approaches used (e.g., computing tools, computer languages, and shell and simulation programs), the types of methodologies employed (e.g., types of knowledge, reasoning and inference mechanisms, and diagnostic approach), and the scope of the system. The major issues of process diagnostics and computer-based diagnostic systems are identified and cross-correlated with the various categories used for classification. Ninety-five publications are reviewed

  5. AI techniques in geomagnetic storm forecasting

    Science.gov (United States)

    Lundstedt, Henrik

    This review deals with how geomagnetic storms can be predicted with the use of Artificial Intelligence (AI) techniques. Today many different Al techniques have been developed, such as symbolic systems (expert and fuzzy systems) and connectionism systems (neural networks). Even integrations of AI techniques exist, so called Intelligent Hybrid Systems (IHS). These systems are capable of learning the mathematical functions underlying the operation of non-linear dynamic systems and also to explain the knowledge they have learned. Very few such powerful systems exist at present. Two such examples are the Magnetospheric Specification Forecast Model of Rice University and the Lund Space Weather Model of Lund University. Various attempts to predict geomagnetic storms on long to short-term are reviewed in this article. Predictions of a month to days ahead most often use solar data as input. The first SOHO data are now available. Due to the high temporal and spatial resolution new solar physics have been revealed. These SOHO data might lead to a breakthrough in these predictions. Predictions hours ahead and shorter rely on real-time solar wind data. WIND gives us real-time data for only part of the day. However, with the launch of the ACE spacecraft in 1997, real-time data during 24 hours will be available. That might lead to the second breakthrough for predictions of geomagnetic storms.

  6. Artificial intelligence, expert systems, computer vision, and natural language processing

    Science.gov (United States)

    Gevarter, W. B.

    1984-01-01

    An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

  7. Social Intelligence Design in Ambient Intelligence

    NARCIS (Netherlands)

    Nijholt, Antinus; Stock, Oliviero; Stock, O.; Nishida, T.; Nishida, Toyoaki

    2009-01-01

    This Special Issue of AI and Society contains a selection of papers presented at the 6th Social Intelligence Design Workshop held at ITC-irst, Povo (Trento, Italy) in July 2007. Being the 6th in a series means that there now is a well-established and also a growing research area. The interest in

  8. [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.

  9. 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

  10. Fourth Conference on Artificial Intelligence for Space Applications

    Science.gov (United States)

    Odell, Stephen L. (Compiler); Denton, Judith S. (Compiler); Vereen, Mary (Compiler)

    1988-01-01

    Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth 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: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming.

  11. Selected business intelligence methods for decision-making support in a finance institution

    OpenAIRE

    Mezera, Filip; Křupka, Jiří

    2017-01-01

    This article deals with decision-making support methods’ implementation in a medium size financial company with international operations. The objective of this article is to show the abilities of these methods to precise decision-making of management. At the beginning of this article there is briefly described the existing situation in this business sector in Central Europe. After that part Business Intelligence methods are described as well as the reasons while these methods have been introd...

  12. Modern architectures for intelligent systems: reusable ontologies and problem-solving methods.

    Science.gov (United States)

    Musen, M A

    1998-01-01

    When interest in intelligent systems for clinical medicine soared in the 1970s, workers in medical informatics became particularly attracted to rule-based systems. Although many successful rule-based applications were constructed, development and maintenance of large rule bases remained quite problematic. In the 1980s, an entire industry dedicated to the marketing of tools for creating rule-based systems rose and fell, as workers in medical informatics began to appreciate deeply why knowledge acquisition and maintenance for such systems are difficult problems. During this time period, investigators began to explore alternative programming abstractions that could be used to develop intelligent systems. The notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) domain-independent problem-solving methods-standard algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper will highlight how intelligent systems for diverse tasks can be efficiently automated using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community.

  13. Artificial Intelligence Methodologies and Their Application to Diabetes.

    Science.gov (United States)

    Rigla, Mercedes; García-Sáez, Gema; Pons, Belén; Hernando, Maria Elena

    2018-03-01

    In the past decade diabetes management has been transformed by the addition of continuous glucose monitoring and insulin pump data. More recently, a wide variety of functions and physiologic variables, such as heart rate, hours of sleep, number of steps walked and movement, have been available through wristbands or watches. New data, hydration, geolocation, and barometric pressure, among others, will be incorporated in the future. All these parameters, when analyzed, can be helpful for patients and doctors' decision support. Similar new scenarios have appeared in most medical fields, in such a way that in recent years, there has been an increased interest in the development and application of the methods of artificial intelligence (AI) to decision support and knowledge acquisition. Multidisciplinary research teams integrated by computer engineers and doctors are more and more frequent, mirroring the need of cooperation in this new topic. AI, as a science, can be defined as the ability to make computers do things that would require intelligence if done by humans. Increasingly, diabetes-related journals have been incorporating publications focused on AI tools applied to diabetes. In summary, diabetes management scenarios have suffered a deep transformation that forces diabetologists to incorporate skills from new areas. This recently needed knowledge includes AI tools, which have become part of the diabetes health care. The aim of this article is to explain in an easy and plane way the most used AI methodologies to promote the implication of health care providers-doctors and nurses-in this field.

  14. 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.

  15. AI technology and automobile. ; Toward vehicle autonomy. AI gijutsu to jidosha. ; Sharyo no jiritsuka ni mukatte

    Energy Technology Data Exchange (ETDEWEB)

    Okuno, A. (Mazda Motor Corp., Hiroshima (Japan))

    1991-01-01

    This report describes the vehicle autonomy by using artificial intelligence (AI) technology. Owing to a remarkable progress of AI technology, it is forecasted that driving support system will be introduced into the market till 2000, and higher autonomous navigation system will be introduced since about 2010. Autonomous vehicles have capacities of recognizing the outside world and of navigating roads by themselves, and with their enfanced environment adaptability the road transportation in the future is expected to be much more safer than in the present. The autonomous vehicle can warn its driver of potential dangers and correct operational errors of the driver. In order to realize such autonomous vehicles, extensive researches on perception systems, decision making systems and driving support systems are needed. 9 refs., 10 figs., 1 tab.

  16. Reviewing the development of an artificial intelligence based risk program

    International Nuclear Information System (INIS)

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

    1985-01-01

    A successful application of nonconventional programming methods has been achieved in computer-assisted probabilistic risk assessment (PRA). The event tree sequence importance calculator, SQUIMP, provides for prompted data entry, generic expansion, on-line pruning, boolean reductions, and importance factor selection. SQUIMP employs constructs typically found in artificial intelligence (AI) programs. The development history of SQUIMP is outlined and its internal structure described as background for a discussion on the applicability of symbolic programming methods in PRA

  17. A novel method for intelligent fault diagnosis of rolling bearings using ensemble deep auto-encoders

    Science.gov (United States)

    Shao, Haidong; Jiang, Hongkai; Lin, Ying; Li, Xingqiu

    2018-03-01

    Automatic and accurate identification of rolling bearings fault categories, especially for the fault severities and fault orientations, is still a major challenge in rotating machinery fault diagnosis. In this paper, a novel method called ensemble deep auto-encoders (EDAEs) is proposed for intelligent fault diagnosis of rolling bearings. Firstly, different activation functions are employed as the hidden functions to design a series of auto-encoders (AEs) with different characteristics. Secondly, EDAEs are constructed with various auto-encoders for unsupervised feature learning from the measured vibration signals. Finally, a combination strategy is designed to ensure accurate and stable diagnosis results. The proposed method is applied to analyze the experimental bearing vibration signals. The results confirm that the proposed method can get rid of the dependence on manual feature extraction and overcome the limitations of individual deep learning models, which is more effective than the existing intelligent diagnosis methods.

  18. Towards a New Approach of the Economic Intelligence Process: Basic Concepts, Analysis Methods and Informational Tools

    Directory of Open Access Journals (Sweden)

    Sorin Briciu

    2009-04-01

    Full Text Available One of the obvious trends in current business environment is the increased competition. In this context, organizations are becoming more and more aware of the importance of knowledge as a key factor in obtaining competitive advantage. A possible solution in knowledge management is Economic Intelligence (EI that involves the collection, evaluation, processing, analysis, and dissemination of economic data (about products, clients, competitors, etc. inside organizations. The availability of massive quantities of data correlated with advances in information and communication technology allowing for the filtering and processing of these data provide new tools for the production of economic intelligence.The research is focused on innovative aspects of economic intelligence process (models of analysis, activities, methods and informational tools and is providing practical guidelines for initiating this process. In this paper, we try: (a to contribute to a coherent view on economic intelligence process (approaches, stages, fields of application; b to describe the most important models of analysis related to this process; c to analyze the activities, methods and tools associated with each stage of an EI process.

  19. Application of AI technology to nuclear plant operations

    International Nuclear Information System (INIS)

    Sackett, J.I.

    1988-01-01

    In this paper, applications of Artificial Intelligence (AI) Technology to nuclear-power plant operation are reviewed. AI Technology is advancing rapidly and in the next five years is expected to enjoy widespread application to operation, maintenance, management and safety. Near term emphasis on a sensor validation, scheduling, alarm handling, and expert systems for procedural assistance. Ultimate applications are envisioned to culminate in autonomous control such as would be necessary for a power system in space, where automatic control actions are taken based upon reasoned conclusions regarding plant conditions, capability and control objectives

  20. AiGERM: A logic programming front end for GERM

    Science.gov (United States)

    Hashim, Safaa H.

    1990-01-01

    AiGerm (Artificially Intelligent Graphical Entity Relation Modeler) is a relational data base query and programming language front end for MCC (Mission Control Center)/STP's (Space Test Program) Germ (Graphical Entity Relational Modeling) system. It is intended as an add-on component of the Germ system to be used for navigating very large networks of information. It can also function as an expert system shell for prototyping knowledge-based systems. AiGerm provides an interface between the programming language and Germ.

  1. Progress and Challenge of Artificial Intelligence

    Institute of Scientific and Technical Information of China (English)

    Zhong-Zhi Shi; Nan-Ning Zheng

    2006-01-01

    Artificial Intelligence (AI) is generally considered to be a subfield of computer science, that is concerned to attempt simulation, extension and expansion of human intelligence. Artificial intelligence has enjoyed tremendous success over the last fifty years. In this paper we only focus on visual perception, granular computing, agent computing, semantic grid. Human-level intelligence is the long-term goal of artificial intelligence. We should do joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. A new cross discipline intelligence science is undergoing a rapid development. Future challenges are given in final section.

  2. SOLVING TRANSPORT LOGISTICS PROBLEMS IN A VIRTUAL ENTERPRISE THROUGH ARTIFICIAL INTELLIGENCE METHODS

    OpenAIRE

    PAVLENKO, Vitaliy; PAVLENKO, Tetiana; MOROZOVA, Olga; KUZNETSOVA, Anna; VOROPAI, Olena

    2017-01-01

    The paper offers a solution to the problem of material flow allocation within a virtual enterprise by using artificial intelligence methods. The research is based on the use of fuzzy relations when planning for optimal transportation modes to deliver components for manufactured products. The Fuzzy Logic Toolbox is used to determine the optimal route for transportation of components for manufactured products. The methods offered have been exemplified in the present research. The authors have b...

  3. A Reasoning Method of Cyber-Attack Attribution Based on Threat Intelligence

    OpenAIRE

    Li Qiang; Yang Ze-Ming; Liu Bao-Xu; Jiang Zheng-Wei

    2016-01-01

    With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain a...

  4. Future and Feature of Intelligent Systems and Their Societies

    African Journals Online (AJOL)

    2012-12-01

    Dec 1, 2012 ... work covered the consequences of having artificial intelligent systems with us in the near future. Keywords: intelligence, systems, artificial ... AI as science and technology to develop computers that can think and function in.

  5. 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) ... (2006) applied rainfall–runoff modeling using ANN ... in artificial intelligence, engineering and science .... usually be estimated from a sample of observations.

  6. Development of a method of continuous improvement of services using the Business Intelligence tools

    Directory of Open Access Journals (Sweden)

    Svetlana V. Kulikova

    2018-01-01

    Full Text Available The purpose of the study was to develop a method of continuous improvement of services using the Business Intelligence tools.Materials and methods: the materials are used on the concept of the Deming Cycle, methods and Business Intelligence technologies, Agile methodology and SCRUM.Results: the article considers the problem of continuous improvement of services and offers solutions using methods and technologies of Business Intelligence. In this case, the purpose of this technology is to solve and make the final decision regarding what needs to be improved in the current organization of services. In other words, Business Intelligence helps the product manager to see what is hidden from the “human eye” on the basis of received and processed data. Development of a method based on the concept of the Deming Cycle and Agile methodologies, and SCRUM.The article describes the main stages of development of method based on activity of the enterprise. It is necessary to fully build the Business Intelligence system in the enterprise to identify bottlenecks and justify the need for their elimination and, in general, for continuous improvement of the services. This process is represented in the notation of DFD. The article presents a scheme for the selection of suitable agile methodologies.The proposed concept of the solution of the stated objectives, including methods of identification of problems through Business Intelligence technology, development of the system for troubleshooting and analysis of results of the introduced changes. The technical description of the project is given.Conclusion: following the work of the authors there was formed the concept of the method for the continuous improvement of the services, using the Business Intelligence technology with the specifics of the enterprises, offering SaaS solutions. It was also found that when using this method, the recommended development methodology is SCRUM. The result of this scientific

  7. Intelligent Knowledge Recommendation Methods for R&D Knowledge Portals

    Institute of Scientific and Technical Information of China (English)

    KIM Jongwoo; LEE Hongjoo; PARK Sungjoo

    2004-01-01

    The personalization in knowledge portals and knowledge management systems is mainly performed based on users' explicitly specified categories and keywords. The explicit specification approach requires users' participation to start personalization services, and has limitation to adapt changes of users' preference. This paper suggests two implicit personalization approaches: automatic user category assignment method and automatic keyword profile generation method. The performances of the implicit personalization approaches are compared with traditional personalization approach using an Internet news site experiment. The result of the experiment shows that the suggested personalization approaches provide sufficient recommendation effectiveness with lessening users'unwanted involvement in personalization process.

  8. A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS

    Directory of Open Access Journals (Sweden)

    Grover Zurita

    2016-09-01

    Full Text Available In the industry, gears and rolling bearings failures are one of the foremost causes of breakdown in rotating machines, reducing availability time of the production and resulting in costly systems downtime. Therefore, there are growing demands for vibration condition based monitoring of gears and bearings, and any method in order to improve the effectiveness, reliability, and accuracy of the bearing faults diagnosis ought to be evaluated. In order to perform machine diagnosis efficiently, researchers have extensively investigated different advanced digital signal processing techniques and artificial intelligence methods to accurately extract fault characteristics from vibration signals. The main goal of this article is to present the state-of-the-art development in vibration analysis for machine diagnosis based on artificial intelligence methods.

  9. Intelligent screening of electrofusion-polyethylene joints based on a thermal NDT method

    Science.gov (United States)

    Doaei, Marjan; Tavallali, M. Sadegh

    2018-05-01

    The combinations of infrared thermal images and artificial intelligence methods have opened new avenues for pushing the boundaries of available testing methods. Hence, in the current study, a novel thermal non-destructive testing method for polyethylene electrofusion joints was combined with k-means clustering algorithms as an intelligent screening tool. The experiments focused on ovality of pipes in the coupler, as well as misalignment of pipes-couplers in 25 mm diameter joints. The temperature responses of each joint to an internal heat pulse were recorded by an IR thermal camera, and further processed to identify the faulty joints. The results represented clustering accuracy of 92%, as well as more than 90% abnormality detection capabilities.

  10. AI its nature and future

    CERN Document Server

    Boden, Margaret A

    2016-01-01

    least - on the Internet. Margaret Boden considers the realistic and unrealistic expectations we have placed on AI, analyses its progress, and considers the value of its byproducts. ations we have placed on AI, analyses its progress, and considers the value of its byproducts.

  11. State-of-the-art review of some artificial intelligence applications in pile foundations

    Directory of Open Access Journals (Sweden)

    Mohamed A. Shahin

    2016-01-01

    Full Text Available Geotechnical engineering deals with materials (e.g. soil and rock that, by their very nature, exhibit varied and uncertain behavior due to the imprecise physical processes associated with the formation of these materials. Modeling the behavior of such materials in geotechnical engineering applications is complex and sometimes beyond the ability of most traditional forms of physically-based engineering methods. Artificial intelligence (AI is becoming more popular and particularly amenable to modeling the complex behavior of most geotechnical engineering applications because it has demonstrated superior predictive ability compared to traditional methods. This paper provides state-of-the-art review of some selected AI techniques and their applications in pile foundations, and presents the salient features associated with the modeling development of these AI techniques. The paper also discusses the strength and limitations of the selected AI techniques compared to other available modeling approaches.

  12. State-of-the-art review of some artificial intelligence applications in pile foundations

    Institute of Scientific and Technical Information of China (English)

    Mohamed A. Shahin

    2016-01-01

    Geotechnical engineering deals with materials (e.g. soil and rock) that, by their very nature, exhibit varied and uncertain behavior due to the imprecise physical processes associated with the formation of these materials. Modeling the behavior of such materials in geotechnical engineering applications is complex and sometimes beyond the ability of most traditional forms of physically-based engineering methods. Artificial intelligence (AI) is becoming more popular and particularly amenable to modeling the complex behavior of most geotechnical engineering applications because it has demonstrated superior predictive ability compared to traditional methods. This paper provides state-of-the-art review of some selected AI techniques and their applications in pile foundations, and presents the salient features associated with the modeling development of these AI techniques. The paper also discusses the strength and limitations of the selected AI techniques compared to other available modeling approaches.

  13. Developing energy forecasting model using hybrid artificial intelligence method

    Institute of Scientific and Technical Information of China (English)

    Shahram Mollaiy-Berneti

    2015-01-01

    An important problem in demand planning for energy consumption is developing an accurate energy forecasting model. In fact, it is not possible to allocate the energy resources in an optimal manner without having accurate demand value. A new energy forecasting model was proposed based on the back-propagation (BP) type neural network and imperialist competitive algorithm. The proposed method offers the advantage of local search ability of BP technique and global search ability of imperialist competitive algorithm. Two types of empirical data regarding the energy demand (gross domestic product (GDP), population, import, export and energy demand) in Turkey from 1979 to 2005 and electricity demand (population, GDP, total revenue from exporting industrial products and electricity consumption) in Thailand from 1986 to 2010 were investigated to demonstrate the applicability and merits of the present method. The performance of the proposed model is found to be better than that of conventional back-propagation neural network with low mean absolute error.

  14. Integrating Symbolic and Statistical Methods for Testing Intelligent Systems Applications to Machine Learning and Computer Vision

    Energy Technology Data Exchange (ETDEWEB)

    Jha, Sumit Kumar [University of Central Florida, Orlando; Pullum, Laura L [ORNL; Ramanathan, Arvind [ORNL

    2016-01-01

    Embedded intelligent systems ranging from tiny im- plantable biomedical devices to large swarms of autonomous un- manned aerial systems are becoming pervasive in our daily lives. While we depend on the flawless functioning of such intelligent systems, and often take their behavioral correctness and safety for granted, it is notoriously difficult to generate test cases that expose subtle errors in the implementations of machine learning algorithms. Hence, the validation of intelligent systems is usually achieved by studying their behavior on representative data sets, using methods such as cross-validation and bootstrapping.In this paper, we present a new testing methodology for studying the correctness of intelligent systems. Our approach uses symbolic decision procedures coupled with statistical hypothesis testing to. We also use our algorithm to analyze the robustness of a human detection algorithm built using the OpenCV open-source computer vision library. We show that the human detection implementation can fail to detect humans in perturbed video frames even when the perturbations are so small that the corresponding frames look identical to the naked eye.

  15. Effects of Cooperative Learning Method Type Stad, Language Aptitude, and Intelligence on the Achievement English Hotel at Medan Tourism Academy

    Directory of Open Access Journals (Sweden)

    Abdul Kadir Ritonga

    2017-01-01

    Full Text Available STAD cooperative learning method which is considered effective in achieving the goal of learning the English language, especially for students majoring in Tourism Academy who are required to master English for Specific Purposes (ESP in accordance with their needs. This study uses factorial design 2x3x3 version of the non-equivalent control group design with ANOVA 3 Ways. The subjects were students MDK III / 5 A and B courses MDK III.5 Rooms Division department Hospitality Academy Year 2015/2016. The samples are saturated samples. Data were collected through a pretest, posttest, and instrument of Language Aptitude and Intelligence parametric statistics analyzed by parametric statistics with significance level of 0.05%. The results showed that: (1 there are differences between method STAD cooperative learning and expository on Hospitality English achievement, (2 there are differences between the students who have high language aptitude and low language aptitude on English achievement, (3 there are differences between students who have high language aptitude and medium on Hospitality English achievement, (4 there are differences between students who have the medium language aptitude and low language aptitude on Hospitality English achievement, (5 there are differences between students who have high intelligence and low intelligence\\ on Hospitality English achievement, (6 there are no differences between who have high intelligence and medium intelligence on Hospitality English achievement, (7 there are differences between students who have the medium intelligence and low intelligence on Hospitality English achievement, (8 there is no interaction between the learning method and language aptitude on Hospitality English achievement, (9 there is an interaction between the learning method and the intelligence on Hospitality English achievement, (10 there is no interaction between intelligence and language aptitude on Hospitality English achievement. (11

  16. Genetic algorithms in teaching artificial intelligence (automated generation of specific algebras)

    Science.gov (United States)

    Habiballa, Hashim; Jendryscik, Radek

    2017-11-01

    The problem of teaching essential Artificial Intelligence (AI) methods is an important task for an educator in the branch of soft-computing. The key focus is often given to proper understanding of the principle of AI methods in two essential points - why we use soft-computing methods at all and how we apply these methods to generate reasonable results in sensible time. We present one interesting problem solved in the non-educational research concerning automated generation of specific algebras in the huge search space. We emphasize above mentioned points as an educational case study of an interesting problem in automated generation of specific algebras.

  17. Brosimacutins A-I, nine new flavonoids from Brosimum acutifolium.

    Science.gov (United States)

    Takashima, Junko; Ohsaki, Ayumi

    2002-12-01

    Nine new flavonoids, brosimacutins A-I (1-9), and four known flavonoids were isolated from the bark of Brosimum acutifolium, a Brazilian folk medicine ("Mururé"). Their structures were elucidated by spectroscopic methods, including 2D NMR. Brosimacutins A-I possess differentially functionalized isoprene units at C-8.

  18. Artificial intelligence and engineering curricula - are changes needed?

    International Nuclear Information System (INIS)

    Jenkins, J.P.

    1988-01-01

    The purpose of this paper is to identify the expected impact of artificial intelligence (AI) on curricula and training courses. From this examination, new elements are proposed for the academic preparation and training of engineers who will evaluate and use these systems and capabilities. Artificial intelligence, from an operational viewpoint, begins with a set of rules governing the operation of logic, implemented via computer software and userware. These systems apply logic and experience to handling problems in an intelligent approach, especially when the number of alternatives to problem solution is beyond the scope of the human user. Usually, AI applications take the form of expert systems. An expert system embodies in the computer the knowledge-based component of an expert, such as domain knowledge and reasoning techniques, in such a form that the system can offer intelligent advice and, on demand, justify its own line of reasoning. Two languages predominate, LISP and Prolog. The AI user may interface with the knowledge base via one of these languages or by means of menu displays, cursor selections, or other conventional user interface methods

  19. Control and Driving Methods for LED Based Intelligent Light Sources

    DEFF Research Database (Denmark)

    Beczkowski, Szymon

    of the diode is controlled either by varying the magnitude of the current or by driving the LED with a pulsed current and regulate the width of the pulse. It has been shown previously, that these two methods yield different effects on diode's efficacy and colour point. A hybrid dimming strategy has been...... proposed where two variable quantities control the intensity of the diode. This increases the controllability of the diode giving new optimisation possibilities. It has been shown that it is possible to compensate for temperature drift of white diode's colour point using hybrid dimming strategy. Also...

  20. Artificial Intelligence Methods Applied to Parameter Detection of Atrial Fibrillation

    Science.gov (United States)

    Arotaritei, D.; Rotariu, C.

    2015-09-01

    In this paper we present a novel method to develop an atrial fibrillation (AF) based on statistical descriptors and hybrid neuro-fuzzy and crisp system. The inference of system produce rules of type if-then-else that care extracted to construct a binary decision system: normal of atrial fibrillation. We use TPR (Turning Point Ratio), SE (Shannon Entropy) and RMSSD (Root Mean Square of Successive Differences) along with a new descriptor, Teager- Kaiser energy, in order to improve the accuracy of detection. The descriptors are calculated over a sliding window that produce very large number of vectors (massive dataset) used by classifier. The length of window is a crisp descriptor meanwhile the rest of descriptors are interval-valued type. The parameters of hybrid system are adapted using Genetic Algorithm (GA) algorithm with fitness single objective target: highest values for sensibility and sensitivity. The rules are extracted and they are part of the decision system. The proposed method was tested using the Physionet MIT-BIH Atrial Fibrillation Database and the experimental results revealed a good accuracy of AF detection in terms of sensitivity and specificity (above 90%).

  1. Computational Foundations of Natural Intelligence.

    Science.gov (United States)

    van Gerven, Marcel

    2017-01-01

    New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.

  2. Computational Foundations of Natural Intelligence

    Directory of Open Access Journals (Sweden)

    Marcel van Gerven

    2017-12-01

    Full Text Available New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.

  3. Aerial robot intelligent control method based on back-stepping

    Science.gov (United States)

    Zhou, Jian; Xue, Qian

    2018-05-01

    The aerial robot is characterized as strong nonlinearity, high coupling and parameter uncertainty, a self-adaptive back-stepping control method based on neural network is proposed in this paper. The uncertain part of the aerial robot model is compensated online by the neural network of Cerebellum Model Articulation Controller and robust control items are designed to overcome the uncertainty error of the system during online learning. At the same time, particle swarm algorithm is used to optimize and fix parameters so as to improve the dynamic performance, and control law is obtained by the recursion of back-stepping regression. Simulation results show that the designed control law has desired attitude tracking performance and good robustness in case of uncertainties and large errors in the model parameters.

  4. Advances in intelligent diagnosis methods for pulmonary ground-glass opacity nodules.

    Science.gov (United States)

    Yang, Jing; Wang, Hailin; Geng, Chen; Dai, Yakang; Ji, Jiansong

    2018-02-07

    Pulmonary nodule is one of the important lesions of lung cancer, mainly divided into two categories of solid nodules and ground glass nodules. The improvement of diagnosis of lung cancer has significant clinical significance, which could be realized by machine learning techniques. At present, there have been a lot of researches focusing on solid nodules. But the research on ground glass nodules started late, and lacked research results. This paper summarizes the research progress of the method of intelligent diagnosis for pulmonary nodules since 2014. It is described in details from four aspects: nodular signs, data analysis methods, prediction models and system evaluation. This paper aims to provide the research material for researchers of the clinical diagnosis and intelligent analysis of lung cancer, and further improve the precision of pulmonary ground glass nodule diagnosis.

  5. An intelligent detection method for high-field asymmetric waveform ion mobility spectrometry.

    Science.gov (United States)

    Li, Yue; Yu, Jianwen; Ruan, Zhiming; Chen, Chilai; Chen, Ran; Wang, Han; Liu, Youjiang; Wang, Xiaozhi; Li, Shan

    2018-04-01

    In conventional high-field asymmetric waveform ion mobility spectrometry signal acquisition, multi-cycle detection is time consuming and limits somewhat the technique's scope for rapid field detection. In this study, a novel intelligent detection approach has been developed in which a threshold was set on the relative error of α parameters, which can eliminate unnecessary time spent on detection. In this method, two full-spectrum scans were made in advance to obtain the estimated compensation voltage at different dispersion voltages, resulting in a narrowing down of the whole scan area to just the peak area(s) of interest. This intelligent detection method can reduce the detection time to 5-10% of that of the original full-spectrum scan in a single cycle.

  6. A Lateral Control Method of Intelligent Vehicle Based on Fuzzy Neural Network

    Directory of Open Access Journals (Sweden)

    Linhui Li

    2015-01-01

    Full Text Available A lateral control method is proposed for intelligent vehicle to track the desired trajectory. Firstly, a lateral control model is established based on the visual preview and dynamic characteristics of intelligent vehicle. Then, the lateral error and orientation error are melded into an integrated error. Considering the system parameter perturbation and the external interference, a sliding model control is introduced in this paper. In order to design a sliding surface, the integrated error is chosen as the parameter of the sliding mode switching function. The sliding mode switching function and its derivative are selected as two inputs of the controller, and the front wheel angle is selected as the output. Next, a fuzzy neural network is established, and the self-learning functions of neural network is utilized to construct the fuzzy rules. Finally, the simulation results demonstrate the effectiveness and robustness of the proposed method.

  7. Condition Monitoring Using Computational Intelligence Methods Applications in Mechanical and Electrical Systems

    CERN Document Server

    Marwala, Tshilidzi

    2012-01-01

    Condition monitoring uses the observed operating characteristics of a machine or structure to diagnose trends in the signal being monitored and to predict the need for maintenance before a breakdown occurs. This reduces the risk, inherent in a fixed maintenance schedule, of performing maintenance needlessly early or of having a machine fail before maintenance is due either of which can be expensive with the latter also posing a risk of serious accident especially in systems like aeroengines in which a catastrophic failure would put lives at risk. The technique also measures responses from the whole of the system under observation so it can detect the effects of faults which might be hidden deep within a system, hidden from traditional methods of inspection. Condition Monitoring Using Computational Intelligence Methods promotes the various approaches gathered under the umbrella of computational intelligence to show how condition monitoring can be used to avoid equipment failures and lengthen its useful life, m...

  8. Developing an Intelligent Automatic Appendix Extraction Method from Ultrasonography Based on Fuzzy ART and Image Processing

    Directory of Open Access Journals (Sweden)

    Kwang Baek Kim

    2015-01-01

    Full Text Available Ultrasound examination (US does a key role in the diagnosis and management of the patients with clinically suspected appendicitis which is the most common abdominal surgical emergency. Among the various sonographic findings of appendicitis, outer diameter of the appendix is most important. Therefore, clear delineation of the appendix on US images is essential. In this paper, we propose a new intelligent method to extract appendix automatically from abdominal sonographic images as a basic building block of developing such an intelligent tool for medical practitioners. Knowing that the appendix is located at the lower organ area below the bottom fascia line, we conduct a series of image processing techniques to find the fascia line correctly. And then we apply fuzzy ART learning algorithm to the organ area in order to extract appendix accurately. The experiment verifies that the proposed method is highly accurate (successful in 38 out of 40 cases in extracting appendix.

  9. Application of artificial intelligence in Geodesy - A review of theoretical foundations and practical examples

    Science.gov (United States)

    Reiterer, Alexander; Egly, Uwe; Vicovac, Tanja; Mai, Enrico; Moafipoor, Shahram; Grejner-Brzezinska, Dorota A.; Toth, Charles K.

    2010-12-01

    Artificial Intelligence (AI) is one of the key technologies in many of today's novel applications. It is used to add knowledge and reasoning to systems. This paper illustrates a review of AI methods including examples of their practical application in Geodesy like data analysis, deformation analysis, navigation, network adjustment, and optimization of complex measurement procedures. We focus on three examples, namely, a geo-risk assessment system supported by a knowledge-base, an intelligent dead reckoning personal navigator, and evolutionary strategies for the determination of Earth gravity field parameters. Some of the authors are members of IAG Sub-Commission 4.2 - Working Group 4.2.3, which has the main goal to study and report on the application of AI in Engineering Geodesy.

  10. Long Term Solar Radiation Forecast Using Computational Intelligence Methods

    Directory of Open Access Journals (Sweden)

    João Paulo Coelho

    2014-01-01

    Full Text Available The point prediction quality is closely related to the model that explains the dynamic of the observed process. Sometimes the model can be obtained by simple algebraic equations but, in the majority of the physical systems, the relevant reality is too hard to model with simple ordinary differential or difference equations. This is the case of systems with nonlinear or nonstationary behaviour which require more complex models. The discrete time-series problem, obtained by sampling the solar radiation, can be framed in this type of situation. By observing the collected data it is possible to distinguish multiple regimes. Additionally, due to atmospheric disturbances such as clouds, the temporal structure between samples is complex and is best described by nonlinear models. This paper reports the solar radiation prediction by using hybrid model that combines support vector regression paradigm and Markov chains. The hybrid model performance is compared with the one obtained by using other methods like autoregressive (AR filters, Markov AR models, and artificial neural networks. The results obtained suggests an increasing prediction performance of the hybrid model regarding both the prediction error and dynamic behaviour.

  11. An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

    OpenAIRE

    Bo Sun; Qiang Feng; Songjie Li

    2012-01-01

    According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules) based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negoti...

  12. Method and apparatus for optimizing operation of a power generating plant using artificial intelligence techniques

    Science.gov (United States)

    Wroblewski, David [Mentor, OH; Katrompas, Alexander M [Concord, OH; Parikh, Neel J [Richmond Heights, OH

    2009-09-01

    A method and apparatus for optimizing the operation of a power generating plant using artificial intelligence techniques. One or more decisions D are determined for at least one consecutive time increment, where at least one of the decisions D is associated with a discrete variable for the operation of a power plant device in the power generating plant. In an illustrated embodiment, the power plant device is a soot cleaning device associated with a boiler.

  13. Mapping change in scientific specialties: a scientometric case study of the development or artificial intelligence

    NARCIS (Netherlands)

    van den Besselaar, P.; Leydesdorff, L.

    1996-01-01

    Has an identifiable core of activities called AI been established, during the AI-boom in the eighties? Is AI already in a “paradigmatic” phase? There has been a lot of disagreement among commentators and specialists about the nature of Artificial Intelligence as a specialty. This makes AI an

  14. A framework for AI-based nuclear design support system

    International Nuclear Information System (INIS)

    Furuta, Kazuo; Kondo, Shunsuke

    1991-01-01

    Nowadays many computer programs are being developed and used for the analytic tasks in nuclear reactor design, but experienced designers are still responsible for most of the synthetic tasks which are not amenable to algorithmic computer processes. Artificial intelligence (AI) is a promising technology to deal with these intractable tasks in design. In development of AI-based design support systems, it is desirable to choose a comprehensive framework based on the scientific theory of design. In this work a framework for AI-based design support systems for nuclear reactor design will be proposed based on an exploration model of design. The fundamental architectures of this framework will be described especially on knowledge representation, context management and design planning. (author)

  15. Framework for AI-based nuclear reactor design support system

    International Nuclear Information System (INIS)

    Furuta, Kazuo; Kondo, Shunsuke

    1992-01-01

    Nowadays many computer programs are being developed and used for the analytic tasks in nuclear reactor design, but experienced designers are still responsible for most of the synthetic tasks which are not amenable to algorithmic computer processes. Artificial intelligence (AI) is a promising technology to deal with these intractable tasks in design. In development of AI-based design support systems, it is desirable to choose a comprehensive framework based on the scientific theory of design. In this work a framework for AI-based design support systems for nuclear reactor design will be proposed based on an explorative abduction model of design. The fundamental architectures of this framework will be described especially on knowledge representation, context management and design planning. (author)

  16. Towards AI-powered personalization in MOOC learning

    Science.gov (United States)

    Yu, Han; Miao, Chunyan; Leung, Cyril; White, Timothy John

    2017-12-01

    Massive Open Online Courses (MOOCs) represent a form of large-scale learning that is changing the landscape of higher education. In this paper, we offer a perspective on how advances in artificial intelligence (AI) may enhance learning and research on MOOCs. We focus on emerging AI techniques including how knowledge representation tools can enable students to adjust the sequence of learning to fit their own needs; how optimization techniques can efficiently match community teaching assistants to MOOC mediation tasks to offer personal attention to learners; and how virtual learning companions with human traits such as curiosity and emotions can enhance learning experience on a large scale. These new capabilities will also bring opportunities for educational researchers to analyse students' learning skills and uncover points along learning paths where students with different backgrounds may require different help. Ethical considerations related to the application of AI in MOOC education research are also discussed.

  17. Comparison of artificial intelligence methods and empirical equations to estimate daily solar radiation

    Science.gov (United States)

    Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

    2016-08-01

    In the present research, three artificial intelligence methods including Gene Expression Programming (GEP), Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) as well as, 48 empirical equations (10, 12 and 26 equations were temperature-based, sunshine-based and meteorological parameters-based, respectively) were used to estimate daily solar radiation in Kerman, Iran in the period of 1992-2009. To develop the GEP, ANN and ANFIS models, depending on the used empirical equations, various combinations of minimum air temperature, maximum air temperature, mean air temperature, extraterrestrial radiation, actual sunshine duration, maximum possible sunshine duration, sunshine duration ratio, relative humidity and precipitation were considered as inputs in the mentioned intelligent methods. To compare the accuracy of empirical equations and intelligent models, root mean square error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE) and determination coefficient (R2) indices were used. The results showed that in general, sunshine-based and meteorological parameters-based scenarios in ANN and ANFIS models presented high accuracy than mentioned empirical equations. Moreover, the most accurate method in the studied region was ANN11 scenario with five inputs. The values of RMSE, MAE, MARE and R2 indices for the mentioned model were 1.850 MJ m-2 day-1, 1.184 MJ m-2 day-1, 9.58% and 0.935, respectively.

  18. Probabilistic reasoning in intelligent systems networks of plausible inference

    CERN Document Server

    Pearl, Judea

    1988-01-01

    Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provid

  19. Artificial Intelligence Support for Computational Chemistry

    Science.gov (United States)

    Duch, Wlodzislaw

    Possible forms of artificial intelligence (AI) support for quantum chemistry are discussed. Questions addressed include: what kind of support is desirable, what kind of support is feasible, what can we expect in the coming years. Advantages and disadvantages of current AI techniques are presented and it is argued that at present the memory-based systems are the most effective for large scale applications. Such systems may be used to predict the accuracy of calculations and to select the least expensive methods and basis sets belonging to the same accuracy class. Advantages of the Feature Space Mapping as an improvement on the memory based systems are outlined and some results obtained in classification problems given. Relevance of such classification systems to computational chemistry is illustrated with two examples showing similarity of results obtained by different methods that take electron correlation into account.

  20. How AI turned the chess world upside down

    KAUST Repository

    Polgar, Susan

    2018-01-22

    Man vs. Machine! In 1977 an IBM supercomputer \\'Deep Blue\\' beat the reigning World Chess Champion Gary Kasparov in a 6 game chess match played under tournament conditions. This was the first time a machine beat a human at chess. It symbolized the emergence of Artificial Intelligence (AI) and the potential for great good (and great harm) from machines that have aspects of human intelligence. During this lecture Susan Polgar, a pioneer for Women in Chess, will share her remarkable story as well as how technology has changed the world of chess.

  1. Intelligent fault diagnosis and failure management of flight control actuation systems

    Science.gov (United States)

    Bonnice, William F.; Baker, Walter

    1988-01-01

    The real-time fault diagnosis and failure management (FDFM) of current operational and experimental dual tandem aircraft flight control system actuators was investigated. Dual tandem actuators were studied because of the active FDFM capability required to manage the redundancy of these actuators. The FDFM methods used on current dual tandem actuators were determined by examining six specific actuators. The FDFM capability on these six actuators was also evaluated. One approach for improving the FDFM capability on dual tandem actuators may be through the application of artificial intelligence (AI) technology. Existing AI approaches and applications of FDFM were examined and evaluated. Based on the general survey of AI FDFM approaches, the potential role of AI technology for real-time actuator FDFM was determined. Finally, FDFM and maintainability improvements for dual tandem actuators were recommended.

  2. Ada in AI or AI in Ada. On developing a rationale for integration

    Science.gov (United States)

    Collard, Philippe E.; Goforth, Andre

    1988-01-01

    The use of Ada as an Artificial Intelligence (AI) language is gaining interest in the NASA Community, i.e., by parties who have a need to deploy Knowledge Based-Systems (KBS) compatible with the use of Ada as the software standard for the Space Station. A fair number of KBS and pseudo-KBS implementations in Ada exist today. Currently, no widely used guidelines exist to compare and evaluate these with one another. The lack of guidelines illustrates a fundamental problem inherent in trying to compare and evaluate implementations of any sort in languages that are procedural or imperative in style, such as Ada, with those in languages that are functional in style, such as Lisp. Discussed are the strengths and weakness of using Ada as an AI language and a preliminary analysis provided of factors needed for the development of criteria for the integration of these two families of languages and the environments in which they are implemented. The intent for developing such criteria is to have a logical rationale that may be used to guide the development of Ada tools and methodology to support KBS requirements, and to identify those AI technology components that may most readily and effectively be deployed in Ada.

  3. Little AI: Playing a constructivist robot

    Science.gov (United States)

    Georgeon, Olivier L.

    Little AI is a pedagogical game aimed at presenting the founding concepts of constructivist learning and developmental Artificial Intelligence. It primarily targets students in computer science and cognitive science but it can also interest the general public curious about these topics. It requires no particular scientific background; even children can find it entertaining. Professors can use it as a pedagogical resource in class or in online courses. The player presses buttons to control a simulated "baby robot". The player cannot see the robot and its environment, and initially ignores the effects of the commands. The only information received by the player is feedback from the player's commands. The player must learn, at the same time, the functioning of the robot's body and the structure of the environment from patterns in the stream of commands and feedback. We argue that this situation is analogous to how infants engage in early-stage developmental learning (e.g., Piaget (1937), [1]).

  4. Is Intelligence Artificial?

    OpenAIRE

    Greer, Kieran

    2014-01-01

    Our understanding of intelligence is directed primarily at the level of human beings. This paper attempts to give a more unifying definition that can be applied to the natural world in general. The definition would be used more to verify a degree of intelligence, not to quantify it and might help when making judgements on the matter. A version of an accepted test for AI is then put forward as the 'acid test' for Artificial Intelligence itself. It might be what a free-thinking program or robot...

  5. Code AI Personal Web Pages

    Science.gov (United States)

    Garcia, Joseph A.; Smith, Charles A. (Technical Monitor)

    1998-01-01

    The document consists of a publicly available web site (george.arc.nasa.gov) for Joseph A. Garcia's personal web pages in the AI division. Only general information will be posted and no technical material. All the information is unclassified.

  6. Making Computers Smarter: A Look At the Controversial Field of Artificial Intelligence.

    Science.gov (United States)

    Green, John O.

    1984-01-01

    Defines artificial intelligence (AI) and discusses its history; the current state of the art, research, experimentation, and practical applications; and probable future developments. Key dates in the history of AI and eight references are provided. (MBR)

  7. Proceedings of conference on AI applications in physical sciences

    International Nuclear Information System (INIS)

    1993-01-01

    A Conference cum workshop on AI applications in Physical Sciences was organised by the Indian Physics Association at Bhabha Atomic Research Centre, Bombay during January 15-17, 1992. It was held in memory of Late Shri S.N. Seshadri, who was the moving spirit behind self reliance in instrumentation development for research and industry. The two day conference which was followed by one day workshop covered the following broad spectrum of topics in Artificial Intelligence: AI Tools and Techniques, Neural Networks, Robotics and Machine Vision, Fuzzy Control and Applications, Natural Language and Speech Processing, Knowledge based Systems, and AI and Allied applications. The conference dealt with recent advances and achievements in AI. It provided a forum for the exchange of valuable information and expertise in this fast emerging field. Over 200 scientists, engineers and computer professionals from various universities, R and D institutes and industries actively participated. 45 contributed papers and 8 invited talks were presented in the symposium. The volume contains selected papers which were contributed by the participants. Some of them dealt with AI applications in nuclear science and technology. (original)

  8. Application of artificial intelligence methods for prediction of steel mechanical properties

    Directory of Open Access Journals (Sweden)

    Z. Jančíková

    2008-10-01

    Full Text Available The target of the contribution is to outline possibilities of applying artificial neural networks for the prediction of mechanical steel properties after heat treatment and to judge their perspective use in this field. The achieved models enable the prediction of final mechanical material properties on the basis of decisive parameters influencing these properties. By applying artificial intelligence methods in combination with mathematic-physical analysis methods it will be possible to create facilities for designing a system of the continuous rationalization of existing and also newly developing industrial technologies.

  9. SOLVING TRANSPORT LOGISTICS PROBLEMS IN A VIRTUAL ENTERPRISE THROUGH ARTIFICIAL INTELLIGENCE METHODS

    Directory of Open Access Journals (Sweden)

    Vitaliy PAVLENKO

    2017-06-01

    Full Text Available The paper offers a solution to the problem of material flow allocation within a virtual enterprise by using artificial intelligence methods. The research is based on the use of fuzzy relations when planning for optimal transportation modes to deliver components for manufactured products. The Fuzzy Logic Toolbox is used to determine the optimal route for transportation of components for manufactured products. The methods offered have been exemplified in the present research. The authors have built a simulation model for component transportation and delivery for manufactured products using the Simulink graphical environment for building models.

  10. Intelligent tuning method of PID parameters based on iterative learning control for atomic force microscopy.

    Science.gov (United States)

    Liu, Hui; Li, Yingzi; Zhang, Yingxu; Chen, Yifu; Song, Zihang; Wang, Zhenyu; Zhang, Suoxin; Qian, Jianqiang

    2018-01-01

    Proportional-integral-derivative (PID) parameters play a vital role in the imaging process of an atomic force microscope (AFM). Traditional parameter tuning methods require a lot of manpower and it is difficult to set PID parameters in unattended working environments. In this manuscript, an intelligent tuning method of PID parameters based on iterative learning control is proposed to self-adjust PID parameters of the AFM according to the sample topography. This method gets enough information about the output signals of PID controller and tracking error, which will be used to calculate the proper PID parameters, by repeated line scanning until convergence before normal scanning to learn the topography. Subsequently, the appropriate PID parameters are obtained by fitting method and then applied to the normal scanning process. The feasibility of the method is demonstrated by the convergence analysis. Simulations and experimental results indicate that the proposed method can intelligently tune PID parameters of the AFM for imaging different topographies and thus achieve good tracking performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. A new hybrid optimization method inspired from swarm intelligence: Fuzzy adaptive swallow swarm optimization algorithm (FASSO

    Directory of Open Access Journals (Sweden)

    Mehdi Neshat

    2015-11-01

    Full Text Available In this article, the objective was to present effective and optimal strategies aimed at improving the Swallow Swarm Optimization (SSO method. The SSO is one of the best optimization methods based on swarm intelligence which is inspired by the intelligent behaviors of swallows. It has been able to offer a relatively strong method for solving optimization problems. However, despite its many advantages, the SSO suffers from two shortcomings. Firstly, particles movement speed is not controlled satisfactorily during the search due to the lack of an inertia weight. Secondly, the variables of the acceleration coefficient are not able to strike a balance between the local and the global searches because they are not sufficiently flexible in complex environments. Therefore, the SSO algorithm does not provide adequate results when it searches in functions such as the Step or Quadric function. Hence, the fuzzy adaptive Swallow Swarm Optimization (FASSO method was introduced to deal with these problems. Meanwhile, results enjoy high accuracy which are obtained by using an adaptive inertia weight and through combining two fuzzy logic systems to accurately calculate the acceleration coefficients. High speed of convergence, avoidance from falling into local extremum, and high level of error tolerance are the advantages of proposed method. The FASSO was compared with eleven of the best PSO methods and SSO in 18 benchmark functions. Finally, significant results were obtained.

  12. Cognitive Artificial Intelligence Method for Interpreting Transformer Condition Based on Maintenance Data

    Directory of Open Access Journals (Sweden)

    Karel Octavianus Bachri

    2017-07-01

    Full Text Available A3S(Arwin-Adang-Aciek-Sembiring is a method of information fusion at a single observation and OMA3S(Observation Multi-time A3S is a method of information fusion for time-series data. This paper proposes OMA3S-based Cognitive Artificial-Intelligence method for interpreting Transformer Condition, which is calculated based on maintenance data from Indonesia National Electric Company (PLN. First, the proposed method is tested using the previously published data, and then followed by implementation on maintenance data. Maintenance data are fused to obtain part condition, and part conditions are fused to obtain transformer condition. Result shows proposed method is valid for DGA fault identification with the average accuracy of 91.1%. The proposed method not only can interpret the major fault, it can also identify the minor fault occurring along with the major fault, allowing early warning feature. Result also shows part conditions can be interpreted using information fusion on maintenance data, and the transformer condition can be interpreted using information fusion on part conditions. The future works on this research is to gather more data, to elaborate more factors to be fused, and to design a cognitive processor that can be used to implement this concept of intelligent instrumentation.

  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. 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.

  15. 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...

  16. Semantics and artificial intelligence in machine translation

    Energy Technology Data Exchange (ETDEWEB)

    King, M

    1981-01-01

    The author exemplifies three types of ambiguity that the introduction of semantics or of AI methods might be expected to solve: word sense, structural, and referential ambiguity. From this point of view she examines the works of Schank, Riesbeck, Minsky, Charniak, and Wilks, and she comes to the conclusion that the systems described will not be of much help for the development of operational MT-systems, except within a well-defined, constrained world. The latter aspect is illustrated by the author by means of a description of the Edinburgh Mecho-project. But, as the vast majority of texts destined for MT does not come from a constrained world, such systems will hardly be used as MT production systems. Still, MT-systems like Eurotra give the chance of making intelligent use of AI ideas. 16 references.

  17. Research on Intelligent Avoidance Method of Shipwreck Based on Bigdata Analysis

    Directory of Open Access Journals (Sweden)

    Li Wei

    2017-11-01

    Full Text Available In order to solve the problem that current avoidance method of shipwreck has the problem of low success rate of avoidance, this paper proposes a method of intelligent avoidance of shipwreck based on big data analysis. Firstly,our method used big data analysis to calculate the safe distance of approach of ship under the head-on situation, the crossing situation and the overtaking situation.On this basis, by calculating the risk-degree of collision of ships,our research determined the degree of immediate danger of ships.Finally, we calculated the three kinds of evaluation function of ship navigation, and used genetic algorithm to realize the intelligent avoidance of shipwreck.Experimental result shows that compared the proposed method with the traditional method in two in a recent meeting when the distance to closest point of approach between two ships is 0.13nmile, they can effectively evade.The success rate of avoidance is high.

  18. Radioimmunoassay of apolipoprotein A-I of rat serum

    International Nuclear Information System (INIS)

    Fainaru, M.; Havel, R.J.; Felker, T.E.

    1976-01-01

    A double antibody radioimmunoassay technique was developed for quantification of apolipoprotein A-I, the major apoprotein of rat high density lipoprotein. Apo A-I was labelled with 125 I by the chloramine-T method. 125 I-labeled apo A-I had the same electrophoretic mobility as unlabeled apo A-I and more than 80% of the 125 I was precipitated by rabbit anti apo A-I antibodies. The assay is sensitive at the level of 0.5-5 ng, and has intraassay and interassay coefficients of variation of 4.5 and 6.5% respectively. The specificity of the assay was established by competitive displacement of 125 I-labeled apo A-I from its antibody by apo A-I and lipoproteins containing apo A-I, but not by rat albumin and other apoproteins. Immunoreactivity of high density lipoprotein and serum was only about 35% of that of their delipidated forms when Veronal buffer was used as a diluent. Inclusion of 5 mM sodium decyl sulfate in the incubation mixture brought out reactivity equivalent to that found after delipidation. Completeness of the reaction was verified by comparison with the amount of apo A-I in chromatographic fractions of the total apoprotein of high density lipoprotein. Content (weight %, mean values +- S.D.) of immunoassayable apo A-I was: 62.3 +- 5.9 in high density lipoprotein; 1.7 +- 0.3 in low density lipoprotein; 0.09 +- 0.03 in very low density lipoprotein and 25.0 +- 5.0 in lymph chylomicrons. Concentration in whole serum was 51.4 +- 8.9 mg/dl and 33.6 +- 4.1 mg/dl for female and male rats, respectively (p 1.21 g/ml and <1% in lipoproteins of d<1.063 g/ml

  19. 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.…

  20. Nonlinear study of AI Velorum

    International Nuclear Information System (INIS)

    Cox, A.N.; Hodson, S.W.

    1979-01-01

    Using results from earlier studies of double-mode dwarf Cepheids by Cox, King, and Hodson, hydrodynamic calculations were undertaken for AI Vel. The earlier derived evolution theory mass of 1.8 M sub solar, a luminosity of of 23 L sub solar and a T/sub e/ of 7500 0 K give the observed period of 0.11 day and the observed period ratio PI 1 /PI 0 = 0.773. A cooler T/sub e/ than the observed one (7620 0 K) was used because 7620 0 K is beyond the fundamental pulsation mode blue edge. The composition used is X = 0.70 Z = 0.01. This lower than normal Z is necessary to make the period ratio as large as observed. The goal is to see if double-mode behavior, due to either mode switching or a permanent state, can be predicted for the model. Progress in converging the model to a periodic pulsation solution by the von Sengbusch--Stellingwerf relaxation method will be reported. 17 references

  1. 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.

  2. Adding intelligence to scientific data management

    Science.gov (United States)

    Campbell, William J.; Short, Nicholas M., Jr.; Treinish, Lloyd A.

    1989-01-01

    NASA plans to solve some of the problems of handling large-scale scientific data bases by turning to artificial intelligence (AI) are discussed. The growth of the information glut and the ways that AI can help alleviate the resulting problems are reviewed. The employment of the Intelligent User Interface prototype, where the user will generate his own natural language query with the assistance of the system, is examined. Spatial data management, scientific data visualization, and data fusion are discussed.

  3. 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...

  4. Hybrid Intelligent Control Method to Improve the Frequency Support Capability of Wind Energy Conversion Systems

    Directory of Open Access Journals (Sweden)

    Shin Young Heo

    2015-10-01

    Full Text Available This paper presents a hybrid intelligent control method that enables frequency support control for permanent magnet synchronous generators (PMSGs wind turbines. The proposed method for a wind energy conversion system (WECS is designed to have PMSG modeling and full-scale back-to-back insulated-gate bipolar transistor (IGBT converters comprising the machine and grid side. The controller of the machine side converter (MSC and the grid side converter (GSC are designed to achieve maximum power point tracking (MPPT based on an improved hill climb searching (IHCS control algorithm and de-loaded (DL operation to obtain a power margin. Along with this comprehensive control of maximum power tracking mode based on the IHCS, a method for kinetic energy (KE discharge control of the supporting primary frequency control scheme with DL operation is developed to regulate the short-term frequency response and maintain reliable operation of the power system. The effectiveness of the hybrid intelligent control method is verified by a numerical simulation in PSCAD/EMTDC. Simulation results show that the proposed approach can improve the frequency regulation capability in the power system.

  5. Based on Short Motion Paths and Artificial Intelligence Method for Chinese Chess Game

    Directory of Open Access Journals (Sweden)

    Chien-Ming Hung

    2017-08-01

    Full Text Available The article develops the decision rules to win each set of the Chinese chess game using evaluation algorithm and artificial intelligence method, and uses the mobile robot to be instead of the chess, and presents the movement scenarios using the shortest motion paths for mobile robots. Player can play the Chinese chess game according to the game rules with the supervised computer. The supervised computer decides the optimal motion path to win the set using artificial intelligence method, and controls mobile robots according to the programmed motion paths of the assigned chesses moving on the platform via wireless RF interface. We uses enhance A* searching algorithm to solve the shortest path problem of the assigned chess, and solve the collision problems of the motion paths for two mobile robots moving on the platform simultaneously. We implement a famous set to be called lwild horses run in farmr using the proposed method. First we use simulation method to display the motion paths of the assigned chesses for the player and the supervised computer. Then the supervised computer implements the simulation results on the chessboard platform using mobile robots. Mobile robots move on the chessboard platform according to the programmed motion paths and is guided to move on the centre line of the corridor, and avoid the obstacles (chesses, and detect the cross point of the platform using three reflective IR modules.

  6. 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.

  7. Artificial intelligence applications at the ICPP

    International Nuclear Information System (INIS)

    Johnson, C.E.

    1989-01-01

    Westinghouse Idaho Nuclear Company (WINCO) initiated an aggressive program for artificial intelligence (AI) expert system implementations in 1985. The first expert system, Safety Analysis Methods Advisor (SAMA) was completed in 1986 to help operational safety analysts select analysis methodologies for safety analysis reports. The SAMA expert system was implemented as a rule-based system using a commercial expert system shell. The major benefit of the system is for training new safety analysts. The first successful implementation launched three other expert system projects: a process alarm filtering system, a process control advisor, and a mass spectrometer trouble-shooting advisor. This paper describes the current status of these projects

  8. An Opening Chapter of the First Generation of Artificial Intelligence in Medicine: The First Rutgers AIM Workshop, June 1975.

    Science.gov (United States)

    Kulikowski, C A

    2015-08-13

    The first generation of Artificial Intelligence (AI) in Medicine methods were developed in the early 1970's drawing on insights about problem solving in AI. They developed new ways of representing structured expert knowledge about clinical and biomedical problems using causal, taxonomic, associational, rule, and frame-based models. By 1975, several prototype systems had been developed and clinically tested, and the Rutgers Research Resource on Computers in Biomedicine hosted the first in a series of workshops on AI in Medicine that helped researchers and clinicians share their ideas, demonstrate their models, and comment on the prospects for the field. These developments and the workshops themselves benefited considerably from Stanford's SUMEX-AIM pioneering experiment in biomedical computer networking. This paper focuses on discussions about issues at the intersection of medicine and artificial intelligence that took place during the presentations and panels at the First Rutgers AIM Workshop in New Brunswick, New Jersey from June 14 to 17, 1975.

  9. Intelligent Detection of Structure from Remote Sensing Images Based on Deep Learning Method

    Science.gov (United States)

    Xin, L.

    2018-04-01

    Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.

  10. An Intelligent Method of Product Scheme Design Based on Product Gene

    Directory of Open Access Journals (Sweden)

    Qing Song Ai

    2013-01-01

    Full Text Available Nowadays, in order to have some featured products, many customers tend to buy customized products instead of buying common ones in supermarket. The manufacturing enterprises, with the purpose of improving their competitiveness, are focusing on providing customized products with high quality and low cost as well. At present, how to produce customized products rapidly and cheaply has been the key challenge to manufacturing enterprises. In this paper, an intelligent modeling approach applied to supporting the modeling of customized products is proposed, which may improve the efficiency during the product design process. Specifically, the product gene (PG method, which is an analogy of biological evolution in engineering area, is employed to model products in a new way. Based on product gene, we focus on the intelligent modeling method to generate product schemes rapidly and automatically. The process of our research includes three steps: (1 develop a product gene model for customized products; (2 find the obtainment and storage method for product gene; and (3 propose a specific genetic algorithm used for calculating the solution of customized product and generating new product schemes. Finally, a case study is applied to test the usefulness of our study.

  11. 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.

  12. Artificial Intelligence in Surgery: Promises and Perils.

    Science.gov (United States)

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

    2018-07-01

    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.

  13. 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.

  14. Artificial intelligence techniques used in respiratory sound analysis--a systematic review.

    Science.gov (United States)

    Palaniappan, Rajkumar; Sundaraj, Kenneth; Sundaraj, Sebastian

    2014-02-01

    Artificial intelligence (AI) has recently been established as an alternative method to many conventional methods. The implementation of AI techniques for respiratory sound analysis can assist medical professionals in the diagnosis of lung pathologies. This article highlights the importance of AI techniques in the implementation of computer-based respiratory sound analysis. Articles on computer-based respiratory sound analysis using AI techniques were identified by searches conducted on various electronic resources, such as the IEEE, Springer, Elsevier, PubMed, and ACM digital library databases. Brief descriptions of the types of respiratory sounds and their respective characteristics are provided. We then analyzed each of the previous studies to determine the specific respiratory sounds/pathology analyzed, the number of subjects, the signal processing method used, the AI techniques used, and the performance of the AI technique used in the analysis of respiratory sounds. A detailed description of each of these studies is provided. In conclusion, this article provides recommendations for further advancements in respiratory sound analysis.

  15. Implementasi Rule Base System dan Fuzzy Logic Artifical Intelligence pada Game Kartu Capsa

    OpenAIRE

    Pangkatodi, Edo; Liliana, Liliana; Budhi, Gregorius Satia

    2016-01-01

    In the era of globalization today, science and technology is developing very fast, particularly in entertainment media, specifically in the gaming world. Today, games are not only used as an entertainment, but also can be used as an alternative in the world of work, education, and even sports. In the world of gaming, artificial intelligence, or AI is a factor that cannot be separated. With the right methods and the specific rules of the AI can walk like a human being doing a job. So it is not...

  16. 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.

  17. Prediction of shear wave velocity using empirical correlations and artificial intelligence methods

    Science.gov (United States)

    Maleki, Shahoo; Moradzadeh, Ali; Riabi, Reza Ghavami; Gholami, Raoof; Sadeghzadeh, Farhad

    2014-06-01

    Good understanding of mechanical properties of rock formations is essential during the development and production phases of a hydrocarbon reservoir. Conventionally, these properties are estimated from the petrophysical logs with compression and shear sonic data being the main input to the correlations. This is while in many cases the shear sonic data are not acquired during well logging, which may be for cost saving purposes. In this case, shear wave velocity is estimated using available empirical correlations or artificial intelligent methods proposed during the last few decades. In this paper, petrophysical logs corresponding to a well drilled in southern part of Iran were used to estimate the shear wave velocity using empirical correlations as well as two robust artificial intelligence methods knows as Support Vector Regression (SVR) and Back-Propagation Neural Network (BPNN). Although the results obtained by SVR seem to be reliable, the estimated values are not very precise and considering the importance of shear sonic data as the input into different models, this study suggests acquiring shear sonic data during well logging. It is important to note that the benefits of having reliable shear sonic data for estimation of rock formation mechanical properties will compensate the possible additional costs for acquiring a shear log.

  18. Methods of Computational Intelligence in the Context of Quality Assurance in Foundry Products

    Directory of Open Access Journals (Sweden)

    Rojek G.

    2016-06-01

    Full Text Available One way to ensure the required technical characteristics of castings is the strict control of production parameters affecting the quality of the finished products. If the production process is improperly configured, the resulting defects in castings lead to huge losses. Therefore, from the point of view of economics, it is advisable to use the methods of computational intelligence in the field of quality assurance and adjustment of parameters of future production. At the same time, the development of knowledge in the field of metallurgy, aimed to raise the technical level and efficiency of the manufacture of foundry products, should be followed by the development of information systems to support production processes in order to improve their effectiveness and compliance with the increasingly more stringent requirements of ergonomics, occupational safety, environmental protection and quality. This article is a presentation of artificial intelligence methods used in practical applications related to quality assurance. The problem of control of the production process involves the use of tools such as the induction of decision trees, fuzzy logic, rough set theory, artificial neural networks or case-based reasoning.

  19. Prediction of shear wave velocity using empirical correlations and artificial intelligence methods

    Directory of Open Access Journals (Sweden)

    Shahoo Maleki

    2014-06-01

    Full Text Available Good understanding of mechanical properties of rock formations is essential during the development and production phases of a hydrocarbon reservoir. Conventionally, these properties are estimated from the petrophysical logs with compression and shear sonic data being the main input to the correlations. This is while in many cases the shear sonic data are not acquired during well logging, which may be for cost saving purposes. In this case, shear wave velocity is estimated using available empirical correlations or artificial intelligent methods proposed during the last few decades. In this paper, petrophysical logs corresponding to a well drilled in southern part of Iran were used to estimate the shear wave velocity using empirical correlations as well as two robust artificial intelligence methods knows as Support Vector Regression (SVR and Back-Propagation Neural Network (BPNN. Although the results obtained by SVR seem to be reliable, the estimated values are not very precise and considering the importance of shear sonic data as the input into different models, this study suggests acquiring shear sonic data during well logging. It is important to note that the benefits of having reliable shear sonic data for estimation of rock formation mechanical properties will compensate the possible additional costs for acquiring a shear log.

  20. Intelligent Continuous Double Auction method For Service Allocation in Cloud Computing

    Directory of Open Access Journals (Sweden)

    Nima Farajian

    2013-10-01

    Full Text Available Market-oriented approach is an effective method for resource management because of its regulation of supply and demand and is suitable for cloud environment where the computing resources, either software or hardware, are virtualized and allocated as services from providers to users. In this paper a continuous double auction method for efficient cloud service allocation is presented in which i enables consumers to order various resources (services for workflows and coallocation, ii consumers and providers make bid and request prices based on deadline and workload time and in addition providers can tradeoff between utilization time and price of bids, iii auctioneers can intelligently find optimum matching by sharing and merging resources which result more trades. Experimental results show that proposed method is efficient in terms of successful allocation rate and resource utilization.

  1. 5th International Workshop on Combinations of Intelligent Methods and Applications

    CERN Document Server

    Palade, Vasile; Prentzas, Jim

    2017-01-01

    Complex problems usually cannot be solved by individual methods or techniques and require the synergism of more than one of them to be solved. This book presents a number of current efforts that use combinations of methods or techniques to solve complex problems in the areas of sentiment analysis, search in GIS, graph-based social networking, intelligent e-learning systems, data mining and recommendation systems. Most of them are connected with specific applications, whereas the rest are combinations based on principles. Most of the chapters are extended versions of the corresponding papers presented in CIMA-15 Workshop, which took place in conjunction with IEEE ICTAI-15, in November 2015. The rest are invited papers that responded to special call for papers for the book. The book is addressed to researchers and practitioners from academia or industry, who are interested in using combined methods in solving complex problems in the above areas.

  2. Artificial intelligence methods applied for quantitative analysis of natural radioactive sources

    International Nuclear Information System (INIS)

    Medhat, M.E.

    2012-01-01

    Highlights: ► Basic description of artificial neural networks. ► Natural gamma ray sources and problem of detections. ► Application of neural network for peak detection and activity determination. - Abstract: Artificial neural network (ANN) represents one of artificial intelligence methods in the field of modeling and uncertainty in different applications. The objective of the proposed work was focused to apply ANN to identify isotopes and to predict uncertainties of their activities of some natural radioactive sources. The method was tested for analyzing gamma-ray spectra emitted from natural radionuclides in soil samples detected by a high-resolution gamma-ray spectrometry based on HPGe (high purity germanium). The principle of the suggested method is described, including, relevant input parameters definition, input data scaling and networks training. It is clear that there is satisfactory agreement between obtained and predicted results using neural network.

  3. Risk assessment for pipelines with active defects based on artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Anghel, Calin I. [Department of Chemical Engineering, Faculty of Chemistry and Chemical Engineering, University ' Babes-Bolyai' , Cluj-Napoca (Romania)], E-mail: canghel@chem.ubbcluj.ro

    2009-07-15

    The paper provides another insight into the pipeline risk assessment for in-service pressure piping containing defects. Beside of the traditional analytical approximation methods or sampling-based methods safety index and failure probability of pressure piping containing defects will be obtained based on a novel type of support vector machine developed in a minimax manner. The safety index or failure probability is carried out based on a binary classification approach. The procedure named classification reliability procedure, involving a link between artificial intelligence and reliability methods was developed as a user-friendly computer program in MATLAB language. To reveal the capacity of the proposed procedure two comparative numerical examples replicating a previous related work and predicting the failure probabilities of pressured pipeline with defects were presented.

  4. Risk assessment for pipelines with active defects based on artificial intelligence methods

    International Nuclear Information System (INIS)

    Anghel, Calin I.

    2009-01-01

    The paper provides another insight into the pipeline risk assessment for in-service pressure piping containing defects. Beside of the traditional analytical approximation methods or sampling-based methods safety index and failure probability of pressure piping containing defects will be obtained based on a novel type of support vector machine developed in a minimax manner. The safety index or failure probability is carried out based on a binary classification approach. The procedure named classification reliability procedure, involving a link between artificial intelligence and reliability methods was developed as a user-friendly computer program in MATLAB language. To reveal the capacity of the proposed procedure two comparative numerical examples replicating a previous related work and predicting the failure probabilities of pressured pipeline with defects were presented.

  5. 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.

  6. Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

    Science.gov (United States)

    Kong, Changduk; Lim, Semyeong

    2011-12-01

    Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

  7. Artificial intelligence based models for stream-flow forecasting: 2000-2015

    Science.gov (United States)

    Yaseen, Zaher Mundher; El-shafie, Ahmed; Jaafar, Othman; Afan, Haitham Abdulmohsin; Sayl, Khamis Naba

    2015-11-01

    The use of Artificial Intelligence (AI) has increased since the middle of the 20th century as seen in its application in a wide range of engineering and science problems. The last two decades, for example, has seen a dramatic increase in the development and application of various types of AI approaches for stream-flow forecasting. Generally speaking, AI has exhibited significant progress in forecasting and modeling non-linear hydrological applications and in capturing the noise complexity in the dataset. This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream-flow. The review also identifies the major challenges and opportunities for prospective research, including, a new scheme for modeling the inflow, a novel method for preprocessing time series frequency based on Fast Orthogonal Search (FOS) techniques, and Swarm Intelligence (SI) as an optimization approach.

  8. Towards Brain-inspired Web Intelligence

    Science.gov (United States)

    Zhong, Ning

    Artificial Intelligence (AI) has been mainly studied within the realm of computer based technologies. Various computational models and knowledge based systems have been developed for automated reasoning, learning, and problem-solving. However, there still exist several grand challenges. The AI research has not produced major breakthrough recently due to a lack of understanding of human brains and natural intelligence. In addition, most of the AI models and systems will not work well when dealing with large-scale, dynamically changing, open and distributed information sources at a Web scale.

  9. 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.

  10. 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.)

  11. 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...

  12. A comprehensive review of the use of computational intelligence methods in mineral exploration

    Directory of Open Access Journals (Sweden)

    Habibollah Bazdar

    2017-11-01

    Full Text Available Introduction Mineral exploration is a process by which it is decided whether or not continuing explorations at the end of each stage t will be cost-effective or not. This decision is dependent upon many factors including technical factors, economic, social and other related factors. All new methods used in mineral exploration are meant to make this decision making more simplified. In recent years, advanced computational intelligence methods for modeling along with many other disciplines of science, including the science of mineral exploration have been used. Although the results of the application of these methods show a good performance, it is essential to determine the mineral potential in terms of geology, mineralogy, petrology and other factors for a final decision. The purpose of this paper is to provide a comprehensive set of mineral exploration research and different applications of computational intelligence techniques in this respect during the last decades. Materials and methods Artificial neural network and its application in mineral exploration Artificial neural network (ANN is a series of communications between the units or nodes that try to function like neurons of the human brain (Jorjani et al., 2008. The network processing capability of communication between the units and the weights connection originates or comes from learning or are predetermined (Monjezi and Dehghani, 2008. The ANN method has been applied in different branches of mining exploration in the last decades (Brown et al., 2000; Leite and de Souza Filho, 2009; Porwal et al., 2003. Support vector machines (SVM and its application in mineral exploration SVM uses a set of examples with known class of information to build a linear hyperplane separating samples of different classes. This initial dataset is known as a training set and every sample within it is characterized by features upon which the classification is based (Smirnoff et al., 2008. The SVM classifier is a

  13. Quality control of intelligence research

    International Nuclear Information System (INIS)

    Lu Yan; Xin Pingping; Wu Jian

    2014-01-01

    Quality control of intelligence research is the core issue of intelligence management, is a problem in study of information science This paper focuses on the performance of intelligence to explain the significance of intelligence research quality control. In summing up the results of the study on the basis of the analysis, discusses quality control methods in intelligence research, introduces the experience of foreign intelligence research quality control, proposes some recommendations to improve quality control in intelligence research. (authors)

  14. Intelligence diagnosis method for roller bearings using features of AE signal

    International Nuclear Information System (INIS)

    Pan, J; Wang, H Q; Wang, F; Yang, J F; Liu, W B

    2012-01-01

    Rolling bearings are important components in rotating machines, which are wildly used in industrial production. The fault diagnosis technology plays a very important role for quality and life of machines. Based on symptom parameters of acoustic emission (AE) signals, this paper presents an intelligent diagnosis method for roller bearings using the principal component analysis, rough sets, and BP neural network to detect faults and distinguish fault types. The principal component analysis and the rough sets algorithm are used to reduce details of time-domain symptom parameters for training the BP neural network. The BP neural network, which is used for condition diagnosis of roller bearings, can obtain good convergence using the symptom parameters acquired by the principal component analysis and the rough sets during learning, and automatically distinguish fault types during diagnosing. Practical examples are provided to verify the efficiency of the proposed method.

  15. Methods and Technologies of XML Data Modeling for IP Mode Intelligent Measuring and Controlling System

    International Nuclear Information System (INIS)

    Liu, G X; Hong, X B; Liu, J G

    2006-01-01

    This paper presents the IP mode intelligent measuring and controlling system (IMIMCS). Based on object-oriented modeling technology of UML and XML Schema, the innovative methods and technologies of some key problems for XML data modeling in the IMIMCS were especially discussed, including refinement for systemic business by means of use-case diagram of UML, the confirmation of the content of XML data model and logic relationship of the objects of XML Schema with the aid of class diagram of UML, the mapping rules from the UML object model to XML Schema. Finally, the application of the IMIMCS based on XML for a modern greenhouse was presented. The results show that the modeling methods of the measuring and controlling data in the IMIMCS involving the multi-layer structure and many operating systems process strong reliability and flexibility, guarantee uniformity of complex XML documents and meet the requirement of data communication across platform

  16. Nuclear power plant monitoring and fault diagnosis methods based on the artificial intelligence technique

    International Nuclear Information System (INIS)

    Yoshikawa, S.; Saiki, A.; Ugolini, D.; Ozawa, K.

    1996-01-01

    The main objective of this paper is to develop an advanced diagnosis system based on the artificial intelligence technique to monitor the operation and to improve the operational safety of nuclear power plants. Three different methods have been elaborated in this study: an artificial neural network local diagnosis (NN ds ) scheme that acting at the component level discriminates between normal and abnormal transients, a model-based diagnostic reasoning mechanism that combines a physical causal network model-based knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge. Although the three methods have been developed and verified independently, they are highly correlated and, when connected together, form a effective and robust diagnosis and monitoring tool. (authors)

  17. 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.

  18. A quick overview of artificial intelligence and expert systems

    International Nuclear Information System (INIS)

    Engelmore, R.S.

    1989-01-01

    Artificial intelligence (AI) is almost a household word these days. There have been several conferences held in this country over the last two years on artificial intelligence and its applications. The international AI conference at Snowbird, Utah, in 1987 centered on AI applications in the nuclear industry. This paper serves as an introductory overview of the subject of AI for this state-of-the-art review of AI applications in the nuclear industry. We introduce the subject in a way that will be relevant to many people in the nuclear industry who have heard of AI but are not familiar with it and are looking for answers to several simple questions. We attempt to answer those simple questions here and prepare the reader so that he or she can appreciate the following sections on AI applications in the nuclear field. (orig./GL)

  19. Artificial intelligence methods applied in the controlled synthesis of polydimethilsiloxane - poly (methacrylic acid) copolymer networks with imposed properties

    Science.gov (United States)

    Rusu, Teodora; Gogan, Oana Marilena

    2016-05-01

    This paper describes the use of artificial intelligence method in copolymer networks design. In the present study, we pursue a hybrid algorithm composed from two research themes in the genetic design framework: a Kohonen neural network (KNN), path (forward problem) combined with a genetic algorithm path (backward problem). The Tabu Search Method is used to improve the performance of the genetic algorithm path.

  20. Artificial-intelligence-based optimization of the management of snow removal assets and resources.

    Science.gov (United States)

    2002-10-01

    Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent : snow removal asset management system (SRAMS). The system has been evaluated through a case study examining : snow removal from the ...

  1. Expanding the Possibilities of AIS Data with Heuristics

    Directory of Open Access Journals (Sweden)

    Bjørnar Brende Smestad

    2017-06-01

    Full Text Available Automatic Identification System (AIS is primarily used as a tracking system for ships, but with the launch of satellites to collect these data, new and previously untested possibilities are emerging. This paper presents the development of heuristics for establishing the specific ship type using information retrieved from AIS data alone. These heuristics expand the possibilities of AIS data, as the specific ship type is vital for several transportation research cases, such as emission analyses of ship traffic and studies on slow steaming. The presented method for developing heuristics can be used for a wider range of vessels. These heuristics may form the basis of large-scale studies on ship traffic using AIS data when it is not feasible or desirable to use commercial ship data registers.

  2. Des résumés en français

    Directory of Open Access Journals (Sweden)

    Bogdan Patrut

    2010-09-01

    Full Text Available Des résumés en français
    BRAIN. Broad Research in Artificial Intelligence and Neuroscience
    CERVEAU. Recherche large en intelligence artificielle et neurosciences
    Volume 1, Numéro 4
    Juillet 2010: « Automne 2010»
    www.brain.edusoft.ro
    Sous la direction de: Bogdan Pătruţ

  3. AI mass spectrometers for space shuttle health monitoring

    Science.gov (United States)

    Adams, F. W.

    1991-01-01

    The facility Hazardous Gas Detection System (HGDS) at Kennedy Space Center (KSC) is a mass spectrometer based gas analyzer. Two instruments make up the HGDS, which is installed in a prime/backup arrangement, with the option of using both analyzers on the same sample line, or on two different lines simultaneously. It is used for monitoring the Shuttle during fuel loading, countdown, and drainback, if necessary. The use of complex instruments, operated over many shifts, has caused problems in tracking the status of the ground support equipment (GSE) and the vehicle. A requirement for overall system reliability has been a major force in the development of Shuttle GSE, and is the ultimate driver in the choice to pursue artificial intelligence (AI) techniques for Shuttle and Advanced Launch System (ALS) mass spectrometer systems. Shuttle applications of AI are detailed.

  4. Artificial intelligence in astronomy - a forecast.

    Science.gov (United States)

    Adorf, H. M.

    Since several years artificial intelligence techniques are being actively used in astronomy, particularly within the Hubble Space Telescope project. This contribution reviews achievements, analyses some problems of using artificial intelligence in an astronomical environment, and projects current AI programming trends into the future.

  5. 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…

  6. Calibrating AIS images using the surface as a reference

    Science.gov (United States)

    Smith, M. O.; Roberts, D. A.; Shipman, H. M.; Adams, J. B.; Willis, S. C.; Gillespie, A. R.

    1987-01-01

    A method of evaluating the initial assumptions and uncertainties of the physical connection between Airborne Imaging Spectrometer (AIS) image data and laboratory/field spectrometer data was tested. The Tuscon AIS-2 image connects to lab reference spectra by an alignment to the image spectral endmembers through a system gain and offset for each band. Images were calibrated to reflectance so as to transform the image into a measure that is independent of the solar radiant flux. This transformation also makes the image spectra directly comparable to data from lab and field spectrometers. A method was tested for calibrating AIS images using the surface as a reference. The surface heterogeneity is defined by lab/field spectral measurements. It was found that the Tuscon AIS-2 image is consistent with each of the initial hypotheses: (1) that the AIS-2 instrument calibration is nearly linear; (2) the spectral variance is caused by sub-pixel mixtures of spectrally distinct materials and shade, and (3) that sub-pixel mixtures can be treated as linear mixtures of pure endmembers. It was also found that the image can be characterized by relatively few endmembers using the AIS-2 spectra.

  7. Does Wittgenstein Actually Undermine the Foundation of Artificial Intelligence?

    Institute of Scientific and Technical Information of China (English)

    XU Yingjin

    2016-01-01

    Wittgenstein is widely viewed as a potential critic of a key philosophical assumption of the Strong Artificial Intelligence (AI) thesis,namely,that it is in principle possible to build a programmed machine which can achieve real intelligence.Stuart Shanker has provided the most systematic reconstruction of the Wittgensteinian argument against AI,building on Wittgenstein's own statements,the "rule-following" feature of language-games,and the putative alliance between AI and psychologism.This article will attempt to refute this reconstruction and its constituent arguments,thereby paving the way for a new and amicable rather than agonistic conception of the Wittgensteinian position on AI.

  8. On Intelligent Design and Planning Method of Process Route Based on Gun Breech Machining Process

    Science.gov (United States)

    Hongzhi, Zhao; Jian, Zhang

    2018-03-01

    The paper states an approach of intelligent design and planning of process route based on gun breech machining process, against several problems, such as complex machining process of gun breech, tedious route design and long period of its traditional unmanageable process route. Based on gun breech machining process, intelligent design and planning system of process route are developed by virtue of DEST and VC++. The system includes two functional modules--process route intelligent design and its planning. The process route intelligent design module, through the analysis of gun breech machining process, summarizes breech process knowledge so as to complete the design of knowledge base and inference engine. And then gun breech process route intelligently output. On the basis of intelligent route design module, the final process route is made, edited and managed in the process route planning module.

  9. AI Tools Bridge Technology Gap.

    Science.gov (United States)

    Rauch-Hindin, Wendy

    1985-01-01

    This second part of a report on artificial intelligence focuses on the development of expert systems in a variety of applications, from engineering to science, and details expectations for implementation of these systems. (JN)

  10. DESIGNING AI TEACHER ASSISTANT ON ONLINE-COURSE BASED ON WORD2VEC TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    Pavel Aleksandrovich Rozhkin

    2018-05-01

    Full Text Available The purpose of this work is to develop an AI teacher assistant, who can find answers to online course participants questions among answers previously published at the training forum. Currently, there are already successful experiments on the use of artificial intelligence systems (IBM WATSON in online training. In this paper, we investigate the possibility of constructing such a system using word2vec technology. A two-stage method for finding an answer to a question is constructed. Method use word2vec technology for vector representation of questions and answers. At the first stage, the subject matter of the issue is determined and, if it corresponds to the theme of the forum, then the articles most relevant to the question are searched. A real situation was simulated with 16 themes and 80 answers to possible questions within the section of the online course “Linear Algebra and Geometry”. The question-answer system was designed and its performance was evaluated. The parameters have been chosen to achieve the best result. In 83% of the cases, the relevant answer to the formulated question was contained among the top 3 responses that the system offered. The issues of further development of applied approaches and increasing utility of the constructed question-answer system are considered. Purpose: developing an AI teacher assistant, who can find answers to online course participants questions among answers previously published at the training forum. Methodology: vectorization of questions and answers, neural network classification of the subject matter, construction of the answers rating. Results: acceptable accuracy in finding a relevant answer to a question are received. Practical implications: The results of the research can be used as a basis for designing an AI teacher assistant in online courses.

  11. 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

  12. Managing Sustainability with the Support of Business Intelligence Methods and Tools

    Science.gov (United States)

    Petrini, Maira; Pozzebon, Marlei

    In this paper we explore the role of business intelligence (BI) in helping to support the management of sustainability in contemporary firms. The concepts of sustainability and corporate social responsibility (CSR) are among the most important themes to have emerged in the last decade at the global level. We suggest that BI methods and tools have an important but not yet well studied role to play in helping organizations implement and monitor sustainable and socially responsible business practices. Using grounded theory, the main contribution of our study is to propose a conceptual model that seeks to support the process of definition and monitoring of socio-environmental indicators and the relationship between their management and business strategy.

  13. An intelligent despeckling method for swept source optical coherence tomography images of skin

    Science.gov (United States)

    Adabi, Saba; Mohebbikarkhoran, Hamed; Mehregan, Darius; Conforto, Silvia; Nasiriavanaki, Mohammadreza

    2017-03-01

    Optical Coherence Optical coherence tomography is a powerful high-resolution imaging method with a broad biomedical application. Nonetheless, OCT images suffer from a multiplicative artefacts so-called speckle, a result of coherent imaging of system. Digital filters become ubiquitous means for speckle reduction. Addressing the fact that there still a room for despeckling in OCT, we proposed an intelligent speckle reduction framework based on OCT tissue morphological, textural and optical features that through a trained network selects the winner filter in which adaptively suppress the speckle noise while preserve structural information of OCT signal. These parameters are calculated for different steps of the procedure to be used in designed Artificial Neural Network decider that select the best denoising technique for each segment of the image. Results of training shows the dominant filter is BM3D from the last category.

  14. The use of foresight methods in strategic raw materials intelligence - an international review

    Science.gov (United States)

    Konrat Martins, Marco Antonio; Bodo, Balazs; Falck, Eberhard

    2017-04-01

    Foresight methods are systematic attempts to look into the longer term future of science, society, economy and technology. There is a range of tools and techniques that can be used individually or combined, most commonly classified into qualitative, quantitative or semi-quantitative methods, that follow an exploratory or normative approach. These tools can help to identify the longer term visions, orienting policy formulation and decisions, triggering actions, among other objectives. There is an identified lack of European strategic foresight knowledge in the raw materials domain. Since the European Raw Materials Initiative was launched in 2008, the EU has been attempting to overcome challenges related to the future access of non-energy and non-agricultural raw materials. In this context, the ongoing H2020 project, MICA (Mineral Intelligence Capacity Analysis, Grant Agreement No. 689648), has been launched to answer to stakeholders needs by consolidating relevant data, determining relevant methods and tools, and investigating Raw Materials Intelligence options for European mineral policy development, all tailored to fit under the umbrella of a European Raw Materials Intelligence Capacity Platform (EU-RMICP). As part of the MICA activities, an assessment of best practices and benchmarks of international raw materials foresight case studies has been carried out in order to review how EU and non-EU countries have employed foresight. A pool of 30 case studies has been collected and reviewed internationally, one third of which were selected for detailed assessment. These were classified according to their background and goals, in function of methods employed, and to the purpose of each method in the study: a total of 12 different methods were identified in these studies. For longer time frames, qualitative predictive methods such as Scenario Development have been repeatedly observed for mineral raw materials foresight studies. Substantial variations were observed in

  15. 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.

  16. Optimizing Limousine Service with AI

    OpenAIRE

    Chun, Andy Hon Wai

    2011-01-01

    A common problem for companies with strong business growth is that it is hard to find enough experienced staff to support expansion needs. This problem is particular pronounced for operations planners and controllers who must be very highly knowledgeable and experienced with the business domain. This article is a case study of how one of the largest travel agencies in Hong Kong alleviated this problem by using AI to support decision-making and problem-solving so that their planners and contro...

  17. Intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization.

    Science.gov (United States)

    Li, Ke; Chen, Peng

    2011-01-01

    Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called "relative ratio symptom parameters" are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks.

  18. Development of advanced methods for signal processing in the monitoring of sodium-cooled reactors

    International Nuclear Information System (INIS)

    Schleisiek, K.; Aberle, J.; Massier, H.; Scherer, K.P.; Vaeth, W.; Leder, H.J.; Schade, H.J.

    1987-01-01

    Selected examples (acoustic boiling detection, pattern recognition method, identification of fuel element vibrations, diagnosis system for KNK II) are used to demonstrate the benefits of up-to-date information technology in the monitoring of nuclear facilities. The methods used range from intelligent frequency analysis to AI methods like pattern recognition and expert systems. (DG) [de

  19. An Intelligent Method for Structural Reliability Analysis Based on Response Surface

    Institute of Scientific and Technical Information of China (English)

    桂劲松; 刘红; 康海贵

    2004-01-01

    As water depth increases, the structural safety and reliability of a system become more and more important and challenging. Therefore, the structural reliability method must be applied in ocean engineering design such as offshore platform design. If the performance function is known in structural reliability analysis, the first-order second-moment method is often used. If the performance function could not be definitely expressed, the response surface method is always used because it has a very clear train of thought and simple programming. However, the traditional response surface method fits the response surface of quadratic polynomials where the problem of accuracy could not be solved, because the true limit state surface can be fitted well only in the area near the checking point. In this paper, an intelligent computing method based on the whole response surface is proposed, which can be used for the situation where the performance function could not be definitely expressed in structural reliability analysis. In this method, a response surface of the fuzzy neural network for the whole area should be constructed first, and then the structural reliability can be calculated by the genetic algorithm. In the proposed method, all the sample points for the training network come from the whole area, so the true limit state surface in the whole area can be fitted. Through calculational examples and comparative analysis, it can be known that the proposed method is much better than the traditional response surface method of quadratic polynomials, because, the amount of calculation of finite element analysis is largely reduced, the accuracy of calculation is improved,and the true limit state surface can be fitted very well in the whole area. So, the method proposed in this paper is suitable for engineering application.

  20. Little AI: Playing a constructivist robot

    Directory of Open Access Journals (Sweden)

    Olivier L. Georgeon

    2017-01-01

    Full Text Available Little AI is a pedagogical game aimed at presenting the founding concepts of constructivist learning and developmental Artificial Intelligence. It primarily targets students in computer science and cognitive science but it can also interest the general public curious about these topics. It requires no particular scientific background; even children can find it entertaining. Professors can use it as a pedagogical resource in class or in online courses. The player presses buttons to control a simulated “baby robot”. The player cannot see the robot and its environment, and initially ignores the effects of the commands. The only information received by the player is feedback from the player’s commands. The player must learn, at the same time, the functioning of the robot’s body and the structure of the environment from patterns in the stream of commands and feedback. We argue that this situation is analogous to how infants engage in early-stage developmental learning (e.g., Piaget (1937, [1].

  1. STAR - A computer language for hybrid AI applications

    Science.gov (United States)

    Borchardt, G. C.

    1986-01-01

    Constructing Artificial Intelligence application systems which rely on both symbolic and non-symbolic processing places heavy demands on the communication of data between dissimilar languages. This paper describes STAR (Simple Tool for Automated Reasoning), a computer language for the development of AI application systems which supports the transfer of data structures between a symbolic level and a non-symbolic level defined in languages such as FORTRAN, C and PASCAL. The organization of STAR is presented, followed by the description of an application involving STAR in the interpretation of airborne imaging spectrometer data.

  2. Alarm processing system using AI techniques for nuclear power plant

    International Nuclear Information System (INIS)

    Yang, Joon On; Chang, Soon Heung

    1990-01-01

    An alarm processing system (APS) has been developed using artificial intelligence (AI) techniques. The alarms of nuclear power plants (NPP's) are classified into the generalized and special alarms. The generalized alarms are also classified into the global and local alarms. For each type of alarms, the specific processing rules are applied to filter and suppress unnecessary and potentially misleading alarms. The local processing are based on 'model-based reasoning.' The global and special alarms are processed by using the general cause-consequence check rules. The priorities of alarms are determined according to the plant state and the consistencies between them

  3. ReACT!: An Interactive Educational Tool for AI Planning for Robotics

    Science.gov (United States)

    Dogmus, Zeynep; Erdem, Esra; Patogulu, Volkan

    2015-01-01

    This paper presents ReAct!, an interactive educational tool for artificial intelligence (AI) planning for robotics. ReAct! enables students to describe robots' actions and change in dynamic domains without first having to know about the syntactic and semantic details of the underlying formalism, and to solve planning problems using…

  4. Cognitive Maps, AI Agents and Personalized Virtual Environments in Internet Learning Experiences.

    Science.gov (United States)

    Maule, R. William

    1998-01-01

    Develops frameworks to help Internet media designers address end-user information presentation preferences by advancing structures for assessing metadata design variables which are then linked to user cognitive styles. An underlying theme is that artificial intelligence (AI) methodologies may be used to help automate the Internet media design…

  5. Autonomously generating operations sequences for a Mars Rover using AI-based planning

    Science.gov (United States)

    Sherwood, Rob; Mishkin, Andrew; Estlin, Tara; Chien, Steve; Backes, Paul; Cooper, Brian; Maxwell, Scott; Rabideau, Gregg

    2001-01-01

    This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from highlevel science and engineering activities. This prototype is based on ASPEN, the Automated Scheduling and Planning Environment. This Artificial Intelligence (AI) based planning and scheduling system will automatically generate a command sequence that will execute within resource constraints and satisfy flight rules.

  6. NASA space station automation: AI-based technology review. Executive summary

    Science.gov (United States)

    Firschein, O.; Georgeff, M. P.; Park, W.; Cheeseman, P. C.; Goldberg, J.; Neumann, P.; Kautz, W. H.; Levitt, K. N.; Rom, R. J.; Poggio, A. A.

    1985-01-01

    Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics.

  7. The use of artificial intelligence methods for visual analysis of properties of surface layers

    Directory of Open Access Journals (Sweden)

    Tomasz Wójcicki

    2014-12-01

    Full Text Available [b]Abstract[/b]. The article presents a selected area of research on the possibility of automatic prediction of material properties based on the analysis of digital images. Original, holistic model of forecasting properties of surface layers based on a multi-step process that includes the selected methods of processing and analysis of images, inference with the use of a priori knowledge bases and multi-valued fuzzy logic, and simulation with the use of finite element methods is presented. Surface layers characteristics and core technologies of their production processes such as mechanical, thermal, thermo-mechanical, thermo-chemical, electrochemical, physical are discussed. Developed methods used in the model for the classification of images of the surface layers are shown. The objectives of the use of selected methods of processing and analysis of digital images, including techniques for improving the quality of images, segmentation, morphological transformation, pattern recognition and simulation of physical phenomena in the structures of materials are described.[b]Keywords[/b]: image analysis, surface layer, artificial intelligence, fuzzy logic

  8. Study (Prediction of Main Pipes Break Rates in Water Distribution Systems Using Intelligent and Regression Methods

    Directory of Open Access Journals (Sweden)

    Massoud Tabesh

    2011-07-01

    Full Text Available Optimum operation of water distribution networks is one of the priorities of sustainable development of water resources, considering the issues of increasing efficiency and decreasing the water losses. One of the key subjects in optimum operational management of water distribution systems is preparing rehabilitation and replacement schemes, prediction of pipes break rate and evaluation of their reliability. Several approaches have been presented in recent years regarding prediction of pipe failure rates which each one requires especial data sets. Deterministic models based on age and deterministic multi variables and stochastic group modeling are examples of the solutions which relate pipe break rates to parameters like age, material and diameters. In this paper besides the mentioned parameters, more factors such as pipe depth and hydraulic pressures are considered as well. Then using multi variable regression method, intelligent approaches (Artificial neural network and neuro fuzzy models and Evolutionary polynomial Regression method (EPR pipe burst rate are predicted. To evaluate the results of different approaches, a case study is carried out in a part ofMashhadwater distribution network. The results show the capability and advantages of ANN and EPR methods to predict pipe break rates, in comparison with neuro fuzzy and multi-variable regression methods.

  9. Improved Ordinary Measure and Image Entropy Theory based intelligent Copy Detection Method

    Directory of Open Access Journals (Sweden)

    Dengpan Ye

    2011-10-01

    Full Text Available Nowadays, more and more multimedia websites appear in social network. It brings some security problems, such as privacy, piracy, disclosure of sensitive contents and so on. Aiming at copyright protection, the copy detection technology of multimedia contents becomes a hot topic. In our previous work, a new computer-based copyright control system used to detect the media has been proposed. Based on this system, this paper proposes an improved media feature matching measure and an entropy based copy detection method. The Levenshtein Distance was used to enhance the matching degree when using for feature matching measure in copy detection. For entropy based copy detection, we make a fusion of the two features of entropy matrix of the entropy feature we extracted. Firstly,we extract the entropy matrix of the image and normalize it. Then, we make a fusion of the eigenvalue feature and the transfer matrix feature of the entropy matrix. The fused features will be used for image copy detection. The experiments show that compared to use these two kinds of features for image detection singly, using feature fusion matching method is apparent robustness and effectiveness. The fused feature has a high detection for copy images which have been received some attacks such as noise, compression, zoom, rotation and so on. Comparing with referred methods, the method proposed is more intelligent and can be achieved good performance.

  10. 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 ...

  11. Algorithms in ambient intelligence

    NARCIS (Netherlands)

    Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Verhaegh, W.F.J.; Aarts, E.H.L.; Korst, J.H.M.

    2004-01-01

    In this chapter, we discuss the new paradigm for user-centered computing known as ambient intelligence and its relation with methods and techniques from the field of computational intelligence, including problem solving, machine learning, and expert systems.

  12. Design of Intelligent Hydraulic Excavator Control System Based on PID Method

    Science.gov (United States)

    Zhang, Jun; Jiao, Shengjie; Liao, Xiaoming; Yin, Penglong; Wang, Yulin; Si, Kuimao; Zhang, Yi; Gu, Hairong

    Most of the domestic designed hydraulic excavators adopt the constant power design method and set 85%~90% of engine power as the hydraulic system adoption power, it causes high energy loss due to mismatching of power between the engine and the pump. While the variation of the rotational speed of engine could sense the power shift of the load, it provides a new method to adjust the power matching between engine and pump through engine speed. Based on negative flux hydraulic system, an intelligent hydraulic excavator control system was designed based on rotational speed sensing method to improve energy efficiency. The control system was consisted of engine control module, pump power adjusted module, engine idle module and system fault diagnosis module. Special PLC with CAN bus was used to acquired the sensors and adjusts the pump absorption power according to load variation. Four energy saving control strategies with constant power method were employed to improve the fuel utilization. Three power modes (H, S and L mode) were designed to meet different working status; Auto idle function was employed to save energy through two work status detected pressure switches, 1300rpm was setting as the idle speed according to the engine consumption fuel curve. Transient overload function was designed for deep digging within short time without spending extra fuel. An increasing PID method was employed to realize power matching between engine and pump, the rotational speed's variation was taken as the PID algorithm's input; the current of proportional valve of variable displacement pump was the PID's output. The result indicated that the auto idle could decrease fuel consumption by 33.33% compared to work in maximum speed of H mode, the PID control method could take full use of maximum engine power at each power mode and keep the engine speed at stable range. Application of rotational speed sensing method provides a reliable method to improve the excavator's energy efficiency and

  13. Synthesis and Analysis in Artificial Intelligence: The Role of Theory in Agent Implementation

    NARCIS (Netherlands)

    Raine, Roxanne B.; op den Akker, Hendrikus J.A.; Cai, Zhiqiang; Graesser, Arthur C.; McNamara, Danielle S.

    2009-01-01

    The domain of artificial intelligence (AI) progresses with extraordinary vicissitude. Whereas prior authors have divided AI into the two categories of analysis and synthesis, Raine and op den Akker distinguish between four types of AI: that of appearance, function, simulation and interpretation.

  14. Comparison of AI techniques for prediction of liver fibrosis in hepatitis patients.

    Science.gov (United States)

    Keltch, Brian; Lin, Yuan; Bayrak, Coskun

    2014-08-01

    Globally one in twelve people have the Hepatitis B or Hepatitis C virus. Diagnosis and treatment of this disease is guided by liver biopsies where a small amount of tissue is removed by a surgeon and examined by a pathologist to determine the fibrosis stage from F(0) (no damage) to F(4) (cirrhosis). Biopsies are costly and carry some risk for the patient. Non-invasive techniques for determining fibrosis stage have been developed and evaluated since 2003. Non-invasive methods have utilized serum markers, imaging test, and genetic studies. The accuracy of these non-invasive techniques has not achieved sufficient acceptance and so the invasive biopsy is still considered the gold standard.Clinical decision support systems (CDSS) use decision support system theory and technology to assist clinicians in the evaluation and treatment process. Using historical clinical data and the relationship processed by Artificial Intelligence (AI) techniques to aid physicians in their decision making process is the goal of CDSS. The CDSS provides a large number of medical support functions to help clinicians make the most reasonable diagnosis and choose the best treatment measures.This paper applies four artificial intelligence predictive techniques to publicly available data on 424 Hepatitis B and Hepatitis C patients. Demographic and standard serum markers are utilized to predict fibrosis stage and compare these predictions to known biopsy results. A final decision tree evaluation is applied to make a final prediction. We have also developed a publically available web application that can be used as a prototype for presenting AI predictive results in a CDSS environment based on these models. This technique along with others could mitigate the need for some liver biopsies in the more than 500 million Hepatitis B and C patients worldwide with additional validation and verification.

  15. Effectiveness of Agile Implementation Methods in Business Intelligence Projects from an End-user Perspective

    Directory of Open Access Journals (Sweden)

    Anna Maria Misiak

    2016-06-01

    Full Text Available The global Business Intelligence (BI market grew by 10% in 2013 according to the Gartner Report. Today organizations require better use of data and analytics to support their business decisions. Internet power and business trend changes have provided a broad term for data analytics – Big Data. To be able to handle it and leverage a value of having access to Big Data, organizations have no other choice than to get proper systems implemented and working. However traditional methods are not efficient for changing business needs. The long time between project start and go-live causes a gap between initial solution blueprint and actual user requirements in the end of the project. This article presents the latest market trends in BI systems implementation by comparing Agile with traditional methods. It presents a case study provided in a large telecommunications company (20K employees and the results of a pilot research provided in the three large companies: telecommunications, digital, and insurance. Both studies prove that Agile methods might be more effective in BI projects from an end-user perspective and give first results and added value in a much shorter time compared to a traditional approach.

  16. Intelligent Photovoltaic Systems by Combining the Improved Perturbation Method of Observation and Sun Location Tracking

    Science.gov (United States)

    Wang, Yajie; Shi, Yunbo; Yu, Xiaoyu; Liu, Yongjie

    2016-01-01

    Currently, tracking in photovoltaic (PV) systems suffers from some problems such as high energy consumption, poor anti-interference performance, and large tracking errors. This paper presents a solar PV tracking system on the basis of an improved perturbation and observation method, which maximizes photoelectric conversion efficiency. According to the projection principle, we design a sensor module with a light-intensity-detection module for environmental light-intensity measurement. The effect of environmental factors on the system operation is reduced, and intelligent identification of the weather is realized. This system adopts the discrete-type tracking method to reduce power consumption. A mechanical structure with a level-pitch double-degree-of-freedom is designed, and attitude correction is performed by closed-loop control. A worm-and-gear mechanism is added, and the reliability, stability, and precision of the system are improved. Finally, the perturbation and observation method designed and improved by this study was tested by simulated experiments. The experiments verified that the photoelectric sensor resolution can reach 0.344°, the tracking error is less than 2.5°, the largest improvement in the charge efficiency can reach 44.5%, and the system steadily and reliably works. PMID:27327657

  17. An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

    Directory of Open Access Journals (Sweden)

    Bo Sun

    2012-01-01

    Full Text Available According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negotiation and independent negotiation is established, and the heuristic rules applied to global and local maintenance decision making is proposed. Based on Contract Net Protocol and the heuristic rules, the maintenance decision making algorithm is put forward. Finally, a fleet consisting of 10 aircrafts on a 3-wave continuous mission is illustrated to verify this method. Simulation results indicate that this method can improve the availability of the fleet, meet mission demands, rationalize the utilization of support resources and provide support for online maintenance decision making among a mission oriented fleet.

  18. New evaluation methods for conceptual design selection using computational intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai [University of Electronic Science and Technology of China, Chengdu (China); Xue, Lihua [Higher Education Press, Beijing (China)

    2013-03-15

    The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

  19. New evaluation methods for conceptual design selection using computational intelligence techniques

    International Nuclear Information System (INIS)

    Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai; Xue, Lihua

    2013-01-01

    The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

  20. Intelligent Photovoltaic Systems by Combining the Improved Perturbation Method of Observation and Sun Location Tracking.

    Directory of Open Access Journals (Sweden)

    Yajie Wang

    Full Text Available Currently, tracking in photovoltaic (PV systems suffers from some problems such as high energy consumption, poor anti-interference performance, and large tracking errors. This paper presents a solar PV tracking system on the basis of an improved perturbation and observation method, which maximizes photoelectric conversion efficiency. According to the projection principle, we design a sensor module with a light-intensity-detection module for environmental light-intensity measurement. The effect of environmental factors on the system operation is reduced, and intelligent identification of the weather is realized. This system adopts the discrete-type tracking method to reduce power consumption. A mechanical structure with a level-pitch double-degree-of-freedom is designed, and attitude correction is performed by closed-loop control. A worm-and-gear mechanism is added, and the reliability, stability, and precision of the system are improved. Finally, the perturbation and observation method designed and improved by this study was tested by simulated experiments. The experiments verified that the photoelectric sensor resolution can reach 0.344°, the tracking error is less than 2.5°, the largest improvement in the charge efficiency can reach 44.5%, and the system steadily and reliably works.

  1. Intelligent Photovoltaic Systems by Combining the Improved Perturbation Method of Observation and Sun Location Tracking.

    Science.gov (United States)

    Wang, Yajie; Shi, Yunbo; Yu, Xiaoyu; Liu, Yongjie

    2016-01-01

    Currently, tracking in photovoltaic (PV) systems suffers from some problems such as high energy consumption, poor anti-interference performance, and large tracking errors. This paper presents a solar PV tracking system on the basis of an improved perturbation and observation method, which maximizes photoelectric conversion efficiency. According to the projection principle, we design a sensor module with a light-intensity-detection module for environmental light-intensity measurement. The effect of environmental factors on the system operation is reduced, and intelligent identification of the weather is realized. This system adopts the discrete-type tracking method to reduce power consumption. A mechanical structure with a level-pitch double-degree-of-freedom is designed, and attitude correction is performed by closed-loop control. A worm-and-gear mechanism is added, and the reliability, stability, and precision of the system are improved. Finally, the perturbation and observation method designed and improved by this study was tested by simulated experiments. The experiments verified that the photoelectric sensor resolution can reach 0.344°, the tracking error is less than 2.5°, the largest improvement in the charge efficiency can reach 44.5%, and the system steadily and reliably works.

  2. 26th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE)

    CERN Document Server

    Bosse, Tibor; Hindriks, Koen; Hoogendoorn, Mark; Jonker, Catholijn; Treur, Jan; Contemporary Challenges and Solutions in Applied Artificial Intelligence

    2013-01-01

      Since its origination in the mid-twentieth century, the area of Artificial Intelligence (AI) has undergone a number of developments. While the early interest in AI was mainly triggered by the desire to develop artifacts that show the same intelligent behavior as humans, nowadays scientists have realized that research in AI involves a multitude of separate challenges, besides the traditional goal to replicate human intelligence. In particular, recent history has pointed out that a variety of ‘intelligent’ computational techniques, part of which are inspired by human intelligence, may be successfully applied to solve all kinds of practical problems. This sub-area of AI, which has its main emphasis on applications of intelligent systems to solve real-life problems, is currently known under the term Applied Intelligence.   The objective of the International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE) is to promote and disseminate recent research ...

  3. Prediction of 5-year overall survival in cervical cancer patients treated with radical hysterectomy using computational intelligence methods.

    Science.gov (United States)

    Obrzut, Bogdan; Kusy, Maciej; Semczuk, Andrzej; Obrzut, Marzanna; Kluska, Jacek

    2017-12-12

    Computational intelligence methods, including non-linear classification algorithms, can be used in medical research and practice as a decision making tool. This study aimed to evaluate the usefulness of artificial intelligence models for 5-year overall survival prediction in patients with cervical cancer treated by radical hysterectomy. The data set was collected from 102 patients with cervical cancer FIGO stage IA2-IIB, that underwent primary surgical treatment. Twenty-three demographic, tumor-related parameters and selected perioperative data of each patient were collected. The simulations involved six computational intelligence methods: the probabilistic neural network (PNN), multilayer perceptron network, gene expression programming classifier, support vector machines algorithm, radial basis function neural network and k-Means algorithm. The prediction ability of the models was determined based on the accuracy, sensitivity, specificity, as well as the area under the receiver operating characteristic curve. The results of the computational intelligence methods were compared with the results of linear regression analysis as a reference model. The best results were obtained by the PNN model. This neural network provided very high prediction ability with an accuracy of 0.892 and sensitivity of 0.975. The area under the receiver operating characteristics curve of PNN was also high, 0.818. The outcomes obtained by other classifiers were markedly worse. The PNN model is an effective tool for predicting 5-year overall survival in cervical cancer patients treated with radical hysterectomy.

  4. 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.

  5. Challenges in introduction of artificial intelligence in medical practice – a review of clinical trials concerning adaptation of artificial intelligence in medicine

    OpenAIRE

    Mielnik, Pawel Franciszek; Fojcik, Marcin; Kulbacki, Marek; Segen, Jakub

    2016-01-01

    An interest in Artificial Intelligence [AI] as science is growing in the last years. It has become gradually more used in the medicine. Methodology of development and testing of AI algorithms is generally well established. Use of AI in medicine requires elaboration of standards of its validation in clinical settings. This paper is a review of literature concerning clinical trials on AI adaptation in medicine

  6. "It's Going to Kill Us!" and Other Myths about the Future of Artificial Intelligence

    Science.gov (United States)

    Atkinson, Robert D.

    2016-01-01

    Given the promise that artificial intelligence (AI) holds for economic growth and societal advancement, it is critical that policymakers not only avoid retarding the progress of AI innovation, but also actively support its further development and use. This report provides a primer on artificial intelligence and debunks five prevailing myths that,…

  7. Residential building energy estimation method based on the application of artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Marshall, S.; Kajl, S.

    1999-07-01

    The energy requirements of a residential building five to twenty-five stories high can be measured using a newly proposed analytical method based on artificial intelligence. The method is fast and provides a wide range of results such as total energy consumption values, power surges, and heating or cooling consumption values. A series of database were created to take into account the particularities which influence the energy consumption of a building. In this study, DOE-2 software was created for use in 8 apartment models. A total of 27 neural networks were used, 3 for the estimation of energy consumption in the corridor, and 24 for inside the apartments. Three user interfaces were created to facilitate the estimation of energy consumption. These were named the Energy Estimation Assistance System (EEAS) interfaces and are only accessible using MATLAB software. The input parameters for EEAS are: climatic region, exterior wall resistance, roofing resistance, type of windows, infiltration, number of storeys, and corridor ventilation system operating schedule. By changing the parameters, the EEAS can determine annual heating, cooling and basic energy consumption levels for apartments and corridors. 2 tabs., 2 figs.

  8. Computational Intelligence Method for Early Diagnosis Dengue Haemorrhagic Fever Using Fuzzy on Mobile Device

    Directory of Open Access Journals (Sweden)

    Salman Afan

    2014-03-01

    Full Text Available Mortality from Dengue Haemorrhagic Fever (DHF is still increasing in Indonesia particularly in Jakarta. Diagnosis of the dengue shall be made as early as possible so that first aid can be given in expectation of decreasing death risk. The Study will be conducted by developing expert system based on Computational Intelligence Method. On the first year, study will use the Fuzzy Inference System (FIS Method to diagnose Dengue Haemorrhagic Fever particularly in Mobile Device consist of smart phone. Expert system application which particularly using fuzzy system can be applied in mobile device and it is useful to make early diagnosis of Dengue Haemorrhagic Fever that produce outcome faster than laboratory test. The evaluation of this application is conducted by performing accuracy test before and after validation using data of patient who has the Dengue Haemorrhagic Fever. This expert system application is easy, convenient, and practical to use, also capable of making the early diagnosis of Dengue Haemorraghic to avoid mortality in the first stage.

  9. 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.

  10. 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

  11. 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.

  12. Advances in intelligent process-aware information systems concepts, methods, and technologies

    CERN Document Server

    Oberhauser, Roy; Reichert, Manfred

    2017-01-01

    This book provides a state-of-the-art perspective on intelligent process-aware information systems and presents chapters on specific facets and approaches applicable to such systems. Further, it highlights novel advances and developments in various aspects of intelligent process-aware information systems and business process management systems. Intelligence capabilities are increasingly being integrated into or created in many of today’s software products and services. Process-aware information systems provide critical computing infrastructure to support the various processes involved in the creation and delivery of business products and services. Yet the integration of intelligence capabilities into process-aware information systems is a non-trivial yet necessary evolution of these complex systems. The book’s individual chapters address adaptive process management, case management processes, autonomically-capable processes, process-oriented information logistics, process recommendations, reasoning over ...

  13. On the Need for Artificial Intelligence and Advanced Test and Evaluation Methods for Space Exploration

    Science.gov (United States)

    Scheidt, D. H.; Hibbitts, C. A.; Chen, M. H.; Paxton, L. J.; Bekker, D. L.

    2017-02-01

    Implementing mature artificial intelligence would create the ability to significantly increase the science return from a mission, while potentially saving costs in mission and instrument operations, and solving currently intractable problems.

  14. Operation Iraqi Freedom 04 - 06: Opportunities to Apply Quantitative Methods to Intelligence Analysis

    National Research Council Canada - National Science Library

    Hansen, Eric C

    2005-01-01

    The purpose of this presentation is to illustrate the need for a quantitative analytical capability within organizations and staffs that provide intelligence analysis to Army, Joint, and Coalition Force headquarters...

  15. 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 ...

  16. 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...

  17. Emotional intelligence among medical students: a mixed methods study from Chennai, India.

    Science.gov (United States)

    Sundararajan, Subashini; Gopichandran, Vijayaprasad

    2018-05-04

    Emotional Intelligence is the ability of a person to understand and respond to one's own and others' emotions and use this understanding to guide one's thoughts and actions. To assess the level of emotional intelligence of medical students in a medical college in Chennai and to explore their understanding of the role of emotions in medical practice. A quantitative, cross sectional, questionnaire based, survey was conducted among 207 medical students in a college in Chennai, India using the Quick Emotional Intelligence Self Assessment Test and some hypothetical emotional clinical vignettes. This was followed by a qualitative moderated fish-bowl discussion to elicit the opinion of medical students on role of emotions in the practice of medicine. The mean score of Emotional Intelligence was 107.58 (SD 16.44) out of a maximum possible score of 160. Students who went to government schools for high school education had greater emotional intelligence than students from private schools (p = 0.044) and women were more emotionally intelligent in their response to emotional vignettes than men (p = 0.056). The fish bowl discussion highlighted several positive and negative impacts of emotions in clinical care. The students concluded at the end of the discussion that emotions are inevitable in the practice of medicine and a good physician should know how to handle them. Medical students, both men and women, had good level of emotional intelligence in the college that was studied. Students from collectivist social settings like government high schools have better emotional intelligence, which may indicate that a collectivist, community oriented medical education can serve the same purpose. Though students have diverse opinions on the role of emotions in clinical care, cognitive reflection exercises can help them understand its importance.

  18. Algorithms in ambient intelligence

    NARCIS (Netherlands)

    Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Weber, W.; Rabaey, J.M.; Aarts, E.

    2005-01-01

    We briefly review the concept of ambient intelligence and discuss its relation with the domain of intelligent algorithms. By means of four examples of ambient intelligent systems, we argue that new computing methods and quantification measures are needed to bridge the gap between the class of

  19. Advance in study of intelligent diagnostic method for nuclear power plant

    International Nuclear Information System (INIS)

    Zhou Gang; Yang Li

    2008-01-01

    The advance of research on the application of three types of intelligent diagnostic approach based on neural network (ANN), fuzzy logic and expert system to the operation status monitoring and fault diagnosis of nuclear power plant (NPP) was reviewed. The research status and characters on status monitoring and fault diagnosis approaches based on neural network, fuzzy logic and expert system for nuclear power plant were analyzed. The development trend of applied research on intelligent diagnostic approaches for nuclear power plant was explored. The analysis results show that the research achievements on intelligent diagnostic approaches based on fuzzy logic and expert system for nuclear power plant are not much relatively. The research of intelligent diagnostic approaches for nuclear power plant concentrate on the aspect of operation status monitoring and fault diagnosis based on neural networks for nuclear power plant. The advancing tendency of intelligent diagnostic approaches for nuclear power plant is the combination of various intelligent diagnostic approaches, the combination of neural network diagnostic approaches and other diagnostic approaches as well as multiple neural network diagnostic approaches. (authors)

  20. The use of artificial intelligence for safeguarding fuel reprocessing plants

    International Nuclear Information System (INIS)

    Wachter, J.W.; Forgy, C.L.

    1987-01-01

    Recorded process data from the ''Minirun'' campaigns conducted at the Barnwell Nuclear Fuel Plant (BNFP) in Barnwell, South Carolina during 1980 to 1981 have been utilized to study the suitability of computer-based Artificial Intelligence (AI) methods for process monitoring for safeguards purposes. The techniques of knowledge engineering were used to formulate the decision-making software which operates on the process data customarily used for process operations. The OPS5 AI language was used to construct an Expert System for this purpose. Such systems are able to form reasoned conclusions from incomplete, inaccurate or otherwise ''fuzzy'' data, and to explain the reasoning that led to them. The programs were tested using minirun data taken during simulated diversions ranging in size from 1 to 20 L of solution that had been monitored previously using conventional procedural techniques. 13 refs., 3 figs

  1. The use of artificial intelligence for safeguard fuel reprocessing plants

    International Nuclear Information System (INIS)

    Wachter, J.W.; Forgy, C.L.

    1987-01-01

    Recorded process data from minirun campaigns conducted at the Barnwell Nuclear Fuels Plant have been utilized to study the suitability of computer-based artificial intelligence (AI) methods for process monitoring for safeguards purposes. The techniques of knowledge engineering were used to formulate the decision-making software. The computer software accepted as input process data customarily used for process operations that had previously been recorded on magnetic tape during the 1980 miniruns. The OPS5 AI language was used to construct an expert system for simulated monitoring of the process. Such expert systems facilitate the employment of the heuristic reasoning used by human observers to form reasoned conclusions from incomplete, inaccurate, or otherwise fuzzy data

  2. Application of artificial intelligence to radiation control, (1)

    International Nuclear Information System (INIS)

    Kimura, Yoshitaka; Hasegawa, Keisuke; Ikezawa, Yoshio

    1990-01-01

    Recently artificial intelligence (AI) which has functions of our interpretations and judgments has been applied to various fields of science. In the first application of AI to the transport procedure of the radioactive material, a prototype of expert system was developed with UTI-LISP programming language to appropriately classify mainly the packages and packagings according to regulations for the safe transport of radioactive material. Classification of the packages and packagings for the consignment is mainly determined from input informations such as radionuclides, its activities, states and conveyances through a forward reasoning method of the expert system. The rationalization of practice on our interpretations and judgments for transport of radioactive material including uniformity and reliability of our decision were confirmed as the result of an application to radiation control. (author)

  3. Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources

    Science.gov (United States)

    Hortos, William S.

    2006-05-01

    A wireless ad hoc sensor network (WSN) is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. To a greater degree than the terminals found in mobile ad hoc networks (MANETs) for communications, sensor nodes are resource-constrained, with limited computational processing, bandwidth, memory, and power, and are typically unattended once in operation. Consequently, the level of information exchange among nodes, to support any complex adaptive algorithms to establish network connectivity and optimize throughput, not only deplete those limited resources and creates high overhead in narrowband communications, but also increase network vulnerability to eavesdropping by malicious nodes. Cooperation among nodes, critical to the mission of sensor networks, can thus be disrupted by the inappropriate choice of the method for self-organization. Recent published contributions to the self-configuration of ad hoc sensor networks, e.g., self-organizing mapping and swarm intelligence techniques, have been based on the adaptive control of the cross-layer interactions found in MANET protocols to achieve one or more performance objectives: connectivity, intrusion resistance, power control, throughput, and delay. However, few studies have examined the performance of these algorithms when implemented with the limited resources of WSNs. In this paper, self-organization algorithms for the initiation, operation and maintenance of a network topology from a collection of wireless sensor nodes are proposed that improve the performance metrics significant to WSNs. The intelligent algorithm approach emphasizes low computational complexity, energy efficiency and robust adaptation to change, allowing distributed implementation with the actual limited resources of the cooperative nodes of the network. Extensions of the

  4. Learning modalities in artificial intelligence systems: a framework and review

    Energy Technology Data Exchange (ETDEWEB)

    Araya, A A

    1982-01-01

    Intelligent systems should possess two fundamental capabilities: problem solving and learning. Problem solving capabilities allow an intelligent system to cope with problems in a given domain. Learning capabilities make possible for an intelligent system to improve the solution to the problems within its current reach or to cope with new problems. This paper examines research in artificial intelligence from the perspective of learning with the purpose of: 1) developing and understanding of the problem of learning from the AI point of view, and II) characterizing the current state of the art on learning in AI. 35 references.

  5. An intelligent fault diagnosis method of rolling bearings based on regularized kernel Marginal Fisher analysis

    International Nuclear Information System (INIS)

    Jiang Li; Shi Tielin; Xuan Jianping

    2012-01-01

    Generally, the vibration signals of fault bearings are non-stationary and highly nonlinear under complicated operating conditions. Thus, it's a big challenge to extract optimal features for improving classification and simultaneously decreasing feature dimension. Kernel Marginal Fisher analysis (KMFA) is a novel supervised manifold learning algorithm for feature extraction and dimensionality reduction. In order to avoid the small sample size problem in KMFA, we propose regularized KMFA (RKMFA). A simple and efficient intelligent fault diagnosis method based on RKMFA is put forward and applied to fault recognition of rolling bearings. So as to directly excavate nonlinear features from the original high-dimensional vibration signals, RKMFA constructs two graphs describing the intra-class compactness and the inter-class separability, by combining traditional manifold learning algorithm with fisher criteria. Therefore, the optimal low-dimensional features are obtained for better classification and finally fed into the simplest K-nearest neighbor (KNN) classifier to recognize different fault categories of bearings. The experimental results demonstrate that the proposed approach improves the fault classification performance and outperforms the other conventional approaches.

  6. Artificial Intelligence Mechanisms on Interactive Modified Simplex Method with Desirability Function for Optimising Surface Lapping Process

    Directory of Open Access Journals (Sweden)

    Pongchanun Luangpaiboon

    2014-01-01

    Full Text Available A study has been made to optimise the influential parameters of surface lapping process. Lapping time, lapping speed, downward pressure, and charging pressure were chosen from the preliminary studies as parameters to determine process performances in terms of material removal, lap width, and clamp force. The desirability functions of the-nominal-the-best were used to compromise multiple responses into the overall desirability function level or D response. The conventional modified simplex or Nelder-Mead simplex method and the interactive desirability function are performed to optimise online the parameter levels in order to maximise the D response. In order to determine the lapping process parameters effectively, this research then applies two powerful artificial intelligence optimisation mechanisms from harmony search and firefly algorithms. The recommended condition of (lapping time, lapping speed, downward pressure, and charging pressure at (33, 35, 6.0, and 5.0 has been verified by performing confirmation experiments. It showed that the D response level increased to 0.96. When compared with the current operating condition, there is a decrease of the material removal and lap width with the improved process performance indices of 2.01 and 1.14, respectively. Similarly, there is an increase of the clamp force with the improved process performance index of 1.58.

  7. Hybrid-augmented intelligence:collaboration and cognition

    Institute of Scientific and Technical Information of China (English)

    Nan-ning ZHENG; Zi-yi LIU; Peng-ju REN; Yong-qiang MA; Shi-tao CHEN; Si-yu YU; Jian-ru XUE

    2017-01-01

    The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models:one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.

  8. On the Edge: Intelligent CALL in the 1990s.

    Science.gov (United States)

    Underwood, John

    1989-01-01

    Examines the possibilities of developing computer-assisted language learning (CALL) based on the best of modern technology, arguing that artificial intelligence (AI) strategies will radically improve the kinds of exercises that can be performed. Recommends combining AI technology with other tools for delivering instruction, such as simulation and…

  9. 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…

  10. Introduction to the Articles on Innovative Applications of Artificial Intelligence

    OpenAIRE

    Rychtyckyj, Nestor; Shapiro, Daniel

    2011-01-01

    This issue of AI Magazine provides extended versions of several papers that were recently presented at the Innovative Applications of Artificial Intelligence Conference (IAAI-2010). We present three articles reflecting deployed applications of AI, one describing a unique, emerging application, plus an article based on the invited talk by Jay M. Tenenbaum, who was the 2010 Engelmore Award recipient.

  11. 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…

  12. 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.

  13. A brief overview of artificial intelligence in South Africa

    CSIR Research Space (South Africa)

    Ferrein, A

    2013-10-01

    Full Text Available One of the consequences of the growth in AI research in South Africa in recent years is the establishment of a number of research hubs involved in AI activities ranging from mobile robotics and computational intelligence to knowledge representation...

  14. 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.

  15. An SDR based AIS receiver for satellites

    DEFF Research Database (Denmark)

    Larsen, Jesper Abildgaard; Mortensen, Hans Peter; Nielsen, Jens Frederik Dalsgaard

    2011-01-01

    For a few years now, there has been a high interest in monitoring the global ship traffic from space. A few satellite, capable of listening for ship borne AIS transponders have already been launched, and soon the AAUSAT3, carrying two different types of AIS receivers will also be launched. One...... of the AIS receivers onboard AAUSAT3 is an SDR based AIS receiver. This paper serves to describe the background of the AIS system, and how the SDR based receiver has been integrated into the AAUSAT3 satellite. Amongst some of the benefits of using an SDR based receiver is, that due to its versatility, new...... detection algorithms are easily deployed, and it is easily adapted the new proposed AIS transmission channels....

  16. True Visions The Emergence of Ambient Intelligence

    CERN Document Server

    Aarts, Emile

    2006-01-01

    Ambient intelligence (AI) refers to a developing technology that will increasingly make our everyday environment sensitive and responsive to our presence. The AI vision requires technology invisibly embedded in our everyday surroundings, present whenever we need it that will lead to the seamless integration of lighting, sounds, vision, domestic appliances, and personal healthcare products to enhance our living experience. Written for the non-specialist seeking an authoritative but accessible overview of this interdisciplinary field, True Visions explains how the devices making up the AI world will operate collectively using information and intelligence hidden in the wireless network connecting them. Expert contributions address key AI components such as smart materials and textiles, system architecture, mobile computing, broadband communication, and underlying issues of human-environment interactions. It seeks to unify the perspectives of scientists from diverse backgrounds ranging from the physics of materia...

  17. Artificial Intelligence as Structural Estimation: Economic Interpretations of Deep Blue, Bonanza, and AlphaGo

    OpenAIRE

    Igami, Mitsuru

    2017-01-01

    Artificial intelligence (AI) has achieved superhuman performance in a growing number of tasks, but understanding and explaining AI remain challenging. This paper clarifies the connections between machine-learning algorithms to develop AIs and the econometrics of dynamic structural models through the case studies of three famous game AIs. Chess-playing Deep Blue is a calibrated value function, whereas shogi-playing Bonanza is an estimated value function via Rust's (1987) nested fixed-point met...

  18. IJCAI-91 Workshop on Objects and Artificial Intelligence

    OpenAIRE

    Hatzilygeroudis, Ioannis

    1994-01-01

    The Objects and Artificial Intelligence Workshop was held on 25 August 1991 in conjunction with the 1991 International Joint Conference on Artificial Intelligence. The workshop brought together researchers in AI and object-oriented programming to exchange ideas and investigate possible avenues of cooperation between AI and object-oriented programming. The workshop dealt with both the theoretical and the practical aspects of this cooperation.

  19. 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.

  20. 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,...

  1. A study on the applications of AI in finishing of additive manufacturing parts

    Science.gov (United States)

    Fathima Patham, K.

    2017-06-01

    Artificial intelligent and computer simulation are the technological powerful tools for solving complex problems in the manufacturing industries. Additive Manufacturing is one of the powerful manufacturing techniques that provide design flexibilities to the products. The products with complex shapes are directly manufactured without the need of any machining and tooling using Additive Manufacturing. However, the main drawback of the components produced using the Additive Manufacturing processes is the quality of the surfaces. This study aims to minimize the defects caused during Additive Manufacturing with the aid of Artificial Intelligence. The developed AI system has three layers, each layer is trying to eliminate or minimize the production errors. The first layer of the AI system optimizes the digitization of the 3D CAD model of the product and hence reduces the stair case errors. The second layer of the AI system optimizes the 3D printing machine parameters in order to eliminate the warping effect. The third layer of AI system helps to choose the surface finishing technique suitable for the printed component based on the Degree of Complexity of the product and the material. The efficiency of the developed AI system was examined on the functional parts such as gears.

  2. Cargo flows distribution over the loading sites of enterprises by using methods of artificial intelligence

    Directory of Open Access Journals (Sweden)

    Олександр Павлович Кіркін

    2017-06-01

    Full Text Available Development of information technologies and market requirements in effective control over cargo flows, forces enterprises to look for new ways and methods of automated control over the technological operations. For rail transportation one of the most complicated tasks of automation is the cargo flows distribution over the sites of loading and unloading. In this article the solution with the use of one of the methods of artificial intelligence – a fuzzy inference has been proposed. The analysis of the last publications showed that the fuzzy inference method is effective for the solution of similar tasks, it makes it possible to accumulate experience, it is stable to temporary impacts of the environmental conditions. The existing methods of the cargo flows distribution over the sites of loading and unloading are too simplified and can lead to incorrect decisions. The purpose of the article is to create a distribution model of cargo flows of the enterprises over the sites of loading and unloading, basing on the fuzzy inference method and to automate the control. To achieve the objective a mathematical model of the cargo flows distribution over the sites of loading and unloading has been made using fuzzy logic. The key input parameters of the model are: «number of loading sites», «arrival of the next set of cars», «availability of additional operations». The output parameter is «a variety of set of cars». Application of the fuzzy inference method made it possible to reduce loading time by 15% and to reduce costs for preparatory operations before loading by 20%. Thus this method is an effective means and holds the greatest promise for railway competitiveness increase. Interaction between different types of transportation and their influence on the cargo flows distribution over the sites of loading and unloading hasn’t been considered. These sites may be busy transshipping at that very time which is characteristic of large enterprises

  3. USACE AIS Transmit Technical Support Summary Report

    Science.gov (United States)

    2014-09-01

    the TAG block for the correct transmitters, and then send to the USACE AIS network. B. Outbound openings in the USCG firewall for the USCG Message...USACE AIS Transmit Technical Support Summary Report Distribution Statement A: Approved for public release; distribution is unlimited...September 2014 Report No. CD-D-09-15 USACE AIS Transmit Technical Support Summary Report ii UNCLAS//Public | CG-926 RDC | I. Gonin et al. Public

  4. 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…

  5. Shimadzu AI-PACS 'SAIPACS'

    International Nuclear Information System (INIS)

    Andoh, Minoru; Asai, Shigeya; Matsui, Norihisa; Nishida, Shinichiro; Horino, Masato

    1990-01-01

    The PACS-WS named SAIPACS-WS(workstation) has been developed as the first step of complete PACS. This SAIPACS-WS is different from other PACS-WS's, because this is including computer aided diagnostic reporting and computer aided diagnosis by using artificial intelligence technique. In this paper we will report detail of the SAIPACS-WS and discuss the future development of the total PACS setting the SAIPACS-WS in its center. (author)

  6. Adaptive Motion Gaming AI for Health Promotion

    OpenAIRE

    Paliyawan, Pujana; Kusano, Takahiro; Nakagawa, Yuto; Harada, Tomohiro; Thawonmas, Ruck

    2017-01-01

    This paper presents a design of a non-player character (AI) for promoting balancedness in use of body segments when engaging in full-body motion gaming. In our experiment, we settle a battle between the proposed AI and a player by using FightingICE, a fighting game platform for AI development. A middleware called UKI is used to allow the player to control the game by using body motion instead of the keyboard and mouse. During gameplay, the proposed AI analyze health states of the player; it d...

  7. Advanced intelligent systems

    CERN Document Server

    Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul

    2014-01-01

    Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...

  8. Intelligent inversion method for pre-stack seismic big data based on MapReduce

    Science.gov (United States)

    Yan, Xuesong; Zhu, Zhixin; Wu, Qinghua

    2018-01-01

    Seismic exploration is a method of oil exploration that uses seismic information; that is, according to the inversion of seismic information, the useful information of the reservoir parameters can be obtained to carry out exploration effectively. Pre-stack data are characterised by a large amount of data, abundant information, and so on, and according to its inversion, the abundant information of the reservoir parameters can be obtained. Owing to the large amount of pre-stack seismic data, existing single-machine environments have not been able to meet the computational needs of the huge amount of data; thus, the development of a method with a high efficiency and the speed to solve the inversion problem of pre-stack seismic data is urgently needed. The optimisation of the elastic parameters by using a genetic algorithm easily falls into a local optimum, which results in a non-obvious inversion effect, especially for the optimisation effect of the density. Therefore, an intelligent optimisation algorithm is proposed in this paper and used for the elastic parameter inversion of pre-stack seismic data. This algorithm improves the population initialisation strategy by using the Gardner formula and the genetic operation of the algorithm, and the improved algorithm obtains better inversion results when carrying out a model test with logging data. All of the elastic parameters obtained by inversion and the logging curve of theoretical model are fitted well, which effectively improves the inversion precision of the density. This algorithm was implemented with a MapReduce model to solve the seismic big data inversion problem. The experimental results show that the parallel model can effectively reduce the running time of the algorithm.

  9. 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...

  10. 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

  11. 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.

  12. Artificial Intelligence and the Future of Defense

    DEFF Research Database (Denmark)

    De Spiegeleire, Stephan; Maas, Matthijs Michiel; Sweijs, Tim

    Artificial intelligence (AI) is on everybody’s minds these days. Most of the world’s leading companies are making massive investments in it. Governments are scrambling to catch up. Every single one of us who uses Google Search or any of the new digital assistants on our smartphones has witnessed...... suggests that the advent of artificial super-intelligence (i.e. AI that is superior across the board to human intelligence), which many experts now put firmly within the longer-term planning horizons of our DSOs, presents us with unprecedented risks but also opportunities that we have to start to explore....... The report contains an overview of the role that ‘intelligence’ - the computational part of the ability to achieve goals in the world - has played in defense and security throughout human history; a primer on AI (what it is, where it comes from and where it stands today - in both civilian and military...

  13. Artificial intelligence applications in space and SDI: A survey

    Science.gov (United States)

    Fiala, Harvey E.

    1988-01-01

    The purpose of this paper is to survey existing and planned Artificial Intelligence (AI) applications to show that they are sufficiently advanced for 32 percent of all space applications and SDI (Space Defense Initiative) software to be AI-based software. To best define the needs that AI can fill in space and SDI programs, this paper enumerates primary areas of research and lists generic application areas. Current and planned NASA and military space projects in AI will be reviewed. This review will be largely in the selected area of expert systems. Finally, direct applications of AI to SDI will be treated. The conclusion covers the importance of AI to space and SDI applications, and conversely, their importance to AI.

  14. Artificial intelligence and knowledge management

    OpenAIRE

    Hoesch, Hugo Cesar; Barcellos, Vânia

    2006-01-01

    This article intends to make an analysis about the Artificial Intelligence (AI) and the Knowledge Management (KM). Faced with the dualism mind and body how we be able to see it AI? It doesn’t intent to create identical copy of human being, but try to find the better form to represent all the knowledge contained in our minds. The society of the information lives a great paradox, at the same time that we have access to an innumerable amount of information, the capacity and the forms of its proc...

  15. Epistasis analysis using artificial intelligence.

    Science.gov (United States)

    Moore, Jason H; Hill, Doug P

    2015-01-01

    Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of expert knowledge as a guide. The methodology presented here is based on computational evolution, which is a type of genetic programming. The ability to generate interesting solutions while at the same time learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data.

  16. Groundhog Day for Medical Artificial Intelligence.

    Science.gov (United States)

    London, Alex John

    2018-05-01

    Following a boom in investment and overinflated expectations in the 1980s, artificial intelligence entered a period of retrenchment known as the "AI winter." With advances in the field of machine learning and the availability of large datasets for training various types of artificial neural networks, AI is in another cycle of halcyon days. Although medicine is particularly recalcitrant to change, applications of AI in health care have professionals in fields like radiology worried about the future of their careers and have the public tittering about the prospect of soulless machines making life-and-death decisions. Medicine thus appears to be at an inflection point-a kind of Groundhog Day on which either AI will bring a springtime of improved diagnostic and predictive practices or the shadow of public and professional fear will lead to six more metaphorical weeks of winter in medical AI. © 2018 The Hastings Center.

  17. 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

  18. Computer aided diagnosis based on medical image processing and artificial intelligence methods

    Science.gov (United States)

    Stoitsis, John; Valavanis, Ioannis; Mougiakakou, Stavroula G.; Golemati, Spyretta; Nikita, Alexandra; Nikita, Konstantina S.

    2006-12-01

    Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

  19. Computer aided diagnosis based on medical image processing and artificial intelligence methods

    International Nuclear Information System (INIS)

    Stoitsis, John; Valavanis, Ioannis; Mougiakakou, Stavroula G.; Golemati, Spyretta; Nikita, Alexandra; Nikita, Konstantina S.

    2006-01-01

    Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis

  20. Computer aided diagnosis based on medical image processing and artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Stoitsis, John [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece)]. E-mail: stoitsis@biosim.ntua.gr; Valavanis, Ioannis [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece); Mougiakakou, Stavroula G. [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece); Golemati, Spyretta [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece); Nikita, Alexandra [University of Athens, Medical School 152 28 Athens (Greece); Nikita, Konstantina S. [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece)

    2006-12-20

    Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

  1. Artificial intelligence and design: Opportunities, research problems and directions

    Science.gov (United States)

    Amarel, Saul

    1990-01-01

    The issues of industrial productivity and economic competitiveness are of major significance in the U.S. at present. By advancing the science of design, and by creating a broad computer-based methodology for automating the design of artifacts and of industrial processes, we can attain dramatic improvements in productivity. It is our thesis that developments in computer science, especially in Artificial Intelligence (AI) and in related areas of advanced computing, provide us with a unique opportunity to push beyond the present level of computer aided automation technology and to attain substantial advances in the understanding and mechanization of design processes. To attain these goals, we need to build on top of the present state of AI, and to accelerate research and development in areas that are especially relevant to design problems of realistic complexity. We propose an approach to the special challenges in this area, which combines 'core work' in AI with the development of systems for handling significant design tasks. We discuss the general nature of design problems, the scientific issues involved in studying them with the help of AI approaches, and the methodological/technical issues that one must face in developing AI systems for handling advanced design tasks. Looking at basic work in AI from the perspective of design automation, we identify a number of research problems that need special attention. These include finding solution methods for handling multiple interacting goals, formation problems, problem decompositions, and redesign problems; choosing representations for design problems with emphasis on the concept of a design record; and developing approaches for the acquisition and structuring of domain knowledge with emphasis on finding useful approximations to domain theories. Progress in handling these research problems will have major impact both on our understanding of design processes and their automation, and also on several fundamental questions

  2. Global Research on Artificial Intelligence from 1990–2014: Spatially-Explicit Bibliometric Analysis

    Directory of Open Access Journals (Sweden)

    Jiqiang Niu

    2016-05-01

    Full Text Available In this article, we conducted the evaluation of artificial intelligence research from 1990–2014 by using bibliometric analysis. We introduced spatial analysis and social network analysis as geographic information retrieval methods for spatially-explicit bibliometric analysis. This study is based on the analysis of data obtained from database of the Science Citation Index Expanded (SCI-Expanded and Conference Proceedings Citation Index-Science (CPCI-S. Our results revealed scientific outputs, subject categories and main journals, author productivity and geographic distribution, international productivity and collaboration, and hot issues and research trends. The growth of article outputs in artificial intelligence research has exploded since the 1990s, along with increasing collaboration, reference, and citations. Computer science and engineering were the most frequently-used subject categories in artificial intelligence studies. The top twenty productive authors are distributed in countries with a high investment of research and development. The United States has the highest number of top research institutions in artificial intelligence, producing most single-country and collaborative articles. Although there is more and more collaboration among institutions, cooperation, especially international ones, are not highly prevalent in artificial intelligence research as expected. The keyword analysis revealed interesting research preferences, confirmed that methods, models, and application are in the central position of artificial intelligence. Further, we found interesting related keywords with high co-occurrence frequencies, which have helped identify new models and application areas in recent years. Bibliometric analysis results from our study will greatly facilitate the understanding of the progress and trends in artificial intelligence, in particular, for those researchers interested in domain-specific AI-driven problem-solving. This will be

  3. A study on the Web intelligence

    Institute of Scientific and Technical Information of China (English)

    Sang-Geun Kim

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI). 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, systens, and activities. As a direction for scientific research and devlopment, WI can be extremely beneficial for the field of Artificial Intelligence in Education (AIED). This paper covers these issues only very briefly. It focuses more on other issues in WI, such as intelligent Web services, and semantic web, and proposes how to use them as basis for tackling new and challenging research problems in AIED.

  4. 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...

  5. Application of Computational Intelligence Methods to In-Core Fuel Management

    International Nuclear Information System (INIS)

    Erdogan, A.

    2001-01-01

    k e ff higher than reference values were stored as candidate optimum patterns. At the last stage of the work, an alternative loading pattern generator based on genetic algorithm method was developed. In this method, an initial loading pattern is improved by applying the genetic operators to obtain the optimum. The loading patterns obtained from the rule-based and the genetic algorithm methods were compared, and the genetic algorithm was shown to be more successful than the former. It was seen that, it is possible to automate in-core fuel management activities by applying artificial intelligence techniques

  6. JGOMAS: New Approach to AI Teaching

    Science.gov (United States)

    Barella, A.; Valero, S.; Carrascosa, C.

    2009-01-01

    This paper presents a new environment for teaching practical work in AI subjects. The main purpose of this environment is to make AI techniques more appealing to students and to facilitate the use of the toolkits which are currently widely used in research and development. This new environment has a toolkit for developing and executing agents,…

  7. Adaptive game AI with dynamic scripting

    NARCIS (Netherlands)

    Spronck, P.; Ponsen, M.J.V.; Sprinkhuizen-Kuyper, I.G.; Postma, E.O.

    2006-01-01

    Online learning in commercial computer games allows computer-controlled opponents to adapt to the way the game is being played. As such it provides a mechanism to deal with weaknesses in the game AI, and to respond to changes in human player tactics.We argue that online learning of game AI should

  8. 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.

  9. 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.

  10. 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.

  11. Methods for Model-Based Reasoning within Agent-Based Ambient Intelligence Applications

    NARCIS (Netherlands)

    Bosse, T.; Both, F.; Gerritsen, C.; Hoogendoorn, M.; Treur, J.

    2012-01-01

    Within agent-based Ambient Intelligence applications agents react to humans based on information obtained by sensoring and their knowledge about human functioning. Appropriate types of reactions depend on the extent to which an agent understands the human and is able to interpret the available

  12. Fetal Intelligent Navigation Echocardiography (FINE): a novel method for rapid, simple, and automatic examination of the fetal heart.

    Science.gov (United States)

    Yeo, Lami; Romero, Roberto

    2013-09-01

    To describe a novel method (Fetal Intelligent Navigation Echocardiography (FINE)) for visualization of standard fetal echocardiography views from volume datasets obtained with spatiotemporal image correlation (STIC) and application of 'intelligent navigation' technology. We developed a method to: 1) demonstrate nine cardiac diagnostic planes; and 2) spontaneously navigate the anatomy surrounding each of the nine cardiac diagnostic planes (Virtual Intelligent Sonographer Assistance (VIS-Assistance®)). The method consists of marking seven anatomical structures of the fetal heart. The following echocardiography views are then automatically generated: 1) four chamber; 2) five chamber; 3) left ventricular outflow tract; 4) short-axis view of great vessels/right ventricular outflow tract; 5) three vessels and trachea; 6) abdomen/stomach; 7) ductal arch; 8) aortic arch; and 9) superior and inferior vena cava. The FINE method was tested in a separate set of 50 STIC volumes of normal hearts (18.6-37.2 weeks of gestation), and visualization rates for fetal echocardiography views using diagnostic planes and/or VIS-Assistance® were calculated. To examine the feasibility of identifying abnormal cardiac anatomy, we tested the method in four cases with proven congenital heart defects (coarctation of aorta, tetralogy of Fallot, transposition of great vessels and pulmonary atresia with intact ventricular septum). In normal cases, the FINE method was able to generate nine fetal echocardiography views using: 1) diagnostic planes in 78-100% of cases; 2) VIS-Assistance® in 98-100% of cases; and 3) a combination of diagnostic planes and/or VIS-Assistance® in 98-100% of cases. In all four abnormal cases, the FINE method demonstrated evidence of abnormal fetal cardiac anatomy. The FINE method can be used to visualize nine standard fetal echocardiography views in normal hearts by applying 'intelligent navigation' technology to STIC volume datasets. This method can simplify

  13. AN INTRODUCTION TO KNOWLEDGE-GROWING SYSTEM: A NOVEL FIELD IN ARTIFICIAL INTELLIGENCE

    Directory of Open Access Journals (Sweden)

    Arwin Datumaya Wahyudi Sumari

    2010-07-01

    Full Text Available The essential matter of Artificial Intelligence (AI is how to build an entity that mimics human intelligence in the way of learning of a phenomenon in a real life to gain knowledge of it and uses the knowledge to solve problems related to it. Based on the findings of intelligenct characteristic displayed by the human brain in growing and generating new knowledge by fusing information perceived by sensory organs, we develop brain-inspired Knowledge-Growing System (KGS that is, a system that is capable of growing its knowledge along with the accretion of information as the time passes. The essential matter of KGS is knowledge-growing method which is based on a new algorithm called Observation Multi-time A3S (OMA3S information-inferencing fusion method. In this paper we deliver the development of KGS along with some examples of KGS application to a real-life problem. Based on the state-of-the-art of AI and approaches to construct OMA3S method as KG method as well as validations to assess the system performance, we state that brain-inspired KGS is a novel field in AI.

  14. Realization of Personalized Services for Intelligent Residential Space based on User Identification Method using Sequential Walking Footprints

    Directory of Open Access Journals (Sweden)

    Jin-Woo Jung

    2005-04-01

    Full Text Available A new human-friendly assistive home environment, Intelligent Sweet Home (ISH, developed at KAIST, Korea for testing advanced concepts for independent living of the elderly/the physically handicapped. The concept of ISH is to consider the home itself as an intelligent robot. ISH always checks the intention or health status of the resident. Therefore, ISH can do actively the most proper services considering the resident's life-style by the detected intention or emergency information. But, when there are more than two residents, ISH cannot consider the residents' characteristics or tastes if ISH cannot identify who he/she is before. To realize a personalized service system in the intelligent residential space like ISH, we deal with a human-friendly user identification method for ubiquitous computing environment, specially focused on dynamic human footprint recognition. And then, we address some case studies of personalized services that have been experienced by Human-friendly Welfare Robot System research center, KAIST.

  15. Analysis of operator support method based on intelligent dynamic interlock in lead-cooled fast reactor simulator

    International Nuclear Information System (INIS)

    Xu, Peng; Wang, Jianye; Yang, Minghan; Wang, Weitian; Bai, Yunqing; Song, Yong

    2017-01-01

    Highlights: • We development an operator support method based on intelligent dynamic interlock. • We offer an integrated aid system to reduce the working strength of operators. • The method can help operators avoid dangerous, irreversible operation. • This method can be used in the fusion research reactor in the further. - Abstract: In nuclear systems, operators have to carry out corrective actions when abnormal situations occur. However, operators might make mistakes under pressure. In order to avoid serious consequences of the human errors, a new method for operators support based on intelligent dynamic interlock was proposed. The new method based on full digital instrumentation and control system, contains real-time alarm analysis process, decision support process and automatic safety interlock process. Once abnormal conditions occur, necessary safety interlock parameter based on analysis of real-time alarm and decision support process can be loaded into human-machine interfaces and controllers automatically, and avoid human errors effectively. Furthermore, the new method can make recommendations for further use and development of this technique in nuclear power plant or fusion research reactor.

  16. Toward New-Generation Intelligent Manufacturing

    Directory of Open Access Journals (Sweden)

    Ji Zhou

    2018-02-01

    Full Text Available Intelligent manufacturing is a general concept that is under continuous development. It can be categorized into three basic paradigms: digital manufacturing, digital-networked manufacturing, and new-generation intelligent manufacturing. New-generation intelligent manufacturing represents an in-depth integration of new-generation artificial intelligence (AI technology and advanced manufacturing technology. It runs through every link in the full life-cycle of design, production, product, and service. The concept also relates to the optimization and integration of corresponding systems; the continuous improvement of enterprises’ product quality, performance, and service levels; and reduction in resources consumption. New-generation intelligent manufacturing acts as the core driving force of the new industrial revolution and will continue to be the main pathway for the transformation and upgrading of the manufacturing industry in the decades to come. Human-cyber-physical systems (HCPSs reveal the technological mechanisms of new-generation intelligent manufacturing and can effectively guide related theoretical research and engineering practice. Given the sequential development, cross interaction, and iterative upgrading characteristics of the three basic paradigms of intelligent manufacturing, a technology roadmap for “parallel promotion and integrated development” should be developed in order to drive forward the intelligent transformation of the manufacturing industry in China. Keywords: Advanced manufacturing, New-generation intelligent manufacturing, Human-cyber-physical system, New-generation AI, Basic paradigms, Parallel promotion, Integrated development

  17. AI based HealthCare Platform for Real Time, Predictive and Prescriptive Analytics using Reactive Programming

    Science.gov (United States)

    Kaur, Jagreet; Singh Mann, Kulwinder, Dr.

    2018-01-01

    AI in Healthcare needed to bring real, actionable insights and Individualized insights in real time for patients and Doctors to support treatment decisions., We need a Patient Centred Platform for integrating EHR Data, Patient Data, Prescriptions, Monitoring, Clinical research and Data. This paper proposes a generic architecture for enabling AI based healthcare analytics Platform by using open sources Technologies Apache beam, Apache Flink Apache Spark, Apache NiFi, Kafka, Tachyon, Gluster FS, NoSQL- Elasticsearch, Cassandra. This paper will show the importance of applying AI based predictive and prescriptive analytics techniques in Health sector. The system will be able to extract useful knowledge that helps in decision making and medical monitoring in real-time through an intelligent process analysis and big data processing.

  18. 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.

  19. System for intelligent teleoperation research

    International Nuclear Information System (INIS)

    Orlando, N.E.

    1983-01-01

    The Automation Technology Branch of NASA Langley Research Center is developing a research capability in the field of artificial intelligence, particularly as applicable in teleoperator/robotics development for remote space operations. As a testbed for experimentation in these areas, a system concept has been developed and is being implemented. This system, termed DAISIE (Distributed Artificially Intelligent System for Interacting with the Environment), interfaces the key processes of perception, reasoning, and manipulation by linking hardware sensors and manipulators to a modular artificial intelligence (AI) software system in a hierarchical control structure. Verification experiments have been performed: one experiment used a blocksworld database and planner embedded in the DAISIE system to intelligently manipulate a simple physical environment; the other experiment implemented a joint-space collision avoidance algorithm. Continued system development is planned

  20. 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

  1. 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…

  2. Active and intelligent food packaging: legal aspects and safety concerns

    NARCIS (Netherlands)

    Dainelli, D.; Gontard, N.; Spyropoulos, D.; Zondervan-van den Beuken, E.; Tobback, P.

    2008-01-01

    'Active and intelligent' (A&I) food packaging is based on a deliberate interaction of the packaging with the food and/or its direct environment. This article presents: (i) the main types of materials developed for food contact; (ii) the global market and the future trends of active and intelligent

  3. "All-In-One Test" (AI1)

    DEFF Research Database (Denmark)

    Giacalone, Davide; Bredie, Wender Laurentius Petrus; Frøst, Michael Bom

    2013-01-01

    by the Check-All-That-Apply (CATA) technique is reported. In this exploratory "All-In-One Test"(AI1), subjects (N = 160) filled out a questionnaire with demographic and psychographic variables, and appropriateness ratings for specific sensory descriptors of beer. Subsequently, subjects gave hedonic ratings...... between appropriateness and actual hedonic response. Overall, the AI1 test provided interpretable results concerning consumer perception (sensory/hedonic) of the beers, and revealed relations with consumers' background information. Initial results with AI1 test show that it is an efficient and versatile...

  4. A Novel Strain-Based Method to Estimate Tire Conditions Using Fuzzy Logic for Intelligent Tires

    Directory of Open Access Journals (Sweden)

    Daniel Garcia-Pozuelo

    2017-02-01

    Full Text Available The so-called intelligent tires are one of the most promising research fields for automotive engineers. These tires are equipped with sensors which provide information about vehicle dynamics. Up to now, the commercial intelligent tires only provide information about inflation pressure and their contribution to stability control systems is currently very limited. Nowadays one of the major problems for intelligent tire development is how to embed feasible and low cost sensors to obtain reliable information such as inflation pressure, vertical load or rolling speed. These parameters provide key information for vehicle dynamics characterization. In this paper, we propose a novel algorithm based on fuzzy logic to estimate the mentioned parameters by means of a single strain-based system. Experimental tests have been carried out in order to prove the suitability and durability of the proposed on-board strain sensor system, as well as its low cost advantages, and the accuracy of the obtained estimations by means of fuzzy logic.

  5. Health Information in French (français)

    Science.gov (United States)

    ... Biopsy - français (French) Bilingual PDF Health Information Translations Breast Biopsy - français (French) Bilingual PDF Health Information Translations Colposcopy - français (French) Bilingual PDF ...

  6. Art in the Age of Machine Intelligence

    Directory of Open Access Journals (Sweden)

    Blaise Agüera y Arcas

    2017-09-01

    Full Text Available In this wide‐ranging essay, the leader of Google’s Seattle AI group and founder of the Artists and Machine Intelligence program discusses the long‐standing and complex relationship between art and technology. The transformation of artistic practice and theory that attended the 19th century photographic revolution is explored as a parallel for the current revolution in machine intelligence, which promises not only to mechanize (or democratize the means of reproduction, but also of production.

  7. 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?

  8. 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...

  9. Development of a simplified method for intelligent glazed façade design under different control strategies and verified by building simulation tool BSim

    DEFF Research Database (Denmark)

    Liu, Mingzhe; Wittchen, Kim Bjarne; Heiselberg, Per

    2014-01-01

    The research aims to develop a simplified calculation method for intelligent glazed facade under different control conditions (night shutter, solar shading and natural ventilation) to simulate the energy performance and indoor environment of an office room installed with the intelligent facade......, it is possible to calculate the whole year performance of a room or building with intelligent glazed façade, which makes it a less time consuming tool to investigate the performance of the intelligent façade under different control strategies in the design stage with acceptable accuracy. Results showed good....... The method took the angle dependence of the solar characteristic into account, including the simplified hourly building model developed according to EN 13790 to evaluate the influence of the controlled façade on both the indoor environment (indoor air temperature, solar transmittance through the façade...

  10. Fully automatic AI-based leak detection system

    Energy Technology Data Exchange (ETDEWEB)

    Tylman, Wojciech; Kolczynski, Jakub [Dept. of Microelectronics and Computer Science, Technical University of Lodz in Poland, ul. Wolczanska 221/223, Lodz (Poland); Anders, George J. [Kinectrics Inc., 800 Kipling Ave., Toronto, Ontario M8Z 6C4 (Canada)

    2010-09-15

    This paper presents a fully automatic system intended to detect leaks of dielectric fluid in underground high-pressure, fluid-filled (HPFF) cables. The system combines a number of artificial intelligence (AI) and data processing techniques to achieve high detection capabilities for various rates of leaks, including leaks as small as 15 l per hour. The system achieves this level of precision mainly thanks to a novel auto-tuning procedure, enabling learning of the Bayesian network - the decision-making component of the system - using simulated leaks of various rates. Significant new developments extending the capabilities of the original leak detection system described in and form the basis of this paper. Tests conducted on the real-life HPFF cable system in New York City are also discussed. (author)

  11. Applying AI techniques to improve alarm display effectiveness

    International Nuclear Information System (INIS)

    Gross, J.M.; Birrer, S.A.; Crosberg, D.R.

    1987-01-01

    The Alarm Filtering System (AFS) addresses the problem of information overload in a control room during abnormal operations. Since operators can miss vital information during these periods, systems which emphasize important messages are beneficial. AFS uses the artificial intelligence (AI) technique of object-oriented programming to filter and dynamically prioritize alarm messages. When an alarm's status changes, AFS determines the relative importance of that change according to the current process state. AFS bases that relative importance on relationships the newly changed alarm has with other activated alarms. Evaluations of a alarm importance take place without regard to the activation sequence of alarm signals. The United States Department of Energy has applied for a patent on the approach used in this software. The approach was originally developed by EG and G Idaho for a nuclear reactor control room

  12. 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

  13. The Singularity, or How I Learned to Stop Worrying and Love AI

    OpenAIRE

    Bishop, Mark (J. M.)

    2015-01-01

    Professor Stephen Hawking recently warned about the growing power of Artificial Intelligence (AI) to imbue robots with the ability to both replicate them- selves and to increase the rate at which they get smarter - leading to a tipping point or ‘technological singularity’ when they can outsmart humans. In this chapter I will argue that Hawking is essentially correct to flag up an existential danger surrounding widespread deployment of ‘autonomous machines’, but wrong to be so concerned about ...

  14. 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)

  15. Sensor assignment to mission in AI-TECD

    Science.gov (United States)

    Ganger, Robert; de Mel, Geeth; Pham, Tien; Rudnicki, Ronald; Schreiber, Yonatan

    2016-05-01

    Sensor-mission assignment involves the allocation of sensors and other information-providing resources to missions in order to cover the information needs of the individual tasks within each mission. The importance of efficient and effective means to find appropriate resources for tasks is exacerbated in the coalition context where the operational environment is dynamic and a multitude of critically important tasks need to achieve their collective goals to meet the objectives of the coalition. The Sensor Assignment to Mission (SAM) framework—a research product of the International Technology Alliance in Network and Information Sciences (NIS-ITA) program—provided the first knowledge intensive resource selection approach for the sensor network domain so that contextual information could be used to effectively select resources for tasks in coalition environments. Recently, CUBRC, Inc. was tasked with operationalizing the SAM framework through the use of the I2WD Common Core Ontologies for the Communications-Electronics Research, Development and Engineering Center (CERDEC) sponsored Actionable Intelligence Technology Enabled Capabilities Demonstration (AI-TECD). The demonstration event took place at Fort Dix, New Jersey during July 2015, and this paper discusses the integration and the successful demonstration of the SAM framework within the AI-TECD, lessons learned, and its potential impact in future operations.

  16. 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

    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 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 ...

  17. AIS Ship Traffic: Hawaii: 2011-2012

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Ship position data from a satellite-based Automatic Identification System (AIS) were obtained jointly by PacIOOS (J. Potemra), SOEST/ORE of the University of Hawaii...

  18. Cracks appear in the AI gravy train

    Energy Technology Data Exchange (ETDEWEB)

    Mill, J.

    1983-10-01

    This article highlights some of the problems facing the Alvey committee and outlines some reasons for believing that the optimistically founded Alvey and Esprit funding programmes are no guarantee Britain will win the AI race.

  19. National AIS at 1 Minute Intervals

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — OCM plans to contract for AIS data per the following description. The United States Automatic Identification System Database contains vessel traffic data for...

  20. Biomimetics in Intelligent Sensor and Actuator Automation Systems

    Science.gov (United States)

    Bruckner, Dietmar; Dietrich, Dietmar; Zucker, Gerhard; Müller, Brit

    Intelligent machines are really an old mankind's dream. With increasing technological development, the requirements for intelligent devices also increased. However, up to know, artificial intelligence (AI) lacks solutions to the demands of truly intelligent machines that have no problems to integrate themselves into daily human environments. Current hardware with a processing power of billions of operations per second (but without any model of human-like intelligence) could not substantially contribute to the intelligence of machines when compared with that of the early AI times. There are great results, of course. Machines are able to find the shortest path between far apart cities on the map; algorithms let you find information described only by few key words. But no machine is able to get us a cup of coffee from the kitchen yet.