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

Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

NASA Technical Reports Server (NTRS)

Broderick, Ron

1997-01-01

The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network development. The changes were to include evaluation tools that can be applied to neural networks at each phase of the software engineering life cycle. The result was a formal evaluation approach to increase the product quality of systems that use neural networks for their implementation.

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.

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.

[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.

The application and development of artificial intelligence in smart clothing

NASA Astrophysics Data System (ADS)

Wei, Xiong

2018-03-01

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

Inspection Methods in Programming: Cliches and Plans.

DTIC Science & Technology

1987-12-01

PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREA & WORK UN IT NUMBERS J 545 Technology Square Cambridge, MA 02139 $L. CONTROLLING...U) MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB C RICH DEC 87 AI-M-±05 UNCLASSIFIED NW014-B5-K-0124 F/G 12/5 NL ’lllll l l l...S %P W. J % % %s MASSACHUSETTS INSTITUTE OF TECHNOLOGY N ARTIFICIAL INTELLIGENCE LABORATORY 00 A.I. Memo No. 1005 December 1987 N Inspection Methods

New directions for Artificial Intelligence (AI) methods in optimum design

NASA Technical Reports Server (NTRS)

Hajela, Prabhat

1989-01-01

Developments and applications of artificial intelligence (AI) methods in the design of structural systems is reviewed. Principal shortcomings in the current approach are emphasized, and the need for some degree of formalism in the development environment for such design tools is underscored. Emphasis is placed on efforts to integrate algorithmic computations in expert systems.

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…

A Memory-Process Model of Symbolic Assimilation

DTIC Science & Technology

1974-04-01

Systems: Final Report of a Study Group, published for Artificial Intellegence by North-Holland/Amorican...contribution of the methods is answered by evaluating the same program in the context of the field of artificial intelligence. The remainder of the...been widely demonstrated on a diversity of tasks in tha history of artificial intelligence. See [r.71], chapter 2. Given a particular task to be

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.

Database in Artificial Intelligence.

ERIC Educational Resources Information Center

Wilkinson, Julia

1986-01-01

Describes a specialist bibliographic database of literature in the field of artificial intelligence created by the Turing Institute (Glasgow, Scotland) using the BRS/Search information retrieval software. The subscription method for end-users--i.e., annual fee entitles user to unlimited access to database, document provision, and printed awareness…

Efficient Effects-Based Military Planning Final Report

DTIC Science & Technology

2010-11-13

using probabilistic infer- ence methods,” in Proc. 8th Annu. Conf. Uncertainty Artificial Intelli - gence (UAI), Stanford, CA. San Mateo, CA: Morgan...Imprecise Probabilities, the 24th Conference on Uncertainty in Artificial Intelligence (UAI), 2008. 7. Yan Tong and Qiang Ji, Learning Bayesian Networks...Bayesian Networks using Constraints Cassio P. de Campos cassiopc@acm.org Dalle Molle Institute for Artificial Intelligence Galleria 2, Manno 6928

International experience on the use of artificial neural networks in gastroenterology.

PubMed

Grossi, E; Mancini, A; Buscema, M

2007-03-01

In this paper, we reconsider the scientific background for the use of artificial intelligence tools in medicine. A review of some recent significant papers shows that artificial neural networks, the more advanced and effective artificial intelligence technique, can improve the classification accuracy and survival prediction of a number of gastrointestinal diseases. We discuss the 'added value' the use of artificial neural networks-based tools can bring in the field of gastroenterology, both at research and clinical application level, when compared with traditional statistical or clinical-pathological methods.

Contribution of artificial intelligence to the knowledge of prognostic factors in laryngeal carcinoma.

PubMed

Zapater, E; Moreno, S; Fortea, M A; Campos, A; Armengot, M; Basterra, J

2000-11-01

Many studies have investigated prognostic factors in laryngeal carcinoma, with sometimes conflicting results. Apart from the importance of environmental factors, the different statistical methods employed may have influenced such discrepancies. A program based on artificial intelligence techniques is designed to determine the prognostic factors in a series of 122 laryngeal carcinomas. The results obtained are compared with those derived from two classical statistical methods (Cox regression and mortality tables). Tumor location was found to be the most important prognostic factor by all methods. The proposed intelligent system is found to be a sound method capable of detecting exceptional cases.

Multistep Methods for Integrating the Solar System

DTIC Science & Technology

1988-07-01

Technical Report 1055 [Multistep Methods for Integrating the Solar System 0 Panayotis A. Skordos’ MIT Artificial Intelligence Laboratory DTIC S D g8...RMA ELEENT. PROECT. TASK Artific ial Inteligence Laboratory ARE1A G WORK UNIT NUMBERS 545 Technology Square Cambridge, MA 02139 IL. CONTROLLING...describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology, supported by the Advanced Research Projects

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,…

[Methods of artificial intelligence: a new trend in pharmacy].

PubMed

Dohnal, V; Kuca, K; Jun, D

2005-07-01

Artificial neural networks (ANN) and genetic algorithms are one group of methods called artificial intelligence. The application of ANN on pharmaceutical data can lead to an understanding of the inner structure of data and a possibility to build a model (adaptation). In addition, for certain cases it is possible to extract rules from data. The adapted ANN is prepared for the prediction of properties of compounds which were not used in the adaptation phase. The applications of ANN have great potential in pharmaceutical industry and in the interpretation of analytical, pharmacokinetic or toxicological data.

Decade Review (1999-2009): Artificial Intelligence Techniques in Student Modeling

NASA Astrophysics Data System (ADS)

Drigas, Athanasios S.; Argyri, Katerina; Vrettaros, John

Artificial Intelligence applications in educational field are getting more and more popular during the last decade (1999-2009) and that is why much relevant research has been conducted. In this paper, we present the most interesting attempts to apply artificial intelligence methods such as fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro - fuzzy systems and genetic programming neural networks (GPNN) in student modeling. This latest research trend is a part of every Intelligent Tutoring System and aims at generating and updating a student model in order to modify learning content to fit individual needs or to provide reliable assessment and feedback to student's answers. In this paper, we make a brief presentation of methods used to point out their qualities and then we attempt a navigation to the most representative studies sought in the decade of our interest after classifying them according to the principal aim they attempted to serve.

Report on Ada (Trademark) Program Libraries Workshop Held at Monterey, California on November 1-3, 1983,

DTIC Science & Technology

1983-11-03

capability. An intelligent library management system will be supported by knowledge-based techniques. In fact, until a formal specification of library...from artificial intelligence and information science 2 might also be useful, for example automatic indexing and cataloging schemes, methods for fast...Artificial Intelligence 5:1045-1058, 1977. [Burstall & Goguen 801 Burstall, R. M., and Goguen, J. A. The Semantics of Clear, a Specification Language. In

Artificial Intelligence for Controlling Robotic Aircraft

NASA Technical Reports Server (NTRS)

Krishnakumar, Kalmanje

2005-01-01

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

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.

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.

Second Conference on Artificial Intelligence for Space Applications

NASA Technical Reports Server (NTRS)

Dollman, Thomas (Compiler)

1988-01-01

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

Dynamic Restructuring Of Problems In Artificial Intelligence

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.

1992-01-01

"Dynamic tradeoff evaluation" (DTE) denotes proposed method and procedure for restructuring problem-solving strategies in artificial intelligence to satisfy need for timely responses to changing conditions. Detects situations in which optimal problem-solving strategies cannot be pursued because of real-time constraints, and effects tradeoffs among nonoptimal strategies in such way to minimize adverse effects upon performance of system.

Artificial Intelligence and Information Retrieval.

ERIC Educational Resources Information Center

Teodorescu, Ioana

1987-01-01

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

Fifth Conference on Artificial Intelligence for Space Applications

NASA Technical Reports Server (NTRS)

Odell, Steve L. (Compiler)

1990-01-01

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

Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

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

2003-01-01

This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an AI method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.

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

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

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…

Northeast Artificial Intelligence Consortium (NAIC) Review of Technical Tasks. Volume 2, Part 2.

DTIC Science & Technology

1987-07-01

A-A19 774 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUN (MIC) 1/5 YVIEN OF TEOICR. T.. (U) NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM SYRACUSE MY J...NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM (NAIC) *p,* ~ Review of Technical Tasks ,.. 12 PERSONAL AUTHOR(S) (See reverse) . P VI J.F. Allen, P.B. Berra...See reverse) /" I ABSTRACT (Coninue on ’.wrse if necessary and identify by block number) % .. *. -. ’ The Northeast Artificial Intelligence Consortium

Artificial intelligence in medicine.

PubMed

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

2004-09-01

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

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

NASA Astrophysics Data System (ADS)

Qiu, Feng; Dai, Guang; Zhang, Ying

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

Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

NASA Astrophysics Data System (ADS)

Mishra, D.; Goyal, P.

2014-12-01

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

Artificial Intelligence.

ERIC Educational Resources Information Center

Information Technology Quarterly, 1985

1985-01-01

This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

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

DOEpatents

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

2009-09-01

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

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

PubMed

Park, Seong Ho; Han, Kyunghwa

2018-03-01

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

Artificial Intelligence Project

DTIC Science & Technology

1990-01-01

Artifcial Intelligence Project at The University of Texas at Austin, University of Texas at Austin, Artificial Intelligence Laboratory AITR84-01. Novak...Texas at Austin, Artificial Intelligence Laboratory A187-52, April 1987. Novak, G. "GLISP: A Lisp-Based Programming System with Data Abstraction...of Texas at Austin, Artificial Intelligence Laboratory AITR85-14.) Rim, Hae-Chang, and Simmons, R. F. "Extracting Data Base Knowledge from Medical

Artificial Intelligence and Vocational Education: An Impending Confluence.

ERIC Educational Resources Information Center

Roth, Gene L.; McEwing, Richard A.

1986-01-01

Reports on the relatively new field of artificial intelligence and its relationship to vocational education. Compares human intelligence with artificial intelligence. Discusses expert systems, natural language technology, and current trends. Lists potential applications for vocational education. (CH)

Web Intelligence and Artificial Intelligence in Education

ERIC Educational Resources Information Center

Devedzic, Vladan

2004-01-01

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

Northeast Artificial Intelligence Consortium Annual Report. Volume 2. 1988 Discussing, Using, and Recognizing Plans (NLP)

DTIC Science & Technology

1989-10-01

Encontro Portugues de Inteligencia Artificial (EPIA), Oporto, Portugal, September 1985. [15] N. J. Nilsson. Principles Of Artificial Intelligence. Tioga...FI1 F COPY () RADC-TR-89-259, Vol II (of twelve) Interim Report October 1969 AD-A218 154 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL...7a. NAME OF MONITORING ORGANIZATION Northeast Artificial Of p0ilcabe) Intelligence Consortium (NAIC) Rome_____ Air___ Development____Center

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

The application of artificial intelligence for the identification of the maceral groups and mineral components of coal

NASA Astrophysics Data System (ADS)

Mlynarczuk, Mariusz; Skiba, Marta

2017-06-01

The correct and consistent identification of the petrographic properties of coal is an important issue for researchers in the fields of mining and geology. As part of the study described in this paper, investigations concerning the application of artificial intelligence methods for the identification of the aforementioned characteristics were carried out. The methods in question were used to identify the maceral groups of coal, i.e. vitrinite, inertinite, and liptinite. Additionally, an attempt was made to identify some non-organic minerals. The analyses were performed using pattern recognition techniques (NN, kNN), as well as artificial neural network techniques (a multilayer perceptron - MLP). The classification process was carried out using microscopy images of polished sections of coals. A multidimensional feature space was defined, which made it possible to classify the discussed structures automatically, based on the methods of pattern recognition and algorithms of the artificial neural networks. Also, from the study we assessed the impact of the parameters for which the applied methods proved effective upon the final outcome of the classification procedure. The result of the analyses was a high percentage (over 97%) of correct classifications of maceral groups and mineral components. The paper discusses also an attempt to analyze particular macerals of the inertinite group. It was demonstrated that using artificial neural networks to this end makes it possible to classify the macerals properly in over 91% of cases. Thus, it was proved that artificial intelligence methods can be successfully applied for the identification of selected petrographic features of coal.

Smithtown: An Intelligent Tutoring System.

ERIC Educational Resources Information Center

Raghavan, Kalyani; Katz, Arnold

1989-01-01

Described is an instructional aid that employs artificial intelligence methods to assist students in beginning economics courses to improve their problem-solving skills. Discussed are the rationale, structure, and evaluation of this program. (CW)

Artificial Intelligence.

ERIC Educational Resources Information Center

Thornburg, David D.

1986-01-01

Overview of the artificial intelligence (AI) field provides a definition; discusses past research and areas of future research; describes the design, functions, and capabilities of expert systems and the "Turing Test" for machine intelligence; and lists additional sources for information on artificial intelligence. Languages of AI are…

Prerequisites for Deriving Formal Specifications from Natural Language Requirements.

DTIC Science & Technology

1983-04-01

International Joint Conference on Artificial Intell1ence, American Association for Artificial Intelligence, Mento Park, CA, 1981, 385-387. Mann, William C...Centering". Proceedings of the Seventh International Joint Conference on Artificial Intelligence, American Association for Artificial Intelligence, Mento

Intelligent detection of cracks in metallic surfaces using a waveguide sensor loaded with metamaterial elements.

PubMed

Ali, Abdulbaset; Hu, Bing; Ramahi, Omar

2015-05-15

This work presents a real life experiment of implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor's signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impact in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks and the obtained experimental results showed good crack classification accuracy rates.

Intelligent Detection of Cracks in Metallic Surfaces Using a Waveguide Sensor Loaded with Metamaterial Elements

PubMed Central

Ali, Abdulbaset; Hu, Bing; Ramahi, Omar M.

2015-01-01

This work presents a real-life experiment implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor's signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impacts in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing the data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks, and the experimental results showed good crack classification accuracy rates. PMID:25988871

Classification of intelligence quotient via brainwave sub-band power ratio features and artificial neural network.

PubMed

Jahidin, A H; Megat Ali, M S A; Taib, M N; Tahir, N Md; Yassin, I M; Lias, S

2014-04-01

This paper elaborates on the novel intelligence assessment method using the brainwave sub-band power ratio features. The study focuses only on the left hemisphere brainwave in its relaxed state. Distinct intelligence quotient groups have been established earlier from the score of the Raven Progressive Matrices. Sub-band power ratios are calculated from energy spectral density of theta, alpha and beta frequency bands. Synthetic data have been generated to increase dataset from 50 to 120. The features are used as input to the artificial neural network. Subsequently, the brain behaviour model has been developed using an artificial neural network that is trained with optimized learning rate, momentum constant and hidden nodes. Findings indicate that the distinct intelligence quotient groups can be classified from the brainwave sub-band power ratios with 100% training and 88.89% testing accuracies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Knowledge representation by connection matrices: A method for the on-board implementation of large expert systems

NASA Technical Reports Server (NTRS)

Kellner, A.

1987-01-01

Extremely large knowledge sources and efficient knowledge access characterizing future real-life artificial intelligence applications represent crucial requirements for on-board artificial intelligence systems due to obvious computer time and storage constraints on spacecraft. A type of knowledge representation and corresponding reasoning mechanism is proposed which is particularly suited for the efficient processing of such large knowledge bases in expert systems.

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.

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…

AIonAI: a humanitarian law of artificial intelligence and robotics.

PubMed

Ashrafian, Hutan

2015-02-01

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

Can Artificial Intelligences Suffer from Mental Illness? A Philosophical Matter to Consider.

PubMed

Ashrafian, Hutan

2017-04-01

The potential for artificial intelligences and robotics in achieving the capacity of consciousness, sentience and rationality offers the prospect that these agents have minds. If so, then there may be a potential for these minds to become dysfunctional, or for artificial intelligences and robots to suffer from mental illness. The existence of artificially intelligent psychopathology can be interpreted through the philosophical perspectives of mental illness. This offers new insights into what it means to have either robot or human mental disorders, but may also offer a platform on which to examine the mechanisms of biological or artificially intelligent psychiatric disease. The possibility of mental illnesses occurring in artificially intelligent individuals necessitates the consideration that at some level, they may have achieved a mental capability of consciousness, sentience and rationality such that they can subsequently become dysfunctional. The deeper philosophical understanding of these conditions in mankind and artificial intelligences might therefore offer reciprocal insights into mental health and mechanisms that may lead to the prevention of mental dysfunction.

An Intelligent Tutor for Intrusion Detection on Computer Systems.

ERIC Educational Resources Information Center

Rowe, Neil C.; Schiavo, Sandra

1998-01-01

Describes an intelligent tutor incorporating a program using artificial-intelligence planning methods to generate realistic audit files reporting actions of simulated users and intruders of a UNIX system, and a program simulating the system afterwards that asks students to inspect the audit and fix problems. Experiments show that students using…

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,…

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

NASA Astrophysics Data System (ADS)

Habiballa, Hashim; Jendryscik, Radek

2017-11-01

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

The application of hybrid artificial intelligence systems for forecasting

NASA Astrophysics Data System (ADS)

Lees, Brian; Corchado, Juan

1999-03-01

The results to date are presented from an ongoing investigation, in which the aim is to combine the strengths of different artificial intelligence methods into a single problem solving system. The premise underlying this research is that a system which embodies several cooperating problem solving methods will be capable of achieving better performance than if only a single method were employed. The work has so far concentrated on the combination of case-based reasoning and artificial neural networks. The relative merits of artificial neural networks and case-based reasoning problem solving paradigms, and their combination are discussed. The integration of these two AI problem solving methods in a hybrid systems architecture, such that the neural network provides support for learning from past experience in the case-based reasoning cycle, is then presented. The approach has been applied to the task of forecasting the variation of physical parameters of the ocean. Results obtained so far from tests carried out in the dynamic oceanic environment are presented.

Artificial Intelligence and Autonomy: Opportunities and Challenges

DTIC Science & Technology

2017-10-01

Cleared for Public Release Artificial Intelligence & Autonomy Opportunities and Challenges Andrew Ilachinski October 2017 Copyright © 2017 CNA... Artificial Intelligence & Autonomy Opportunities and 5a. CONTRACT NUMBER N00014-16-D-5003 Challenges 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 0605154N...conducted by unmanned and increasingly autonomous weapon systems. This exploratory study considers the state-of-the-art of artificial intelligence (AI

Artificial Intelligence Information Sources for the Beginner and Expert

DTIC Science & Technology

1991-05-01

SUBPLEETAR TMS T bepbhdi" Artificial Intelligence ApplictionsforMlitar Expertis SystemsWilasbrVA 527Mrh 91 12a. DSCRIBTION C AIITY 6 STAEENRTY CTO SECb.T...DLSIFC ISTR BUMATION OC Apnclassified pu ncrlase; ituied inlsife unlimited. Artificial Intelligence Information Sources for the Beginner and Expert...mgivenfdsac.dia.mil UUCP: {...).osu-cisidsac!mgiven ABSTRACT A tremendous amount of information on artificial intelligence is available via different

Rapid Simulation of Blast Wave Propagation in Built Environments Using Coarse-Grain Based Intelligent Modeling Methods

DTIC Science & Technology

2011-04-01

experiments was performed using an artificial neural network to try to capture the nonlinearities. The radial Gaussian artificial neural network system...Modeling Blast-Wave Propagation using Artificial Neural Network Methods‖, in International Journal of Advanced Engineering Informatics, Elsevier

The Outline of Personhood Law Regarding Artificial Intelligences and Emulated Human Entities

NASA Astrophysics Data System (ADS)

Muzyka, Kamil

2013-12-01

On the verge of technological breakthroughs, which define and revolutionize our understanding of intelligence, cognition, and personhood, especially when speaking of artificial intelligences and mind uploads, one must consider the legal implications of granting personhood rights to artificial intelligences or emulated human entities

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.

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

DTIC Science & Technology

1989-03-01

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

An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

DOT National Transportation Integrated Search

1996-01-01

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

Using Students' Knowledge to Generate Individual Feedback: Concept for an Intelligent Educational System on Logistics.

ERIC Educational Resources Information Center

Ziems, Dietrich; Neumann, Gaby

1997-01-01

Discusses a methods kit for interactive problem-solving exercises in engineering education as well as a methodology for intelligent evaluation of solutions. The quality of a system teaching logistics thinking can be improved using artificial intelligence. Embedding a rule-based diagnosis module that evaluates the student's knowledge actively…

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…

Prediction of Human Intestinal Absorption of Compounds Using Artificial Intelligence Techniques.

PubMed

Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

2017-01-01

Information about Pharmacokinetics of compounds is an essential component of drug design and development. Modeling the pharmacokinetic properties require identification of the factors effecting absorption, distribution, metabolism and excretion of compounds. There have been continuous attempts in the prediction of intestinal absorption of compounds using various Artificial intelligence methods in the effort to reduce the attrition rate of drug candidates entering to preclinical and clinical trials. Currently, there are large numbers of individual predictive models available for absorption using machine learning approaches. Six Artificial intelligence methods namely, Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis were used for prediction of absorption of compounds. Prediction accuracy of Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis for prediction of intestinal absorption of compounds was found to be 91.54%, 88.33%, 84.30%, 86.51%, 79.07% and 80.08% respectively. Comparative analysis of all the six prediction models suggested that Support vector machine with Radial basis function based kernel is comparatively better for binary classification of compounds using human intestinal absorption and may be useful at preliminary stages of drug design and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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.

A Primer for Problem Solving Using Artificial Intelligence.

ERIC Educational Resources Information Center

Schell, George P.

1988-01-01

Reviews the development of artificial intelligence systems and the mechanisms used, including knowledge representation, programing languages, and problem processing systems. Eleven books and 6 journals are listed as sources of information on artificial intelligence. (23 references) (CLB)

Research and applications: Artificial intelligence

NASA Technical Reports Server (NTRS)

Raphael, B.; Fikes, R. E.; Chaitin, L. J.; Hart, P. E.; Duda, R. O.; Nilsson, N. J.

1971-01-01

A program of research in the field of artificial intelligence is presented. The research areas discussed include automatic theorem proving, representations of real-world environments, problem-solving methods, the design of a programming system for problem-solving research, techniques for general scene analysis based upon television data, and the problems of assembling an integrated robot system. Major accomplishments include the development of a new problem-solving system that uses both formal logical inference and informal heuristic methods, the development of a method of automatic learning by generalization, and the design of the overall structure of a new complete robot system. Eight appendices to the report contain extensive technical details of the work described.

Intelligence Fusion Modeling. A Proposed Approach.

DTIC Science & Technology

1983-09-16

based techniques developed by artificial intelligence researchers. This paper describes the application of these techniques in the modeling of an... intelligence requirements, although the methods presented are applicable . We treat PIR/IR as given. -7- -- -W V"W v* 1.- . :71.,v It k*~ ~-- Movement...items from the PIR/IR/HVT decomposition are received from the CMDS. Formatted tactical intelligence reports are received from sensors of like types

Modeling of biological intelligence for SCM system optimization.

PubMed

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

PubMed Central

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

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

NASA Astrophysics Data System (ADS)

Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

2016-08-01

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

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.

A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems

DTIC Science & Technology

1990-11-01

Intelligence Systems," in Distributed Artifcial Intelligence , vol. II, L. Gasser and M. Huhns (eds), Pitman, London, 1989, pp. 413-430. Shaw, M. Harrow, B...IDTIC FILE COPY A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems N Michael I. Shaw...SUBTITLE 5. FUNDING NUMBERS A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems 6

2017 Cybersecurity Workshop: Readouts from Working Groups - Video Text

Science.gov Websites

applicability of artificial intelligence to search for cybersecurity gaps in our existing SKATA networks. Second primarily renewable that all back each other up; that are all highly intelligent, artificial intelligence we have in cyber security, digital technologies, artificial intelligence. We think that that would

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.

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

ERIC Educational Resources Information Center

Pickett, John C.

1984-01-01

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

Artificial intelligence in astronomy - a forecast.

NASA Astrophysics Data System (ADS)

Adorf, H. M.

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

In Pursuit of Artificial Intelligence.

ERIC Educational Resources Information Center

Watstein, Sarah; Kesselman, Martin

1986-01-01

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

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

PubMed

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

2018-04-20

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

Analysis and Implementation of Robust Grasping Behaviors

DTIC Science & Technology

1990-05-01

34 Technical Report 992, MIT Artificial Intelligence Laboratory, Cambridge, MA, May, 1987. 2. Brooks, R. A. "Achieving Artifci &l Intelligence Through...DTIu FILE COPY Technical Report 1237 ’Analysis and Implementation of NRobust Grasping Behaviors Camille Z. Chammas MIT Artificial Intelligence ...describes research conducted at the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the laboratory’s

An Approach to Object Recognition: Aligning Pictorial Descriptions.

DTIC Science & Technology

1986-12-01

PERFORMING 0RGANIZATION NAMIE ANDORS IS551. PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREKA A WORK UNIT NUMBERS ( 545 Technology... ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 931 December, 1986 AN APPROACH TO OBJECT RECOGNITION: ALIGNING PICTORIAL DESCRIPTIONS Shimon Ullman...within the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the A.I. Laboratory’s artificial intelligence

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 in Astronomy

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

The Artificial Intelligence Applications to Learning Programme.

ERIC Educational Resources Information Center

Williams, Noel

1992-01-01

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

Artificial Intelligence and Language Comprehension.

ERIC Educational Resources Information Center

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

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

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,…

Dynamical Systems and Motion Vision.

DTIC Science & Technology

1988-04-01

TASK Artificial Inteligence Laboratory AREA I WORK UNIT NUMBERS 545 Technology Square . Cambridge, MA 02139 C\\ II. CONTROLLING OFFICE NAME ANO0 ADDRESS...INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I.Memo No. 1037 April, 1988 Dynamical Systems and Motion Vision Joachim Heel Abstract: In this... Artificial Intelligence L3 Laboratory of the Massachusetts Institute of Technology. Support for the Laboratory’s [1 Artificial Intelligence Research is

Northeast Artificial Intelligence Consortium (NAIC). Volume 2. Discussing, Using, and Recognizing Plans

DTIC Science & Technology

1990-12-01

knowledge and meta-reasoning. In Proceedings of EP14-85 ("Encontro Portugues de Inteligencia Artificial "), pages 138-154, Oporto, Portugal, 1985. [19] N, J...See reverse) 7. PERFORMING ORGANIZATION NAME(S) AND ADORESS(ES) 8. PERFORMING ORGANIZATION Northeast Artificial Intelligence...ABSTRACTM-2.,-- The Northeast Artificial Intelligence Consortium (NAIC) was created by the Air Force Systems Command, Rome Air Development Center, and

Artificial Intelligence Study (AIS).

DTIC Science & Technology

1987-02-01

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

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

NASA Technical Reports Server (NTRS)

Baron, S.; Feehrer, C.

1985-01-01

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

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

ERIC Educational Resources Information Center

Buckland, Michael K.; Florian, Doris

1991-01-01

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

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

Reasoning methods in medical consultation systems: artificial intelligence approaches.

PubMed

Shortliffe, E H

1984-01-01

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

Improving designer productivity. [artificial intelligence

NASA Technical Reports Server (NTRS)

Hill, Gary C.

1992-01-01

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

De Novo Design of Bioactive Small Molecules by Artificial Intelligence

PubMed Central

Merk, Daniel; Friedrich, Lukas; Grisoni, Francesca

2018-01-01

Abstract Generative artificial intelligence offers a fresh view on molecular design. We present the first‐time prospective application of a deep learning model for designing new druglike compounds with desired activities. For this purpose, we trained a recurrent neural network to capture the constitution of a large set of known bioactive compounds represented as SMILES strings. By transfer learning, this general model was fine‐tuned on recognizing retinoid X and peroxisome proliferator‐activated receptor agonists. We synthesized five top‐ranking compounds designed by the generative model. Four of the compounds revealed nanomolar to low‐micromolar receptor modulatory activity in cell‐based assays. Apparently, the computational model intrinsically captured relevant chemical and biological knowledge without the need for explicit rules. The results of this study advocate generative artificial intelligence for prospective de novo molecular design, and demonstrate the potential of these methods for future medicinal chemistry. PMID:29319225

Knowledge-based processing for aircraft flight control

NASA Technical Reports Server (NTRS)

Painter, John H.; Glass, Emily; Economides, Gregory; Russell, Paul

1994-01-01

This Contractor Report documents research in Intelligent Control using knowledge-based processing in a manner dual to methods found in the classic stochastic decision, estimation, and control discipline. Such knowledge-based control has also been called Declarative, and Hybid. Software architectures were sought, employing the parallelism inherent in modern object-oriented modeling and programming. The viewpoint adopted was that Intelligent Control employs a class of domain-specific software architectures having features common over a broad variety of implementations, such as management of aircraft flight, power distribution, etc. As much attention was paid to software engineering issues as to artificial intelligence and control issues. This research considered that particular processing methods from the stochastic and knowledge-based worlds are duals, that is, similar in a broad context. They provide architectural design concepts which serve as bridges between the disparate disciplines of decision, estimation, control, and artificial intelligence. This research was applied to the control of a subsonic transport aircraft in the airport terminal area.

The Case for Artificial Intelligence in Medicine

PubMed Central

Reggia, James A.

1983-01-01

Current artificial intelligence (AI) technology can be viewed as producing “systematic artifacts” onto which we project an interpretation of intelligent behavior. One major benefit this technology could bring to medicine is help with handling the tremendous and growing volume of medical knowledge. The reader is led to a vision of the medical library of tomorrow, an interactive, artificially intelligent knowledge source that is fully and directly integrated with daily patient care.

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

List of ARI Conference Papers, Journal Articles, Books, and Book Chapters: 1982-1991

DTIC Science & Technology

1992-10-01

and Engineering Applications of Artificial Intelligence and Expert Systems, Tullahoma, TN. Goehring, D.J., & Hart, R.J. (1985, October). Automated...systems: Computkr-based authoring. Proceedings of the 30th annual meeting of the Artificial Intelligence Society, Dayton, OH. Knapp, D.J., & Pliske, R.M...Moses, F.L. (1984-85) Intelligence vehicle integrated displays. Paper presented at the Conference on Applied Artificial Intelligence , the Data Processing

Knowledge-Based Software Development Tools

DTIC Science & Technology

1993-09-01

GREEN, C., AND WESTFOLD, S. Knowledge-based programming self-applied. In Machine Intelligence 10, J. E. Hayes, D. Mitchie, and Y. Pao, Eds., Wiley...Technical Report KES.U.84.2, Kestrel Institute, April 1984. [181 KORF, R. E. Toward a model of representation changes. Artificial Intelligence 14, 1...Artificial Intelligence 27, 1 (February 1985), 43-96. Replinted in Readings in Artificial Intelligence and Software Engineering, C. Rich •ad R. Waters

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 use of artificially intelligent agents with bounded rationality in the study of economic markets

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

Rajan, V.; Slagle, J.R.

The concepts of {open_quote}knowledge{close_quote} and {open_quote}rationality{close_quote} are of central importance to fields of science that are interested in human behavior and learning, such as artificial intelligence, economics, and psychology. The similarity between artificial intelligence and economics - both are concerned with intelligent thought, rational behavior, and the use and acquisition of knowledge - has led to the use of economic models as a paradigm for solving problems in distributed artificial intelligence (DAI) and multi agent systems (MAS). What we propose is the opposite; the use of artificial intelligence in the study of economic markets. Over the centuries various theories ofmore » market behavior have been advanced. The prevailing theory holds that an asset`s current price converges to the risk adjusted value of the rationally expected dividend stream. While this rational expectations model holds in equilibrium or near-equilibrium conditions, it does not sufficiently explain conditions of market disequilibrium. An example of market disequilibrium is the phenomenon of a speculative bubble. We present an example of using artificially intelligent agents with bounded rationality in the study of speculative bubbles.« less

Application of artifical intelligence principles to the analysis of "crazy" speech.

PubMed

Garfield, D A; Rapp, C

1994-04-01

Artificial intelligence computer simulation methods can be used to investigate psychotic or "crazy" speech. Here, symbolic reasoning algorithms establish semantic networks that schematize speech. These semantic networks consist of two main structures: case frames and object taxonomies. Node-based reasoning rules apply to object taxonomies and pathway-based reasoning rules apply to case frames. Normal listeners may recognize speech as "crazy talk" based on violations of node- and pathway-based reasoning rules. In this article, three separate segments of schizophrenic speech illustrate violations of these rules. This artificial intelligence approach is compared and contrasted with other neurolinguistic approaches and is discussed as a conceptual link between neurobiological and psychodynamic understandings of psychopathology.

Intelligent failure-tolerant control

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1991-01-01

An overview of failure-tolerant control is presented, beginning with robust control, progressing through parallel and analytical redundancy, and ending with rule-based systems and artificial neural networks. By design or implementation, failure-tolerant control systems are 'intelligent' systems. All failure-tolerant systems require some degrees of robustness to protect against catastrophic failure; failure tolerance often can be improved by adaptivity in decision-making and control, as well as by redundancy in measurement and actuation. Reliability, maintainability, and survivability can be enhanced by failure tolerance, although each objective poses different goals for control system design. Artificial intelligence concepts are helpful for integrating and codifying failure-tolerant control systems, not as alternatives but as adjuncts to conventional design methods.

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.

What Is Artificial Intelligence Anyway?

ERIC Educational Resources Information Center

Kurzweil, Raymond

1985-01-01

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

Self-Calibration and Optimal Response in Intelligent Sensors Design Based on Artificial Neural Networks

PubMed Central

Rivera, José; Carrillo, Mariano; Chacón, Mario; Herrera, Gilberto; Bojorquez, Gilberto

2007-01-01

The development of smart sensors involves the design of reconfigurable systems capable of working with different input sensors. Reconfigurable systems ideally should spend the least possible amount of time in their calibration. An autocalibration algorithm for intelligent sensors should be able to fix major problems such as offset, variation of gain and lack of linearity, as accurately as possible. This paper describes a new autocalibration methodology for nonlinear intelligent sensors based on artificial neural networks, ANN. The methodology involves analysis of several network topologies and training algorithms. The proposed method was compared against the piecewise and polynomial linearization methods. Method comparison was achieved using different number of calibration points, and several nonlinear levels of the input signal. This paper also shows that the proposed method turned out to have a better overall accuracy than the other two methods. Besides, experimentation results and analysis of the complete study, the paper describes the implementation of the ANN in a microcontroller unit, MCU. In order to illustrate the method capability to build autocalibration and reconfigurable systems, a temperature measurement system was designed and tested. The proposed method is an improvement over the classic autocalibration methodologies, because it impacts on the design process of intelligent sensors, autocalibration methodologies and their associated factors, like time and cost.

Visiting Scholars Program

DTIC Science & Technology

2016-09-01

other associated grants. 15. SUBJECT TERMS SUNY Poly, STEM, Artificial Intelligence , Command and Control 16. SECURITY CLASSIFICATION OF: 17...neuromorphic system has the potential to be widely used in a high-efficiency artificial intelligence system. Simulation results have indicated that the...novel multiresolution fusion and advanced fusion performance evaluation tool for an Artificial Intelligence based natural language annotation engine for

The Joint Tactical Aerial Resupply Vehicle Impact on Sustainment Operations

DTIC Science & Technology

2017-06-09

Artificial Intelligence , Sustainment Operations, Rifle Company, Autonomous Aerial Resupply, Joint Tactical Autonomous Aerial Resupply System 16...Integrations and Development System AI Artificial Intelligence ARCIC Army Capabilities Integration Center ARDEC Armament Research, Development and...semi- autonomous systems, and fully autonomous systems. Autonomy of machines depends on sophisticated software, including Artificial Intelligence

Artificial Intelligence Measurement System, Overview and Lessons Learned. Final Project Report.

ERIC Educational Resources Information Center

Baker, Eva L.; Butler, Frances A.

This report summarizes the work conducted for the Artificial Intelligence Measurement System (AIMS) Project which was undertaken as an exploration of methodology to consider how the effects of artificial intelligence systems could be compared to human performance. The research covered four areas of inquiry: (1) natural language processing and…

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…

Computer science, artificial intelligence, and cybernetics: Applied artificial intelligence in Japan

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

Rubinger, B.

1988-01-01

This sourcebook provides information on the developments in artificial intelligence originating in Japan. Spanning such innovations as software productivity, natural language processing, CAD, and parallel inference machines, this volume lists leading organizations conducting research or implementing AI systems, describes AI applications being pursued, illustrates current results achieved, and highlights sources reporting progress.

The importance of motivation and emotion for explaining human cognition.

PubMed

Güss, C Dominik; Dörner, Dietrich

2017-01-01

Lake et al. discuss building blocks of human intelligence that are quite different from those of artificial intelligence. We argue that a theory of human intelligence has to incorporate human motivations and emotions. The interaction of motivation, emotion, and cognition is the real strength of human intelligence and distinguishes it from artificial intelligence.

New application of intelligent agents in sporadic amyotrophic lateral sclerosis identifies unexpected specific genetic background.

PubMed

Penco, Silvana; Buscema, Massimo; Patrosso, Maria Cristina; Marocchi, Alessandro; Grossi, Enzo

2008-05-30

Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis. An unexpected discovery of a strong genetic background in sporadic ALS using a DNA multiarray panel and analytical processing of the data with advanced artificial neural networks was found. The predictive accuracy obtained with Linear Discriminant Analysis and Standard Artificial Neural Networks ranged from 70% to 79% (average 75.31%) and from 69.1 to 86.2% (average 76.6%) respectively. The corresponding value obtained with Advanced Intelligent Systems reached an average of 96.0% (range 94.4 to 97.6%). This latter approach allowed the identification of seven genetic variants essential to differentiate cases from controls: apolipoprotein E arg158cys; hepatic lipase -480 C/T; endothelial nitric oxide synthase 690 C/T and glu298asp; vitamin K-dependent coagulation factor seven arg353glu, glycoprotein Ia/IIa 873 G/A and E-selectin ser128arg. This study provides an alternative and reliable method to approach complex diseases. Indeed, the application of a novel artificial intelligence-based method offers a new insight into genetic markers of sporadic ALS pointing out the existence of a strong genetic background.

Northeast Artificial Intelligence Consortium Annual Report. 1988 Interference Techniques for Knowledge Base Maintenance Using Logic Programming Methodologies. Volume 11

DTIC Science & Technology

1989-10-01

Northeast Aritificial Intelligence Consortium (NAIC). i Table of Contents Execu tive Sum m ary...o g~nIl ’vLr COPY o~ T- RADC-TR-89-259, Vol XI (of twelve) N Interim Report SOctober 1989 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT...ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Northeast Artificial (If applicable) Intelligence Consortium (NAIC) . Rome Air Development

The 1990 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor)

1990-01-01

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

Artificial intelligence in sports on the example of weight training.

PubMed

Novatchkov, Hristo; Baca, Arnold

2013-01-01

The overall goal of the present study was to illustrate the potential of artificial intelligence (AI) techniques in sports on the example of weight training. The research focused in particular on the implementation of pattern recognition methods for the evaluation of performed exercises on training machines. The data acquisition was carried out using way and cable force sensors attached to various weight machines, thereby enabling the measurement of essential displacement and force determinants during training. On the basis of the gathered data, it was consequently possible to deduce other significant characteristics like time periods or movement velocities. These parameters were applied for the development of intelligent methods adapted from conventional machine learning concepts, allowing an automatic assessment of the exercise technique and providing individuals with appropriate feedback. In practice, the implementation of such techniques could be crucial for the investigation of the quality of the execution, the assistance of athletes but also coaches, the training optimization and for prevention purposes. For the current study, the data was based on measurements from 15 rather inexperienced participants, performing 3-5 sets of 10-12 repetitions on a leg press machine. The initially preprocessed data was used for the extraction of significant features, on which supervised modeling methods were applied. Professional trainers were involved in the assessment and classification processes by analyzing the video recorded executions. The so far obtained modeling results showed good performance and prediction outcomes, indicating the feasibility and potency of AI techniques in assessing performances on weight training equipment automatically and providing sportsmen with prompt advice. Key pointsArtificial intelligence is a promising field for sport-related analysis.Implementations integrating pattern recognition techniques enable the automatic evaluation of data measurements.Artificial neural networks applied for the analysis of weight training data show good performance and high classification rates.

Artificial Intelligence in Sports on the Example of Weight Training

PubMed Central

Novatchkov, Hristo; Baca, Arnold

2013-01-01

The overall goal of the present study was to illustrate the potential of artificial intelligence (AI) techniques in sports on the example of weight training. The research focused in particular on the implementation of pattern recognition methods for the evaluation of performed exercises on training machines. The data acquisition was carried out using way and cable force sensors attached to various weight machines, thereby enabling the measurement of essential displacement and force determinants during training. On the basis of the gathered data, it was consequently possible to deduce other significant characteristics like time periods or movement velocities. These parameters were applied for the development of intelligent methods adapted from conventional machine learning concepts, allowing an automatic assessment of the exercise technique and providing individuals with appropriate feedback. In practice, the implementation of such techniques could be crucial for the investigation of the quality of the execution, the assistance of athletes but also coaches, the training optimization and for prevention purposes. For the current study, the data was based on measurements from 15 rather inexperienced participants, performing 3-5 sets of 10-12 repetitions on a leg press machine. The initially preprocessed data was used for the extraction of significant features, on which supervised modeling methods were applied. Professional trainers were involved in the assessment and classification processes by analyzing the video recorded executions. The so far obtained modeling results showed good performance and prediction outcomes, indicating the feasibility and potency of AI techniques in assessing performances on weight training equipment automatically and providing sportsmen with prompt advice. Key points Artificial intelligence is a promising field for sport-related analysis. Implementations integrating pattern recognition techniques enable the automatic evaluation of data measurements. Artificial neural networks applied for the analysis of weight training data show good performance and high classification rates. PMID:24149722

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…

Quantum neuromorphic hardware for quantum artificial intelligence

NASA Astrophysics Data System (ADS)

Prati, Enrico

2017-08-01

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

Functional integration of automated system databases by means of artificial intelligence

NASA Astrophysics Data System (ADS)

Dubovoi, Volodymyr M.; Nikitenko, Olena D.; Kalimoldayev, Maksat; Kotyra, Andrzej; Gromaszek, Konrad; Iskakova, Aigul

2017-08-01

The paper presents approaches for functional integration of automated system databases by means of artificial intelligence. The peculiarities of turning to account the database in the systems with the usage of a fuzzy implementation of functions were analyzed. Requirements for the normalization of such databases were defined. The question of data equivalence in conditions of uncertainty and collisions in the presence of the databases functional integration is considered and the model to reveal their possible occurrence is devised. The paper also presents evaluation method of standardization of integrated database normalization.

The role of networks and artificial intelligence in nanotechnology design and analysis.

PubMed

Hudson, D L; Cohen, M E

2004-05-01

Techniques with their origins in artificial intelligence have had a great impact on many areas of biomedicine. Expert-based systems have been used to develop computer-assisted decision aids. Neural networks have been used extensively in disease classification and more recently in many bioinformatics applications including genomics and drug design. Network theory in general has proved useful in modeling all aspects of biomedicine from healthcare organizational structure to biochemical pathways. These methods show promise in applications involving nanotechnology both in the design phase and in interpretation of system functioning.

The role of artificial intelligence techniques in scheduling systems

NASA Technical Reports Server (NTRS)

Geoffroy, Amy L.; Britt, Daniel L.; Gohring, John R.

1990-01-01

Artificial Intelligence (AI) techniques provide good solutions for many of the problems which are characteristic of scheduling applications. However, scheduling is a large, complex heterogeneous problem. Different applications will require different solutions. Any individual application will require the use of a variety of techniques, including both AI and conventional software methods. The operational context of the scheduling system will also play a large role in design considerations. The key is to identify those places where a specific AI technique is in fact the preferable solution, and to integrate that technique into the overall architecture.

Estimation of urban runoff and water quality using remote sensing and artificial intelligence.

PubMed

Ha, S R; Park, S Y; Park, D H

2003-01-01

Water quality and quantity of runoff are strongly dependent on the landuse and landcover (LULC) criteria. In this study, we developed a more improved parameter estimation procedure for the environmental model using remote sensing (RS) and artificial intelligence (AI) techniques. Landsat TM multi-band (7bands) and Korea Multi-Purpose Satellite (KOMPSAT) panchromatic data were selected for input data processing. We employed two kinds of artificial intelligence techniques, RBF-NN (radial-basis-function neural network) and ANN (artificial neural network), to classify LULC of the study area. A bootstrap resampling method, a statistical technique, was employed to generate the confidence intervals and distribution of the unit load. SWMM was used to simulate the urban runoff and water quality and applied to the study watershed. The condition of urban flow and non-point contaminations was simulated with rainfall-runoff and measured water quality data. The estimated total runoff, peak time, and pollutant generation varied considerably according to the classification accuracy and percentile unit load applied. The proposed procedure would efficiently be applied to water quality and runoff simulation in a rapidly changing urban area.

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

PubMed

Bianchini, Francesco

2016-10-01

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

Protecting Networks Via Automated Defense of Cyber Systems

DTIC Science & Technology

2016-09-01

autonomics, and artificial intelligence . Our conclusion is that automation is the future of cyber defense, and that advances are being made in each of...SUBJECT TERMS Internet of Things, autonomics, sensors, artificial intelligence , cyber defense, active cyber defense, automated indicator sharing...called Automated Defense of Cyber Systems, built upon three core technological components: sensors, autonomics, and artificial intelligence . Our

Automated Knowledge Generation with Persistent Surveillance Video

DTIC Science & Technology

2008-03-26

5 2.1 Artificial Intelligence . . . . . . . . . . . . . . . . . . . . 5 2.1.1 Formal Logic . . . . . . . . . . . . . . . . . . . 6 2.1.2...background of Artificial Intelligence and the reasoning engines that will be applied to generate knowledge from data. Section 2.2 discusses background on...generation from persistent video. 4 II. Background In this chapter, we will discuss the background of Artificial Intelligence, Semantic Web, image

Finding Edges and Lines in Images.

DTIC Science & Technology

1983-06-01

34 UNCLASSI FlED , SECURITY CLASSIFICATION OF THIS PAGE ("osen Data Entered) READ INSTRUCTIONSREPORT DOCUMENTATION PAGE BEFORE COMPLETING FORM I. REPORT...PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA&WORKUNITNUMBERS 545 Technology Square...in the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory’s artificial intelligence research

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

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

Instrumentation for Scientific Computing in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics.

DTIC Science & Technology

1987-10-01

include Security Classification) Instrumentation for scientific computing in neural networks, information science, artificial intelligence, and...instrumentation grant to purchase equipment for support of research in neural networks, information science, artificail intellignece , and applied mathematics...in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics Contract AFOSR 86-0282 Principal Investigator: Stephen

Real Rules of Inference

DTIC Science & Technology

1986-01-01

the AAAI Workshop on Uncertainty and Probability in Artificial Intelligence , 1985. [McC771 McCarthy, J. "Epistemological Problems of Aritificial ...NUMBER OF PAGES Artificial Intelligence , Data Fusion, Inference, Probability, 30 Philosophy, Inheritance Hierachies, Default Reasoning ia.PRCECODE I...prominent philosophers Glymour and Thomason even applaud the uninhibited steps: Artificial Intelligence has done us the service not only of reminding us

Current Uses of Artificial Intelligence in Special Education. Abstract XI: Research & Resources on Special Education.

ERIC Educational Resources Information Center

ERIC Clearinghouse on Handicapped and Gifted Children, Reston, VA.

Summarized are two reports of a federally funded project on the use of artificial intelligence in special education. The first report, "Artificial Intelligence Applications in Special Education: How Feasible?," by Alan Hofmeister and Joseph Ferrara, provides information on the development and evaluation of a series of prototype systems in special…

Cultural Modelling: Literature review

DTIC Science & Technology

2006-09-01

of mood and/or emotions. Our review did show some evidence that artificial intelligence research has tended to depict human decision making as...pp. 72-79). The Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB). Halfill, T., Sundstrom, E., Nielsen, T. M...M. & Thagard, P. (2005). Changing personalities: Towards realistic virtual characters. Journal of Experimental & Theoretical Artificial Intelligence

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

ERIC Educational Resources Information Center

Atkinson, Robert D.

2016-01-01

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

Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

ERIC Educational Resources Information Center

Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

2010-01-01

Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

Smart Collections: Can Artificial Intelligence Tools and Techniques Assist with Discovering, Evaluating and Tagging Digital Learning Resources?

ERIC Educational Resources Information Center

Leibbrandt, Richard; Yang, Dongqiang; Pfitzner, Darius; Powers, David; Mitchell, Pru; Hayman, Sarah; Eddy, Helen

2010-01-01

This paper reports on a joint proof of concept project undertaken by researchers from the Flinders University Artificial Intelligence Laboratory in partnership with information managers from the Education Network Australia (edna) team at Education Services Australia to address the question of whether artificial intelligence techniques could be…

ESD/MITRE Software Acquisition Symposium Proceedings; an ESD/Industry Dialogue held in Bedford, Massachusetts on May 6-7, 1986

DTIC Science & Technology

1986-05-07

Cycle? Moderator: Christine M. Anderson Dennis D. Doe Manager of Engineering Software and Artificial Intelligence Boeing Aerospace Company In... intelligence systems development pro- cess affect the life cycle? Artificial intelligence developers seem to be the last haven for people who don’t...of Engineering Software and Artificial Intelligence at the Boeing Aerospace Company. In this capacity, Mr. Doe is the focal point for software

Knowledge Based Simulation: An Artificial Intelligence Approach to System Modeling and Automating the Simulation Life Cycle.

DTIC Science & Technology

1988-04-13

Simulation: An Artificial Intelligence Approach to System Modeling and Automating the Simulation Life Cycle Mark S. Fox, Nizwer Husain, Malcolm...McRoberts and Y.V.Reddy CMU-RI-TR-88-5 Intelligent Systems Laboratory The Robotics Institute Carnegie Mellon University Pittsburgh, Pennsylvania D T T 13...years of research in the application of Artificial Intelligence to Simulation. Our focus has been in two areas: the use of Al knowledge representation

Application of Neural Network Technologies for Price Forecasting in the Liberalized Electricity Market

NASA Astrophysics Data System (ADS)

Gerikh, Valentin; Kolosok, Irina; Kurbatsky, Victor; Tomin, Nikita

2009-01-01

The paper presents the results of experimental studies concerning calculation of electricity prices in different price zones in Russia and Europe. The calculations are based on the intelligent software "ANAPRO" that implements the approaches based on the modern methods of data analysis and artificial intelligence technologies.

The Role of Artificial Intelligence in Diagnostic Radiology: A Survey at a Single Radiology Residency Training Program.

PubMed

Collado-Mesa, Fernando; Alvarez, Edilberto; Arheart, Kris

2018-02-21

Advances in artificial intelligence applied to diagnostic radiology are predicted to have a major impact on this medical specialty. With the goal of establishing a baseline upon which to build educational activities on this topic, a survey was conducted among trainees and attending radiologists at a single residency program. An anonymous questionnaire was distributed. Comparisons of categorical data between groups (trainees and attending radiologists) were made using Pearson χ 2 analysis or an exact analysis when required. Comparisons were made using the Wilcoxon rank sum test when the data were not normally distributed. An α level of 0.05 was used. The overall response rate was 66% (69 of 104). Thirty-six percent of participants (n = 25) reported not having read a scientific medical article on the topic of artificial intelligence during the past 12 months. Twenty-nine percent of respondents (n = 12) reported using artificial intelligence tools during their daily work. Trainees were more likely to express doubts on whether they would have pursued diagnostic radiology as a career had they known of the potential impact artificial intelligence is predicted to have on the specialty (P = .0254) and were also more likely to plan to learn about the topic (P = .0401). Radiologists lack exposure to current scientific medical articles on artificial intelligence. Trainees are concerned by the implications artificial intelligence may have on their jobs and desire to learn about the topic. There is a need to develop educational resources to help radiologists assume an active role in guiding and facilitating the development and implementation of artificial intelligence tools in diagnostic radiology. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

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

Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data

NASA Astrophysics Data System (ADS)

Jia, Feng; Lei, Yaguo; Lin, Jing; Zhou, Xin; Lu, Na

2016-05-01

Aiming to promptly process the massive fault data and automatically provide accurate diagnosis results, numerous studies have been conducted on intelligent fault diagnosis of rotating machinery. Among these studies, the methods based on artificial neural networks (ANNs) are commonly used, which employ signal processing techniques for extracting features and further input the features to ANNs for classifying faults. Though these methods did work in intelligent fault diagnosis of rotating machinery, they still have two deficiencies. (1) The features are manually extracted depending on much prior knowledge about signal processing techniques and diagnostic expertise. In addition, these manual features are extracted according to a specific diagnosis issue and probably unsuitable for other issues. (2) The ANNs adopted in these methods have shallow architectures, which limits the capacity of ANNs to learn the complex non-linear relationships in fault diagnosis issues. As a breakthrough in artificial intelligence, deep learning holds the potential to overcome the aforementioned deficiencies. Through deep learning, deep neural networks (DNNs) with deep architectures, instead of shallow ones, could be established to mine the useful information from raw data and approximate complex non-linear functions. Based on DNNs, a novel intelligent method is proposed in this paper to overcome the deficiencies of the aforementioned intelligent diagnosis methods. The effectiveness of the proposed method is validated using datasets from rolling element bearings and planetary gearboxes. These datasets contain massive measured signals involving different health conditions under various operating conditions. The diagnosis results show that the proposed method is able to not only adaptively mine available fault characteristics from the measured signals, but also obtain superior diagnosis accuracy compared with the existing methods.

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…

Research on UAV Intelligent Obstacle Avoidance Technology During Inspection of Transmission Line

NASA Astrophysics Data System (ADS)

Wei, Chuanhu; Zhang, Fei; Yin, Chaoyuan; Liu, Yue; Liu, Liang; Li, Zongyu; Wang, Wanguo

Autonomous obstacle avoidance of unmanned aerial vehicle (hereinafter referred to as UAV) in electric power line inspection process has important significance for operation safety and economy for UAV intelligent inspection system of transmission line as main content of UAV intelligent inspection system on transmission line. In the paper, principles of UAV inspection obstacle avoidance technology of transmission line are introduced. UAV inspection obstacle avoidance technology based on particle swarm global optimization algorithm is proposed after common obstacle avoidance technologies are studied. Stimulation comparison is implemented with traditional UAV inspection obstacle avoidance technology which adopts artificial potential field method. Results show that UAV inspection strategy of particle swarm optimization algorithm, adopted in the paper, is prominently better than UAV inspection strategy of artificial potential field method in the aspects of obstacle avoidance effect and the ability of returning to preset inspection track after passing through the obstacle. An effective method is provided for UAV inspection obstacle avoidance of transmission line.

Satellite image processing for precision agriculture and agroindustry using convolutional neural network and genetic algorithm

NASA Astrophysics Data System (ADS)

Firdaus; Arkeman, Y.; Buono, A.; Hermadi, I.

2017-01-01

Translating satellite imagery to a useful data for decision making during this time are usually done manually by human. In this research, we are going to translate satellite imagery by using artificial intelligence method specifically using convolutional neural network and genetic algorithm to become a useful data for decision making, especially for precision agriculture and agroindustry. In this research, we are focused on how to made a sustainable land use planning with 3 objectives. The first is maximizing economic factor. Second is minimizing CO2 emission and the last is minimizing land degradation. Results show that by using artificial intelligence method, can produced a good pareto optimum solutions in a short time.

Space applications of artificial intelligence; 1990 Goddard Conference, Greenbelt, MD, May 1, 2, 1990, Selected Papers

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor)

1990-01-01

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

Research Needs for Artificial Intelligence Applications in Support of C3 (Command, Control, and Communication).

DTIC Science & Technology

1984-12-01

system. The reconstruction process is Simply data fusion after allA data are in. After reconstruction, artifcial intelligence (Al) techniques may be...14. CATE OF fhPM~TVW MWtvt Ogv It PAWE COMN Interim __100 -_ TO December 1984 24 MILD ON" s-o Artificial intelligence Command control Data fusion...RD-Ai5O 867 RESEARCH NEEDS FOR ARTIFICIAL INTELLIGENCE APPLICATIONS i/i IN SUPPORT OF C3 (..(U) NAVAL OCEAN SVSTEIIS CENTER SAN DIEGO CA R R DILLARD

A Cyber Situational Awareness Model for Network Administrators

DTIC Science & Technology

2017-03-01

environments, the Internet of Things, artificial intelligence , and so on. As users’ data requirements grow more complex, they demand information...security of systems of interest. Further, artificial intelligence is a powerful concept in information technology. Therefore, new research should...look into how to use artificial intelligence to develop CSA. Human interaction with cyber systems is not making networks and their components safer

The 1994 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Hostetter, Carl F. (Editor)

1994-01-01

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

Artificial Intelligence and Its Potential as an Aid to Vocational Training and Education.

ERIC Educational Resources Information Center

Aleksander, I.; And Others

This document contains a series of papers which attempt to de-mystify the subject of artificial intelligence and to show how some countries in the European Community (EC) are approaching the promotion of development and application of artificial intelligence systems that can be used as an aid in vocational training programs, as well as to…

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

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

The 1993 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Hostetter, Carl F. (Editor)

1993-01-01

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

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

Patient behavior and the benefits of artificial intelligence: the perils of "dangerous" literacy and illusory patient empowerment.

PubMed

Schulz, Peter J; Nakamoto, Kent

2013-08-01

Artificial intelligence can provide important support of patient health. However, limits to realized benefits can arise as patients assume an active role in their health decisions. Distinguishing the concepts of health literacy and patient empowerment, we analyze conditions that bias patient use of the Internet and limit access to and impact of artificial intelligence. Improving health literacy in the face of the Internet requires significant guidance. Patients must be directed toward the appropriate tools and also provided with key background knowledge enabling them to use the tools and capitalize on the artificial intelligence technology. Benefits of tools employing artificial intelligence to promote health cannot be realized without recognizing and addressing the patients' desires, expectations, and limitations that impact their Internet behavior. In order to benefit from artificial intelligence, patients need a substantial level of background knowledge and skill in information use-i.e., health literacy. It is critical that health professionals respond to patient search for information on the Internet, first by guiding their search to relevant, authoritative, and responsive sources, and second by educating patients about how to interpret the information they are likely to encounter. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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

ERIC Educational Resources Information Center

Yaratan, Huseyin

2003-01-01

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

STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

DTIC Science & Technology

ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

Advanced training systems

NASA Technical Reports Server (NTRS)

Savely, Robert T.; Loftin, R. Bowen

1990-01-01

Training is a major endeavor in all modern societies. Common training methods include training manuals, formal classes, procedural computer programs, simulations, and on-the-job training. NASA's training approach has focussed primarily on on-the-job training in a simulation environment for both crew and ground based personnel. NASA must explore new approaches to training for the 1990's and beyond. Specific autonomous training systems are described which are based on artificial intelligence technology for use by NASA astronauts, flight controllers, and ground based support personnel that show an alternative to current training systems. In addition to these specific systems, the evolution of a general architecture for autonomous intelligent training systems that integrates many of the features of traditional training programs with artificial intelligence techniques is presented. These Intelligent Computer Aided Training (ICAT) systems would provide much of the same experience that could be gained from the best on-the-job training.

A new modelling approach for zooplankton behaviour

NASA Astrophysics Data System (ADS)

Keiyu, A. Y.; Yamazaki, H.; Strickler, J. R.

We have developed a new simulation technique to model zooplankton behaviour. The approach utilizes neither the conventional artificial intelligence nor neural network methods. We have designed an adaptive behaviour network, which is similar to BEER [(1990) Intelligence as an adaptive behaviour: an experiment in computational neuroethology, Academic Press], based on observational studies of zooplankton behaviour. The proposed method is compared with non- "intelligent" models—random walk and correlated walk models—as well as observed behaviour in a laboratory tank. Although the network is simple, the model exhibits rich behavioural patterns similar to live copepods.

An Intelligent Approach to Educational Data: Performance Comparison of the Multilayer Perceptron and the Radial Basis Function Artificial Neural Networks

ERIC Educational Resources Information Center

Kayri, Murat

2015-01-01

The objective of this study is twofold: (1) to investigate the factors that affect the success of university students by employing two artificial neural network methods (i.e., multilayer perceptron [MLP] and radial basis function [RBF]); and (2) to compare the effects of these methods on educational data in terms of predictive ability. The…

Spontaneous Analogy by Piggybacking on a Perceptual System

DTIC Science & Technology

2013-08-01

1992). High-level Perception, Representation, and Analogy: A Critique of Artificial Intelligence Methodology. J. Exp. Theor. Artif . Intell., 4(3...nrl.navy.mil David W. Aha Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory (Code 5510); Washington, DC 20375 david.aha...Research Laboratory,Center for Applied Research in Artificial Intelligence (Code 5510),4555 Overlook Ave., SW,Washington,DC,20375 8. PERFORMING ORGANIZATION

Circumscribing Circumscription. A Guide to Relevance and Incompleteness,

DTIC Science & Technology

1985-10-01

other rules of conjecture, to account for resource limitations. P "- h’ MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo...of conjecture, to account for resource limitations. This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts...Institute of Technology. Support for the laboratory’s artificial intelligence research is provided in part by the Advanced Research Projects Agency

Why the United States Must Adopt Lethal Autonomous Weapon Systems

DTIC Science & Technology

2017-05-25

2017. http://www.designboom.com/ technology /designboom-tech-predictions-robotics-12-26- 2016/. Egan, Matt. "Robots Write Thousands Of News Stories A...views on the morality of artificial intelligence (AI) and robotics technology . Eastern culture sees artificial intelligence as an economic savior...Army, 37 pages. The East and West have differing views on the morality of artificial intelligence (AI) and robotics technology . Eastern culture

Artificial Intelligence-Based Student Learning Evaluation: A Concept Map-Based Approach for Analyzing a Student's Understanding of a Topic

ERIC Educational Resources Information Center

Jain, G. Panka; Gurupur, Varadraj P.; Schroeder, Jennifer L.; Faulkenberry, Eileen D.

2014-01-01

In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of…

An Intelligence Collection Management Model.

DTIC Science & Technology

1984-06-01

classification of inteligence collection requirements in terms of. the a-.- metnodo"c, .ev--e in Chaster Five. 116 APPgENDIX A A METHOD OF RANKING...of Artificial Intelligence Tools and Technigues to!TN’X n~l is n rs aa~emfft-.3-ufnyva: ’A TZ Ashby W. Ecss. An Introduction to Cybernetics. New York

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

NASA Astrophysics Data System (ADS)

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

2013-10-01

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

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

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

PubMed Central

2015-01-01

Summary The first generation of Artificial Intelligence (AI) in Medicine methods were developed in the early 1970’s drawing on insights about problem solving in AI. They developed new ways of representing structured expert knowledge about clinical and biomedical problems using causal, taxonomic, associational, rule, and frame-based models. By 1975, several prototype systems had been developed and clinically tested, and the Rutgers Research Resource on Computers in Biomedicine hosted the first in a series of workshops on AI in Medicine that helped researchers and clinicians share their ideas, demonstrate their models, and comment on the prospects for the field. These developments and the workshops themselves benefited considerably from Stanford’s SUMEX-AIM pioneering experiment in biomedical computer networking. This paper focuses on discussions about issues at the intersection of medicine and artificial intelligence that took place during the presentations and panels at the First Rutgers AIM Workshop in New Brunswick, New Jersey from June 14 to 17, 1975. PMID:26123911

Artificial intelligence-assisted occupational lung disease diagnosis.

PubMed

Harber, P; McCoy, J M; Howard, K; Greer, D; Luo, J

1991-08-01

An artificial intelligence expert-based system for facilitating the clinical recognition of occupational and environmental factors in lung disease has been developed in a pilot fashion. It utilizes a knowledge representation scheme to capture relevant clinical knowledge into structures about specific objects (jobs, diseases, etc) and pairwise relations between objects. Quantifiers describe both the closeness of association and risk, as well as the degree of belief in the validity of a fact. An independent inference engine utilizes the knowledge, combining likelihoods and uncertainties to achieve estimates of likelihood factors for specific paths from work to illness. The system creates a series of "paths," linking work activities to disease outcomes. One path links a single period of work to a single possible disease outcome. In a preliminary trial, the number of "paths" from job to possible disease averaged 18 per subject in a general population and averaged 25 per subject in an asthmatic population. Artificial intelligence methods hold promise in the future to facilitate diagnosis in pulmonary and occupational medicine.

De Novo Design of Bioactive Small Molecules by Artificial Intelligence.

PubMed

Merk, Daniel; Friedrich, Lukas; Grisoni, Francesca; Schneider, Gisbert

2018-01-01

Generative artificial intelligence offers a fresh view on molecular design. We present the first-time prospective application of a deep learning model for designing new druglike compounds with desired activities. For this purpose, we trained a recurrent neural network to capture the constitution of a large set of known bioactive compounds represented as SMILES strings. By transfer learning, this general model was fine-tuned on recognizing retinoid X and peroxisome proliferator-activated receptor agonists. We synthesized five top-ranking compounds designed by the generative model. Four of the compounds revealed nanomolar to low-micromolar receptor modulatory activity in cell-based assays. Apparently, the computational model intrinsically captured relevant chemical and biological knowledge without the need for explicit rules. The results of this study advocate generative artificial intelligence for prospective de novo molecular design, and demonstrate the potential of these methods for future medicinal chemistry. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Predicting asthma exacerbations using artificial intelligence.

PubMed

Finkelstein, Joseph; Wood, Jeffrey

2013-01-01

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

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

PubMed

Kulikowski, C A

2015-08-13

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

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

PubMed

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

2015-06-01

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

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.

How artificial intelligence tools can be used to assess individual patient risk in cardiovascular disease: problems with the current methods.

PubMed

Grossi, Enzo

2006-05-03

In recent years a number of algorithms for cardiovascular risk assessment has been proposed to the medical community. These algorithms consider a number of variables and express their results as the percentage risk of developing a major fatal or non-fatal cardiovascular event in the following 10 to 20 years The author has identified three major pitfalls of these algorithms, linked to the limitation of the classical statistical approach in dealing with this kind of non linear and complex information. The pitfalls are the inability to capture the disease complexity, the inability to capture process dynamics, and the wide confidence interval of individual risk assessment. Artificial Intelligence tools can provide potential advantage in trying to overcome these limitations. The theoretical background and some application examples related to artificial neural networks and fuzzy logic have been reviewed and discussed. The use of predictive algorithms to assess individual absolute risk of cardiovascular future events is currently hampered by methodological and mathematical flaws. The use of newer approaches, such as fuzzy logic and artificial neural networks, linked to artificial intelligence, seems to better address both the challenge of increasing complexity resulting from a correlation between predisposing factors, data on the occurrence of cardiovascular events, and the prediction of future events on an individual level.

Applications of Some Artificial Intelligence Methods to Satellite Soundings

NASA Technical Reports Server (NTRS)

Munteanu, M. J.; Jakubowicz, O.

1985-01-01

Hard clustering of temperature profiles and regression temperature retrievals were used to refine the method using the probabilities of membership of each pattern vector in each of the clusters derived with discriminant analysis. In hard clustering the maximum probability is taken and the corresponding cluster as the correct cluster are considered discarding the rest of the probabilities. In fuzzy partitioned clustering these probabilities are kept and the final regression retrieval is a weighted regression retrieval of several clusters. This method was used in the clustering of brightness temperatures where the purpose was to predict tropopause height. A further refinement is the division of temperature profiles into three major regions for classification purposes. The results are summarized in the tables total r.m.s. errors are displayed. An approach based on fuzzy logic which is intimately related to artificial intelligence methods is recommended.

Estimation of mechanical properties of nanomaterials using artificial intelligence methods

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

Fourth Conference on Artificial Intelligence for Space Applications

NASA Technical Reports Server (NTRS)

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

1988-01-01

Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming.

Swarm intelligence in bioinformatics: methods and implementations for discovering patterns of multiple sequences.

PubMed

Cui, Zhihua; Zhang, Yi

2014-02-01

As a promising and innovative research field, bioinformatics has attracted increasing attention recently. Beneath the enormous number of open problems in this field, one fundamental issue is about the accurate and efficient computational methodology that can deal with tremendous amounts of data. In this paper, we survey some applications of swarm intelligence to discover patterns of multiple sequences. To provide a deep insight, ant colony optimization, particle swarm optimization, artificial bee colony and artificial fish swarm algorithm are selected, and their applications to multiple sequence alignment and motif detecting problem are discussed.

Artificial Intelligence in Autonomous Telescopes

NASA Astrophysics Data System (ADS)

Mahoney, William; Thanjavur, Karun

2011-03-01

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

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

DOT National Transportation Integrated Search

2002-10-01

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

Magnetron Sputtered Pulsed Laser Deposition Scale Up

DTIC Science & Technology

2003-08-14

2:721-726 34 S. J. P. Laube and E. F. Stark, “ Artificial Intellegence in Process Control of Pulsed Laser Deposition”, Proceedings of...The model would be based on mathematical simulation of real process data, neural-networks, or other artificial intelligence methods based on in situ...Laube and E. F. Stark, Proc. Symp. Artificial Intel. Real Time Control, Valencia, Spain, 3-5 Oct. ,1994, p.159-163. International Federation of

Facts and fiction of learning systems. [decision making intelligent control

NASA Technical Reports Server (NTRS)

Saridis, G. N.

1975-01-01

The methodology that will provide the updated precision for the hardware control and the advanced decision making and planning in the software control is called learning systems and intelligent control. It was developed theoretically as an alternative for the nonsystematic heuristic approaches of artificial intelligence experiments and the inflexible formulation of modern optimal control methods. Its basic concepts are discussed and some feasibility studies of some practical applications are presented.

Simulating the Mind

NASA Astrophysics Data System (ADS)

Dietrich, Dietmar; Fodor, Georg; Zucker, Gerhard; Bruckner, Dietmar

The approach to developing models described within the following chapters breaks with some of the previously used approaches in Artificial Intelligence. This is the first attempt to use methods from psychoanalysis organized in a strictly topdown design method in order to take an important step towards the creation of intelligent systems. Hence, the vision and the research hypothesis are described in the beginning and will hopefully prove to have sufficient grounds for this approach.

Niépce-Bell or Turing: how to test odour reproduction.

PubMed

Harel, David

2016-12-01

Decades before the existence of anything resembling an artificial intelligence system, Alan Turing raised the question of how to test whether machines can think, or, in modern terminology, whether a computer claimed to exhibit intelligence indeed does so. This paper raises the analogous issue for olfaction: how to test the validity of a system claimed to reproduce arbitrary odours artificially, in a way recognizable to humans. Although odour reproduction systems are still far from being viable, the question of how to test candidates thereof is claimed to be interesting and non-trivial, and a novel method is proposed. Despite the similarity between the two questions and their surfacing long before the tested systems exist, the present question cannot be answered adequately by a Turing-like method. Instead, our test is very different: it is conditional, requiring from the artificial no more than is required from the original, and it employs a novel method of immersion that takes advantage of the availability of easily recognizable reproduction methods for sight and sound, a la Nicéphore Niépce and Alexander Graham Bell. © 2016 The Authors.

Niépce–Bell or Turing: how to test odour reproduction

PubMed Central

2016-01-01

Decades before the existence of anything resembling an artificial intelligence system, Alan Turing raised the question of how to test whether machines can think, or, in modern terminology, whether a computer claimed to exhibit intelligence indeed does so. This paper raises the analogous issue for olfaction: how to test the validity of a system claimed to reproduce arbitrary odours artificially, in a way recognizable to humans. Although odour reproduction systems are still far from being viable, the question of how to test candidates thereof is claimed to be interesting and non-trivial, and a novel method is proposed. Despite the similarity between the two questions and their surfacing long before the tested systems exist, the present question cannot be answered adequately by a Turing-like method. Instead, our test is very different: it is conditional, requiring from the artificial no more than is required from the original, and it employs a novel method of immersion that takes advantage of the availability of easily recognizable reproduction methods for sight and sound, a la Nicéphore Niépce and Alexander Graham Bell. PMID:28003527

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.

A Spoken English Recognition Expert System.

DTIC Science & Technology

1983-09-01

Davidson. "Representation of Knowledge," Handbook of Artificial Intelligence, edited by Avron Barr and Edward A. Felgenbaum. DTIC document number AD...Regents of the University of CalTorni, 1981. 9. Gardner, Anne. "Search," Handbook of Artificial Intelligence, edited by Avron Barr and Edward A...Felgenbaum, DTIC document number AD A074078, 1979. 10. Gardner, Anne,et al. "Natural Language Understanding," Handbook of Artificial Intelligence, edited

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

Strategic Computing. New-Generation Computing Technology: A Strategic Plan for Its Development and Application to Critical Problems in Defense

DTIC Science & Technology

1983-10-28

Computing. By seizing an opportunity to leverage recent advances in artificial intelligence, computer science, and microelectronics, the Agency plans...occurred in many separated areas of artificial intelligence, computer science, and microelectronics. Advances in "expert system" technology now...and expert knowledge o Advances in Artificial Intelligence: Mechanization of speech recognition, vision, and natural language understanding. o

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

NASA Technical Reports Server (NTRS)

Hostetter, Carl F. (Editor)

1995-01-01

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

Defense Information Systems Program Automated CORDIVEM Design Requirements,

DTIC Science & Technology

1984-02-28

for the Soviet military organization and equipment. Dr. John Spagnuolo incorporated artificial intelligence techniques in the discussion of functional...4-44 4.1.2.18.2 Artificial Intelligence ...... ........ 4-49 4.1.2.18.3 Types of A.I ................. 4-51 4.1.2.19 General Planning Requirements...described later. Further, some subprocesses may need one of the various techniques associated with the broad field of Artificial Intelligence (A.I.) in

A multi-assets artificial stock market with zero-intelligence traders

NASA Astrophysics Data System (ADS)

Ponta, L.; Raberto, M.; Cincotti, S.

2011-01-01

In this paper, a multi-assets artificial financial market populated by zero-intelligence traders with finite financial resources is presented. The market is characterized by different types of stocks representing firms operating in different sectors of the economy. Zero-intelligence traders follow a random allocation strategy which is constrained by finite resources, past market volatility and allocation universe. Within this framework, stock price processes exhibit volatility clustering, fat-tailed distribution of returns and reversion to the mean. Moreover, the cross-correlations between returns of different stocks are studied using methods of random matrix theory. The probability distribution of eigenvalues of the cross-correlation matrix shows the presence of outliers, similar to those recently observed on real data for business sectors. It is worth noting that business sectors have been recovered in our framework without dividends as only consequence of random restrictions on the allocation universe of zero-intelligence traders. Furthermore, in the presence of dividend-paying stocks and in the case of cash inflow added to the market, the artificial stock market points out the same structural results obtained in the simulation without dividends. These results suggest a significative structural influence on statistical properties of multi-assets stock market.

[The application and development of artificial intelligence in medical diagnosis systems].

PubMed

Chen, Zhencheng; Jiang, Yong; Xu, Mingyu; Wang, Hongyan; Jiang, Dazong

2002-09-01

This paper has reviewed the development of artificial intelligence in medical practice and medical diagnostic expert systems, and has summarized the application of artificial neural network. It explains that a source of difficulty in medical diagnostic system is the co-existence of multiple diseases--the potentially inter-related diseases. However, the difficulty of image expert systems is inherent in high-level vision. And it increases the complexity of expert system in medical image. At last, the prospect for the development of artificial intelligence in medical image expert systems is made.

Artificial intelligence in radiology.

PubMed

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

2018-05-17

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

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)

Deep into the Brain: Artificial Intelligence in Stroke Imaging

PubMed Central

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

2017-01-01

Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AI techniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives. PMID:29037014

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Deep into the Brain: Artificial Intelligence in Stroke Imaging.

PubMed

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

2017-09-01

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

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

PubMed

Miksztai-Réthey, Brigitta; Faragó, Kinga Bettina

2015-01-01

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

Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

PubMed

Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

PubMed Central

Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

Gene selection for microarray cancer classification using a new evolutionary method employing artificial intelligence concepts.

PubMed

Dashtban, M; Balafar, Mohammadali

2017-03-01

Gene selection is a demanding task for microarray data analysis. The diverse complexity of different cancers makes this issue still challenging. In this study, a novel evolutionary method based on genetic algorithms and artificial intelligence is proposed to identify predictive genes for cancer classification. A filter method was first applied to reduce the dimensionality of feature space followed by employing an integer-coded genetic algorithm with dynamic-length genotype, intelligent parameter settings, and modified operators. The algorithmic behaviors including convergence trends, mutation and crossover rate changes, and running time were studied, conceptually discussed, and shown to be coherent with literature findings. Two well-known filter methods, Laplacian and Fisher score, were examined considering similarities, the quality of selected genes, and their influences on the evolutionary approach. Several statistical tests concerning choice of classifier, choice of dataset, and choice of filter method were performed, and they revealed some significant differences between the performance of different classifiers and filter methods over datasets. The proposed method was benchmarked upon five popular high-dimensional cancer datasets; for each, top explored genes were reported. Comparing the experimental results with several state-of-the-art methods revealed that the proposed method outperforms previous methods in DLBCL dataset. Copyright © 2017 Elsevier Inc. All rights reserved.

Deploying an Intelligent Pairing Assistant for Air Operation Centers

DTIC Science & Technology

2016-06-23

primary contributions of this case study are applying artificial intelligence techniques to a novel domain and discussing the software evaluation...their standard workflows. The primary contributions of this case study are applying artificial intelligence techniques to a novel domain and...users for more efficient and accurate pairing? Participants Participants in the evaluation consisted of three SMEs employed at Intelligent Software

Northeast Artificial Intelligence Consortium Annual Report - 1988 Parallel Vision. Volume 9

DTIC Science & Technology

1989-10-01

supports the Northeast Aritificial Intelligence Consortium (NAIC). Volume 9 Parallel Vision Report submitted by Christopher M. Brown Randal C. Nelson...NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT - 1988 Parallel Vision Syracuse University Christopher M. Brown and Randal C. Nelson...Technical Director Directorate of Intelligence & Reconnaissance FOR THE COMMANDER: IGOR G. PLONISCH Directorate of Plans & Programs If your address has

Artificial intelligence approaches to astronomical observation scheduling

NASA Technical Reports Server (NTRS)

Johnston, Mark D.; Miller, Glenn

1988-01-01

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

Thutmose - Investigation of Machine Learning-Based Intrusion Detection Systems

DTIC Science & Technology

2016-06-01

research is being done to incorporate the field of machine learning into intrusion detection. Machine learning is a branch of artificial intelligence (AI...adversarial drift." Proceedings of the 2013 ACM workshop on Artificial intelligence and security. ACM. (2013) Kantarcioglu, M., Xi, B., and Clifton, C. "A...34 Proceedings of the 4th ACM workshop on Security and artificial intelligence . ACM. (2011) Dua, S., and Du, X. Data Mining and Machine Learning in

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.

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

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

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

NASA Astrophysics Data System (ADS)

Doaei, Marjan; Tavallali, M. Sadegh

2018-05-01

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

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.…

Expert Systems and Special Education.

ERIC Educational Resources Information Center

Hofmeister, Alan M.; Ferrara, Joseph M.

The application of artificial intelligence to the problems of education is examined. One of the most promising areas in artificial intelligence is expert systems technology which engages the user in a problem-solving diaglogue. Some of the characteristics that make expert systems "intelligent" are identified and exemplified. The rise of…

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

ERIC Educational Resources Information Center

Adams, Dennis M.; Hamm, Mary

1988-01-01

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

Artificial intelligence techniques for embryo and oocyte classification.

PubMed

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

2013-01-01

One of the most relevant aspects in assisted reproduction technology is the possibility of characterizing and identifying the most viable oocytes or embryos. In most cases, embryologists select them by visual examination and their evaluation is totally subjective. Recently, due to the rapid growth in the capacity to extract texture descriptors from a given image, a growing interest has been shown in the use of artificial intelligence methods for embryo or oocyte scoring/selection in IVF programmes. This work concentrates the efforts on the possible prediction of the quality of embryos and oocytes in order to improve the performance of assisted reproduction technology, starting from their images. The artificial intelligence system proposed in this work is based on a set of Levenberg-Marquardt neural networks trained using textural descriptors (the local binary patterns). The proposed system was tested on two data sets of 269 oocytes and 269 corresponding embryos from 104 women and compared with other machine learning methods already proposed in the past for similar classification problems. Although the results are only preliminary, they show an interesting classification performance. This technique may be of particular interest in those countries where legislation restricts embryo selection. One of the most relevant aspects in assisted reproduction technology is the possibility of characterizing and identifying the most viable oocytes or embryos. In most cases, embryologists select them by visual examination and their evaluation is totally subjective. Recently, due to the rapid growth in our capacity to extract texture descriptors from a given image, a growing interest has been shown in the use of artificial intelligence methods for embryo or oocyte scoring/selection in IVF programmes. In this work, we concentrate our efforts on the possible prediction of the quality of embryos and oocytes in order to improve the performance of assisted reproduction technology, starting from their images. The artificial intelligence system proposed in this work is based on a set of Levenberg-Marquardt neural networks trained using textural descriptors (the 'local binary patterns'). The proposed system is tested on two data sets, of 269 oocytes and 269 corresponding embryos from 104 women, and compared with other machine learning methods already proposed in the past for similar classification problems. Although the results are only preliminary, they showed an interesting classification performance. This technique may be of particular interest in those countries where legislation restricts embryo selection. Copyright © 2012 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Artificial Intelligence Estimation of Carotid-Femoral Pulse Wave Velocity using Carotid Waveform.

PubMed

Tavallali, Peyman; Razavi, Marianne; Pahlevan, Niema M

2018-01-17

In this article, we offer an artificial intelligence method to estimate the carotid-femoral Pulse Wave Velocity (PWV) non-invasively from one uncalibrated carotid waveform measured by tonometry and few routine clinical variables. Since the signal processing inputs to this machine learning algorithm are sensor agnostic, the presented method can accompany any medical instrument that provides a calibrated or uncalibrated carotid pressure waveform. Our results show that, for an unseen hold back test set population in the age range of 20 to 69, our model can estimate PWV with a Root-Mean-Square Error (RMSE) of 1.12 m/sec compared to the reference method. The results convey the fact that this model is a reliable surrogate of PWV. Our study also showed that estimated PWV was significantly associated with an increased risk of CVDs.

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

DTIC Science & Technology

1988-01-01

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

Artificial Neural Networks and Instructional Technology.

ERIC Educational Resources Information Center

Carlson, Patricia A.

1991-01-01

Artificial neural networks (ANN), part of artificial intelligence, are discussed. Such networks are fed sample cases (training sets), learn how to recognize patterns in the sample data, and use this experience in handling new cases. Two cognitive roles for ANNs (intelligent filters and spreading, associative memories) are examined. Prototypes…

Parallel Logic Programming Architecture

DTIC Science & Technology

1990-04-01

Section 3.1. 3.1. A STATIC ALLOCATION SCHEME (SAS) Methods that have been used for decomposing distributed problems in artificial intelligence...multiple agents, knowledge organization and allocation, and cooperative parallel execution. These difficulties are common to distributed artificial ...for the following reasons. First, intellegent backtracking requires much more bookkeeping and is therefore more costly during consult-time and during

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

ERIC Educational Resources Information Center

McCalla, Gordon I.

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

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.…

AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search

DTIC Science & Technology

1976-07-01

Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search by Douglas B. Len-t APPROVED FOR PUBLIC RELEASE; DISTRIBUTION IS UNLIMITED (A...570 AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search by Douglas B. Lenat ABSTRACT A program, called "AM", is...While AM’s " approach " to empirical research may be used in other scientific domains, the main limitation (reliance on hindsight) will probably recur

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…

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.

Center for Artificial Intelligence

DTIC Science & Technology

1992-03-14

builder’s intelligent assistant. The basic approach of IGOR is to integrate the complementary strategies of exploratory and confirmatory data analysis...Recovery: A Model and Experiments," in Proceedings of the Ninth National Conference on Artifcial Intelligence , Anaheim, CA, July 1991, pp. 801-808. Howe...Lehnert University of Massachusetts, Amherst, MAJ (413) 545-1322 Lessei•:s.umass.edu Title: Center for Artificial Intelligence Contract #: N00014-86-K

Artificial intelligence in diagnosis of obstructive lung disease: current status and future potential.

PubMed

Das, Nilakash; Topalovic, Marko; Janssens, Wim

2018-03-01

The application of artificial intelligence in the diagnosis of obstructive lung diseases is an exciting phenomenon. Artificial intelligence algorithms work by finding patterns in data obtained from diagnostic tests, which can be used to predict clinical outcomes or to detect obstructive phenotypes. The purpose of this review is to describe the latest trends and to discuss the future potential of artificial intelligence in the diagnosis of obstructive lung diseases. Machine learning has been successfully used in automated interpretation of pulmonary function tests for differential diagnosis of obstructive lung diseases. Deep learning models such as convolutional neural network are state-of-the art for obstructive pattern recognition in computed tomography. Machine learning has also been applied in other diagnostic approaches such as forced oscillation test, breath analysis, lung sound analysis and telemedicine with promising results in small-scale studies. Overall, the application of artificial intelligence has produced encouraging results in the diagnosis of obstructive lung diseases. However, large-scale studies are still required to validate current findings and to boost its adoption by the medical community.

Behavioral biometrics for verification and recognition of malicious software agents

NASA Astrophysics Data System (ADS)

Yampolskiy, Roman V.; Govindaraju, Venu

2008-04-01

Homeland security requires technologies capable of positive and reliable identification of humans for law enforcement, government, and commercial applications. As artificially intelligent agents improve in their abilities and become a part of our everyday life, the possibility of using such programs for undermining homeland security increases. Virtual assistants, shopping bots, and game playing programs are used daily by millions of people. We propose applying statistical behavior modeling techniques developed by us for recognition of humans to the identification and verification of intelligent and potentially malicious software agents. Our experimental results demonstrate feasibility of such methods for both artificial agent verification and even for recognition purposes.

The application of artificial intelligence technology to aeronautical system design

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Integrated human-machine intelligence in space systems.

PubMed

Boy, G A

1992-07-01

This paper presents an artificial intelligence approach to integrated human-machine intelligence in space systems. It discusses the motivations for Intelligent Assistant Systems in both nominal and abnormal situations. The problem of constructing procedures is shown to be a very critical issue. In particular, keeping procedural experience in both design and operation is critical. We suggest what artificial intelligence can offer in this direction. Some crucial problems induced by this approach are discussed in detail. Finally, we analyze the various roles that would be shared by both astronauts, ground operators, and the intelligent assistant system.

How artificial intelligence tools can be used to assess individual patient risk in cardiovascular disease: problems with the current methods

PubMed Central

Grossi, Enzo

2006-01-01

Background In recent years a number of algorithms for cardiovascular risk assessment has been proposed to the medical community. These algorithms consider a number of variables and express their results as the percentage risk of developing a major fatal or non-fatal cardiovascular event in the following 10 to 20 years Discussion The author has identified three major pitfalls of these algorithms, linked to the limitation of the classical statistical approach in dealing with this kind of non linear and complex information. The pitfalls are the inability to capture the disease complexity, the inability to capture process dynamics, and the wide confidence interval of individual risk assessment. Artificial Intelligence tools can provide potential advantage in trying to overcome these limitations. The theoretical background and some application examples related to artificial neural networks and fuzzy logic have been reviewed and discussed. Summary The use of predictive algorithms to assess individual absolute risk of cardiovascular future events is currently hampered by methodological and mathematical flaws. The use of newer approaches, such as fuzzy logic and artificial neural networks, linked to artificial intelligence, seems to better address both the challenge of increasing complexity resulting from a correlation between predisposing factors, data on the occurrence of cardiovascular events, and the prediction of future events on an individual level. PMID:16672045

Artificial intelligence: the clinician of the future.

PubMed

Gallagher, S M

2001-09-01

Human beings have long been fascinated with the idea of artificial intelligence. This fascination is fueled by popular films such as Stanley Kubrick's 2001: A Space Odyssey and Stephen Spielberg's recent film, AI. However intriguing artificial intelligence may be, Hubert and Spencer Dreyfus contend that qualities exist that are uniquely human--the qualities thought to be inaccessible to the computer "mind." Patricia Benner further investigated the qualities that guide clinicians in making decisions and assessments that are not entirely evidence-based or grounded in scientific data. Perhaps it is the intuitive nature of the human being that separates us from the machine. The state of artificial intelligence is described herein, along with a discussion of computerized clinical decision-making and the role of the human being in these decisions.

[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.

Toward Augmented Radiologists: Changes in Radiology Education in the Era of Machine Learning and Artificial Intelligence.

PubMed

Tajmir, Shahein H; Alkasab, Tarik K

2018-06-01

Radiology practice will be altered by the coming of artificial intelligence, and the process of learning in radiology will be similarly affected. In the short term, radiologists will need to understand the first wave of artificially intelligent tools, how they can help them improve their practice, and be able to effectively supervise their use. Radiology training programs will need to develop curricula to help trainees acquire the knowledge to carry out this new supervisory duty of radiologists. In the longer term, artificially intelligent software assistants could have a transformative effect on the training of residents and fellows, and offer new opportunities to bring learning into the ongoing practice of attending radiologists. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Bayesian Model Averaging of Artificial Intelligence Models for Hydraulic Conductivity Estimation

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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.

Role of artificial intelligence in the care of patients with nonsmall cell lung cancer.

PubMed

Rabbani, Mohamad; Kanevsky, Jonathan; Kafi, Kamran; Chandelier, Florent; Giles, Francis J

2018-04-01

Lung cancer is the leading cause of cancer death worldwide. In up to 57% of patients, it is diagnosed at an advanced stage and the 5-year survival rate ranges between 10%-16%. There has been a significant amount of research using machine learning to generate tools using patient data to improve outcomes. This narrative review is based on research material obtained from PubMed up to Nov 2017. The search terms include "artificial intelligence," "machine learning," "lung cancer," "Nonsmall Cell Lung Cancer (NSCLC)," "diagnosis" and "treatment." Recent studies support the use of computer-aided systems and the use of radiomic features to help diagnose lung cancer earlier. Other studies have looked at machine learning (ML) methods that offer prognostic tools to doctors and help them in choosing personalized treatment options for their patients based on molecular, genetics and histological features. Combining artificial intelligence approaches into health care may serve as a beneficial tool for patients with NSCLC, and this review outlines these benefits and current shortcomings throughout the continuum of care. We present a review of the various applications of ML methods in NSCLC as it relates to improving diagnosis, treatment and outcomes. © 2018 Stichting European Society for Clinical Investigation Journal Foundation.

Searching for Order Within Chaos: Complexity Theorys Implications to Intelligence Support During Joint Operational Planning

DTIC Science & Technology

2017-06-09

structures constantly arise in firefights and skirmishes on the battlefield. Source: Andrew Ilachinski, Artificial War: Multiagent- Based Simulation of...Alternative Methods of Analysis and Innovative Organizational Structures .” Conference, Rome, Italy March 31-April 2. ...Intelligence Analysis, Joint Operational Planning, Cellular Automata, Agent- Based Modeling 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18

Possible Conflicts, ARRs, and Conflicts

DTIC Science & Technology

2002-05-04

Fourteenth European Conference on Artificial Intelligence Inteligencia Artificial , 41-53, (2001). (ECAI 2000), pp. 136-140, Berlin, Germany, (2000). [31] B...introduced), or proach to model-based diagnosis within the Artificial Intelligence backward (when a discrepancy is found, such as in CAEN [2, 21], community... Artificial Intelli- Relations (ARRs for short), for fault detection and localization [34]. gence community (usually known as DX). It is a research

Artificial Intelligence and Expert Systems.

ERIC Educational Resources Information Center

Wilson, Harold O.; Burford, Anna Marie

1990-01-01

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

The Hospital of the Future. Megatrends, Driving Forces, Barriers to Implementation, Overarching Perspectives, Major Trends into the Future, Implications for TATRC And Specific Recommendations for Action

DTIC Science & Technology

2008-10-01

Healthcare Systems Will Be Those That Work With Data/Info In New Ways • Artificial Intelligence Will Come to the Fore o Effectively Acquire...Education • Artificial Intelligence Will Assist in o History and Physical Examination o Imaging Selection via algorithms o Test Selection via algorithms...medical language into a simulation model based upon artificial intelligence , and • the content verification and validation of the cognitive

Applications of artificial intelligence V; Proceedings of the Meeting, Orlando, FL, May 18-20, 1987

NASA Technical Reports Server (NTRS)

Gilmore, John F. (Editor)

1987-01-01

The papers contained in this volume focus on current trends in applications of artificial intelligence. Topics discussed include expert systems, image understanding, artificial intelligence tools, knowledge-based systems, heuristic systems, manufacturing applications, and image analysis. Papers are presented on expert system issues in automated, autonomous space vehicle rendezvous; traditional versus rule-based programming techniques; applications to the control of optional flight information; methodology for evaluating knowledge-based systems; and real-time advisory system for airborne early warning.

Color regeneration from reflective color sensor using an artificial intelligent technique.

PubMed

Saracoglu, Ömer Galip; Altural, Hayriye

2010-01-01

A low-cost optical sensor based on reflective color sensing is presented. Artificial neural network models are used to improve the color regeneration from the sensor signals. Analog voltages of the sensor are successfully converted to RGB colors. The artificial intelligent models presented in this work enable color regeneration from analog outputs of the color sensor. Besides, inverse modeling supported by an intelligent technique enables the sensor probe for use of a colorimetric sensor that relates color changes to analog voltages.

Challenges facing the distribution of an artificial-intelligence-based system for nursing.

PubMed

Evans, S

1985-04-01

The marketing and successful distribution of artificial-intelligence-based decision-support systems for nursing face special barriers and challenges. Issues that must be confronted arise particularly from the present culture of the nursing profession as well as the typical organizational structures in which nurses predominantly work. Generalizations in the literature based on the limited experience of physician-oriented artificial intelligence applications (predominantly in diagnosis and pharmacologic treatment) must be modified for applicability to other health professions.

AAAIC '88 - Aerospace Applications of Artificial Intelligence; Proceedings of the Fourth Annual Conference, Dayton, OH, Oct. 25-27, 1988. Volumes 1 2

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

Johnson, J.R.; Netrologic, Inc., San Diego, CA)

1988-01-01

Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks.

Artificial Intelligence: Threat or Boon to Radiologists?

PubMed

Recht, Michael; Bryan, R Nick

2017-11-01

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

Artificial Intelligence and Spacecraft Power Systems

NASA Technical Reports Server (NTRS)

Dugel-Whitehead, Norma R.

1997-01-01

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

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

PubMed

Liew, Charlene

2018-05-01

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

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

Parallel Algorithms for Computer Vision.

DTIC Science & Technology

1989-01-01

34 IEEE Tran. Pattern Ankyaij and Ma- Artifcial Intelligence , Tokyo, 1979. chine Intelligence , 6, 1984. Kirkpatrick, S., C.D. Gelatt, Jr. and M.P. Vecchi...MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB T P06010 JAN 89 ETL-0529 UNCLASSIFIED DACA76-85-C-0010 F.’G 12/1I N mommiimmmiiso...PoggioI Massachusetts Institute of Technology i Artificial Intelligence Laboratory 545 Technology Square Cambridge, Massachusetts 02139 DTIC January

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.

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

ERIC Educational Resources Information Center

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

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

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)

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…

Modeling of steam distillation mechanism during steam injection process using artificial intelligence.

PubMed

Daryasafar, Amin; Ahadi, Arash; Kharrat, Riyaz

2014-01-01

Steam distillation as one of the important mechanisms has a great role in oil recovery in thermal methods and so it is important to simulate this process experimentally and theoretically. In this work, the simulation of steam distillation is performed on sixteen sets of crude oil data found in the literature. Artificial intelligence (AI) tools such as artificial neural network (ANN) and also adaptive neurofuzzy interference system (ANFIS) are used in this study as effective methods to simulate the distillate recoveries of these sets of data. Thirteen sets of data were used to train the models and three sets were used to test the models. The developed models are highly compatible with respect to input oil properties and can predict the distillate yield with minimum entry. For showing the performance of the proposed models, simulation of steam distillation is also done using modified Peng-Robinson equation of state. Comparison between the calculated distillates by ANFIS and neural network models and also equation of state-based method indicates that the errors of the ANFIS model for training data and test data sets are lower than those of other methods.

Modeling of Steam Distillation Mechanism during Steam Injection Process Using Artificial Intelligence

PubMed Central

Ahadi, Arash; Kharrat, Riyaz

2014-01-01

Steam distillation as one of the important mechanisms has a great role in oil recovery in thermal methods and so it is important to simulate this process experimentally and theoretically. In this work, the simulation of steam distillation is performed on sixteen sets of crude oil data found in the literature. Artificial intelligence (AI) tools such as artificial neural network (ANN) and also adaptive neurofuzzy interference system (ANFIS) are used in this study as effective methods to simulate the distillate recoveries of these sets of data. Thirteen sets of data were used to train the models and three sets were used to test the models. The developed models are highly compatible with respect to input oil properties and can predict the distillate yield with minimum entry. For showing the performance of the proposed models, simulation of steam distillation is also done using modified Peng-Robinson equation of state. Comparison between the calculated distillates by ANFIS and neural network models and also equation of state-based method indicates that the errors of the ANFIS model for training data and test data sets are lower than those of other methods. PMID:24883365

The Method of Immersion the Problem of Comparing Technical Objects in an Expert Shell in the Class of Artificial Intelligence Algorithms

NASA Astrophysics Data System (ADS)

Sergey Vasilievich, Buharin; Aleksandr Vladimirovich, Melnikov; Svetlana Nikolaevna, Chernyaeva; Lyudmila Anatolievna, Korobova

2017-08-01

The method of dip of the underlying computational problem of comparing technical object in an expert shell in the class of data mining methods is examined. An example of using the proposed method is given.

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

Bibliography: Artificial Intelligence.

ERIC Educational Resources Information Center

Smith, Richard L.

1986-01-01

Annotates reference material on artificial intelligence, mostly at an introductory level, with applications to education and learning. Topics include: (1) programing languages; (2) expert systems; (3) language instruction; (4) tutoring systems; and (5) problem solving and reasoning. (JM)

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.

Artificial intelligence: A social spin on language analysis

NASA Astrophysics Data System (ADS)

Rosé, Carolyn Penstein

2017-05-01

Understanding the prevalence and impact of personal attacks in online discussions is challenging. A method that combines crowdsourcing and machine learning provides a way forward, but caveats must be considered.

Artificial intelligence in predicting bladder cancer outcome: a comparison of neuro-fuzzy modeling and artificial neural networks.

PubMed

Catto, James W F; Linkens, Derek A; Abbod, Maysam F; Chen, Minyou; Burton, Julian L; Feeley, Kenneth M; Hamdy, Freddie C

2003-09-15

New techniques for the prediction of tumor behavior are needed, because statistical analysis has a poor accuracy and is not applicable to the individual. Artificial intelligence (AI) may provide these suitable methods. Whereas artificial neural networks (ANN), the best-studied form of AI, have been used successfully, its hidden networks remain an obstacle to its acceptance. Neuro-fuzzy modeling (NFM), another AI method, has a transparent functional layer and is without many of the drawbacks of ANN. We have compared the predictive accuracies of NFM, ANN, and traditional statistical methods, for the behavior of bladder cancer. Experimental molecular biomarkers, including p53 and the mismatch repair proteins, and conventional clinicopathological data were studied in a cohort of 109 patients with bladder cancer. For all three of the methods, models were produced to predict the presence and timing of a tumor relapse. Both methods of AI predicted relapse with an accuracy ranging from 88% to 95%. This was superior to statistical methods (71-77%; P < 0.0006). NFM appeared better than ANN at predicting the timing of relapse (P = 0.073). The use of AI can accurately predict cancer behavior. NFM has a similar or superior predictive accuracy to ANN. However, unlike the impenetrable "black-box" of a neural network, the rules of NFM are transparent, enabling validation from clinical knowledge and the manipulation of input variables to allow exploratory predictions. This technique could be used widely in a variety of areas of medicine.

Simulation as an Engine of Physical Scene Understanding

DTIC Science & Technology

2013-11-05

critical to the origins of intelligence : Researchers in developmental psychology, language, animal cognition, and artificial intelligence (2–6) con- sider...implemented computationally in classic artificial intelligence systems (18–20). However, these systems have not attempted to engage with physical scene un...N00014-09-0124, N00014-07-1-0937, and 1015GNA126; by Qualcomm; and by Intelligence Advanced Research Project Activity Grant D10PC20023. 1. Marr D (1982

[Artificial intelligence in medicine: project of a mobile platform in an intelligent environment for the care of disabled and elderly people].

PubMed

Cortés, Ulises; Annicchiarico, Roberta; Campana, Fabio; Vázquez-Salceda, Javier; Urdiales, Cristina; Canãmero, Lola; López, Maite; Sánchez-Marrè, Miquel; Di Vincenzo, Sarah; Caltagirone, Carlo

2004-04-01

A project based on the integration of new technologies and artificial intelligence to develop a device--e-tool--for disabled patients and elderly people is presented. A mobile platform in intelligent environments (skilled-care facilities and home-care), controlled and managed by a multi-level architecture, is proposed to support patients and caregivers to increase self-dependency in activities of daily living.

A system for intelligent teleoperation research

NASA Technical Reports Server (NTRS)

Orlando, N. E.

1983-01-01

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

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

Decision-Making and the Interface between Human Intelligence and Artificial Intelligence. AIR 1987 Annual Forum Paper.

ERIC Educational Resources Information Center

Henard, Ralph E.

Possible future developments in artificial intelligence (AI) as well as its limitations are considered that have implications for institutional research in higher education, and especially decision making and decision support systems. It is noted that computer software programs have been developed that store knowledge and mimic the decision-making…

Experiments in Knowledge Refinement for a Large Rule-Based System

DTIC Science & Technology

1993-08-01

empirical analysis to refine expert system knowledge bases. Aritificial Intelligence , 22:23-48, 1984. *! ...The Addison- Weslev series in artificial intelligence . Addison-Weslev. Reading, Massachusetts. 1981. Cooke, 1991: ttoger M. Cooke. Experts in...ment for classification systems. Artificial Intelligence , 35:197-226, 1988. 14 Overall, we believe that it will be possible to build a heuristic system

The Potential Role of Artificial Intelligence Technology in Education.

ERIC Educational Resources Information Center

Salem, Abdel-Badeeh M.

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

Demonstration of artificial intelligence technology for transit railcar diagnostics

DOT National Transportation Integrated Search

1999-01-01

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

Software Reviews. PC Software for Artificial Intelligence Applications.

ERIC Educational Resources Information Center

Epp, Helmut; And Others

1988-01-01

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

Artificial Intelligence Assists Ultrasonic Inspection

NASA Technical Reports Server (NTRS)

Schaefer, Lloyd A.; Willenberg, James D.

1992-01-01

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

In vitro and in vivo assessment of an intelligent artificial anal sphincter in rabbits.

PubMed

Huang, Zong-Hai; Shi, Fu-Jun; Chen, Fei; Liang, Fei-Xue; Li, Qiang; Yu, Jin-Long; Li, Zhou; Han, Xin-Jun

2011-10-01

Artificial sphincters have been developed for patients with fecal incontinence, but finding a way to make such sphincters more "intelligent" remains a problem. We assessed the function of a novel intelligent artificial anal sphincter (IAAS) in vitro and in vivo in rabbits. After the prosthesis was activated, rabbits were continent of feces during 81.4% of the activation time. The fecal detection unit provided 100% correct signals on stool in vitro and 65.7% in vivo. The results indicated that the IAAS could efficiently maintain continence and detect stool; however, the IAAS is still in the preliminary experimental stage and more work is needed to improve the system. © 2011, Copyright the Authors. Artificial Organs © 2011, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Modeling and Evaluating Emotions Impact on Cognition

DTIC Science & Technology

2013-07-01

Causality and Responsibility Judgment in Multi-Agent Interactions: Extended abstract. 23rd International Joint Conference on Artificial Inteligence ...responsibility judgment in multi-agent interactions." Journal of Artificial Intelligence Research v44(1), 223- 273. • Morteza Dehghani, Jonathan Gratch... Artificial Intelligence (AAAI’11). Grant related invited talks: • Keynote speaker, Workshop on Empathic and Emotional Agents at the International

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

Modelling intelligent behavior

NASA Technical Reports Server (NTRS)

Green, H. S.; Triffet, T.

1993-01-01

An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.

i-SAIRAS '90; Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space, Kobe, Japan, Nov. 18-20, 1990

NASA Technical Reports Server (NTRS)

1990-01-01

The present conference on artificial intelligence (AI), robotics, and automation in space encompasses robot systems, lunar and planetary robots, advanced processing, expert systems, knowledge bases, issues of operation and management, manipulator control, and on-orbit service. Specific issues addressed include fundamental research in AI at NASA, the FTS dexterous telerobot, a target-capture experiment by a free-flying robot, the NASA Planetary Rover Program, the Katydid system for compiling KEE applications to Ada, and speech recognition for robots. Also addressed are a knowledge base for real-time diagnosis, a pilot-in-the-loop simulation of an orbital docking maneuver, intelligent perturbation algorithms for space scheduling optimization, a fuzzy control method for a space manipulator system, hyperredundant manipulator applications, robotic servicing of EOS instruments, and a summary of astronaut inputs on automation and robotics for the Space Station Freedom.

The 1988 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

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

NASA Technical Reports Server (NTRS)

Culbert, C.

1985-01-01

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

Abstraction and reformulation in artificial intelligence.

PubMed Central

Holte, Robert C.; Choueiry, Berthe Y.

2003-01-01

This paper contributes in two ways to the aims of this special issue on abstraction. The first is to show that there are compelling reasons motivating the use of abstraction in the purely computational realm of artificial intelligence. The second is to contribute to the overall discussion of the nature of abstraction by providing examples of the abstraction processes currently used in artificial intelligence. Although each type of abstraction is specific to a somewhat narrow context, it is hoped that collectively they illustrate the richness and variety of abstraction in its fullest sense. PMID:12903653

Abstraction and reformulation in artificial intelligence.

PubMed

Holte, Robert C; Choueiry, Berthe Y

2003-07-29

This paper contributes in two ways to the aims of this special issue on abstraction. The first is to show that there are compelling reasons motivating the use of abstraction in the purely computational realm of artificial intelligence. The second is to contribute to the overall discussion of the nature of abstraction by providing examples of the abstraction processes currently used in artificial intelligence. Although each type of abstraction is specific to a somewhat narrow context, it is hoped that collectively they illustrate the richness and variety of abstraction in its fullest sense.

AAAI (American Association on Artificial Intelligence) Workshop on AI (Artificial Intelligence) Simulation Held in Philadelphia, Pennsylvania on August 11, 1986,

DTIC Science & Technology

1986-08-01

is then applied in i ABSTRCT : ,.:,.vu knowledge acquisition from those multiple sources for a specific design, for example, an expert system for...67. N 181.1 47.U3 a75 269;9.6 % A. %3 3 Genetic Explanations: For the concept of a genetic explanation (see .d -. above) to apply to the Gaither...Simulation Research Unit (Acock,1985; Baker,1983; Baker,1985). -. MD’,EX srves as an inner shell for apPlying Artificial Intelligence and E:pert System

Integrated Artificial Intelligence Approaches for Disease Diagnostics.

PubMed

Vashistha, Rajat; Chhabra, Deepak; Shukla, Pratyoosh

2018-06-01

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

Artificial intelligence in cardiology.

PubMed

Bonderman, Diana

2017-12-01

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

CI Controls for Energy and Environment

NASA Technical Reports Server (NTRS)

Biondo, Samuel J.

1996-01-01

Computational intelligence (CI) is a rapidly evolving field that utilizes life imitating metaphors for guiding model building including, but not limited to neural networks, fuzzy logic, genetic algorithms, artificial life, and hybrid CI paradigms. Although the boundaries between artificial intelligence (AI) and CI are not distinct, their research communities are separate and distinct. CI researchers tend to focus on processing numerical data from sensors, while the AI community generally relies on symbolic computing to capture human knowledge. In both areas, there is a great deal of interest and activity in hybrid systems that can offset the limitations of individual methods, extend their capabilities, and create new capabilities. Examples of the benefits that can accrue from hybrid systems are contained.

Rule based artificial intelligence expert system for determination of upper extremity impairment rating.

PubMed

Lim, I; Walkup, R K; Vannier, M W

1993-04-01

Quantitative evaluation of upper extremity impairment, a percentage rating most often determined using a rule based procedure, has been implemented on a personal computer using an artificial intelligence, rule-based expert system (AI system). In this study, the rules given in Chapter 3 of the AMA Guides to the Evaluation of Permanent Impairment (Third Edition) were used to develop such an AI system for the Apple Macintosh. The program applies the rules from the Guides in a consistent and systematic fashion. It is faster and less error-prone than the manual method, and the results have a higher degree of precision, since intermediate values are not truncated.

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.

Artificial Intelligence Support for Computational Chemistry

NASA Astrophysics Data System (ADS)

Duch, Wlodzislaw

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

What Artificial Intelligence Is Doing for Training.

ERIC Educational Resources Information Center

Kirrane, Peter R.; Kirrane, Diane E.

1989-01-01

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

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.

The coming of age of artificial intelligence in medicine.

PubMed

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

2009-05-01

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

Tuberculosis control, and the where and why of artificial intelligence

PubMed Central

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

2017-01-01

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

The Coming of Age of Artificial Intelligence in Medicine*

PubMed Central

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

2009-01-01

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

A review of European applications of artificial intelligence to space

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

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

PubMed

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

2017-04-01

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

Qualitative and Quantitative Proofs of Security Properties

DTIC Science & Technology

2013-04-01

Naples, Italy (September 2012) – Australasian Joint Conference on Artifical Intelligence (December 2012). • Causality, Responsibility, and Blame...realistic solution concept, Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI 2009), 2009, pp. 153–158. 17. J...Conference on Artificial Intelligence (AAAI-12), 2012, pp. 1917-1923. 29. J. Y. Halpern and S. Leung, Weighted sets of probabilities and minimax

Bibliography of Research in Natural Language Generation

DTIC Science & Technology

1993-11-01

on 1397] Barbara J. Gross Focuing and description in Artifcial Intelligence (GWAI-88), Geseke, West natural language dialogues, In Joshi et al. (557...Proceedings of the Fifth Canadian Conference from information in a frame structure. Data and on Artificial Intelligence , pages Ŕ-24, London, Knowledge...generation workshops (IWNLGS, ENLGWS), natural language processing conferences (ANLP, TINLAP, SPEECH), artificial intelligence conferences (AAAI, SCA

High-Level Connectionist Models

DTIC Science & Technology

1993-04-01

The Ohio State University, Columbus Ohio. To appearto Artifcial Life IlL Angeline, P., Saunders, G., Pollack, J. (1993). An evolutionary algorithm...of Robotics and Automation, 2(1):14-23. Brooks, R. A. (1991). Intelligence without representations. Artificial Intelligence , 47:139- 159. Connell, J. H...1990). Minimalist Mobile Robotics: A Colony-style Architecture for an Creature, Volume 5 of Perspectives in Artificial Intelligence . Academic Press

Repairing Learned Knowledge Using Experience

DTIC Science & Technology

1990-05-01

34 Artifcial Intelligence Journal, vol. 19, no. 3. Winston, Patrick Henry (1984], Artificial Intelligence , Second Edition, Addison-Wesley. Analogical...process speeds up future problem solving, but the scope of the learni ng- augmented theory remains unchanged. In con- (continued on back) PD D J7 1473...Distribution/ Avaiability Codes Avail and/or .Dist Special MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 1231

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

Robot Programming.

DTIC Science & Technology

1982-12-01

Paris, France, June, 1982, 519-530. Latoinbe, J. C. "Equipe Intelligence Artificielle et Robotique: Etat d’avancement des recherches," Laboratoire...8217AD-A127 233 ROBOT PROGRRMMING(U) MASSACHUSETTS INST OFGTECHi/ CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB T LOZANO-PEREZ UNCLASSIFIED DC8 AI-9 N884...NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA I WORK UNIT NUMBERS ,. 545 Technology Square Cambridge

Artificial intelligence applications in the intensive care unit.

PubMed

Hanson, C W; Marshall, B E

2001-02-01

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

Launch vehicle operations cost reduction through artificial intelligence techniques

NASA Technical Reports Server (NTRS)

Davis, Tom C., Jr.

1988-01-01

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

Toward a Theory of Representation Design

DTIC Science & Technology

1989-05-01

understanding. This report describes research done at the Artificial Inteligence Laboratory of the Massachusetts Institute of Technology. Support for this...AD-A210 885 Technical Report 1128 Toward a Theory of Representation Design Jeffrey Van Baale MIT Artificial Intelligence Laboratory DTIC ELECTE A... Artificial Intelligence Laboratory 545 Technology Square Cambridge, MA 02139 11. CONTROLLING OFFICE NAME AND ADDRESS 11. REPORT DATE Advanced Research

Supporting Organizational Problem Solving with a Workstation.

DTIC Science & Technology

1982-07-01

G. [., and Sussman, G. J. AMORD: Explicit Control or Reasoning. In Proceedings of the Symposium on Artificial Intellignece and Programming Languagues...0505 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA& WORK UNIT NUMBERS 545...extending ideas from the field of Artificial Intelligence (A), we describ office work as a problem solving activity. A knowledge embedding language called

Third Conference on Artificial Intelligence for Space Applications, part 1

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

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

Artificial Intelligence Techniques for Automatic Screening of Amblyogenic Factors

PubMed Central

Van Eenwyk, Jonathan; Agah, Arvin; Giangiacomo, Joseph; Cibis, Gerhard

2008-01-01

Purpose To develop a low-cost automated video system to effectively screen children aged 6 months to 6 years for amblyogenic factors. Methods In 1994 one of the authors (G.C.) described video vision development assessment, a digitizable analog video-based system combining Brückner pupil red reflex imaging and eccentric photorefraction to screen young children for amblyogenic factors. The images were analyzed manually with this system. We automated the capture of digital video frames and pupil images and applied computer vision and artificial intelligence to analyze and interpret results. The artificial intelligence systems were evaluated by a tenfold testing method. Results The best system was the decision tree learning approach, which had an accuracy of 77%, compared to the “gold standard” specialist examination with a “refer/do not refer” decision. Criteria for referral were strabismus, including microtropia, and refractive errors and anisometropia considered to be amblyogenic. Eighty-two percent of strabismic individuals were correctly identified. High refractive errors were also correctly identified and referred 90% of the time, as well as significant anisometropia. The program was less correct in identifying more moderate refractive errors, below +5 and less than −7. Conclusions Although we are pursuing a variety of avenues to improve the accuracy of the automated analysis, the program in its present form provides acceptable cost benefits for detecting ambylogenic factors in children aged 6 months to 6 years. PMID:19277222

Automatic Generation of Mechanical Assembly Sequences

DTIC Science & Technology

1988-12-01

Planning Algorithm for General Robot Manipulators. In AAAI-86 Proceedings of the F~th National Conference on Artifcial Intelligence , pages 626-631...topic in artificial intelligence , and the Al approach has dominated much of the research in robot task planning using domain-independent methods. The...computed, using the data in the relational model: " The GEOMETRIC-FEASIBILITY predicate which is true if there exists a collision-free path to bring the two

Intelligent reservoir operation system based on evolving artificial neural networks

NASA Astrophysics Data System (ADS)

Chaves, Paulo; Chang, Fi-John

2008-06-01

We propose a novel intelligent reservoir operation system based on an evolving artificial neural network (ANN). Evolving means the parameters of the ANN model are identified by the GA evolutionary optimization technique. Accordingly, the ANN model should represent the operational strategies of reservoir operation. The main advantages of the Evolving ANN Intelligent System (ENNIS) are as follows: (i) only a small number of parameters to be optimized even for long optimization horizons, (ii) easy to handle multiple decision variables, and (iii) the straightforward combination of the operation model with other prediction models. The developed intelligent system was applied to the operation of the Shihmen Reservoir in North Taiwan, to investigate its applicability and practicability. The proposed method is first built to a simple formulation for the operation of the Shihmen Reservoir, with single objective and single decision. Its results were compared to those obtained by dynamic programming. The constructed network proved to be a good operational strategy. The method was then built and applied to the reservoir with multiple (five) decision variables. The results demonstrated that the developed evolving neural networks improved the operation performance of the reservoir when compared to its current operational strategy. The system was capable of successfully simultaneously handling various decision variables and provided reasonable and suitable decisions.

Autonomous and Connected Vehicles: A Law Enforcement Primer

DTIC Science & Technology

2015-12-01

CYBERSECURITY FOR AUTOMOBILES Intelligent Transportation Systems (ITS) that are emerging around the globe achieve that classification based on the convergence...Car Works,” October 18, 2011, IEEE Spectrum, http://spectrum.ieee.org/automaton/robotics/ artificial - intelligence /how-google-self-driving-car-works...whereby artificial intelligence acts on behalf of a human, but carries the same life or death consequences.435 States should encourage and engage in

Complexity, Heuristic, and Search Analysis for the Games of Crossings and Epaminondas

DTIC Science & Technology

2014-03-27

research in Artifical Intelligence (Section 2.1) and why games are studied (Section 2.2). Section 2.3 discusses how games are played and solved. An...5 2.1 Games in Artificial Intelligence . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Game Study...Artificial Intelligence UCT Upper Confidence Bounds applied to Trees HUCT Heuristic Guided UCT LOA Lines of Action UCB Upper Confidence Bound RAVE Rapid

Ontological Engineering and Mapping in Multiagent Systems Development

DTIC Science & Technology

2002-03-01

for knowledge engineering or artificial intelligence . Nicola Guarino compares the various definitions and the differences in their meaning in...act upon the environment through effectors [Russel and Norvig 1995]. An intelligent agent is an agent that takes the best possible action in a...situation in order to accomplish its goals. Determining what exactly characterizes the best possible action splits the field of artificial intelligence

Communication and Attitude Revision

DTIC Science & Technology

1992-01-01

Conference on Aritificial Intelligence , (1989) 1074- 1079 3. Clark, H., Marshal, C.: Definite reference and mutual knowledge. In Joshi, A., Sag, I.. and...21st Annual Meeting of the ACL (1983) 57-63 9. Konolige, K.: On the relation between default and autoepistemic logic. Artificial Intelligence 35(3...reasoning. Artificial Intelligence 13 (1980) 81-132 16. Richmond Thomason. Accommodation, meaning, and implicature. In Cohen, P., Morgan, J., and

Knowledge Based Consultation for Finite Element Structural Analysis.

DTIC Science & Technology

1980-05-01

Intelligence Finite Element Program Tutorial 20 ABSTRACT (Continue. on rees side If necessary and ide.n’ty b,’ bit,, k nionh.) In recent years, techniques of...involved in Artificial Intelligence at Stanford University developed the program MYCIN F2], for clinical consultation of diseases that require...and Rules The basic backward chaining logic, characteristic to Artificial Intelligence . approaching 1he problem of knowledge representation was

Distribution Planning: An Integration of Constraint Satisfaction & Heuristic Search Techniques

DTIC Science & Technology

1990-01-01

Proceedings of the Symposium on Aritificial Intelligence in ~~litary Logistics, Arlington, VA: American Defense Preparedness Assoc. pp. 177-182...dynamic changes, too many variables, and lack pf planning time. The Human Engineeri n ~ Laboratory (HEL) is developing artificial intelligence (AI...first attempt. The field of artificial intelligence includes a variety of knowledge-based approaches. Most widely known are Expert Systems, that are

Coordination in Distributed Intelligent Systems Applications

DTIC Science & Technology

2009-12-13

working in the area of Distributed Artificial Intelligence (DAI) unanimously endorses the idea that coordination - a fundamental paradigm - represents a...using the distributed artificial intelligence paradigm. Section 4 discusses the healthcare applications. On the other hand, Section 5 describes...coordination mechanisms should be used is in the control of swarms of UA Vs (unmanned aerial vehicles). The UAVs are considered in this case as highly mobile

Parallel Logic Programming and Parallel Systems Software and Hardware

DTIC Science & Technology

1989-07-29

Conference, Dallas TX. January 1985. (55) [Rous75] Roussel, P., "PROLOG: Manuel de Reference et d’Uilisation", Group d’ Intelligence Artificielle , Universite d...completed. Tools were provided for software development using artificial intelligence techniques. Al software for massively parallel architectures was...using artificial intelligence tech- niques. Al software for massively parallel architectures was started. 1. Introduction We describe research conducted

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

PubMed

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

2018-02-01

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

Artificial Intelligence Techniques: Applications for Courseware Development.

ERIC Educational Resources Information Center

Dear, Brian L.

1986-01-01

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

An Artificial Intelligence Approach to Analyzing Student Errors in Statistics.

ERIC Educational Resources Information Center

Sebrechts, Marc M.; Schooler, Lael J.

1987-01-01

Describes the development of an artificial intelligence system called GIDE that analyzes student errors in statistics problems by inferring the students' intentions. Learning strategies involved in problem solving are discussed and the inclusion of goal structures is explained. (LRW)

Ethical Implications of an Experiment in Artificial Intelligence.

ERIC Educational Resources Information Center

Levinson, Stephen E.

2003-01-01

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

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)

A Modular Artificial Intelligence Inference Engine System (MAIS) for support of on orbit experiments

NASA Technical Reports Server (NTRS)

Hancock, Thomas M., III

1994-01-01

This paper describes a Modular Artificial Intelligence Inference Engine System (MAIS) support tool that would provide health and status monitoring, cognitive replanning, analysis and support of on-orbit Space Station, Spacelab experiments and systems.

1988 Goddard Conference on Space Applications of Artificial Intelligence, Greenbelt, MD, May 24, 1988, Proceedings

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor)

1988-01-01

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

The Toulmin Argument Model in Artificial Intelligence

NASA Astrophysics Data System (ADS)

Verheij, Bart

In 1958, Toulmin published The Uses of Argument. Although this anti-formalistic monograph initially received mixed reviews (see section 2 of [20] for Toulmin’s own recounting of the reception of his book), it has become a classical text on argumentation, and the number of references to the book (when writing these words1 —by a nice numerological coincidence—1958) continues to grow (see [7] and the special issue of Argumentation 2005; Vol. 19, No. 3). Also the field of Artificial Intelligence has discovered Toulmin’s work. Especially four of Toulmin’s themes have found follow-up in Artificial Intelligence.

Northeast Artificial Intelligence Consortium Annual Report 1987. Volume 2, Part B. Discussing, Using, and Recognizing Plans

DTIC Science & Technology

1989-03-01

1978. Williams. B.C. Qualitative Analysis of MOS Circuits. Artificial Inteligence . 1984. 24.. Wilson. K. From Association to Structure. Amsterdam:North...D-A208 378 RADC-TR-88-324, Vol II (of nine), Part B Interim Report March 1969 4. NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT 1987...II (of nine), Part B 6a. NAME OF PERFORMING ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Northeast Artificial (ff ’aolicbl

A Test of Genetic Algorithms in Relevance Feedback.

ERIC Educational Resources Information Center

Lopez-Pujalte, Cristina; Guerrero Bote, Vicente P.; Moya Anegon, Felix de

2002-01-01

Discussion of information retrieval, query optimization techniques, and relevance feedback focuses on genetic algorithms, which are derived from artificial intelligence techniques. Describes an evaluation of different genetic algorithms using a residual collection method and compares results with the Ide dec-hi method (Salton and Buckley, 1990…

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.

JPRS Report, East Europe

DTIC Science & Technology

1987-12-08

34 artificial intelligence," on which we will also rely in the future, but once again, experience has shown that the smallest error in the construction...Western press presents such accidents as the transformation of the advantages of artificial intelligence into tragedies of artificial stupidity...life more tellingly than the recent studies con- cerning the ozone "void" discovered by satellites over the two poles, or the effects of the

Adaptive Modeling and Real-Time Simulation

DTIC Science & Technology

1984-01-01

34 Artificial Inteligence , Vol. 13, pp. 27-39 (1980). Describes circumscription which is just the assumption that everything that is known to have a particular... Artificial Intelligence Truth Maintenance Planning Resolution Modeling Wcrld Models ~ .. ~2.. ASSTR AT (Coninue n evrse sieIf necesaran Identfy by...represents a marriage of (1) the procedural-network st, planning technology developed in artificial intelligence with (2) the PERT/CPM technology developed in

LISP on a Reduced-Instruction-Set-Processor,

DTIC Science & Technology

1986-01-01

Digital * Press, 1984. 19. Steele, G. L. Jr., and Sussman, G.J. LAMBDA : The Ultimate Imperative. Al Memo 353, MIT, Artificial ,, Inteligence Laboratory...procedure B is No 444, MIT Artificial Intelligence Laboratory, August, recursive, if procedure A can be reexecuted before the call 1977. returns. This...the programs Artificial Intelligence Programming. Lawrence Erlbaum use apply and eval, and of these three only frl uses eval Associates, Hillsdale, New

A Multiagent Based Model for Tactical Planning

DTIC Science & Technology

2002-10-01

Pub. Co. 1985. [10] Castillo, J.M. Aproximación mediante procedimientos de Inteligencia Artificial al planeamiento táctico. Doctoral Thesis...been developed under the same conceptual model and using similar Artificial Intelligence Tools. We use four different stimulus/response agents in...The conceptual model is built on base of the Agents theory. To implement the different agents we have used Artificial Intelligence techniques such

High-Level Vision and Planning Workshop Proceedings

DTIC Science & Technology

1989-08-01

Correspondence in Line Drawings of Multiple View-. In Proc. of 8th Intern. Joint Conf. on Artificial intellignece . 1983. [63] Tomiyasu, K. Tutorial...joint U.S.-Israeli workshop on artificial intelligence are provided in this Institute for Defense Analyses document. This document is based on a broad...participants is provided along with applicable references for individual papers. 14. SUBJECT TERMS 15. NUMBER OF PAGES Artificial Intelligence; Machine Vision

Proceedings of the MIT/ONR Workshop on Distributed Communication and Decision Problems Motivated by Naval C3 Systems (2nd). Held in Monterey, California on 16-27 July 1979. Volume 2

DTIC Science & Technology

1980-03-01

artificial intellegence methods to organize and control the system as well as to interpret surveillance data. • Surveillance and tracking of low-flying...algorithms and an artificial Intellegence approach to the processing and interpretation of the sensor data. At the very least we will consider how to...8:00-8:30 REGISTRATION 8:30-9:30 HALTING THE PROLIFERATION OF ERRORS - AN APPLICATION FOR ARTIFICIAL INTELLIGENCE Gerald Wilson, Senior Comcuter

Advanced Methods of Approximate Reasoning

DTIC Science & Technology

1990-11-30

about Knowledge and Action. Technical Note 191, Menlo Park, California: SRI International. 1980 . 20 [26] N.J. Nilsson. Probabilistic logic. Artificial...reasoning. Artificial Intelligence, 13:81-132, 1980 . S[30 R. Reiter. On close world data bases. In H. Gallaire and J. Minker, editors, Logic and Data...specially grateful to Dr. Abraham Waksman of the Air Force Office of Scientific Research and Dr. David Hislop of the Army Research Office for their

Artificial Intelligence: A Selected Bibliography.

ERIC Educational Resources Information Center

Smith, Linda C., Comp.

1984-01-01

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

Artificial Intelligence in Speech Understanding: Two Applications at C.R.I.N.

ERIC Educational Resources Information Center

Carbonell, N.; And Others

1986-01-01

This article explains how techniques of artificial intelligence are applied to expert systems for acoustic-phonetic decoding, phonological interpretation, and multi-knowledge sources for man-machine dialogue implementation. The basic ideas are illustrated with short examples. (Author/JDH)

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…

Counseling, Artificial Intelligence, and Expert Systems.

ERIC Educational Resources Information Center

Illovsky, Michael E.

1994-01-01

Considers the use of artificial intelligence and expert systems in counseling. Limitations are explored; candidates for counseling versus those for expert systems are discussed; programming considerations are reviewed; and techniques for dealing with rational, nonrational, and irrational thoughts and feelings are described. (Contains 46…

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…

Top 10 "Smart" Technologies for Schools.

ERIC Educational Resources Information Center

Fodeman, Doug; Holzberg, Carol S.; Kennedy, Kristen; McIntire, Todd; McLester, Susan; Ohler, Jason; Parham, Charles; Poftak, Amy; Schrock, Kathy; Warlick, David

2002-01-01

Describes 10 smart technologies for education, including voice to text software; mobile computing; hybrid computing; virtual reality; artificial intelligence; telementoring; assessment methods; digital video production; fingerprint recognition; and brain functions. Lists pertinent Web sites for each technology. (LRW)

PC graphics generation and management tool for real-time applications

NASA Technical Reports Server (NTRS)

Truong, Long V.

1992-01-01

A graphics tool was designed and developed for easy generation and management of personal computer graphics. It also provides methods and 'run-time' software for many common artificial intelligence (AI) or expert system (ES) applications.

Using a computer-based simulation with an artificial intelligence component and discovery learning to formulate training needs for a new technology

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

Hillis, D.R.

A computer-based simulation with an artificial intelligence component and discovery learning was investigated as a method to formulate training needs for new or unfamiliar technologies. Specifically, the study examined if this simulation method would provide for the recognition of applications and knowledge/skills which would be the basis for establishing training needs. The study also examined the effect of field-dependence/independence on recognition of applications and knowledge/skills. A pretest-posttest control group experimental design involving fifty-eight college students from an industrial technology program was used. The study concluded that the simulation was effective in developing recognition of applications and the knowledge/skills for amore » new or unfamiliar technology. And, the simulation's effectiveness for providing this recognition was not limited by an individual's field-dependence/independence.« less

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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.

Prediction of the Wall Factor of Arbitrary Particle Settling through Various Fluid Media in a Cylindrical Tube Using Artificial Intelligence

PubMed Central

Li, Mingzhong; Xue, Jianquan; Li, Yanchao; Tang, Shukai

2014-01-01

Considering the influence of particle shape and the rheological properties of fluid, two artificial intelligence methods (Artificial Neural Network and Support Vector Machine) were used to predict the wall factor which is widely introduced to deduce the net hydrodynamic drag force of confining boundaries on settling particles. 513 data points were culled from the experimental data of previous studies, which were divided into training set and test set. Particles with various shapes were divided into three kinds: sphere, cylinder, and rectangular prism; feature parameters of each kind of particle were extracted; prediction models of sphere and cylinder using artificial neural network were established. Due to the little number of rectangular prism sample, support vector machine was used to predict the wall factor, which is more suitable for addressing the problem of small samples. The characteristic dimension was presented to describe the shape and size of the diverse particles and a comprehensive prediction model of particles with arbitrary shapes was established to cover all types of conditions. Comparisons were conducted between the predicted values and the experimental results. PMID:24772024

Prediction of the wall factor of arbitrary particle settling through various fluid media in a cylindrical tube using artificial intelligence.

PubMed

Li, Mingzhong; Zhang, Guodong; Xue, Jianquan; Li, Yanchao; Tang, Shukai

2014-01-01

Considering the influence of particle shape and the rheological properties of fluid, two artificial intelligence methods (Artificial Neural Network and Support Vector Machine) were used to predict the wall factor which is widely introduced to deduce the net hydrodynamic drag force of confining boundaries on settling particles. 513 data points were culled from the experimental data of previous studies, which were divided into training set and test set. Particles with various shapes were divided into three kinds: sphere, cylinder, and rectangular prism; feature parameters of each kind of particle were extracted; prediction models of sphere and cylinder using artificial neural network were established. Due to the little number of rectangular prism sample, support vector machine was used to predict the wall factor, which is more suitable for addressing the problem of small samples. The characteristic dimension was presented to describe the shape and size of the diverse particles and a comprehensive prediction model of particles with arbitrary shapes was established to cover all types of conditions. Comparisons were conducted between the predicted values and the experimental results.

An improved clustering algorithm based on reverse learning in intelligent transportation

NASA Astrophysics Data System (ADS)

Qiu, Guoqing; Kou, Qianqian; Niu, Ting

2017-05-01

With the development of artificial intelligence and data mining technology, big data has gradually entered people's field of vision. In the process of dealing with large data, clustering is an important processing method. By introducing the reverse learning method in the clustering process of PAM clustering algorithm, to further improve the limitations of one-time clustering in unsupervised clustering learning, and increase the diversity of clustering clusters, so as to improve the quality of clustering. The algorithm analysis and experimental results show that the algorithm is feasible.

Using Crowdsourced Geospatial Data to Aid in Nuclear Proliferation Monitoring

DTIC Science & Technology

2016-12-01

M. Stephens, and Ronald D. Bonnell, “DAI for Document Retrieval: The MINDS Project,” in Distributed Artificial Intelligence , ed. Michael N. Huhns...Ronald D. Bonnell. “DAI for Document Retrieval: The MINDS Project,” In Distributed Artificial Intelligence , edited by Michael N. Huhns, 249–283...was for the director of National Intelligence to explore ways that crowdsourced geospatial imagery technologies could aid existing governmental

DATA MAYHEM VERSUS NIMBLE INFORMATION: TRANSFORMING HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS

DTIC Science & Technology

2017-10-01

AU/ACSC/MORALES/AY17 AIR COMMAND AND STAFF COLLEGE DISTANCE LEARNING AIR UNIVERSITY DATA MAYHEM VERSUS NIMBLE INFORMATION : TRANSFORMING...HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS by Luis A. Morales, Major, USAF A Research...finding solutions to compliment and supplement human analysts’ capacity, so intelligence and information can reach operators and end-users at the

List of U.S. Army Research Institute Research and Technical Publications. Fiscal Year 2006

DTIC Science & Technology

2007-08-01

performance support systems and computer-generated simulations powered by artificial intelligence , and super-broad bandwidth. We then present a set of...dialogue, Artificial Intelligence SBIR Phase I Report 61 FY 2006 Books and Book Chapters Durlach, P.J., Neuman, J.L., & Bowens, L.D...mediation of the social intelligence -social performance relationship by social knowledge, was supported for three out of five social performance

The Analysis of Nominal Compounds,

DTIC Science & Technology

1985-12-01

34Phenomenologically plausible parsing" in Proceedings of the 1984 American Association for Aritificial Intelligence Conference, pp. 335-339. 27 Wilensky, R...34December, 1985 - CPTM #8 LJ _DTIC -5ELECTE’ DEC 1 6 198M This series of internal memos describes research in E artificial intelligence conducted under...representational techniques for natural language that have evolved in linguistics and artificial intelligence , it is difficult to find much uniformity in the

Issues in Adaptive Planning

DTIC Science & Technology

1986-06-30

approach to the application of theorem proving to problem solving, Aritificial Intelligence 2 (1Q71), 18Q- 208. 4. Fikes, R., Hart, P. and Nilsson, N...by emphasizing the structure of knowledge. 1.2. Planning Literature The earliest work in planning in Artificial Intelligence grew out of the work on...References 1. Newell, A., Artificial Intelligence and the concept of mind, in Computer models of thought and language, Schank, R. and Colby, K. (editor

Constraint-Directed Search: A Case Study of Job-Shop Scheduling.

DTIC Science & Technology

1983-12-13

Structures But Were Unable to Represent", Proceedings of the American Association for Aritificial Intelligence , pp. 212-214, Stanford University...under these constraints raises a number of issues of interest to the artificial intelligence community such as: - knowledge representation semantics for...Management Science 15 2.3. Artificial Intelligence 17 2.4. Relationship to Previous Research 21 3. ISIS Modeling System 23 3.1. Introduction 24 3.2. Layer

Framework for Evolutionary Development of an Autonomous Expert System for Acoustically Identifying Classifications of Vessels

DTIC Science & Technology

1989-01-01

completely autonomous system. SOMMIIRE Une exp6rience en intelligence artificielle (IA) en cours au CRDA vise la misc au point 6ventuelle d’un syst~me...identifying vessel classifications from 0aaV Mcute SOAifatwgms is the ultimate goal of Artificial Intelligence (Al) wod ?bhig- eouaduted -*DRAR~ An...Friendly Interface ..................................................................... 4 3 Concepts of Assistant and Autonomous Artificially Intelligent

Communications and control for electric power systems: Power system stability applications of artificial neural networks

NASA Technical Reports Server (NTRS)

Toomarian, N.; Kirkham, Harold

1994-01-01

This report investigates the application of artificial neural networks to the problem of power system stability. The field of artificial intelligence, expert systems, and neural networks is reviewed. Power system operation is discussed with emphasis on stability considerations. Real-time system control has only recently been considered as applicable to stability, using conventional control methods. The report considers the use of artificial neural networks to improve the stability of the power system. The networks are considered as adjuncts and as replacements for existing controllers. The optimal kind of network to use as an adjunct to a generator exciter is discussed.

Artificial intelligence - New tools for aerospace project managers

NASA Technical Reports Server (NTRS)

Moja, D. C.

1985-01-01

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

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

NASA Technical Reports Server (NTRS)

1994-01-01

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

The Heuristic of George Polya and Its Relation to Artificial Intelligence

DTIC Science & Technology

1981-07-01

entitled Mathematical methods in physical science -- odd, in not being the standard freshman fare of physics, chemistry , western civilization and...the questions teachers should use. The first I I Having used a linguistic variation lo convey a matter of substance, a comment on etymology is in...Intelligence to Chemistry : The DEN ORAL project. New York- McGraw-Hill 1980. McDermott, J. Learning to use analogies. Proceedings of the International Joint

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.

Finding Creativity in an Artificial Artist

ERIC Educational Resources Information Center

Norton, David; Heath, Derrall; Ventura, Dan

2013-01-01

Creativity is an important component of human intelligence, and imbuing artificially intelligent systems with creativity is an interesting challenge. In particular, it is difficult to quantify (or even qualify) creativity. Recently, it has been suggested that conditions for attributing creativity to a system include: appreciation, imagination, and…

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…

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

Hybrid Applications Of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Borchardt, Gary C.

1988-01-01

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

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)

A Starter's Guide to Artificial Intelligence.

ERIC Educational Resources Information Center

McConnell, Barry A.; McConnell, Nancy J.

1988-01-01

Discussion of the history and development of artificial intelligence (AI) highlights a bibliography of introductory books on various aspects of AI, including AI programing; problem solving; automated reasoning; game playing; natural language; expert systems; machine learning; robotics and vision; critics of AI; and representative software. (LRW)

Application of an artificial intelligence program to therapy of high-risk surgical patients.

PubMed

Patil, R S; Adibi, J; Shoemaker, W C

1996-11-01

We developed an artificial intelligence program from a large computerized database of hemodynamic and oxygen transport measurements together with prior studies defining survivors' values, outcome predictors, and a branched-chain decision tree. The artificial intelligence program was then tested on the data of 100 survivors and 100 nonsurvivors not used for the development of the program or other analyses. Using the predictor as a surrogate outcome measure, the therapy recommended by the program improved the predicted outcome 3.16% per therapeutic intervention while the actual therapy given increased outcome 1.86% in surviving patients; the artificial intelligence-recommended therapy improved outcome 7.9% in nonsurvivors, while the actual therapy given increased predicted outcome -0.29% in nonsurvivors (p < .05). There were fewer patients whose predicted outcome decreased after recommended treatment (14%) than after the actual therapy given (37%). Review of therapy recommended by the program did not reveal instances of inappropriate or potentially harmful recommendations.

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.

Artificial intelligence and robot responsibilities: innovating beyond rights.

PubMed

Ashrafian, Hutan

2015-04-01

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

Herbert: A Second Generation Mobile Robot.

DTIC Science & Technology

1988-01-01

PROJECT. TASK S Artificial Inteligence Laboratory AREA A WORK UNIT NUMBERS ’ ~ 545 Technology Square Cambridge, MA 02139 11. CONTROLLING OFFICE NAME...AD-AI93 632 WMRT: A SECOND GENERTION MOBILE ROWT(U) / MASSACHUSETTS IMST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB R BROOKS ET AL .JAN l8 Al-M...MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A. I. Memo 1016 January, 1988 HERBERT: A SECOND GENERATION MOBILE ROBOT Rodney A

3D Object Recognition: Symmetry and Virtual Views

DTIC Science & Technology

1992-12-01

NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATIONI Artificial Intelligence Laboratory REPORT NUMBER 545 Technology Square AIM 1409 Cambridge... ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING A.I. Memo No. 1409 December 1992 C.B.C.L. Paper No. 76 3D Object...research done within the Center for Biological and Computational Learning in the Department of Brain and Cognitive Sciences, and at the Artificial

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

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

PubMed

Palaniappan, Rajkumar; Sundaraj, Kenneth; Sundaraj, Sebastian

2014-02-01

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

Using string invariants for prediction searching for optimal parameters

NASA Astrophysics Data System (ADS)

Bundzel, Marek; Kasanický, Tomáš; Pinčák, Richard

2016-02-01

We have developed a novel prediction method based on string invariants. The method does not require learning but a small set of parameters must be set to achieve optimal performance. We have implemented an evolutionary algorithm for the parametric optimization. We have tested the performance of the method on artificial and real world data and compared the performance to statistical methods and to a number of artificial intelligence methods. We have used data and the results of a prediction competition as a benchmark. The results show that the method performs well in single step prediction but the method's performance for multiple step prediction needs to be improved. The method works well for a wide range of parameters.

Heuristic Analysis Model of Nitrided Layers’ Formation Consisting of the Image Processing and Analysis and Elements of Artificial Intelligence

PubMed Central

Wójcicki, Tomasz; Nowicki, Michał

2016-01-01

The article presents a selected area of research and development concerning the methods of material analysis based on the automatic image recognition of the investigated metallographic sections. The objectives of the analyses of the materials for gas nitriding technology are described. The methods of the preparation of nitrided layers, the steps of the process and the construction and operation of devices for gas nitriding are given. We discuss the possibility of using the methods of digital images processing in the analysis of the materials, as well as their essential task groups: improving the quality of the images, segmentation, morphological transformations and image recognition. The developed analysis model of the nitrided layers formation, covering image processing and analysis techniques, as well as selected methods of artificial intelligence are presented. The model is divided into stages, which are formalized in order to better reproduce their actions. The validation of the presented method is performed. The advantages and limitations of the developed solution, as well as the possibilities of its practical use, are listed. PMID:28773389

Application Of Artificial Intelligence To Wind Tunnels

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

Fundamental research in artificial intelligence at NASA

NASA Technical Reports Server (NTRS)

Friedland, Peter

1990-01-01

This paper describes basic research at NASA in the field of artificial intelligence. The work is conducted at the Ames Research Center and the Jet Propulsion Laboratory, primarily under the auspices of the NASA-wide Artificial Intelligence Program in the Office of Aeronautics, Exploration and Technology. The research is aimed at solving long-term NASA problems in missions operations, spacecraft autonomy, preservation of corporate knowledge about NASA missions and vehicles, and management/analysis of scientific and engineering data. From a scientific point of view, the research is broken into the categories of: planning and scheduling; machine learning; and design of and reasoning about large-scale physical systems.

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…

Artificial Intelligence Applications to Videodisc Technology

PubMed Central

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

1985-01-01

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

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…

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…

Soar: A Unified Theory of Cognition?

ERIC Educational Resources Information Center

Waldrop, M. Mitchell

1988-01-01

Describes an artificial intelligence system known as SOAR that approximates a theory of human cognition. Discusses cognition as problem solving, working memory, long term memory, autonomy and adaptability, and learning from experience as they relate to artificial intelligence generally and to SOAR specifically. Highlights the status of the…

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 Is for Real: Undergraduate Students Should Know about It.

ERIC Educational Resources Information Center

Liebowitz, Jay

1988-01-01

Discussion of the possibilities of introducing artificial intelligence (AI) into the undergraduate curriculum highlights the introduction of AI in an introduction to information processing course for business students at George Washington University. Topics discussed include robotics, expert systems prototyping in class, and the interdisciplinary…

Progress in cybernetics and systems research. Vol. XI. Data base design. International Information Systems. Semiotic Systems. Artificial Intelligence. Cybernetics and Philosophy. Special aspects

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

Trappl, R.; Findler, N.V.; Horn, W.

1982-01-01

This book covers current research topics in six areas. These are data base design, international information systems, semiotic systems, artificial intelligence, cybernetics and philosophy, and special aspects of systems research. 1326 references.

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)

Automatic food detection in egocentric images using artificial intelligence technology

USDA-ARS?s Scientific Manuscript database

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

Artificial intelligence may help in predicting the need for additional surgery after endoscopic resection of T1 colorectal cancer.

PubMed

Ichimasa, Katsuro; Kudo, Shin-Ei; Mori, Yuichi; Misawa, Masashi; Matsudaira, Shingo; Kouyama, Yuta; Baba, Toshiyuki; Hidaka, Eiji; Wakamura, Kunihiko; Hayashi, Takemasa; Kudo, Toyoki; Ishigaki, Tomoyuki; Yagawa, Yusuke; Nakamura, Hiroki; Takeda, Kenichi; Haji, Amyn; Hamatani, Shigeharu; Mori, Kensaku; Ishida, Fumio; Miyachi, Hideyuki

2018-03-01

 Decisions concerning additional surgery after endoscopic resection of T1 colorectal cancer (CRC) are difficult because preoperative prediction of lymph node metastasis (LNM) is problematic. We investigated whether artificial intelligence can predict LNM presence, thus minimizing the need for additional surgery.  Data on 690 consecutive patients with T1 CRCs that were surgically resected in 2001 - 2016 were retrospectively analyzed. We divided patients into two groups according to date: data from 590 patients were used for machine learning for the artificial intelligence model, and the remaining 100 patients were included for model validation. The artificial intelligence model analyzed 45 clinicopathological factors and then predicted positivity or negativity for LNM. Operative specimens were used as the gold standard for the presence of LNM. The artificial intelligence model was validated by calculating the sensitivity, specificity, and accuracy for predicting LNM, and comparing these data with those of the American, European, and Japanese guidelines.  Sensitivity was 100 % (95 % confidence interval [CI] 72 % to 100 %) in all models. Specificity of the artificial intelligence model and the American, European, and Japanese guidelines was 66 % (95 %CI 56 % to 76 %), 44 % (95 %CI 34 % to 55 %), 0 % (95 %CI 0 % to 3 %), and 0 % (95 %CI 0 % to 3 %), respectively; and accuracy was 69 % (95 %CI 59 % to 78 %), 49 % (95 %CI 39 % to 59 %), 9 % (95 %CI 4 % to 16 %), and 9 % (95 %CI 4 % - 16 %), respectively. The rates of unnecessary additional surgery attributable to misdiagnosing LNM-negative patients as having LNM were: 77 % (95 %CI 62 % to 89 %) for the artificial intelligence model, and 85 % (95 %CI 73 % to 93 %; P  < 0.001), 91 % (95 %CI 84 % to 96 %; P  < 0.001), and 91 % (95 %CI 84 % to 96 %; P  < 0.001) for the American, European, and Japanese guidelines, respectively.  Compared with current guidelines, artificial intelligence significantly reduced unnecessary additional surgery after endoscopic resection of T1 CRC without missing LNM positivity. © Georg Thieme Verlag KG Stuttgart · New York.

An overview of the artificial intelligence and expert systems component of RICIS

NASA Technical Reports Server (NTRS)

Feagin, Terry

1987-01-01

Artificial Intelligence and Expert Systems are the important component of RICIS (Research Institute and Information Systems) research program. For space applications, a number of problem areas that should be able to make good use of the above tools include: resource allocation and management, control and monitoring, environmental control and life support, power distribution, communications scheduling, orbit and attitude maintenance, redundancy management, intelligent man-machine interfaces and fault detection, isolation and recovery.

Human Factors Issues in the Use of Virtual and Augmented Reality for Military Purposes - USA

DTIC Science & Technology

2005-12-01

and provide a means of output, MOVES has built a prototype system and continues research into the artificial intelligence and other factors required...role in any attempt to create automaton warriors. Indeed game-theoretic notions have been utilized in applications of artificial intelligence to...Review Board at the Defense Intelligence Agency (DIA). AFRL was notified that DIA will sponsor DTNG for Certification and Accreditation. Det 4 is expected

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

Enhancement of submarine pressure hull steel ultrasonic inspection using imaging and artificial intelligence

NASA Astrophysics Data System (ADS)

Hay, D. Robert; Brassard, Michel; Matthews, James R.; Garneau, Stephane; Morchat, Richard

1995-06-01

The convergence of a number of contemporary technologies with increasing demands for improvements in inspection capabilities in maritime applications has created new opportunities for ultrasonic inspection. An automated ultrasonic inspection and data collection system APHIUS (automated pressure hull intelligent ultrasonic system), incorporates hardware and software developments to meet specific requirements for the maritime vessels, in particular, submarines in the Canadian Navy. Housed within a hardened portable computer chassis, instrumentation for digital ultrasonic data acquisition and transducer position measurement provide new capabilities that meet more demanding requirements for inspection of the aging submarine fleet. Digital data acquisition enables a number of new important capabilites including archiving of the complete inspection session, interpretation assistance through imaging, and automated interpretation using artificial intelligence methods. With this new reliable inspection system, in conjunction with a complementary study of the significance of real defect type and location, comprehensive new criteria can be generated which will eliminate unnecessary defect removal. As a consequence, cost savings will be realized through shortened submarine refit schedules.

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Intelligent computer-aided training and tutoring

NASA Technical Reports Server (NTRS)

Loftin, R. Bowen; Savely, Robert T.

1991-01-01

Specific autonomous training systems based on artificial intelligence technology for use by NASA astronauts, flight controllers, and ground-based support personnel that demonstrate an alternative to current training systems are described. In addition to these specific systems, the evolution of a general architecture for autonomous intelligent training systems that integrates many of the features of traditional training programs with artificial intelligence techniques is presented. These Intelligent Computer-Aided Training (ICAT) systems would provide, for the trainee, much of the same experience that could be gained from the best on-the-job training. By integrating domain expertise with a knowledge of appropriate training methods, an ICAT session should duplicate, as closely as possible, the trainee undergoing on-the-job training in the task environment, benefitting from the full attention of a task expert who is also an expert trainer. Thus, the philosophy of the ICAT system is to emulate the behavior of an experienced individual devoting his full time and attention to the training of a novice - proposing challenging training scenarios, monitoring and evaluating the actions of the trainee, providing meaningful comments in response to trainee errors, responding to trainee requests for information, giving hints (if appropriate), and remembering the strengths and weaknesses displayed by the trainee so that appropriate future exercises can be designed.

Automated Test Requirement Document Generation

DTIC Science & Technology

1987-11-01

DIAGNOSTICS BASED ON THE PRINCIPLES OF ARTIFICIAL INTELIGENCE ", 1984 International Test Conference, 01Oct84, (A3, 3, Cs D3, E2, G2, H2, 13, J6, K) 425...j0O GLOSSARY OF ACRONYMS 0 ABBREVIATION DEFINITION AFSATCOM Air Force Satellite Communication Al Artificial Intelligence ASIC Application Specific...In-Test Equipment (BITE) and AI ( Artificial Intelligence) - Expert Systems - need to be fully applied before a completely automated process can be

Reification without Evaluation.

DTIC Science & Technology

1988-06-01

PROJECT. TASK Artificial Inteligence Laboratory AREA & WORK UNIT NuMBERS ’’ 545 Technology Square 0 Cambridge, MA 02139 L $I 1, CONTROLLINO OFFICE NAME...7RD-ft" 28 REIFICRIO WITHOUT EYRURTION(U) rASSACHUSETTS INST OF 1/:LTECH CUZDGE ARTIFICI L INTELLIGENCE LUN R MEN JUN 60 RI-M-946 NM14-5-K-0-0124...themselves. This report, describes research done at, tie Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the

Artificial intelligence in process control: Knowledge base for the shuttle ECS model

NASA Technical Reports Server (NTRS)

Stiffler, A. Kent

1989-01-01

The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

Introduction to the Special Issue on Innovative Applications of Artificial Intelligence 2014

DOE PAGES

Stracuzzi, David J.; Gunning, David

2015-09-28

This issue features expanded versions of articles selected from the 2014 AAAI Conference on Innovative Applications of Artificial Intelligence held in Quebec City, Canada. We present a selection of four articles describing deployed applications plus two more articles that discuss work on emerging applications.

AI in CALL--Artificially Inflated or Almost Imminent?

ERIC Educational Resources Information Center

Schulze, Mathias

2008-01-01

The application of techniques from artificial intelligence (AI) to CALL has commonly been referred to as intelligent CALL (ICALL). ICALL is only slightly older than the "CALICO Journal", and this paper looks back at a quarter century of published research mainly in North America and by North American scholars. This "inventory…

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,…

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…

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

Magical Stories: Blending Virtual Reality and Artificial Intelligence.

ERIC Educational Resources Information Center

McLellan, Hilary

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

Introduction to the Special Issue on Innovative Applications of Artificial Intelligence 2014

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

Stracuzzi, David J.; Gunning, David

This issue features expanded versions of articles selected from the 2014 AAAI Conference on Innovative Applications of Artificial Intelligence held in Quebec City, Canada. We present a selection of four articles describing deployed applications plus two more articles that discuss work on emerging applications.

RESEARCH AREA -- ARTIFICIAL INTELLIGENCE CONTROL (AIR POLLUTION TECHNOLOGY BRANCH, AIR POLLUTION PREVENTION AND CONTROL DIVISION, NRMRL)

EPA Science Inventory

The Air Pollution Technology Branch (APTB) of NRMRL's Air Pollution Prevention and Control Division in Research Triangle Park, NC, has conducted several research projects for evaluating the use of artificial intelligence (AI) to improve the control of pollution control systems an...

Artificial Intelligence and School Library Media Centers.

ERIC Educational Resources Information Center

Young, Robert J.

1990-01-01

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

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…

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…

Research and applications: Artificial intelligence

NASA Technical Reports Server (NTRS)

Chaitin, L. J.; Duda, R. O.; Johanson, P. A.; Raphael, B.; Rosen, C. A.; Yates, R. A.

1970-01-01

The program is reported for developing techniques in artificial intelligence and their application to the control of mobile automatons for carrying out tasks autonomously. Visual scene analysis, short-term problem solving, and long-term problem solving are discussed along with the PDP-15 simulator, LISP-FORTRAN-MACRO interface, resolution strategies, and cost effectiveness.

Artificial intelligence within AFSC

NASA Technical Reports Server (NTRS)

Gersh, Mark A.

1990-01-01

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

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

NASA Technical Reports Server (NTRS)

Ali, Moonis; Whitehead, Bruce; Gupta, Uday K.; Ferber, Harry

1995-01-01

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system.

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

ERIC Educational Resources Information Center

Abelson, H.; And Others

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

Artificial intelligence in a mission operations and satellite test environment

NASA Technical Reports Server (NTRS)

Busse, Carl

1988-01-01

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

A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms

PubMed Central

Meiring, Gys Albertus Marthinus; Myburgh, Hermanus Carel

2015-01-01

In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced. PMID:26690164

A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms.

PubMed

Meiring, Gys Albertus Marthinus; Myburgh, Hermanus Carel

2015-12-04

In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

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

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong

2011-12-01

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

Modeling rainfall-runoff process using soft computing techniques

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Shiri, Jalal; Tombul, Mustafa

2013-02-01

Rainfall-runoff process was modeled for a small catchment in Turkey, using 4 years (1987-1991) of measurements of independent variables of rainfall and runoff values. The models used in the study were Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Gene Expression Programming (GEP) which are Artificial Intelligence (AI) approaches. The applied models were trained and tested using various combinations of the independent variables. The goodness of fit for the model was evaluated in terms of the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and scatter index (SI). A comparison was also made between these models and traditional Multi Linear Regression (MLR) model. The study provides evidence that GEP (with RMSE=17.82 l/s, MAE=6.61 l/s, CE=0.72 and R2=0.978) is capable of modeling rainfall-runoff process and is a viable alternative to other applied artificial intelligence and MLR time-series methods.

New model for prediction binary mixture of antihistamine decongestant using artificial neural networks and least squares support vector machine by spectrophotometry method

NASA Astrophysics Data System (ADS)

Mofavvaz, Shirin; Sohrabi, Mahmoud Reza; Nezamzadeh-Ejhieh, Alireza

2017-07-01

In the present study, artificial neural networks (ANNs) and least squares support vector machines (LS-SVM) as intelligent methods based on absorption spectra in the range of 230-300 nm have been used for determination of antihistamine decongestant contents. In the first step, one type of network (feed-forward back-propagation) from the artificial neural network with two different training algorithms, Levenberg-Marquardt (LM) and gradient descent with momentum and adaptive learning rate back-propagation (GDX) algorithm, were employed and their performance was evaluated. The performance of the LM algorithm was better than the GDX algorithm. In the second one, the radial basis network was utilized and results compared with the previous network. In the last one, the other intelligent method named least squares support vector machine was proposed to construct the antihistamine decongestant prediction model and the results were compared with two of the aforementioned networks. The values of the statistical parameters mean square error (MSE), Regression coefficient (R2), correlation coefficient (r) and also mean recovery (%), relative standard deviation (RSD) used for selecting the best model between these methods. Moreover, the proposed methods were compared to the high- performance liquid chromatography (HPLC) as a reference method. One way analysis of variance (ANOVA) test at the 95% confidence level applied to the comparison results of suggested and reference methods that there were no significant differences between them.

Artificial Intelligence and Its Use in Cost Type analyses with an Example in Cost Performance Measurement.

DTIC Science & Technology

1985-01-01

7-Ai6i 817 ARTIFICIAL INTELLIGENCE AND ITS USE IN COST TYE1/I ANALYSES WdITH ANt EXAMPLE IN COST PERFORMANCE I MERSUREMENT(U) DEFENSE SYSTEMS...INTELLIGENCE-THE EMERGING TECHNOLOGY/ NATURAL LANGUAGE PROCESSORS K ~ With the advent of ARTIFICAL INTELLEGENCE (AI), we are entering into a new era of...language processor which is commerically available is INTELLECT, by Artifical Intellegence Incorporated, Waltham, Mass. To illustrate what a natural

Mechanical Transformation of Task Heuristics into Operational Procedures

DTIC Science & Technology

1981-04-14

Introduction A central theme of recent research in artificial intelligence is that *Intelligent task performance requires large amounts of knowledge...PLAY P1 C4] (. (LEADING (QSO)) (OR (CAN-LEAO- HEARrS (gSO)J (mEg (SUIT-OF C3) H])] C-) (FOLLOWING (QSO)) (OR [VOID (OSO) (SUIT-LED)3 [IN-SUIT C3 (SUIT...Production rules as a representation for a knowledge based consultation system. Artificial Intelligence 8:15-45, Spring, 1977. [Davis 77b] R. Davis

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

PubMed

Altman, R B

2017-05-01

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

Artificial Intelligence in Maintenance: Proceedings of the Joint Services Workshop Held at Boulder, Colorado on 4-6 October 1983.

DTIC Science & Technology

1984-06-01

intelligence . I strongly suspect that we’ll use data links to Rome so we can take advantage of both of the computer systems. Again, we see the need for close... data base indexing system would come up with a hit on those three key words I’ve just said. What is it? The hit is "artificial intelligence ." (This...pieces of data and is not classificatory in nature. In MDX there is S an intelligent data base component, called PATREC [6, 7], for doing such reasoning

Qualitative Reasoning methods for CELSS modeling.

PubMed

Guerrin, F; Bousson, K; Steyer JPh; Trave-Massuyes, L

1994-11-01

Qualitative Reasoning (QR) is a branch of Artificial Intelligence that arose from research on engineering problem solving. This paper describes the major QR methods and techniques, which, we believe, are capable of addressing some of the problems that are emphasized in the literature and posed by CELSS modeling, simulation, and control at the supervisory level.

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

The dynamic lift of developmental process.

PubMed

Smith, Linda B; Breazeal, Cynthia

2007-01-01

What are the essential properties of human intelligence, currently unparalleled in its power relative to other biological forms and relative to artificial forms of intelligence? We suggest that answering this question depends critically on understanding developmental process. This paper considers three principles potentially essential to building human-like intelligence: the heterogeneity of the component processes, the embedding of development in a social world, and developmental processes that change the cognitive system as a function of the history of soft-assemblies of these heterogeneous processes in specific tasks. The paper uses examples from human development and from developmental robotics to show how these processes also may underlie biological intelligence and enable us to generate more advanced forms of artificial intelligence.

Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era.

PubMed

Jing, Yankang; Bian, Yuemin; Hu, Ziheng; Wang, Lirong; Xie, Xiang-Qun Sean

2018-03-30

Over the last decade, deep learning (DL) methods have been extremely successful and widely used to develop artificial intelligence (AI) in almost every domain, especially after it achieved its proud record on computational Go. Compared to traditional machine learning (ML) algorithms, DL methods still have a long way to go to achieve recognition in small molecular drug discovery and development. And there is still lots of work to do for the popularization and application of DL for research purpose, e.g., for small molecule drug research and development. In this review, we mainly discussed several most powerful and mainstream architectures, including the convolutional neural network (CNN), recurrent neural network (RNN), and deep auto-encoder networks (DAENs), for supervised learning and nonsupervised learning; summarized most of the representative applications in small molecule drug design; and briefly introduced how DL methods were used in those applications. The discussion for the pros and cons of DL methods as well as the main challenges we need to tackle were also emphasized.

A survey on the design of multiprocessing systems for artificial intelligence applications

NASA Technical Reports Server (NTRS)

Wah, Benjamin W.; Li, Guo Jie

1989-01-01

Some issues in designing computers for artificial intelligence (AI) processing are discussed. These issues are divided into three levels: the representation level, the control level, and the processor level. The representation level deals with the knowledge and methods used to solve the problem and the means to represent it. The control level is concerned with the detection of dependencies and parallelism in the algorithmic and program representations of the problem, and with the synchronization and sheduling of concurrent tasks. The processor level addresses the hardware and architectural components needed to evaluate the algorithmic and program representations. Solutions for the problems of each level are illustrated by a number of representative systems. Design decisions in existing projects on AI computers are classed into top-down, bottom-up, and middle-out approaches.

Modelling the effect of structural QSAR parameters on skin penetration using genetic programming

NASA Astrophysics Data System (ADS)

Chung, K. K.; Do, D. Q.

2010-09-01

In order to model relationships between chemical structures and biological effects in quantitative structure-activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data.

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.

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.

Development and evaluation of a novel lossless image compression method (AIC: artificial intelligence compression method) using neural networks as artificial intelligence.

PubMed

Fukatsu, Hiroshi; Naganawa, Shinji; Yumura, Shinnichiro

2008-04-01

This study was aimed to validate the performance of a novel image compression method using a neural network to achieve a lossless compression. The encoding consists of the following blocks: a prediction block; a residual data calculation block; a transformation and quantization block; an organization and modification block; and an entropy encoding block. The predicted image is divided into four macro-blocks using the original image for teaching; and then redivided into sixteen sub-blocks. The predicted image is compared to the original image to create the residual image. The spatial and frequency data of the residual image are compared and transformed. Chest radiography, computed tomography (CT), magnetic resonance imaging, positron emission tomography, radioisotope mammography, ultrasonography, and digital subtraction angiography images were compressed using the AIC lossless compression method; and the compression rates were calculated. The compression rates were around 15:1 for chest radiography and mammography, 12:1 for CT, and around 6:1 for other images. This method thus enables greater lossless compression than the conventional methods. This novel method should improve the efficiency of handling of the increasing volume of medical imaging data.

Analysis of cognitive theories in artificial intelligence and psychology in relation to the qualitative process of emotion

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

Semrau, P.

The purpose of this study was to analyze selected cognitive theories in the areas of artificial intelligence (A.I.) and psychology to determine the role of emotions in the cognitive or intellectual processes. Understanding the relationship of emotions to processes of intelligence has implications for constructing theories of aesthetic response and A.I. systems in art. Psychological theories were examined that demonstrated the changing nature of the research in emotion related to cognition. The basic techniques in A.I. were reviewed and the A.I. research was analyzed to determine the process of cognition and the role of emotion. The A.I. research emphasized themore » digital, quantifiable character of the computer and associated cognitive models and programs. In conclusion, the cognitive-emotive research in psychology and the cognitive research in A.I. emphasized quantification methods over analog and qualitative characteristics required for a holistic explanation of cognition. Further A.I. research needs to examine the qualitative aspects of values, attitudes, and beliefs on influencing the creative thinking processes. Inclusion of research related to qualitative problem solving in art provides a more comprehensive base of study for examining the area of intelligence in computers.« less

Artificial intelligence in medicine: the challenges ahead.

PubMed

Coiera, E W

1996-01-01

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

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.

Utilization of artificial intelligence techniques for the Space Station power system

NASA Technical Reports Server (NTRS)

Evatt, Thomas C.; Gholdston, Edward W.

1988-01-01

Due to the complexity of the Space Station Electrical Power System (EPS) as currently envisioned, artificial intelligence/expert system techniques are being investigated to automate operations, maintenance, and diagnostic functions. A study was conducted to investigate this technology as it applies to failure detection, isolation, and reconfiguration (FDIR) and health monitoring of power system components and of the total system. Control system utilization of expert systems for load scheduling and shedding operations was also researched. A discussion of the utilization of artificial intelligence/expert systems for Initial Operating Capability (IOC) for the Space Station effort is presented along with future plans at Rocketdyne for the utilization of this technology for enhanced Space Station power capability.

Structural analysis of peptides that fill sites near the active center of the two different enzyme molecules by artificial intelligence and computer simulations

NASA Astrophysics Data System (ADS)

Nishiyama, Katsuhiko

2018-05-01

Using artificial intelligence, the binding styles of 167 tetrapeptides were predicted in the active site of papain and cathepsin K. Five tetrapeptides (Asn-Leu-Lys-Trp, Asp-Gln-Trp-Gly, Cys-Gln-Leu-Arg, Gln-Leu-Trp-Thr and Arg-Ser-Glu-Arg) were found to bind sites near the active center of both papain and cathepsin K. These five tetrapeptides have the potential to also bind sites of other cysteine proteases, and structural characteristics of these tetrapeptides should aid the design of a common inhibitor of cysteine proteases. Smart application of artificial intelligence should accelerate data mining of important complex systems.

Planning and Problem Solving

DTIC Science & Technology

1982-10-01

Artificial Intelig ~ence (Vol. III, edited by Paul R. Cohen and’ Edward A.. Feigenbaum)’, The chapter was written B’ Paul Cohen, with contributions... Artificial Intelligence (Vol. III, edited by Paul R. Cohen and EdWard A. Feigenbaum). The chapter was written by Paul R. Cohen, with contributions by Stephen...Wheevoats"EntermdI’ Planning and Problem ’Solving by Paul R. Cohen Chaptb-rXV-of Volumec III’of the Handbook of Artificial Intelligence edited by Paul R

Mission Profiles and Evidential Reasoning for Estimating Information Relevancy in Multi-Agent Supervisory Control Applications

DTIC Science & Technology

2010-06-01

artificial agents, their limited scope and singular purpose lead us to believe that human-machine trust will be very portable. That is, if one operator... Artificial Intelligence Review 2(2), 1988. [E88] M.R. Endsley. Situation awareness global assessment technique (SAGAT). In Proceedings of the National...1995. [F98] J. Ferber, Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence, Addison- Wesley, 1998. [NP01] I. Niles and A

Intelligent open-architecture controller using knowledge server

NASA Astrophysics Data System (ADS)

Nacsa, Janos; Kovacs, George L.; Haidegger, Geza

2001-12-01

In an ideal scenario of intelligent machine tools [22] the human mechanist was almost replaced by the controller. During the last decade many efforts have been made to get closer to this ideal scenario, but the way of information processing within the CNC did not change too much. The paper summarizes the requirements of an intelligent CNC evaluating the different research efforts done in this field using different artificial intelligence (AI) methods. The need for open CNC architecture was emerging at many places around the world. The second part of the paper introduces and shortly compares these efforts. In the third part a low cost concept for intelligent and open systems named Knowledge Server for Controllers (KSC) is introduced. It allows more devices to solve their intelligent processing needs using the same server that is capable to process intelligent data. In the final part the KSC concept is used in an open CNC environment to build up some elements of an intelligent CNC. The preliminary results of the implementation are also introduced.

Quantitative structure-activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods.

PubMed

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure-activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7-7-1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure-activity relationship model suggested is robust and satisfactory.

Quantitative structure–activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods

PubMed Central

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure–activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7−7−1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure–activity relationship model suggested is robust and satisfactory. PMID:26600858

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…

Artificial Intelligence Applications to Learning and Training. Occasional Paper--InTER/2/88.

ERIC Educational Resources Information Center

Cumming, Geoff

This report summarizes and interprets the discussions at a seminar on artificial intelligence (AI) training domains and knowledge representations which was sponsored by the United Kingdom Training Commission. The following broad areas are addressed: (1) the context, process, and diversity of requirements of training and training needs; (2)…

Artificial Intelligence, Counseling, and Cognitive Psychology.

ERIC Educational Resources Information Center

Brack, Greg; And Others

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

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…

Simulated Classrooms and Artificial Students: The Potential Effects of New Technologies on Teacher Education.

ERIC Educational Resources Information Center

Brown, Abbie Howard

1999-01-01

Describes and discusses how simulation activities can be used in teacher education to augment the traditional field-experience approach, focusing on artificial intelligence, virtual reality, and intelligent tutoring systems. Includes an overview of simulation as a teaching and learning strategy and specific examples of high-technology simulations…

Implications of Artificial Intelligence for End User Use of Online Systems.

ERIC Educational Resources Information Center

Smith, Linda C.

1980-01-01

Reviewed are several studies which demonstrate how artificial intelligence techniques can be applied in the design of end user-oriented interfaces (which would eliminate the need for an intermediary) to existing online systems, as well as in the development of future generations of online systems intended for the end user. (Author/SW)

Turtle Escapes the Plane: Some Advanced Turtle Geometry. Artificial Intelligence Memo Number 348.

ERIC Educational Resources Information Center

diSessa, Andy

The LOGO Turtles, originally developed at the Massachusetts Institute of Technology Artificial Intelligence Laboratory for teaching concepts in elementary geometry to primary-age children, can also be used in teaching higher-level mathematics. In the exercises described here, the turtle was programed to traverse curved surfaces. Both geometric and…

Application of artificial intelligence to risk analysis for forested ecosystems

Treesearch

Daniel L. Schmoldt

2001-01-01

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

Exploiting Artificial Intelligence To Enhance Training: A Short- and Medium-Term Perspective.

ERIC Educational Resources Information Center

Cumming, Geoff

This paper is an introductory discussion of industrial training, artificial intelligence (AI), and AI applications in training, prepared in the context of the United Kingdom Training Commission (TC) program. Following an outline of the activities and aims of the program, individual sections describe perspectives on: (1) training needs, including…

A Retrospective and Prospective View of Information Retrieval and Artificial Intelligence in the 21st Century.

ERIC Educational Resources Information Center

Garfield, Eugene

2001-01-01

Traces the development of information retrieval/services and suggests that the creation of large digital libraries seems inevitable. Examines possibilities for increasing electronic access and the role of artificial intelligence. Highlights include: searching full text; sending full texts; selective dissemination of information (SDI) profiling and…

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.

Artificial Intelligence Software Acquisition Program. Volume 2.

DTIC Science & Technology

1987-12-01

34Architect tire prototyping in the software engineering environment". 1BBA! .’ qtins Jo urnal, vol. 23, No. 1, p. 4-18, 1984. 3v Boehmi, Barry W_. Gray...on Artificial Intelligence, Sponsored by AAAI, December 1986. ..- ~[31] Pressman , Roger S. "Software Engineering: A Practitioner’s Approach". McGraw

An Artificial Intelligence Approach to the Symbolic Factorization of Multivariable Polynomials. Technical Report No. CS74019-R.

ERIC Educational Resources Information Center

Claybrook, Billy G.

A new heuristic factorization scheme uses learning to improve the efficiency of determining the symbolic factorization of multivariable polynomials with interger coefficients and an arbitrary number of variables and terms. The factorization scheme makes extensive use of artificial intelligence techniques (e.g., model-building, learning, and…

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…

Artificial Intelligence Applications to Fire Management

Treesearch

Don J. Latham

1987-01-01

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

The 1992 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor)

1992-01-01

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

Telerobot task planning and reasoning: Introduction to JPL artificial intelligence research

NASA Technical Reports Server (NTRS)

Atkinson, D. J.

1987-01-01

A view of the capabilities and areas of artificial intelligence research which are required for autonomous space telerobotics extending through the year 2000 is given. In the coming years, JPL will be conducting directed research to achieve these capabilities, as well as drawing heavily on collaborative efforts conducted with other research laboratories.

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…

PROLOG to the Future: A Glimpse of Things to Come in Artificial Intelligence.

ERIC Educational Resources Information Center

Herther, Nancy K.

1986-01-01

Briefly introduces the programming languages of artificial intelligence and presents information on some of the new versions of these languages available for microcomputers. A tutorial for PROLOG-86, a new microcomputer version of PROLOG, is given. Information on other microcomputer versions of these programs and a bibliography are included.…

Elements for an Ontology of Care in the Field of Artificial Intelligence.

PubMed

González Aguña, Alexandra; Fernández Batalla, Marta; Cercas Duque, Adriana; Herrero Jaén, Sara; Monsalvo San Macario, Enrique; Jiménez Rodríguez, Ma Lourdes; Santamaría García, José Ma; Ramírez Sánchez, Sylvia Claudine; Vialart Vidal, Niurka; Condor Camara, Daniel Flavio

2018-01-01

An ontology of care is a formal, explicit specification of a shared conceptualization. Constructing an ontology is a process that requires four elements: knowledge object, subject that knows, knowledge operation and result. These elements configure theframework to generate ontologies that can be used in Artificial Intelligence systems for care.

An Artificial Intelligence-Based Distance Education System: Artimat

ERIC Educational Resources Information Center

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

2013-01-01

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

An Application of Fuzzy Analytic Hierarchy Process (FAHP) for Evaluating Students' Project

ERIC Educational Resources Information Center

Çebi, Ayça; Karal, Hasan

2017-01-01

In recent years, artificial intelligence applications for understanding the human thinking process and transferring it to virtual environments come into prominence. The fuzzy logic which paves the way for modeling human behaviors and expressing even vague concepts mathematically, and is also regarded as an artificial intelligence technique has…

Massachusetts Institute of Technology Artificial Intelligence Laboratory Bibliography.

ERIC Educational Resources Information Center

Massachusetts Inst. of Tech., Cambridge. Artificial Intelligence Lab.

Massachusetts Institute of Technology (MIT) presents a bibliography of more than 350 reports, theses, and papers from its artificial intelligence laboratory. Title, author, and identification number are given for all items, and most also have a date and contract number. Some items are no longer available, and others may be obtained from National…

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.

Use of artificial intelligence to analyze clinical database reduces workload on surgical house staff.

PubMed

Grossi, E A; Steinberg, B M; LeBoutillier, M; Coppa, G F; Roses, D F

1994-08-01

The current quantity and diversity of hospital clinical, laboratory, and pharmacy records have resulted in a glut of information, which can be overwhelming to house staff. This study was performed to measure the impact of artificial intelligence analysis of such data on the junior surgical house staff's workload, time for direct patient care, and quality of life. A personal computer was interfaced with the hospital computerized patient data system. Artificial intelligence algorithms were applied to retrieve and condense laboratory values, microbiology reports, and medication orders. Unusual laboratory tests were reported without artificial intelligence filtering. A survey of 23 junior house staff showed a requirement for a total of 30.75 man-hours per day, an average of 184.5 minutes per service twice a day for five surgical services each with an average of 40.7 patients, to manually produce a report in contrast to a total of 3.4 man-hours, an average of 20.5 minutes on the same basis (88.9% reduction, p < 0.001), to computer generate and distribute a similarly useful report. Two thirds of the residents reported an increased ability to perform patient care. Current medical practice has created an explosion of information, which is a burden for surgical house staff. Artificial intelligence preprocessing of the hospital database information focuses attention, eliminates superfluous data, and significantly reduces surgical house staff clerical work, allowing more time for education, research, and patient care.

Acquaintance to Artificial Neural Networks and use of artificial intelligence as a diagnostic tool for tuberculosis: A review.

PubMed

Dande, Payal; Samant, Purva

2018-01-01

Tuberculosis [TB] has afflicted numerous nations in the world. As per a report by the World Health Organization [WHO], an estimated 1.4 million TB deaths in 2015 and an additional 0.4 million deaths resulting from TB disease among people living with HIV, were observed. Most of the TB deaths can be prevented if it is detected at an early stage. The existing processes of diagnosis like blood tests or sputum tests are not only tedious but also take a long time for analysis and cannot differentiate between different drug resistant stages of TB. The need to find newer prompt methods for disease detection has been aided by the latest Artificial Intelligence [AI] tools. Artificial Neural Network [ANN] is one of the important tools that is being used widely in diagnosis and evaluation of medical conditions. This review aims at providing brief introduction to various AI tools that are used in TB detection and gives a detailed description about the utilization of ANN as an efficient diagnostic technique. The paper also provides a critical assessment of ANN and the existing techniques for their diagnosis of TB. Researchers and Practitioners in the field are looking forward to use ANN and other upcoming AI tools such as Fuzzy-logic, genetic algorithms and artificial intelligence simulation as a promising current and future technology tools towards tackling the global menace of Tuberculosis. Latest advancements in the diagnostic field include the combined use of ANN with various other AI tools like the Fuzzy-logic, which has led to an increase in the efficacy and specificity of the diagnostic techniques. Copyright © 2017 Elsevier Ltd. All rights reserved.