Optical Inference Machines

DTIC Science & Technology

1988-06-27

de olf nessse end Id e ;-tl Sb ieeI smleo) ,Optical Artificial Intellegence ; Optical inference engines; Optical logic; Optical informationprocessing...common. They arise in areas such as expert systems and other artificial intelligence systems. In recent years, the computer science language PROLOG has...cal processors should in principle be well suited for : I artificial intelligence applications. In recent years, symbolic logic processing. , the

Artificial Intelligence and Expert Systems.

ERIC Educational Resources Information Center

Lawlor, Joseph

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

Intelligent Computer-Assisted Language Learning.

ERIC Educational Resources Information Center

Harrington, Michael

1996-01-01

Introduces the field of intelligent computer assisted language learning (ICALL) and relates them to current practice in computer assisted language learning (CALL) and second language learning. Points out that ICALL applies expertise from artificial intelligence and the computer and cognitive sciences to the development of language learning…

Computer Assisted Instructional Design for Computer-Based Instruction. Final Report. Working Papers.

ERIC Educational Resources Information Center

Russell, Daniel M.; Pirolli, Peter

Recent advances in artificial intelligence and the cognitive sciences have made it possible to develop successful intelligent computer-aided instructional systems for technical and scientific training. In addition, computer-aided design (CAD) environments that support the rapid development of such computer-based instruction have also been recently…

Computational Social Creativity.

PubMed

Saunders, Rob; Bown, Oliver

2015-01-01

This article reviews the development of computational models of creativity where social interactions are central. We refer to this area as computational social creativity. Its context is described, including the broader study of creativity, the computational modeling of other social phenomena, and computational models of individual creativity. Computational modeling has been applied to a number of areas of social creativity and has the potential to contribute to our understanding of creativity. A number of requirements for computational models of social creativity are common in artificial life and computational social science simulations. Three key themes are identified: (1) computational social creativity research has a critical role to play in understanding creativity as a social phenomenon and advancing computational creativity by making clear epistemological contributions in ways that would be challenging for other approaches; (2) the methodologies developed in artificial life and computational social science carry over directly to computational social creativity; and (3) the combination of computational social creativity with individual models of creativity presents significant opportunities and poses interesting challenges for the development of integrated models of creativity that have yet to be realized.

Amplify scientific discovery with artificial intelligence

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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

Nontrivial, Nonintelligent, Computer-Based Learning.

ERIC Educational Resources Information Center

Bork, Alfred

1987-01-01

This paper describes three interactive computer programs used with personal computers to present science learning modules for all ages. Developed by groups of teachers at the Educational Technology Center at the University of California, Irvine, these instructional materials do not use the techniques of contemporary artificial intelligence. (GDC)

Artificial Intelligence in Business: Technocrat Jargon or Quantum Leap?

ERIC Educational Resources Information Center

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…

Videos | Argonne National Laboratory

Science.gov Websites

science --Agent-based modeling --Applied mathematics --Artificial intelligence --Cloud computing management -Intelligence & counterterrorrism -Vulnerability assessment -Sensors & detectors Programs

Teaching Psychology Students Computer Applications.

ERIC Educational Resources Information Center

Atnip, Gilbert W.

This paper describes an undergraduate-level course designed to teach the applications of computers that are most relevant in the social sciences, especially psychology. After an introduction to the basic concepts and terminology of computing, separate units were devoted to word processing, data analysis, data acquisition, artificial intelligence,…

Collective Computation of Neural Network

DTIC Science & Technology

1990-03-15

Sciences, Beijing ABSTRACT Computational neuroscience is a new branch of neuroscience originating from current research on the theory of computer...scientists working in artificial intelligence engineering and neuroscience . The paper introduces the collective computational properties of model neural...vision research. On this basis, the authors analyzed the significance of the Hopfield model. Key phrases: Computational Neuroscience , Neural Network, Model

Research approaches to mass casualty incidents response: development from routine perspectives to complexity science.

PubMed

Shen, Weifeng; Jiang, Libing; Zhang, Mao; Ma, Yuefeng; Jiang, Guanyu; He, Xiaojun

2014-01-01

To review the research methods of mass casualty incident (MCI) systematically and introduce the concept and characteristics of complexity science and artificial system, computational experiments and parallel execution (ACP) method. We searched PubMed, Web of Knowledge, China Wanfang and China Biology Medicine (CBM) databases for relevant studies. Searches were performed without year or language restrictions and used the combinations of the following key words: "mass casualty incident", "MCI", "research method", "complexity science", "ACP", "approach", "science", "model", "system" and "response". Articles were searched using the above keywords and only those involving the research methods of mass casualty incident (MCI) were enrolled. Research methods of MCI have increased markedly over the past few decades. For now, dominating research methods of MCI are theory-based approach, empirical approach, evidence-based science, mathematical modeling and computer simulation, simulation experiment, experimental methods, scenario approach and complexity science. This article provides an overview of the development of research methodology for MCI. The progresses of routine research approaches and complexity science are briefly presented in this paper. Furthermore, the authors conclude that the reductionism underlying the exact science is not suitable for MCI complex systems. And the only feasible alternative is complexity science. Finally, this summary is followed by a review that ACP method combining artificial systems, computational experiments and parallel execution provides a new idea to address researches for complex MCI.

Testing meta tagger

DTIC Science & Technology

2017-12-21

rank , and computer vision. Machine learning is closely related to (and often overlaps with) computational statistics, which also focuses on...Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed.[1] Arthur Samuel...an American pioneer in the field of computer gaming and artificial intelligence, coined the term "Machine Learning " in 1959 while at IBM[2]. Evolved

Abstracts of Research, July 1975-June 1976.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Computer and Information Science Research Center.

Abstracts of research papers in computer and information science are given for 62 papers in the areas of information storage and retrieval; computer facilities; information analysis; linguistics analysis; artificial intelligence; information processes in physical, biological, and social systems; mathematical technigues; systems programming;…

Using Microcomputers Simulations in the Classroom: Examples from Undergraduate and Faculty Computer Literacy Courses.

ERIC Educational Resources Information Center

Hart, Jeffrey A.

1985-01-01

Presents a discussion of how computer simulations are used in two undergraduate social science courses and a faculty computer literacy course on simulations and artificial intelligence. Includes a list of 60 simulations for use on mainframes and microcomputers. Entries include type of hardware required, publisher's address, and cost. Sample…

Architecture of a Message-Driven Processor,

DTIC Science & Technology

1987-11-01

Jon Kaplan, Paul Song, Brian Totty, and Scott Wills Artifcial Intelligence Laboratory -4 Laboratory for Computer Science Massachusetts Institute of...Information Dally, Chao, Chien, Hassoun, Horwat, Kaplan, Song, Totty & Wills: Artificial Intelligence i Laboratory and Laboratory for Computer Science, MIT...applied to a problem if we could are 36 bits long (32 data bits + 4 tag bits) and are used to hold efficiently run programs with a granularity of 5s

Data mining: sophisticated forms of managed care modeling through artificial intelligence.

PubMed

Borok, L S

1997-01-01

Data mining is a recent development in computer science that combines artificial intelligence algorithms and relational databases to discover patterns automatically, without the use of traditional statistical methods. Work with data mining tools in health care is in a developmental stage that holds great promise, given the combination of demographic and diagnostic information.

The Seeds of Artificial Intelligence. SUMEX-AIM.

ERIC Educational Resources Information Center

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…

Automated Explanation for Educational Applications.

ERIC Educational Resources Information Center

Suthers, Daniel D.

1991-01-01

Artificial intelligence techniques available for generating explanations for teaching purposes are surveyed, and the way in which they are combined in a computer program that provides explanations is described. The program responds to questions in the physical sciences. Potential contributions of this technology to computer-based education are…

Abstracts of Research, July 1973 through June 1974.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Computer and Information Science Research Center.

Abstracts of research papers in the fields of computer and information science are given; 72 papers are abstracted in the areas of information storage and retrieval, information processing, linguistic analysis, artificial intelligence, mathematical techniques, systems programing, and computer networks. In addition, the Ohio State University…

Enhancing Tele-robotics with Immersive Virtual Reality

DTIC Science & Technology

2017-11-03

graduate and undergraduate students within the Digital Gaming and Simulation, Computer Science, and psychology programs have actively collaborated...investigates the use of artificial intelligence and visual computing. Numerous fields across the human-computer interaction and gaming research areas...invested in digital gaming and simulation to cognitively stimulate humans by computers, forming a $10.5B industry [1]. On the other hand, cognitive

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

PubMed

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.

From Years of Work in Psychology and Computer Science, Scientists Build Theories of Thinking and Learning.

ERIC Educational Resources Information Center

Wheeler, David L.

1988-01-01

Scientists feel that progress in artificial intelligence and the availability of thousands of experimental results make this the right time to build and test theories on how people think and learn, using the computer to model minds. (MSE)

Cognitive Computational Neuroscience: A New Conference for an Emerging Discipline.

PubMed

Naselaris, Thomas; Bassett, Danielle S; Fletcher, Alyson K; Kording, Konrad; Kriegeskorte, Nikolaus; Nienborg, Hendrikje; Poldrack, Russell A; Shohamy, Daphna; Kay, Kendrick

2018-05-01

Understanding the computational principles that underlie complex behavior is a central goal in cognitive science, artificial intelligence, and neuroscience. In an attempt to unify these disconnected communities, we created a new conference called Cognitive Computational Neuroscience (CCN). The inaugural meeting revealed considerable enthusiasm but significant obstacles remain. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

ERIC Educational Resources Information Center

Sayre, Scott Alan

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

Temporal Reasoning and Default Logics.

DTIC Science & Technology

1985-10-01

Aritificial Intelligence ", Computer Science Research Report, Yale University, forthcoming (1985). . 74 .-, A Axioms for Describing Persistences and Clipping...34Circumscription - A Form of Non-Monotonic Reasoning", Artificial Intelligence , vol. 13 (1980), pp. 27-39. [13] McCarthy, John, "Applications of...and P. J. Hayes, "Some philosophical problems from the standpoint of artificial intelligence ", in: B. Meltzer and D. Michie (eds.), Machine

"Have Them Read a Good Book": Enriching the Scientific and Technical Writing Curriculum.

ERIC Educational Resources Information Center

Miles, Thomas H.

1989-01-01

Lists approximately 200 recent science and technology book titles (some with annotations). Notes that this literature acquaints students with the history of science and technology and helps them understand debated philosophical issues. Includes the following subject areas: anthropology; chemistry; computers and artificial intelligence; ecology;…

Optimization of knowledge-based systems and expert system building tools

NASA Technical Reports Server (NTRS)

Yasuda, Phyllis; Mckellar, Donald

1993-01-01

The objectives of the NASA-AMES Cooperative Agreement were to investigate, develop, and evaluate, via test cases, the system parameters and processing algorithms that constrain the overall performance of the Information Sciences Division's Artificial Intelligence Research Facility. Written reports covering various aspects of the grant were submitted to the co-investigators for the grant. Research studies concentrated on the field of artificial intelligence knowledge-based systems technology. Activities included the following areas: (1) AI training classes; (2) merging optical and digital processing; (3) science experiment remote coaching; (4) SSF data management system tests; (5) computer integrated documentation project; (6) conservation of design knowledge project; (7) project management calendar and reporting system; (8) automation and robotics technology assessment; (9) advanced computer architectures and operating systems; and (10) honors program.

Problem Solving with General Semantics.

ERIC Educational Resources Information Center

Hewson, David

1996-01-01

Discusses how to use general semantics formulations to improve problem solving at home or at work--methods come from the areas of artificial intelligence/computer science, engineering, operations research, and psychology. (PA)

Machine learning: Trends, perspectives, and prospects.

PubMed

Jordan, M I; Mitchell, T M

2015-07-17

Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science and statistics, and at the core of artificial intelligence and data science. Recent progress in machine learning has been driven both by the development of new learning algorithms and theory and by the ongoing explosion in the availability of online data and low-cost computation. The adoption of data-intensive machine-learning methods can be found throughout science, technology and commerce, leading to more evidence-based decision-making across many walks of life, including health care, manufacturing, education, financial modeling, policing, and marketing. Copyright © 2015, American Association for the Advancement of Science.

Human Inspired Self-developmental Model of Neural Network (HIM): Introducing Content/Form Computing

NASA Astrophysics Data System (ADS)

Krajíček, Jiří

This paper presents cross-disciplinary research between medical/psychological evidence on human abilities and informatics needs to update current models in computer science to support alternative methods for computation and communication. In [10] we have already proposed hypothesis introducing concept of human information model (HIM) as cooperative system. Here we continue on HIM design in detail. In our design, first we introduce Content/Form computing system which is new principle of present methods in evolutionary computing (genetic algorithms, genetic programming). Then we apply this system on HIM (type of artificial neural network) model as basic network self-developmental paradigm. Main inspiration of our natural/human design comes from well known concept of artificial neural networks, medical/psychological evidence and Sheldrake theory of "Nature as Alive" [22].

A Game Based e-Learning System to Teach Artificial Intelligence in the Computer Sciences Degree

ERIC Educational Resources Information Center

de Castro-Santos, Amable; Fajardo, Waldo; Molina-Solana, Miguel

2017-01-01

Our students taking the Artificial Intelligence and Knowledge Engineering courses often encounter a large number of problems to solve which are not directly related to the subject to be learned. To solve this problem, we have developed a game based e-learning system. The elected game, that has been implemented as an e-learning system, allows to…

MLeXAI: A Project-Based Application-Oriented Model

ERIC Educational Resources Information Center

Russell, Ingrid; Markov, Zdravko; Neller, Todd; Coleman, Susan

2010-01-01

Our approach to teaching introductory artificial intelligence (AI) unifies its diverse core topics through a theme of machine learning, and emphasizes how AI relates more broadly with computer science. Our work, funded by a grant from the National Science Foundation, involves the development, implementation, and testing of a suite of projects that…

Teacher's Guide for Computational Models of Animal Behavior: A Computer-Based Curriculum Unit to Accompany the Elementary Science Study Guide "Behavior of Mealworms." Artificial Intelligence Memo No. 432.

ERIC Educational Resources Information Center

Abelson, Hal; Goldenberg, Paul

This experimental curriculum unit suggests how dramatic innovations in classroom content may be achieved through use of computers. The computational perspective is viewed as one which can enrich and transform traditional curricula, act as a focus for integrating insights from diverse disciplines, and enable learning to become more active and…

Modernization (Selected Articles),

DTIC Science & Technology

1986-09-18

newly developed science such as control theory, artificial intelligence, model identification, computer and microelectronics technology, graphic...five "top guns" from around the country specializing in intellignece , mechanics, software and hardware as our technical advisors. In addition

Mediagraphy: Print and Nonprint Resources.

ERIC Educational Resources Information Center

Educational Media and Technology Yearbook, 1998

1998-01-01

Lists educational media-related journals, books, ERIC documents, journal articles, and nonprint resources classified by Artificial Intelligence, Robotics, Electronic Performance Support Systems; Computer-Assisted Instruction; Distance Education; Educational Research; Educational Technology; Electronic Publishing; Information Science and…

Application of artificial intelligence to pharmacy and medicine.

PubMed

Dasta, J F

1992-04-01

Artificial intelligence (AI) is a branch of computer science dealing with solving problems using symbolic programming. It has evolved into a problem solving science with applications in business, engineering, and health care. One application of AI is expert system development. An expert system consists of a knowledge base and inference engine, coupled with a user interface. A crucial aspect of expert system development is knowledge acquisition and implementing computable ways to solve problems. There have been several expert systems developed in medicine to assist physicians with medical diagnosis. Recently, several programs focusing on drug therapy have been described. They provide guidance on drug interactions, drug therapy monitoring, and drug formulary selection. There are many aspects of pharmacy that AI can have an impact on and the reader is challenged to consider these possibilities because they may some day become a reality in pharmacy.

Applications of Multi-Agent Technology to Power Systems

NASA Astrophysics Data System (ADS)

Nagata, Takeshi

Currently, agents are focus of intense on many sub-fields of computer science and artificial intelligence. Agents are being used in an increasingly wide variety of applications. Many important computing applications such as planning, process control, communication networks and concurrent systems will benefit from using multi-agent system approach. A multi-agent system is a structure given by an environment together with a set of artificial agents capable to act on this environment. Multi-agent models are oriented towards interactions, collaborative phenomena, and autonomy. This article presents the applications of multi-agent technology to the power systems.

Baby, Where Did You Get Those Eyes?: IEEE Pulse talks with Mark Sagar about the new face of artificial intelligence.

PubMed

Campbell, Sarah

2015-01-01

Mark Sagar is changing the way we look at computers by giving them faces?disconcertingly realistic human faces. Sagar first gained widespread recognition for his pioneering work in rendering faces for Hollywood movies, including Avatar and King Kong. With a Ph.D. degree in bioengineering and two Academy Awards under his belt, Sagar now directs a research lab at the University of Auckland, New Zealand, a combinatorial hub where artificial intelligence (AI), neuroscience, computer science, philosophy, and cognitive psychology intersect in creating interactive, intelligent technologies.

Applications of artificial neural networks in medical science.

PubMed

Patel, Jigneshkumar L; Goyal, Ramesh K

2007-09-01

Computer technology has been advanced tremendously and the interest has been increased for the potential use of 'Artificial Intelligence (AI)' in medicine and biological research. One of the most interesting and extensively studied branches of AI is the 'Artificial Neural Networks (ANNs)'. Basically, ANNs are the mathematical algorithms, generated by computers. ANNs learn from standard data and capture the knowledge contained in the data. Trained ANNs approach the functionality of small biological neural cluster in a very fundamental manner. They are the digitized model of biological brain and can detect complex nonlinear relationships between dependent as well as independent variables in a data where human brain may fail to detect. Nowadays, ANNs are widely used for medical applications in various disciplines of medicine especially in cardiology. ANNs have been extensively applied in diagnosis, electronic signal analysis, medical image analysis and radiology. ANNs have been used by many authors for modeling in medicine and clinical research. Applications of ANNs are increasing in pharmacoepidemiology and medical data mining. In this paper, authors have summarized various applications of ANNs in medical science.

Mediagraphy: Print and Nonprint Resources.

ERIC Educational Resources Information Center

Educational Media and Technology Yearbook, 1999

1999-01-01

Provides annotated listings for current journals, books, ERIC documents, articles, and nonprint resources in the following categories: artificial intelligence/robotics/electronic performance support systems; computer-assisted instruction; distance education; educational research; educational technology; information science and technology;…

Evolution, learning, and cognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Y.C.

1988-01-01

The book comprises more than fifteen articles in the areas of neural networks and connectionist systems, classifier systems, adaptive network systems, genetic algorithm, cellular automata, artificial immune systems, evolutionary genetics, cognitive science, optical computing, combinatorial optimization, and cybernetics.

Technology 2001: The Second National Technology Transfer Conference and Exposition, volume 1

NASA Technical Reports Server (NTRS)

1991-01-01

Papers from the technical sessions of the Technology 2001 Conference and Exposition are presented. The technical sessions featured discussions of advanced manufacturing, artificial intelligence, biotechnology, computer graphics and simulation, communications, data and information management, electronics, electro-optics, environmental technology, life sciences, materials science, medical advances, robotics, software engineering, and test and measurement.

An Ankle-Foot Orthosis Powered by Artificial Pneumatic Muscles

PubMed Central

Ferris, Daniel P.; Czerniecki, Joseph M.; Hannaford, Blake

2005-01-01

We developed a pneumatically powered orthosis for the human ankle joint. The orthosis consisted of a carbon fiber shell, hinge joint, and two artificial pneumatic muscles. One artificial pneumatic muscle provided plantar flexion torque and the second one provided dorsiflexion torque. Computer software adjusted air pressure in each artificial muscle independently so that artificial muscle force was proportional to rectified low-pass-filtered electromyography (EMG) amplitude (i.e., proportional myoelectric control). Tibialis anterior EMG activated the artificial dorsiflexor and soleus EMG activated the artificial plantar flexor. We collected joint kinematic and artificial muscle force data as one healthy participant walked on a treadmill with the orthosis. Peak plantar flexor torque provided by the orthosis was 70 Nm, and peak dorsiflexor torque provided by the orthosis was 38 Nm. The orthosis could be useful for basic science studies on human locomotion or possibly for gait rehabilitation after neurological injury. PMID:16082019

Experiments with microcomputer-based artificial intelligence environments

USGS Publications Warehouse

Summers, E.G.; MacDonald, R.A.

1988-01-01

The U.S. Geological Survey (USGS) has been experimenting with the use of relatively inexpensive microcomputers as artificial intelligence (AI) development environments. Several AI languages are available that perform fairly well on desk-top personal computers, as are low-to-medium cost expert system packages. Although performance of these systems is respectable, their speed and capacity limitations are questionable for serious earth science applications foreseen by the USGS. The most capable artificial intelligence applications currently are concentrated on what is known as the "artificial intelligence computer," and include Xerox D-series, Tektronix 4400 series, Symbolics 3600, VAX, LMI, and Texas Instruments Explorer. The artificial intelligence computer runs expert system shells and Lisp, Prolog, and Smalltalk programming languages. However, these AI environments are expensive. Recently, inexpensive 32-bit hardware has become available for the IBM/AT microcomputer. USGS has acquired and recently completed Beta-testing of the Gold Hill Systems 80386 Hummingboard, which runs Common Lisp on an IBM/AT microcomputer. Hummingboard appears to have the potential to overcome many of the speed/capacity limitations observed with AI-applications on standard personal computers. USGS is a Beta-test site for the Gold Hill Systems GoldWorks expert system. GoldWorks combines some high-end expert system shell capabilities in a medium-cost package. This shell is developed in Common Lisp, runs on the 80386 Hummingboard, and provides some expert system features formerly available only on AI-computers including frame and rule-based reasoning, on-line tutorial, multiple inheritance, and object-programming. ?? 1988 International Association for Mathematical Geology.

Mediagraphy: Print and Nonprint Resources.

ERIC Educational Resources Information Center

Educational Media and Technology Yearbook, 1996

1996-01-01

This annotated list includes media-related resources classified under the following headings: artificial intelligence and robotics, CD-ROM, computer-assisted instruction, databases and online searching, distance education, educational research, educational technology, electronic publishing, information science and technology, instructional design…

Mediagraphy: Print and Nonprint Resources.

ERIC Educational Resources Information Center

Educational Media and Technology Yearbook, 1997

1997-01-01

This annotated list includes media-related resources classified under the following headings: artificial intelligence and robotics, CD-ROM, computer-assisted instruction, databases and online searching, distance education, educational research, educational technology, electronic publishing, information science and technology, instructional design…

Technology 2004, Vol. 2

NASA Technical Reports Server (NTRS)

1995-01-01

Proceedings from symposia of the Technology 2004 Conference, November 8-10, 1994, Washington, DC. Volume 2 features papers on computers and software, virtual reality simulation, environmental technology, video and imaging, medical technology and life sciences, robotics and artificial intelligence, and electronics.

Complex systems and health behavior change: insights from cognitive science.

PubMed

Orr, Mark G; Plaut, David C

2014-05-01

To provide proof-of-concept that quantum health behavior can be instantiated as a computational model that is informed by cognitive science, the Theory of Reasoned Action, and quantum health behavior theory. We conducted a synthetic review of the intersection of quantum health behavior change and cognitive science. We conducted simulations, using a computational model of quantum health behavior (a constraint satisfaction artificial neural network) and tested whether the model exhibited quantum-like behavior. The model exhibited clear signs of quantum-like behavior. Quantum health behavior can be conceptualized as constraint satisfaction: a mitigation between current behavioral state and the social contexts in which it operates. We outlined implications for moving forward with computational models of both quantum health behavior and health behavior in general.

Proceedings from an International Conference on Computers and Philosophy, i-C&P 2006 held 3-5 May 2006 in Laval, France

DTIC Science & Technology

2008-10-20

embedded intelligence and cultural adaptations to the onslaught of robots in society. This volume constitutes a key contribution to the body of... Robotics , CNRS/Toulouse University, France Nathalie COLINEAU, Language & Multi-modality, CSIRO, Australia Roberto CORDESCHI, Computation & Communication...Intelligence, SONY CSL ­ Paris Nik KASABOV, Computer and Information Sciences, Auckland University, New Zealand Oussama KHATIB, Robotics & Artificial

In-Storage Embedded Accelerator for Sparse Pattern Processing

DTIC Science & Technology

2016-09-13

computation . As a result, a very small processor could be used and still make full use of storage device bandwidth. When the host software sends...Rean Griffith, Anthony D. Joseph, Randy Katz, Andy Konwinski, Gunho Lee et al. "A view of cloud computing ."Communications of the ACM 53, no. 4 (2010...Laboratory, * MIT Computer Science & Artificial Intelligence Laboratory Abstract— We present a novel system architecture for sparse pattern

Deductive Synthesis of the Unification Algorithm,

DTIC Science & Technology

1981-06-01

DEDUCTIVE SYNTHESIS OF THE I - UNIFICATION ALGORITHM Zohar Manna Richard Waldinger I F? Computer Science Department Artificial Intelligence Center...theorem proving," Artificial Intelligence Journal, Vol. 9, No. 1, pp. 1-35. Boyer, R. S. and J S. Moore [Jan. 19751, "Proving theorems about LISP...d’Intelligence Artificielle , U.E.R. de Luminy, Universit6 d’ Aix-Marseille II. Green, C. C. [May 1969], "Application of theorem proving to problem

Multi-layer robot skin with embedded sensors and muscles

NASA Astrophysics Data System (ADS)

Tomar, Ankit; Tadesse, Yonas

2016-04-01

Soft artificial skin with embedded sensors and actuators is proposed for a crosscutting study of cognitive science on a facial expressive humanoid platform. This paper focuses on artificial muscles suitable for humanoid robots and prosthetic devices for safe human-robot interactions. Novel composite artificial skin consisting of sensors and twisted polymer actuators is proposed. The artificial skin is conformable to intricate geometries and includes protective layers, sensor layers, and actuation layers. Fluidic channels are included in the elastomeric skin to inject fluids in order to control actuator response time. The skin can be used to develop facially expressive humanoid robots or other soft robots. The humanoid robot can be used by computer scientists and other behavioral science personnel to test various algorithms, and to understand and develop more perfect humanoid robots with facial expression capability. The small-scale humanoid robots can also assist ongoing therapeutic treatment research with autistic children. The multilayer skin can be used for many soft robots enabling them to detect both temperature and pressure, while actuating the entire structure.

AI in Informal Science Education: Bringing Turing Back to Life to Perform the Turing Test

ERIC Educational Resources Information Center

Gonzalez, Avelino J.; Hollister, James R.; DeMara, Ronald F.; Leigh, Jason; Lanman, Brandan; Lee, Sang-Yoon; Parker, Shane; Walls, Christopher; Parker, Jeanne; Wong, Josiah; Barham, Clayton; Wilder, Bryan

2017-01-01

This paper describes an interactive museum exhibit featuring an avatar of Alan Turing that informs museum visitors about artificial intelligence and Turing's seminal Turing Test for machine intelligence. The objective of the exhibit is to engage and motivate visiting children in the hope of sparking an interest in them about computer science and…

Mediagraphy: Print and Nonprint Resources.

ERIC Educational Resources Information Center

Price, Brooke, Ed.

2001-01-01

Lists media-related journals, books, ERIC documents, journal articles, and nonprint resources published in 1999-2000. The annotated entries are classified under the following headings: artificial intelligence; computer assisted instruction; distance education; educational research; educational technology; information science and technology;…

Mediagraphy: Print and Nonprint Resources.

ERIC Educational Resources Information Center

Burdett, Anna E.

2003-01-01

Lists media-related journals, books, ERIC documents, journal articles, and nonprint resources published in 2001-2002. The annotated entries are classified under the following headings: artificial intelligence; computer assisted instruction; distance education; educational research; educational technology; information science and technology;…

The emergence of mind and brain: an evolutionary, computational, and philosophical approach.

PubMed

Mainzer, Klaus

2008-01-01

Modern philosophy of mind cannot be understood without recent developments in computer science, artificial intelligence (AI), robotics, neuroscience, biology, linguistics, and psychology. Classical philosophy of formal languages as well as symbolic AI assume that all kinds of knowledge must explicitly be represented by formal or programming languages. This assumption is limited by recent insights into the biology of evolution and developmental psychology of the human organism. Most of our knowledge is implicit and unconscious. It is not formally represented, but embodied knowledge, which is learnt by doing and understood by bodily interacting with changing environments. That is true not only for low-level skills, but even for high-level domains of categorization, language, and abstract thinking. The embodied mind is considered an emergent capacity of the brain as a self-organizing complex system. Actually, self-organization has been a successful strategy of evolution to handle the increasing complexity of the world. Genetic programs are not sufficient and cannot prepare the organism for all kinds of complex situations in the future. Self-organization and emergence are fundamental concepts in the theory of complex dynamical systems. They are also applied in organic computing as a recent research field of computer science. Therefore, cognitive science, AI, and robotics try to model the embodied mind in an artificial evolution. The paper analyzes these approaches in the interdisciplinary framework of complex dynamical systems and discusses their philosophical impact.

From Self-Flying Helicopters to Classrooms of the Future

ERIC Educational Resources Information Center

Young, Jeffrey R.

2012-01-01

On a summer day four years ago, a Stanford University computer-science professor named Andrew Ng held an unusual air show on a field near the campus. His fleet of small helicopter drones flew under computer control, piloted by artificial-intelligence software that could teach itself to fly after watching a human operator. By the end of the day,…

Shake, Rattle and Roles: Lessons from Experimental Earthquake Engineering for Incorporating Remote Users in Large-Scale E-Science Experiments

DTIC Science & Technology

2007-01-01

Mechanical Turk: Artificial Artificial Intelligence . Retrieved May 15, 2006 from http://www.mturk.com/ mturk/welcome Atkins, D. E., Droegemeier, K. K...Turk (Amazon, 2006) site goes beyond volunteers and pays people to do Human Intelligence Tasks, those that are difficult for computers but relatively...geographically distributed scientific collaboration, and the use of videogame technology for training. Address: U.S. Army Research Institute, 2511 Jefferson

Educational Technology: Integration?

ERIC Educational Resources Information Center

Christensen, Dean L.; Tennyson, Robert D.

This paper presents a perspective of the current state of technology-assisted instruction integrating computer language, artificial intelligence (AI), and a review of cognitive science applied to instruction. The following topics are briefly discussed: (1) the language of instructional technology, i.e., programming languages, including authoring…

Technology.

ERIC Educational Resources Information Center

Online-Offline, 1998

1998-01-01

Focuses on technology, on advances in such areas as aeronautics, electronics, physics, the space sciences, as well as computers and the attendant progress in medicine, robotics, and artificial intelligence. Describes educational resources for elementary and middle school students, including Web sites, CD-ROMs and software, videotapes, books,…

Abstracts of Research. July 1974-June 1975.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Computer and Information Science Research Center.

Abstracts of research papers in computer and information science are given for 68 papers in the areas of information storage and retrieval; human information processing; information analysis; linguistic analysis; artificial intelligence; information processes in physical, biological, and social systems; mathematical techniques; systems…

Artificial intelligence in nanotechnology.

PubMed

Sacha, G M; Varona, P

2013-11-15

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

Artificial intelligence in nanotechnology

NASA Astrophysics Data System (ADS)

Sacha, G. M.; Varona, P.

2013-11-01

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

Applications of artificial intelligence to scientific research

NASA Technical Reports Server (NTRS)

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.

The image recognition based on neural network and Bayesian decision

NASA Astrophysics Data System (ADS)

Wang, Chugege

2018-04-01

The artificial neural network began in 1940, which is an important part of artificial intelligence. At present, it has become a hot topic in the fields of neuroscience, computer science, brain science, mathematics, and psychology. Thomas Bayes firstly reported the Bayesian theory in 1763. After the development in the twentieth century, it has been widespread in all areas of statistics. In recent years, due to the solution of the problem of high-dimensional integral calculation, Bayesian Statistics has been improved theoretically, which solved many problems that cannot be solved by classical statistics and is also applied to the interdisciplinary fields. In this paper, the related concepts and principles of the artificial neural network are introduced. It also summarizes the basic content and principle of Bayesian Statistics, and combines the artificial neural network technology and Bayesian decision theory and implement them in all aspects of image recognition, such as enhanced face detection method based on neural network and Bayesian decision, as well as the image classification based on the Bayesian decision. It can be seen that the combination of artificial intelligence and statistical algorithms has always been the hot research topic.

Translations on Eastern Europe, Scientific Affairs, Number 542.

DTIC Science & Technology

1977-04-18

transplanting human tissue has not as yet been given a final juridical approval like euthanasia, artificial insemination , abortion, birth control, and others...and data teleprocessing. This computer may also be used as a satellite computer for complex systems. The IZOT 310 has a large instruction...a well-known truth that modern science is using the most modern and leading technical facilities—from bathyscaphes to satellites , from gigantic

Image Understanding Research and Its Application to Cartography and Computer-Based Analysis of Aerial Imagery

DTIC Science & Technology

1983-09-01

Report Al-TR-346. Artifcial Intelligence Laboratory, Mamachusetts Institute of Tech- niugy. Cambridge, Mmeh mett. June 19 [G.usmn@ A. Gaman-Arenas...Testbed Coordinator, 415/859-4395 Artificial Intelligence Center Computer Science and Technology Division Prepared for: Defense Advanced Research...to support processing of aerial photographs for such military applications as cartography, Intelligence , weapon guidance, and targeting. A key

JPRS Report Science & Technology Japan Space Artificial Intelligence/Robotics/Automation Symposium.

DTIC Science & Technology

1989-12-28

Kazuya Kaku, et al. ] 28 Spacecraft Automatic Monitoring System [Kazuya Kaku, et al. ] 36 Autonomous Space Robot, Related Computer ...type space vehicle Space station , orbital sup - lport systems Transport systems Ground Systems 1 et»*:«..,..... ri,(rn™ Communciations ...axis torque sensor. Motorola’s VME-10 is used as the computer . 5. Experimental Results To investigate the state of separation between the external

[Algorithms of artificial neural networks--practical application in medical science].

PubMed

Stefaniak, Bogusław; Cholewiński, Witold; Tarkowska, Anna

2005-12-01

Artificial Neural Networks (ANN) may be a tool alternative and complementary to typical statistical analysis. However, in spite of many computer applications of various ANN algorithms ready for use, artificial intelligence is relatively rarely applied to data processing. This paper presents practical aspects of scientific application of ANN in medicine using widely available algorithms. Several main steps of analysis with ANN were discussed starting from material selection and dividing it into groups, to the quality assessment of obtained results at the end. The most frequent, typical reasons for errors as well as the comparison of ANN method to the modeling by regression analysis were also described.

Intelligence: Real or artificial?

PubMed Central

Schlinger, Henry D.

1992-01-01

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

Remarks on neurocybernetics and its links to computing science. To the memory of Prof. Luigi M. Ricciardi.

PubMed

Moreno-Díaz, Roberto; Moreno-Díaz, Arminda

2013-06-01

This paper explores the origins and content of neurocybernetics and its links to artificial intelligence, computer science and knowledge engineering. Starting with three remarkable pieces of work, we center attention on a number of events that initiated and developed basic topics that are still nowadays a matter of research and inquire, from goal directed activity theories to circular causality and to reverberations and learning. Within this context, we pay tribute to the memory of Prof. Ricciardi documenting the importance of his contributions in the mathematics of brain, neural nets and neurophysiological models, computational simulations and techniques. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Biologically inspired intelligent robots

NASA Astrophysics Data System (ADS)

Bar-Cohen, Yoseph; Breazeal, Cynthia

2003-07-01

Humans throughout history have always sought to mimic the appearance, mobility, functionality, intelligent operation, and thinking process of biological creatures. This field of biologically inspired technology, having the moniker biomimetics, has evolved from making static copies of human and animals in the form of statues to the emergence of robots that operate with realistic behavior. Imagine a person walking towards you where suddenly you notice something weird about him--he is not real but rather he is a robot. Your reaction would probably be "I can't believe it but this robot looks very real" just as you would react to an artificial flower that is a good imitation. You may even proceed and touch the robot to check if your assessment is correct but, as oppose to the flower case, the robot may be programmed to respond physical and verbally. This science fiction scenario could become a reality as the current trend continues in developing biologically inspired technologies. Technology evolution led to such fields as artificial muscles, artificial intelligence, and artificial vision as well as biomimetic capabilities in materials science, mechanics, electronics, computing science, information technology and many others. This paper will review the state of the art and challenges to biologically-inspired technologies and the role that EAP is expected to play as the technology evolves.

A Spacelab Expert System for Remote Engineering and Science

NASA Technical Reports Server (NTRS)

Groleau, Nick; Colombano, Silvano; Friedland, Peter (Technical Monitor)

1994-01-01

NASA's space science program is based on strictly pre-planned activities. This approach does not always result in the best science. We describe an existing computer system that enables space science to be conducted in a more reactive manner through advanced automation techniques that have recently been used in SLS-2 October 1993 space shuttle flight. Advanced computing techniques, usually developed in the field of Artificial Intelligence, allow large portions of the scientific investigator's knowledge to be "packaged" in a portable computer to present advice to the astronaut operator. We strongly believe that this technology has wide applicability to other forms of remote science/engineering. In this brief article, we present the technology of remote science/engineering assistance as implemented for the SLS-2 space shuttle flight. We begin with a logical overview of the system (paying particular attention to the implementation details relevant to the use of the embedded knowledge for system reasoning), then describe its use and success in space, and conclude with ideas about possible earth uses of the technology in the life and medical sciences.

First-principles data-driven discovery of transition metal oxides for artificial photosynthesis

NASA Astrophysics Data System (ADS)

Yan, Qimin

We develop a first-principles data-driven approach for rapid identification of transition metal oxide (TMO) light absorbers and photocatalysts for artificial photosynthesis using the Materials Project. Initially focusing on Cr, V, and Mn-based ternary TMOs in the database, we design a broadly-applicable multiple-layer screening workflow automating density functional theory (DFT) and hybrid functional calculations of bulk and surface electronic and magnetic structures. We further assess the electrochemical stability of TMOs in aqueous environments from computed Pourbaix diagrams. Several promising earth-abundant low band-gap TMO compounds with desirable band edge energies and electrochemical stability are identified by our computational efforts and then synergistically evaluated using high-throughput synthesis and photoelectrochemical screening techniques by our experimental collaborators at Caltech. Our joint theory-experiment effort has successfully identified new earth-abundant copper and manganese vanadate complex oxides that meet highly demanding requirements for photoanodes, substantially expanding the known space of such materials. By integrating theory and experiment, we validate our approach and develop important new insights into structure-property relationships for TMOs for oxygen evolution photocatalysts, paving the way for use of first-principles data-driven techniques in future applications. This work is supported by the Materials Project Predictive Modeling Center and the Joint Center for Artificial Photosynthesis through the U.S. Department of Energy, Office of Basic Energy Sciences, Materials Sciences and Engineering Division, under Contract No. DE-AC02-05CH11231. Computational resources also provided by the Department of Energy through the National Energy Supercomputing Center.

Is chess the drosophila of artificial intelligence? A social history of an algorithm.

PubMed

Ensmenger, Nathan

2012-02-01

Since the mid 1960s, researchers in computer science have famously referred to chess as the 'drosophila' of artificial intelligence (AI). What they seem to mean by this is that chess, like the common fruit fly, is an accessible, familiar, and relatively simple experimental technology that nonetheless can be used productively to produce valid knowledge about other, more complex systems. But for historians of science and technology, the analogy between chess and drosophila assumes a larger significance. As Robert Kohler has ably described, the decision to adopt drosophila as the organism of choice for genetics research had far-reaching implications for the development of 20th century biology. In a similar manner, the decision to focus on chess as the measure of both human and computer intelligence had important and unintended consequences for AL research. This paper explores the emergence of chess as an experimental technology, its significance in the developing research practices of the AI community, and the unique ways in which the decision to focus on chess shaped the program of AI research in the decade of the 1970s. More broadly, it attempts to open up the virtual black box of computer software--and of computer games in particular--to the scrutiny of historical and sociological analysis.

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

PubMed

Sancipriano, G P

2005-01-01

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

Australian DefenceScience. Volume 16, Number 1, Autumn

DTIC Science & Technology

2008-01-01

are carried via VOIP technology, and multicast IP traffic for audio -visual communications is also supported. The SSATIN system overall is seen to...Artificial Intelligence and Soft Computing Palma de Mallorca, Spain http://iasted.com/conferences/home-628.html 1 - 3 Sep 2008 Visualisation , Imaging and

The AI Interdisciplinary Context: Single or Multiple Research Bases?

ERIC Educational Resources Information Center

Khawam, Yves J.

1992-01-01

This study used citation analysis to determine whether the disciplines contributing to the journal literature of artificial intelligence (AI)--philosophy, psychology, linguistics, computer science, and engineering--share a common AI research base. The idea that AI consists of a completely interdisciplinary endeavor was refuted. (MES)

It's 1984 and Robots Are in the Classroom.

ERIC Educational Resources Information Center

Howe, Samuel F.

1984-01-01

Describes the features of TOPO, HERO, RB5X, and Tasman Turtle, personal robots used in elementary and secondary schools and colleges to introduce concepts of artificial intelligence, advanced high school and college computer science, and elementary level programming. Mechanical arms are also briefly mentioned. (MBR)

Computer finds ore

NASA Astrophysics Data System (ADS)

Bell, Peter M.

Artificial intelligence techniques are being used for the first time to evaluate geophysical, geochemical, and geologic data and theory in order to locate ore deposits. After several years of development, an intelligent computer code has been formulated and applied to the Mount Tolman area in Washington state. In a project funded by the United States Geological Survey and the National Science Foundation a set of computer programs, under the general title Prospector, was used successfully to locate a previously unknown ore-grade porphyry molybdenum deposit in the vicinity of Mount Tolman (Science, Sept. 3, 1982).The general area of the deposit had been known to contain exposures of porphyry mineralization. Between 1964 and 1978, exploration surveys had been run by the Bear Creek Mining Company, and later exploration was done in the area by the Amax Corporation. Some of the geophysical data and geochemical and other prospecting surveys were incorporated into the programs, and mine exploration specialists contributed to a set of rules for Prospector. The rules were encoded as ‘inference networks’ to form the ‘expert system’ on which the artificial intelligence codes were based. The molybdenum ore deposit discovered by the test is large, located subsurface, and has an areal extent of more than 18 km2.

Application Of The CSRL Language To The Design Of Diagnostic Expert Systems: The Moodis Experience, A Preliminary Report

NASA Astrophysics Data System (ADS)

Bravos, Angelo; Hill, Howard; Choca, James; Bresolin, Linda B.; Bresolin, Michael J.

1986-03-01

Computer technology is rapidly becoming an inseparable part of many health science specialties. Recently, a new area of computer technology, namely Artificial Intelligence, has been applied toward assisting the medical experts in their diagnostic and therapeutic decision making process. MOODIS is an experimental diagnostic expert system which assists Psychiatry specialists in diagnosing human Mood Disorders, better known as Affective Disorders. Its diagnostic methodology is patterned after MDX, a diagnostic expert system developed at LAIR (Laboratory for Artificial Intelligence Research) of Ohio State University. MOODIS is implemented in CSRL (Conceptual Structures Representation Language) also developed at LAIR. This paper describes MOODIS in terms of conceptualization and requirements, and discusses why the MDX approach and CSRL were chosen.

Pencil-and-Paper Neural Networks: An Undergraduate Laboratory Exercise in Computational Neuroscience

PubMed Central

Crisp, Kevin M.; Sutter, Ellen N.; Westerberg, Jacob A.

2015-01-01

Although it has been more than 70 years since McCulloch and Pitts published their seminal work on artificial neural networks, such models remain primarily in the domain of computer science departments in undergraduate education. This is unfortunate, as simple network models offer undergraduate students a much-needed bridge between cellular neurobiology and processes governing thought and behavior. Here, we present a very simple laboratory exercise in which students constructed, trained and tested artificial neural networks by hand on paper. They explored a variety of concepts, including pattern recognition, pattern completion, noise elimination and stimulus ambiguity. Learning gains were evident in changes in the use of language when writing about information processing in the brain. PMID:26557791

Biologically inspired technologies using artificial muscles

NASA Astrophysics Data System (ADS)

Bar-Cohen, Yoseph

2005-01-01

After billions of years of evolution, nature developed inventions that work, which are appropriate for the intended tasks and that last. The evolution of nature led to the introduction of highly effective and power efficient biological mechanisms that are scalable from micron to many meters in size. Imitating these mechanisms offers enormous potentials for the improvement of our life and the tools we use. Humans have always made efforts to imitate nature and we are increasingly reaching levels of advancement where it becomes significantly easier to imitate, copy, and adapt biological methods, processes and systems. Some of the biomimetic technologies that have emerged include artificial muscles, artificial intelligence, and artificial vision to which significant advances in materials science, mechanics, electronics, and computer science have contributed greatly. One of the newest fields of biomimetics is the electroactive polymers (EAP) that are also known as artificial muscles. To take advantage of these materials, efforts are made worldwide to establish a strong infrastructure addressing the need for comprehensive analytical modeling of their operation mechanism and develop effective processing and characterization techniques. The field is still in its emerging state and robust materials are not readily available however in recent years significant progress has been made and commercial products have already started to appear. This paper covers the state-of-the-art and challenges to making artificial muscles and their potential biomimetic applications.

The Teaching and Learning Environment SAIDA: Some Features and Lessons.

ERIC Educational Resources Information Center

Grandbastien, Monique; Morinet-Lambert, Josette

Written in ADA language, SAIDA, a Help System for Data Implementation, is an experimental teaching and learning environment which uses artificial intelligence techniques to teach a computer science course on abstract data representations. The application domain is teaching advanced programming concepts which have not received much attention from…

Educational Assessment Using Intelligent Systems. Research Report. ETS RR-08-68

ERIC Educational Resources Information Center

Shute, Valerie J.; Zapata-Rivera, Diego

2008-01-01

Recent advances in educational assessment, cognitive science, and artificial intelligence have made it possible to integrate valid assessment and instruction in the form of modern computer-based intelligent systems. These intelligent systems leverage assessment information that is gathered from various sources (e.g., summative and formative). This…

Ultra-fast Object Recognition from Few Spikes

DTIC Science & Technology

2005-07-06

Computer Science and Artificial Intelligence Laboratory Ultra-fast Object Recognition from Few Spikes Chou Hung, Gabriel Kreiman , Tomaso Poggio...neural code for different kinds of object-related information. *The authors, Chou Hung and Gabriel Kreiman , contributed equally to this work...Supplementary Material is available at http://ramonycajal.mit.edu/ kreiman /resources/ultrafast

What is the Value of Embedding Artificial Emotional Prosody in Human–Computer Interactions? Implications for Theory and Design in Psychological Science

PubMed Central

Mitchell, Rachel L. C.; Xu, Yi

2015-01-01

In computerized technology, artificial speech is becoming increasingly important, and is already used in ATMs, online gaming and healthcare contexts. However, today’s artificial speech typically sounds monotonous, a main reason for this being the lack of meaningful prosody. One particularly important function of prosody is to convey different emotions. This is because successful encoding and decoding of emotions is vital for effective social cognition, which is increasingly recognized in human–computer interaction contexts. Current attempts to artificially synthesize emotional prosody are much improved relative to early attempts, but there remains much work to be done due to methodological problems, lack of agreed acoustic correlates, and lack of theoretical grounding. If the addition of synthetic emotional prosody is not of sufficient quality, it may risk alienating users instead of enhancing their experience. So the value of embedding emotion cues in artificial speech may ultimately depend on the quality of the synthetic emotional prosody. However, early evidence on reactions to synthesized non-verbal cues in the facial modality bodes well. Attempts to implement the recognition of emotional prosody into artificial applications and interfaces have perhaps been met with greater success, but the ultimate test of synthetic emotional prosody will be to critically compare how people react to synthetic emotional prosody vs. natural emotional prosody, at the behavioral, socio-cognitive and neural levels. PMID:26617563

A conceptual and computational model of moral decision making in human and artificial agents.

PubMed

Wallach, Wendell; Franklin, Stan; Allen, Colin

2010-07-01

Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational models of this kind has created the field of artificial general intelligence (AGI). Moral decision making is arguably one of the most challenging tasks for computational approaches to higher-order cognition. The need for increasingly autonomous artificial agents to factor moral considerations into their choices and actions has given rise to another new field of inquiry variously known as Machine Morality, Machine Ethics, Roboethics, or Friendly AI. In this study, we discuss how LIDA, an AGI model of human cognition, can be adapted to model both affective and rational features of moral decision making. Using the LIDA model, we will demonstrate how moral decisions can be made in many domains using the same mechanisms that enable general decision making. Comprehensive models of human cognition typically aim for compatibility with recent research in the cognitive and neural sciences. Global workspace theory, proposed by the neuropsychologist Bernard Baars (1988), is a highly regarded model of human cognition that is currently being computationally instantiated in several software implementations. LIDA (Franklin, Baars, Ramamurthy, & Ventura, 2005) is one such computational implementation. LIDA is both a set of computational tools and an underlying model of human cognition, which provides mechanisms that are capable of explaining how an agent's selection of its next action arises from bottom-up collection of sensory data and top-down processes for making sense of its current situation. We will describe how the LIDA model helps integrate emotions into the human decision-making process, and we will elucidate a process whereby an agent can work through an ethical problem to reach a solution that takes account of ethically relevant factors. Copyright © 2010 Cognitive Science Society, Inc.

Artificial intelligence in hematology.

PubMed

Zini, Gina

2005-10-01

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

Programs as Causal Models: Speculations on Mental Programs and Mental Representation

ERIC Educational Resources Information Center

Chater, Nick; Oaksford, Mike

2013-01-01

Judea Pearl has argued that counterfactuals and causality are central to intelligence, whether natural or artificial, and has helped create a rich mathematical and computational framework for formally analyzing causality. Here, we draw out connections between these notions and various current issues in cognitive science, including the nature of…

Biomimetic robots using EAP as artificial muscles - progress and challenges

NASA Technical Reports Server (NTRS)

Bar-Cohen, Yoseph

2004-01-01

Biology offers a great model for emulation in areas ranging from tools, computational algorithms, materials science, mechanisms and information technology. In recent years, the field of biomimetics, namely mimicking biology, has blossomed with significant advances enabling the reverse engineering of many animals' functions and implementation of some of these capabilities.

A Functional Programming Approach to AI Search Algorithms

ERIC Educational Resources Information Center

Panovics, Janos

2012-01-01

The theory and practice of search algorithms related to state-space represented problems form the major part of the introductory course of Artificial Intelligence at most of the universities and colleges offering a degree in the area of computer science. Students usually meet these algorithms only in some imperative or object-oriented language…

Capturing Problem-Solving Processes Using Critical Rationalism

ERIC Educational Resources Information Center

Chitpin, Stephanie; Simon, Marielle

2012-01-01

The examination of problem-solving processes continues to be a current research topic in education. Knowing how to solve problems is not only a key aspect of learning mathematics but is also at the heart of cognitive theories, linguistics, artificial intelligence, and computers sciences. Problem solving is a multistep, higher-order cognitive task…

Cognitive biases, linguistic universals, and constraint-based grammar learning.

PubMed

Culbertson, Jennifer; Smolensky, Paul; Wilson, Colin

2013-07-01

According to classical arguments, language learning is both facilitated and constrained by cognitive biases. These biases are reflected in linguistic typology-the distribution of linguistic patterns across the world's languages-and can be probed with artificial grammar experiments on child and adult learners. Beginning with a widely successful approach to typology (Optimality Theory), and adapting techniques from computational approaches to statistical learning, we develop a Bayesian model of cognitive biases and show that it accounts for the detailed pattern of results of artificial grammar experiments on noun-phrase word order (Culbertson, Smolensky, & Legendre, 2012). Our proposal has several novel properties that distinguish it from prior work in the domains of linguistic theory, computational cognitive science, and machine learning. This study illustrates how ideas from these domains can be synthesized into a model of language learning in which biases range in strength from hard (absolute) to soft (statistical), and in which language-specific and domain-general biases combine to account for data from the macro-level scale of typological distribution to the micro-level scale of learning by individuals. Copyright © 2013 Cognitive Science Society, Inc.

Technology 2000, volume 2

NASA Technical Reports Server (NTRS)

1991-01-01

Technology 2000 was the first major industrial conference and exposition spotlighting NASA technology and technology transfer. It's purpose was, and continues to be, to increase awareness of existing NASA-developed technologies that are available for immediate use in the development of new products and processes, and to lay the groundwork for the effective utilization of emerging technologies. Included are sessions on: computer technology and software engineering; human factors engineering and life sciences; materials science; sensors and measurement technology; artificial intelligence; environmental technology; optics and communications; and superconductivity.

Technology 2000, volume 1

NASA Technical Reports Server (NTRS)

1991-01-01

The purpose of the conference was to increase awareness of existing NASA developed technologies that are available for immediate use in the development of new products and processes, and to lay the groundwork for the effective utilization of emerging technologies. There were sessions on the following: Computer technology and software engineering; Human factors engineering and life sciences; Information and data management; Material sciences; Manufacturing and fabrication technology; Power, energy, and control systems; Robotics; Sensors and measurement technology; Artificial intelligence; Environmental technology; Optics and communications; and Superconductivity.

Visualization Techniques in Space and Atmospheric Sciences

NASA Technical Reports Server (NTRS)

Szuszczewicz, E. P. (Editor); Bredekamp, Joseph H. (Editor)

1995-01-01

Unprecedented volumes of data will be generated by research programs that investigate the Earth as a system and the origin of the universe, which will in turn require analysis and interpretation that will lead to meaningful scientific insight. Providing a widely distributed research community with the ability to access, manipulate, analyze, and visualize these complex, multidimensional data sets depends on a wide range of computer science and technology topics. Data storage and compression, data base management, computational methods and algorithms, artificial intelligence, telecommunications, and high-resolution display are just a few of the topics addressed. A unifying theme throughout the papers with regards to advanced data handling and visualization is the need for interactivity, speed, user-friendliness, and extensibility.

Artificial neural networks in evaluation and optimization of modified release solid dosage forms.

PubMed

Ibrić, Svetlana; Djuriš, Jelena; Parojčić, Jelena; Djurić, Zorica

2012-10-18

Implementation of the Quality by Design (QbD) approach in pharmaceutical development has compelled researchers in the pharmaceutical industry to employ Design of Experiments (DoE) as a statistical tool, in product development. Among all DoE techniques, response surface methodology (RSM) is the one most frequently used. Progress of computer science has had an impact on pharmaceutical development as well. Simultaneous with the implementation of statistical methods, machine learning tools took an important place in drug formulation. Twenty years ago, the first papers describing application of artificial neural networks in optimization of modified release products appeared. Since then, a lot of work has been done towards implementation of new techniques, especially Artificial Neural Networks (ANN) in modeling of production, drug release and drug stability of modified release solid dosage forms. The aim of this paper is to review artificial neural networks in evaluation and optimization of modified release solid dosage forms.

Artificial Neural Networks in Evaluation and Optimization of Modified Release Solid Dosage Forms

PubMed Central

Ibrić, Svetlana; Djuriš, Jelena; Parojčić, Jelena; Djurić, Zorica

2012-01-01

Implementation of the Quality by Design (QbD) approach in pharmaceutical development has compelled researchers in the pharmaceutical industry to employ Design of Experiments (DoE) as a statistical tool, in product development. Among all DoE techniques, response surface methodology (RSM) is the one most frequently used. Progress of computer science has had an impact on pharmaceutical development as well. Simultaneous with the implementation of statistical methods, machine learning tools took an important place in drug formulation. Twenty years ago, the first papers describing application of artificial neural networks in optimization of modified release products appeared. Since then, a lot of work has been done towards implementation of new techniques, especially Artificial Neural Networks (ANN) in modeling of production, drug release and drug stability of modified release solid dosage forms. The aim of this paper is to review artificial neural networks in evaluation and optimization of modified release solid dosage forms. PMID:24300369

Expert systems research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duda, R.O.; Shortliffe, E.H.

1983-04-15

Artificial intelligence, long a topic of basic computer science research, is now being applied to problems of scientific, technical, and commercial interest. Some consultation programs although limited in versatility, have achieved levels of performance rivaling those of human experts. A collateral benefit of this work is the systematization of previously unformalized knowledge in areas such as medical diagnosis and geology. 30 references.

Human-Computer Interaction: A Journal of Theoretical, Empirical and Methodological Issues of User Science and of System Design. Volume 7, Number 1

DTIC Science & Technology

1992-01-01

Norman .................................... University of California, San Diego, CA Dan R . Olsen, Jr ........................................ Brigham...Peter G. Poison .............................................. University of Colorado, Boulder, CO James R . Rhyne ................. IBM T J Watson...and artificial intelligence, among which are: * reasoning about concurrent systems, including program verification ( Barringer , 1985), operating

An Object-Oriented Software Reuse Tool

DTIC Science & Technology

1989-04-01

Square Cambridge, MA 02139 I. CONTROLLING OFFICE NAME ANO ADDRESS 12. REPORT DATIE Advanced Research Projects Agency April 1989 1400 Wilson Blvd. IS...Office of Naval Research UNCLASSIFIED Information Systems Arlington, VA 22217 1s,. DECLASSIFICATION/DOWNGRAOINGSCHEDUL.E 6. O:STRIILJTION STATEMENT (of...DISTRIBUTION: Defense Technical Information Center Computer Sciences Division ONR, Code 1133 Navy Center for Applied Research in Artificial

Analytical Cost Metrics : Days of Future Past

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prajapati, Nirmal; Rajopadhye, Sanjay; Djidjev, Hristo Nikolov

As we move towards the exascale era, the new architectures must be capable of running the massive computational problems efficiently. Scientists and researchers are continuously investing in tuning the performance of extreme-scale computational problems. These problems arise in almost all areas of computing, ranging from big data analytics, artificial intelligence, search, machine learning, virtual/augmented reality, computer vision, image/signal processing to computational science and bioinformatics. With Moore’s law driving the evolution of hardware platforms towards exascale, the dominant performance metric (time efficiency) has now expanded to also incorporate power/energy efficiency. Therefore the major challenge that we face in computing systems researchmore » is: “how to solve massive-scale computational problems in the most time/power/energy efficient manner?”« less

Gesture Analysis for Astronomy Presentation Software

NASA Astrophysics Data System (ADS)

Robinson, Marc A.

Astronomy presentation software in a planetarium setting provides a visually stimulating way to introduce varied scientific concepts, including computer science concepts, to a wide audience. However, the underlying computational complexity and opportunities for discussion are often overshadowed by the brilliance of the presentation itself. To bring this discussion back out into the open, a method needs to be developed to make the computer science applications more visible. This thesis introduces the GAAPS system, which endeavors to implement free-hand gesture-based control of astronomy presentation software, with the goal of providing that talking point to begin the discussion of computer science concepts in a planetarium setting. The GAAPS system incorporates gesture capture and analysis in a unique environment presenting unique challenges, and introduces a novel algorithm called a Bounding Box Tree to create and select features for this particular gesture data. This thesis also analyzes several different machine learning techniques to determine a well-suited technique for the classification of this particular data set, with an artificial neural network being chosen as the implemented algorithm. The results of this work will allow for the desired introduction of computer science discussion into the specific setting used, as well as provide for future work pertaining to gesture recognition with astronomy presentation software.

P ≠NP Millenium-Problem(MP) TRIVIAL Physics Proof Via NATURAL TRUMPS Artificial-``Intelligence'' Via: Euclid Geometry, Plato Forms, Aristotle Square-of-Opposition, Menger Dimension-Theory Connections!!! NO Computational-Complexity(CC)/ANYthing!!!: Geometry!!!

NASA Astrophysics Data System (ADS)

Clay, London; Menger, Karl; Rota, Gian-Carlo; Euclid, Alexandria; Siegel, Edward

P ≠NP MP proof is by computer-''science''/SEANCE(!!!)(CS) computational-''intelligence'' lingo jargonial-obfuscation(JO) NATURAL-Intelligence(NI) DISambiguation! CS P =(?) =NP MEANS (Deterministic)(PC) = (?) =(Non-D)(PC) i.e. D(P) =(?) = N(P). For inclusion(equality) vs. exclusion (inequality) irrelevant (P) simply cancels!!! (Equally any/all other CCs IF both sides identical). Crucial question left: (D) =(?) =(ND), i.e. D =(?) = N. Algorithmics[Sipser[Intro. Thy.Comp.(`97)-p.49Fig.1.15!!!

Artificial Intelligence in Medical Practice: The Question to the Answer?

PubMed

Miller, D Douglas; Brown, Eric W

2018-02-01

Computer science advances and ultra-fast computing speeds find artificial intelligence (AI) broadly benefitting modern society-forecasting weather, recognizing faces, detecting fraud, and deciphering genomics. AI's future role in medical practice remains an unanswered question. Machines (computers) learn to detect patterns not decipherable using biostatistics by processing massive datasets (big data) through layered mathematical models (algorithms). Correcting algorithm mistakes (training) adds to AI predictive model confidence. AI is being successfully applied for image analysis in radiology, pathology, and dermatology, with diagnostic speed exceeding, and accuracy paralleling, medical experts. While diagnostic confidence never reaches 100%, combining machines plus physicians reliably enhances system performance. Cognitive programs are impacting medical practice by applying natural language processing to read the rapidly expanding scientific literature and collate years of diverse electronic medical records. In this and other ways, AI may optimize the care trajectory of chronic disease patients, suggest precision therapies for complex illnesses, reduce medical errors, and improve subject enrollment into clinical trials. Copyright © 2018 Elsevier Inc. All rights reserved.

Identifying Key Features, Cutting Edge Cloud Resources, and Artificial Intelligence Tools to Achieve User-Friendly Water Science in the Cloud

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2017-12-01

Decision making for groundwater systems is becoming increasingly important, as shifting water demands increasingly impact aquifers. As buffer systems, aquifers provide room for resilient responses and augment the actual timeframe for hydrological response. Yet the pace impacts, climate shifts, and degradation of water resources is accelerating. To meet these new drivers, groundwater science is transitioning toward the emerging field of Integrated Water Resources Management, or IWRM. IWRM incorporates a broad array of dimensions, methods, and tools to address problems that tend to be complex. Computational tools and accessible cyberinfrastructure (CI) are needed to cross the chasm between science and society. Fortunately cloud computing environments, such as the new Jetstream system, are evolving rapidly. While still targeting scientific user groups systems such as, Jetstream, offer configurable cyberinfrastructure to enable interactive computing and data analysis resources on demand. The web-based interfaces allow researchers to rapidly customize virtual machines, modify computing architecture and increase the usability and access for broader audiences to advanced compute environments. The result enables dexterous configurations and opening up opportunities for IWRM modelers to expand the reach of analyses, number of case studies, and quality of engagement with stakeholders and decision makers. The acute need to identify improved IWRM solutions paired with advanced computational resources refocuses the attention of IWRM researchers on applications, workflows, and intelligent systems that are capable of accelerating progress. IWRM must address key drivers of community concern, implement transdisciplinary methodologies, adapt and apply decision support tools in order to effectively support decisions about groundwater resource management. This presentation will provide an overview of advanced computing services in the cloud using integrated groundwater management case studies to highlight how Cloud CI streamlines the process for setting up an interactive decision support system. Moreover, advances in artificial intelligence offer new techniques for old problems from integrating data to adaptive sensing or from interactive dashboards to optimizing multi-attribute problems. The combination of scientific expertise, flexible cloud computing solutions, and intelligent systems opens new research horizons.

Computer Simulated Visual and Tactile Feedback as an Aid to Manipulator and Vehicle Control,

DTIC Science & Technology

1981-05-08

STATEMENT ........................ 8 Artificial Intellegence Versus Supervisory Control ....... 8 Computer Generation of Operator Feedback...operator. Artificial Intelligence Versus Supervisory Control The use of computers to aid human operators can be divided into two catagories: artificial ...operator. Artificial intelligence ( A. I. ) attempts to give the computer maximum intelligence and to replace all operator functions by the computer

Artificial intelligence. Fears of an AI pioneer.

PubMed

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.

Study on digital teeth selection and virtual teeth arrangement for complete denture.

PubMed

Yu, Xiaoling; Cheng, Xiaosheng; Dai, Ning; Chen, Hu; Yu, Changjiang; Sun, Yuchun

2018-03-01

In dentistry, the complete denture is a conventional treatment for edentulous patients. The computer-aided design and computer-aided manufacturing (CAD/CAM) has been applied on the digital complete denture which is developed rapidly. Tooth selection and arrangement is one of the most important parts in digital complete denture. In this paper, we propose a new method of personalized teeth arrangement. This paper presents a method of arranging teeth virtually for a complete denture. First, scan and extract the feature points of the 3D triangular mesh data of artificial teeth (PLY format), then establish a tooth selection system. Second, scan and mark the anatomic characteristics of the maxillary and mandibular cast surfaces, such as facial midline, the curve of the arches. With the enter information, the study calculates the common arrangement lines of artificial teeth. Third, select the preferred artificial teeth and automatically arrange them virtually in the correct position by using our own software. After that, design the gingival part of the dentures on the basic of the arranged teeth on the screen and then fabricated it by using Computerized Numerical Control (CNC) technology, Rapid Prototyping (RP) technology or 3D printer technology. Finally, select artificial teeth were embedded in wax rims. This system can choose artificial teeth reasonably and the teeth placement can meet the dentist's request to a certain extent, whereas all the operations are based on the medical principles. The study performed here involves computer sciences, medicine, and dentistry, a teeth selection system was proposed and virtual teeth arrangement was described. This study has the capacity of helping operators to select teeth, which improved the accuracy of tooth arrangement, and customized complete denture. Copyright © 2017 Elsevier B.V. All rights reserved.

Computer-aided Human Centric Cyber Situation Awareness

DTIC Science & Technology

2016-03-20

in Video, IJCAI: International Joint Conf. on Artificial Intelligence . 16-JUL-11, . : , Kun Sun, Sushil Jajodia, Jason Li, Yi Cheng, Wei Tang...Cyber-Security Conference, June 2015. 2. V.S. Subrahmanian, Invited Speaker, Summer School on Business Intelligence and Big Data Analysis, Capri, Italy... Cybersecurity Conference, Yuval Ne’eman Workshop for Science, Technology and Security, Tel Aviv University, the Israeli National Cyber Bureau, Prime

Artificial intelligence and robotics in high throughput post-genomics.

PubMed

Laghaee, Aroosha; Malcolm, Chris; Hallam, John; Ghazal, Peter

2005-09-15

The shift of post-genomics towards a systems approach has offered an ever-increasing role for artificial intelligence (AI) and robotics. Many disciplines (e.g. engineering, robotics, computer science) bear on the problem of automating the different stages involved in post-genomic research with a view to developing quality assured high-dimensional data. We review some of the latest contributions of AI and robotics to this end and note the limitations arising from the current independent, exploratory way in which specific solutions are being presented for specific problems without regard to how these could be eventually integrated into one comprehensible integrated intelligent system.

Artificial neural networks in biology and chemistry: the evolution of a new analytical tool.

PubMed

Cartwright, Hugh M

2008-01-01

Once regarded as an eccentric and unpromising algorithm for the analysis of scientific data, the neural network has been developed in the last decade into a powerful computational tool. Its use now spans all areas of science, from the physical sciences and engineering to the life sciences and allied subjects. Applications range from the assessment of epidemiological data or the deconvolution of spectra to highly practical applications, such as the electronic nose. This introductory chapter considers briefly the growth in the use of neural networks and provides some general background in preparation for the more detailed chapters that follow.

The Biological Relevance of Artificial Life: Lessons from Artificial Intelligence

NASA Technical Reports Server (NTRS)

Colombano, Silvano

2000-01-01

There is no fundamental reason why A-life couldn't simply be a branch of computer science that deals with algorithms that are inspired by, or emulate biological phenomena. However, if these are the limits we place on this field, we miss the opportunity to help advance Theoretical Biology and to contribute to a deeper understanding of the nature of life. The history of Artificial Intelligence provides a good example, in that early interest in the nature of cognition quickly was lost to the process of building tools, such as "expert systems" that, were certainly useful, but provided little insight in the nature of cognition. Based on this lesson, I will discuss criteria for increasing the biological relevance of A-life and the probability that this field may provide a theoretical foundation for Biology.

Artificial astrocytes improve neural network performance.

PubMed

Porto-Pazos, Ana B; Veiguela, Noha; Mesejo, Pablo; Navarrete, Marta; Alvarellos, Alberto; Ibáñez, Oscar; Pazos, Alejandro; Araque, Alfonso

2011-04-19

Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN) and artificial neuron-glia networks (NGN) to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function.

Artificial Astrocytes Improve Neural Network Performance

PubMed Central

Porto-Pazos, Ana B.; Veiguela, Noha; Mesejo, Pablo; Navarrete, Marta; Alvarellos, Alberto; Ibáñez, Oscar; Pazos, Alejandro; Araque, Alfonso

2011-01-01

Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN) and artificial neuron-glia networks (NGN) to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function. PMID:21526157

Situation resolution with context-sensitive fuzzy relations

NASA Astrophysics Data System (ADS)

Jakobson, Gabriel; Buford, John; Lewis, Lundy

2009-05-01

Context plays a significant role in situation resolution by intelligent agents (human or machine) by affecting how the situations are recognized, interpreted, acted upon or predicted. Many definitions and formalisms for the notion of context have emerged in various research fields including psychology, economics and computer science (computational linguistics, data management, control theory, artificial intelligence and others). In this paper we examine the role of context in situation management, particularly how to resolve situations that are described by using fuzzy (inexact) relations among their components. We propose a language for describing context sensitive inexact constraints and an algorithm for interpreting relations using inexact (fuzzy) computations.

Report of Defense Science Board Task Force on Industry-to-Industry International Armaments Cooperation. Phase II. Japan

DTIC Science & Technology

1984-06-01

TEMPERATURE MAT’LS IMAGE RECOGNITION ROCKET PROPULSION SPEECH RECOGNITION/TRANSLATION COMPUTER-AIDED DESIGN ARTIFICIAL INTELLIGENCE PRODUCTION TECHNOLOGY...planning, intelligence exchange, and logistics. While not called out in the Guidelines, any further standardization in equipments and interoperability...COST AND TIME THAN DEVELCPING THEM -ESTABLISHMENT OF PRODUCTIVE LONG-TERM BUSINESS RELATIONSH IPS WITH JAPANESE COMPAN IES * PROBLEM -POSSIBILITY OF

Reflections on Heckman and Pinto’s Causal Analysis After Haavelmo

DTIC Science & Technology

2013-11-01

Econometric Analysis , Cambridge University Press, 477–490, 1995. Halpern, J. (1998). Axiomatizing causal reasoning. In Uncertainty in Artificial...Models, Structural Models and Econometric Policy Evaluation. Elsevier B.V., Amsterdam, 4779–4874. Heckman, J. J. (1979). Sample selection bias as a...Reflections on Heckman and Pinto’s “Causal Analysis After Haavelmo” Judea Pearl University of California, Los Angeles Computer Science Department Los

Active Learning with Statistical Models.

DTIC Science & Technology

1995-01-01

Active Learning with Statistical Models ASC-9217041, NSF CDA-9309300 6. AUTHOR(S) David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan 7. PERFORMING...TERMS 15. NUMBER OF PAGES Al, MIT, Artificial Intelligence, active learning , queries, locally weighted 6 regression, LOESS, mixtures of gaussians...COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES A.I. Memo No. 1522 January 9. 1995 C.B.C.L. Paper No. 110 Active Learning with

Arguing Artificially: A Rhetorical Analysis of the Debates That Have Shaped Cognitive Science.

ERIC Educational Resources Information Center

Gibson, Keith

2003-01-01

Attempts a rhetorical analysis of the history of artificial intelligence research. Responds to scholarly needs in three areas: the rhetorical nature of science, the social construction of science knowledge, and the rhetorical strategies used in artificial intelligence (AI). Suggests that this work can help rhetoricians more accurately describe the…

[The Durkheim Test. Remarks on Susan Leigh Star's Boundary Objects].

PubMed

Gießmann, Sebastian

2015-09-01

The article reconstructs Susan Leigh Star's conceptual work on the notion of 'boundary objects'. It traces the emergence of the concept, beginning with her PhD thesis and its publication as Regions of the Mind in 1989. 'Boundary objects' attempt to represent the distributed, multifold nature of scientific work and its mediations between different 'social worlds'. Being addressed to several 'communities of practice', the term responded to questions from Distributed Artificial Intelligence in Computer Science, Workplace Studies and Computer Supported Cooperative Work (CSCW), and microhistorical approaches inside the growing Science and Technology Studies. Yet the interdisciplinary character and interpretive flexibility of Star’s invention has rarely been noticed as a conceptual tool for media theory. I therefore propose to reconsider Star's 'Durkheim test' for sociotechnical media practices.

Quantum Machine Learning

NASA Technical Reports Server (NTRS)

Biswas, Rupak

2018-01-01

Quantum computing promises an unprecedented ability to solve intractable problems by harnessing quantum mechanical effects such as tunneling, superposition, and entanglement. The Quantum Artificial Intelligence Laboratory (QuAIL) at NASA Ames Research Center is the space agency's primary facility for conducting research and development in quantum information sciences. QuAIL conducts fundamental research in quantum physics but also explores how best to exploit and apply this disruptive technology to enable NASA missions in aeronautics, Earth and space sciences, and space exploration. At the same time, machine learning has become a major focus in computer science and captured the imagination of the public as a panacea to myriad big data problems. In this talk, we will discuss how classical machine learning can take advantage of quantum computing to significantly improve its effectiveness. Although we illustrate this concept on a quantum annealer, other quantum platforms could be used as well. If explored fully and implemented efficiently, quantum machine learning could greatly accelerate a wide range of tasks leading to new technologies and discoveries that will significantly change the way we solve real-world problems.

DeepStack: Expert-level artificial intelligence in heads-up no-limit poker.

PubMed

Moravčík, Matej; Schmid, Martin; Burch, Neil; Lisý, Viliam; Morrill, Dustin; Bard, Nolan; Davis, Trevor; Waugh, Kevin; Johanson, Michael; Bowling, Michael

2017-05-05

Artificial intelligence has seen several breakthroughs in recent years, with games often serving as milestones. A common feature of these games is that players have perfect information. Poker, the quintessential game of imperfect information, is a long-standing challenge problem in artificial intelligence. We introduce DeepStack, an algorithm for imperfect-information settings. It combines recursive reasoning to handle information asymmetry, decomposition to focus computation on the relevant decision, and a form of intuition that is automatically learned from self-play using deep learning. In a study involving 44,000 hands of poker, DeepStack defeated, with statistical significance, professional poker players in heads-up no-limit Texas hold'em. The approach is theoretically sound and is shown to produce strategies that are more difficult to exploit than prior approaches. Copyright © 2017, American Association for the Advancement of Science.

Autonomous Driver Based on an Intelligent System of Decision-Making.

PubMed

Czubenko, Michał; Kowalczuk, Zdzisław; Ordys, Andrew

The paper presents and discusses a system ( xDriver ) which uses an Intelligent System of Decision-making (ISD) for the task of car driving. The principal subject is the implementation, simulation and testing of the ISD system described earlier in our publications (Kowalczuk and Czubenko in artificial intelligence and soft computing lecture notes in computer science, lecture notes in artificial intelligence, Springer, Berlin, 2010, 2010, In Int J Appl Math Comput Sci 21(4):621-635, 2011, In Pomiary Autom Robot 2(17):60-5, 2013) for the task of autonomous driving. The design of the whole ISD system is a result of a thorough modelling of human psychology based on an extensive literature study. Concepts somehow similar to the ISD system can be found in the literature (Muhlestein in Cognit Comput 5(1):99-105, 2012; Wiggins in Cognit Comput 4(3):306-319, 2012), but there are no reports of a system which would model the human psychology for the purpose of autonomously driving a car. The paper describes assumptions for simulation, the set of needs and reactions (characterizing the ISD system), the road model and the vehicle model, as well as presents some results of simulation. It proves that the xDriver system may behave on the road as a very inexperienced driver.

Computed Flow Through An Artificial Heart And Valve

NASA Technical Reports Server (NTRS)

Rogers, Stuart E.; Kwak, Dochan; Kiris, Cetin; Chang, I-Dee

1994-01-01

NASA technical memorandum discusses computations of flow of blood through artificial heart and through tilting-disk artificial heart valve. Represents further progress in research described in "Numerical Simulation of Flow Through an Artificial Heart" (ARC-12478). One purpose of research to exploit advanced techniques of computational fluid dynamics and capabilities of supercomputers to gain understanding of complicated internal flows of viscous, essentially incompressible fluids like blood. Another to use understanding to design better artificial hearts and valves.

Use of Computational Functional Genomics in Drug Discovery and Repurposing for Analgesic Indications.

PubMed

Lötsch, Jörn; Kringel, Dario

2018-06-01

The novel research area of functional genomics investigates biochemical, cellular, or physiological properties of gene products with the goal of understanding the relationship between the genome and the phenotype. These developments have made analgesic drug research a data-rich discipline mastered only by making use of parallel developments in computer science, including the establishment of knowledge bases, mining methods for big data, machine-learning, and artificial intelligence, (Table ) which will be exemplarily introduced in the following. © 2018 The Authors Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Artificial Intelligence and Computer Assisted Instruction. CITE Report No. 4.

ERIC Educational Resources Information Center

Elsom-Cook, Mark

The purpose of the paper is to outline some of the major ways in which artificial intelligence research and techniques can affect usage of computers in an educational environment. The role of artificial intelligence is defined, and the difference between Computer Aided Instruction (CAI) and Intelligent Computer Aided Instruction (ICAI) is…

Importance of nonverbal expression to the emergence of emotive artificial intelligence systems

NASA Astrophysics Data System (ADS)

Pioggia, Giovanni; Hanson, David; Dinelli, Serena; Di Francesco, Fabio; Francesconi, R.; De Rossi, Danilo

2002-07-01

The nonverbal expression of the emotions, especially in the human face, has rapidly become an area of intense interest in computer science and robotics. Exploring the emotions as a link between external events and behavioural responses, artificial intelligence designers and psychologists are approaching a theoretical understanding of foundational principles which will be key to the physical embodiment of artificial intelligence. In fact, it has been well demonstrated that many important aspects of intelligence are grounded in intimate communication with the physical world- so-called embodied intelligence . It follows naturally, then, that recent advances in emotive artificial intelligence show clear and undeniable broadening in the capacities of biologically-inspired robots to survive and thrive in a social environment. The means by which AI may express its foundling emotions are clearly integral to such capacities. In effect: powerful facial expressions are critical to the development of intelligent, sociable robots. Following discussion the importance of the nonverbal expression of emotions in humans and robots, this paper describes methods used in robotically emulating nonverbal expressions using human-like robotic faces. Furthermore, it describes the potentially revolutionary impact of electroactive polymer (EAP) actuators as artificial muscles for such robotic devices.

What is data ethics?

PubMed

Floridi, Luciano; Taddeo, Mariarosaria

2016-12-28

This theme issue has the founding ambition of landscaping data ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data ethics builds on the foundation provided by computer and information ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the level of abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations-the interactions among hardware, software and data-rather than on the variety of digital technologies that enable them. And it emphasizes the complexity of the ethical challenges posed by data science. Because of such complexity, data ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of data science and its applications within a consistent, holistic and inclusive framework. Only as a macroethics will data ethics provide solutions that can maximize the value of data science for our societies, for all of us and for our environments.This article is part of the themed issue 'The ethical impact of data science'. © 2016 The Author(s).

The Future Medical Science and Colorectal Surgeons

PubMed Central

2017-01-01

Future medical technology breakthroughs will build from the incredible progress made in computers, biotechnology, and nanotechnology and from the information learned from the human genome. With such technology and information, computer-aided diagnoses, organ replacement, gene therapy, personalized drugs, and even age reversal will become possible. True 3-dimensional system technology will enable surgeons to envision key clinical features and will help them in planning complex surgery. Surgeons will enter surgical instructions in a virtual space from a remote medical center, order a medical robot to perform the operation, and review the operation in real time on a monitor. Surgeons will be better than artificial intelligence or automated robots when surgeons (or we) love patients and ask questions for a better future. The purpose of this paper is looking at the future medical science and the changes of colorectal surgeons. PMID:29354602

The Future Medical Science and Colorectal Surgeons.

PubMed

Kim, Young Jin

2017-12-01

Future medical technology breakthroughs will build from the incredible progress made in computers, biotechnology, and nanotechnology and from the information learned from the human genome. With such technology and information, computer-aided diagnoses, organ replacement, gene therapy, personalized drugs, and even age reversal will become possible. True 3-dimensional system technology will enable surgeons to envision key clinical features and will help them in planning complex surgery. Surgeons will enter surgical instructions in a virtual space from a remote medical center, order a medical robot to perform the operation, and review the operation in real time on a monitor. Surgeons will be better than artificial intelligence or automated robots when surgeons (or we) love patients and ask questions for a better future. The purpose of this paper is looking at the future medical science and the changes of colorectal surgeons.

Artificial Neural Network Metamodels of Stochastic Computer Simulations

DTIC Science & Technology

1994-08-10

SUBTITLE r 5. FUNDING NUMBERS Artificial Neural Network Metamodels of Stochastic I () Computer Simulations 6. AUTHOR(S) AD- A285 951 Robert Allen...8217!298*1C2 ARTIFICIAL NEURAL NETWORK METAMODELS OF STOCHASTIC COMPUTER SIMULATIONS by Robert Allen Kilmer B.S. in Education Mathematics, Indiana...dedicate this document to the memory of my father, William Ralph Kilmer. mi ABSTRACT Signature ARTIFICIAL NEURAL NETWORK METAMODELS OF STOCHASTIC

Image steganalysis using Artificial Bee Colony algorithm

NASA Astrophysics Data System (ADS)

Sajedi, Hedieh

2017-09-01

Steganography is the science of secure communication where the presence of the communication cannot be detected while steganalysis is the art of discovering the existence of the secret communication. Processing a huge amount of information takes extensive execution time and computational sources most of the time. As a result, it is needed to employ a phase of preprocessing, which can moderate the execution time and computational sources. In this paper, we propose a new feature-based blind steganalysis method for detecting stego images from the cover (clean) images with JPEG format. In this regard, we present a feature selection technique based on an improved Artificial Bee Colony (ABC). ABC algorithm is inspired by honeybees' social behaviour in their search for perfect food sources. In the proposed method, classifier performance and the dimension of the selected feature vector depend on using wrapper-based methods. The experiments are performed using two large data-sets of JPEG images. Experimental results demonstrate the effectiveness of the proposed steganalysis technique compared to the other existing techniques.

"Artificial humans": Psychology and neuroscience perspectives on embodiment and nonverbal communication.

PubMed

Vogeley, Kai; Bente, Gary

2010-01-01

"Artificial humans", so-called "Embodied Conversational Agents" and humanoid robots, are assumed to facilitate human-technology interaction referring to the unique human capacities of interpersonal communication and social information processing. While early research and development in artificial intelligence (AI) focused on processing and production of natural language, the "new AI" has also taken into account the emotional and relational aspects of communication with an emphasis both on understanding and production of nonverbal behavior. This shift in attention in computer science and engineering is reflected in recent developments in psychology and social cognitive neuroscience. This article addresses key challenges which emerge from the goal to equip machines with socio-emotional intelligence and to enable them to interpret subtle nonverbal cues and to respond to social affordances with naturally appearing behavior from both perspectives. In particular, we propose that the creation of credible artificial humans not only defines the ultimate test for our understanding of human communication and social cognition but also provides a unique research tool to improve our knowledge about the underlying psychological processes and neural mechanisms. Copyright © 2010. Published by Elsevier Ltd.

Mask Matching for Linear Feature Detection.

DTIC Science & Technology

1987-01-01

decide which matched masks are part of a linear feature by sim- ple thresholding of the confidence measures. However, it is shown in a compan - ion report...Laboratory, Center for Automation Research, University of Maryland, January 1987. 3. E.M. Allen, R.H. Trigg, and R.J. Wood, The Maryland Artificial ... Intelligence Group Franz Lisp Environment, Variation 3.5, TR-1226, Department of Computer Science, University of Maryland, December 1984. 4. D.E. Knuth, The

An Interrogative Model of Computer-Aided Adaptive Testing: Some Experimental Evidence

DTIC Science & Technology

1988-09-01

Ahilitfas 2 Final 3g zj, research report, Office of Naval Research, Arlington, VA, June 1986. Brovn, 3. S. and Harris, a., " Artificial Intelligence and...Building an Intellegent Tutoring System," in Methods and Tactics in Cggnitive Science (Rds. Kintsch, Miller, and Poison), Lavrence Zrlbaum Associates...Education, Washington, DC, November 1984. 89 -7- In SIvasankaran, T. R. and Bul, Tung X., "A Bayesian Diagnostic Model for Intellegent CAI Systems

Soar: An Architecture for General Intelligence

DTIC Science & Technology

1987-09-29

procedure". Artifcial Intelligence 12 (1979). 201-214. 6. Boggs M. & Carbonell. J. A Tutorial Introduction to DYPAR-1. Computer Science Department...P Tf 1 F COPY SOAR: AN ARCHITECTURE FOR0 GENERAL INTELLIGENCE OTechnical Report AIP-9 0[ John E. Laird, Allen Newell and Paul S. Rosenbloom...University of Michigan . 0 j Carnegie-Mellon University Stanford University The Artificial Intelligence and Psychology r Project DTJC S ELEC TEN;it* EC 2 9 1

Northeast Artificial Intelligence Consortium (NAIC). Volume 12. Computer Architecture for Very Large Knowledge Bases

DTIC Science & Technology

1990-12-01

data rate to the electronics would be much lower on the average and the data much "richer" in information. Intelligent use of...system bottleneck, a high data rate should be provided by I/O systems. 2. machines with intelligent storage management specially designed for logic...management information processing, surveillance sensors, intelligence data collection and handling, solid state sciences, electromagnetics, and propagation, and electronic reliability/maintainability and compatibility.

Computed Flow Through An Artificial Heart Valve

NASA Technical Reports Server (NTRS)

Rogers, Stewart E.; Kwak, Dochan; Kiris, Cetin; Chang, I-Dee

1994-01-01

Report discusses computations of blood flow through prosthetic tilting disk valve. Computational procedure developed in simulation used to design better artificial hearts and valves by reducing or eliminating following adverse flow characteristics: large pressure losses, which prevent hearts from working efficiently; separated and secondary flows, which causes clotting; and high turbulent shear stresses, which damages red blood cells. Report reiterates and expands upon part of NASA technical memorandum "Computed Flow Through an Artificial Heart and Valve" (ARC-12983). Also based partly on research described in "Numerical Simulation of Flow Through an Artificial Heart" (ARC-12478).

Artificial Intelligence in Sports Biomechanics: New Dawn or False Hope?

PubMed Central

Bartlett, Roger

2006-01-01

This article reviews developments in the use of Artificial Intelligence (AI) in sports biomechanics over the last decade. It outlines possible uses of Expert Systems as diagnostic tools for evaluating faults in sports movements (‘techniques’) and presents some example knowledge rules for such an expert system. It then compares the analysis of sports techniques, in which Expert Systems have found little place to date, with gait analysis, in which they are routinely used. Consideration is then given to the use of Artificial Neural Networks (ANNs) in sports biomechanics, focusing on Kohonen self-organizing maps, which have been the most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of ANNs in sports biomechanics are presented for javelin and discus throwing, shot putting and football kicking. I also present an example of the use of Evolutionary Computation in movement optimization in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. After briefly overviewing the use of AI in both sports science and biomechanics in general, the article concludes with some speculations about future uses of AI in sports biomechanics. Key Points Expert Systems remain almost unused in sports biomechanics, unlike in the similar discipline of gait analysis. Artificial Neural Networks, particularly Kohonen Maps, have been used, although their full value remains unclear. Other AI applications, including Evolutionary Computation, have received little attention. PMID:24357939

Artificial intelligence in sports biomechanics: new dawn or false hope?

PubMed

Bartlett, Roger

2006-12-15

This article reviews developments in the use of Artificial Intelligence (AI) in sports biomechanics over the last decade. It outlines possible uses of Expert Systems as diagnostic tools for evaluating faults in sports movements ('techniques') and presents some example knowledge rules for such an expert system. It then compares the analysis of sports techniques, in which Expert Systems have found little place to date, with gait analysis, in which they are routinely used. Consideration is then given to the use of Artificial Neural Networks (ANNs) in sports biomechanics, focusing on Kohonen self-organizing maps, which have been the most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of ANNs in sports biomechanics are presented for javelin and discus throwing, shot putting and football kicking. I also present an example of the use of Evolutionary Computation in movement optimization in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. After briefly overviewing the use of AI in both sports science and biomechanics in general, the article concludes with some speculations about future uses of AI in sports biomechanics. Key PointsExpert Systems remain almost unused in sports biomechanics, unlike in the similar discipline of gait analysis.Artificial Neural Networks, particularly Kohonen Maps, have been used, although their full value remains unclear.Other AI applications, including Evolutionary Computation, have received little attention.

Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network.

PubMed

Goto, Hayato

2016-02-22

The dynamics of nonlinear systems qualitatively change depending on their parameters, which is called bifurcation. A quantum-mechanical nonlinear oscillator can yield a quantum superposition of two oscillation states, known as a Schrödinger cat state, via quantum adiabatic evolution through its bifurcation point. Here we propose a quantum computer comprising such quantum nonlinear oscillators, instead of quantum bits, to solve hard combinatorial optimization problems. The nonlinear oscillator network finds optimal solutions via quantum adiabatic evolution, where nonlinear terms are increased slowly, in contrast to conventional adiabatic quantum computation or quantum annealing, where quantum fluctuation terms are decreased slowly. As a result of numerical simulations, it is concluded that quantum superposition and quantum fluctuation work effectively to find optimal solutions. It is also notable that the present computer is analogous to neural computers, which are also networks of nonlinear components. Thus, the present scheme will open new possibilities for quantum computation, nonlinear science, and artificial intelligence.

Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network

NASA Astrophysics Data System (ADS)

Goto, Hayato

2016-02-01

The dynamics of nonlinear systems qualitatively change depending on their parameters, which is called bifurcation. A quantum-mechanical nonlinear oscillator can yield a quantum superposition of two oscillation states, known as a Schrödinger cat state, via quantum adiabatic evolution through its bifurcation point. Here we propose a quantum computer comprising such quantum nonlinear oscillators, instead of quantum bits, to solve hard combinatorial optimization problems. The nonlinear oscillator network finds optimal solutions via quantum adiabatic evolution, where nonlinear terms are increased slowly, in contrast to conventional adiabatic quantum computation or quantum annealing, where quantum fluctuation terms are decreased slowly. As a result of numerical simulations, it is concluded that quantum superposition and quantum fluctuation work effectively to find optimal solutions. It is also notable that the present computer is analogous to neural computers, which are also networks of nonlinear components. Thus, the present scheme will open new possibilities for quantum computation, nonlinear science, and artificial intelligence.

Artificial Intelligence in Surgery: Promises and Perils.

PubMed

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.

Role of Artificial Intelligence Techniques (Automatic Classifiers) in Molecular Imaging Modalities in Neurodegenerative Diseases.

PubMed

Cascianelli, Silvia; Scialpi, Michele; Amici, Serena; Forini, Nevio; Minestrini, Matteo; Fravolini, Mario Luca; Sinzinger, Helmut; Schillaci, Orazio; Palumbo, Barbara

2017-01-01

Artificial Intelligence (AI) is a very active Computer Science research field aiming to develop systems that mimic human intelligence and is helpful in many human activities, including Medicine. In this review we presented some examples of the exploiting of AI techniques, in particular automatic classifiers such as Artificial Neural Network (ANN), Support Vector Machine (SVM), Classification Tree (ClT) and ensemble methods like Random Forest (RF), able to analyze findings obtained by positron emission tomography (PET) or single-photon emission tomography (SPECT) scans of patients with Neurodegenerative Diseases, in particular Alzheimer's Disease. We also focused our attention on techniques applied in order to preprocess data and reduce their dimensionality via feature selection or projection in a more representative domain (Principal Component Analysis - PCA - or Partial Least Squares - PLS - are examples of such methods); this is a crucial step while dealing with medical data, since it is necessary to compress patient information and retain only the most useful in order to discriminate subjects into normal and pathological classes. Main literature papers on the application of these techniques to classify patients with neurodegenerative disease extracting data from molecular imaging modalities are reported, showing that the increasing development of computer aided diagnosis systems is very promising to contribute to the diagnostic process.

Social energy: mining energy from the society

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Jun Jason; Gao, David Wenzhong; Zhang, Yingchen

The inherent nature of energy, i.e., physicality, sociality and informatization, implies the inevitable and intensive interaction between energy systems and social systems. From this perspective, we define 'social energy' as a complex sociotechnical system of energy systems, social systems and the derived artificial virtual systems which characterize the intense intersystem and intra-system interactions. The recent advancement in intelligent technology, including artificial intelligence and machine learning technologies, sensing and communication in Internet of Things technologies, and massive high performance computing and extreme-scale data analytics technologies, enables the possibility of substantial advancement in socio-technical system optimization, scheduling, control and management. In thismore » paper, we provide a discussion on the nature of energy, and then propose the concept and intention of social energy systems for electrical power. A general methodology of establishing and investigating social energy is proposed, which is based on the ACP approach, i.e., 'artificial systems' (A), 'computational experiments' (C) and 'parallel execution' (P), and parallel system methodology. A case study on the University of Denver (DU) campus grid is provided and studied to demonstrate the social energy concept. In the concluding remarks, we discuss the technical pathway, in both social and nature sciences, to social energy, and our vision on its future.« less

Constructing Artificial Rock Outcrops as Tools for Fostering Earth and Environmental Science Thinking

NASA Astrophysics Data System (ADS)

Totten, I. M.; Hall, F.; Buxton, C.

2004-12-01

The Earth and Environmental Science Education Group at the University of New Orleans has created an innovative visualization teaching tool. Through funding made available by the National Science Foundation a 12'x10'x5' artificial rock outcrop was fabricated at the University of New Orleans. An accompanying curriculum, which includes a series of artificial rock outcrop labs, was also created for the outcrop. The labs incorporated fundamental concepts from the geosciences and the field of science education. The overarching philosophy behind the unity of the content knowledge and the pedagogy was to develop a more inclusive and deliberate teaching approach that utilized strategies known to enhance student learning in the sciences. The artificial outcrop lab series emphasized the following geoscience topics: relative dating, rock movement, and depositional environments. The series also integrated pedagogical ideas such as inquiry-based learning, conceptual mapping, constructivist teaching, pattern recognition, and contextualized knowledge development. Each component of the curriculum was purposefully designed to address what the body of research in science education reveals as critical to science teaching and learning. After developing the artificial rock outcrop curriculum a pilot study was done with 40 pre-service elementary education undergraduates. In the pilot study students completed the following assessments: three outcrop labs, journal reflections for each lab, pre/post attitude surveys, group video-recordings, and preconception and final interviews. Data from these assessments were analyzed using qualitative and quantitative methodologies. The following conclusions were revealed from the data: student's attitudes towards learning earth science increased after working with the artificial rock outcrop, students conceptual understanding of the concepts were clearer after working with the outcrop, students were able to answer multifaceted, higher order questions as a result of working with the outcrop, and students confidence in their abilities to think scientifically improved after their experience with the outcrop. The artificial rock outcrop has consequently been incorporated into several courses that have large enrollments from the following student populations: pre-service elementary education majors, undergraduate non-science majors, geology majors, and in-service MAST (Masters of Art in Science Teaching) students. Approximately, 1300 college students and 500 students in the 4th-12th grade levels from the local metropolitan school area work with the artificial rock outcrop annually. The artificial rock outcrop curriculum was a much-needed teaching tool in New Orleans considering the absence of natural rock outcrops along the entire coastal plain province.

Research on application of intelligent computation based LUCC model in urbanization process

NASA Astrophysics Data System (ADS)

Chen, Zemin

2007-06-01

Global change study is an interdisciplinary and comprehensive research activity with international cooperation, arising in 1980s, with the largest scopes. The interaction between land use and cover change, as a research field with the crossing of natural science and social science, has become one of core subjects of global change study as well as the front edge and hot point of it. It is necessary to develop research on land use and cover change in urbanization process and build an analog model of urbanization to carry out description, simulation and analysis on dynamic behaviors in urban development change as well as to understand basic characteristics and rules of urbanization process. This has positive practical and theoretical significance for formulating urban and regional sustainable development strategy. The effect of urbanization on land use and cover change is mainly embodied in the change of quantity structure and space structure of urban space, and LUCC model in urbanization process has been an important research subject of urban geography and urban planning. In this paper, based upon previous research achievements, the writer systematically analyzes the research on land use/cover change in urbanization process with the theories of complexity science research and intelligent computation; builds a model for simulating and forecasting dynamic evolution of urban land use and cover change, on the basis of cellular automation model of complexity science research method and multi-agent theory; expands Markov model, traditional CA model and Agent model, introduces complexity science research theory and intelligent computation theory into LUCC research model to build intelligent computation-based LUCC model for analog research on land use and cover change in urbanization research, and performs case research. The concrete contents are as follows: 1. Complexity of LUCC research in urbanization process. Analyze urbanization process in combination with the contents of complexity science research and the conception of complexity feature to reveal the complexity features of LUCC research in urbanization process. Urban space system is a complex economic and cultural phenomenon as well as a social process, is the comprehensive characterization of urban society, economy and culture, and is a complex space system formed by society, economy and nature. It has dissipative structure characteristics, such as opening, dynamics, self-organization, non-balance etc. Traditional model cannot simulate these social, economic and natural driving forces of LUCC including main feedback relation from LUCC to driving force. 2. Establishment of Markov extended model of LUCC analog research in urbanization process. Firstly, use traditional LUCC research model to compute change speed of regional land use through calculating dynamic degree, exploitation degree and consumption degree of land use; use the theory of fuzzy set to rewrite the traditional Markov model, establish structure transfer matrix of land use, forecast and analyze dynamic change and development trend of land use, and present noticeable problems and corresponding measures in urbanization process according to research results. 3. Application of intelligent computation research and complexity science research method in LUCC analog model in urbanization process. On the basis of detailed elaboration of the theory and the model of LUCC research in urbanization process, analyze the problems of existing model used in LUCC research (namely, difficult to resolve many complexity phenomena in complex urban space system), discuss possible structure realization forms of LUCC analog research in combination with the theories of intelligent computation and complexity science research. Perform application analysis on BP artificial neural network and genetic algorithms of intelligent computation and CA model and MAS technology of complexity science research, discuss their theoretical origins and their own characteristics in detail, elaborate the feasibility of them in LUCC analog research, and bring forward improvement methods and measures on existing problems of this kind of model. 4. Establishment of LUCC analog model in urbanization process based on theories of intelligent computation and complexity science. Based on the research on abovementioned BP artificial neural network, genetic algorithms, CA model and multi-agent technology, put forward improvement methods and application assumption towards their expansion on geography, build LUCC analog model in urbanization process based on CA model and Agent model, realize the combination of learning mechanism of BP artificial neural network and fuzzy logic reasoning, express the regulation with explicit formula, and amend the initial regulation through self study; optimize network structure of LUCC analog model and methods and procedures of model parameters with genetic algorithms. In this paper, I introduce research theory and methods of complexity science into LUCC analog research and presents LUCC analog model based upon CA model and MAS theory. Meanwhile, I carry out corresponding expansion on traditional Markov model and introduce the theory of fuzzy set into data screening and parameter amendment of improved model to improve the accuracy and feasibility of Markov model in the research on land use/cover change.

Entanglement-Based Machine Learning on a Quantum Computer

NASA Astrophysics Data System (ADS)

Cai, X.-D.; Wu, D.; Su, Z.-E.; Chen, M.-C.; Wang, X.-L.; Li, Li; Liu, N.-L.; Lu, C.-Y.; Pan, J.-W.

2015-03-01

Machine learning, a branch of artificial intelligence, learns from previous experience to optimize performance, which is ubiquitous in various fields such as computer sciences, financial analysis, robotics, and bioinformatics. A challenge is that machine learning with the rapidly growing "big data" could become intractable for classical computers. Recently, quantum machine learning algorithms [Lloyd, Mohseni, and Rebentrost, arXiv.1307.0411] were proposed which could offer an exponential speedup over classical algorithms. Here, we report the first experimental entanglement-based classification of two-, four-, and eight-dimensional vectors to different clusters using a small-scale photonic quantum computer, which are then used to implement supervised and unsupervised machine learning. The results demonstrate the working principle of using quantum computers to manipulate and classify high-dimensional vectors, the core mathematical routine in machine learning. The method can, in principle, be scaled to larger numbers of qubits, and may provide a new route to accelerate machine learning.

Artificial intelligence for multi-mission planetary operations

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

To Strengthen American Cognitive Science for the Twenty-First Century. Report of a Planning Workshop for the Cognitive Science Initiative at the National Science Foundation (Washington, D.C., April 20-21, 1991).

ERIC Educational Resources Information Center

National Science Foundation, Washington, DC.

Cognitive science, the study of both biological and artificial intelligent systems, is an inherently interdisciplinary activity that embraces aspects of psychology, linguistics, artificial intelligence, neuroscience, engineering, and other behavioral and social sciences. This document reports the results of a workshop designed to provide advice to…

eHealth research from the user's perspective.

PubMed

Hesse, Bradford W; Shneiderman, Ben

2007-05-01

The application of information technology (IT) to issues of healthcare delivery has had a long and tortuous history in the United States. Within the field of eHealth, vanguard applications of advanced computing techniques, such as applications in artificial intelligence or expert systems, have languished in spite of a track record of scholarly publication and decisional accuracy. The problem is one of purpose, of asking the right questions for the science to solve. Historically, many computer science pioneers have been tempted to ask "what can the computer do?" New advances in eHealth are prompting developers to ask "what can people do?" How can eHealth take part in national goals for healthcare reform to empower relationships between healthcare professionals and patients, healthcare teams and families, and hospitals and communities to improve health equitably throughout the population? To do this, eHealth researchers must combine best evidence from the user sciences (human factors engineering, human-computer interaction, psychology, and usability) with best evidence in medicine to create transformational improvements in the quality of care that medicine offers. These improvements should follow recommendations from the Institute of Medicine to create a healthcare system that is (1) safe, (2) effective (evidence based), (3) patient centered, and (4) timely. Relying on the eHealth researcher's intuitive grasp of systems issues, improvements should be made with considerations of users and beneficiaries at the individual (patient-physician), group (family-staff), community, and broad environmental levels.

Interdisciplinary Study on Artificial Intelligence.

DTIC Science & Technology

1983-07-01

systems, uiophysics of information processing, cognitive science, and traditional artificial intelligence. The objective behi d this objective was to...information processing, cognitive science, and traditional * artificial intelligence. The objective behind this objective was to provide a vehicle for reviewing...Another departure from ’classical’ neurodynamics must be sought in the strong coupling between the micro and macroscopic scales. No other physical mechanism

Computational aerodynamics and artificial intelligence

NASA Technical Reports Server (NTRS)

Mehta, U. B.; Kutler, P.

1984-01-01

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

Three Short Papers on Language and Connectionism

DTIC Science & Technology

1987-09-29

n t, 0 4 4 - ,.. .* .~’ 4 r. The Artificial Intelligence and Psychology Project DTIC eELECTE=M Departments of DEC 2 91988 Computer Science and...rib u ticn u n! -zted 4 PERFORMING ORt4iZATION REPOIRT NUMUER(S) S. MONITORING ORGANIZATION REPORT NUMUER(S) AIP - 1 6. NAME OF PERFORMING ORGANIZATION...1473, 84 MAR 83 APR edition r"ay oo used until eurlaust* 4 . SECURITY CLASSIFICATION OF THIS PAGE All otlMer 0itionl art oVS0lete Unclassified Tri 0~$ Oh

Instructional Applications of Artificial Intelligence.

ERIC Educational Resources Information Center

Halff, Henry M.

1986-01-01

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

What is data ethics?

PubMed Central

2016-01-01

This theme issue has the founding ambition of landscaping data ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data ethics builds on the foundation provided by computer and information ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the level of abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations—the interactions among hardware, software and data—rather than on the variety of digital technologies that enable them. And it emphasizes the complexity of the ethical challenges posed by data science. Because of such complexity, data ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of data science and its applications within a consistent, holistic and inclusive framework. Only as a macroethics will data ethics provide solutions that can maximize the value of data science for our societies, for all of us and for our environments. This article is part of the themed issue ‘The ethical impact of data science’. PMID:28336805

An Assessment of Artificial Compressibility and Pressure Projection Methods for Incompressible Flow Simulations

NASA Technical Reports Server (NTRS)

Kwak, Dochan; Kiris, C.; Smith, Charles A. (Technical Monitor)

1998-01-01

Performance of the two commonly used numerical procedures, one based on artificial compressibility method and the other pressure projection method, are compared. These formulations are selected primarily because they are designed for three-dimensional applications. The computational procedures are compared by obtaining steady state solutions of a wake vortex and unsteady solutions of a curved duct flow. For steady computations, artificial compressibility was very efficient in terms of computing time and robustness. For an unsteady flow which requires small physical time step, pressure projection method was found to be computationally more efficient than an artificial compressibility method. This comparison is intended to give some basis for selecting a method or a flow solution code for large three-dimensional applications where computing resources become a critical issue.

Research and Development Annual Report, 1992

NASA Technical Reports Server (NTRS)

1993-01-01

Issued as a companion to Johnson Space Center's Research and Technology Annual Report, which reports JSC accomplishments under NASA Research and Technology Operating Plan (RTOP) funding, this report describes 42 additional JSC projects that are funded through sources other than the RTOP. Emerging technologies in four major disciplines are summarized: space systems technology, medical and life sciences, mission operations, and computer systems. Although these projects focus on support of human spacecraft design, development, and safety, most have wide civil and commercial applications in areas such as advanced materials, superconductors, advanced semiconductors, digital imaging, high density data storage, high performance computers, optoelectronics, artificial intelligence, robotics and automation, sensors, biotechnology, medical devices and diagnosis, and human factors engineering.

The JSC Research and Development Annual Report 1993

NASA Technical Reports Server (NTRS)

1994-01-01

Issued as a companion to Johnson Space Center's Research and Technology Annual Report, which reports JSC accomplishments under NASA Research and Technology Operating Plan (RTOP) funding, this report describes 47 additional projects that are funded through sources other than the RTOP. Emerging technologies in four major disciplines are summarized: space systems technology, medical and life sciences, mission operations, and computer systems. Although these projects focus on support of human spacecraft design, development, and safety, most have wide civil and commercial applications in areas such as advanced materials, superconductors, advanced semiconductors, digital imaging, high density data storage, high performance computers, optoelectronics, artificial intelligence, robotics and automation, sensors, biotechnology, medical devices and diagnosis, and human factors engineering.

Building brains for bodies

NASA Technical Reports Server (NTRS)

Brooks, Rodney Allen; Stein, Lynn Andrea

1994-01-01

We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We will build an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to 'think' by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience.

Incorporating time and spatial-temporal reasoning into situation management

NASA Astrophysics Data System (ADS)

Jakobson, Gabriel

2010-04-01

Spatio-temporal reasoning plays a significant role in situation management that is performed by intelligent agents (human or machine) by affecting how the situations are recognized, interpreted, acted upon or predicted. Many definitions and formalisms for the notion of spatio-temporal reasoning have emerged in various research fields including psychology, economics and computer science (computational linguistics, data management, control theory, artificial intelligence and others). In this paper we examine the role of spatio-temporal reasoning in situation management, particularly how to resolve situations that are described by using spatio-temporal relations among events and situations. We discuss a model for describing context sensitive temporal relations and show have the model can be extended for spatial relations.

Actors: A Model of Concurrent Computation in Distributed Systems.

DTIC Science & Technology

1985-06-01

Artificial Intelligence Labora- tory of the Massachusetts Institute of Technology. Support for the labora- tory’s aritificial intelligence research is...RD-A157 917 ACTORS: A MODEL OF CONCURRENT COMPUTATION IN 1/3- DISTRIBUTED SY𔃿TEMS(U) MASSACHUSETTS INST OF TECH CRMBRIDGE ARTIFICIAL INTELLIGENCE ...Computation In Distributed Systems Gui A. Aghai MIT Artificial Intelligence Laboratory Thsdocument ha. been cipp-oved I= pblicrelease and sale; itsI

The 'Biologically-Inspired Computing' Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2006-01-01

The field of Biology changed dramatically in 1953, with the determination by Francis Crick and James Dewey Watson of the double helix structure of DNA. This discovery changed Biology for ever, allowing the sequencing of the human genome, and the emergence of a "new Biology" focused on DNA, genes, proteins, data, and search. Computational Biology and Bioinformatics heavily rely on computing to facilitate research into life and development. Simultaneously, an understanding of the biology of living organisms indicates a parallel with computing systems: molecules in living cells interact, grow, and transform according to the "program" dictated by DNA. Moreover, paradigms of Computing are emerging based on modelling and developing computer-based systems exploiting ideas that are observed in nature. This includes building into computer systems self-management and self-governance mechanisms that are inspired by the human body's autonomic nervous system, modelling evolutionary systems analogous to colonies of ants or other insects, and developing highly-efficient and highly-complex distributed systems from large numbers of (often quite simple) largely homogeneous components to reflect the behaviour of flocks of birds, swarms of bees, herds of animals, or schools of fish. This new field of "Biologically-Inspired Computing", often known in other incarnations by other names, such as: Autonomic Computing, Pervasive Computing, Organic Computing, Biomimetics, and Artificial Life, amongst others, is poised at the intersection of Computer Science, Engineering, Mathematics, and the Life Sciences. Successes have been reported in the fields of drug discovery, data communications, computer animation, control and command, exploration systems for space, undersea, and harsh environments, to name but a few, and augur much promise for future progress.

Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network

PubMed Central

Goto, Hayato

2016-01-01

The dynamics of nonlinear systems qualitatively change depending on their parameters, which is called bifurcation. A quantum-mechanical nonlinear oscillator can yield a quantum superposition of two oscillation states, known as a Schrödinger cat state, via quantum adiabatic evolution through its bifurcation point. Here we propose a quantum computer comprising such quantum nonlinear oscillators, instead of quantum bits, to solve hard combinatorial optimization problems. The nonlinear oscillator network finds optimal solutions via quantum adiabatic evolution, where nonlinear terms are increased slowly, in contrast to conventional adiabatic quantum computation or quantum annealing, where quantum fluctuation terms are decreased slowly. As a result of numerical simulations, it is concluded that quantum superposition and quantum fluctuation work effectively to find optimal solutions. It is also notable that the present computer is analogous to neural computers, which are also networks of nonlinear components. Thus, the present scheme will open new possibilities for quantum computation, nonlinear science, and artificial intelligence. PMID:26899997

Computational Analysis of Behavior.

PubMed

Egnor, S E Roian; Branson, Kristin

2016-07-08

In this review, we discuss the emerging field of computational behavioral analysis-the use of modern methods from computer science and engineering to quantitatively measure animal behavior. We discuss aspects of experiment design important to both obtaining biologically relevant behavioral data and enabling the use of machine vision and learning techniques for automation. These two goals are often in conflict. Restraining or restricting the environment of the animal can simplify automatic behavior quantification, but it can also degrade the quality or alter important aspects of behavior. To enable biologists to design experiments to obtain better behavioral measurements, and computer scientists to pinpoint fruitful directions for algorithm improvement, we review known effects of artificial manipulation of the animal on behavior. We also review machine vision and learning techniques for tracking, feature extraction, automated behavior classification, and automated behavior discovery, the assumptions they make, and the types of data they work best with.

A computational fluid dynamics simulation of the hypersonic flight of the Pegasus(TM) vehicle using an artificial viscosity model and a nonlinear filtering method. M.S. Thesis

NASA Technical Reports Server (NTRS)

Mendoza, John Cadiz

1995-01-01

The computational fluid dynamics code, PARC3D, is tested to see if its use of non-physical artificial dissipation affects the accuracy of its results. This is accomplished by simulating a shock-laminar boundary layer interaction and several hypersonic flight conditions of the Pegasus(TM) launch vehicle using full artificial dissipation, low artificial dissipation, and the Engquist filter. Before the filter is applied to the PARC3D code, it is validated in one-dimensional and two-dimensional form in a MacCormack scheme against the Riemann and convergent duct problem. For this explicit scheme, the filter shows great improvements in accuracy and computational time as opposed to the nonfiltered solutions. However, for the implicit PARC3D code it is found that the best estimate of the Pegasus experimental heat fluxes and surface pressures is the simulation utilizing low artificial dissipation and no filter. The filter does improve accuracy over the artificially dissipative case but at a computational expense greater than that achieved by the low artificial dissipation case which has no computational time penalty and shows better results. For the shock-boundary layer simulation, the filter does well in terms of accuracy for a strong impingement shock but not as well for weaker shock strengths. Furthermore, for the latter problem the filter reduces the required computational time to convergence by 18.7 percent.

Editorial: Cognitive Architectures, Model Comparison and AGI

NASA Astrophysics Data System (ADS)

Lebiere, Christian; Gonzalez, Cleotilde; Warwick, Walter

2010-12-01

Cognitive Science and Artificial Intelligence share compatible goals of understanding and possibly generating broadly intelligent behavior. In order to determine if progress is made, it is essential to be able to evaluate the behavior of complex computational models, especially those built on general cognitive architectures, and compare it to benchmarks of intelligent behavior such as human performance. Significant methodological challenges arise, however, when trying to extend approaches used to compare model and human performance from tightly controlled laboratory tasks to complex tasks involving more open-ended behavior. This paper describes a model comparison challenge built around a dynamic control task, the Dynamic Stocks and Flows. We present and discuss distinct approaches to evaluating performance and comparing models. Lessons drawn from this challenge are discussed in light of the challenge of using cognitive architectures to achieve Artificial General Intelligence.

CREATIVE COMPUTATION.

DTIC Science & Technology

ARTIFICIAL INTELLIGENCE , RECURSIVE FUNCTIONS), (*RECURSIVE FUNCTIONS, ARTIFICIAL INTELLIGENCE ), (*MATHEMATICAL LOGIC, ARTIFICIAL INTELLIGENCE ), METAMATHEMATICS, AUTOMATA, NUMBER THEORY, INFORMATION THEORY, COMBINATORIAL ANALYSIS

Neural Networks In Mining Sciences - General Overview And Some Representative Examples

NASA Astrophysics Data System (ADS)

Tadeusiewicz, Ryszard

2015-12-01

The many difficult problems that must now be addressed in mining sciences make us search for ever newer and more efficient computer tools that can be used to solve those problems. Among the numerous tools of this type, there are neural networks presented in this article - which, although not yet widely used in mining sciences, are certainly worth consideration. Neural networks are a technique which belongs to so called artificial intelligence, and originates from the attempts to model the structure and functioning of biological nervous systems. Initially constructed and tested exclusively out of scientific curiosity, as computer models of parts of the human brain, neural networks have become a surprisingly effective calculation tool in many areas: in technology, medicine, economics, and even social sciences. Unfortunately, they are relatively rarely used in mining sciences and mining technology. The article is intended to convince the readers that neural networks can be very useful also in mining sciences. It contains information how modern neural networks are built, how they operate and how one can use them. The preliminary discussion presented in this paper can help the reader gain an opinion whether this is a tool with handy properties, useful for him, and what it might come in useful for. Of course, the brief introduction to neural networks contained in this paper will not be enough for the readers who get convinced by the arguments contained here, and want to use neural networks. They will still need a considerable portion of detailed knowledge so that they can begin to independently create and build such networks, and use them in practice. However, an interested reader who decides to try out the capabilities of neural networks will also find here links to references that will allow him to start exploration of neural networks fast, and then work with this handy tool efficiently. This will be easy, because there are currently quite a few ready-made computer programs, easily available, which allow their user to quickly and effortlessly create artificial neural networks, run them, train and use in practice. The key issue is the question how to use these networks in mining sciences. The fact that this is possible and desirable is shown by convincing examples included in the second part of this study. From the very rich literature on the various applications of neural networks, we have selected several works that show how and what neural networks are used in the mining industry, and what has been achieved thanks to their use. The review of applications will continue in the next article, filed already for publication in the journal "Archives of Mining Sciences". Only studying these two articles will provide sufficient knowledge for initial guidance in the area of issues under consideration here.

SHARP: A multi-mission artificial intelligence system for spacecraft telemetry monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Lawson, Denise L.; James, Mark L.

1989-01-01

The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager 2 spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

Artificial Neural Networks for Modeling Knowing and Learning in Science.

ERIC Educational Resources Information Center

Roth, Wolff-Michael

2000-01-01

Advocates artificial neural networks as models for cognition and development. Provides an example of how such models work in the context of a well-known Piagetian developmental task and school science activity: balance beam problems. (Contains 59 references.) (Author/WRM)

Designing Artificial Enzymes by Intuition and Computation

PubMed Central

Nanda, Vikas; Koder, Ronald L.

2012-01-01

The rational design of artificial enzymes either by applying physio-chemical intuition of protein structure and function or with the aid of computation methods is a promising area of research with the potential to tremendously impact medicine, industrial chemistry and energy production. Designed proteins also provide a powerful platform for dissecting enzyme mechanisms of natural systems. Artificial enzymes have come a long way, from simple α-helical peptide catalysts to proteins that facilitate multi-step chemical reactions designed by state-of-the-art computational methods. Looking forward, we examine strategies employed by natural enzymes which could be used to improve the speed and selectivity of artificial catalysts. PMID:21124375

Soft computing prediction of economic growth based in science and technology factors

NASA Astrophysics Data System (ADS)

Marković, Dušan; Petković, Dalibor; Nikolić, Vlastimir; Milovančević, Miloš; Petković, Biljana

2017-01-01

The purpose of this research is to develop and apply the Extreme Learning Machine (ELM) to forecast the gross domestic product (GDP) growth rate. In this study the GDP growth was analyzed based on ten science and technology factors. These factors were: research and development (R&D) expenditure in GDP, scientific and technical journal articles, patent applications for nonresidents, patent applications for residents, trademark applications for nonresidents, trademark applications for residents, total trademark applications, researchers in R&D, technicians in R&D and high-technology exports. The ELM results were compared with genetic programming (GP), artificial neural network (ANN) and fuzzy logic results. Based upon simulation results, it is demonstrated that ELM has better forecasting capability for the GDP growth rate.

Constructing Smart Protocells with Built-In DNA Computational Core to Eliminate Exogenous Challenge.

PubMed

Lyu, Yifan; Wu, Cuichen; Heinke, Charles; Han, Da; Cai, Ren; Teng, I-Ting; Liu, Yuan; Liu, Hui; Zhang, Xiaobing; Liu, Qiaoling; Tan, Weihong

2018-06-06

A DNA reaction network is like a biological algorithm that can respond to "molecular input signals", such as biological molecules, while the artificial cell is like a microrobot whose function is powered by the encapsulated DNA reaction network. In this work, we describe the feasibility of using a DNA reaction network as the computational core of a protocell, which will perform an artificial immune response in a concise way to eliminate a mimicked pathogenic challenge. Such a DNA reaction network (RN)-powered protocell can realize the connection of logical computation and biological recognition due to the natural programmability and biological properties of DNA. Thus, the biological input molecules can be easily involved in the molecular computation and the computation process can be spatially isolated and protected by artificial bilayer membrane. We believe the strategy proposed in the current paper, i.e., using DNA RN to power artificial cells, will lay the groundwork for understanding the basic design principles of DNA algorithm-based nanodevices which will, in turn, inspire the construction of artificial cells, or protocells, that will find a place in future biomedical research.

Artificial Intelligence: An Analysis of Potential Applications to Training, Performance Measurement, and Job Performance Aiding.

DTIC Science & Technology

1983-09-01

AD-Ali33 592 ARTIFICIAL INTELLIGENCE: AN ANALYSIS OF POTENTIAL 1/1 APPLICATIONS TO TRAININ..(U) DENVER RESEARCH INST CO JRICHARDSON SEP 83 AFHRL-TP...83-28 b ’ 3 - 4. TITLE (aied Suhkie) 5. TYPE OF REPORT & PERIOD COVERED ARTIFICIAL INTEL11GENCE: AN ANALYSIS OF Interim POTENTIAL APPLICATIONS TO...8217 sde if neceseamy end ides*f by black naumber) artificial intelligence military research * computer-aided diagnosis performance tests computer

eHealth Research from the User’s Perspective

PubMed Central

Hesse, Bradford W.; Shneiderman, Ben

2007-01-01

The application of Information Technology (IT) to issues of healthcare delivery has had a long and tortuous history in the U.S. Within the field of eHealth, vanguard applications of advanced computing techniques, such as applications in artificial intelligence or expert systems, have languished in spite of a track record of scholarly publication and decisional accuracy. The problem is one of purpose, of asking the right questions for the science to solve. Historically, many computer science pioneers have been tempted to ask “what can the computer do?” New advances in eHealth are prompting developers to ask “what can people do?” How can eHealth take part in national goals for healthcare reform to empower relationships between healthcare professionals and patients, healthcare teams and families, and hospitals and communities to improve health equitably throughout the population? To do this, eHealth researchers must combine best evidence from the user sciences (human factors engineering, human-computer interaction, psychology, and usability) with best evidence in medicine to create transformational improvements in the quality of care that medicine offers. These improvements should follow recommendations from the Institute of Medicine to create a health care system that is (a) safe, (b) effective (evidence-based), (c) patient-centered, and (d) timely. Relying on the eHealth researcher’s intuitive grasp of systems issues, improvements should be made with considerations of users and beneficiaries at the individual (patient/physician), group (family/staff), community, and broad environmental levels. PMID:17466825

Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

PubMed

Darsey, Jerry A; Griffin, William O; Joginipelli, Sravanthi; Melapu, Venkata Kiran

2015-01-01

Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion that tolerates noise and error has attracted many researchers and provided the starting point for the development of artificial neural networks: the intelligent systems. Intelligent systems can acclimatize to the environment or data and can maximize the chances of success or improve the efficiency of a search. Due to massive parallelism with large numbers of interconnected processers and their ability to learn from the data, neural networks can solve a variety of challenging computational problems. Neural networks have the ability to derive meaning from complicated and imprecise data; they are used in detecting patterns, and trends that are too complex for humans, or other computer systems. Solutions to the toughest problems will not be found through one narrow specialization; therefore we need to combine interdisciplinary approaches to discover the solutions to a variety of problems. Many researchers in different disciplines such as medicine, bioinformatics, molecular biology, and pharmacology have successfully applied artificial neural networks. This chapter helps the reader in understanding the basics of artificial neural networks, their applications, and methodology; it also outlines the network learning process and architecture. We present a brief outline of the application of neural networks to medical diagnosis, drug discovery, gene identification, and protein structure prediction. We conclude with a summary of the results from our study on tuberculosis data using neural networks, in diagnosing active tuberculosis, and predicting chronic vs. infiltrative forms of tuberculosis.

Artificial Life Art, Creativity, and Techno-hybridization (editor's introduction).

PubMed

Dorin, Alan

2015-01-01

Artists and engineers have devised lifelike technology for millennia. Their ingenious devices have often prompted inquiry into our preferences, prejudices, and beliefs about living systems, especially regarding their origins, status, constitution, and behavior. A recurring fabrication technique is shared across artificial life art, science, and engineering. This involves aggregating representations or re-creations of familiar biological parts-techno-hybridization-but the motives of practitioners may differ markedly. This article, and the special issue it introduces, explores how ground familiar to contemporary artificial life science and engineering has been assessed and interpreted in parallel by (a) artists and (b) theorists studying creativity explicitly. This activity offers thoughtful, alternative perspectives on artificial life science and engineering, highlighting and sometimes undermining the fields' underlying assumptions, or exposing avenues that are yet to be explored outside of art. Additionally, art has the potential to engage the general public, supporting and exploring the findings of scientific research and engineering. This adds considerably to the maturity of a culture tackling the issues the discipline of artificial life raises.

Planning and Scheduling of Software Manufacturing Projects

DTIC Science & Technology

1991-03-01

based on the previous results in social analysis of computing, operations research in manufacturing, artificial intelligence in manufacturing...planning and scheduling, and the traditional approaches to planning in artificial intelligence, and extends the techniques that have been developed by them...social analysis of computing, operations research in manufacturing, artificial intelligence in manufacturing planning and scheduling, and the

Bioinspired principles for large-scale networked sensor systems: an overview.

PubMed

Jacobsen, Rune Hylsberg; Zhang, Qi; Toftegaard, Thomas Skjødeberg

2011-01-01

Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy.

IEEE 1982. Proceedings of the international conference on cybernetics and society

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1982-01-01

The following topics were dealt with: knowledge-based systems; risk analysis; man-machine interactions; human information processing; metaphor, analogy and problem-solving; manual control modelling; transportation systems; simulation; adaptive and learning systems; biocybernetics; cybernetics; mathematical programming; robotics; decision support systems; analysis, design and validation of models; computer vision; systems science; energy systems; environmental modelling and policy; pattern recognition; nuclear warfare; technological forecasting; artificial intelligence; the Turin shroud; optimisation; workloads. Abstracts of individual papers can be found under the relevant classification codes in this or future issues.

Power to the People: Addressing Big Data Challenges in Neuroscience by Creating a New Cadre of Citizen Neuroscientists.

PubMed

Roskams, Jane; Popović, Zoran

2016-11-02

Global neuroscience projects are producing big data at an unprecedented rate that informatic and artificial intelligence (AI) analytics simply cannot handle. Online games, like Foldit, Eterna, and Eyewire-and now a new neuroscience game, Mozak-are fueling a people-powered research science (PPRS) revolution, creating a global community of "new experts" that over time synergize with computational efforts to accelerate scientific progress, empowering us to use our collective cerebral talents to drive our understanding of our brain. Copyright © 2016 Elsevier Inc. All rights reserved.

Technology transfer from the science of medicine to the real world: the potential role played by artificial adaptive systems.

PubMed

Grossi, Enzo

2007-01-01

The author describes a refiguration of medical thought that originates from nonlinear dynamics and chaos theory. The coupling of computer science and these new theoretical bases coming from complex systems mathematics allows the creation of "intelligent" agents capable of adapting themselves dynamically to problems of high complexity: the artificial neural networks (ANNs). ANNs are able to reproduce the dynamic interaction of multiple factors simultaneously, allowing the study of complexity; they can also draw conclusions on an individual basis and not as average trends. These tools can allow a more efficient technology transfer from the science of medicine to the real world, overcoming many obstacles responsible for the present translational failure. They also contribute to a new holistic vision of the human subject person, contrasting the statistical reductionism that tends to squeeze or even delete the single subject, sacrificing him to his group of belongingness. A remarkable contribution to this individual approach comes from fuzzy logic, according to which there are no sharp limits between opposite things, such as wealth and disease. This approach allows one to partially escape from the probability theory trap in situations where it is fundamental to express a judgement based on a single case and favor a novel humanism directed to the management of the patient as an individual subject person.

ICCE/ICCAI 2000 Full & Short Papers (Artificial Intelligence in Education).

ERIC Educational Resources Information Center

2000

This document contains the full and short papers on artificial intelligence in education from ICCE/ICCAI 2000 (International Conference on Computers in Education/International Conference on Computer-Assisted Instruction) covering the following topics: a computational model for learners' motivation states in individualized tutoring system; a…

NASA Intelligent Systems Project: Results, Accomplishments and Impact on Science Missions.

NASA Astrophysics Data System (ADS)

Coughlan, J. C.

2005-12-01

The Intelligent Systems Project was responsible for much of NASA's programmatic investment in artificial intelligence and advanced information technologies. IS has completed three major project milestones which demonstrated increased capabilities in autonomy, human centered computing, and intelligent data understanding. Autonomy involves the ability of a robot to place an instrument on a remote surface with a single command cycle, human centered computing supported a collaborative, mission centric data and planning system for the Mars Exploration Rovers and data understanding has produced key components of a terrestrial satellite observation system with automated modeling and data analysis capabilities. This paper summarizes the technology demonstrations and metrics which quantify and summarize these new technologies which are now available for future NASA missions.

NASA Intelligent Systems Project: Results, Accomplishments and Impact on Science Missions

NASA Technical Reports Server (NTRS)

Coughlan, Joseph C.

2005-01-01

The Intelligent Systems Project was responsible for much of NASA's programmatic investment in artificial intelligence and advanced information technologies. IS has completed three major project milestones which demonstrated increased capabilities in autonomy, human centered computing, and intelligent data understanding. Autonomy involves the ability of a robot to place an instrument on a remote surface with a single command cycle. Human centered computing supported a collaborative, mission centric data and planning system for the Mars Exploration Rovers and data understanding has produced key components of a terrestrial satellite observation system with automated modeling and data analysis capabilities. This paper summarizes the technology demonstrations and metrics which quantify and summarize these new technologies which are now available for future Nasa missions.

Improving multivariate Horner schemes with Monte Carlo tree search

NASA Astrophysics Data System (ADS)

Kuipers, J.; Plaat, A.; Vermaseren, J. A. M.; van den Herik, H. J.

2013-11-01

Optimizing the cost of evaluating a polynomial is a classic problem in computer science. For polynomials in one variable, Horner's method provides a scheme for producing a computationally efficient form. For multivariate polynomials it is possible to generalize Horner's method, but this leaves freedom in the order of the variables. Traditionally, greedy schemes like most-occurring variable first are used. This simple textbook algorithm has given remarkably efficient results. Finding better algorithms has proved difficult. In trying to improve upon the greedy scheme we have implemented Monte Carlo tree search, a recent search method from the field of artificial intelligence. This results in better Horner schemes and reduces the cost of evaluating polynomials, sometimes by factors up to two.

AIAA/NASA International Symposium on Space Information Systems, 2nd, Pasadena, CA, Sept. 17-19, 1990, Proceedings. Vols. 1 & 2

NASA Technical Reports Server (NTRS)

Tavenner, Leslie A. (Editor)

1991-01-01

These proceedings overview major space information system projects and lessons learned from current missions. Other topics include the science information system requirements for the 1990s, an information systems design approach for major programs, the technology needs and projections, the standards for space data information systems, the artificial intelligence technology and applications, international interoperability, and spacecraft data systems and architectures advanced communications. Other topics include the software engineering technology and applications, the multimission multidiscipline information system architectures, the distributed planning and scheduling systems and operations, and the computer and information systems architectures. Paper presented include prospects for scientific data analysis systems for solar-terrestrial physics in the 1990s, the Columbus data management system, data storage technologies for the future, the German aerospace research establishment, and launching artificial intelligence in NASA ground systems.

Exploiting Artificial Intelligence for Analysis and Data Selection on-board the Puerto Rico CubeSat

NASA Astrophysics Data System (ADS)

Bergman, J. E. S.; Bruhn, F.; Funk, P.; Isham, B.; Rincón-Charris, A. A.; Capo-Lugo, P.; Åhlén, L.

2015-10-01

CubeSat missions are constrained by the limited resources provided by the platform. Many payload providers have learned to cope with the low mass and power but the poor telemetry allocation remains a bottleneck. In the end, it is the data delivered to ground which determines the value of the mission. However, transmitting more data does not necessarily guarantee high value, since the value also depends on the data quality. By exploiting fast on-board computing and efficient artificial intelligence (AI) algorithms for analysis and data selection one could optimize the usage of the telemetry link and so increase the value of the mission. In a pilot project, we attempt to do this on the Puerto Rico CubeSat, where science objectives include the acquisition of space weather data to aid better understanding of the Sun to Earth connection.

[Application of microelectronics CAD tools to synthetic biology].

PubMed

Madec, Morgan; Haiech, Jacques; Rosati, Élise; Rezgui, Abir; Gendrault, Yves; Lallement, Christophe

2017-02-01

Synthetic biology is an emerging science that aims to create new biological functions that do not exist in nature, based on the knowledge acquired in life science over the last century. Since the beginning of this century, several projects in synthetic biology have emerged. The complexity of the developed artificial bio-functions is relatively low so that empirical design methods could be used for the design process. Nevertheless, with the increasing complexity of biological circuits, this is no longer the case and a large number of computer aided design softwares have been developed in the past few years. These tools include languages for the behavioral description and the mathematical modelling of biological systems, simulators at different levels of abstraction, libraries of biological devices and circuit design automation algorithms. All of these tools already exist in other fields of engineering sciences, particularly in microelectronics. This is the approach that is put forward in this paper. © 2017 médecine/sciences – Inserm.

Design and Implementation of a Relational Database Management System for the AFIT Thesis Process.

DTIC Science & Technology

1985-09-01

AIRLIFT Gourdin 4. APPLIED MATHEMATICS Daneman Lee Na rga rsen ker 5. ARTIFICIAL INTELLEGENCE Gen et 6. CAPARILITY ASSESSMENT S Budde Talbott 31...05 ARTIFICIAL INTELLIGENCE 06 CAPABILITY ASSESSMENT 07 COMMUNIICATIONS 08 COMPUTER AIDED DESIGN 09 COMPUTER BASED TRAINING 10 COMPUTER SOFTWARE 11

Using an Artificial Rock Outcrop to Teach Geology

ERIC Educational Resources Information Center

Totten, Iris

2005-01-01

Teaching Earth science without exposure to rock outcrops limits students depth of understanding of Earth's processes, limits the concept of scale from their spatial visualization imaging, and distorts their perception of geologic time (Totten 2003). Through a grant funded by the National Science Foundation, an artificial rock outcrop was…

Study on Electro-polymerization Nano-micro Wiring System Imitating Axonal Growth of Artificial Neurons towards Machine Learning

NASA Astrophysics Data System (ADS)

Dang, Nguyen Tuan; Akai-Kasada, Megumi; Asai, Tetsuya; Saito, Akira; Kuwahara, Yuji; Hokkaido University Collaboration

2015-03-01

Machine learning using the artificial neuron network research is supposed to be the best way to understand how the human brain trains itself to process information. In this study, we have successfully developed the programs using supervised machine learning algorithm. However, these supervised learning processes for the neuron network required the very strong computing configuration. Derivation from the necessity of increasing in computing ability and in reduction of power consumption, accelerator circuits become critical. To develop such accelerator circuits using supervised machine learning algorithm, conducting polymer micro/nanowires growing process was realized and applied as a synaptic weigh controller. In this work, high conductivity Polypyrrole (PPy) and Poly (3, 4 - ethylenedioxythiophene) PEDOT wires were potentiostatically grown crosslinking the designated electrodes, which were prefabricated by lithography, when appropriate square wave AC voltage and appropriate frequency were applied. Micro/nanowire growing process emulated the neurotransmitter release process of synapses inside a biological neuron and wire's resistance variation during the growing process was preferred to as the variation of synaptic weigh in machine learning algorithm. In a cooperation with Graduate School of Information Science and Technology, Hokkaido University.

A Contrast-Based Computational Model of Surprise and Its Applications.

PubMed

Macedo, Luis; Cardoso, Amílcar

2017-11-19

We review our work on a contrast-based computational model of surprise and its applications. The review is contextualized within related research from psychology, philosophy, and particularly artificial intelligence. Influenced by psychological theories of surprise, the model assumes that surprise-eliciting events initiate a series of cognitive processes that begin with the appraisal of the event as unexpected, continue with the interruption of ongoing activity and the focusing of attention on the unexpected event, and culminate in the analysis and evaluation of the event and the revision of beliefs. It is assumed that the intensity of surprise elicited by an event is a nonlinear function of the difference or contrast between the subjective probability of the event and that of the most probable alternative event (which is usually the expected event); and that the agent's behavior is partly controlled by actual and anticipated surprise. We describe applications of artificial agents that incorporate the proposed surprise model in three domains: the exploration of unknown environments, creativity, and intelligent transportation systems. These applications demonstrate the importance of surprise for decision making, active learning, creative reasoning, and selective attention. Copyright © 2017 Cognitive Science Society, Inc.

Levels and loops: the future of artificial intelligence and neuroscience.

PubMed Central

Bell, A J

1999-01-01

In discussing artificial intelligence and neuroscience, I will focus on two themes. The first is the universality of cycles (or loops): sets of variables that affect each other in such a way that any feed-forward account of causality and control, while informative, is misleading. The second theme is based around the observation that a computer is an intrinsically dualistic entity, with its physical set-up designed so as not to interfere with its logical set-up, which executes the computation. The brain is different. When analysed empirically at several different levels (cellular, molecular), it appears that there is no satisfactory way to separate a physical brain model (or algorithm, or representation), from a physical implementational substrate. When program and implementation are inseparable and thus interfere with each other, a dualistic point-of-view is impossible. Forced by empiricism into a monistic perspective, the brain-mind appears as neither embodied by or embedded in physical reality, but rather as identical to physical reality. This perspective has implications for the future of science and society. I will approach these from a negative point-of-view, by critiquing some of our millennial culture's popular projected futures. PMID:10670021

Magnetic skyrmion-based artificial neuron device

NASA Astrophysics Data System (ADS)

Li, Sai; Kang, Wang; Huang, Yangqi; Zhang, Xichao; Zhou, Yan; Zhao, Weisheng

2017-08-01

Neuromorphic computing, inspired by the biological nervous system, has attracted considerable attention. Intensive research has been conducted in this field for developing artificial synapses and neurons, attempting to mimic the behaviors of biological synapses and neurons, which are two basic elements of a human brain. Recently, magnetic skyrmions have been investigated as promising candidates in neuromorphic computing design owing to their topologically protected particle-like behaviors, nanoscale size and low driving current density. In one of our previous studies, a skyrmion-based artificial synapse was proposed, with which both short-term plasticity and long-term potentiation functions have been demonstrated. In this work, we further report on a skyrmion-based artificial neuron by exploiting the tunable current-driven skyrmion motion dynamics, mimicking the leaky-integrate-fire function of a biological neuron. With a simple single-device implementation, this proposed artificial neuron may enable us to build a dense and energy-efficient spiking neuromorphic computing system.

Numerical Simulation Of Flow Through An Artificial Heart

NASA Technical Reports Server (NTRS)

Rogers, Stuart; Kutler, Paul; Kwak, Dochan; Kiris, Centin

1991-01-01

Research in both artificial hearts and fluid dynamics benefits from computational studies. Algorithm that implements Navier-Stokes equations of flow extended to simulate flow of viscous, incompressible blood through articifial heart. Ability to compute details of such flow important for two reasons: internal flows with moving boundaries of academic interest in their own right, and many of deficiencies of artificial hearts attributable to dynamics of flow.

Sparse distributed memory and related models

NASA Technical Reports Server (NTRS)

Kanerva, Pentti

1992-01-01

Described here is sparse distributed memory (SDM) as a neural-net associative memory. It is characterized by two weight matrices and by a large internal dimension - the number of hidden units is much larger than the number of input or output units. The first matrix, A, is fixed and possibly random, and the second matrix, C, is modifiable. The SDM is compared and contrasted to (1) computer memory, (2) correlation-matrix memory, (3) feet-forward artificial neural network, (4) cortex of the cerebellum, (5) Marr and Albus models of the cerebellum, and (6) Albus' cerebellar model arithmetic computer (CMAC). Several variations of the basic SDM design are discussed: the selected-coordinate and hyperplane designs of Jaeckel, the pseudorandom associative neural memory of Hassoun, and SDM with real-valued input variables by Prager and Fallside. SDM research conducted mainly at the Research Institute for Advanced Computer Science (RIACS) in 1986-1991 is highlighted.

Machine learning methods in chemoinformatics

PubMed Central

Mitchell, John B O

2014-01-01

Machine learning algorithms are generally developed in computer science or adjacent disciplines and find their way into chemical modeling by a process of diffusion. Though particular machine learning methods are popular in chemoinformatics and quantitative structure–activity relationships (QSAR), many others exist in the technical literature. This discussion is methods-based and focused on some algorithms that chemoinformatics researchers frequently use. It makes no claim to be exhaustive. We concentrate on methods for supervised learning, predicting the unknown property values of a test set of instances, usually molecules, based on the known values for a training set. Particularly relevant approaches include Artificial Neural Networks, Random Forest, Support Vector Machine, k-Nearest Neighbors and naïve Bayes classifiers. WIREs Comput Mol Sci 2014, 4:468–481. How to cite this article: WIREs Comput Mol Sci 2014, 4:468–481. doi:10.1002/wcms.1183 PMID:25285160

Geodesy? What’s That? My Personal Involvement in the Age-Old Quest for the Size and Shape of the Earth

NASA Astrophysics Data System (ADS)

Morrison, Foster

2009-06-01

Imagine a story about a stay-at-home mother who, anticipating the departure of her children for college, takes a job at a government agency and by dint of hard work and persistence becomes a world-renowned scientist. This might sound improbable, but it happens to be the true story of Irene K. Fischer, a geodesist and AGU Fellow. How it happened and the way it did is a fascinating and complex story. In 1952, Fischer started working at the U.S. Army Map Service (AMS) in Brookmont, Md. (now part of Bethesda), at a time when computers were large, expensive, and feeble compared with the cheapest desktop personal computers available today. Much computing was still done on slow and noisy mechanical calculators. Artificial satellites, space probes, global positioning systems, and the like were science fiction fantasies.

Nondestructive pavement evaluation using ILLI-PAVE based artificial neural network models.

DOT National Transportation Integrated Search

2008-09-01

The overall objective in this research project is to develop advanced pavement structural analysis models for more accurate solutions with fast computation schemes. Soft computing and modeling approaches, specifically the Artificial Neural Network (A...

Survey of Artificial Intelligence and Expert Systems in Library and Information Science Literature.

ERIC Educational Resources Information Center

Hsieh, Cynthia C.; Hall, Wendy

1989-01-01

Examines the definition and history of artificial intelligence (AI) and investigates the body of literature on AI found in "Library Literature" and "Library and Information Science Abstracts." The results reported include the number of articles by year and per journal, and the percentage of articles dealing with library…

Computational models of music perception and cognition I: The perceptual and cognitive processing chain

NASA Astrophysics Data System (ADS)

Purwins, Hendrik; Herrera, Perfecto; Grachten, Maarten; Hazan, Amaury; Marxer, Ricard; Serra, Xavier

2008-09-01

We present a review on perception and cognition models designed for or applicable to music. An emphasis is put on computational implementations. We include findings from different disciplines: neuroscience, psychology, cognitive science, artificial intelligence, and musicology. The article summarizes the methodology that these disciplines use to approach the phenomena of music understanding, the localization of musical processes in the brain, and the flow of cognitive operations involved in turning physical signals into musical symbols, going from the transducers to the memory systems of the brain. We discuss formal models developed to emulate, explain and predict phenomena involved in early auditory processing, pitch processing, grouping, source separation, and music structure computation. We cover generic computational architectures of attention, memory, and expectation that can be instantiated and tuned to deal with specific musical phenomena. Criteria for the evaluation of such models are presented and discussed. Thereby, we lay out the general framework that provides the basis for the discussion of domain-specific music models in Part II.

Naval Computer-Based Instruction: Cost, Implementation and Effectiveness Issues.

DTIC Science & Technology

1988-03-01

logical follow on to MITIPAC and are an attempt to use some artificial intelligence (AI) techniques with computer-based training. A good intelligent ...principles of steam plant operation and maintenance. Steamer was written in LISP on a LISP machine in an attempt to use artificial intelligence . "What... Artificial Intelligence and Speech Technology", Electronic Learning, September 1987. Montague, William. E., code 5, Navy Personnel Research and

Use of the computational-informational web-GIS system for the development of climatology students' skills in modeling and understanding climate change

NASA Astrophysics Data System (ADS)

Gordova, Yulia; Martynova, Yulia; Shulgina, Tamara

2015-04-01

The current situation with the training of specialists in environmental sciences is complicated by the fact that the very scientific field is experiencing a period of rapid development. Global change has caused the development of measurement techniques and modeling of environmental characteristics, accompanied by the expansion of the conceptual and mathematical apparatus. Understanding and forecasting processes in the Earth system requires extensive use of mathematical modeling and advanced computing technologies. As a rule, available training programs in the environmental sciences disciplines do not have time to adapt to such rapid changes in the domain content. As a result, graduates of faculties do not understand processes and mechanisms of the global change, have only superficial knowledge of mathematical modeling of processes in the environment. They do not have the required skills in numerical modeling, data processing and analysis of observations and computation outputs and are not prepared to work with the meteorological data. For adequate training of future specialists in environmental sciences we propose the following approach, which reflects the new "research" paradigm in education. We believe that the training of such specialists should be done not in an artificial learning environment, but based on actual operating information-computational systems used in environment studies, in the so-called virtual research environment via development of virtual research and learning laboratories. In the report the results of the use of computational-informational web-GIS system "Climate" (http://climate.scert.ru/) as a prototype of such laboratory are discussed. The approach is realized at Tomsk State University to prepare bachelors in meteorology. Student survey shows that their knowledge has become deeper and more systemic after undergoing training in virtual learning laboratory. The scientific team plans to assist any educators to utilize the system in earth science education. This work is partially supported by SB RAS project VIII.80.2.1, RFBR grants 13-05-12034 and 14-05-00502.

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

PubMed

Cipresso, Pietro; Riva, Giuseppe

2015-01-01

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

ENGINEERING ECONOMIC ANALYSIS OF A PROGRAM FOR ARTIFICIAL GROUNDWATER RECHARGE.

USGS Publications Warehouse

Reichard, Eric G.; Bredehoeft, John D.

1984-01-01

This study describes and demonstrates two alternate methods for evaluating the relative costs and benefits of artificial groundwater recharge using percolation ponds. The first analysis considers the benefits to be the reduction of pumping lifts and land subsidence; the second considers benefits as the alternative costs of a comparable surface delivery system. Example computations are carried out for an existing artificial recharge program in Santa Clara Valley in California. A computer groundwater model is used to estimate both the average long term and the drought period effects of artificial recharge in the study area. Results indicate that the costs of artificial recharge are considerably smaller than the alternative costs of an equivalent surface system. Refs.

Computer-Aided Design and Computer-Aided Manufacturing Hydroxyapatite/Epoxide Acrylate Maleic Compound Construction for Craniomaxillofacial Bone Defects.

PubMed

Zhang, Lei; Shen, Shunyao; Yu, Hongbo; Shen, Steve Guofang; Wang, Xudong

2015-07-01

The aim of this study was to investigate the use of computer-aided design and computer-aided manufacturing hydroxyapatite (HA)/epoxide acrylate maleic (EAM) compound construction artificial implants for craniomaxillofacial bone defects. Computed tomography, computer-aided design/computer-aided manufacturing and three-dimensional reconstruction, as well as rapid prototyping were performed in 12 patients between 2008 and 2013. The customized HA/EAM compound artificial implants were manufactured through selective laser sintering using a rapid prototyping machine into the exact geometric shapes of the defect. The HA/EAM compound artificial implants were then implanted during surgical reconstruction. Color-coded superimpositions demonstrated the discrepancy between the virtual plan and achieved results using Geomagic Studio. As a result, the HA/EAM compound artificial bone implants were perfectly matched with the facial areas that needed reconstruction. The postoperative aesthetic and functional results were satisfactory. The color-coded superimpositions demonstrated good consistency between the virtual plan and achieved results. The three-dimensional maximum deviation is 2.12 ± 0.65  mm and the three-dimensional mean deviation is 0.27 ± 0.07  mm. No facial nerve weakness or pain was observed at the follow-up examinations. Only 1 implant had to be removed 2 months after the surgery owing to severe local infection. No other complication was noted during the follow-up period. In conclusion, computer-aided, individually fabricated HA/EAM compound construction artificial implant was a good craniomaxillofacial surgical technique that yielded improved aesthetic results and functional recovery after reconstruction.

Templet Web: the use of volunteer computing approach in PaaS-style cloud

NASA Astrophysics Data System (ADS)

Vostokin, Sergei; Artamonov, Yuriy; Tsarev, Daniil

2018-03-01

This article presents the Templet Web cloud service. The service is designed for high-performance scientific computing automation. The use of high-performance technology is specifically required by new fields of computational science such as data mining, artificial intelligence, machine learning, and others. Cloud technologies provide a significant cost reduction for high-performance scientific applications. The main objectives to achieve this cost reduction in the Templet Web service design are: (a) the implementation of "on-demand" access; (b) source code deployment management; (c) high-performance computing programs development automation. The distinctive feature of the service is the approach mainly used in the field of volunteer computing, when a person who has access to a computer system delegates his access rights to the requesting user. We developed an access procedure, algorithms, and software for utilization of free computational resources of the academic cluster system in line with the methods of volunteer computing. The Templet Web service has been in operation for five years. It has been successfully used for conducting laboratory workshops and solving research problems, some of which are considered in this article. The article also provides an overview of research directions related to service development.

The beginning of the space age: information and mathematical aspect. To the 60th anniversary of the launch of the first sputnik

NASA Astrophysics Data System (ADS)

Sushkevich, T. A.

2017-11-01

60 years ago, on 4 October 1957, the USSR successfully launched into space the FIRST SPUTNIK (artificial Earth satellite). From this date begins the countdown of the space age. Information and mathematical software is an integral component of any space project. Discusses the history and future of space exploration and the role of mathematics and computers. For illustration, presents a large list of publications. It is important to pay attention to the role of mathematics and computer science in space projects and research, remote sensing problems, the evolution of the Earth's environment and climate, where the theory of radiation transfer plays a key role, and the achievements of Russian scientists at the dawn of the space age.

Center for Computational Structures Technology

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Perry, Ferman W.

1995-01-01

The Center for Computational Structures Technology (CST) is intended to serve as a focal point for the diverse CST research activities. The CST activities include the use of numerical simulation and artificial intelligence methods in modeling, analysis, sensitivity studies, and optimization of flight-vehicle structures. The Center is located at NASA Langley and is an integral part of the School of Engineering and Applied Science of the University of Virginia. The key elements of the Center are: (1) conducting innovative research on advanced topics of CST; (2) acting as pathfinder by demonstrating to the research community what can be done (high-potential, high-risk research); (3) strong collaboration with NASA scientists and researchers from universities and other government laboratories; and (4) rapid dissemination of CST to industry, through integration of industrial personnel into the ongoing research efforts.

Camera systems in human motion analysis for biomedical applications

NASA Astrophysics Data System (ADS)

Chin, Lim Chee; Basah, Shafriza Nisha; Yaacob, Sazali; Juan, Yeap Ewe; Kadir, Aida Khairunnisaa Ab.

2015-05-01

Human Motion Analysis (HMA) system has been one of the major interests among researchers in the field of computer vision, artificial intelligence and biomedical engineering and sciences. This is due to its wide and promising biomedical applications, namely, bio-instrumentation for human computer interfacing and surveillance system for monitoring human behaviour as well as analysis of biomedical signal and image processing for diagnosis and rehabilitation applications. This paper provides an extensive review of the camera system of HMA, its taxonomy, including camera types, camera calibration and camera configuration. The review focused on evaluating the camera system consideration of the HMA system specifically for biomedical applications. This review is important as it provides guidelines and recommendation for researchers and practitioners in selecting a camera system of the HMA system for biomedical applications.

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

NASA Astrophysics Data System (ADS)

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.

Artificial neural network detects human uncertainty

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Frolov, Nikita S.; Maksimenko, Vladimir A.; Makarov, Vladimir V.; Koronovskii, Alexey A.; Garcia-Prieto, Juan; Antón-Toro, Luis Fernando; Maestú, Fernando; Pisarchik, Alexander N.

2018-03-01

Artificial neural networks (ANNs) are known to be a powerful tool for data analysis. They are used in social science, robotics, and neurophysiology for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience, ANNs allow the recognition of specific forms of brain activity from multichannel EEG or MEG data. This makes the ANN an efficient computational core for brain-machine systems. However, despite significant achievements of artificial intelligence in recognition and classification of well-reproducible patterns of neural activity, the use of ANNs for recognition and classification of patterns in neural networks still requires additional attention, especially in ambiguous situations. According to this, in this research, we demonstrate the efficiency of application of the ANN for classification of human MEG trials corresponding to the perception of bistable visual stimuli with different degrees of ambiguity. We show that along with classification of brain states associated with multistable image interpretations, in the case of significant ambiguity, the ANN can detect an uncertain state when the observer doubts about the image interpretation. With the obtained results, we describe the possible application of ANNs for detection of bistable brain activity associated with difficulties in the decision-making process.

Deep learning for computational chemistry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goh, Garrett B.; Hodas, Nathan O.; Vishnu, Abhinav

The rise and fall of artificial neural networks is well documented in the scientific literature of both the fields of computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on “deep” neural networks. Within the last few years, we have seen the transformative impact of deep learning the computer science domain, notably in speech recognition and computer vision, to the extent that the majority of practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. Inmore » this review, we provide an introductory overview into the theory of deep neural networks and their unique properties as compared to traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including QSAR, virtual screening, protein structure modeling, QM calculations, materials synthesis and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non neural networks state-of-the-art models across disparate research topics, and deep neural network based models often exceeded the “glass ceiling” expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a useful tool and may grow into a pivotal role for various challenges in the computational chemistry field.« less

Fuzzy Logic, Neural Networks, Genetic Algorithms: Views of Three Artificial Intelligence Concepts Used in Modeling Scientific Systems

ERIC Educational Resources Information Center

Sunal, Cynthia Szymanski; Karr, Charles L.; Sunal, Dennis W.

2003-01-01

Students' conceptions of three major artificial intelligence concepts used in the modeling of systems in science, fuzzy logic, neural networks, and genetic algorithms were investigated before and after a higher education science course. Students initially explored their prior ideas related to the three concepts through active tasks. Then,…

Initiative for safe driving and enhanced utilization of crash data

NASA Astrophysics Data System (ADS)

Wagner, John F.

1994-03-01

This initiative addresses the utilization of current technology to increase the efficiency of police officers to complete required Driving Under the Influence (DUI) forms and to enhance their ability to acquire and record crash and accident information. The project is a cooperative program among the New Mexico Alliance for Transportation Research (ATR), Science Applications International Corporation (SAIC), Los Alamos National Laboratory, and the New Mexico State Highway and Transportation Department. The approach utilizes an in-car computer and associated sensors for information acquisition and recording. Los Alamos artificial intelligence technology is leveraged to ensure ease of data entry and use.

Bioinspired Principles for Large-Scale Networked Sensor Systems: An Overview

PubMed Central

Jacobsen, Rune Hylsberg; Zhang, Qi; Toftegaard, Thomas Skjødeberg

2011-01-01

Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy. PMID:22163841

A survey of SAT solver

NASA Astrophysics Data System (ADS)

Gong, Weiwei; Zhou, Xu

2017-06-01

In Computer Science, the Boolean Satisfiability Problem(SAT) is the problem of determining if there exists an interpretation that satisfies a given Boolean formula. SAT is one of the first problems that was proven to be NP-complete, which is also fundamental to artificial intelligence, algorithm and hardware design. This paper reviews the main algorithms of the SAT solver in recent years, including serial SAT algorithms, parallel SAT algorithms, SAT algorithms based on GPU, and SAT algorithms based on FPGA. The development of SAT is analyzed comprehensively in this paper. Finally, several possible directions for the development of the SAT problem are proposed.

Designing a connectionist network supercomputer.

PubMed

Asanović, K; Beck, J; Feldman, J; Morgan, N; Wawrzynek, J

1993-12-01

This paper describes an effort at UC Berkeley and the International Computer Science Institute to develop a supercomputer for artificial neural network applications. Our perspective has been strongly influenced by earlier experiences with the construction and use of a simpler machine. In particular, we have observed Amdahl's Law in action in our designs and those of others. These observations inspire attention to many factors beyond fast multiply-accumulate arithmetic. We describe a number of these factors along with rough expressions for their influence and then give the applications targets, machine goals and the system architecture for the machine we are currently designing.

Introduction to autonomous mobile robotics using Lego Mindstorms NXT

NASA Astrophysics Data System (ADS)

Akın, H. Levent; Meriçli, Çetin; Meriçli, Tekin

2013-12-01

Teaching the fundamentals of robotics to computer science undergraduates requires designing a well-balanced curriculum that is complemented with hands-on applications on a platform that allows rapid construction of complex robots, and implementation of sophisticated algorithms. This paper describes such an elective introductory course where the Lego Mindstorms NXT kits are used as the robot platform. The aims, scope and contents of the course are presented, and the design of the laboratory sessions as well as the term projects, which address several core problems of robotics and artificial intelligence simultaneously, are explained in detail.

Emergence, Agency, and Interaction-Notes from the Field.

PubMed

Penny, Simon

2015-01-01

This article describes the development of several interactive installations and robotic artworks developed through the 1990s and the technological, theoretical, and discursive context in which those works arose. The main works discussed are Petit Mal (1989-1995), Sympathetic Sentience (1996-1997), Fugitive I (1996-1997), Traces (1998-1999), and Fugitive II (2001-2004)-full documentation at ( www.simonpenny.net/works ). These works were motivated by a critical analysis of cognitivist computer science, which contrasted with notions of embodied experience arising from the arts. The works address questions of agency and interaction, informed by cybernetics and artificial life.

Computational Environments and Analysis methods available on the NCI High Performance Computing (HPC) and High Performance Data (HPD) Platform

NASA Astrophysics Data System (ADS)

Evans, B. J. K.; Foster, C.; Minchin, S. A.; Pugh, T.; Lewis, A.; Wyborn, L. A.; Evans, B. J.; Uhlherr, A.

2014-12-01

The National Computational Infrastructure (NCI) has established a powerful in-situ computational environment to enable both high performance computing and data-intensive science across a wide spectrum of national environmental data collections - in particular climate, observational data and geoscientific assets. This paper examines 1) the computational environments that supports the modelling and data processing pipelines, 2) the analysis environments and methods to support data analysis, and 3) the progress in addressing harmonisation of the underlying data collections for future transdisciplinary research that enable accurate climate projections. NCI makes available 10+ PB major data collections from both the government and research sectors based on six themes: 1) weather, climate, and earth system science model simulations, 2) marine and earth observations, 3) geosciences, 4) terrestrial ecosystems, 5) water and hydrology, and 6) astronomy, social and biosciences. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. The data is largely sourced from NCI's partners (which include the custodians of many of the national scientific records), major research communities, and collaborating overseas organisations. The data is accessible within an integrated HPC-HPD environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large scale and high-bandwidth Lustre filesystems. This computational environment supports a catalogue of integrated reusable software and workflows from earth system and ecosystem modelling, weather research, satellite and other observed data processing and analysis. To enable transdisciplinary research on this scale, data needs to be harmonised so that researchers can readily apply techniques and software across the corpus of data available and not be constrained to work within artificial disciplinary boundaries. Future challenges will involve the further integration and analysis of this data across the social sciences to facilitate the impacts across the societal domain, including timely analysis to more accurately predict and forecast future climate and environmental state.

Computer graphics testbed to simulate and test vision systems for space applications

NASA Technical Reports Server (NTRS)

Cheatham, John B.

1991-01-01

Artificial intelligence concepts are applied to robotics. Artificial neural networks, expert systems and laser imaging techniques for autonomous space robots are being studied. A computer graphics laser range finder simulator developed by Wu has been used by Weiland and Norwood to study use of artificial neural networks for path planning and obstacle avoidance. Interest is expressed in applications of CLIPS, NETS, and Fuzzy Control. These applications are applied to robot navigation.

Developing Deep Learning Applications for Life Science and Pharma Industry.

PubMed

Siegismund, Daniel; Tolkachev, Vasily; Heyse, Stephan; Sick, Beate; Duerr, Oliver; Steigele, Stephan

2018-06-01

Deep Learning has boosted artificial intelligence over the past 5 years and is seen now as one of the major technological innovation areas, predicted to replace lots of repetitive, but complex tasks of human labor within the next decade. It is also expected to be 'game changing' for research activities in pharma and life sciences, where large sets of similar yet complex data samples are systematically analyzed. Deep learning is currently conquering formerly expert domains especially in areas requiring perception, previously not amenable to standard machine learning. A typical example is the automated analysis of images which are typically produced en-masse in many domains, e. g., in high-content screening or digital pathology. Deep learning enables to create competitive applications in so-far defined core domains of 'human intelligence'. Applications of artificial intelligence have been enabled in recent years by (i) the massive availability of data samples, collected in pharma driven drug programs (='big data') as well as (ii) deep learning algorithmic advancements and (iii) increase in compute power. Such applications are based on software frameworks with specific strengths and weaknesses. Here, we introduce typical applications and underlying frameworks for deep learning with a set of practical criteria for developing production ready solutions in life science and pharma research. Based on our own experience in successfully developing deep learning applications we provide suggestions and a baseline for selecting the most suited frameworks for a future-proof and cost-effective development. © Georg Thieme Verlag KG Stuttgart · New York.

Finding fossils in new ways: an artificial neural network approach to predicting the location of productive fossil localities.

PubMed

Anemone, Robert; Emerson, Charles; Conroy, Glenn

2011-01-01

Chance and serendipity have long played a role in the location of productive fossil localities by vertebrate paleontologists and paleoanthropologists. We offer an alternative approach, informed by methods borrowed from the geographic information sciences and using recent advances in computer science, to more efficiently predict where fossil localities might be found. Our model uses an artificial neural network (ANN) that is trained to recognize the spectral characteristics of known productive localities and other land cover classes, such as forest, wetlands, and scrubland, within a study area based on the analysis of remotely sensed (RS) imagery. Using these spectral signatures, the model then classifies other pixels throughout the study area. The results of the neural network classification can be examined and further manipulated within a geographic information systems (GIS) software package. While we have developed and tested this model on fossil mammal localities in deposits of Paleocene and Eocene age in the Great Divide Basin of southwestern Wyoming, a similar analytical approach can be easily applied to fossil-bearing sedimentary deposits of any age in any part of the world. We suggest that new analytical tools and methods of the geographic sciences, including remote sensing and geographic information systems, are poised to greatly enrich paleoanthropological investigations, and that these new methods should be embraced by field workers in the search for, and geospatial analysis of, fossil primates and hominins. Copyright © 2011 Wiley-Liss, Inc.

Intelligent supercomputers: the Japanese computer sputnik

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walter, G.

1983-11-01

Japan's government-supported fifth-generation computer project has had a pronounced effect on the American computer and information systems industry. The US firms are intensifying their research on and production of intelligent supercomputers, a combination of computer architecture and artificial intelligence software programs. While the present generation of computers is built for the processing of numbers, the new supercomputers will be designed specifically for the solution of symbolic problems and the use of artificial intelligence software. This article discusses new and exciting developments that will increase computer capabilities in the 1990s. 4 references.

Comparative randomised controlled clinical trial of a herbal eye drop with artificial tear and placebo in computer vision syndrome.

PubMed

Biswas, N R; Nainiwal, S K; Das, G K; Langan, U; Dadeya, S C; Mongre, P K; Ravi, A K; Baidya, P

2003-03-01

A comparative randomised double masked multicentric clinical trial has been conducted to find out the efficacy and safety of a herbal eye drop preparation, itone eye drops with artificial tear and placebo in 120 patients with computer vision syndrome. Patients using computer for at least 2 hours continuosly per day having symptoms of irritation, foreign body sensation, watering, redness, headache, eyeache and signs of conjunctival congestion, mucous/debris, corneal filaments, corneal staining or lacrimal lake were included in this study. Every patient was instructed to put two drops of either herbal drugs or placebo or artificial tear in the eyes regularly four times for 6 weeks. Objective and subjective findings were recorded at bi-weekly intervals up to six weeks. Side-effects, if any, were also noted. In computer vision syndrome the herbal eye drop preparation was found significantly better than artificial tear (p < 0.01). No side-effects were noted by any of the drugs. Both subjective and objective improvements were observed in itone treated cases. So, itone can be considered as a useful drug in computer vision syndrome.

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

NASA Astrophysics Data System (ADS)

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.

Accelerating artificial intelligence with reconfigurable computing

NASA Astrophysics Data System (ADS)

Cieszewski, Radoslaw

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

A Computer-Aided Instruction Program for Teaching the TOPS20-MM Facility on the DDN (Defense Data Network)

DTIC Science & Technology

1988-06-01

Continue on reverse if necessary and identify by block number) FIELD GROUP SUB-GROUP Computer Assisted Instruction; Artificial Intelligence 194...while he/she tries to perform given tasks. Means-ends analysis, a classic technique for solving search problems in Artificial Intelligence, has been...he/she tries to perform given tasks. Means-ends analysis, a classic technique for solving search problems in Artificial Intelligence, has been used

How Computers Are Used in the Teaching of Music and Speculations about How Artificial Intelligence Could Be Applied to Radically Improve the Learning of Compositional Skills. CITE Report No. 6.

ERIC Educational Resources Information Center

Holland, Simon

This paper forms part of a preliminary survey for work on the application of artificial intelligence theories and techniques to the learning of music composition skills. The paper deals with present day applications of computers to the teaching of music and speculations about how artificial intelligence might be used to foster music composition in…

Quantum-like Probabilistic Models Outside Physics

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei

We present a quantum-like (QL) model in that contexts (complexes of e.g. mental, social, biological, economic or even political conditions) are represented by complex probability amplitudes. This approach gives the possibility to apply the mathematical quantum formalism to probabilities induced in any domain of science. In our model quantum randomness appears not as irreducible randomness (as it is commonly accepted in conventional quantum mechanics, e.g. by von Neumann and Dirac), but as a consequence of obtaining incomplete information about a system. We pay main attention to the QL description of processing of incomplete information. Our QL model can be useful in cognitive, social and political sciences as well as economics and artificial intelligence. In this paper we consider in a more detail one special application — QL modeling of brain's functioning. The brain is modeled as a QL-computer.

Science of the science, drug discovery and artificial neural networks.

PubMed

Patel, Jigneshkumar

2013-03-01

Drug discovery process many times encounters complex problems, which may be difficult to solve by human intelligence. Artificial Neural Networks (ANNs) are one of the Artificial Intelligence (AI) technologies used for solving such complex problems. ANNs are widely used for primary virtual screening of compounds, quantitative structure activity relationship studies, receptor modeling, formulation development, pharmacokinetics and in all other processes involving complex mathematical modeling. Despite having such advanced technologies and enough understanding of biological systems, drug discovery is still a lengthy, expensive, difficult and inefficient process with low rate of new successful therapeutic discovery. In this paper, author has discussed the drug discovery science and ANN from very basic angle, which may be helpful to understand the application of ANN for drug discovery to improve efficiency.

What Machines Need to Learn to Support Human Problem-Solving

NASA Technical Reports Server (NTRS)

Vera, Alonso

2017-01-01

In the development of intelligent systems that interact with humans, there is often confusion between how the system functions with respect to the humans it interacts with and how it interfaces with those humans. The former is a much deeper challenge than the latter it requires a system-level understanding of evolving human roles as well as an understanding of what humans need to know (and when) in order to perform their tasks. This talk will focus on some of the challenges in getting this right as well as on the type of research and development that results in successful human-autonomy teaming. Brief Bio: Dr. Alonso Vera is Chief of the Human Systems Integration Division at NASA Ames Research Center. His expertise is in human-computer interaction, information systems, artificial intelligence, and computational human performance modeling. He has led the design, development and deployment of mission software systems across NASA robotic and human space flight missions, including Mars Exploration Rovers, Phoenix Mars Lander, ISS, Constellation, and Exploration Systems. Dr. Vera received a Bachelor of Science with First Class Honors from McGill University in 1985 and a Ph.D. from Cornell University in 1991. He went on to a Post-Doctoral Fellowship in the School of Computer Science at Carnegie Mellon University from 1990-93.

Computational protein design: a review

NASA Astrophysics Data System (ADS)

Coluzza, Ivan

2017-04-01

Proteins are one of the most versatile modular assembling systems in nature. Experimentally, more than 110 000 protein structures have been identified and more are deposited every day in the Protein Data Bank. Such an enormous structural variety is to a first approximation controlled by the sequence of amino acids along the peptide chain of each protein. Understanding how the structural and functional properties of the target can be encoded in this sequence is the main objective of protein design. Unfortunately, rational protein design remains one of the major challenges across the disciplines of biology, physics and chemistry. The implications of solving this problem are enormous and branch into materials science, drug design, evolution and even cryptography. For instance, in the field of drug design an effective computational method to design protein-based ligands for biological targets such as viruses, bacteria or tumour cells, could give a significant boost to the development of new therapies with reduced side effects. In materials science, self-assembly is a highly desired property and soon artificial proteins could represent a new class of designable self-assembling materials. The scope of this review is to describe the state of the art in computational protein design methods and give the reader an outline of what developments could be expected in the near future.

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

ERIC Educational Resources Information Center

Moore, Gwendolyn B.; And Others

1986-01-01

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

Computer Intelligence: Unlimited and Untapped.

ERIC Educational Resources Information Center

Staples, Betsy

1983-01-01

Herbert Simon (Nobel prize-winning economist/professor) expresses his views on human and artificial intelligence, problem solving, inventing concepts, and the future. Includes comments on expert systems, state of the art in artificial intelligence, robotics, and "Bacon," a computer program that finds scientific laws hidden in raw data.…

Computer graphics testbed to simulate and test vision systems for space applications

NASA Technical Reports Server (NTRS)

Cheatham, John B.

1991-01-01

Research activity has shifted from computer graphics and vision systems to the broader scope of applying concepts of artificial intelligence to robotics. Specifically, the research is directed toward developing Artificial Neural Networks, Expert Systems, and Laser Imaging Techniques for Autonomous Space Robots.

Applying Gradient Descent in Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Cui, Nan

2018-04-01

With the development of the integrated circuit and computer science, people become caring more about solving practical issues via information technologies. Along with that, a new subject called Artificial Intelligent (AI) comes up. One popular research interest of AI is about recognition algorithm. In this paper, one of the most common algorithms, Convolutional Neural Networks (CNNs) will be introduced, for image recognition. Understanding its theory and structure is of great significance for every scholar who is interested in this field. Convolution Neural Network is an artificial neural network which combines the mathematical method of convolution and neural network. The hieratical structure of CNN provides it reliable computer speed and reasonable error rate. The most significant characteristics of CNNs are feature extraction, weight sharing and dimension reduction. Meanwhile, combining with the Back Propagation (BP) mechanism and the Gradient Descent (GD) method, CNNs has the ability to self-study and in-depth learning. Basically, BP provides an opportunity for backwardfeedback for enhancing reliability and GD is used for self-training process. This paper mainly discusses the CNN and the related BP and GD algorithms, including the basic structure and function of CNN, details of each layer, the principles and features of BP and GD, and some examples in practice with a summary in the end.

An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part C: Basic AI topics

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1983-01-01

Readily understandable overviews of search oriented problem solving, knowledge representation, and computational logic are provided. Mechanization, automation and artificial intelligence are discussed as well as how they interrelate.

3D artificial bones for bone repair prepared by computed tomography-guided fused deposition modeling for bone repair.

PubMed

Xu, Ning; Ye, Xiaojian; Wei, Daixu; Zhong, Jian; Chen, Yuyun; Xu, Guohua; He, Dannong

2014-09-10

The medical community has expressed significant interest in the development of new types of artificial bones that mimic natural bones. In this study, computed tomography (CT)-guided fused deposition modeling (FDM) was employed to fabricate polycaprolactone (PCL)/hydroxyapatite (HA) and PCL 3D artificial bones to mimic natural goat femurs. The in vitro mechanical properties, in vitro cell biocompatibility, and in vivo performance of the artificial bones in a long load-bearing goat femur bone segmental defect model were studied. All of the results indicate that CT-guided FDM is a simple, convenient, relatively low-cost method that is suitable for fabricating natural bonelike artificial bones. Moreover, PCL/HA 3D artificial bones prepared by CT-guided FDM have more close mechanics to natural bone, good in vitro cell biocompatibility, biodegradation ability, and appropriate in vivo new bone formation ability. Therefore, PCL/HA 3D artificial bones could be potentially be of use in the treatment of patients with clinical bone defects.

Human-technology Integration

NASA Astrophysics Data System (ADS)

Mullen, Katharine M.

Human-technology integration is the replacement of human parts and extension of human capabilities with engineered devices and substrates. Its result is hybrid biological-artificial systems. We discuss here four categories of products furthering human-technology integration: wearable computers, pervasive computing environments, engineered tissues and organs, and prosthetics, and introduce examples of currently realized systems in each category. We then note that realization of a completely artificial sytem via the path of human-technology integration presents the prospect of empirical confirmation of an aware artificially embodied system.

Artificial Intelligence in Precision Cardiovascular Medicine.

PubMed

Krittanawong, Chayakrit; Zhang, HongJu; Wang, Zhen; Aydar, Mehmet; Kitai, Takeshi

2017-05-30

Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes, learning capacity, and knowledge storage. AI techniques have been applied in cardiovascular medicine to explore novel genotypes and phenotypes in existing diseases, improve the quality of patient care, enable cost-effectiveness, and reduce readmission and mortality rates. Over the past decade, several machine-learning techniques have been used for cardiovascular disease diagnosis and prediction. Each problem requires some degree of understanding of the problem, in terms of cardiovascular medicine and statistics, to apply the optimal machine-learning algorithm. In the near future, AI will result in a paradigm shift toward precision cardiovascular medicine. The potential of AI in cardiovascular medicine is tremendous; however, ignorance of the challenges may overshadow its potential clinical impact. This paper gives a glimpse of AI's application in cardiovascular clinical care and discusses its potential role in facilitating precision cardiovascular medicine. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

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

ERIC Educational Resources Information Center

Moore, Gwendolyn B.; And Others

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

Command History for 1990

DTIC Science & Technology

1991-05-01

Marine Corps Tiaining Systems (CBESS) memorization training Inteligence Center, Dam Neck Threat memorization training Commander Tactical Wings, Atlantic...News Shipbuilding Technical training AEGIS Training Center, Dare Artificial Intelligence (Al) Tools Computerized firm-end analysis tools NETSCPAC...Technology Department and provides computational and electronic mail support for research in areas of artificial intelligence, computer-assisted instruction

Artificial Intelligence and the High School Computer Curriculum.

ERIC Educational Resources Information Center

Dillon, Richard W.

1993-01-01

Describes a four-part curriculum that can serve as a model for incorporating artificial intelligence (AI) into the high school computer curriculum. The model includes examining questions fundamental to AI, creating and designing an expert system, language processing, and creating programs that integrate machine vision with robotics and…

A Challenge to Watson

ERIC Educational Resources Information Center

Detterman, Douglas K.

2011-01-01

Watson's Jeopardy victory raises the question of the similarity of artificial intelligence and human intelligence. Those of us who study human intelligence issue a challenge to the artificial intelligence community. We will construct a unique battery of tests for any computer that would provide an actual IQ score for the computer. This is the same…

Artificial Intelligence Methods in Computer-Based Instructional Design. The Minnesota Adaptive Instructional System.

ERIC Educational Resources Information Center

Tennyson, Robert

1984-01-01

Reviews educational applications of artificial intelligence and presents empirically-based design variables for developing a computer-based instruction management system. Taken from a programmatic research effort based on the Minnesota Adaptive Instructional System, variables include amount and sequence of instruction, display time, advisement,…

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

NASA Technical Reports Server (NTRS)

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.

Data Characterization Using Artificial-Star Tests: Performance Evaluation

NASA Astrophysics Data System (ADS)

Hu, Yi; Deng, Licai; de Grijs, Richard; Liu, Qiang

2011-01-01

Traditional artificial-star tests are widely applied to photometry in crowded stellar fields. However, to obtain reliable binary fractions (and their uncertainties) of remote, dense, and rich star clusters, one needs to recover huge numbers of artificial stars. Hence, this will consume much computation time for data reduction of the images to which the artificial stars must be added. In this article, we present a new method applicable to data sets characterized by stable, well-defined, point-spread functions, in which we add artificial stars to the retrieved-data catalog instead of to the raw images. Taking the young Large Magellanic Cloud cluster NGC 1818 as an example, we compare results from both methods and show that they are equivalent, while our new method saves significant computational time.

Simulation of Blood flow in Artificial Heart Valve Design through Left heart

NASA Astrophysics Data System (ADS)

Hafizah Mokhtar, N.; Abas, Aizat

2018-05-01

In this work, an artificial heart valve is designed for use in real heart with further consideration on the effect of thrombosis, vorticity, and stress. The design of artificial heart valve model is constructed by Computer-aided design (CAD) modelling and simulated using Computational fluid dynamic (CFD) software. The effect of blood flow pattern, velocity and vorticity of the artificial heart valve design has been analysed in this research work. Based on the results, the artificial heart valve design shows that it has a Doppler velocity index that is less than the allowable standards for the left heart with values of more than 0.30 and less than 2.2. These values are safe to be used as replacement of the human heart valve.

Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.

PubMed

Kriegeskorte, Nikolaus

2015-11-24

Recent advances in neural network modeling have enabled major strides in computer vision and other artificial intelligence applications. Human-level visual recognition abilities are coming within reach of artificial systems. Artificial neural networks are inspired by the brain, and their computations could be implemented in biological neurons. Convolutional feedforward networks, which now dominate computer vision, take further inspiration from the architecture of the primate visual hierarchy. However, the current models are designed with engineering goals, not to model brain computations. Nevertheless, initial studies comparing internal representations between these models and primate brains find surprisingly similar representational spaces. With human-level performance no longer out of reach, we are entering an exciting new era, in which we will be able to build biologically faithful feedforward and recurrent computational models of how biological brains perform high-level feats of intelligence, including vision.

Patch models and their applications to multivehicle command and control.

PubMed

Rao, Venkatesh G; D'Andrea, Raffaello

2007-06-01

We introduce patch models, a computational modeling formalism for multivehicle combat domains, based on spatiotemporal abstraction methods developed in the computer science community. The framework yields models that are expressive enough to accommodate nontrivial controlled vehicle dynamics while being within the representational capabilities of common artificial intelligence techniques used in the construction of autonomous systems. The framework allows several key design requirements of next-generation network-centric command and control systems, such as maintenance of shared situation awareness, to be achieved. Major features include support for multiple situation models at each decision node and rapid mission plan adaptation. We describe the formal specification of patch models and our prototype implementation, i.e., Patchworks. The capabilities of patch models are validated through a combat mission simulation in Patchworks, which involves two defending teams protecting a camp from an enemy attacking team.

Projective simulation for artificial intelligence

NASA Astrophysics Data System (ADS)

Briegel, Hans J.; de Las Cuevas, Gemma

2012-05-01

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

An Argumentation Framework based on Paraconsistent Logic

NASA Astrophysics Data System (ADS)

Umeda, Yuichi; Takahashi, Takehisa; Sawamura, Hajime

Argumentation is the most representative of intelligent activities of humans. Therefore, it is natural to think that it could have many implications for artificial intelligence and computer science as well. Specifically, argumentation may be considered a most primitive capability for interaction among computational agents. In this paper we present an argumentation framework based on the four-valued paraconsistent logic. Tolerance and acceptance of inconsistency that this logic has as its logical feature allow for arguments on inconsistent knowledge bases with which we are often confronted. We introduce various concepts for argumentation, such as arguments, attack relations, argument justification, preferential criteria of arguments based on social norms, and so on, in a way proper to the four-valued paraconsistent logic. Then, we provide the fixpoint semantics and dialectical proof theory for our argumentation framework. We also give the proofs of the soundness and completeness.

Efficient Variational Quantum Simulator Incorporating Active Error Minimization

NASA Astrophysics Data System (ADS)

Li, Ying; Benjamin, Simon C.

2017-04-01

One of the key applications for quantum computers will be the simulation of other quantum systems that arise in chemistry, materials science, etc., in order to accelerate the process of discovery. It is important to ask the following question: Can this simulation be achieved using near-future quantum processors, of modest size and under imperfect control, or must it await the more distant era of large-scale fault-tolerant quantum computing? Here, we propose a variational method involving closely integrated classical and quantum coprocessors. We presume that all operations in the quantum coprocessor are prone to error. The impact of such errors is minimized by boosting them artificially and then extrapolating to the zero-error case. In comparison to a more conventional optimized Trotterization technique, we find that our protocol is efficient and appears to be fundamentally more robust against error accumulation.

Projective simulation for artificial intelligence

PubMed Central

Briegel, Hans J.; De las Cuevas, Gemma

2012-01-01

We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation. PMID:22590690

Artificial intelligence and design: Opportunities, research problems and directions

NASA Technical Reports Server (NTRS)

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 that are of intrinsic concern to AI. We present examples of current AI work on specific design tasks, and discuss new directions of research, both as extensions of current work and in the context of new design tasks where domain knowledge is either intractable or incomplete. The domains discussed include Digital Circuit Design, Mechanical Design of Rotational Transmissions, Design of Computer Architectures, Marine Design, Aircraft Design, and Design of Chemical Processes and Materials. Work in these domains is significant on technical grounds, and it is also important for economic and policy reasons.

Software Reviews.

ERIC Educational Resources Information Center

Wulfson, Stephen, Ed.

1988-01-01

Reviews seven instructional software packages covering a variety of topics. Includes: "Science Square-Off"; "The Desert"; "Science Courseware: Physical Science"; "Odell Lake"; "Safety First"; "An Experience in Artificial Intelligence"; and "Master Mapper." (TW)

New Types of Artificial Muscles for Large Stroke and High Force Applications

DTIC Science & Technology

2012-10-10

University of Texas at Dallas and include Aerogel Muscles, Torsional and Tensile Yarn Muscles, Artificial Muscles Based on Polypyrrole Laminates and...Stroke, Superelastic Carbon Nanotube Aerogel Muscles 3. Torsional and Tensile Carbon Nanotube Yarn Muscles 4. Artificial Muscles Based on...in numerous press releases and TV programs. As we reported in Science 2009, carbon nanotube aerogel sheets are the sole component of new artificial

Numerical Simulation of Flow Through an Artificial Heart

NASA Technical Reports Server (NTRS)

Rogers, Stuart E.; Kutler, Paul; Kwak, Dochan; Kiris, Cetin

1989-01-01

A solution procedure was developed that solves the unsteady, incompressible Navier-Stokes equations, and was used to numerically simulate viscous incompressible flow through a model of the Pennsylvania State artificial heart. The solution algorithm is based on the artificial compressibility method, and uses flux-difference splitting to upwind the convective terms; a line-relaxation scheme is used to solve the equations. The time-accuracy of the method is obtained by iteratively solving the equations at each physical time step. The artificial heart geometry involves a piston-type action with a moving solid wall. A single H-grid is fit inside the heart chamber. The grid is continuously compressed and expanded with a constant number of grid points to accommodate the moving piston. The computational domain ends at the valve openings where nonreflective boundary conditions based on the method of characteristics are applied. Although a number of simplifing assumptions were made regarding the geometry, the computational results agreed reasonably well with an experimental picture. The computer time requirements for this flow simulation, however, are quite extensive. Computational study of this type of geometry would benefit greatly from improvements in computer hardware speed and algorithm efficiency enhancements.

Computational evolution: taking liberties.

PubMed

Correia, Luís

2010-09-01

Evolution has, for a long time, inspired computer scientists to produce computer models mimicking its behavior. Evolutionary algorithm (EA) is one of the areas where this approach has flourished. EAs have been used to model and study evolution, but they have been especially developed for their aptitude as optimization tools for engineering. Developed models are quite simple in comparison with their natural sources of inspiration. However, since EAs run on computers, we have the freedom, especially in optimization models, to test approaches both realistic and outright speculative, from the biological point of view. In this article, we discuss different common evolutionary algorithm models, and then present some alternatives of interest. These include biologically inspired models, such as co-evolution and, in particular, symbiogenetics and outright artificial operators and representations. In each case, the advantages of the modifications to the standard model are identified. The other area of computational evolution, which has allowed us to study basic principles of evolution and ecology dynamics, is the development of artificial life platforms for open-ended evolution of artificial organisms. With these platforms, biologists can test theories by directly manipulating individuals and operators, observing the resulting effects in a realistic way. An overview of the most prominent of such environments is also presented. If instead of artificial platforms we use the real world for evolving artificial life, then we are dealing with evolutionary robotics (ERs). A brief description of this area is presented, analyzing its relations to biology. Finally, we present the conclusions and identify future research avenues in the frontier of computation and biology. Hopefully, this will help to draw the attention of more biologists and computer scientists to the benefits of such interdisciplinary research.

What's statistical about learning? Insights from modelling statistical learning as a set of memory processes

PubMed Central

2017-01-01

Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274, 1926–1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105, 2745–2750; Thiessen & Yee 2010 Child Development 81, 1287–1303; Saffran 2002 Journal of Memory and Language 47, 172–196; Misyak & Christiansen 2012 Language Learning 62, 302–331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39, 246–263; Thiessen et al. 2013 Psychological Bulletin 139, 792–814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik 2013 Cognitive Science 37, 310–343). This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences'. PMID:27872374

What's statistical about learning? Insights from modelling statistical learning as a set of memory processes.

PubMed

Thiessen, Erik D

2017-01-05

Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274: , 1926-1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105: , 2745-2750; Thiessen & Yee 2010 Child Development 81: , 1287-1303; Saffran 2002 Journal of Memory and Language 47: , 172-196; Misyak & Christiansen 2012 Language Learning 62: , 302-331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39: , 246-263; Thiessen et al. 2013 Psychological Bulletin 139: , 792-814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik 2013 Cognitive Science 37: , 310-343).This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

THRESHOLD LOGIC IN ARTIFICIAL INTELLIGENCE

DTIC Science & Technology

COMPUTER LOGIC, ARTIFICIAL INTELLIGENCE , BIONICS, GEOMETRY, INPUT OUTPUT DEVICES, LINEAR PROGRAMMING, MATHEMATICAL LOGIC, MATHEMATICAL PREDICTION, NETWORKS, PATTERN RECOGNITION, PROBABILITY, SWITCHING CIRCUITS, SYNTHESIS

Analysis of the frontier technology of agricultural IoT and its predication research

NASA Astrophysics Data System (ADS)

Han, Shuqing; Zhang, Jianhua; Zhu, Mengshuai; Wu, Jianzhai; Shen, Chen; Kong, Fantao

2017-09-01

Agricultural IoT (Internet of Things) develops rapidly. Nanotechnology, biotechnology and optoelectronic technology are successfully integrated into the agricultural sensor technology. Big data, cloud computing and artificial intelligence technology have also been successfully used in IoT. This paper carries out the research on integration of agricultural sensor technology, nanotechnology, biotechnology and optoelectronic technology and the application of big data, cloud computing and artificial intelligence technology in agricultural IoT. The advantages and development of the integration of nanotechnology, biotechnology and optoelectronic technology with agricultural sensor technology were discussed. The application of big data, cloud computing and artificial intelligence technology in IoT and their development trend were analysed.

Artificial life and Piaget.

PubMed

Mueller, Ulrich; Grobman, K H.

2003-04-01

Artificial life provides important theoretical and methodological tools for the investigation of Piaget's developmental theory. This new method uses artificial neural networks to simulate living phenomena in a computer. A recent study by Parisi and Schlesinger suggests that artificial life might reinvigorate the Piagetian framework. We contrast artificial life with traditional cognitivist approaches, discuss the role of innateness in development, and examine the relation between physiological and psychological explanations of intelligent behaviour.

Introduction to Concepts in Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Niebur, Dagmar

1995-01-01

This introduction to artificial neural networks summarizes some basic concepts of computational neuroscience and the resulting models of artificial neurons. The terminology of biological and artificial neurons, biological and machine learning and neural processing is introduced. The concepts of supervised and unsupervised learning are explained with examples from the power system area. Finally, a taxonomy of different types of neurons and different classes of artificial neural networks is presented.

Artificial Intelligence and Its Importance in Education.

ERIC Educational Resources Information Center

Tilmann, Martha J.

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

Towards Computational Fronesis: Verifying Contextual Appropriateness of Emotions

ERIC Educational Resources Information Center

Ptaszynski, Michal; Dybala, Pawel; Mazur, Michal; Rzepka, Rafal; Araki, Kenji; Momouchi, Yoshio

2013-01-01

This paper presents research in Contextual Affect Analysis (CAA) for the need of future application in intelligent agents, such as conversational agents or artificial tutors. The authors propose a new term, Computational Fronesis (CF), to embrace the tasks included in CAA applied to development of conversational agents such as artificial tutors.…

Artificial Intelligence, Computational Thinking, and Mathematics Education

ERIC Educational Resources Information Center

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.…

Automated Management Of Documents

NASA Technical Reports Server (NTRS)

Boy, Guy

1995-01-01

Report presents main technical issues involved in computer-integrated documentation. Problems associated with automation of management and maintenance of documents analyzed from perspectives of artificial intelligence and human factors. Technologies that may prove useful in computer-integrated documentation reviewed: these include conventional approaches to indexing and retrieval of information, use of hypertext, and knowledge-based artificial-intelligence systems.

Generative Computer-Assisted Instruction and Artificial Intelligence. Report No. 5.

ERIC Educational Resources Information Center

Sinnott, Loraine T.

This paper reviews the state-of-the-art in generative computer-assisted instruction and artificial intelligence. It divides relevant research into three areas of instructional modeling: models of the subject matter; models of the learner's state of knowledge; and models of teaching strategies. Within these areas, work sponsored by Advanced…

JPRS Report Science & Technology Japan STA 1988 White Paper Part 2.

DTIC Science & Technology

1989-12-13

artificial insemination . In connection with the "Progress of Life Sciences and Their Harmony With Mankind and Society," a theme whose importance is pointed...Research Dept. The Weather Satellite Research Department has been reorganized into the Weather Satellite / Monitoring System Research Dept. The...research on undersea greening technology (creation of seaweed farms using artificial light), and 3) research on tech- nology for probing and breeding

Physiology of man and animals in the Tenth Five-Year Plan: Proceedings of the Thirteenth Congress of the I. P. Pavlov All-Union Physiological Society

NASA Technical Reports Server (NTRS)

Lange, K. A.

1980-01-01

Research in the field of animal and human physiology is reviewed. The following topics on problems of physiological science and related fields of knowledge are discussed: neurophysiology and higher nervous activity, physiology of sensory systems, physiology of visceral systems, evolutionary and ecological physiology, physiological cybernetics, computer application in physiology, information support of physiological research, history and theory of development of physiology. Also discussed were: artificial intelligence, physiological problems of reflex therapy, correlation of structure and function of the brain, adaptation and activity, microcirculation, and physiological studies in nerve and mental diseases.

Digging deeper on "deep" learning: A computational ecology approach.

PubMed

Buscema, Massimo; Sacco, Pier Luigi

2017-01-01

We propose an alternative approach to "deep" learning that is based on computational ecologies of structurally diverse artificial neural networks, and on dynamic associative memory responses to stimuli. Rather than focusing on massive computation of many different examples of a single situation, we opt for model-based learning and adaptive flexibility. Cross-fertilization of learning processes across multiple domains is the fundamental feature of human intelligence that must inform "new" artificial intelligence.

Computational Models of Neuron-Astrocyte Interactions Lead to Improved Efficacy in the Performance of Neural Networks

PubMed Central

Alvarellos-González, Alberto; Pazos, Alejandro; Porto-Pazos, Ana B.

2012-01-01

The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem. PMID:22649480

Computational models of neuron-astrocyte interactions lead to improved efficacy in the performance of neural networks.

PubMed

Alvarellos-González, Alberto; Pazos, Alejandro; Porto-Pazos, Ana B

2012-01-01

The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem.

Science and Religious Education: A Deepening Conversation.

ERIC Educational Resources Information Center

Petersen, Rodney L.

1997-01-01

Argues that science and technology associated with research in artificial intelligence, the Human Genome Project, cosmology, and sociobiology raise questions that promote dialog between the worlds of science and religion. (DDR)

Artificial Intelligence--Applications in Education.

ERIC Educational Resources Information Center

Poirot, James L.; Norris, Cathleen A.

1987-01-01

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

Apple Fool! An Introduction to Artificial Flavors.

ERIC Educational Resources Information Center

Journal of Chemical Education, 2003

2003-01-01

Presents a science activity on consumer chemistry in which students explore artificial flavors that are commonly used in foods, such as isoamyl acetate and methyl salicylate. Includes instructor information and a student worksheet. (YDS)

Image pattern recognition supporting interactive analysis and graphical visualization

NASA Technical Reports Server (NTRS)

Coggins, James M.

1992-01-01

Image Pattern Recognition attempts to infer properties of the world from image data. Such capabilities are crucial for making measurements from satellite or telescope images related to Earth and space science problems. Such measurements can be the required product itself, or the measurements can be used as input to a computer graphics system for visualization purposes. At present, the field of image pattern recognition lacks a unified scientific structure for developing and evaluating image pattern recognition applications. The overall goal of this project is to begin developing such a structure. This report summarizes results of a 3-year research effort in image pattern recognition addressing the following three principal aims: (1) to create a software foundation for the research and identify image pattern recognition problems in Earth and space science; (2) to develop image measurement operations based on Artificial Visual Systems; and (3) to develop multiscale image descriptions for use in interactive image analysis.

Cognitive science in the era of artificial intelligence: A roadmap for reverse-engineering the infant language-learner.

PubMed

Dupoux, Emmanuel

2018-04-01

Spectacular progress in the information processing sciences (machine learning, wearable sensors) promises to revolutionize the study of cognitive development. Here, we analyse the conditions under which 'reverse engineering' language development, i.e., building an effective system that mimics infant's achievements, can contribute to our scientific understanding of early language development. We argue that, on the computational side, it is important to move from toy problems to the full complexity of the learning situation, and take as input as faithful reconstructions of the sensory signals available to infants as possible. On the data side, accessible but privacy-preserving repositories of home data have to be setup. On the psycholinguistic side, specific tests have to be constructed to benchmark humans and machines at different linguistic levels. We discuss the feasibility of this approach and present an overview of current results. Copyright © 2017 Elsevier B.V. All rights reserved.

Little AI: Playing a constructivist robot

NASA Astrophysics Data System (ADS)

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]).

Sci-Fi Science.

ERIC Educational Resources Information Center

Freudenrich, Craig C.

2000-01-01

Recommends using science fiction television episodes, novels, and films for teaching science and motivating students. Studies Newton's Law of Motion, principles of relativity, journey to Mars, interplanetary trajectories, artificial gravity, and Martian geology. Discusses science fiction's ability to capture student interest and the advantages of…

A State Cyber Hub Operations Framework

DTIC Science & Technology

2016-06-01

to communicate and sense or interact with their internal states or the external environment. Machine Learning: A type of artificial intelligence that... artificial intelligence , and computational linguistics concerned with the interactions between computers and human (natural) languages. Patching: A piece...formalizing a proof of concept for cyber initiatives and developed frameworks for operationalizing the data and intelligence produced across state

An algebraic interpretation of PSP composition.

PubMed

Vaucher, G

1998-01-01

The introduction of time in artificial neurons is a delicate problem on which many groups are working. Our approach combines some properties of biological models and the algebraic properties of McCulloch and Pitts artificial neuron (AN) (McCulloch and Pitts, 1943) to produce a new model which links both characteristics. In this extended artificial neuron, postsynaptic potentials (PSPs) are considered as numerical elements, having two degrees of freedom, on which the neuron computes operations. Modelled in this manner, a group of neurons can be seen as a computer with an asynchronous architecture. To formalize the functioning of this computer, we propose an algebra of impulses. This approach might also be interesting in the modelling of the passive electrical properties in some biological neurons.

Complex network problems in physics, computer science and biology

NASA Astrophysics Data System (ADS)

Cojocaru, Radu Ionut

There is a close relation between physics and mathematics and the exchange of ideas between these two sciences are well established. However until few years ago there was no such a close relation between physics and computer science. Even more, only recently biologists started to use methods and tools from statistical physics in order to study the behavior of complex system. In this thesis we concentrate on applying and analyzing several methods borrowed from computer science to biology and also we use methods from statistical physics in solving hard problems from computer science. In recent years physicists have been interested in studying the behavior of complex networks. Physics is an experimental science in which theoretical predictions are compared to experiments. In this definition, the term prediction plays a very important role: although the system is complex, it is still possible to get predictions for its behavior, but these predictions are of a probabilistic nature. Spin glasses, lattice gases or the Potts model are a few examples of complex systems in physics. Spin glasses and many frustrated antiferromagnets map exactly to computer science problems in the NP-hard class defined in Chapter 1. In Chapter 1 we discuss a common result from artificial intelligence (AI) which shows that there are some problems which are NP-complete, with the implication that these problems are difficult to solve. We introduce a few well known hard problems from computer science (Satisfiability, Coloring, Vertex Cover together with Maximum Independent Set and Number Partitioning) and then discuss their mapping to problems from physics. In Chapter 2 we provide a short review of combinatorial optimization algorithms and their applications to ground state problems in disordered systems. We discuss the cavity method initially developed for studying the Sherrington-Kirkpatrick model of spin glasses. We extend this model to the study of a specific case of spin glass on the Bethe lattice at zero temperature and then we apply this formalism to the K-SAT problem defined in Chapter 1. The phase transition which physicists study often corresponds to a change in the computational complexity of the corresponding computer science problem. Chapter 3 presents phase transitions which are specific to the problems discussed in Chapter 1 and also known results for the K-SAT problem. We discuss the replica method and experimental evidences of replica symmetry breaking. The physics approach to hard problems is based on replica methods which are difficult to understand. In Chapter 4 we develop novel methods for studying hard problems using methods similar to the message passing techniques that were discussed in Chapter 2. Although we concentrated on the symmetric case, cavity methods show promise for generalizing our methods to the un-symmetric case. As has been highlighted by John Hopfield, several key features of biological systems are not shared by physical systems. Although living entities follow the laws of physics and chemistry, the fact that organisms adapt and reproduce introduces an essential ingredient that is missing in the physical sciences. In order to extract information from networks many algorithm have been developed. In Chapter 5 we apply polynomial algorithms like minimum spanning tree in order to study and construct gene regulatory networks from experimental data. As future work we propose the use of algorithms like min-cut/max-flow and Dijkstra for understanding key properties of these networks.

"Vague and artificial": the historically elusive distinction between pure and applied science.

PubMed

Gooday, Graeme

2012-09-01

This essay argues for the historicity of applied science as a contested category within laissez-faire Victorian British science. This distinctively pre-twentieth-century notion of applied science as a self-sustaining, autonomous enterprise was thrown into relief from the 1880s by a campaign on the part of T. H. Huxley and his followers to promote instead the primacy of "pure" science. Their attempt to relegate applied science to secondary status involved radically reconfiguring it as the mere application of pre-existing pure science. This new notion of extrinsically funded pure science that would produce only contingently future social benefits as a mere by-product came under pressure during World War I, when military priorities focused attention once again on science for immediate utility. This threatened the Cambridge-based promoters of self-referential pure science who collectively published Science and the Nation in 1917. Yet most contributors to this work discussed forms of "applied" science that had no prior "pure" form. Even the U.K.'s leading government scientist, Lord Moulton, dismissed the book's provocative distinction between pure and applied science as unhelpfully "vague and artificial."

The Spatial and the Visual in Mental Spatial Reasoning: An Ill-Posed Distinction

NASA Astrophysics Data System (ADS)

Schultheis, Holger; Bertel, Sven; Barkowsky, Thomas; Seifert, Inessa

It is an ongoing and controversial debate in cognitive science which aspects of knowledge humans process visually and which ones they process spatially. Similarly, artificial intelligence (AI) and cognitive science research, in building computational cognitive systems, tended to use strictly spatial or strictly visual representations. The resulting systems, however, were suboptimal both with respect to computational efficiency and cognitive plau sibility. In this paper, we propose that the problems in both research strands stem from a mis conception of the visual and the spatial in mental spatial knowl edge pro cessing. Instead of viewing the visual and the spatial as two clearly separable categories, they should be conceptualized as the extremes of a con tinuous dimension of representation. Regarding psychology, a continuous di mension avoids the need to exclusively assign processes and representations to either one of the cate gories and, thus, facilitates a more unambiguous rating of processes and rep resentations. Regarding AI and cognitive science, the con cept of a continuous spatial / visual dimension provides the possibility of rep re sentation structures which can vary continuously along the spatial / visual di mension. As a first step in exploiting these potential advantages of the pro posed conception we (a) introduce criteria allowing for a non-dichotomic judgment of processes and representations and (b) present an approach towards rep re sentation structures that can flexibly vary along the spatial / visual dimension.

A Research Program on Artificial Intelligence in Process Engineering.

ERIC Educational Resources Information Center

Stephanopoulos, George

1986-01-01

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

Several necessary conditions for the evolution of complex forms of life in an artificial environment.

PubMed

Suzuki, Hideaki; Ono, Naoaki; Yuta, Kikuo

2003-01-01

In order for an artificial life (Alife) system to evolve complex creatures, an artificial environment prepared by a designer has to satisfy several conditions. To clarify this requirement, we first assume that an artificial environment implemented in the computational medium is composed of an information space in which elementary symbols move around and react with each other according to human-prepared elementary rules. As fundamental properties of these factors (space, symbols, transportation, and reaction), we present ten criteria from a comparison with the biochemical reaction space in the real world. Then, in the latter half of the article, we take several computational Alife systems one by one, and assess them in terms of the proposed criteria. The assessment can be used not only for improving previous Alife systems but also for devising new Alife models in which complex forms of artificial creatures can be expected to evolve.

A comprehensive overview of the applications of artificial life.

PubMed

Kim, Kyung-Joong; Cho, Sung-Bae

2006-01-01

We review the applications of artificial life (ALife), the creation of synthetic life on computers to study, simulate, and understand living systems. The definition and features of ALife are shown by application studies. ALife application fields treated include robot control, robot manufacturing, practical robots, computer graphics, natural phenomenon modeling, entertainment, games, music, economics, Internet, information processing, industrial design, simulation software, electronics, security, data mining, and telecommunications. In order to show the status of ALife application research, this review primarily features a survey of about 180 ALife application articles rather than a selected representation of a few articles. Evolutionary computation is the most popular method for designing such applications, but recently swarm intelligence, artificial immune network, and agent-based modeling have also produced results. Applications were initially restricted to the robotics and computer graphics, but presently, many different applications in engineering areas are of interest.

Semantic Coherence Facilitates Distributional Learning.

PubMed

Ouyang, Long; Boroditsky, Lera; Frank, Michael C

2017-04-01

Computational models have shown that purely statistical knowledge about words' linguistic contexts is sufficient to learn many properties of words, including syntactic and semantic category. For example, models can infer that "postman" and "mailman" are semantically similar because they have quantitatively similar patterns of association with other words (e.g., they both tend to occur with words like "deliver," "truck," "package"). In contrast to these computational results, artificial language learning experiments suggest that distributional statistics alone do not facilitate learning of linguistic categories. However, experiments in this paradigm expose participants to entirely novel words, whereas real language learners encounter input that contains some known words that are semantically organized. In three experiments, we show that (a) the presence of familiar semantic reference points facilitates distributional learning and (b) this effect crucially depends both on the presence of known words and the adherence of these known words to some semantic organization. Copyright © 2016 Cognitive Science Society, Inc.

The Classification, Detection and Handling of Imperfect Theory Problems.

DTIC Science & Technology

1987-04-20

Explanation-Based Learning: Failure-Driven Schema Refinement." Proceedings of the Third IEEE Conference on Artificial Intelligence Applications . Orlando...A. Rajamoney. Gerald F. DeJong Artificial Intelligence Research Group " . Coordinated Science Laboratory " University of Illinois at Urbana-Champaign...Urbana. IL 61801 . April 1987 ABSTRACT This paper also appears in the Proceedings of the Tenth International Conference on Artificial Intelligence

Magnetoresistance in Permalloy Connected Brickwork Artificial Spin Ice

NASA Astrophysics Data System (ADS)

Park, Jungsik; Le, Brian; Chern, Gia-Wei; Watts, Justin; Leighton, Chris; Schiffer, Peter

Artificial spin ice refers to a two-dimensional array of elongated ferromagnetic elements in which frustrated lattice geometry induces novel magnetic behavior. Here we examine room-temperature magnetoresistance properties of connected permalloy (Ni81Fe19) brickwork artificial spin ice. Both the longitudinal and transverse magnetoresistance of the nanostructure demonstrate an angular sensitivity that has not been previously observed. The observed magnetoresistance behavior can be explained from micromagnetic modelling using an anisotropic magnetoresistance model (AMR). As part of this study, we find that the ground state of the connected brickwork artificial spin ice can be reproducibly created by a simple field sweep in a narrow range of angles, and manifests in the magnetotransport with a distinct signal. Supported by the US Department of Energy, Office of Basic Energy Sciences, Materials Sciences and Engineering Division under Grant Number DE-SC0010778. Work at the University of Minnesota was supported by the NSF MRSEC under award DMR-1420013, and DMR-1507048.

Neurobiomimetic constructs for intelligent unmanned systems and robotics

NASA Astrophysics Data System (ADS)

Braun, Jerome J.; Shah, Danelle C.; DeAngelus, Marianne A.

2014-06-01

This paper discusses a paradigm we refer to as neurobiomimetic, which involves emulations of brain neuroanatomy and neurobiology aspects and processes. Neurobiomimetic constructs include rudimentary and down-scaled computational representations of brain regions, sub-regions, and synaptic connectivity. Many different instances of neurobiomimetic constructs are possible, depending on various aspects such as the initial conditions of synaptic connectivity, number of neuron elements in regions, connectivity specifics, and more, and we refer to these instances as `animats'. While downscaled for computational feasibility, the animats are very large constructs; the animats implemented in this work contain over 47,000 neuron elements and over 720,000 synaptic connections. The paper outlines aspects of the animats implemented, spatial memory and learning cognitive task, the virtual-reality environment constructed to study the animat performing that task, and discussion of results. In a broad sense, we argue that the neurobiomimetic paradigm pursued in this work constitutes a particularly promising path to artificial cognition and intelligent unmanned systems. Biological brains readily cope with challenges of real-life tasks that consistently prove beyond even the most sophisticated algorithmic approaches known. At the cross-over point of neuroscience, cognitive science and computer science, paradigms such as the one pursued in this work aim to mimic the mechanisms of biological brains and as such, we argue, may lead to machines with abilities closer to those of biological species.

Partial Bibliography of Work on Expert Systems,

DTIC Science & Technology

1982-12-01

Bibliography: AAAI American Association for Artificial Intelligence ACM Association for Computing Machinery AFIPS American Federation of Information...Processing Societies ECAI European Conference on Artificial Intelligence IEEE Institute for Electrical and Electronic Engineers IFIPS International...Federation of Information Processing Societies IJCAI International Joint Conferences on Artificial Intelligence SIGPLAN ACM Special Interest Group on

Acquiring General Iterative Concepts by Reformulating Explanations of Observed Examples.

DTIC Science & Technology

1987-12-01

CODES I&16 SUBJECT TERMS (Continue on revitn if nectsuty and identify by block number) FIELD GROUP SUE-GROUIP -, artificial intelligence, machine...N00014-86-K-0309, by the National Science Foundation under grant NSF IST 85-11542, and by a University of Illinois Cognitive Science/ Artificial ...Conference o, Arificiel InteLigence . pp 221-22> \\1ilan. 1 alv kugJsI I h Holder, L B., "Discovering Substructures in Examples," \\IS. Thesis (in preparation

ALOG: A spreadsheet-based program for generating artificial logs

Treesearch

Matthew F. Winn; Randolph H. Wynne; Philip A. Araman

2004-01-01

Log sawing simulation computer programs can be valuable tools for training sawyers as well as for testing different sawing patterns. Most available simulation programs rely on databases from which to draw logs and can be very costly and time-consuming to develop. ALOG (Artificial LOg Generator) is a Microsoft Excel®-based computer program that was developed to...

Artificial Intelligence Methods: Challenge in Computer Based Polymer Design

NASA Astrophysics Data System (ADS)

Rusu, Teodora; Pinteala, Mariana; Cartwright, Hugh

2009-08-01

This paper deals with the use of Artificial Intelligence Methods (AI) in the design of new molecules possessing desired physical, chemical and biological properties. This is an important and difficult problem in the chemical, material and pharmaceutical industries. Traditional methods involve a laborious and expensive trial-and-error procedure, but computer-assisted approaches offer many advantages in the automation of molecular design.

Allergy risks with laptop computers - nickel and cobalt release.

PubMed

Midander, Klara; Hurtig, Anna; Borg Tornberg, Anette; Julander, Anneli

2016-06-01

Laptop computers may release nickel and cobalt when they come into contact with skin. Few computer brands have been studied. To evaluate nickel and cobalt release from laptop computers belonging to several brands by using spot tests, and to quantify the release from one new computer by using artificial sweat solution. Nickel and cobalt spot tests were used on the lid and wrist supports of 31 laptop computers representing five brands. The same surfaces were tested on all computers. In addition, one new computer was bought and dismantled for release tests in artificial sweat according to the standard method described in EN1811. Thirty-nine per cent of the laptop computers were nickel spot test-positive, and 6% were positive for cobalt. The nickel on the surface could be worn off by consecutive spot testing of the same surface. The release test in artificial sweat of one computer showed that nickel and cobalt were released, although in low concentrations. As they constitute a potential source of skin exposure to metals, laptop computers should qualify as objects to be included within the restriction of nickel in REACH, following the definition of 'prolonged skin contact'. Skin contact resulting from laptop use may contribute to an accumulated skin dose of nickel that can be problematic for sensitized individuals. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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.

Get immersed in the Soil Sciences: the first community of avatars in the EGU Assembly 2015!

NASA Astrophysics Data System (ADS)

Castillo, Sebastian; Alarcón, Purificación; Beato, Mamen; Emilio Guerrero, José; José Martínez, Juan; Pérez, Cristina; Ortiz, Leovigilda; Taguas, Encarnación V.

2015-04-01

Virtual reality and immersive worlds refer to artificial computer-generated environments, with which users act and interact as in a known environment by the use of figurative virtual individuals (avatars). Virtual environments will be the technology of the early twenty-first century that will most dramatically change the way we live, particularly in the areas of training and education, product development and entertainment (Schmorrow, 2009). The usefulness of immersive worlds has been proved in different fields. They reduce geographic and social barriers between different stakeholders and create virtual social spaces which can positively impact learning and discussion outcomes (Lorenzo et al. 2012). In this work we present a series of interactive meetings in a virtual building to celebrate the International Year of Soil to promote the importance of soil functions and its conservation. In a virtual room, the avatars of different senior researchers will meet young scientist avatars to talk about: 1) what remains to be done in Soil Sciences; 2) which are their main current limitations and difficulties and 3) which are the future hot research lines. The interactive participation does not require physically attend to the EGU Assembly 2015. In addition, this virtual building inspired in Soil Sciences can be completed with different teaching resources from different locations around the world and it will be used to improve the learning of Soil Sciences in a multicultural context. REFERENCES: Lorenzo C.M., Sicilia, M.A., Sánchez S. 2012. Studying the effectiveness of multi-user immersive environments for collaborative evaluation tasks. Computers & Education 59 (2012) 1361-1376 Schmorrow D.D. 2009. "Why virtual?" Theoretical Issues in Ergonomics Science 10(3): 279-282.

Artificial Muscles Based on Electroactive Polymers as an Enabling Tool in Biomimetics

NASA Technical Reports Server (NTRS)

Bar-Cohen, Y.

2007-01-01

Evolution has resolved many of nature's challenges leading to working and lasting solutions that employ principles of physics, chemistry, mechanical engineering, materials science, and many other fields of science and engineering. Nature's inventions have always inspired human achievements leading to effective materials, structures, tools, mechanisms, processes, algorithms, methods, systems, and many other benefits. Some of the technologies that have emerged include artificial intelligence, artificial vision, and artificial muscles, where the latter is the moniker for electroactive polymers (EAPs). To take advantage of these materials and make them practical actuators, efforts are made worldwide to develop capabilities that are critical to the field infrastructure. Researchers are developing analytical model and comprehensive understanding of EAP materials response mechanism as well as effective processing and characterization techniques. The field is still in its emerging state and robust materials are still not readily available; however, in recent years, significant progress has been made and commercial products have already started to appear. In the current paper, the state-of-the-art and challenges to artificial muscles as well as their potential application to biomimetic mechanisms and devices are described and discussed.

Paraconsistent Annotated Logic in Viability Analysis: an Approach to Product Launching

NASA Astrophysics Data System (ADS)

Romeu de Carvalho, Fábio; Brunstein, Israel; Abe, Jair Minoro

2004-08-01

In this paper we present an application of the Para-analyzer, a logical analyzer based on the Paraconsistent Annotated Logic Pτ, introduced by Da Silva Filho and Abe in the decision-making systems. An example is analyzed in detail showing how uncertainty, inconsistency and paracompleteness can be elegantly handled with this logical system. As application for the Para-analyzer in decision-making, we developed the BAM — Baricenter Analysis Method. In order to make the presentation easier, we present the BAM applied in the viability analysis of product launching. Some of the techniques of Paraconsistent Annotated Logic have been applied in Artificial Intelligence, Robotics, Information Technolgy (Computer Sciences), etc..

Identifying Jets Using Artifical Neural Networks

NASA Astrophysics Data System (ADS)

Rosand, Benjamin; Caines, Helen; Checa, Sofia

2017-09-01

We investigate particle jet interactions with the Quark Gluon Plasma (QGP) using artificial neural networks modeled on those used in computer image recognition. We create jet images by binning jet particles into pixels and preprocessing every image. We analyzed the jets with a Multi-layered maxout network and a convolutional network. We demonstrate each network's effectiveness in differentiating simulated quenched jets from unquenched jets, and we investigate the method that the network uses to discriminate among different quenched jet simulations. Finally, we develop a greater understanding of the physics behind quenched jets by investigating what the network learnt as well as its effectiveness in differentiating samples. Yale College Freshman Summer Research Fellowship in the Sciences and Engineering.

The Potential of Artificial Intelligence in Aids for the Disabled.

ERIC Educational Resources Information Center

Boyer, John J.

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

Potential application of artificial concepts to aerodynamic simulation

NASA Technical Reports Server (NTRS)

Kutler, P.; Mehta, U. B.; Andrews, A.

1984-01-01

The concept of artificial intelligence as it applies to computational fluid dynamics simulation is investigated. How expert systems can be adapted to speed the numerical aerodynamic simulation process is also examined. A proposed expert grid generation system is briefly described which, given flow parameters, configuration geometry, and simulation constraints, uses knowledge about the discretization process to determine grid point coordinates, computational surface information, and zonal interface parameters.

CBT Pilot Program Instructional Guide. Basic Drafting Skills Curriculum Delivered through CAD Workstations and Artificial Intelligence Software.

ERIC Educational Resources Information Center

Smith, Richard J.; Sauer, Mardelle A.

This guide is intended to assist teachers in using computer-aided design (CAD) workstations and artificial intelligence software to teach basic drafting skills. The guide outlines a 7-unit shell program that may also be used as a generic authoring system capable of supporting computer-based training (CBT) in other subject areas. The first section…

Artificial intelligence issues related to automated computing operations

NASA Technical Reports Server (NTRS)

Hornfeck, William A.

1989-01-01

Large data processing installations represent target systems for effective applications of artificial intelligence (AI) constructs. The system organization of a large data processing facility at the NASA Marshall Space Flight Center is presented. The methodology and the issues which are related to AI application to automated operations within a large-scale computing facility are described. Problems to be addressed and initial goals are outlined.

Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

NASA Astrophysics Data System (ADS)

Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed

2017-05-01

Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.

SHARP: A multi-mission AI system for spacecraft telemetry monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Lawson, Denise L.; James, Mark L.

1989-01-01

The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real-time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

Publishing Trends in Educational Computing.

ERIC Educational Resources Information Center

O'Hair, Marilyn; Johnson, D. LaMont

1989-01-01

Describes results of a survey of secondary school and college teachers that was conducted to determine subject matter that should be included in educational computing journals. Areas of interest included computer applications; artificial intelligence; computer-aided instruction; computer literacy; computer-managed instruction; databases; distance…

Computational Hemodynamics Involving Artificial Devices

NASA Technical Reports Server (NTRS)

Kwak, Dochan; Kiris, Cetin; Feiereisen, William (Technical Monitor)

2001-01-01

This paper reports the progress being made towards developing complete blood flow simulation capability in human, especially, in the presence of artificial devices such as valves and ventricular assist devices. Devices modeling poses unique challenges different from computing the blood flow in natural hearts and arteries. There are many elements needed such as flow solvers, geometry modeling including flexible walls, moving boundary procedures and physiological characterization of blood. As a first step, computational technology developed for aerospace applications was extended in the recent past to the analysis and development of mechanical devices. The blood flow in these devices is practically incompressible and Newtonian, and thus various incompressible Navier-Stokes solution procedures can be selected depending on the choice of formulations, variables and numerical schemes. Two primitive variable formulations used are discussed as well as the overset grid approach to handle complex moving geometry. This procedure has been applied to several artificial devices. Among these, recent progress made in developing DeBakey axial flow blood pump will be presented from computational point of view. Computational and clinical issues will be discussed in detail as well as additional work needed.

Application of artificial neural networks to composite ply micromechanics

NASA Technical Reports Server (NTRS)

Brown, D. A.; Murthy, P. L. N.; Berke, L.

1991-01-01

Artificial neural networks can provide improved computational efficiency relative to existing methods when an algorithmic description of functional relationships is either totally unavailable or is complex in nature. For complex calculations, significant reductions in elapsed computation time are possible. The primary goal is to demonstrate the applicability of artificial neural networks to composite material characterization. As a test case, a neural network was trained to accurately predict composite hygral, thermal, and mechanical properties when provided with basic information concerning the environment, constituent materials, and component ratios used in the creation of the composite. A brief introduction on neural networks is provided along with a description of the project itself.

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

PubMed

Ashrafian, Hutan; Darzi, Ara; Athanasiou, Thanos

2015-03-01

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

Virtual personal assistance

NASA Astrophysics Data System (ADS)

Aditya, K.; Biswadeep, G.; Kedar, S.; Sundar, S.

2017-11-01

Human computer communication has growing demand recent days. The new generation of autonomous technology aspires to give computer interfaces emotional states that relate and consider user as well as system environment considerations. In the existing computational model is based an artificial intelligent and externally by multi-modal expression augmented with semi human characteristics. But the main problem with is multi-model expression is that the hardware control given to the Artificial Intelligence (AI) is very limited. So, in our project we are trying to give the Artificial Intelligence (AI) more control on the hardware. There are two main parts such as Speech to Text (STT) and Text to Speech (TTS) engines are used accomplish the requirement. In this work, we are using a raspberry pi 3, a speaker and a mic as hardware and for the programing part, we are using python scripting.

Active Ambiguity Reduction: An Experiment Design Approach to Tractable Qualitative Reasoning.

DTIC Science & Technology

1987-04-20

Approach to Tractable Qualitative Reasoning Shankar A. Rajamoney t [ For Gerald F. DeJong Artificial Intelligence Research Group Coordinated Science...Representations of Knowledge in a Mechanics Problem- Solver." Proceedings of the Fifth International Joint Conference on Artificial Intelligence. Cambridge. MIA...International Joint Conference on Artificial Intelligence. Tokyo. Japan. 1979. [de Kleer84] J. de Kleer and J. S. Brown. "A Qualitative Physics Based on

Natural Object Categorization.

DTIC Science & Technology

1987-11-01

6-A194 103 NATURAL OBJECT CATEGORIZATION(U) MASSACHUSETTS INST OF 1/3 TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB R F DBICK NOY 87 AI-TR-1091 NBSSI4...ORGANI1ZATION NAME AN40 ACORES$ 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREA A WORK UNIT MUMBERS 545 Technology Square Cambridge...describes research done at the Department of Brain and Cognitive Sciences and the Artificial Intelligence Laboratory at the Massachusetts Institute of

Maxillofacial reconstruction using custom-made artificial bones fabricated by inkjet printing technology.

PubMed

Saijo, Hideto; Igawa, Kazuyo; Kanno, Yuki; Mori, Yoshiyuki; Kondo, Kayoko; Shimizu, Koutaro; Suzuki, Shigeki; Chikazu, Daichi; Iino, Mitsuki; Anzai, Masahiro; Sasaki, Nobuo; Chung, Ung-il; Takato, Tsuyoshi

2009-01-01

Ideally, artificial bones should be dimensionally compatible with deformities, and be biodegradable and osteoconductive; however, there are no artificial bones developed to date that satisfy these requirements. We fabricated novel custom-made artificial bones from alpha-tricalcium phosphate powder using an inkjet printer and implanted them in ten patients with maxillofacial deformities. The artificial bones had dimensional compatibility in all the patients. The operation time was reduced due to minimal need for size adjustment and fixing manipulation. The postsurgical computed tomography analysis detected partial union between the artificial bones and host bone tissues. There were no serious adverse reactions. These findings provide support for further clinical studies of the inkjet-printed custom-made artificial bones.

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

PubMed

Sniecinski, Irena; Seghatchian, Jerard

2018-05-09

Artificial Intelligence (AI) reflects the intelligence exhibited by machines and software. It is a highly desirable academic field of many current fields of studies. Leading AI researchers describe the field as "the study and design of intelligent agents". McCarthy invented this term in 1955 and defined it as "the science and engineering of making intelligent machines". The central goals of AI research are reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. In fact the multidisplinary AI field is considered to be rather interdisciplinary covering numerous number of sciences and professions, including computer science, psychology, linguistics, philosophy and neurosciences. The field was founded on the claim that a central intellectual property of humans, intelligence-the sapience of Homo Sapiens "can be so precisely described that a machine can be made to simulate it". This raises philosophical issues about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence. Artificial Intelligence has been the subject of tremendous optimism but has also suffered stunning setbacks. The goal of this narrative is to review the potential use of AI approaches and their integration into pediatric cellular therapies and regenerative medicine. Emphasis is placed on recognition and application of AI techniques in the development of predictive models for personalized treatments with engineered stem cells, immune cells and regenerated tissues in adults and children. These intelligent machines could dissect the whole genome and isolate the immune particularities of individual patient's disease in a matter of minutes and create the treatment that is customized to patient's genetic specificity and immune system capability. AI techniques could be used for optimization of clinical trials of innovative stem cell and gene therapies in pediatric patients 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.

Virtual reality and 3D animation in forensic visualization.

PubMed

Ma, Minhua; Zheng, Huiru; Lallie, Harjinder

2010-09-01

Computer-generated three-dimensional (3D) animation is an ideal media to accurately visualize crime or accident scenes to the viewers and in the courtrooms. Based upon factual data, forensic animations can reproduce the scene and demonstrate the activity at various points in time. The use of computer animation techniques to reconstruct crime scenes is beginning to replace the traditional illustrations, photographs, and verbal descriptions, and is becoming popular in today's forensics. This article integrates work in the areas of 3D graphics, computer vision, motion tracking, natural language processing, and forensic computing, to investigate the state-of-the-art in forensic visualization. It identifies and reviews areas where new applications of 3D digital technologies and artificial intelligence could be used to enhance particular phases of forensic visualization to create 3D models and animations automatically and quickly. Having discussed the relationships between major crime types and level-of-detail in corresponding forensic animations, we recognized that high level-of-detail animation involving human characters, which is appropriate for many major crime types but has had limited use in courtrooms, could be useful for crime investigation. © 2010 American Academy of Forensic Sciences.

Artificial intelligence: Learning to see and act

NASA Astrophysics Data System (ADS)

Schölkopf, Bernhard

2015-02-01

An artificial-intelligence system uses machine learning from massive training sets to teach itself to play 49 classic computer games, demonstrating that it can adapt to a variety of tasks. See Letter p.529

Artificial synapse network on inorganic proton conductor for neuromorphic systems.

PubMed

Zhu, Li Qiang; Wan, Chang Jin; Guo, Li Qiang; Shi, Yi; Wan, Qing

2014-01-01

The basic units in our brain are neurons, and each neuron has more than 1,000 synapse connections. Synapse is the basic structure for information transfer in an ever-changing manner, and short-term plasticity allows synapses to perform critical computational functions in neural circuits. Therefore, the major challenge for the hardware implementation of neuromorphic computation is to develop artificial synapse network. Here in-plane lateral-coupled oxide-based artificial synapse network coupled by proton neurotransmitters are self-assembled on glass substrates at room-temperature. A strong lateral modulation is observed due to the proton-related electrical-double-layer effect. Short-term plasticity behaviours, including paired-pulse facilitation, dynamic filtering and spatiotemporally correlated signal processing are mimicked. Such laterally coupled oxide-based protonic/electronic hybrid artificial synapse network proposed here is interesting for building future neuromorphic systems.

Case-Based Planning: An Integrated Theory of Planning, Learning and Memory

DTIC Science & Technology

1986-10-01

rtvoeoo oldo II nocomtmry and Idonltly by block numbor) planning Case-based reasoning learning Artificial Intelligence 20. ABSTRACT (Conllnum...Computational Model of Analogical Prob- lem Solving, Proceedings of the Seventh International Joint Conference on Artificial Intelligence ...Understanding and Generalizing Plans., Proceedings of the Eight Interna- tional Joint Conference on Artificial Intelligence , IJCAI, Karlsrhue, Germany

The development, assessment and validation of virtual reality for human anatomy instruction

NASA Technical Reports Server (NTRS)

Marshall, Karen Benn

1996-01-01

This research project seeks to meet the objective of science training by developing, assessing, validating and utilizing VR as a human anatomy training medium. Current anatomy instruction is primarily in the form of lectures and usage of textbooks. In ideal situations, anatomic models, computer-based instruction, and cadaver dissection are utilized to augment traditional methods of instruction. At many institutions, lack of financial resources limits anatomy instruction to textbooks and lectures. However, human anatomy is three-dimensional, unlike the one-dimensional depiction found in textbooks and the two-dimensional depiction found on the computer. Virtual reality allows one to step through the computer screen into a 3-D artificial world. The primary objective of this project is to produce a virtual reality application of the abdominopelvic region of a human cadaver that can be taken back to the classroom. The hypothesis is that an immersive learning environment affords quicker anatomic recognition and orientation and a greater level of retention in human anatomy instruction. The goal is to augment not replace traditional modes of instruction.

Quality use of the computer: Computational mechanics, artificial intelligence, robotics, and acoustic sensing; Proceedings of the ASME/JSME Pressure Vessels and Piping Conference, Honolulu, HI, July 23-27, 1989

NASA Astrophysics Data System (ADS)

Cory, J. F., Jr.; Gordon, J. L.; Miyoshi, T.; Suzuki, K.

1989-06-01

Papers are presented on the use of microcomputers, supercomputers, and workstations in solid and structural mechanics. Artificial intelligence technology, the development and use of expert systems, and research in the area of robotics are discussed. Attention is also given to probabilistic finite element and boundary element methods and acoustic sensing.

The Art of Artificial Intelligence. 1. Themes and Case Studies of Knowledge Engineering

DTIC Science & Technology

1977-08-01

in scientific and medical inference illuminate the art of knowledge engineering and its parent science , Artificial Intelligence....The knowledge engineer practices the art of bringing the principles and tools of AI research to bear on difficult applications problems requiring

Systems in Science: Modeling Using Three Artificial Intelligence Concepts.

ERIC Educational Resources Information Center

Sunal, Cynthia Szymanski; Karr, Charles L.; Smith, Coralee; Sunal, Dennis W.

2003-01-01

Describes an interdisciplinary course focusing on modeling scientific systems. Investigates elementary education majors' applications of three artificial intelligence concepts used in modeling scientific systems before and after the course. Reveals a great increase in understanding of concepts presented but inconsistent application. (Author/KHR)

Artificial multilayers and nanomagnetic materials.

PubMed

Shinjo, Teruya

2013-01-01

The author has been actively engaged in research on nanomagnetic materials for about 50 years. Nanomagnetic materials are comprised of ferromagnetic systems for which the size and shape are controlled on a nanometer scale. Typical examples are ultrafine particles, ultrathin films, multilayered films and nano-patterned films. In this article, the following four areas of the author's studies are described.(1) Mössbauer spectroscopic studies of nanomagnetic materials and interface magnetism.(2) Preparation and characterization of metallic multilayers with artificial superstructures.(3) Giant magnetoresistance (GMR) effect in magnetic multilayers.(4) Novel properties of nanostructured ferromagnetic thin films (dots and wires).A subject of particular interest in the author's research was the artificially prepared multilayers consisting of metallic elements. The motivation to initiate the multilayer investigation is described and the physical properties observed in the artificial multilayers are introduced. The author's research was initially in the field of pure physical science and gradually extended into applied science. His achievements are highly regarded not only from the fundamental point of view but also from the technological viewpoint.

Computers, Nanotechnology and Mind

NASA Astrophysics Data System (ADS)

Ekdahl, Bertil

2008-10-01

In 1958, two years after the Dartmouth conference, where the term artificial intelligence was coined, Herbert Simon and Allen Newell asserted the existence of "machines that think, that learn and create." They were further prophesying that the machines' capacity would increase and be on par with the human mind. Now, 50 years later, computers perform many more tasks than one could imagine in the 1950s but, virtually, no computer can do more than could the first digital computer, developed by John von Neumann in the 1940s. Computers still follow algorithms, they do not create them. However, the development of nanotechnology seems to have given rise to new hopes. With nanotechnology two things are supposed to happen. Firstly, due to the small scale it will be possible to construct huge computer memories which are supposed to be the precondition for building an artificial brain, secondly, nanotechnology will make it possible to scan the brain which in turn will make reverse engineering possible; the mind will be decoded by studying the brain. The consequence of such a belief is that the brain is no more than a calculator, i.e., all that the mind can do is in principle the results of arithmetical operations. Computers are equivalent to formal systems which in turn was an answer to an idea by Hilbert that proofs should contain ideal statements for which operations cannot be applied in a contentual way. The advocates of artificial intelligence will place content in a machine that is developed not only to be free of content but also cannot contain content. In this paper I argue that the hope for artificial intelligence is in vain.

Rebooting Computers as Learning Machines

DOE PAGES

DeBenedictis, Erik P.

2016-06-13

Artificial neural networks could become the technological driver that replaces Moore's law, boosting computers' utlity through a process akin to automatic programming--although physics and computer architecture would are also a factor.

Rebooting Computers as Learning Machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeBenedictis, Erik P.

Artificial neural networks could become the technological driver that replaces Moore's law, boosting computers' utlity through a process akin to automatic programming--although physics and computer architecture would are also a factor.

Computer-Assisted Drug Formulation Design: Novel Approach in Drug Delivery.

PubMed

Metwally, Abdelkader A; Hathout, Rania M

2015-08-03

We hypothesize that, by using several chemo/bio informatics tools and statistical computational methods, we can study and then predict the behavior of several drugs in model nanoparticulate lipid and polymeric systems. Accordingly, two different matrices comprising tripalmitin, a core component of solid lipid nanoparticles (SLN), and PLGA were first modeled using molecular dynamics simulation, and then the interaction of drugs with these systems was studied by means of computing the free energy of binding using the molecular docking technique. These binding energies were hence correlated with the loadings of these drugs in the nanoparticles obtained experimentally from the available literature. The obtained relations were verified experimentally in our laboratory using curcumin as a model drug. Artificial neural networks were then used to establish the effect of the drugs' molecular descriptors on the binding energies and hence on the drug loading. The results showed that the used soft computing methods can provide an accurate method for in silico prediction of drug loading in tripalmitin-based and PLGA nanoparticulate systems. These results have the prospective of being applied to other nano drug-carrier systems, and this integrated statistical and chemo/bio informatics approach offers a new toolbox to the formulation science by proposing what we present as computer-assisted drug formulation design (CADFD).

Construction of Optimal-Path Maps for Homogeneous-Cost-Region Path-Planning Problems

DTIC Science & Technology

1989-09-01

of Artificial Inteligence , 9%,4. 24. Kirkpatrick, S., Gelatt Jr., C. D., and Vecchi, M. P., "Optinization by Sinmulated Ani- nealing", Science, Vol...studied in depth by researchers in such fields as artificial intelligence, robot;cs, and computa- tional geometry. Most methods require homogeneous...the results of the research. 10 U. L SLEVANT RESEARCH A. APPLICABLE CONCEPTS FROM ARTIFICIAL INTELLIGENCE 1. Search Methods One of the central

Artificial Intelligence and Expert Systems Research and Their Possible Impact on Information Science.

ERIC Educational Resources Information Center

Borko, Harold

1985-01-01

Defines artificial intelligence (AI) and expert systems; describes library applications utilizing AI to automate creation of document representations, request formulations, and design and modify search strategies for information retrieval systems; discusses expert system development for information services; and reviews impact of these…

Bibliography. Computer-Oriented Projects, 1987.

ERIC Educational Resources Information Center

Smith, Richard L., Comp.

1988-01-01

Provides an annotated list of references on computer-oriented projects. Includes information on computers; hands-on versus simulations; games; instruction; students' attitudes and learning styles; artificial intelligence; tutoring; and application of spreadsheets. (RT)

Towards Robot Scientists for autonomous scientific discovery

PubMed Central

2010-01-01

We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical experiments using robotic systems, analyses and interprets the resulting data, and repeats the cycle. We describe our two prototype Robot Scientists: Adam and Eve. Adam has recently proven the potential of such systems by identifying twelve genes responsible for catalysing specific reactions in the metabolic pathways of the yeast Saccharomyces cerevisiae. This work has been formally recorded in great detail using logic. We argue that the reporting of science needs to become fully formalised and that Robot Scientists can help achieve this. This will make scientific information more reproducible and reusable, and promote the integration of computers in scientific reasoning. We believe the greater automation of both the physical and intellectual aspects of scientific investigations to be essential to the future of science. Greater automation improves the accuracy and reliability of experiments, increases the pace of discovery and, in common with conventional laboratory automation, removes tedious and repetitive tasks from the human scientist. PMID:20119518

Towards Robot Scientists for autonomous scientific discovery.

PubMed

Sparkes, Andrew; Aubrey, Wayne; Byrne, Emma; Clare, Amanda; Khan, Muhammed N; Liakata, Maria; Markham, Magdalena; Rowland, Jem; Soldatova, Larisa N; Whelan, Kenneth E; Young, Michael; King, Ross D

2010-01-04

We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical experiments using robotic systems, analyses and interprets the resulting data, and repeats the cycle. We describe our two prototype Robot Scientists: Adam and Eve. Adam has recently proven the potential of such systems by identifying twelve genes responsible for catalysing specific reactions in the metabolic pathways of the yeast Saccharomyces cerevisiae. This work has been formally recorded in great detail using logic. We argue that the reporting of science needs to become fully formalised and that Robot Scientists can help achieve this. This will make scientific information more reproducible and reusable, and promote the integration of computers in scientific reasoning. We believe the greater automation of both the physical and intellectual aspects of scientific investigations to be essential to the future of science. Greater automation improves the accuracy and reliability of experiments, increases the pace of discovery and, in common with conventional laboratory automation, removes tedious and repetitive tasks from the human scientist.

Magnetic Charge Organization and Screening in Thermalized Artificial Spin Ice

NASA Astrophysics Data System (ADS)

Gilbert, Ian

2014-03-01

Artificial spin ice is a material-by-design in which interacting single-domain ferromagnetic nanoislands are used to model Ising spins in frustrated spin systems. Artificial spin ice has proved a useful system in which to directly probe the physics of geometrical frustration, allowing us to better understand materials such as spin ice. Recently, several new experimental techniques have been developed that allow effective thermalization of artificial spin ice. Given the intense interest in magnetic monopole excitations in spin ice materials and artificial spin ice's success in modeling these materials, it should not come as a surprise that interesting monopole physics emerges here as well. The first experimental investigation of thermalized artificial square spin ice determined that the system's monopole-like excitations obeyed a Boltzmann distribution and also found evidence for monopole-antimonopole interactions. Further experiments have implicated these monopole excitations in the growth of ground state domains. Our recent study of artificial kagome spin ice, whose odd-coordinated vertices always possess a net magnetic charge, has revealed a theoretically-predicted magnetic charge ordering transition which has not been previously observed experimentally. We have also investigated the details of magnetic charge interactions in lattices of mixed coordination number. This work was done in collaboration with Sheng Zhang, Cristiano Nisoli, Gia-Wei Chern, Michael Erickson, Liam O'Brien, Chris Leighton, Paul Lammert, Vincent Crespi, and Peter Schiffer. This work was primarily funded by the US Department of Energy, Office of Basic Energy Sciences, Materials Science and Engineering Division, grant no. DE-SC0005313.

Computing Visible-Surface Representations,

DTIC Science & Technology

1985-03-01

Terzopoulos N00014-75-C-0643 9. PERFORMING ORGANIZATION NAME AMC ADDRESS 10. PROGRAM ELEMENT. PROJECT, TASK Artificial Inteligence Laboratory AREA A...Massachusetts Institute of lechnolog,. Support lbr the laboratory’s Artificial Intelligence research is provided in part by the Advanced Rtccarcl Proj...dynamically maintaining visible surface representations. Whether the intention is to model human vision or to design competent artificial vision systems

Using Artificial Physics to Control Agents

DTIC Science & Technology

1999-11-01

unlimited 13. SUPPLEMENTARY NOTES IEEE International Conference on Information, Intelligence, and Systems, Oct 31 -Nov 3,1999. Bethesda, MD 14. ABSTRACT...distributed control can also perform distributed computation. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same...1995. [9] H. Pattee. Artificial life needs a real epistemology. In Moran, Moreno, Merelo, and Chacon , editors, Advances in Artificial Life, pages

Organisational Structure and Information Technology (IT): Exploring the Implications of IT for Future Military Structures

DTIC Science & Technology

2006-07-01

4 Abbreviations AI Artificial Intelligence AM Artificial Memory CAD Computer Aided...memory (AM), artificial intelligence (AI), and embedded knowledge systems it is possible to expand the “effective span of competence” of...Technology J Joint J2 Joint Intelligence J3 Joint Operations NATO North Atlantic Treaty Organisation NCW Network Centric Warfare NHS National Health

FIRST Quantum-(1980)-Computing DISCOVERY in Siegel-Rosen-Feynman-...A.-I. Neural-Networks: Artificial(ANN)/Biological(BNN) and Siegel FIRST Semantic-Web and Siegel FIRST ``Page''-``Brin'' ``PageRank'' PRE-Google Search-Engines!!!

NASA Astrophysics Data System (ADS)

Rosen, Charles; Siegel, Edward Carl-Ludwig; Feynman, Richard; Wunderman, Irwin; Smith, Adolph; Marinov, Vesco; Goldman, Jacob; Brine, Sergey; Poge, Larry; Schmidt, Erich; Young, Frederic; Goates-Bulmer, William-Steven; Lewis-Tsurakov-Altshuler, Thomas-Valerie-Genot; Ibm/Exxon Collaboration; Google/Uw Collaboration; Microsoft/Amazon Collaboration; Oracle/Sun Collaboration; Ostp/Dod/Dia/Nsa/W.-F./Boa/Ubs/Ub Collaboration

2013-03-01

Belew[Finding Out About, Cambridge(2000)] and separately full-decade pre-Page/Brin/Google FIRST Siegel-Rosen(Machine-Intelligence/Atherton)-Feynman-Smith-Marinov(Guzik Enterprises/Exxon-Enterprises/A.-I./Santa Clara)-Wunderman(H.-P.) [IBM Conf. on Computers and Mathematics, Stanford(1986); APS Mtgs.(1980s): Palo Alto/Santa Clara/San Francisco/...(1980s) MRS Spring-Mtgs.(1980s): Palo Alto/San Jose/San Francisco/...(1980-1992) FIRST quantum-computing via Bose-Einstein quantum-statistics(BEQS) Bose-Einstein CONDENSATION (BEC) in artificial-intelligence(A-I) artificial neural-networks(A-N-N) and biological neural-networks(B-N-N) and Siegel[J. Noncrystalline-Solids 40, 453(1980); Symp. on Fractals..., MRS Fall-Mtg., Boston(1989)-5-papers; Symp. on Scaling..., (1990); Symp. on Transport in Geometric-Constraint (1990)

Development of programmable artificial neural networks

NASA Technical Reports Server (NTRS)

Meade, Andrew J.

1993-01-01

Conventionally programmed digital computers can process numbers with great speed and precision, but do not easily recognize patterns or imprecise or contradictory data. Instead of being programmed in the conventional sense, artificial neural networks are capable of self-learning through exposure to repeated examples. However, the training of an ANN can be a time consuming and unpredictable process. A general method is being developed to mate the adaptability of the ANN with the speed and precision of the digital computer. This method was successful in building feedforward networks that can approximate functions and their partial derivatives from examples in a single iteration. The general method also allows the formation of feedforward networks that can approximate the solution to nonlinear ordinary and partial differential equations to desired accuracy without the need of examples. It is believed that continued research will produce artificial neural networks that can be used with confidence in practical scientific computing and engineering applications.

Cognitive methodology for forecasting oil and gas industry using pattern-based neural information technologies

NASA Astrophysics Data System (ADS)

Gafurov, O.; Gafurov, D.; Syryamkin, V.

2018-05-01

The paper analyses a field of computer science formed at the intersection of such areas of natural science as artificial intelligence, mathematical statistics, and database theory, which is referred to as "Data Mining" (discovery of knowledge in data). The theory of neural networks is applied along with classical methods of mathematical analysis and numerical simulation. The paper describes the technique protected by the patent of the Russian Federation for the invention “A Method for Determining Location of Production Wells during the Development of Hydrocarbon Fields” [1–3] and implemented using the geoinformation system NeuroInformGeo. There are no analogues in domestic and international practice. The paper gives an example of comparing the forecast of the oil reservoir quality made by the geophysicist interpreter using standard methods and the forecast of the oil reservoir quality made using this technology. The technical result achieved shows the increase of efficiency, effectiveness, and ecological compatibility of development of mineral deposits and discovery of a new oil deposit.

Organic electronics: Battery-like artificial synapses

NASA Astrophysics Data System (ADS)

Yang, J. Joshua; Xia, Qiangfei

2017-04-01

Borrowing the operating principles of a battery, a three-terminal organic switch has been developed on a flexible plastic substrate. The device consumes very little power and can be used as an artificial synapse for brain-inspired computing.

Third Conference on Artificial Intelligence for Space Applications, part 2

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Applying "Climate" system to teaching basic climatology and raising public awareness of climate change issues

NASA Astrophysics Data System (ADS)

Gordova, Yulia; Okladnikov, Igor; Titov, Alexander; Gordov, Evgeny

2016-04-01

While there is a strong demand for innovation in digital learning, available training programs in the environmental sciences have no time to adapt to rapid changes in the domain content. A joint group of scientists and university teachers develops and implements an educational environment for new learning experiences in basics of climatic science and its applications. This so-called virtual learning laboratory "Climate" contains educational materials and interactive training courses developed to provide undergraduate and graduate students with profound understanding of changes in regional climate and environment. The main feature of this Laboratory is that students perform their computational tasks on climate modeling and evaluation and assessment of climate change using the typical tools of the "Climate" information-computational system, which are usually used by real-life practitioners performing such kind of research. Students have an opportunity to perform computational laboratory works using information-computational tools of the system and improve skills of their usage simultaneously with mastering the subject. We did not create an artificial learning environment to pass the trainings. On the contrary, the main purpose of association of the educational block and computational information system was to familiarize students with the real existing technologies for monitoring and analysis of data on the state of the climate. Trainings are based on technologies and procedures which are typical for Earth system sciences. Educational courses are designed to permit students to conduct their own investigations of ongoing and future climate changes in a manner that is essentially identical to the techniques used by national and international climate research organizations. All trainings are supported by lectures, devoted to the basic aspects of modern climatology, including analysis of current climate change and its possible impacts ensuring effective links between theory and practice. Along with its usage in graduate and postgraduate education, "Climate" is used as a framework for a developed basic information course on climate change for common public. In this course basic concepts and problems of modern climate change and its possible consequences are described for non-specialists. The course will also include links to relevant information resources on topical issues of Earth Sciences and a number of case studies, which are carried out for a selected region to consolidate the received knowledge.

Pygmalion's Computer.

ERIC Educational Resources Information Center

Peelle, Howard A.

Computers have undoubtedly entered the educational arena, mainly in the areas of computer-assisted instruction (CAI) and artificial intelligence, but whether educators should embrace computers and exactly how they should use them are matters of great debate. The use of computers in support of educational administration is widely accepted.…

Future Tense: Science Fiction Confronts the New Science.

ERIC Educational Resources Information Center

Antczak, Janice

1990-01-01

Describes 10 science fiction stories for young readers whose contents address recent developments on the frontiers of scientific research, including genetic engineering, artificial intelligence, and robotics. The use of these materials to inform young readers about the issues and dangers involved in scientific developments is discussed. (CLB)

Artificial Intelligence Methodologies and Their Application to Diabetes

PubMed Central

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

2017-01-01

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. PMID:28539087

Artificial Intelligence Methodologies and Their Application to Diabetes.

PubMed

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.

An Investment Behavior Analysis using by Brain Computer Interface

NASA Astrophysics Data System (ADS)

Suzuki, Kyoko; Kinoshita, Kanta; Miyagawa, Kazuhiro; Shiomi, Shinichi; Misawa, Tadanobu; Shimokawa, Tetsuya

In this paper, we will construct a new Brain Computer Interface (BCI), for the purpose of analyzing human's investment decision makings. The BCI is made up of three functional parts which take roles of, measuring brain information, determining market price in an artificial market, and specifying investment decision model, respectively. When subjects make decisions, their brain information is conveyed to the part of specifying investment decision model through the part of measuring brain information, whereas, their decisions of investment order are sent to the part of artificial market to form market prices. Both the support vector machine and the 3 layered perceptron are used to assess the investment decision model. In order to evaluate our BCI, we conduct an experiment in which subjects and a computer trader agent trade shares of stock in the artificial market and test how the computer trader agent can forecast market price formation and investment decision makings from the brain information of subjects. The result of the experiment shows that the brain information can improve the accuracy of forecasts, and so the computer trader agent can supply market liquidity to stabilize market volatility without his loss.

Planning: supporting and optimizing clinical guidelines execution.

PubMed

Anselma, Luca; Montani, Stefania

2008-01-01

A crucial feature of computerized clinical guidelines (CGs) lies in the fact that they may be used not only as conventional documents (as if they were just free text) describing general procedures that users have to follow. In fact, thanks to a description of their actions and control flow in some semiformal representation language, CGs can also take advantage of Computer Science methods and Information Technology infrastructures and techniques, to become executable documents, in the sense that they may support clinical decision making and clinical procedures execution. In order to reach this goal, some advanced planning techniques, originally developed within the Artificial Intelligence (AI) community, may be (at least partially) resorted too, after a proper adaptation to the specific CG needs has been carried out.

A Decision Support System for Optimum Use of Fertilizers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoskinson, Reed Louis; Hess, John Richard; Fink, Raymond Keith

1999-07-01

The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems’ infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend inmore » the agricultural decision-making process.« less

A Decision Support System for Optimum Use of Fertilizers

DOE Office of Scientific and Technical Information (OSTI.GOV)

R. L. Hoskinson; J. R. Hess; R. K. Fink

1999-07-01

The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems' infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend inmore » the agricultural decision-making process.« less

Importance of databases of nucleic acids for bioinformatic analysis focused to genomics

NASA Astrophysics Data System (ADS)

Jimenez-Gutierrez, L. R.; Barrios-Hernández, C. J.; Pedraza-Ferreira, G. R.; Vera-Cala, L.; Martinez-Perez, F.

2016-08-01

Recently, bioinformatics has become a new field of science, indispensable in the analysis of millions of nucleic acids sequences, which are currently deposited in international databases (public or private); these databases contain information of genes, RNA, ORF, proteins, intergenic regions, including entire genomes from some species. The analysis of this information requires computer programs; which were renewed in the use of new mathematical methods, and the introduction of the use of artificial intelligence. In addition to the constant creation of supercomputing units trained to withstand the heavy workload of sequence analysis. However, it is still necessary the innovation on platforms that allow genomic analyses, faster and more effectively, with a technological understanding of all biological processes.

Distribution Locational Real-Time Pricing Based Smart Building Control and Management

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hao, Jun; Dai, Xiaoxiao; Zhang, Yingchen

This paper proposes an real-virtual parallel computing scheme for smart building operations aiming at augmenting overall social welfare. The University of Denver's campus power grid and Ritchie fitness center is used for demonstrating the proposed approach. An artificial virtual system is built in parallel to the real physical system to evaluate the overall social cost of the building operation based on the social science based working productivity model, numerical experiment based building energy consumption model and the power system based real-time pricing mechanism. Through interactive feedback exchanged between the real and virtual system, enlarged social welfare, including monetary cost reductionmore » and energy saving, as well as working productivity improvements, can be achieved.« less

Lab architecture

NASA Astrophysics Data System (ADS)

Crease, Robert P.

2008-04-01

There are few more dramatic illustrations of the vicissitudes of laboratory architecturethan the contrast between Building 20 at the Massachusetts Institute of Technology (MIT) and its replacement, the Ray and Maria Stata Center. Building 20 was built hurriedly in 1943 as temporary housing for MIT's famous Rad Lab, the site of wartime radar research, and it remained a productive laboratory space for over half a century. A decade ago it was demolished to make way for the Stata Center, an architecturally striking building designed by Frank Gehry to house MIT's computer science and artificial intelligence labs (above). But in 2004 - just two years after the Stata Center officially opened - the building was criticized for being unsuitable for research and became the subject of still ongoing lawsuits alleging design and construction failures.

Automation technology for aerospace power management

NASA Technical Reports Server (NTRS)

Larsen, R. L.

1982-01-01

The growing size and complexity of spacecraft power systems coupled with limited space/ground communications necessitate increasingly automated onboard control systems. Research in computer science, particularly artificial intelligence has developed methods and techniques for constructing man-machine systems with problem-solving expertise in limited domains which may contribute to the automation of power systems. Since these systems perform tasks which are typically performed by human experts they have become known as Expert Systems. A review of the current state of the art in expert systems technology is presented, and potential applications in power systems management are considered. It is concluded that expert systems appear to have significant potential for improving the productivity of operations personnel in aerospace applications, and in automating the control of many aerospace systems.

Impact of different variables on the outcome of patients with clinically confined prostate carcinoma: prediction of pathologic stage and biochemical failure using an artificial neural network.

PubMed

Ziada, A M; Lisle, T C; Snow, P B; Levine, R F; Miller, G; Crawford, E D

2001-04-15

The advent of advanced computing techniques has provided the opportunity to analyze clinical data using artificial intelligence techniques. This study was designed to determine whether a neural network could be developed using preoperative prognostic indicators to predict the pathologic stage and time of biochemical failure for patients who undergo radical prostatectomy. The preoperative information included TNM stage, prostate size, prostate specific antigen (PSA) level, biopsy results (Gleason score and percentage of positive biopsy), as well as patient age. All 309 patients underwent radical prostatectomy at the University of Colorado Health Sciences Center. The data from all patients were used to train a multilayer perceptron artificial neural network. The failure rate was defined as a rise in the PSA level > 0.2 ng/mL. The biochemical failure rate in the data base used was 14.2%. Univariate and multivariate analyses were performed to validate the results. The neural network statistics for the validation set showed a sensitivity and specificity of 79% and 81%, respectively, for the prediction of pathologic stage with an overall accuracy of 80% compared with an overall accuracy of 67% using the multivariate regression analysis. The sensitivity and specificity for the prediction of failure were 67% and 85%, respectively, demonstrating a high confidence in predicting failure. The overall accuracy rates for the artificial neural network and the multivariate analysis were similar. Neural networks can offer a convenient vehicle for clinicians to assess the preoperative risk of disease progression for patients who are about to undergo radical prostatectomy. Continued investigation of this approach with larger data sets seems warranted. Copyright 2001 American Cancer Society.

Artificial intelligence: Learning to play Go from scratch

NASA Astrophysics Data System (ADS)

Singh, Satinder; Okun, Andy; Jackson, Andrew

2017-10-01

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

A Workshop on the Integration of Numerical and Symbolic Computing Methods Held in Saratoga Springs, New York on July 9-11, 1990

DTIC Science & Technology

1991-04-01

SUMMARY OF COMPLETED PROJECT (for public use) The summary (about 200 words) must be self-contained and intellegible to a scientifically literate reader...dialogue among re- searchers in symbolic methods and numerical computation, and their appli- cations in certain disciplines of artificial intelligence...Lozano-Perez Purdue University Artificial Intelligence Laboratory West Lafayette, IN 47907 Massachusetts Institute of Technology (317) 494-6181 545

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

NASA Astrophysics Data System (ADS)

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.

Information Processing Research.

DTIC Science & Technology

1986-09-01

Kuroe. The 3D MOSAIC Scene Understanding System. In Alan Bundy, Editor, Proceedings of the Eighth International Joint Conference on Artificial ... Artificial Jntelligencel7(1-3):409-460, August, 1981. Given a single picture which is a projection of a three-dimensional scene onto the two...values are detected as outliers by computing the distribution of values over a sliding 80 msec window. During the third pass (based on artificial

Artificial Intelligence for Pathologists Is Not Near--It Is Here: Description of a Prototype That Can Transform How We Practice Pathology Tomorrow.

PubMed

Ye, Jay J

2015-07-01

Pathologists' daily tasks consist of both the professional interpretation of slides and the secretarial tasks of translating these interpretations into final pathology reports, the latter of which is a time-consuming endeavor for most pathologists. To describe an artificial intelligence that performs secretarial tasks, designated as Secretary-Mimicking Artificial Intelligence (SMILE). The underling implementation of SMILE is a collection of computer programs that work in concert to "listen to" the voice commands and to "watch for" the changes of windows caused by slide bar code scanning; SMILE responds to these inputs by acting upon PowerPath Client windows (Sunquest Information Systems, Tucson, Arizona) and its Microsoft Word (Microsoft, Redmond, Washington) Add-In window, eventuating in the reports being typed and finalized. Secretary-Mimicking Artificial Intelligence also communicates relevant information to the pathologist via the computer speakers and message box on the screen. Secretary-Mimicking Artificial Intelligence performs many secretarial tasks intelligently and semiautonomously, with rapidity and consistency, thus enabling pathologists to focus on slide interpretation, which results in a marked increase in productivity, decrease in errors, and reduction of stress in daily practice. Secretary-Mimicking Artificial Intelligence undergoes encounter-based learning continually, resulting in a continuous improvement in its knowledge-based intelligence. Artificial intelligence for pathologists is both feasible and powerful. The future widespread use of artificial intelligence in our profession is certainly going to transform how we practice pathology.

Knowledge Engineering: The Interplay between Information and Historical Sciences in the Study of Change.

ERIC Educational Resources Information Center

McCrank, Lawrence J.

1992-01-01

Discusses trends in the fields of knowledge engineering and historical sciences to speculate about possibilities of converging interests and applications. Topics addressed include artificial intelligence and expert systems; the history of information science; history as a related field; historians as information scientists; multidisciplinary…

Teaching Science Out-of-School with Special Reference to Biology.

ERIC Educational Resources Information Center

Meyer, G. Rex, Ed.; Rao, A. N., Ed.

This book contains a selection of previously unpublished papers from an international Asian symposium on out-of-school science activities. These papers include: "Educational and Social Values of Out-of-School Science" (Peter Kelly); "School Versus Out-of-School: An Artificial Dichotomy" (William Mayer); "Biology of…

Programming Enzyme-Initiated Autonomous DNAzyme Nanodevices in Living Cells.

PubMed

Chen, Feng; Bai, Min; Cao, Ke; Zhao, Yue; Cao, Xiaowen; Wei, Jing; Wu, Na; Li, Jiang; Wang, Lihua; Fan, Chunhai; Zhao, Yongxi

2017-12-26

Molecular nanodevices are computational assemblers that switch defined states upon external stimulation. However, interfacing artificial nanodevices with natural molecular machineries in living cells remains a great challenge. Here, we delineate a generic method for programming assembly of enzyme-initiated DNAzyme nanodevices (DzNanos). Two programs including split assembly of two partzymes and toehold exchange displacement assembly of one intact DNAzyme initiated by telomerase are computed. The intact one obtains higher assembly yield and catalytic performance ascribed to proper conformation folding and active misplaced assembly. By employing MnO 2 nanosheets as both DNA carriers and source of Mn 2+ as DNAzyme cofactor, we find that this DzNano is well assembled via a series of conformational states in living cells and operates autonomously with sustained cleavage activity. Other enzymes can also induce corresponding DzNano assembly with defined programming modules. These DzNanos not only can monitor enzyme catalysis in situ but also will enable the implementation of cellular stages, behaviors, and pathways for basic science, diagnostic, and therapeutic applications as genetic circuits.

Potential consequences of clinical application of artificial gametes: a systematic review of stakeholder views.

PubMed

Hendriks, Saskia; Dondorp, Wybo; de Wert, Guido; Hamer, Geert; Repping, Sjoerd; Dancet, Eline A F

2015-01-01

Recent progress in the formation of artificial gametes, i.e. gametes generated from progenitors or somatic cells, has led to scientific and societal discussion about their use in medically assisted reproduction. In animals, live births have already been achieved using artificial gametes of varying (cell type) sources and biological research seems to be progressing steadily toward clinical application in humans. Artificial gametes could potentially help not only infertile heterosexual couples of reproductive age of which one or both partners lacks functional gametes, but also post-menopausal women and same-sex couples, to conceive a child who will be genetically related to them. But as clinical application of these new technologies may have wider societal consequences, a proactive consideration of the possible impact seems timely and important. This review aims to contribute to this by providing a systematic overview of the potential consequences of clinical application of artificial gametes anticipated by different stakeholders. The electronic database 'Medline/Pubmed' was systematically searched with medical subject heading terms (MesH) for articles published in English between January 1970 and December 2013. Articles were selected based on eligibility and reference lists of eligible studies were hand searched. The reported potential consequences of clinical application of artificial gametes were extracted from the articles and were grouped into categories by content analysis. Per category, we noted which stakeholders referred to which potential consequences, based on author affiliations and, if applicable, study participants. The systematic search yielded 2424 articles, and 84 studies were included after screening. Nine positive consequences, 21 specific consequences requiring consideration and 22 recommendations referring to clinical application of artificial gametes were documented. All positive consequences, consequences requiring consideration and recommendations could be categorized under the following eight objectives to be safeguarded during clinical application of artificial gametes: (i) timing the implementation of new treatments correctly, (ii) meeting 'plausible demands of patients', (iii) improving and safeguarding public health, (iv) promoting the progress of medical science in the interest of future patients, (v) providing treatments that are morally acceptable for the general public, (vi) controlling medical practice, (vii) offering treatments that allow acquisition of informed consent and (viii) funding treatments fairly. Professionals specialized in biomedical science, science journalists and professionals specialized in ethics all addressed these eight objectives on artificial gametes, whereas professionals specialized in law or political science addressed seven objectives. Although one study reported on the perspective of parents of under-aged patients on three objectives, the perspectives of patients themselves were not reported by the reviewed literature. Of course, clinical introduction of artificial gametes should only be considered on the basis of reassuring outcomes of appropriate preclinical effectiveness and safety studies. In addition, potential users' views on the desirability and acceptability of artificial gametes should be studied before clinical introduction. A societal debate including all stakeholders is needed to determine the relative importance of all arguments in favor of and against the introduction of artificial gametes into clinical practice. More broadly, establishing pre-implementation processes for new medical techniques is relevant for all fields of medicine. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

An Overview of Computer-Based Natural Language Processing.

ERIC Educational Resources Information Center

Gevarter, William B.

Computer-based Natural Language Processing (NLP) is the key to enabling humans and their computer-based creations to interact with machines using natural languages (English, Japanese, German, etc.) rather than formal computer languages. NLP is a major research area in the fields of artificial intelligence and computational linguistics. Commercial…

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

ERIC Educational Resources Information Center

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)

Computational protein design with backbone plasticity

PubMed Central

MacDonald, James T.; Freemont, Paul S.

2016-01-01

The computational algorithms used in the design of artificial proteins have become increasingly sophisticated in recent years, producing a series of remarkable successes. The most dramatic of these is the de novo design of artificial enzymes. The majority of these designs have reused naturally occurring protein structures as ‘scaffolds’ onto which novel functionality can be grafted without having to redesign the backbone structure. The incorporation of backbone flexibility into protein design is a much more computationally challenging problem due to the greatly increased search space, but promises to remove the limitations of reusing natural protein scaffolds. In this review, we outline the principles of computational protein design methods and discuss recent efforts to consider backbone plasticity in the design process. PMID:27911735

Design-Based Intervention Research as the Science of the Doubly Artificial

ERIC Educational Resources Information Center

Cole, Michael; Packer, Martin

2016-01-01

This article uses a variety of principles of cultural-historical activity theory to extend Herbert Simon's (1996) insight into the inherent linkage between the creation of artifacts and design. We argue that design research must grapple with the doubly artificial, as the classrooms in which many educational designs are implemented are themselves…

Artificial multilayers and nanomagnetic materials

PubMed Central

SHINJO, Teruya

2013-01-01

The author has been actively engaged in research on nanomagnetic materials for about 50 years. Nanomagnetic materials are comprised of ferromagnetic systems for which the size and shape are controlled on a nanometer scale. Typical examples are ultrafine particles, ultrathin films, multilayered films and nano-patterned films. In this article, the following four areas of the author’s studies are described. (1) Mössbauer spectroscopic studies of nanomagnetic materials and interface magnetism. (2) Preparation and characterization of metallic multilayers with artificial superstructures. (3) Giant magnetoresistance (GMR) effect in magnetic multilayers. (4) Novel properties of nanostructured ferromagnetic thin films (dots and wires). A subject of particular interest in the author’s research was the artificially prepared multilayers consisting of metallic elements. The motivation to initiate the multilayer investigation is described and the physical properties observed in the artificial multilayers are introduced. The author’s research was initially in the field of pure physical science and gradually extended into applied science. His achievements are highly regarded not only from the fundamental point of view but also from the technological viewpoint. PMID:23391605

Know Your Discipline: Teaching the Philosophy of Computer Science

ERIC Educational Resources Information Center

Tedre, Matti

2007-01-01

The diversity and interdisciplinarity of computer science and the multiplicity of its uses in other sciences make it hard to define computer science and to prescribe how computer science should be carried out. The diversity of computer science also causes friction between computer scientists from different branches. Computer science curricula, as…

Data Mining and Knowledge Discover - IBM Cognitive Alternatives for NASA KSC

NASA Technical Reports Server (NTRS)

Velez, Victor Hugo

2016-01-01

Skillful tools in cognitive computing to transform industries have been found favorable and profitable for different Directorates at NASA KSC. In this study is shown how cognitive computing systems can be useful for NASA when computers are trained in the same way as humans are to gain knowledge over time. Increasing knowledge through senses, learning and a summation of events is how the applications created by the firm IBM empower the artificial intelligence in a cognitive computing system. NASA has explored and applied for the last decades the artificial intelligence approach specifically with cognitive computing in few projects adopting similar models proposed by IBM Watson. However, the usage of semantic technologies by the dedicated business unit developed by IBM leads these cognitive computing applications to outperform the functionality of the inner tools and present outstanding analysis to facilitate the decision making for managers and leads in a management information system.

Artificial neuron operations and spike-timing-dependent plasticity using memristive devices for brain-inspired computing

NASA Astrophysics Data System (ADS)

Marukame, Takao; Nishi, Yoshifumi; Yasuda, Shin-ichi; Tanamoto, Tetsufumi

2018-04-01

The use of memristive devices for creating artificial neurons is promising for brain-inspired computing from the viewpoints of computation architecture and learning protocol. We present an energy-efficient multiplier accumulator based on a memristive array architecture incorporating both analog and digital circuitries. The analog circuitry is used to full advantage for neural networks, as demonstrated by the spike-timing-dependent plasticity (STDP) in fabricated AlO x /TiO x -based metal-oxide memristive devices. STDP protocols for controlling periodic analog resistance with long-range stability were experimentally verified using a variety of voltage amplitudes and spike timings.

Method of mobile robot indoor navigation by artificial landmarks with use of computer vision

NASA Astrophysics Data System (ADS)

Glibin, E. S.; Shevtsov, A. A.; Enik, O. A.

2018-05-01

The article describes an algorithm of the mobile robot indoor navigation based on the use of visual odometry. The results of the experiment identifying calculation errors in the distance traveled on a slip are presented. It is shown that the use of computer vision allows one to correct erroneous coordinates of the robot with the help of artificial landmarks. The control system utilizing the proposed method has been realized on the basis of Arduino Mego 2560 controller and a single-board computer Raspberry Pi 3. The results of the experiment on the mobile robot navigation with the use of this control system are presented.

Modified Method of Adaptive Artificial Viscosity for Solution of Gas Dynamics Problems on Parallel Computer Systems

NASA Astrophysics Data System (ADS)

Popov, Igor; Sukov, Sergey

2018-02-01

A modification of the adaptive artificial viscosity (AAV) method is considered. This modification is based on one stage time approximation and is adopted to calculation of gasdynamics problems on unstructured grids with an arbitrary type of grid elements. The proposed numerical method has simplified logic, better performance and parallel efficiency compared to the implementation of the original AAV method. Computer experiments evidence the robustness and convergence of the method to difference solution.

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

PubMed Central

Brenkus, Lawrence M.

1984-01-01

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

Lexical and sublexical units in speech perception.

PubMed

Giroux, Ibrahima; Rey, Arnaud

2009-03-01

Saffran, Newport, and Aslin (1996a) found that human infants are sensitive to statistical regularities corresponding to lexical units when hearing an artificial spoken language. Two sorts of segmentation strategies have been proposed to account for this early word-segmentation ability: bracketing strategies, in which infants are assumed to insert boundaries into continuous speech, and clustering strategies, in which infants are assumed to group certain speech sequences together into units (Swingley, 2005). In the present study, we test the predictions of two computational models instantiating each of these strategies i.e., Serial Recurrent Networks: Elman, 1990; and Parser: Perruchet & Vinter, 1998 in an experiment where we compare the lexical and sublexical recognition performance of adults after hearing 2 or 10 min of an artificial spoken language. The results are consistent with Parser's predictions and the clustering approach, showing that performance on words is better than performance on part-words only after 10 min. This result suggests that word segmentation abilities are not merely due to stronger associations between sublexical units but to the emergence of stronger lexical representations during the development of speech perception processes. Copyright © 2009, Cognitive Science Society, Inc.

An immune-inspired semi-supervised algorithm for breast cancer diagnosis.

PubMed

Peng, Lingxi; Chen, Wenbin; Zhou, Wubai; Li, Fufang; Yang, Jin; Zhang, Jiandong

2016-10-01

Breast cancer is the most frequently and world widely diagnosed life-threatening cancer, which is the leading cause of cancer death among women. Early accurate diagnosis can be a big plus in treating breast cancer. Researchers have approached this problem using various data mining and machine learning techniques such as support vector machine, artificial neural network, etc. The computer immunology is also an intelligent method inspired by biological immune system, which has been successfully applied in pattern recognition, combination optimization, machine learning, etc. However, most of these diagnosis methods belong to a supervised diagnosis method. It is very expensive to obtain labeled data in biology and medicine. In this paper, we seamlessly integrate the state-of-the-art research on life science with artificial intelligence, and propose a semi-supervised learning algorithm to reduce the need for labeled data. We use two well-known benchmark breast cancer datasets in our study, which are acquired from the UCI machine learning repository. Extensive experiments are conducted and evaluated on those two datasets. Our experimental results demonstrate the effectiveness and efficiency of our proposed algorithm, which proves that our algorithm is a promising automatic diagnosis method for breast cancer. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Advances in Artificial Neural Networks - Methodological Development and Application

USDA-ARS?s Scientific Manuscript database

Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other ne...

Artificial Intelligence.

ERIC Educational Resources Information Center

Wash, Darrel Patrick

1989-01-01

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

Artificial Intelligence: Underlying Assumptions and Basic Objectives.

ERIC Educational Resources Information Center

Cercone, Nick; McCalla, Gordon

1984-01-01

Presents perspectives on methodological assumptions underlying research efforts in artificial intelligence (AI) and charts activities, motivations, methods, and current status of research in each of the major AI subareas: natural language understanding; computer vision; expert systems; search, problem solving, planning; theorem proving and logic…

Thinking, Creativity, and Artificial Intelligence.

ERIC Educational Resources Information Center

DeSiano, Michael; DeSiano, Salvatore

This document provides an introduction to the relationship between the current knowledge of focused and creative thinking and artificial intelligence. A model for stages of focused and creative thinking gives: problem encounter/setting, preparation, concentration/incubation, clarification/generation and evaluation/judgment. While a computer can…

How Neural Networks Learn from Experience.

ERIC Educational Resources Information Center

Hinton, Geoffrey E.

1992-01-01

Discusses computational studies of learning in artificial neural networks and findings that may provide insights into the learning abilities of the human brain. Describes efforts to test theories about brain information processing, using artificial neural networks. Vignettes include information concerning how a neural network represents…

The soft computing-based approach to investigate allergic diseases: a systematic review.

PubMed

Tartarisco, Gennaro; Tonacci, Alessandro; Minciullo, Paola Lucia; Billeci, Lucia; Pioggia, Giovanni; Incorvaia, Cristoforo; Gangemi, Sebastiano

2017-01-01

Early recognition of inflammatory markers and their relation to asthma, adverse drug reactions, allergic rhinitis, atopic dermatitis and other allergic diseases is an important goal in allergy. The vast majority of studies in the literature are based on classic statistical methods; however, developments in computational techniques such as soft computing-based approaches hold new promise in this field. The aim of this manuscript is to systematically review the main soft computing-based techniques such as artificial neural networks, support vector machines, bayesian networks and fuzzy logic to investigate their performances in the field of allergic diseases. The review was conducted following PRISMA guidelines and the protocol was registered within PROSPERO database (CRD42016038894). The research was performed on PubMed and ScienceDirect, covering the period starting from September 1, 1990 through April 19, 2016. The review included 27 studies related to allergic diseases and soft computing performances. We observed promising results with an overall accuracy of 86.5%, mainly focused on asthmatic disease. The review reveals that soft computing-based approaches are suitable for big data analysis and can be very powerful, especially when dealing with uncertainty and poorly characterized parameters. Furthermore, they can provide valuable support in case of lack of data and entangled cause-effect relationships, which make it difficult to assess the evolution of disease. Although most works deal with asthma, we believe the soft computing approach could be a real breakthrough and foster new insights into other allergic diseases as well.

Connectionist Modelling and Education.

ERIC Educational Resources Information Center

Evers, Colin W.

2000-01-01

Provides a detailed, technical introduction to the state of cognitive science research, in particular the rise of the "new cognitive science," especially artificial neural net (ANN) models. Explains one influential ANN model and describes diverse applications and their implications for education. (EV)

Citizen Science Provides Valuable Data for Monitoring Global Night Sky Luminance

PubMed Central

Kyba, Christopher C. M.; Wagner, Janna M.; Kuechly, Helga U.; Walker, Constance E.; Elvidge, Christopher D.; Falchi, Fabio; Ruhtz, Thomas; Fischer, Jürgen; Hölker, Franz

2013-01-01

The skyglow produced by artificial lights at night is one of the most dramatic anthropogenic modifications of Earth's biosphere. The GLOBE at Night citizen science project allows individual observers to quantify skyglow using star maps showing different levels of light pollution. We show that aggregated GLOBE at Night data depend strongly on artificial skyglow, and could be used to track lighting changes worldwide. Naked eye time series can be expected to be very stable, due to the slow pace of human eye evolution. The standard deviation of an individual GLOBE at Night observation is found to be 1.2 stellar magnitudes. Zenith skyglow estimates from the “First World Atlas of Artificial Night Sky Brightness” are tested using a subset of the GLOBE at Night data. Although we find the World Atlas overestimates sky brightness in the very center of large cities, its predictions for Milky Way visibility are accurate. PMID:23677222

A Microworld Approach to the Formalization of Musical Knowledge.

ERIC Educational Resources Information Center

Honing, Henkjan

1993-01-01

Discusses the importance of applying computational modeling and artificial intelligence techniques to music cognition and computer music research. Recommends three uses of microworlds to trim computational theories to their bare minimum, allowing for better and easier comparison. (CFR)

Artificial Intelligence and the Teaching of Reading and Writing by Computers.

ERIC Educational Resources Information Center

Balajthy, Ernest

1985-01-01

Discusses how computers can "converse" with students for teaching purposes, demonstrates how these interactions are becoming more complex, and explains how the computer's role is becoming more "human" in giving intelligent responses to students. (HOD)

An Interdisciplinary Bibliography for Computers and the Humanities Courses.

ERIC Educational Resources Information Center

Ehrlich, Heyward

1991-01-01

Presents an annotated bibliography of works related to the subject of computers and the humanities. Groups items into textbooks and overviews; introductions; human and computer languages; literary and linguistic analysis; artificial intelligence and robotics; social issue debates; computers' image in fiction; anthologies; writing and the…

Numerical solution of differential equations by artificial neural networks

NASA Technical Reports Server (NTRS)

Meade, Andrew J., Jr.

1995-01-01

Conventionally programmed digital computers can process numbers with great speed and precision, but do not easily recognize patterns or imprecise or contradictory data. Instead of being programmed in the conventional sense, artificial neural networks (ANN's) are capable of self-learning through exposure to repeated examples. However, the training of an ANN can be a time consuming and unpredictable process. A general method is being developed by the author to mate the adaptability of the ANN with the speed and precision of the digital computer. This method has been successful in building feedforward networks that can approximate functions and their partial derivatives from examples in a single iteration. The general method also allows the formation of feedforward networks that can approximate the solution to nonlinear ordinary and partial differential equations to desired accuracy without the need of examples. It is believed that continued research will produce artificial neural networks that can be used with confidence in practical scientific computing and engineering applications.

Development of soft-sphere contact models for thermal heat conduction in granular flows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morris, A. B.; Pannala, S.; Ma, Z.

2016-06-08

Conductive heat transfer to flowing particles occurs when two particles (or a particle and wall) come into contact. The direct conduction between the two bodies depends on the collision dynamics, namely the size of the contact area and the duration of contact. For soft-sphere discrete-particle simulations, it is computationally expensive to resolve the true collision time because doing so would require a restrictively small numerical time step. To improve the computational speed, it is common to increase the 'softness' of the material to artificially increase the collision time, but doing so affects the heat transfer. In this work, two physically-basedmore » correction terms are derived to compensate for the increased contact area and time stemming from artificial particle softening. By including both correction terms, the impact that artificial softening has on the conductive heat transfer is removed, thus enabling simulations at greatly reduced computational times without sacrificing physical accuracy.« less

Prediction of Software Reliability using Bio Inspired Soft Computing Techniques.

PubMed

Diwaker, Chander; Tomar, Pradeep; Poonia, Ramesh C; Singh, Vijander

2018-04-10

A lot of models have been made for predicting software reliability. The reliability models are restricted to using particular types of methodologies and restricted number of parameters. There are a number of techniques and methodologies that may be used for reliability prediction. There is need to focus on parameters consideration while estimating reliability. The reliability of a system may increase or decreases depending on the selection of different parameters used. Thus there is need to identify factors that heavily affecting the reliability of the system. In present days, reusability is mostly used in the various area of research. Reusability is the basis of Component-Based System (CBS). The cost, time and human skill can be saved using Component-Based Software Engineering (CBSE) concepts. CBSE metrics may be used to assess those techniques which are more suitable for estimating system reliability. Soft computing is used for small as well as large-scale problems where it is difficult to find accurate results due to uncertainty or randomness. Several possibilities are available to apply soft computing techniques in medicine related problems. Clinical science of medicine using fuzzy-logic, neural network methodology significantly while basic science of medicine using neural-networks-genetic algorithm most frequently and preferably. There is unavoidable interest shown by medical scientists to use the various soft computing methodologies in genetics, physiology, radiology, cardiology and neurology discipline. CBSE boost users to reuse the past and existing software for making new products to provide quality with a saving of time, memory space, and money. This paper focused on assessment of commonly used soft computing technique like Genetic Algorithm (GA), Neural-Network (NN), Fuzzy Logic, Support Vector Machine (SVM), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC). This paper presents working of soft computing techniques and assessment of soft computing techniques to predict reliability. The parameter considered while estimating and prediction of reliability are also discussed. This study can be used in estimation and prediction of the reliability of various instruments used in the medical system, software engineering, computer engineering and mechanical engineering also. These concepts can be applied to both software and hardware, to predict the reliability using CBSE.

Towards An Integrative Theory Of Consciousness: Part 2 (An Anthology Of Various Other Models)

PubMed Central

De Sousa, Avinash

2013-01-01

The study of consciousness has today moved beyond neurobiology and cognitive models. In the past few years, there has been a surge of research into various newer areas. The present article looks at the non-neurobiological and non-cognitive theories regarding this complex phenomenon, especially ones that self-psychology, self-theory, artificial intelligence, quantum physics, visual cognitive science and philosophy have to offer. Self-psychology has proposed the need to understand the self and its development, and the ramifications of the self for morality and empathy, which will help us understand consciousness better. There have been inroads made from the fields of computer science, machine technology and artificial intelligence, including robotics, into understanding the consciousness of these machines and their implications for human consciousness. These areas are explored. Visual cortex and emotional theories along with their implications are discussed. The phylogeny and evolution of the phenomenon of consciousness is also highlighted, with theories on the emergence of consciousness in fetal and neonatal life. Quantum physics and its insights into the mind, along with the implications of consciousness and physics and their interface are debated. The role of neurophilosophy to understand human consciousness, the functions of such a concept, embodiment, the dark side of consciousness, future research needs and limitations of a scientific theory of consciousness complete the review. The importance and salient features of each theory are discussed along with certain pitfalls, if present. A need for the integration of various theories to understand consciousness from a holistic perspective is stressed. PMID:23678242

Towards an integrative theory of consciousness: part 2 (an anthology of various other models).

PubMed

De Sousa, Avinash

2013-01-01

The study of consciousness has today moved beyond neurobiology and cognitive models. In the past few years, there has been a surge of research into various newer areas. The present article looks at the non-neurobiological and non-cognitive theories regarding this complex phenomenon, especially ones that self-psychology, self-theory, artificial intelligence, quantum physics, visual cognitive science and philosophy have to offer. Self-psychology has proposed the need to understand the self and its development, and the ramifications of the self for morality and empathy, which will help us understand consciousness better. There have been inroads made from the fields of computer science, machine technology and artificial intelligence, including robotics, into understanding the consciousness of these machines and their implications for human consciousness. These areas are explored. Visual cortex and emotional theories along with their implications are discussed. The phylogeny and evolution of the phenomenon of consciousness is also highlighted, with theories on the emergence of consciousness in fetal and neonatal life. Quantum physics and its insights into the mind, along with the implications of consciousness and physics and their interface are debated. The role of neurophilosophy to understand human consciousness, the functions of such a concept, embodiment, the dark side of consciousness, future research needs and limitations of a scientific theory of consciousness complete the review. The importance and salient features of each theory are discussed along with certain pitfalls, if present. A need for the integration of various theories to understand consciousness from a holistic perspective is stressed.

The 'Wow' Signal, Drake Equation and Exoplanet Considerations

NASA Astrophysics Data System (ADS)

Wheeler, E.

It has been 38 years since the most likely artificial transmission ever recorded from a possible extraterrestrial source was received [1, 2]. Using greatly improved technology, subsequent efforts by the Search for Extraterrestrial Intelligence (SETI) have continued, yet silence from space prevails [3]. This article examines whether the transmission was an artificial signal, and if so why it matters, to include the possibility that the modest technology used by the "Big Ear" receiver could have been accommodated by the source. The transmission and the ensuing long silence may be intended. This paper reconsiders the Drake equation, an estimate for the number of civilizations in our galaxy that may possess technology for interstellar signaling [4, 5], and shows that statement of the current alleged best estimate of two civilizations is not supported [6]. An alternate and original method suggests ~100 civilizations. It importantly relies on experience and detectable events, including recent astronomical evidence about exoplanets as cataloged by the European Exoplanet program and by the National Aeronautics and Space Administration (NASA) Exoplanet Science Institute [7, 8]. In addition it addresses major geological and astronomical occurrences that profoundly affected development of life on Earth and might apply similarly for Extraterrestrial Intelligence (ETI). The alternate approach is not intended to compute ETI precisely but to examine the possibility that, though vastly spread, it likely exists. The discussion anticipates difficulties in communication with an alien civilization, hardly an exercise in science fiction, and explores how international groups can participate in future specific response. One response might be to monitor the electromagnetic radiation spectral line of an element to be determined by consensus.

Artificial Intelligence Applications to High-Technology Training.

ERIC Educational Resources Information Center

Dede, Christopher

1987-01-01

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

Artificial Intelligence and CALL.

ERIC Educational Resources Information Center

Underwood, John H.

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

A Symbolic Model of the Nonconscious Acquisition of Information.

ERIC Educational Resources Information Center

Ling, Charles X.; Marinov, Marin

1994-01-01

Challenges Smolensky's theory that human intuitive/nonconscious cognitive processes can only be accurately explained in terms of subsymbolic computations in artificial neural networks. Symbolic learning models of two cognitive tasks involving nonconscious acquisition of information are presented: learning production rules and artificial finite…

Artificial consciousness, artificial emotions, and autonomous robots.

PubMed

Cardon, Alain

2006-12-01

Nowadays for robots, the notion of behavior is reduced to a simple factual concept at the level of the movements. On another hand, consciousness is a very cultural concept, founding the main property of human beings, according to themselves. We propose to develop a computable transposition of the consciousness concepts into artificial brains, able to express emotions and consciousness facts. The production of such artificial brains allows the intentional and really adaptive behavior for the autonomous robots. Such a system managing the robot's behavior will be made of two parts: the first one computes and generates, in a constructivist manner, a representation for the robot moving in its environment, and using symbols and concepts. The other part achieves the representation of the previous one using morphologies in a dynamic geometrical way. The robot's body will be seen for itself as the morphologic apprehension of its material substrata. The model goes strictly by the notion of massive multi-agent's organizations with a morphologic control.

Quantum neural networks: Current status and prospects for development

NASA Astrophysics Data System (ADS)

Altaisky, M. V.; Kaputkina, N. E.; Krylov, V. A.

2014-11-01

The idea of quantum artificial neural networks, first formulated in [34], unites the artificial neural network concept with the quantum computation paradigm. Quantum artificial neural networks were first systematically considered in the PhD thesis by T. Menneer (1998). Based on the works of Menneer and Narayanan [42, 43], Kouda, Matsui, and Nishimura [35, 36], Altaisky [2, 68], Zhou [67], and others, quantum-inspired learning algorithms for neural networks were developed, and are now used in various training programs and computer games [29, 30]. The first practically realizable scaled hardware-implemented model of the quantum artificial neural network is obtained by D-Wave Systems, Inc. [33]. It is a quantum Hopfield network implemented on the basis of superconducting quantum interference devices (SQUIDs). In this work we analyze possibilities and underlying principles of an alternative way to implement quantum neural networks on the basis of quantum dots. A possibility of using quantum neural network algorithms in automated control systems, associative memory devices, and in modeling biological and social networks is examined.

Teachers and artificial intelligence. The Logo connection.

PubMed

Merbler, J B

1990-12-01

This article describes a three-phase program for training special education teachers to teach Logo and artificial intelligence. Logo is derived from the LISP computer language and is relatively simple to learn and use, and it is argued that these factors make it an ideal tool for classroom experimentation in basic artificial intelligence concepts. The program trains teachers to develop simple demonstrations of artificial intelligence using Logo. The material that the teachers learn to teach is suitable as an advanced level topic for intermediate- through secondary-level students enrolled in computer competency or similar courses. The material emphasizes problem-solving and thinking skills using a nonverbal expressive medium (Logo), thus it is deemed especially appropriate for hearing-impaired children. It is also sufficiently challenging for academically talented children, whether hearing or deaf. Although the notion of teachers as programmers is controversial, Logo is relatively easy to learn, has direct implications for education, and has been found to be an excellent tool for empowerment-for both teachers and children.

AI and cognitive science: the past and next 30 years.

PubMed

Forbus, Kenneth D

2010-07-01

Artificial Intelligence (AI) is a core area of Cognitive Science, yet today few AI researchers attend the Cognitive Science Society meetings. This essay examines why, how AI has changed over the last 30 years, and some emerging areas of potential interest where AI and the Society can go together in the next 30 years, if they choose. Copyright © 2010 Cognitive Science Society, Inc.

Space science experimentation automation and support

NASA Technical Reports Server (NTRS)

Frainier, Richard J.; Groleau, Nicolas; Shapiro, Jeff C.

1994-01-01

This paper outlines recent work done at the NASA Ames Artificial Intelligence Research Laboratory on automation and support of science experiments on the US Space Shuttle in low earth orbit. Three approaches to increasing the science return of these experiments using emerging automation technologies are described: remote control (telescience), science advisors for astronaut operators, and fully autonomous experiments. The capabilities and limitations of these approaches are reviewed.

Automatic aortic anastomosis with an innovative computer-controlled circular stapler for surgical treatment of aortic aneurysm.

PubMed

Takata, Munehisa; Watanabe, Go; Ohtake, Hiroshi; Ushijima, Teruaki; Yamaguchi, Shojiro; Kikuchi, Yujiro; Yamamoto, Yoshitaka

2011-05-01

This study applied a computer-controlled mechanical stapler to vascular end-to-end anastomosis to achieve an automatic aortic anastomosis between the aorta and an artificial graft. In this experimental study, we created a mechanical end-to-end anastomotic model and assessed the strength of the anastomotic site under high pressure. We used a computer-controlled circular stapler named iDrive (Power Medical Interventions, Covidien plc, Dublin, Ireland) for the anastomosis between the porcine aorta and an artificial graft. Then the mechanically stapled group (group A) and the manually sutured group (group B) were compared 10 times, and we assessed the differences at several levels of pressure. To use a mechanical stapler in vascular anastomosis, some special preparations of both the aorta and the artificial graft are necessary to narrow the open end before the procedures. To solve this problem, we established a specially designed purse-string suture for both and finally established end-to-end vascular anastomosis. The anastomosis speed of group A was statistically significantly faster than that of group B (P < .01). The group A anastomotic sites also showed significantly more tolerance to high pressure than those of group B. The computer-controlled stapling device enabled reliable anastomosis of the aorta and the artificial graft. This study showed that mechanical vascular anastomosis with the iDrive was sufficiently strong and safe relative to manual suturing. Copyright © 2011 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.

Knowledge Based Systems: A Critical Survey of Major Concepts, Issues, and Techniques. M.S. Thesis Final Report, 1 Jul. 1985 - 31 Dec. 1987

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Kavi, Srinu

1984-01-01

This Working Paper Series entry presents a detailed survey of knowledge based systems. After being in a relatively dormant state for many years, only recently is Artificial Intelligence (AI) - that branch of computer science that attempts to have machines emulate intelligent behavior - accomplishing practical results. Most of these results can be attributed to the design and use of Knowledge-Based Systems, KBSs (or ecpert systems) - problem solving computer programs that can reach a level of performance comparable to that of a human expert in some specialized problem domain. These systems can act as a consultant for various requirements like medical diagnosis, military threat analysis, project risk assessment, etc. These systems possess knowledge to enable them to make intelligent desisions. They are, however, not meant to replace the human specialists in any particular domain. A critical survey of recent work in interactive KBSs is reported. A case study (MYCIN) of a KBS, a list of existing KBSs, and an introduction to the Japanese Fifth Generation Computer Project are provided as appendices. Finally, an extensive set of KBS-related references is provided at the end of the report.

An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm with Application to the Detection of Distributed Computer Network Intrusions

DTIC Science & Technology

2007-03-01

Intelligence AIS Artificial Immune System ANN Artificial Neural Networks API Application Programming Interface BFS Breadth-First Search BIS Biological...problem domain is too large for only one algorithm’s application . It ranges from network - based sniffer systems, responsible for Enterprise-wide coverage...options to network administrators in choosing detectors to employ in future ID applications . Objectives Our hypothesis validity is based on a set

[Artificial organs].

PubMed

Raguin, Thibaut; Dupret-Bories, Agnès; Debry, Christian

2017-01-01

Research has been fighting against organ failure and shortage of donations by supplying artificial organs for many years. With the raise of new technologies, tissue engineering and regenerative medicine, many organs can benefit of an artificial equivalent: thanks to retinal implants some blind people can visualize stimuli, an artificial heart can be proposed in case of cardiac failure while awaiting for a heart transplant, artificial larynx enables laryngectomy patients to an almost normal life, while the diabetic can get a glycemic self-regulation controlled by smartphones with an artificial device. Dialysis devices become portable, as well as the oxygenation systems for terminal respiratory failure. Bright prospects are being explored or might emerge in a near future. However, the retrospective assessment of putative side effects is not yet sufficient. Finally, the cost of these new devices is significant even if the advent of three dimensional printers may reduce it. © 2017 médecine/sciences – Inserm.

Training Software in Artificial-Intelligence Computing Techniques

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

2005-01-01

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

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

Artificial proteins as allosteric modulators of PDZ3 and SH3 in two-domain constructs: A computational characterization of novel chimeric proteins.

PubMed

Kirubakaran, Palani; Pfeiferová, Lucie; Boušová, Kristýna; Bednarova, Lucie; Obšilová, Veronika; Vondrášek, Jiří

2016-10-01

Artificial multidomain proteins with enhanced structural and functional properties can be utilized in a broad spectrum of applications. The design of chimeric fusion proteins utilizing protein domains or one-domain miniproteins as building blocks is an important advancement for the creation of new biomolecules for biotechnology and medical applications. However, computational studies to describe in detail the dynamics and geometry properties of two-domain constructs made from structurally and functionally different proteins are lacking. Here, we tested an in silico design strategy using all-atom explicit solvent molecular dynamics simulations. The well-characterized PDZ3 and SH3 domains of human zonula occludens (ZO-1) (3TSZ), along with 5 artificial domains and 2 types of molecular linkers, were selected to construct chimeric two-domain molecules. The influence of the artificial domains on the structure and dynamics of the PDZ3 and SH3 domains was determined using a range of analyses. We conclude that the artificial domains can function as allosteric modulators of the PDZ3 and SH3 domains. Proteins 2016; 84:1358-1374. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Application of artificial neural networks to identify equilibration in computer simulations

NASA Astrophysics Data System (ADS)

Leibowitz, Mitchell H.; Miller, Evan D.; Henry, Michael M.; Jankowski, Eric

2017-11-01

Determining which microstates generated by a thermodynamic simulation are representative of the ensemble for which sampling is desired is a ubiquitous, underspecified problem. Artificial neural networks are one type of machine learning algorithm that can provide a reproducible way to apply pattern recognition heuristics to underspecified problems. Here we use the open-source TensorFlow machine learning library and apply it to the problem of identifying which hypothetical observation sequences from a computer simulation are “equilibrated” and which are not. We generate training populations and test populations of observation sequences with embedded linear and exponential correlations. We train a two-neuron artificial network to distinguish the correlated and uncorrelated sequences. We find that this simple network is good enough for > 98% accuracy in identifying exponentially-decaying energy trajectories from molecular simulations.

A novel artificial fish swarm algorithm for solving large-scale reliability-redundancy application problem.

PubMed

He, Qiang; Hu, Xiangtao; Ren, Hong; Zhang, Hongqi

2015-11-01

A novel artificial fish swarm algorithm (NAFSA) is proposed for solving large-scale reliability-redundancy allocation problem (RAP). In NAFSA, the social behaviors of fish swarm are classified in three ways: foraging behavior, reproductive behavior, and random behavior. The foraging behavior designs two position-updating strategies. And, the selection and crossover operators are applied to define the reproductive ability of an artificial fish. For the random behavior, which is essentially a mutation strategy, the basic cloud generator is used as the mutation operator. Finally, numerical results of four benchmark problems and a large-scale RAP are reported and compared. NAFSA shows good performance in terms of computational accuracy and computational efficiency for large scale RAP. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.

PubMed

Mocanu, Decebal Constantin; Mocanu, Elena; Stone, Peter; Nguyen, Phuong H; Gibescu, Madeleine; Liotta, Antonio

2018-06-19

Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from the network properties of biological neural networks (e.g. sparsity, scale-freeness), we argue that (contrary to general practice) artificial neural networks, too, should not have fully-connected layers. Here we propose sparse evolutionary training of artificial neural networks, an algorithm which evolves an initial sparse topology (Erdős-Rényi random graph) of two consecutive layers of neurons into a scale-free topology, during learning. Our method replaces artificial neural networks fully-connected layers with sparse ones before training, reducing quadratically the number of parameters, with no decrease in accuracy. We demonstrate our claims on restricted Boltzmann machines, multi-layer perceptrons, and convolutional neural networks for unsupervised and supervised learning on 15 datasets. Our approach has the potential to enable artificial neural networks to scale up beyond what is currently possible.

Artificial Intelligence: The Expert Way.

ERIC Educational Resources Information Center

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)

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

ERIC Educational Resources Information Center

Reeker, Larry H.; And Others

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

Artificial Intelligence: Applications in Education.

ERIC Educational Resources Information Center

Thorkildsen, Ron J.; And Others

1986-01-01

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

Stable, high-order computation of impedance-impedance operators for three-dimensional layered medium simulations.

PubMed

Nicholls, David P

2018-04-01

The faithful modelling of the propagation of linear waves in a layered, periodic structure is of paramount importance in many branches of the applied sciences. In this paper, we present a novel numerical algorithm for the simulation of such problems which is free of the artificial singularities present in related approaches. We advocate for a surface integral formulation which is phrased in terms of impedance-impedance operators that are immune to the Dirichlet eigenvalues which plague the Dirichlet-Neumann operators that appear in classical formulations. We demonstrate a high-order spectral algorithm to simulate these latter operators based upon a high-order perturbation of surfaces methodology which is rapid, robust and highly accurate. We demonstrate the validity and utility of our approach with a sequence of numerical simulations.

Stable, high-order computation of impedance-impedance operators for three-dimensional layered medium simulations

NASA Astrophysics Data System (ADS)

Nicholls, David P.

2018-04-01

The faithful modelling of the propagation of linear waves in a layered, periodic structure is of paramount importance in many branches of the applied sciences. In this paper, we present a novel numerical algorithm for the simulation of such problems which is free of the artificial singularities present in related approaches. We advocate for a surface integral formulation which is phrased in terms of impedance-impedance operators that are immune to the Dirichlet eigenvalues which plague the Dirichlet-Neumann operators that appear in classical formulations. We demonstrate a high-order spectral algorithm to simulate these latter operators based upon a high-order perturbation of surfaces methodology which is rapid, robust and highly accurate. We demonstrate the validity and utility of our approach with a sequence of numerical simulations.

Z-Score-Based Modularity for Community Detection in Networks

PubMed Central

Miyauchi, Atsushi; Kawase, Yasushi

2016-01-01

Identifying community structure in networks is an issue of particular interest in network science. The modularity introduced by Newman and Girvan is the most popular quality function for community detection in networks. In this study, we identify a problem in the concept of modularity and suggest a solution to overcome this problem. Specifically, we obtain a new quality function for community detection. We refer to the function as Z-modularity because it measures the Z-score of a given partition with respect to the fraction of the number of edges within communities. Our theoretical analysis shows that Z-modularity mitigates the resolution limit of the original modularity in certain cases. Computational experiments using both artificial networks and well-known real-world networks demonstrate the validity and reliability of the proposed quality function. PMID:26808270

Faith in the algorithm, part 1: beyond the turing test

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodriguez, Marko A; Pepe, Alberto

2009-01-01

Since the Turing test was first proposed by Alan Turing in 1950, the goal of artificial intelligence has been predicated on the ability for computers to imitate human intelligence. However, the majority of uses for the computer can be said to fall outside the domain of human abilities and it is exactly outside of this domain where computers have demonstrated their greatest contribution. Another definition for artificial intelligence is one that is not predicated on human mimicry, but instead, on human amplification, where the algorithms that are best at accomplishing this are deemed the most intelligent. This article surveys variousmore » systems that augment human and social intelligence.« less

An application of artificial intelligence to the interpretation of mass spectra.

NASA Technical Reports Server (NTRS)

Buchanan, B. G.; Duffield, A. M.; Robertson, A. V.

1971-01-01

Description of the DENDRAL (Dendritic Algorithm) project, the objectives of which were to base the computer program on an alogorithm that generates an exhaustive, nonredundant list of all the structural isomers of a given chemical composition, and to devise a computer program that would perform an organic structure determination, given a molecular formula and a mass spectrum. This program is called 'Heuristic DENDRAL' and it operates by using the known structure/spectrum correlations to constrain the DENDRAL isomer generator to produce a single isomer for that composition. The collaboration of chemists and computer scientists has produced a tool of some practical utility from the chemical viewpoint, and an interesting program from the viewpoint of artificial intelligence.

Artificial Intelligence and brain.

PubMed

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.

Electron-Electron Interactions in Artificial Graphene

NASA Astrophysics Data System (ADS)

Räsänen, E.; Rozzi, C. A.; Pittalis, S.; Vignale, G.

2012-06-01

Recent advances in the creation and modulation of graphenelike systems are introducing a science of “designer Dirac materials”. In its original definition, artificial graphene is a man-made nanostructure that consists of identical potential wells (quantum dots) arranged in an adjustable honeycomb lattice in the two-dimensional electron gas. As our ability to control the quality of artificial graphene samples improves, so grows the need for an accurate theory of its electronic properties, including the effects of electron-electron interactions. Here we determine those effects on the band structure and on the emergence of Dirac points.

Information Processing in Cognition Process and New Artificial Intelligent Systems

NASA Astrophysics Data System (ADS)

Zheng, Nanning; Xue, Jianru

In this chapter, we discuss, in depth, visual information processing and a new artificial intelligent (AI) system that is based upon cognitive mechanisms. The relationship between a general model of intelligent systems and cognitive mechanisms is described, and in particular we explore visual information processing with selective attention. We also discuss a methodology for studying the new AI system and propose some important basic research issues that have emerged in the intersecting fields of cognitive science and information science. To this end, a new scheme for associative memory and a new architecture for an AI system with attractors of chaos are addressed.

Deep learning with coherent nanophotonic circuits

NASA Astrophysics Data System (ADS)

Shen, Yichen; Harris, Nicholas C.; Skirlo, Scott; Prabhu, Mihika; Baehr-Jones, Tom; Hochberg, Michael; Sun, Xin; Zhao, Shijie; Larochelle, Hugo; Englund, Dirk; Soljačić, Marin

2017-07-01

Artificial neural networks are computational network models inspired by signal processing in the brain. These models have dramatically improved performance for many machine-learning tasks, including speech and image recognition. However, today's computing hardware is inefficient at implementing neural networks, in large part because much of it was designed for von Neumann computing schemes. Significant effort has been made towards developing electronic architectures tuned to implement artificial neural networks that exhibit improved computational speed and accuracy. Here, we propose a new architecture for a fully optical neural network that, in principle, could offer an enhancement in computational speed and power efficiency over state-of-the-art electronics for conventional inference tasks. We experimentally demonstrate the essential part of the concept using a programmable nanophotonic processor featuring a cascaded array of 56 programmable Mach-Zehnder interferometers in a silicon photonic integrated circuit and show its utility for vowel recognition.

The Evolution of Instructional Design Principles for Intelligent Computer-Assisted Instruction.

ERIC Educational Resources Information Center

Dede, Christopher; Swigger, Kathleen

1988-01-01

Discusses and compares the design and development of computer assisted instruction (CAI) and intelligent computer assisted instruction (ICAI). Topics discussed include instructional systems design (ISD), artificial intelligence, authoring languages, intelligent tutoring systems (ITS), qualitative models, and emerging issues in instructional…

Architecture for an artificial immune system.

PubMed

Hofmeyr, S A; Forrest, S

2000-01-01

An artificial immune system (ARTIS) is described which incorporates many properties of natural immune systems, including diversity, distributed computation, error tolerance, dynamic learning and adaptation, and self-monitoring. ARTIS is a general framework for a distributed adaptive system and could, in principle, be applied to many domains. In this paper, ARTIS is applied to computer security in the form of a network intrusion detection system called LISYS. LISYS is described and shown to be effective at detecting intrusions, while maintaining low false positive rates. Finally, similarities and differences between ARTIS and Holland's classifier systems are discussed.

Optical computing research

NASA Astrophysics Data System (ADS)

Goodman, Joseph W.

1987-10-01

Work Accomplished: OPTICAL INTERCONNECTIONS - the powerful interconnect abilities of optical beams have led much optimism about the possible roles for optics in solving interconnect problems at various levels of computer architecture. Examined were the powerful requirements of optical interconnects at the gate-to-gate and chip-to-chip levels. OPTICAL NEUTRAL NETWORKS - basic studies of the convergence properties on the Holfield model, based on mathematical approach - graph theory. OPTICS AND ARTIFICIAL INTELLIGENCE - review the field of optical processing and artificial intelligence, with the aim of finding areas that might be particularly attractive for future investigation(s).

Using artificial intelligence to control fluid flow computations

NASA Technical Reports Server (NTRS)

Gelsey, Andrew

1992-01-01

Computational simulation is an essential tool for the prediction of fluid flow. Many powerful simulation programs exist today. However, using these programs to reliably analyze fluid flow and other physical situations requires considerable human effort and expertise to set up a simulation, determine whether the output makes sense, and repeatedly run the simulation with different inputs until a satisfactory result is achieved. Automating this process is not only of considerable practical importance but will also significantly advance basic artificial intelligence (AI) research in reasoning about the physical world.

Center for Advanced Computational Technology

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.

2000-01-01

The Center for Advanced Computational Technology (ACT) was established to serve as a focal point for diverse research activities pertaining to application of advanced computational technology to future aerospace systems. These activities include the use of numerical simulations, artificial intelligence methods, multimedia and synthetic environments, and computational intelligence, in the modeling, analysis, sensitivity studies, optimization, design and operation of future aerospace systems. The Center is located at NASA Langley and is an integral part of the School of Engineering and Applied Science of the University of Virginia. The Center has four specific objectives: 1) conduct innovative research on applications of advanced computational technology to aerospace systems; 2) act as pathfinder by demonstrating to the research community what can be done (high-potential, high-risk research); 3) help in identifying future directions of research in support of the aeronautical and space missions of the twenty-first century; and 4) help in the rapid transfer of research results to industry and in broadening awareness among researchers and engineers of the state-of-the-art in applications of advanced computational technology to the analysis, design prototyping and operations of aerospace and other high-performance engineering systems. In addition to research, Center activities include helping in the planning and coordination of the activities of a multi-center team of NASA and JPL researchers who are developing an intelligent synthesis environment for future aerospace systems; organizing workshops and national symposia; as well as writing state-of-the-art monographs and NASA special publications on timely topics.

Conceptual Memory: A Theory and Computer Program for Processing the Meaning Content of Natural Language Utterances

DTIC Science & Technology

1974-07-01

iiWU -immmemmmmm This document was generated by the Stanford Artificial Intelligence Laboratory’s document compiler, "PUB" and reproducec’ on a...for more sophisticated artificial (programming) languages. The new issues became those of how to represent a grammar as precise syntactic structures...challenge lies in discovering - either by synthesis of an artificial system, or by analysis of a natural one - the underlying logical (a. opposed to

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

NASA Technical Reports Server (NTRS)

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.

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

ERIC Educational Resources Information Center

Hofmeister, Alan M.; Ferrara, Joseph M.

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

Psychometric Measurement Models and Artificial Neural Networks

ERIC Educational Resources Information Center

Sese, Albert; Palmer, Alfonso L.; Montano, Juan J.

2004-01-01

The study of measurement models in psychometrics by means of dimensionality reduction techniques such as Principal Components Analysis (PCA) is a very common practice. In recent times, an upsurge of interest in the study of artificial neural networks apt to computing a principal component extraction has been observed. Despite this interest, the…

Using Artificial Neural Networks in Educational Research: Some Comparisons with Linear Statistical Models.

ERIC Educational Resources Information Center

Everson, Howard T.; And Others

This paper explores the feasibility of neural computing methods such as artificial neural networks (ANNs) and abductory induction mechanisms (AIM) for use in educational measurement. ANNs and AIMS methods are contrasted with more traditional statistical techniques, such as multiple regression and discriminant function analyses, for making…

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

ERIC Educational Resources Information Center

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.…

Factors influencing exemplary science teachers' levels of computer use

NASA Astrophysics Data System (ADS)

Hakverdi, Meral

This study examines exemplary science teachers' use of technology in science instruction, factors influencing their level of computer use, their level of knowledge/skills in using specific computer applications for science instruction, their use of computer-related applications/tools during their instruction, and their students' use of computer applications/tools in or for their science class. After a relevant review of the literature certain variables were selected for analysis. These variables included personal self-efficacy in teaching with computers, outcome expectancy, pupil-control ideology, level of computer use, age, gender, teaching experience, personal computer use, professional computer use and science teachers' level of knowledge/skills in using specific computer applications for science instruction. The sample for this study includes middle and high school science teachers who received the Presidential Award for Excellence in Science Teaching Award (sponsored by the White House and the National Science Foundation) between the years 1997 and 2003 from all 50 states and U.S. territories. Award-winning science teachers were contacted about the survey via e-mail or letter with an enclosed return envelope. Of the 334 award-winning science teachers, usable responses were received from 92 science teachers, which made a response rate of 27.5%. Analysis of the survey responses indicated that exemplary science teachers have a variety of knowledge/skills in using computer related applications/tools. The most commonly used computer applications/tools are information retrieval via the Internet, presentation tools, online communication, digital cameras, and data collection probes. Results of the study revealed that students' use of technology in their science classroom is highly correlated with the frequency of their science teachers' use of computer applications/tools. The results of the multiple regression analysis revealed that personal self-efficacy related to the exemplary science teachers' level of computer use suggesting that computer use is dependent on perceived abilities at using computers. The teachers' use of computer-related applications/tools during class, and their personal self-efficacy, age, and gender are highly related with their level of knowledge/skills in using specific computer applications for science instruction. The teachers' level of knowledge/skills in using specific computer applications for science instruction and gender related to their use of computer-related applications/tools during class and the students' use of computer-related applications/tools in or for their science class. In conclusion, exemplary science teachers need assistance in learning and using computer-related applications/tool in their science class.

Anesthesia 2.0: internet-based information resources and Web 2.0 applications in anesthesia education.

PubMed

Chu, Larry F; Young, Chelsea; Zamora, Abby; Kurup, Viji; Macario, Alex

2010-04-01

Informatics is a broad field encompassing artificial intelligence, cognitive science, computer science, information science, and social science. The goal of this review is to illustrate how Web 2.0 information technologies could be used to improve anesthesia education. Educators in all specialties of medicine are increasingly studying Web 2.0 technologies to maximize postgraduate medical education of housestaff. These technologies include microblogging, blogs, really simple syndication (RSS) feeds, podcasts, wikis, and social bookmarking and networking. 'Anesthesia 2.0' reflects our expectation that these technologies will foster innovation and interactivity in anesthesia-related web resources which embraces the principles of openness, sharing, and interconnectedness that represent the Web 2.0 movement. Although several recent studies have shown benefits of implementing these systems into medical education, much more investigation is needed. Although direct practice and observation in the operating room are essential, Web 2.0 technologies hold great promise to innovate anesthesia education and clinical practice such that the resident learner need not be in a classroom for a didactic talk, or even in the operating room to see how an arterial line is properly placed. Thoughtful research to maximize implementation of these technologies should be a priority for development by academic anesthesiology departments. Web 2.0 and advanced informatics resources will be part of physician lifelong learning and clinical practice.

Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation.

PubMed

Du, Tingsong; Hu, Yang; Ke, Xianting

2015-01-01

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.

Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation

PubMed Central

Hu, Yang; Ke, Xianting

2015-01-01

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA. PMID:26447713

COMPUTER SUPPORT SYSTEMS FOR ESTIMATING CHEMICAL TOXICITY: PRESENT CAPABILITIES AND FUTURE TRENDS

EPA Science Inventory

Computer Support Systems for Estimating Chemical Toxicity: Present Capabilities and Future Trends

A wide variety of computer-based artificial intelligence (AI) and decision support systems exist currently to aid in the assessment of toxicity for environmental chemicals. T...

Noyce SWARMS Scholars and Two Professional Development Models (LASSI and RAMPED): Summer 2015, 2016, and 2017

NASA Astrophysics Data System (ADS)

Burrows, Andrea C.; Myers, Adam D.; Borowczak, Mike

2018-06-01

This poster showcases an astronomy professional development (PD) for 41 K-12 teachers. The project was entitled Launching Astronomy Standards and STEM Integration (LASSI). A project description (activities in the 18 months - Summer 2015 and 2016) for the astronomy, authentic science, and pre-service teacher opportunities is included. The PD team utilized real-world problems, participant-generated questions, science instruments, technology, evidence, communication, dissemination, and collaboration in the LASSI PD model. Computer science was a feature of the PD and the K-12 teacher participants showcased various methods of its use. Embracing an engineering process with an authentic astronomy PD allowed participants to make connections to current topics and create shareable projects. The PD team highlights teacher work from LASSI entitled - A Model for Determining Size of Objects in an Artificial Solar System. The Sustaining Wyoming's Advancing Reach in Mathematics and Science (SWARMS) Scholars (NSF Noyce funded) interacted with and used the materials from the LASSI PD. The poster highlights PD use from the LASSI participants and SWARMS Scholars as well as explains lessons learned to date as a follow-up PD Robotics, Applied Mathematics, Physics, and Engineering Design (RAMPED) was implemented in Summer 2017 and carried methods from LASSI. The LASSI and RAMPED PD teams included faculty from the College of Education, College of Engineering and Applied Science, College of Arts and Sciences, graduate students, and the teachers themselves. The PD teams created a website with these and other PD materials - UWpd.org - for others to view and change to meet their needs.

The Successive Contributions of Computers to Education: A Survey.

ERIC Educational Resources Information Center

Lelouche, Ruddy

1998-01-01

Shows how education has successively benefited from traditional information processing through programmed instruction and computer-assisted instruction (CAI), artificial intelligence, intelligent CAI, intelligent tutoring systems, and hypermedia techniques. Contains 29 references. (DDR)

Application of Computer-Assisted Design and Manufacturing-Fabricated Artificial Bone in the Reconstruction of Craniofacial Bone Defects.

PubMed

Liang, Weiqiang; Yao, Yuanyuan; Huang, Zixian; Chen, Yuhong; Ji, Chenyang; Zhang, Jinming

2016-07-01

The purpose of this study was to evaluate the clinical application of individual craniofacial bone fabrications using computer-assisted design (CAD)-computer-assisted manufacturing technology for the reconstruction of craniofacial bone defects. A total of 8 patients diagnosed with craniofacial bone defects were enrolled in this study between May 2007 and August 2010. After computed tomography scans were obtained, the patients were fitted with artificial bone that was created using CAD software, rapid prototyping technology, and epoxy-methyl acrylate resin and hydroxyapatite materials. The fabrication was fixed to the defect area with titanium screws, and soft tissue defects were repaired if necessary. The fabrications were precisely fixed to the defect areas, and all wounds healed well without any serious complications except for 1 case with intraoral incision dehiscence, which required further treatment. Postoperative curative effects were retrospectively observed after 6 to 48 months, acceptable anatomic and cosmetic outcomes were obtained, and no rejections or other complications occurred. The use of CAD-computer-assisted manufacturing technology-assisted epoxy-methyl acrylate resin and hydroxyapatite composite artificial bone to treat patients with craniofacial bone defects could enable the precise reconstruction of these defects and obtain good anatomic and cosmetic outcomes. Copyright © 2016 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

[Artificial intelligence in psychiatry-an overview].

PubMed

Meyer-Lindenberg, A

2018-06-18

Artificial intelligence and the underlying methods of machine learning and neuronal networks (NN) have made dramatic progress in recent years and have allowed computers to reach superhuman performance in domains that used to be thought of as uniquely human. In this overview, the underlying methodological developments that made this possible are briefly delineated and then the applications to psychiatry in three domains are discussed: precision medicine and biomarkers, natural language processing and artificial intelligence-based psychotherapeutic interventions. In conclusion, some of the risks of this new technology are mentioned.

Conversion of the CALAP (Computer Aided Landform Analysis Program) Program from FORTRAN to DUCK.

DTIC Science & Technology

1986-09-01

J’ DUCK artificial intelligence logic programming 20 AVrACT (Cthm m reerse stabN ameeaaW idelfr by block mbae) An expert advisor program named CALAP...original program was developed in FORTRAN on an HP- 1000, a mirticomputer. CALAP was reprogrammed in an Artificial Intelligence (AI) language called DUCK...the Artificial Intelligence Center, U.S. Army Engineer Topographic Laboratory, Fort Belvoir. Z" I. S. n- Page 1 I. Introduction An expert advisor

Effects of heat conduction on artificial viscosity methods for shock capturing

DOE PAGES

Cook, Andrew W.

2013-12-01

Here we investigate the efficacy of artificial thermal conductivity for shock capturing. The conductivity model is derived from artificial bulk and shear viscosities, such that stagnation enthalpy remains constant across shocks. By thus fixing the Prandtl number, more physical shock profiles are obtained, only on a larger scale. The conductivity model does not contain any empirical constants. It increases the net dissipation of a computational algorithm but is found to better preserve symmetry and produce more robust solutions for strong-shock problems.

Computer Ethics Topics and Teaching Strategies.

ERIC Educational Resources Information Center

DeLay, Jeanine A.

An overview of six major issues in computer ethics is provided in this paper: (1) unauthorized and illegal database entry, surveillance and monitoring, and privacy issues; (2) piracy and intellectual property theft; (3) equity and equal access; (4) philosophical implications of artificial intelligence and computer rights; (5) social consequences…

Conversational Simulation in Computer-Assisted Language Learning: Potential and Reality.

ERIC Educational Resources Information Center

Coleman, D. Wells

1988-01-01

Addresses the potential of conversational simulations for computer-assisted language learning (CALL) and reasons why this potential is largely untapped. Topics discussed include artificial intelligence; microworlds; parsing; realism versus reality in computer software; intelligent tutoring systems; and criteria to clarify what kinds of CALL…

The Application of Cognitive Diagnostic Approaches via Neural Network Analysis of Serious Educational Games

NASA Astrophysics Data System (ADS)

Lamb, Richard L.

Serious Educational Games (SEGs) have been a topic of increased popularity within the educational realm since the early millennia. SEGs are generalized form of Serious Games to mean games for purposes other than entertainment but, that also specifically include training, educational purpose and pedagogy within their design. This rise in popularity (for SEGs) has occurred at a time when school systems have increased the type, number, and presentations of student achievement tests for decision-making purposes. These tests often task the form of end of course (year) tests and periodic benchmark testing. As the use of these tests, has increased policymakers have suggested their use as a measure for teacher accountability. The change in testing resulted from a push by school districts and policy makers at various component levels for a data-driven decision-making (D3M) approach. With the data-driven decision making approaches by school districts, there has been an increased focus on the measurement and assessment of student content knowledge with little focus on the contributing factors and cognitive attributes within learning that cross multiple-content areas. One-way to increase the focus on these aspects of learning (factors and attributes) that are additional to content learning is through assessments based in cognitive diagnostics. Cognitive diagnostics are a family of methodological approaches in which tasks tie to specific cognitive attributes for analytical purposes. This study explores data derived from computer data logging (n=158,000) in an observational design, using traditional statistical techniques such as clustering (exploratory and confirmatory), item response theory and through data mining techniques such as artificial neural network analysis. From these analyses, a model of student learning emerges illustrating student thinking and learning while engaged in SEG Design. This study seeks to use cognitive diagnostic type approaches to measure student learning while designing science task based SEGs. In addition, the study suggests that it may be possible to use SEGs to provide a means to administer cognitive diagnostic based assessments in real time. Results of this study suggest the confirmation of four families (factors) of traits illustrating a simple factor loading structure. Item response theory (IRT) results illustrate a 2-parameter logistic model (2PLM) fit allowing for parameterization using the IRT-True Score Method (chi2=1.70, df=1, p=0.19). Finally, fit statistics for the artificial neural network suggest the developed model adequately fits the current data set and provides a means to explore cognitive attributes and their effect on task outcomes. This study has developed a justification for combining and developing two distinct areas of research related to student learning. The first is the use of cognitive diagnostic approaches to assess student learning as it relates to the cognitive attributes used during science processing. The second area is an examination and modeling of the relationship between attributes as propagated in an artificial neural network. Results of the study provide for an ANN model of student cognition while designing science based SEGs (r 2=0.73, RMSE= 0.21) at a convergence of 1000 training iterations. The literature presented in this dissertation work integrates work from multiple field areas. Fields represented in this work range from science education, educational psychology, measurement, and computational psychology.

Artificial Intelligence: Themes in the Second Decade. Memo Number 67.

ERIC Educational Resources Information Center

Feigenbaum, Edward A.

The text of an invited address on artificial intelligence (AI) research over the 1963-1968 period is presented. A survey of recent studies on the computer simulation of intellective processes emphasizes developments in heuristic programing, problem-solving and closely related learning models. Progress and problems in these areas are indicated by…

What Artificial Grammar Learning Reveals about the Neurobiology of Syntax

ERIC Educational Resources Information Center

Petersson, Karl-Magnus; Folia, Vasiliki; Hagoort, Peter

2012-01-01

In this paper we examine the neurobiological correlates of syntax, the processing of structured sequences, by comparing FMRI results on artificial and natural language syntax. We discuss these and similar findings in the context of formal language and computability theory. We used a simple right-linear unification grammar in an implicit artificial…

Evaluation of Physiologically-Based Artificial Neural Network Models to Detect Operator Workload in Remotely Piloted Aircraft Operations

DTIC Science & Technology

2016-07-13

to a computer via Bluetooth . Respiration is captured as a breathing waveform signal using a capacitive pressure sensor, sampled at 18 Hz. The...dropouts in the Bluetooth signal and artifacts caused by body movement. Workload models. Four artificial neural network models were created using

A Study for the Feature Selection to Identify GIEMSA-Stained Human Chromosomes Based on Artificial Neural Network

DTIC Science & Technology

2001-10-25

neural network (ANN) has been adopted for the human chromosome classification. It is important to select optimum features for training neural network...Many studies for computer-based chromosome analysis have shown that it is possible to classify chromosomes into 24 subgroups. In addition, artificial

Artificial Intelligence and Language Development and Language Usage with the Deaf.

ERIC Educational Resources Information Center

Leach, John Mark

The paper reviews research on the application of artificial intelligence (AI) in language development and/or instruction with the deaf. Contributions of computer assisted instruction are noted, as are the problems resulting from over-dependence on a drill and practice format and from deaf students' difficulties in receiving and understanding new…

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

ERIC Educational Resources Information Center

Braun, Joseph A., Jr.

1987-01-01

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

Development of artificial meteor for observation of upper atmosphere

NASA Astrophysics Data System (ADS)

Watanabe, Masaki; Sahara, Hironori; Abe, Shinsuke; Watanabe, Takeo; Nojiri, Yuta; Okajima, Lena

2016-04-01

This study proposes a method for the observation of the upper atmosphere using an artificial meteor injected by a mass driver installed on a microsatellite. The mass driver injects a pill at a velocity of 200 m/s and deorbits it into the atmosphere. The emission of the pill can then be observed from the ground at the necessary time and location. This approach could contribute to a better understanding of the global environment as well as different aspects of astronomy and planetary science. To realize the proposed method, the required size and emission of the pill have to be determined. Therefore, we conducted flow-field simulations, spectroscopic estimations, and an experiment on an artificial meteor in the arc heater wind tunnel at the Institute of Space and Astronautical Science in the Japan Aerospace Exploration Agency (ISAS/JAXA). From the results, we confirmed that the light emission could be observed as a shooting star by the naked eye and thus verified the feasibility of the method.

Artificial photosynthesis: understanding water splitting in nature

PubMed Central

Cox, Nicholas; Pantazis, Dimitrios A.; Neese, Frank; Lubitz, Wolfgang

2015-01-01

In the context of a global artificial photosynthesis (GAP) project, we review our current work on nature's water splitting catalyst. In a recent report (Cox et al. 2014 Science 345, 804–808 (doi:10.1126/science.1254910)), we showed that the catalyst—a Mn4O5Ca cofactor—converts into an ‘activated’ form immediately prior to the O–O bond formation step. This activated state, which represents an all MnIV complex, is similar to the structure observed by X-ray crystallography but requires the coordination of an additional water molecule. Such a structure locates two oxygens, both derived from water, in close proximity, which probably come together to form the product O2 molecule. We speculate that formation of the activated catalyst state requires inherent structural flexibility. These features represent new design criteria for the development of biomimetic and bioinspired model systems for water splitting catalysts using first-row transition metals with the aim of delivering globally deployable artificial photosynthesis technologies. PMID:26052426

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

ERIC Educational Resources Information Center

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)

Intelligent Tutoring Systems

NASA Astrophysics Data System (ADS)

Anderson, John R.; Boyle, C. Franklin; Reiser, Brian J.

1985-04-01

Cognitive psychology, artificial intelligence, and computer technology have advanced to the point where it is feasible to build computer systems that are as effective as intelligent human tutors. Computer tutors based on a set of pedagogical principles derived from the ACT theory of cognition have been developed for teaching students to do proofs in geometry and to write computer programs in the language LISP.

Intelligent tutoring systems.

PubMed

Anderson, J R; Boyle, C F; Reiser, B J

1985-04-26

Cognitive psychology, artificial intelligence, and computer technology have advanced to the point where it is feasible to build computer systems that are as effective as intelligent human tutors. Computer tutors based on a set of pedagogical principles derived from the ACT theory of cognition have been developed for teaching students to do proofs in geometry and to write computer programs in the language LISP.

The Effect of Using Item Parameters Calibrated from Paper Administrations in Computer Adaptive Test Administrations

ERIC Educational Resources Information Center

Pommerich, Mary

2007-01-01

Computer administered tests are becoming increasingly prevalent as computer technology becomes more readily available on a large scale. For testing programs that utilize both computer and paper administrations, mode effects are problematic in that they can result in examinee scores that are artificially inflated or deflated. As such, researchers…

Implications for Intelligent Tutoring Systems for Research and Practice in Foreign Language Learning, NFLC Occasional Papers.

ERIC Educational Resources Information Center

Ginsberg, Ralph B.

Most of the now commonplace computer-assisted instruction (CAI) uses computers to increase the capacity to perform logical, numerical, and symbolic computations. However, computers are an interactive and potentially intelligent medium. The implications of artificial intelligence (AI) for learning are more radical than those for traditional CAI. AI…

[I, Robot: artificial intelligence, uniqueness and self-consciousness].

PubMed

Agrest, Martín

2008-01-01

The cinematographic version of the science fiction classical book by Isaac Asimov (I, Robot) is used as a starting point, from the Artificial Intelligence perspective, in order to analyze what it is to have a self. Uniqueness or the exchange impossibility and the continuity of being one self are put forward to understand the movie's characters as well as the possibilities of feeling self conscious.

Curriculum Assessment Using Artificial Neural Network and Support Vector Machine Modeling Approaches: A Case Study. IR Applications. Volume 29

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2010-01-01

Artificial Neural Network (ANN) and Support Vector Machine (SVM) approaches have been on the cutting edge of science and technology for pattern recognition and data classification. In the ANN model, classification accuracy can be achieved by using the feed-forward of inputs, back-propagation of errors, and the adjustment of connection weights. In…

Predicting Diameter Distributions of Longleaf Pine Plantations: A Comparison Between Artificial Neural Networks and Other Accepted Methodologies

Treesearch

Daniel J. Leduc; Thomas G. Matney; Keith L. Belli; V. Clark Baldwin

2001-01-01

Artificial neural networks (NN) are becoming a popular estimation tool. Because they require no assumptions about the form of a fitting function, they can free the modeler from reliance on parametric approximating functions that may or may not satisfactorily fit the observed data. To date there have been few applications in forestry science, but as better NN software...

The LAILAPS search engine: a feature model for relevance ranking in life science databases.

PubMed

Lange, Matthias; Spies, Karl; Colmsee, Christian; Flemming, Steffen; Klapperstück, Matthias; Scholz, Uwe

2010-03-25

Efficient and effective information retrieval in life sciences is one of the most pressing challenge in bioinformatics. The incredible growth of life science databases to a vast network of interconnected information systems is to the same extent a big challenge and a great chance for life science research. The knowledge found in the Web, in particular in life-science databases, are a valuable major resource. In order to bring it to the scientist desktop, it is essential to have well performing search engines. Thereby, not the response time nor the number of results is important. The most crucial factor for millions of query results is the relevance ranking. In this paper, we present a feature model for relevance ranking in life science databases and its implementation in the LAILAPS search engine. Motivated by the observation of user behavior during their inspection of search engine result, we condensed a set of 9 relevance discriminating features. These features are intuitively used by scientists, who briefly screen database entries for potential relevance. The features are both sufficient to estimate the potential relevance, and efficiently quantifiable. The derivation of a relevance prediction function that computes the relevance from this features constitutes a regression problem. To solve this problem, we used artificial neural networks that have been trained with a reference set of relevant database entries for 19 protein queries. Supporting a flexible text index and a simple data import format, this concepts are implemented in the LAILAPS search engine. It can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases. LAILAPS is publicly available for SWISSPROT data at http://lailaps.ipk-gatersleben.de.

Artificial Blood Substitutes: First Steps on the Long Route to Clinical Utility

PubMed Central

Moradi, Samira; Jahanian-Najafabadi, Ali; Roudkenar, Mehryar Habibi

2016-01-01

The 21st century is challenging for human beings. Increased population growth, population aging, generation of new infectious agents, and natural disasters are some threatening factors for the current state of blood transfusion. However, it seems that science and technology not only could overcome these challenges but also would turn many human dreams to reality in this regard. Scientists believe that one of the future evolutionary innovations could be artificial blood substitutes that might pave the way to a new era in transfusion medicine. In this review, recent status and progresses in artificial blood substitutes, focusing on red blood cells substitutes, are summarized. In addition, steps taken toward the development of artificial blood technology and some of their promises and hurdles will be highlighted. However, it must be noted that artificial blood is still at the preliminary stages of development, and to fulfill this dream, ie, to routinely transfuse artificial blood into human vessels, we still have to strengthen our knowledge and be patient. PMID:27812292

Material science lesson from the biological photosystem.

PubMed

Kim, Younghye; Lee, Jun Ho; Ha, Heonjin; Im, Sang Won; Nam, Ki Tae

2016-01-01

Inspired by photosynthesis, artificial systems for a sustainable energy supply are being designed. Each sequential energy conversion process from light to biomass in natural photosynthesis is a valuable model for an energy collection, transport and conversion system. Notwithstanding the numerous lessons of nature that provide inspiration for new developments, the features of natural photosynthesis need to be reengineered to meet man's demands. This review describes recent strategies toward adapting key lessons from natural photosynthesis to artificial systems. We focus on the underlying material science in photosynthesis that combines photosystems as pivotal functional materials and a range of materials into an integrated system. Finally, a perspective on the future development of photosynthesis mimetic energy systems is proposed.