Artificial intelligence in medicine.

PubMed Central

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

2004-01-01

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

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.

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

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.

[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.

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

NASA Technical Reports Server (NTRS)

Swanson, David J.

1990-01-01

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

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)

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.

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)

Keeping Pace with New Technology: An Introduction to Robotics, FORTH, and Artificial Intelligence.

ERIC Educational Resources Information Center

Reck, Gene

A course was developed to introduce students at a community college to four major areas of emphasis in emerging technologies: FORTH programming language, elementary electronic theory, robotics, and artificial intelligence. After a needs assessment indicated the importance of such a course, a pretest focusing on the four areas was given to students…

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

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.

Application of artificial intelligence to the management of urological cancer.

PubMed

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

2007-10-01

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

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.

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.

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

PubMed Central

Contreras, Ivan

2018-01-01

Background Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis. Objective The objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges. Methods A review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review. Results We propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results. Conclusions We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients’ quality of life. PMID:29848472

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…

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)

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--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…

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

[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.

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...

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,…

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 future.

PubMed

Clocksin, William F

2003-08-15

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

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.

PubMed

Contreras, Ivan; Vehi, Josep

2018-05-30

Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis. The objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges. A review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review. We propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results. We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients' quality of life. ©Ivan Contreras, Josep Vehi. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 30.05.2018.

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.

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.

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.

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.

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.

The role of automation and artificial intelligence

NASA Astrophysics Data System (ADS)

Schappell, R. T.

1983-07-01

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

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…

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

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1983-01-01

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

Artificial intelligence 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.

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

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

NASA Technical Reports Server (NTRS)

Wild, Christian; Eckhardt, Dave

1987-01-01

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

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…

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.

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 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.

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 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.

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.

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 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 in Cardiology.

PubMed

Johnson, Kipp W; Torres Soto, Jessica; Glicksberg, Benjamin S; Shameer, Khader; Miotto, Riccardo; Ali, Mohsin; Ashley, Euan; Dudley, Joel T

2018-06-12

Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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

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.

Artificial Intelligence and Virology - quo vadis.

PubMed

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

2017-01-01

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

Artificial Intelligence/Robotics Applications to Navy Aircraft Maintenance.

DTIC Science & Technology

1984-06-01

other automatic machinery such as presses, molding machines , and numerically-controlled machine tools, just as people do. A-36...Robotics Technologies 3 B. Relevant AI Technologies 4 1. Expert Systems 4 2. Automatic Planning 4 3. Natural Language 5 4. Machine Vision...building machines that imitate human behavior. Artificial intelligence is concerned with the functions of the brain, whereas robotics include, in

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…

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...

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)

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.

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…

Artificial Intelligence and Virology - quo vadis

PubMed Central

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

2017-01-01

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

Artificial Intelligence.

PubMed

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

2016-04-01

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

Artificial intelligence technology assessment for the US Army Depot System Command

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

Pennock, K A

1991-07-01

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

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.

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.

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

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.

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

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.

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

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.

Innovative applications of artificial intelligence

NASA Astrophysics Data System (ADS)

Schorr, Herbert; Rappaport, Alain

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

Present situation and trend of precision guidance technology and its intelligence

NASA Astrophysics Data System (ADS)

Shang, Zhengguo; Liu, Tiandong

2017-11-01

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

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

PubMed

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

2007-06-01

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

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.

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.

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

PubMed

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

2017-09-01

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

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)

Trends in telemedicine utilizing artificial intelligence

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Recent developments of artificial intelligence in drying of fresh food: A review.

PubMed

Sun, Qing; Zhang, Min; Mujumdar, Arun S

2018-03-01

Intellectualization is an important direction of drying development and artificial intelligence (AI) technologies have been widely used to solve problems of nonlinear function approximation, pattern detection, data interpretation, optimization, simulation, diagnosis, control, data sorting, clustering, and noise reduction in different food drying technologies due to the advantages of self-learning ability, adaptive ability, strong fault tolerance and high degree robustness to map the nonlinear structures of arbitrarily complex and dynamic phenomena. This article presents a comprehensive review on intelligent drying technologies and their applications. The paper starts with the introduction of basic theoretical knowledge of ANN, fuzzy logic and expert system. Then, we summarize the AI application of modeling, predicting, and optimization of heat and mass transfer, thermodynamic performance parameters, and quality indicators as well as physiochemical properties of dried products in artificial biomimetic technology (electronic nose, computer vision) and different conventional drying technologies. Furthermore, opportunities and limitations of AI technique in drying are also outlined to provide more ideas for researchers in this area.

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

Artificial Intelligence and brain.

PubMed

Shapshak, Paul

2018-01-01

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

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)

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-01-19

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

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.

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

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.

Robotics and artificial intelligence: Jewish ethical perspectives.

PubMed

Rappaport, Z H

2006-01-01

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

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.

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.

Artificial intelligence in hematology.

PubMed

Zini, Gina

2005-10-01

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

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

PubMed

Ashrafian, Hutan; Darzi, Ara; Athanasiou, Thanos

2015-03-01

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

The Roles of Artificial Intelligence in Education: Current Progress and Future Prospects

ERIC Educational Resources Information Center

McArthur, David; Lewis, Matthew; Bishary, Miriam

2005-01-01

This report begins by summarizing current applications of ideas from artificial intelligence (Al) to education. It then uses that summary to project various future applications of Al--and advanced technology in general--to education, as well as highlighting problems that will confront the wide­ scale implementation of these technologies in the…

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.

[Artificial Intelligence in Drug Discovery].

PubMed

Fujiwara, Takeshi; Kamada, Mayumi; Okuno, Yasushi

2018-04-01

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

Artificial Intelligence and Information Management

NASA Astrophysics Data System (ADS)

Fukumura, Teruo

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

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.

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 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…

Artificial intelligence for analyzing orthopedic trauma radiographs.

PubMed

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

2017-12-01

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

[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.

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.

Exodus - Distributed artificial intelligence for Shuttle firing rooms

NASA Technical Reports Server (NTRS)

Heard, Astrid E.

1990-01-01

This paper describes the Expert System for Operations Distributed Users (EXODUS), a knowledge-based artificial intelligence system developed for the four Firing Rooms at the Kennedy Space Center. EXODUS is used by the Shuttle engineers and test conductors to monitor and control the sequence of tasks required for processing and launching Shuttle vehicles. In this paper, attention is given to the goals and the design of EXODUS, the operational requirements, and the extensibility of the technology.

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)

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...

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.

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…

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.

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…

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…

Artificial intelligence and expert systems in-flight software testing

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

[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.

Intelligent systems technology infrastructure for integrated systems

NASA Technical Reports Server (NTRS)

Lum, Henry, Jr.

1991-01-01

Significant advances have occurred during the last decade in intelligent systems technologies (a.k.a. knowledge-based systems, KBS) including research, feasibility demonstrations, and technology implementations in operational environments. Evaluation and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent systems technologies can be realized for Automated Rendezvous and Capture applications. The successful implementation of these technologies involve a complex system infrastructure integrating the requirements of transportation, vehicle checkout and health management, and communication systems without compromise to systems reliability and performance. The resources that must be invoked to accomplish these tasks include remote ground operations and control, built-in system fault management and control, and intelligent robotics. To ensure long-term evolution and integration of new validated technologies over the lifetime of the vehicle, system interfaces must also be addressed and integrated into the overall system interface requirements. An approach for defining and evaluating the system infrastructures including the testbed currently being used to support the on-going evaluations for the evolutionary Space Station Freedom Data Management System is presented and discussed. Intelligent system technologies discussed include artificial intelligence (real-time replanning and scheduling), high performance computational elements (parallel processors, photonic processors, and neural networks), real-time fault management and control, and system software development tools for rapid prototyping capabilities.

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

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)

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.

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.

Use of artificial intelligence to identify cardiovascular compromise in a model of hemorrhagic shock.

PubMed

Glass, Todd F; Knapp, Jason; Amburn, Philip; Clay, Bruce A; Kabrisky, Matt; Rogers, Steven K; Garcia, Victor F

2004-02-01

To determine whether a prototype artificial intelligence system can identify volume of hemorrhage in a porcine model of controlled hemorrhagic shock. Prospective in vivo animal model of hemorrhagic shock. Research foundation animal surgical suite; computer laboratories of collaborating industry partner. Nineteen, juvenile, 25- to 35-kg, male and female swine. Anesthetized animals were instrumented for arterial and systemic venous pressure monitoring and blood sampling, and a splenectomy was performed. Following a 1-hr stabilization period, animals were hemorrhaged in aliquots to 10, 20, 30, 35, 40, 45, and 50% of total blood volume with a 10-min recovery between each aliquot. Data were downloaded directly from a commercial monitoring system into a proprietary PC-based software package for analysis. Arterial and venous blood gas values, glucose, and cardiac output were collected at specified intervals. Electrocardiogram, electroencephalogram, mixed venous oxygen saturation, temperature (core and blood), mean arterial pressure, pulmonary artery pressure, central venous pressure, pulse oximetry, and end-tidal CO(2) were continuously monitored and downloaded. Seventeen of 19 animals (89%) died as a direct result of hemorrhage. Stored data streams were analyzed by the prototype artificial intelligence system. For this project, the artificial intelligence system identified and compared three electrocardiographic features (R-R interval, QRS amplitude, and R-S interval) from each of nine unknown samples of the QRS complex. We found that the artificial intelligence system, trained on only three electrocardiographic features, identified hemorrhage volume with an average accuracy of 91% (95% confidence interval, 84-96%). These experiments demonstrate that an artificial intelligence system, based solely on the analysis of QRS amplitude, R-R interval, and R-S interval of an electrocardiogram, is able to accurately identify hemorrhage volume in a porcine model of lethal

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.

Artificial intelligence for analyzing orthopedic trauma radiographs

PubMed Central

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

2017-01-01

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

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 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.

Artificial intelligence approaches to software engineering

NASA Technical Reports Server (NTRS)

Johannes, James D.; Macdonald, James R.

1988-01-01

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

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.

Neuroscience-Inspired Artificial Intelligence.

PubMed

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

2017-07-19

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

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.

The Use of Video Technology for the Fast-Prototyping of Artificially Intelligent Software.

ERIC Educational Resources Information Center

Klein, Gary L.

This paper describes the use of video to provide a screenplay depiction of a proposed artificial intelligence software system. Advantages of such use are identified: (1) the video can be used to provide a clear conceptualization of the proposed system; (2) it can illustrate abstract technical concepts; (3) it can simulate the functions of the…

Analysis of optoelectronic strategic planning in Taiwan by artificial intelligence portfolio tool

NASA Astrophysics Data System (ADS)

Chang, Rang-Seng

1992-05-01

Taiwan ROC has achieved significant advances in the optoelectronic industry with some Taiwan products ranked high in the world market and technology. Six segmentations of optoelectronic were planned. Each one was divided into several strategic items, design artificial intelligent portfolio tool (AIPT) to analyze the optoelectronic strategic planning in Taiwan. The portfolio is designed to provoke strategic thinking intelligently. This computer- generated strategy should be selected and modified by the individual. Some strategies for the development of the Taiwan optoelectronic industry also are discussed in this paper.

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: 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 guides system's best practices, cutting costs and improving services.

PubMed

1999-06-01

One for the history books. Clinical care improvement initiatives guided by a sophisticated artificial intelligence program have helped a major Virginia integrated health system make dramatic improvements in the cost and quality of its health care services. Find out how the technological innovation has earned Sentara Health System a place in the permanent collection of the Smithsonian's National Museum of American History.

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 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…

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…

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…

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…

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

Artificial intelligence approaches for rational drug design and discovery.

PubMed

Duch, Włodzisław; Swaminathan, Karthikeyan; Meller, Jarosław

2007-01-01

Pattern recognition, machine learning and artificial intelligence approaches play an increasingly important role in rational drug design, screening and identification of candidate molecules and studies on quantitative structure-activity relationships (QSAR). In this review, we present an overview of basic concepts and methodology in the fields of machine learning and artificial intelligence (AI). An emphasis is put on methods that enable an intuitive interpretation of the results and facilitate gaining an insight into the structure of the problem at hand. We also discuss representative applications of AI methods to docking, screening and QSAR studies. The growing trend to integrate computational and experimental efforts in that regard and some future developments are discussed. In addition, we comment on a broader role of machine learning and artificial intelligence approaches in biomedical research.

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).

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.

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…

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.

Clinical Note Creation, Binning, and Artificial Intelligence

PubMed Central

Deliberato, Rodrigo Octávio; Stone, David J

2017-01-01

The creation of medical notes in software applications poses an intrinsic problem in workflow as the technology inherently intervenes in the processes of collecting and assembling information, as well as the production of a data-driven note that meets both individual and healthcare system requirements. In addition, the note writing applications in currently available electronic health records (EHRs) do not function to support decision making to any substantial degree. We suggest that artificial intelligence (AI) could be utilized to facilitate the workflows of the data collection and assembly processes, as well as to support the development of personalized, yet data-driven assessments and plans. PMID:28778845

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: 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)

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 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.

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.

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.

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.

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.

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…

Artificial Intelligence-Based Semantic Internet of Things in a User-Centric Smart City

PubMed Central

Guo, Kun; Lu, Yueming; Gao, Hui; Cao, Ruohan

2018-01-01

Smart city (SC) technologies can provide appropriate services according to citizens’ demands. One of the key enablers in a SC is the Internet of Things (IoT) technology, which enables a massive number of devices to connect with each other. However, these devices usually come from different manufacturers with different product standards, which confront interactive control problems. Moreover, these devices will produce large amounts of data, and efficiently analyzing these data for intelligent services. In this paper, we propose a novel artificial intelligence-based semantic IoT (AI-SIoT) hybrid service architecture to integrate heterogeneous IoT devices to support intelligent services. In particular, the proposed architecture is empowered by semantic and AI technologies, which enable flexible connections among heterogeneous devices. The AI technology can support very implement efficient data analysis and make accurate decisions on service provisions in various kinds. Furthermore, we also present several practical use cases of the proposed AI-SIoT architecture and the opportunities and challenges to implement the proposed AI-SIoT for future SCs are also discussed. PMID:29701679

Artificial Intelligence-Based Semantic Internet of Things in a User-Centric Smart City.

PubMed

Guo, Kun; Lu, Yueming; Gao, Hui; Cao, Ruohan

2018-04-26

Smart city (SC) technologies can provide appropriate services according to citizens’ demands. One of the key enablers in a SC is the Internet of Things (IoT) technology, which enables a massive number of devices to connect with each other. However, these devices usually come from different manufacturers with different product standards, which confront interactive control problems. Moreover, these devices will produce large amounts of data, and efficiently analyzing these data for intelligent services. In this paper, we propose a novel artificial intelligence-based semantic IoT (AI-SIoT) hybrid service architecture to integrate heterogeneous IoT devices to support intelligent services. In particular, the proposed architecture is empowered by semantic and AI technologies, which enable flexible connections among heterogeneous devices. The AI technology can support very implement efficient data analysis and make accurate decisions on service provisions in various kinds. Furthermore, we also present several practical use cases of the proposed AI-SIoT architecture and the opportunities and challenges to implement the proposed AI-SIoT for future SCs are also discussed.

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

Systematic review of dermoscopy and digital dermoscopy/ artificial intelligence for the diagnosis of melanoma.

PubMed

Rajpara, S M; Botello, A P; Townend, J; Ormerod, A D

2009-09-01

Dermoscopy improves diagnostic accuracy of the unaided eye for melanoma, and digital dermoscopy with artificial intelligence or computer diagnosis has also been shown useful for the diagnosis of melanoma. At present there is no clear evidence regarding the diagnostic accuracy of dermoscopy compared with artificial intelligence. To evaluate the diagnostic accuracy of dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis and to compare the diagnostic accuracy of the different dermoscopic algorithms with each other and with digital dermoscopy/artificial intelligence for the detection of melanoma. A literature search on dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis was performed using several databases. Titles and abstracts of the retrieved articles were screened using a literature evaluation form. A quality assessment form was developed to assess the quality of the included studies. Heterogeneity among the studies was assessed. Pooled data were analysed using meta-analytical methods and comparisons between different algorithms were performed. Of 765 articles retrieved, 30 studies were eligible for meta-analysis. Pooled sensitivity for artificial intelligence was slightly higher than for dermoscopy (91% vs. 88%; P = 0.076). Pooled specificity for dermoscopy was significantly better than artificial intelligence (86% vs. 79%; P < 0.001). Pooled diagnostic odds ratio was 51.5 for dermoscopy and 57.8 for artificial intelligence, which were not significantly different (P = 0.783). There were no significance differences in diagnostic odds ratio among the different dermoscopic diagnostic algorithms. Dermoscopy and artificial intelligence performed equally well for diagnosis of melanocytic skin lesions. There was no significant difference in the diagnostic performance of various dermoscopy algorithms. The three-point checklist, the seven-point checklist and Menzies score had better diagnostic odds ratios than the

Demonstrating artificial intelligence for space systems - Integration and project management issues

NASA Technical Reports Server (NTRS)

Hack, Edmund C.; Difilippo, Denise M.

1990-01-01

As part of its Systems Autonomy Demonstration Project (SADP), NASA has recently demonstrated the Thermal Expert System (TEXSYS). Advanced real-time expert system and human interface technology was successfully developed and integrated with conventional controllers of prototype space hardware to provide intelligent fault detection, isolation, and recovery capability. Many specialized skills were required, and responsibility for the various phases of the project therefore spanned multiple NASA centers, internal departments and contractor organizations. The test environment required communication among many types of hardware and software as well as between many people. The integration, testing, and configuration management tools and methodologies which were applied to the TEXSYS project to assure its safe and successful completion are detailed. The project demonstrated that artificial intelligence technology, including model-based reasoning, is capable of the monitoring and control of a large, complex system in real time.

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

PubMed

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

2012-01-01

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

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

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

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…

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

Artificial intelligence in medicine: the challenges ahead.

PubMed Central

Coiera, E W

1996-01-01

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

Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy.

PubMed

Labovitz, Daniel L; Shafner, Laura; Reyes Gil, Morayma; Virmani, Deepti; Hanina, Adam

2017-05-01

This study evaluated the use of an artificial intelligence platform on mobile devices in measuring and increasing medication adherence in stroke patients on anticoagulation therapy. The introduction of direct oral anticoagulants, while reducing the need for monitoring, have also placed pressure on patients to self-manage. Suboptimal adherence goes undetected as routine laboratory tests are not reliable indicators of adherence, placing patients at increased risk of stroke and bleeding. A randomized, parallel-group, 12-week study was conducted in adults (n=28) with recently diagnosed ischemic stroke receiving any anticoagulation. Patients were randomized to daily monitoring by the artificial intelligence platform (intervention) or to no daily monitoring (control). The artificial intelligence application visually identified the patient, the medication, and the confirmed ingestion. Adherence was measured by pill counts and plasma sampling in both groups. For all patients (n=28), mean (SD) age was 57 years (13.2 years) and 53.6% were women. Mean (SD) cumulative adherence based on the artificial intelligence platform was 90.5% (7.5%). Plasma drug concentration levels indicated that adherence was 100% (15 of 15) and 50% (6 of 12) in the intervention and control groups, respectively. Patients, some with little experience using a smartphone, successfully used the technology and demonstrated a 50% improvement in adherence based on plasma drug concentration levels. For patients receiving direct oral anticoagulants, absolute improvement increased to 67%. Real-time monitoring has the potential to increase adherence and change behavior, particularly in patients on direct oral anticoagulant therapy. URL: http://www.clinicaltrials.gov. Unique identifier: NCT02599259. © 2017 American Heart Association, Inc.

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.

Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

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

Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2003-01-01

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

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

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…

Artificial intelligence costs, benefits, risks for selected spacecraft ground system automation scenarios

NASA Technical Reports Server (NTRS)

Truszkowski, Walter F.; Silverman, Barry G.; Kahn, Martha; Hexmoor, Henry

1988-01-01

In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline), (2) standalone expert systems, (3) standardized, reusable knowledge base management systems (KBMS), and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

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)

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

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.

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.

Training Software in Artificial-Intelligence Computing Techniques

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

2005-01-01

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

Forecasting daily lake levels using artificial intelligence approaches

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Shiri, Jalal; Nikoofar, Bagher

2012-04-01

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

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.…

[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.

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)

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

Artificial intelligence - NASA. [robotics for Space Station

NASA Technical Reports Server (NTRS)

Erickson, J. D.

1985-01-01

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

Multisensor system and artificial intelligence in housing for the elderly.

PubMed

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

1998-01-01

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

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…

Enabling Autonomous Space Mission Operations with Artificial Intelligence

NASA Technical Reports Server (NTRS)

Frank, Jeremy

2017-01-01

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

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…

Automated Scheduling Via Artificial Intelligence

NASA Technical Reports Server (NTRS)

Biefeld, Eric W.; Cooper, Lynne P.

1991-01-01

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

Artificial intelligence costs, benefits, and risks for selected spacecraft ground system automation scenarios

NASA Technical Reports Server (NTRS)

Truszkowski, Walter F.; Silverman, Barry G.; Kahn, Martha; Hexmoor, Henry

1988-01-01

In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline); (2) standalone expert systems; (3) standardized, reusable knowledge base management systems (KBMS); and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET)

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

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…

Clinical Note Creation, Binning, and Artificial Intelligence.

PubMed

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

2017-08-03

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

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.

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

Applications of artificial intelligence to scientific research

NASA Technical Reports Server (NTRS)

Prince, Mary Ellen

1986-01-01

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

Implementing Artificial Intelligence Behaviors in a Virtual World

NASA Technical Reports Server (NTRS)

Krisler, Brian; Thome, Michael

2012-01-01

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

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.

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…

Electron beam lithographic modeling assisted by artificial intelligence technology

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

An intelligent remote monitoring system for artificial heart.

PubMed

Choi, Jaesoon; Park, Jun W; Chung, Jinhan; Min, Byoung G

2005-12-01

A web-based database system for intelligent remote monitoring of an artificial heart has been developed. It is important for patients with an artificial heart implant to be discharged from the hospital after an appropriate stabilization period for better recovery and quality of life. Reliable continuous remote monitoring systems for these patients with life support devices are gaining practical meaning. The authors have developed a remote monitoring system for this purpose that consists of a portable/desktop monitoring terminal, a database for continuous recording of patient and device status, a web-based data access system with which clinicians can access real-time patient and device status data and past history data, and an intelligent diagnosis algorithm module that noninvasively estimates blood pump output and makes automatic classification of the device status. The system has been tested with data generation emulators installed on remote sites for simulation study, and in two cases of animal experiments conducted at remote facilities. The system showed acceptable functionality and reliability. The intelligence algorithm also showed acceptable practicality in an application to animal experiment data.

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.

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

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)

Synthetic biology routes to bio-artificial intelligence

PubMed Central

Zaikin, Alexey; Saka, Yasushi; Romano, M. Carmen; Giuraniuc, Claudiu V.; Kanakov, Oleg; Laptyeva, Tetyana

2016-01-01

The design of synthetic gene networks (SGNs) has advanced to the extent that novel genetic circuits are now being tested for their ability to recapitulate archetypal learning behaviours first defined in the fields of machine and animal learning. Here, we discuss the biological implementation of a perceptron algorithm for linear classification of input data. An expansion of this biological design that encompasses cellular ‘teachers’ and ‘students’ is also examined. We also discuss implementation of Pavlovian associative learning using SGNs and present an example of such a scheme and in silico simulation of its performance. In addition to designed SGNs, we also consider the option to establish conditions in which a population of SGNs can evolve diversity in order to better contend with complex input data. Finally, we compare recent ethical concerns in the field of artificial intelligence (AI) and the future challenges raised by bio-artificial intelligence (BI). PMID:27903825

Artificial intelligence: contemporary applications and future compass.

PubMed

Khanna, Sunali

2010-08-01

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

Automatic food detection in egocentric images using artificial intelligence technology.

PubMed

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

2018-03-26

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

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…

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.

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.

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

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

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 and its impact on combat aircraft

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

Anesthesiology, automation, and artificial intelligence.

PubMed

Alexander, John C; Joshi, Girish P

2018-01-01

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

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.

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.

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

ERIC Educational Resources Information Center

Sayre, Scott Alan

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

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)

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.

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

Biologically inspired technologies using artificial muscles

NASA Astrophysics Data System (ADS)

Bar-Cohen, Yoseph

2005-01-01

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

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.…

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

Artificial intelligence in the diagnosis of low back pain.

PubMed

Mann, N H; Brown, M D

1991-04-01

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

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

Anesthesiology, automation, and artificial intelligence

PubMed Central

Alexander, John C.; Joshi, Girish P.

2018-01-01

ABSTRACT There have been many attempts to incorporate automation into the practice of anesthesiology, though none have been successful. Fundamentally, these failures are due to the underlying complexity of anesthesia practice and the inability of rule-based feedback loops to fully master it. Recent innovations in artificial intelligence, especially machine learning, may usher in a new era of automation across many industries, including anesthesiology. It would be wise to consider the implications of such potential changes before they have been fully realized. PMID:29686578

Research and applications: Artificial intelligence

NASA Technical Reports Server (NTRS)

Raphael, B.; Duda, R. O.; Fikes, R. E.; Hart, P. E.; Nilsson, N. J.; Thorndyke, P. W.; Wilber, B. M.

1971-01-01

Research in the field of artificial intelligence is discussed. The focus of recent work has been the design, implementation, and integration of a completely new system for the control of a robot that plans, learns, and carries out tasks autonomously in a real laboratory environment. The computer implementation of low-level and intermediate-level actions; routines for automated vision; and the planning, generalization, and execution mechanisms are reported. A scenario that demonstrates the approximate capabilities of the current version of the entire robot system is presented.

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.

Synthetic biology routes to bio-artificial intelligence.

PubMed

Nesbeth, Darren N; Zaikin, Alexey; Saka, Yasushi; Romano, M Carmen; Giuraniuc, Claudiu V; Kanakov, Oleg; Laptyeva, Tetyana

2016-11-30

The design of synthetic gene networks (SGNs) has advanced to the extent that novel genetic circuits are now being tested for their ability to recapitulate archetypal learning behaviours first defined in the fields of machine and animal learning. Here, we discuss the biological implementation of a perceptron algorithm for linear classification of input data. An expansion of this biological design that encompasses cellular 'teachers' and 'students' is also examined. We also discuss implementation of Pavlovian associative learning using SGNs and present an example of such a scheme and in silico simulation of its performance. In addition to designed SGNs, we also consider the option to establish conditions in which a population of SGNs can evolve diversity in order to better contend with complex input data. Finally, we compare recent ethical concerns in the field of artificial intelligence (AI) and the future challenges raised by bio-artificial intelligence (BI). © 2016 The Author(s). This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).

"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,…

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.

Exploring expressivity and emotion with artificial voice and speech technologies.

PubMed

Pauletto, Sandra; Balentine, Bruce; Pidcock, Chris; Jones, Kevin; Bottaci, Leonardo; Aretoulaki, Maria; Wells, Jez; Mundy, Darren P; Balentine, James

2013-10-01

Emotion in audio-voice signals, as synthesized by text-to-speech (TTS) technologies, was investigated to formulate a theory of expression for user interface design. Emotional parameters were specified with markup tags, and the resulting audio was further modulated with post-processing techniques. Software was then developed to link a selected TTS synthesizer with an automatic speech recognition (ASR) engine, producing a chatbot that could speak and listen. Using these two artificial voice subsystems, investigators explored both artistic and psychological implications of artificial speech emotion. Goals of the investigation were interdisciplinary, with interest in musical composition, augmentative and alternative communication (AAC), commercial voice announcement applications, human-computer interaction (HCI), and artificial intelligence (AI). The work-in-progress points towards an emerging interdisciplinary ontology for artificial voices. As one study output, HCI tools are proposed for future collaboration.

The Seeds of Artificial Intelligence. SUMEX-AIM.

ERIC Educational Resources Information Center

Research Resources Information Center, Rockville, MD.

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

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.

A development framework for artificial intelligence based distributed operations support systems

NASA Technical Reports Server (NTRS)

Adler, Richard M.; Cottman, Bruce H.

1990-01-01

Advanced automation is required to reduce costly human operations support requirements for complex space-based and ground control systems. Existing knowledge based technologies have been used successfully to automate individual operations tasks. Considerably less progress has been made in integrating and coordinating multiple operations applications for unified intelligent support systems. To fill this gap, SOCIAL, a tool set for developing Distributed Artificial Intelligence (DAI) systems is being constructed. SOCIAL consists of three primary language based components defining: models of interprocess communication across heterogeneous platforms; models for interprocess coordination, concurrency control, and fault management; and for accessing heterogeneous information resources. DAI applications subsystems, either new or existing, will access these distributed services non-intrusively, via high-level message-based protocols. SOCIAL will reduce the complexity of distributed communications, control, and integration, enabling developers to concentrate on the design and functionality of the target DAI system itself.

Artificial intelligence in medicine.

PubMed

Hamet, Pavel; Tremblay, Johanne

2017-04-01

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

Intelligent Technologies in Library and Information Service Applications. ASIST Monograph Series.

ERIC Educational Resources Information Center

Lancaster, F. W.; Warner, Amy

The objective of this study was to gain enough familiarity with developments in artificial intelligence (AI) and related technologies to be able to advise the information service community on what can be applied today and what one might reasonably expect to be applicable to library and information services in the near future. The emphasis is on…

Artificial intelligence for turboprop engine maintenance

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

NONE

1995-01-01

Long-term maintenance operations, causing the unit to out of action, may seem economical - but they result in reduced operating readiness. Offsetting that concern, careless, hurried maintenance reduces margins of safety and reliability. Any tool that improves maintenance without causing a sharp increase in cost is valuable. Artificial intelligence (AI) is one of the tools. Expert system and neural networks are two different areas of AI that show promise for turboprop engine maintenance.

Applications of Artificial Intelligence to the Strategic Defense Initiative’s Battle Management/Command and Control Objective.

DTIC Science & Technology

1985-09-01

technology issue is expected to take years of research (20:11). According to Lt Gen James A. Abrahamson, director of the SDI organization heading up...from occurring (14:79). A Wqhite House Panel known as the (Dr. James ) Fletcher Defensive Technologies Study Group has pointed out that, in the past...Handbook of Artificial Intelligence. Volume I. Los Altos CA: WilliamKaufmann Inc., 1981. 5. Basden , Andrew. "On the Application of Expert Systems,N

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

Space station automation: the role of robotics and artificial intelligence (Invited Paper)

NASA Astrophysics Data System (ADS)

Park, W. T.; Firschein, O.

1985-12-01

Automation of the space station is necessary to make more effective use of the crew, to carry out repairs that are impractical or dangerous, and to monitor and control the many space station subsystems. Intelligent robotics and expert systems play a strong role in automation, and both disciplines are highly dependent on a common artificial intelligence (Al) technology base. The AI technology base provides the reasoning and planning capabilities needed in robotic tasks, such as perception of the environment and planning a path to a goal, and in expert systems tasks, such as control of subsystems and maintenance of equipment. This paper describes automation concepts for the space station, the specific robotic and expert systems required to attain this automation, and the research and development required. It also presents an evolutionary development plan that leads to fully automatic mobile robots for servicing satellites. Finally, we indicate the sequence of demonstrations and the research and development needed to confirm the automation capabilities. We emphasize that advanced robotics requires AI, and that to advance, AI needs the "real-world" problems provided by robotics.

Developing Applications of Artificial Intelligence Technology To Provide Consultative Support in the Use of Research Methodology by Practitioners.

ERIC Educational Resources Information Center

Vitale, Michael R.; Romance, Nancy

Adopting perspectives based on applications of artificial intelligence proven in industry, this paper discusses methodological strategies and issues that underlie the development of such software environments. The general concept of an expert system is discussed in the context of its relevance to the problem of increasing the accessibility of…

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.

Using artificial intelligence to automate remittance processing.

PubMed

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

1998-06-01

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

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.

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…

Artificial Intelligence and the High School Computer Curriculum.

ERIC Educational Resources Information Center

Dillon, Richard W.

1993-01-01

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

A Novel Artificial Intelligence System for Endotracheal Intubation.

PubMed

Carlson, Jestin N; Das, Samarjit; De la Torre, Fernando; Frisch, Adam; Guyette, Francis X; Hodgins, Jessica K; Yealy, Donald M

2016-01-01

Adequate visualization of the glottic opening is a key factor to successful endotracheal intubation (ETI); however, few objective tools exist to help guide providers' ETI attempts toward the glottic opening in real-time. Machine learning/artificial intelligence has helped to automate the detection of other visual structures but its utility with ETI is unknown. We sought to test the accuracy of various computer algorithms in identifying the glottic opening, creating a tool that could aid successful intubation. We collected a convenience sample of providers who each performed ETI 10 times on a mannequin using a video laryngoscope (C-MAC, Karl Storz Corp, Tuttlingen, Germany). We recorded each attempt and reviewed one-second time intervals for the presence or absence of the glottic opening. Four different machine learning/artificial intelligence algorithms analyzed each attempt and time point: k-nearest neighbor (KNN), support vector machine (SVM), decision trees, and neural networks (NN). We used half of the videos to train the algorithms and the second half to test the accuracy, sensitivity, and specificity of each algorithm. We enrolled seven providers, three Emergency Medicine attendings, and four paramedic students. From the 70 total recorded laryngoscopic video attempts, we created 2,465 time intervals. The algorithms had the following sensitivity and specificity for detecting the glottic opening: KNN (70%, 90%), SVM (70%, 90%), decision trees (68%, 80%), and NN (72%, 78%). Initial efforts at computer algorithms using artificial intelligence are able to identify the glottic opening with over 80% accuracy. With further refinements, video laryngoscopy has the potential to provide real-time, direction feedback to the provider to help guide successful ETI.

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…

Innovative intelligent technology of distance learning for visually impaired people

NASA Astrophysics Data System (ADS)

Samigulina, Galina; Shayakhmetova, Assem; Nuysuppov, Adlet

2017-12-01

The aim of the study is to develop innovative intelligent technology and information systems of distance education for people with impaired vision (PIV). To solve this problem a comprehensive approach has been proposed, which consists in the aggregate of the application of artificial intelligence methods and statistical analysis. Creating an accessible learning environment, identifying the intellectual, physiological, psychophysiological characteristics of perception and information awareness by this category of people is based on cognitive approach. On the basis of fuzzy logic the individually-oriented learning path of PIV is con- structed with the aim of obtaining high-quality engineering education with modern equipment in the joint use laboratories.

Artificial Intelligence Applications to Maintenance Technology Working Group Report (IDA/OSD R&M (Institute for Defense Analyses/Office of the Secretary of Defense Reliability and Maintainability) Study).

DTIC Science & Technology

1983-08-01

Research and Engineering and Office of the Assistant Secretary of Defense (Mw Reserve Affairs and Logistics) 1WTITR#OR DEFENSE ANALYSES ~~’AND... TITLE (and Subdlee) S.TYPE OF REPORT & PERIOD COVERED Final Artificial Intelligence Applications to Main- July 1982 - August 1983 tenance Technology...of DoD (Short Title : R&M Study). This task order was structured to address the improvement of R&M and readiness through innovative program structuring

Economic reasoning and artificial intelligence.

PubMed

Parkes, David C; Wellman, Michael P

2015-07-17

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

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.

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

Intelligent Information Systems.

ERIC Educational Resources Information Center

Zabezhailo, M. I.; Finn, V. K.

1996-01-01

An Intelligent Information System (IIS) uses data warehouse technology to facilitate the cycle of data and knowledge processing, including input, standardization, storage, representation, retrieval, calculation, and delivery. This article provides an overview of IIS products and artificial intelligence systems, illustrates examples of IIS…

Artificial Intelligence Research Branch future plans

NASA Technical Reports Server (NTRS)

Stewart, Helen (Editor)

1992-01-01

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

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 ...

Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

PubMed

Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

2017-12-01

To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

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.

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…

Space Communications Artificial Intelligence for Link Evaluation Terminal (SCAILET)

NASA Technical Reports Server (NTRS)

Shahidi, Anoosh

1991-01-01

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

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

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)

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.

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.

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.

Artificial intelligence and space power systems automation

NASA Technical Reports Server (NTRS)

Weeks, David J.

1987-01-01

Various applications of artificial intelligence to space electrical power systems are discussed. An overview is given of completed, on-going, and planned knowledge-based system activities. These applications include the Nickel-Cadmium Battery Expert System (NICBES) (the expert system interfaced with the Hubble Space Telescope electrical power system test bed); the early work with the Space Station Experiment Scheduler (SSES); the three expert systems under development in the space station advanced development effort in the core module power management and distribution system test bed; planned cooperation of expert systems in the Core Module Power Management and Distribution (CM/PMAD) system breadboard with expert systems for the space station at other research centers; and the intelligent data reduction expert system under development.

Artificial intelligence support for scientific model-building

NASA Technical Reports Server (NTRS)

Keller, Richard M.

1992-01-01

Scientific model-building can be a time-intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientific development team to understand. We believe that artificial intelligence techniques can facilitate both the model-building and model-sharing process. In this paper, we overview our effort to build a scientific modeling software tool that aids the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high-level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities.

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.

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.

Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer.

PubMed

Enshaei, A; Robson, C N; Edmondson, R J

2015-11-01

The ability to provide accurate prognostic and predictive information to patients is becoming increasingly important as clinicians enter an era of personalized medicine. For a disease as heterogeneous as epithelial ovarian cancer, conventional algorithms become too complex for routine clinical use. This study therefore investigated the potential for an artificial intelligence model to provide this information and compared it with conventional statistical approaches. The authors created a database comprising 668 cases of epithelial ovarian cancer during a 10-year period and collected data routinely available in a clinical environment. They also collected survival data for all the patients, then constructed an artificial intelligence model capable of comparing a variety of algorithms and classifiers alongside conventional statistical approaches such as logistic regression. The model was used to predict overall survival and demonstrated that an artificial neural network (ANN) algorithm was capable of predicting survival with high accuracy (93 %) and an area under the curve (AUC) of 0.74 and that this outperformed logistic regression. The model also was used to predict the outcome of surgery and again showed that ANN could predict outcome (complete/optimal cytoreduction vs. suboptimal cytoreduction) with 77 % accuracy and an AUC of 0.73. These data are encouraging and demonstrate that artificial intelligence systems may have a role in providing prognostic and predictive data for patients. The performance of these systems likely will improve with increasing data set size, and this needs further investigation.

Non-Newtonian Aspects of Artificial Intelligence

NASA Astrophysics Data System (ADS)

Zak, Michail

2016-05-01

The challenge of this work is to connect physics with the concept of intelligence. By intelligence we understand a capability to move from disorder to order without external resources, i.e., in violation of the second law of thermodynamics. The objective is to find such a mathematical object described by ODE that possesses such a capability. The proposed approach is based upon modification of the Madelung version of the Schrodinger equation by replacing the force following from quantum potential with non-conservative forces that link to the concept of information. A mathematical formalism suggests that a hypothetical intelligent particle, besides the capability to move against the second law of thermodynamics, acquires such properties like self-image, self-awareness, self-supervision, etc. that are typical for Livings. However since this particle being a quantum-classical hybrid acquires non-Newtonian and non-quantum properties, it does not belong to the physics matter as we know it: the modern physics should be complemented with the concept of the information force that represents a bridge to intelligent particle. As a follow-up of the proposed concept, the following question is addressed: can artificial intelligence (AI) system composed only of physical components compete with a human? The answer is proven to be negative if the AI system is based only on simulations, and positive if digital devices are included. It has been demonstrated that there exists such a quantum neural net that performs simulations combined with digital punctuations. The universality of this quantum-classical hybrid is in capability to violate the second law of thermodynamics by moving from disorder to order without external resources. This advanced capability is illustrated by examples. In conclusion, a mathematical machinery of the perception that is the fundamental part of a cognition process as well as intelligence is introduced and discussed.

Evolution and Revolution in Artificial Intelligence in Education

ERIC Educational Resources Information Center

Roll, Ido; Wylie, Ruth

2016-01-01

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

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.

Artificial Intelligence in Surgery: Promises and Perils.

PubMed

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

2018-07-01

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

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.

Epistasis analysis using artificial intelligence.

PubMed

Moore, Jason H; Hill, Doug P

2015-01-01

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

Artificial intelligence. Fears of an AI pioneer.

PubMed

Russell, Stuart; Bohannon, John

2015-07-17

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

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 Application in Power Generation Industry: Initial considerations

NASA Astrophysics Data System (ADS)

Ismail, Rahmat Izaizi B.; Ismail Alnaimi, Firas B.; AL-Qrimli, Haidar F.

2016-03-01

With increased competitiveness in power generation industries, more resources are directed in optimizing plant operation, including fault detection and diagnosis. One of the most powerful tools in faults detection and diagnosis is artificial intelligence (AI). Faults should be detected early so correct mitigation measures can be taken, whilst false alarms should be eschewed to avoid unnecessary interruption and downtime. For the last few decades there has been major interest towards intelligent condition monitoring system (ICMS) application in power plant especially with AI development particularly in artificial neural network (ANN). ANN is based on quite simple principles, but takes advantage of their mathematical nature, non-linear iteration to demonstrate powerful problem solving ability. With massive possibility and room for improvement in AI, the inspiration for researching them are apparent, and literally, hundreds of papers have been published, discussing the findings of hybrid AI for condition monitoring purposes. In this paper, the studies of ANN and genetic algorithm (GA) application will be presented.

Groundhog Day for Medical Artificial Intelligence.

PubMed

London, Alex John

2018-05-01

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

The Bright, Artificial Intelligence-Augmented Future of Neuroimaging Reading

PubMed Central

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

2017-01-01

Radiologists are among the first physicians to be directly affected by advances in computer technology. Computers are already capable of analyzing medical imaging data, and with decades worth of digital information available for training, will an artificial intelligence (AI) one day signal the end of the human radiologist? With the ever increasing work load combined with the looming doctor shortage, radiologists will be pushed far beyond their current estimated 3 s allotted time-of-analysis per image; an AI with super-human capabilities might seem like a logical replacement. We feel, however, that AI will lead to an augmentation rather than a replacement of the radiologist. The AI will be relied upon to handle the tedious, time-consuming tasks of detecting and segmenting outliers while possibly generating new, unanticipated results that can then be used as sources of medical discovery. This will affect not only radiologists but all physicians and also researchers dealing with medical imaging. Therefore, we must embrace future technology and collaborate interdisciplinary to spearhead the next revolution in medicine. PMID:28983278

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

PubMed

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

2017-01-01

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

[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.

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…

Software for Intelligent System Health Management

NASA Technical Reports Server (NTRS)

Trevino, Luis C.

2004-01-01

This viewgraph presentation describes the characteristics and advantages of autonomy and artificial intelligence in systems health monitoring. The presentation lists technologies relevant to Intelligent System Health Management (ISHM), and some potential applications.

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)

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

PubMed

Campbell, Sarah

2015-01-01

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

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.

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.

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…

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.

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

PubMed

Ensmenger, Nathan

2012-02-01

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

Validating a UAV artificial intelligence control system using an autonomous test case generator

NASA Astrophysics Data System (ADS)

Straub, Jeremy; Huber, Justin

2013-05-01

The validation of safety-critical applications, such as autonomous UAV operations in an environment which may include human actors, is an ill posed problem. To confidence in the autonomous control technology, numerous scenarios must be considered. This paper expands upon previous work, related to autonomous testing of robotic control algorithms in a two dimensional plane, to evaluate the suitability of similar techniques for validating artificial intelligence control in three dimensions, where a minimum level of airspeed must be maintained. The results of human-conducted testing are compared to this automated testing, in terms of error detection, speed and testing cost.

Connecting Technological Innovation in Artificial Intelligence to Real-world Medical Practice through Rigorous Clinical Validation: What Peer-reviewed Medical Journals Could Do

PubMed Central

2018-01-01

Artificial intelligence (AI) is projected to substantially influence clinical practice in the foreseeable future. However, despite the excitement around the technologies, it is yet rare to see examples of robust clinical validation of the technologies and, as a result, very few are currently in clinical use. A thorough, systematic validation of AI technologies using adequately designed clinical research studies before their integration into clinical practice is critical to ensure patient benefit and safety while avoiding any inadvertent harms. We would like to suggest several specific points regarding the role that peer-reviewed medical journals can play, in terms of study design, registration, and reporting, to help achieve proper and meaningful clinical validation of AI technologies designed to make medical diagnosis and prediction, focusing on the evaluation of diagnostic accuracy efficacy. Peer-reviewed medical journals can encourage investigators who wish to validate the performance of AI systems for medical diagnosis and prediction to pay closer attention to the factors listed in this article by emphasizing their importance. Thereby, peer-reviewed medical journals can ultimately facilitate translating the technological innovations into real-world practice while securing patient safety and benefit. PMID:29805337

Connecting Technological Innovation in Artificial Intelligence to Real-world Medical Practice through Rigorous Clinical Validation: What Peer-reviewed Medical Journals Could Do.

PubMed

Park, Seong Ho; Kressel, Herbert Y

2018-05-28

Artificial intelligence (AI) is projected to substantially influence clinical practice in the foreseeable future. However, despite the excitement around the technologies, it is yet rare to see examples of robust clinical validation of the technologies and, as a result, very few are currently in clinical use. A thorough, systematic validation of AI technologies using adequately designed clinical research studies before their integration into clinical practice is critical to ensure patient benefit and safety while avoiding any inadvertent harms. We would like to suggest several specific points regarding the role that peer-reviewed medical journals can play, in terms of study design, registration, and reporting, to help achieve proper and meaningful clinical validation of AI technologies designed to make medical diagnosis and prediction, focusing on the evaluation of diagnostic accuracy efficacy. Peer-reviewed medical journals can encourage investigators who wish to validate the performance of AI systems for medical diagnosis and prediction to pay closer attention to the factors listed in this article by emphasizing their importance. Thereby, peer-reviewed medical journals can ultimately facilitate translating the technological innovations into real-world practice while securing patient safety and benefit.

Selective Snapshot of State-of-the-Art Artificial Intelligence & Robotics with Reference to the Icarus Starship

NASA Astrophysics Data System (ADS)

Ellery, A.

Since the remarkable British Interplanetary Society starship study of the late 1970s - Daedalus - there have been significant developments in the areas of artificial intelligence and robotics. These will be critical technologies for any starship as indeed they are for the current generation of exploratory spacecraft and in-situ planetary robotic explorers. Although early visions of truly intelligent robots have yet to materialize (reasons for which will be outlined), there are nonetheless revolutionary developments which have attempted to address at least some of these earlier unperceived deficiencies. The current state of the art comprises a number of separate strands of research which provide components of robotic intelligence though no over- arching approach has been forthcoming. The first question to be considered is the level of intelligent functionality required to support a long-duration starship mission. This will, at a minimum, need to be extensive imposed by the requirement for complex reconfigurability and repair. The second question concerns the tools that we have at our disposal to implement the required intelligent functions of the starship. These are based on two very different approaches - good old-fashioned artificial intelligence (GOFAI) based on logical theorem-proving and knowledge-encoding recently augmented by modal, temporal, circumscriptive and fuzzy logics to address the well-known “frame problem”; and the more recent soft computing approaches based on artificial neural networks, evolutionary algorithms and immunity models and their variants to implement learning. The former has some flight heritage through the Remote Agent architecture whilst the latter has yet to be deployed on any space mission. However, the notion of reconfigurable hardware of recent interest in the space community warrants the use of evolutionary algorithms and neural networks implemented on field programmable gate array technology, blurring the distinction between

Artificial intelligence and robotics in high throughput post-genomics.

PubMed

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

2005-09-15

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

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.

Applications of artificial intelligence to space station: General purpose intelligent sensor interface

NASA Technical Reports Server (NTRS)

Mckee, James W.

1988-01-01

This final report describes the accomplishments of the General Purpose Intelligent Sensor Interface task of the Applications of Artificial Intelligence to Space Station grant for the period from October 1, 1987 through September 30, 1988. Portions of the First Biannual Report not revised will not be included but only referenced. The goal is to develop an intelligent sensor system that will simplify the design and development of expert systems using sensors of the physical phenomena as a source of data. This research will concentrate on the integration of image processing sensors and voice processing sensors with a computer designed for expert system development. The result of this research will be the design and documentation of a system in which the user will not need to be an expert in such areas as image processing algorithms, local area networks, image processor hardware selection or interfacing, television camera selection, voice recognition hardware selection, or analog signal processing. The user will be able to access data from video or voice sensors through standard LISP statements without any need to know about the sensor hardware or software.

[I, Robot: artificial intelligence, uniqueness and self-consciousness].

PubMed

Agrest, Martín

2008-01-01

The cinematographic version of the science fiction classical book by Isaac Asimov (I, Robot) is used as a starting point, from the Artificial Intelligence perspective, in order to analyze what it is to have a self. Uniqueness or the exchange impossibility and the continuity of being one self are put forward to understand the movie's characters as well as the possibilities of feeling self conscious.

Artificial intelligence issues related to automated computing operations

NASA Technical Reports Server (NTRS)

Hornfeck, William A.

1989-01-01

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

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.

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

An Artificial Intelligence Approach for Gears Diagnostics in AUVs

PubMed Central

Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

2016-01-01

In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved. PMID:27077868

An Artificial Intelligence Approach for Gears Diagnostics in AUVs.

PubMed

Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

2016-04-12

In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.

A development framework for distributed artificial intelligence

NASA Technical Reports Server (NTRS)

Adler, Richard M.; Cottman, Bruce H.

1989-01-01

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

Probabilistic machine learning and artificial intelligence.

PubMed

Ghahramani, Zoubin

2015-05-28

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

Probabilistic machine learning and artificial intelligence

NASA Astrophysics Data System (ADS)

Ghahramani, Zoubin

2015-05-01

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

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…

Neurolinguistically constrained simulation of sentence comprehension: integrating artificial intelligence and brain theory

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

Gigley, H.M.

1982-01-01

An artificial intelligence approach to the simulation of neurolinguistically constrained processes in sentence comprehension is developed using control strategies for simulation of cooperative computation in associative networks. The desirability of this control strategy in contrast to ATN and production system strategies is explained. A first pass implementation of HOPE, an artificial intelligence simulation model of sentence comprehension, constrained by studies of aphasic performance, psycholinguistics, neurolinguistics, and linguistic theory is described. Claims that the model could serve as a basis for sentence production simulation and for a model of language acquisition as associative learning are discussed. HOPE is a model thatmore » performs in a normal state and includes a lesion simulation facility. HOPE is also a research tool. Its modifiability and use as a tool to investigate hypothesized causes of degradation in comprehension performance by aphasic patients are described. Issues of using behavioral constraints in modelling and obtaining appropriate data for simulated process modelling are discussed. Finally, problems of validation of the simulation results are raised; and issues of how to interpret clinical results to define the evolution of the model are discussed. Conclusions with respect to the feasibility of artificial intelligence simulation process modelling are discussed based on the current state of research.« less

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.

Issues in management of artificial intelligence based projects

NASA Technical Reports Server (NTRS)

Kiss, P. A.; Freeman, Michael S.

1988-01-01

Now that Artificial Intelligence (AI) is gaining acceptance, it is important to examine some of the obstacles that still stand in the way of its progress. Ironically, many of these obstacles are related to management and are aggravated by the very characteristcs that make AI useful. The purpose of this paper is to heighten awareness of management issues in AI development and to focus attention on their resolution.

Artificial intelligence programming languages for computer aided manufacturing

NASA Technical Reports Server (NTRS)

Rieger, C.; Samet, H.; Rosenberg, J.

1979-01-01

Eight Artificial Intelligence programming languages (SAIL, LISP, MICROPLANNER, CONNIVER, MLISP, POP-2, AL, and QLISP) are presented and surveyed, with examples of their use in an automated shop environment. Control structures are compared, and distinctive features of each language are highlighted. A simple programming task is used to illustrate programs in SAIL, LISP, MICROPLANNER, and CONNIVER. The report assumes reader knowledge of programming concepts, but not necessarily of the languages surveyed.

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.

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.

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

ERIC Educational Resources Information Center

Ramaswami, Rama

2009-01-01

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

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.

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.

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.

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.

Distinct Neurocognitive Strategies for Comprehensions of Human and Artificial Intelligence

PubMed Central

Ge, Jianqiao; Han, Shihui

2008-01-01

Although humans have inevitably interacted with both human and artificial intelligence in real life situations, it is unknown whether the human brain engages homologous neurocognitive strategies to cope with both forms of intelligence. To investigate this, we scanned subjects, using functional MRI, while they inferred the reasoning processes conducted by human agents or by computers. We found that the inference of reasoning processes conducted by human agents but not by computers induced increased activity in the precuneus but decreased activity in the ventral medial prefrontal cortex and enhanced functional connectivity between the two brain areas. The findings provide evidence for distinct neurocognitive strategies of taking others' perspective and inhibiting the process referenced to the self that are specific to the comprehension of human intelligence. PMID:18665211

An advanced artificial intelligence tool for menu design.

PubMed

Khan, Abdus Salam; Hoffmann, Achim

2003-01-01

The computer-assisted menu design still remains a difficult task. Usually knowledge that aids in menu design by a computer is hard-coded and because of that a computerised menu planner cannot handle the menu design problem for an unanticipated client. To address this problem we developed a menu design tool, MIKAS (menu construction using incremental knowledge acquisition system), an artificial intelligence system that allows the incremental development of a knowledge-base for menu design. We allow an incremental knowledge acquisition process in which the expert is only required to provide hints to the system in the context of actual problem instances during menu design using menus stored in a so-called Case Base. Our system incorporates Case-Based Reasoning (CBR), an Artificial Intelligence (AI) technique developed to mimic human problem solving behaviour. Ripple Down Rules (RDR) are a proven technique for the acquisition of classification knowledge from expert directly while they are using the system, which complement CBR in a very fruitful way. This combination allows the incremental improvement of the menu design system while it is already in routine use. We believe MIKAS allows better dietary practice by leveraging a dietitian's skills and expertise. As such MIKAS has the potential to be helpful for any institution where dietary advice is practised.

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

Biologically inspired intelligent robots

NASA Astrophysics Data System (ADS)

Bar-Cohen, Yoseph; Breazeal, Cynthia

2003-07-01

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

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…

Games and machine learning: a powerful combination in an artificial intelligence course

NASA Astrophysics Data System (ADS)

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

2010-03-01

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 and Checkers - a classic turn-based board game. From the instructors' prospective, we examine aspects of design and implementation as well as the challenges and rewards of using the curricula. We explore students' responses to the projects via the results of a common survey. Finally, we compare the student perceptions from the game-based projects to non-game based projects from the first phase of Project MLeXAI.

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…

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.

Beyond Artificial Intelligence toward Engineered Psychology

NASA Astrophysics Data System (ADS)

Bozinovski, Stevo; Bozinovska, Liljana

This paper addresses the field of Artificial Intelligence, road it went so far and possible road it should go. The paper was invited by the Conference of IT Revolutions 2008, and discusses some issues not emphasized in AI trajectory so far. The recommendations are that the main focus should be personalities rather than programs or agents, that genetic environment should be introduced in reasoning about personalities, and that limbic system should be studied and modeled. Engineered Psychology is proposed as a road to go. Need for basic principles in psychology are discussed and a mathematical equation is proposed as fundamental law of engineered and human psychology.

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.

Model architecture of intelligent data mining oriented urban transportation information

NASA Astrophysics Data System (ADS)

Yang, Bogang; Tao, Yingchun; Sui, Jianbo; Zhang, Feizhou

2007-06-01

Aiming at solving practical problems in urban traffic, the paper presents model architecture of intelligent data mining from hierarchical view. With artificial intelligent technologies used in the framework, the intelligent data mining technology improves, which is more suitable for the change of real-time road condition. It also provides efficient technology support for the urban transport information distribution, transmission and display.

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…

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)...

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…

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.

An intelligent artificial throat with sound-sensing ability based on laser induced graphene

PubMed Central

Tao, Lu-Qi; Tian, He; Liu, Ying; Ju, Zhen-Yi; Pang, Yu; Chen, Yuan-Quan; Wang, Dan-Yang; Tian, Xiang-Guang; Yan, Jun-Chao; Deng, Ning-Qin; Yang, Yi; Ren, Tian-Ling

2017-01-01

Traditional sound sources and sound detectors are usually independent and discrete in the human hearing range. To minimize the device size and integrate it with wearable electronics, there is an urgent requirement of realizing the functional integration of generating and detecting sound in a single device. Here we show an intelligent laser-induced graphene artificial throat, which can not only generate sound but also detect sound in a single device. More importantly, the intelligent artificial throat will significantly assist for the disabled, because the simple throat vibrations such as hum, cough and scream with different intensity or frequency from a mute person can be detected and converted into controllable sounds. Furthermore, the laser-induced graphene artificial throat has the advantage of one-step fabrication, high efficiency, excellent flexibility and low cost, and it will open practical applications in voice control, wearable electronics and many other areas. PMID:28232739

An intelligent artificial throat with sound-sensing ability based on laser induced graphene.

PubMed

Tao, Lu-Qi; Tian, He; Liu, Ying; Ju, Zhen-Yi; Pang, Yu; Chen, Yuan-Quan; Wang, Dan-Yang; Tian, Xiang-Guang; Yan, Jun-Chao; Deng, Ning-Qin; Yang, Yi; Ren, Tian-Ling

2017-02-24

Traditional sound sources and sound detectors are usually independent and discrete in the human hearing range. To minimize the device size and integrate it with wearable electronics, there is an urgent requirement of realizing the functional integration of generating and detecting sound in a single device. Here we show an intelligent laser-induced graphene artificial throat, which can not only generate sound but also detect sound in a single device. More importantly, the intelligent artificial throat will significantly assist for the disabled, because the simple throat vibrations such as hum, cough and scream with different intensity or frequency from a mute person can be detected and converted into controllable sounds. Furthermore, the laser-induced graphene artificial throat has the advantage of one-step fabrication, high efficiency, excellent flexibility and low cost, and it will open practical applications in voice control, wearable electronics and many other areas.

An intelligent artificial throat with sound-sensing ability based on laser induced graphene

NASA Astrophysics Data System (ADS)

Tao, Lu-Qi; Tian, He; Liu, Ying; Ju, Zhen-Yi; Pang, Yu; Chen, Yuan-Quan; Wang, Dan-Yang; Tian, Xiang-Guang; Yan, Jun-Chao; Deng, Ning-Qin; Yang, Yi; Ren, Tian-Ling

2017-02-01

Traditional sound sources and sound detectors are usually independent and discrete in the human hearing range. To minimize the device size and integrate it with wearable electronics, there is an urgent requirement of realizing the functional integration of generating and detecting sound in a single device. Here we show an intelligent laser-induced graphene artificial throat, which can not only generate sound but also detect sound in a single device. More importantly, the intelligent artificial throat will significantly assist for the disabled, because the simple throat vibrations such as hum, cough and scream with different intensity or frequency from a mute person can be detected and converted into controllable sounds. Furthermore, the laser-induced graphene artificial throat has the advantage of one-step fabrication, high efficiency, excellent flexibility and low cost, and it will open practical applications in voice control, wearable electronics and many other areas.

The socio-organizational age of artificial intelligence in medicine.

PubMed

Stefanelli, M

2001-08-01

The increasing pressure on Health Care Organizations (HCOs) to ensure efficiency and cost-effectiveness, balancing quality of care and cost containment, will drive them towards a more effective management of medical knowledge derived from research findings. The relation between science and health services has until recently been too casual. The primary job of medical research has been to understand the mechanisms of disease and produce new treatments, not to worry about the effectiveness of the new treatments or their implementation. As a result many new treatments have taken years to become part of routine practice, ineffective treatments have been widely used, and medicine has been opinion rather than evidence based. This results in suboptimal care for patients. Knowledge management technology may provide effective approaches in speeding up the diffusion of innovative medical procedures whose clinical effectiveness have been proved: the most interesting one is represented by computer-based utilization of evidence-based clinical guidelines. As researchers in Artificial Intelligence in Medicine (AIM), we are committed to foster the strategic transition from opinion to evidence-based decision making. Reviews of the effectiveness of various methods of guideline dissemination show that the most predictable impact is achieved when the guideline is made accessible through computer-based and patient specific reminders that are integrated into the clinician's workflow. However, the traditional single doctor-patient relationship is being replaced by one in which the patient is managed by a team of health care professionals, each specializing in one aspect of care. Such shared care depends critically on the ability to share patient-specific information and medical knowledge easily among them. Strategically there is a need to take a more clinical process view of health care delivery and to identify the appropriate organizational and information infrastructures to support

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 application of artificial intelligence theory to reconfigurable flight control

NASA Technical Reports Server (NTRS)

Handelman, David A.

1987-01-01

Artificial intelligence techniques were used along with statistical hpyothesis testing and modern control theory, to help the pilot cope with the issues of information, knowledge, and capability in the event of a failure. An intelligent flight control system is being developed which utilizes knowledge of cause and effect relationships between all aircraft components. It will screen the information available to the pilots, supplement his knowledge, and most importantly, utilize the remaining flight capability of the aircraft following a failure. The list of failure types the control system will accommodate includes sensor failures, actuator failures, and structural failures.

Information Processing in Cognition Process and New Artificial Intelligent Systems

NASA Astrophysics Data System (ADS)

Zheng, Nanning; Xue, Jianru

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

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

Protein subcellular localization prediction using artificial intelligence technology.

PubMed

Nair, Rajesh; Rost, Burkhard

2008-01-01

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

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…

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.

Artificial Intelligence-Assisted Online Social Therapy for Youth Mental Health

PubMed Central

D'Alfonso, Simon; Santesteban-Echarri, Olga; Rice, Simon; Wadley, Greg; Lederman, Reeva; Miles, Christopher; Gleeson, John; Alvarez-Jimenez, Mario

2017-01-01

Introduction: Benefits from mental health early interventions may not be sustained over time, and longer-term intervention programs may be required to maintain early clinical gains. However, due to the high intensity of face-to-face early intervention treatments, this may not be feasible. Adjunctive internet-based interventions specifically designed for youth may provide a cost-effective and engaging alternative to prevent loss of intervention benefits. However, until now online interventions have relied on human moderators to deliver therapeutic content. More sophisticated models responsive to user data are critical to inform tailored online therapy. Thus, integration of user experience with a sophisticated and cutting-edge technology to deliver content is necessary to redefine online interventions in youth mental health. This paper discusses the development of the moderated online social therapy (MOST) web application, which provides an interactive social media-based platform for recovery in mental health. We provide an overview of the system's main features and discus our current work regarding the incorporation of advanced computational and artificial intelligence methods to enhance user engagement and improve the discovery and delivery of therapy content. Methods: Our case study is the ongoing Horyzons site (5-year randomized controlled trial for youth recovering from early psychosis), which is powered by MOST. We outline the motivation underlying the project and the web application's foundational features and interface. We discuss system innovations, including the incorporation of pertinent usage patterns as well as identifying certain limitations of the system. This leads to our current motivations and focus on using computational and artificial intelligence methods to enhance user engagement, and to further improve the system with novel mechanisms for the delivery of therapy content to users. In particular, we cover our usage of natural language analysis

Artificial Intelligence-Assisted Online Social Therapy for Youth Mental Health.

PubMed

D'Alfonso, Simon; Santesteban-Echarri, Olga; Rice, Simon; Wadley, Greg; Lederman, Reeva; Miles, Christopher; Gleeson, John; Alvarez-Jimenez, Mario

2017-01-01

Introduction: Benefits from mental health early interventions may not be sustained over time, and longer-term intervention programs may be required to maintain early clinical gains. However, due to the high intensity of face-to-face early intervention treatments, this may not be feasible. Adjunctive internet-based interventions specifically designed for youth may provide a cost-effective and engaging alternative to prevent loss of intervention benefits. However, until now online interventions have relied on human moderators to deliver therapeutic content. More sophisticated models responsive to user data are critical to inform tailored online therapy. Thus, integration of user experience with a sophisticated and cutting-edge technology to deliver content is necessary to redefine online interventions in youth mental health. This paper discusses the development of the moderated online social therapy (MOST) web application, which provides an interactive social media-based platform for recovery in mental health. We provide an overview of the system's main features and discus our current work regarding the incorporation of advanced computational and artificial intelligence methods to enhance user engagement and improve the discovery and delivery of therapy content. Methods: Our case study is the ongoing Horyzons site (5-year randomized controlled trial for youth recovering from early psychosis), which is powered by MOST. We outline the motivation underlying the project and the web application's foundational features and interface. We discuss system innovations, including the incorporation of pertinent usage patterns as well as identifying certain limitations of the system. This leads to our current motivations and focus on using computational and artificial intelligence methods to enhance user engagement, and to further improve the system with novel mechanisms for the delivery of therapy content to users. In particular, we cover our usage of natural language analysis

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.

Intelligent Tutoring Systems

NASA Astrophysics Data System (ADS)

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

1985-04-01

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

Intelligent tutoring systems.

PubMed

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

1985-04-26

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

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…

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

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

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.

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)

Amplify scientific discovery with artificial intelligence

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

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

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

A comparative study of artificial intelligent-based maximum power point tracking for photovoltaic systems

NASA Astrophysics Data System (ADS)

Hussain Mutlag, Ammar; Mohamed, Azah; Shareef, Hussain

2016-03-01

Maximum power point tracking (MPPT) is normally required to improve the performance of photovoltaic (PV) systems. This paper presents artificial intelligent-based maximum power point tracking (AI-MPPT) by considering three artificial intelligent techniques, namely, artificial neural network (ANN), adaptive neuro fuzzy inference system with seven triangular fuzzy sets (7-tri), and adaptive neuro fuzzy inference system with seven gbell fuzzy sets. The AI-MPPT is designed for the 25 SolarTIFSTF-120P6 PV panels, with the capacity of 3 kW peak. A complete PV system is modelled using 300,000 data samples and simulated in the MATLAB/SIMULINK. The AI-MPPT has been tested under real environmental conditions for two days from 8 am to 18 pm. The results showed that the ANN based MPPT gives the most accurate performance and then followed by the 7-tri-based MPPT.

Artificial Intelligence In Computational Fluid Dynamics

NASA Technical Reports Server (NTRS)

Vogel, Alison Andrews

1991-01-01

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

Application of temporal LNC logic in artificial intelligence

NASA Astrophysics Data System (ADS)

Adamek, Marek; Mulawka, Jan

2016-09-01

This paper presents the temporal logic inference engine developed in our university. It is an attempt to demonstrate implementation and practical application of temporal logic LNC developed in Cardinal Stefan Wyszynski University in Warsaw.1 The paper describes the fundamentals of LNC logic, architecture and implementation of inference engine. The practical application is shown by providing the solution for popular in Artificial Intelligence problem of Missionaries and Cannibals in terms of LNC logic. Both problem formulation and inference engine are described in details.

Artificial intelligence techniques for scheduling Space Shuttle missions

NASA Technical Reports Server (NTRS)

Henke, Andrea L.; Stottler, Richard H.

1994-01-01

Planning and scheduling of NASA Space Shuttle missions is a complex, labor-intensive process requiring the expertise of experienced mission planners. We have developed a planning and scheduling system using combinations of artificial intelligence knowledge representations and planning techniques to capture mission planning knowledge and automate the multi-mission planning process. Our integrated object oriented and rule-based approach reduces planning time by orders of magnitude and provides planners with the flexibility to easily modify planning knowledge and constraints without requiring programming expertise.

Reflections on the relationship between artificial intelligence and operations research

NASA Technical Reports Server (NTRS)

Fox, Mark S.

1989-01-01

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

Intelligent Systems For Aerospace Engineering: An Overview

NASA Technical Reports Server (NTRS)

KrishnaKumar, K.

2003-01-01

Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

Intelligent Systems for Aerospace Engineering: An Overview

NASA Technical Reports Server (NTRS)

Krishnakumar, Kalmanje

2002-01-01

Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

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)

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

PubMed

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

2017-05-05

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

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.

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

ERIC Educational Resources Information Center

Crowe, Dale; LaPierre, Martin; Kebritchi, Mansureh

2017-01-01

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

An overview of Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET) Project

NASA Technical Reports Server (NTRS)

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

1991-01-01

A software application to assist end-users of the link evaluation terminal (LET) for satellite communications is being developed. This software application incorporates artificial intelligence (AI) techniques and will be deployed as an interface to LET. The high burst rate (HBR) LET provides 30 GHz transmitting/20 GHz receiving (220/110 Mbps) capability for wideband communications technology experiments with the Advanced Communications Technology Satellite (ACTS). The HBR LET can monitor and evaluate the integrity of the HBR communications uplink and downlink to the ACTS satellite. The uplink HBR transmission is performed by bursting the bit-pattern as a modulated signal to the satellite. The HBR LET can determine the bit error rate (BER) under various atmospheric conditions by comparing the transmitted bit pattern with the received bit pattern. An algorithm for power augmentation will be applied to enhance the system's BER performance at reduced signal strength caused by adverse conditions.

Progress towards autonomous, intelligent systems

NASA Technical Reports Server (NTRS)

Lum, Henry; Heer, Ewald

1987-01-01

An aggressive program has been initiated to develop, integrate, and implement autonomous systems technologies starting with today's expert systems and evolving to autonomous, intelligent systems by the end of the 1990s. This program includes core technology developments and demonstration projects for technology evaluation and validation. This paper discusses key operational frameworks in the content of systems autonomy applications and then identifies major technological challenges, primarily in artificial intelligence areas. Program content and progress made towards critical technologies and demonstrations that have been initiated to achieve the required future capabilities in the year 2000 era are discussed.

Artificial Intelligence: An Analysis of Potential Applications to Training, Performance Measurement, and Job Performance Aiding. Interim Report for Period September 1982-July 1983.

ERIC Educational Resources Information Center

Richardson, J. Jeffrey

This paper is part of an Air Force planning effort to develop a research, development, and applications program for the use of artificial intelligence (AI) technology in three target areas: training, performance measurement, and job performance aiding. The paper is organized in five sections that (1) introduce the reader to AI and those subfields…

Machine learning & artificial intelligence in the quantum domain: a review of recent progress

NASA Astrophysics Data System (ADS)

Dunjko, Vedran; Briegel, Hans J.

2018-07-01

Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research—quantum information versus machine learning (ML) and artificial intelligence (AI)—have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our ‘big data’ world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement—exploring what ML/AI can do for quantum physics and vice versa—researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent

Machine learning & artificial intelligence in the quantum domain: a review of recent progress.

PubMed

Dunjko, Vedran; Briegel, Hans J

2018-07-01

Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research-quantum information versus machine learning (ML) and artificial intelligence (AI)-have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our 'big data' world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement-exploring what ML/AI can do for quantum physics and vice versa-researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and

Quality assurance paradigms for artificial intelligence in modelling and simulation

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

Oren, T.I.

1987-04-01

New classes of quality assurance concepts and techniques are required for the advanced knowledge-processing paradigms (such as artificial intelligence, expert systems, or knowledge-based systems) and the complex problems that only simulative systems can cope with. A systematization of quality assurance problems as well as examples are given to traditional and cognizant quality assurance techniques in traditional and cognizant modelling and simulation.

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…

Robotic air vehicle. Blending artificial intelligence with conventional software

NASA Technical Reports Server (NTRS)

Mcnulty, Christa; Graham, Joyce; Roewer, Paul

1987-01-01

The Robotic Air Vehicle (RAV) system is described. The program's objectives were to design, implement, and demonstrate cooperating expert systems for piloting robotic air vehicles. The development of this system merges conventional programming used in passive navigation with Artificial Intelligence techniques such as voice recognition, spatial reasoning, and expert systems. The individual components of the RAV system are discussed as well as their interactions with each other and how they operate as a system.

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

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.

Recommendations for the ethical use and design of artificial intelligent care providers.

PubMed

Luxton, David D

2014-09-01

This paper identifies and reviews ethical issues associated with artificial intelligent care providers (AICPs) in mental health care and other helping professions. Specific recommendations are made for the development of ethical codes, guidelines, and the design of AICPs. Current developments in the application of AICPs and associated technologies are reviewed and a foundational overview of applicable ethical principles in mental health care is provided. Emerging ethical issues regarding the use of AICPs are then reviewed in detail. Recommendations for ethical codes and guidelines as well as for the development of semi-autonomous and autonomous AICP systems are described. The benefits of AICPs and implications for the helping professions are discussed in order to weigh the pros and cons of their use. Existing ethics codes and practice guidelines do not presently consider the current or the future use of interactive artificial intelligent agents to assist and to potentially replace mental health care professionals. AICPs present new ethical issues that will have significant ramifications for the mental health care and other helping professions. Primary issues involve the therapeutic relationship, competence, liability, trust, privacy, and patient safety. Many of the same ethical and philosophical considerations are applicable to use and design of AICPs in medicine, nursing, social work, education, and ministry. The ethical and moral aspects regarding the use of AICP systems must be well thought-out today as this will help to guide the use and development of these systems in the future. Topics presented are relevant to end users, AI developers, and researchers, as well as policy makers and regulatory boards. Published by Elsevier B.V.

Diagnostic classification of cancer using DNA microarrays and artificial intelligence.

PubMed

Greer, Braden T; Khan, Javed

2004-05-01

The application of artificial intelligence (AI) to microarray data has been receiving much attention in recent years because of the possibility of automated diagnosis in the near future. Studies have been published predicting tumor type, estrogen receptor status, and prognosis using a variety of AI algorithms. The performance of intelligent computing decisions based on gene expression signatures is in some cases comparable to or better than the current clinical decision schemas. The goal of these tools is not to make clinicians obsolete, but rather to give clinicians one more tool in their armamentarium to accurately diagnose and hence better treat cancer patients. Several such applications are summarized in this chapter, and some of the common pitfalls are noted.

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.

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)

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.

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.

Physical intelligence does matter to cumulative technological culture.

PubMed

Osiurak, François; De Oliveira, Emmanuel; Navarro, Jordan; Lesourd, Mathieu; Claidière, Nicolas; Reynaud, Emanuelle

2016-08-01

Tool-based culture is not unique to humans, but cumulative technological culture is. The social intelligence hypothesis suggests that this phenomenon is fundamentally based on uniquely human sociocognitive skills (e.g., shared intentionality). An alternative hypothesis is that cumulative technological culture also crucially depends on physical intelligence, which may reflect fluid and crystallized aspects of intelligence and enables people to understand and improve the tools made by predecessors. By using a tool-making-based microsociety paradigm, we demonstrate that physical intelligence is a stronger predictor of cumulative technological performance than social intelligence. Moreover, learners' physical intelligence is critical not only in observational learning but also when learners interact verbally with teachers. Finally, we show that cumulative performance is only slightly influenced by teachers' physical and social intelligence. In sum, human technological culture needs "great engineers" to evolve regardless of the proportion of "great pedagogues." Social intelligence might play a more limited role than commonly assumed, perhaps in tool-use/making situations in which teachers and learners have to share symbolic representations. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Using artificial intelligence to control fluid flow computations

NASA Technical Reports Server (NTRS)

Gelsey, Andrew

1992-01-01

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

Artificial intelligence applied to process signal analysis

NASA Technical Reports Server (NTRS)

Corsberg, Dan

1988-01-01

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

The Biological Relevance of Artificial Life: Lessons from Artificial Intelligence

NASA Technical Reports Server (NTRS)

Colombano, Silvano

2000-01-01

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

Robotic and artificial intelligence for keyhole neurosurgery: the ROBOCAST project, a multi-modal autonomous path planner.

PubMed

De Momi, E; Ferrigno, G

2010-01-01

The robot and sensors integration for computer-assisted surgery and therapy (ROBOCAST) project (FP7-ICT-2007-215190) is co-funded by the European Union within the Seventh Framework Programme in the field of information and communication technologies. The ROBOCAST project focuses on robot- and artificial-intelligence-assisted keyhole neurosurgery (tumour biopsy and local drug delivery along straight or turning paths). The goal of this project is to assist surgeons with a robotic system controlled by an intelligent high-level controller (HLC) able to gather and integrate information from the surgeon, from diagnostic images, and from an array of on-field sensors. The HLC integrates pre-operative and intra-operative diagnostics data and measurements, intelligence augmentation, multiple-robot dexterity, and multiple sensory inputs in a closed-loop cooperating scheme including a smart interface for improved haptic immersion and integration. This paper, after the overall architecture description, focuses on the intelligent trajectory planner based on risk estimation and human criticism. The current status of development is reported, and first tests on the planner are shown by using a real image stack and risk descriptor phantom. The advantages of using a fuzzy risk description are given by the possibility of upgrading the knowledge on-field without the intervention of a knowledge engineer.

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.

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.

Space Environment Modelling with the Use of Artificial Intelligence Methods

NASA Astrophysics Data System (ADS)

Lundstedt, H.; Wintoft, P.; Wu, J.-G.; Gleisner, H.; Dovheden, V.

1996-12-01

Space based technological systems are affected by the space weather in many ways. Several severe failures of satellites have been reported at times of space storms. Our society also increasingly depends on satellites for communication, navigation, exploration, and research. Predictions of the conditions in the satellite environment have therefore become very important. We will here present predictions made with the use of artificial intelligence (AI) techniques, such as artificial neural networks (ANN) and hybrids of AT methods. We are developing a space weather model based on intelligence hybrid systems (IHS). The model consists of different forecast modules, each module predicts the space weather on a specific time-scale. The time-scales range from minutes to months with the fundamental time-scale of 1-5 minutes, 1-3 hours, 1-3 days, and 27 days. Solar and solar wind data are used as input data. From solar magnetic field measurements, either made on the ground at Wilcox Solar Observatory (WSO) at Stanford, or made from space by the satellite SOHO, solar wind parameters can be predicted and modelled with ANN and MHD models. Magnetograms from WSO are available on a daily basis. However, from SOHO magnetograms will be available every 90 minutes. SOHO magnetograms as input to ANNs will therefore make it possible to even predict solar transient events. Geomagnetic storm activity can today be predicted with very high accuracy by means of ANN methods using solar wind input data. However, at present real-time solar wind data are only available during part of the day from the satellite WIND. With the launch of ACE in 1997, solar wind data will on the other hand be available during 24 hours per day. The conditions of the satellite environment are not only disturbed at times of geomagnetic storms but also at times of intense solar radiation and highly energetic particles. These events are associated with increased solar activity. Predictions of these events are therefore

The 1991 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor)

1991-01-01

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 this proceeding fall into the following areas: Planning and scheduling, fault monitoring/diagnosis/recovery, machine vision, robotics, system development, information management, knowledge acquisition and representation, distributed systems, tools, neural networks, and miscellaneous applications.

Future applications of artificial intelligence to Mission Control Centers

NASA Technical Reports Server (NTRS)

Friedland, Peter

1991-01-01

Future applications of artificial intelligence to Mission Control Centers are presented in the form of the viewgraphs. The following subject areas are covered: basic objectives of the NASA-wide AI program; inhouse research program; constraint-based scheduling; learning and performance improvement for scheduling; GEMPLAN multi-agent planner; planning, scheduling, and control; Bayesian learning; efficient learning algorithms; ICARUS (an integrated architecture for learning); design knowledge acquisition and retention; computer-integrated documentation; and some speculation on future applications.

Applications of Artificial Intelligence (AI) and Expert Systems for Online Searching.

ERIC Educational Resources Information Center

Hawkins, Donald T.

1988-01-01

Discussion of the online searching process identifies the formulation of a search strategy as the major problem area for users of online systems. Artificial intelligence is suggested as a solution to this problem, and several expert systems for information retrieval are described. An annotated list of 24 items for further reading is included. (23…

Applications of artificial intelligence systems in the analysis of epidemiological data.

PubMed

Flouris, Andreas D; Duffy, Jack

2006-01-01

A brief review of the germane literature suggests that the use of artificial intelligence (AI) statistical algorithms in epidemiology has been limited. We discuss the advantages and disadvantages of using AI systems in large-scale sets of epidemiological data to extract inherent, formerly unidentified, and potentially valuable patterns that human-driven deductive models may miss.

Use of artificial intelligence in the production of high quality minced meat

NASA Astrophysics Data System (ADS)

Kapovsky, B. R.; Pchelkina, V. A.; Plyasheshnik, P. I.; Dydykin, A. S.; Lazarev, A. A.

2017-09-01

A design for an automatic line for minced meat production according to new production technology based on an innovative meat milling method is proposed. This method allows the necessary degree of raw material comminution at the stage of raw material preparation to be obtained, which leads to production intensification due to the traditional meat mass comminution equipment being unnecessary. To ensure consistent quality of the product obtained, the use of on-line automatic control of the technological process for minced meat production is envisaged. This system has been developed using artificial intelligence methods and technologies. The system is trainable during the operation process, adapts to changes in processed raw material characteristics and to external impacts that affect the system operation, and manufactures meat shavings with minimal dispersion of the typical particle size. The control system includes equipment for express analysis of the chemical composition of the minced meat and its temperature after comminution. In this case, the minced meat production process can be controlled strictly as a function of time, which excludes subjective factors for assessing the degree of finished product readiness. This will allow finished meat products with consistent, targeted high quality to be produced.

Collective intelligence of the artificial life community on its own successes, failures, and future.

PubMed

Rasmussen, Steen; Raven, Michael J; Keating, Gordon N; Bedau, Mark A

2003-01-01

We describe a novel Internet-based method for building consensus and clarifying conflicts in large stakeholder groups facing complex issues, and we use the method to survey and map the scientific and organizational perspectives of the artificial life community during the Seventh International Conference on Artificial Life (summer 2000). The issues addressed in this survey included artificial life's main successes, main failures, main open scientific questions, and main strategies for the future, as well as the benefits and pitfalls of creating a professional society for artificial life. By illuminating the artificial life community's collective perspective on these issues, this survey illustrates the value of such methods of harnessing the collective intelligence of large stakeholder groups.

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

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.

An Artificial Intelligence Tutor: A Supplementary Tool for Teaching and Practicing Braille

ERIC Educational Resources Information Center

McCarthy, Tessa; Rosenblum, L. Penny; Johnson, Benny G.; Dittel, Jeffrey; Kearns, Devin M.

2016-01-01

Introduction: This study evaluated the usability and effectiveness of an artificial intelligence Braille Tutor designed to supplement the instruction of students with visual impairments as they learned to write braille contractions. Methods: A mixed-methods design was used, which incorporated a single-subject, adapted alternating treatments design…

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.

Intelligent Tutor

NASA Technical Reports Server (NTRS)

1990-01-01

NASA also seeks to advance American education by employing the technology utilization process to develop a computerized, artificial intelligence-based Intelligent Tutoring System (ITS) to help high school and college physics students. The tutoring system is designed for use with the lecture and laboratory portions of a typical physics instructional program. Its importance lies in its ability to observe continually as a student develops problem solutions and to intervene when appropriate with assistance specifically directed at the student's difficulty and tailored to his skill level and learning style. ITS originated as a project of the Johnson Space Center (JSC). It is being developed by JSC's Software Technology Branch in cooperation with Dr. R. Bowen Loftin at the University of Houston-Downtown. Program is jointly sponsored by NASA and ACOT (Apple Classrooms of Tomorrow). Other organizations providing support include Texas Higher Education Coordinating Board, the National Research Council, Pennzoil Products Company and the George R. Brown Foundation. The Physics I class of Clear Creek High School, League City, Texas are providing the classroom environment for test and evaluation of the system. The ITS is a spinoff product developed earlier to integrate artificial intelligence into training/tutoring systems for NASA astronauts flight controllers and engineers.

Artificial intelligence techniques for automatic screening of amblyogenic factors.

PubMed

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

2008-01-01

To develop a low-cost automated video system to effectively screen children aged 6 months to 6 years for amblyogenic factors. 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. 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. 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.

Artificial General Intelligence: Concept, State of the Art, and Future Prospects

NASA Astrophysics Data System (ADS)

Goertzel, Ben

2014-12-01

In recent years broad community of researchers has emerged, focusing on the original ambitious goals of the AI field - the creation and study of software or hardware systems with general intelligence comparable to, and ultimately perhaps greater than, that of human beings. This paper surveys this diverse community and its progress. Approaches to defining the concept of Artificial General Intelligence (AGI) are reviewed including mathematical formalisms, engineering, and biology inspired perspectives. The spectrum of designs for AGI systems includes systems with symbolic, emergentist, hybrid and universalist characteristics. Metrics for general intelligence are evaluated, with a conclusion that, although metrics for assessing the achievement of human-level AGI may be relatively straightforward (e.g. the Turing Test, or a robot that can graduate from elementary school or university), metrics for assessing partial progress remain more controversial and problematic.

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

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…

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…

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.

Use of artificial intelligence in analytical systems for the clinical laboratory

PubMed Central

Truchaud, Alain; Ozawa, Kyoichi; Pardue, Harry; Schnipelsky, Paul

1995-01-01

The incorporation of information-processing technology into analytical systems in the form of standard computing software has recently been advanced by the introduction of artificial intelligence (AI), both as expert systems and as neural networks. This paper considers the role of software in system operation, control and automation, and attempts to define intelligence. AI is characterized by its ability to deal with incomplete and imprecise information and to accumulate knowledge. Expert systems, building on standard computing techniques, depend heavily on the domain experts and knowledge engineers that have programmed them to represent the real world. Neural networks are intended to emulate the pattern-recognition and parallel processing capabilities of the human brain and are taught rather than programmed. The future may lie in a combination of the recognition ability of the neural network and the rationalization capability of the expert system. In the second part of the paper, examples are given of applications of AI in stand-alone systems for knowledge engineering and medical diagnosis and in embedded systems for failure detection, image analysis, user interfacing, natural language processing, robotics and machine learning, as related to clinical laboratories. It is concluded that AI constitutes a collective form of intellectual propery, and that there is a need for better documentation, evaluation and regulation of the systems already being used in clinical laboratories. PMID:18924784

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.

Artificial intelligence in medicine: humans need not apply?

PubMed

Diprose, William; Buist, Nicholas

2016-05-06

Artificial intelligence (AI) is a rapidly growing field with a wide range of applications. Driven by economic constraints and the potential to reduce human error, we believe that over the coming years AI will perform a significant amount of the diagnostic and treatment decision-making traditionally performed by the doctor. Humans would continue to be an important part of healthcare delivery, but in many situations, less expensive fit-for-purpose healthcare workers could be trained to 'fill the gaps' where AI are less capable. As a result, the role of the doctor as an expensive problem-solver would become redundant.

Reverse engineering the human: artificial intelligence and acting theory

NASA Astrophysics Data System (ADS)

Soto-Morettini, Donna

2017-01-01

In two separate papers, Artificial Intelligence (AI)/Robotics researcher Guy Hoffman takes as a starting point that actors have been in the business of reverse engineering human behaviour for centuries. In this paper, I follow the similar trajectories of AI and acting theory (AT), looking at three primary questions, in the hope of framing a response to Hoffman's papers: (1) How are the problems of training a human to simulate a fictional human both similar to and different from training a machine to simulate a human? (2) How are the larger questions of AI design and architecture similar to the larger questions that still remain within the area of AT? (3) Is there anything in the work of AI design that might advance the work of acting theorists and practitioners? The paper explores the use of "swarm intelligence" in recent models of both AT and AI, and considers the issues of embodied cognition, and the kinds of intelligence that enhances or inhibits imaginative immersion for the actor, and concludes with a consideration of the ontological questions raised by the trend towards intersubjective, dynamic systems of generative thought in both AT and AI.

Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

NASA Astrophysics Data System (ADS)

Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

2016-06-01

With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

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.

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 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.

Integrating artificial and human intelligence into tablet production process.

PubMed

Gams, Matjaž; Horvat, Matej; Ožek, Matej; Luštrek, Mitja; Gradišek, Anton

2014-12-01

We developed a new machine learning-based method in order to facilitate the manufacturing processes of pharmaceutical products, such as tablets, in accordance with the Process Analytical Technology (PAT) and Quality by Design (QbD) initiatives. Our approach combines the data, available from prior production runs, with machine learning algorithms that are assisted by a human operator with expert knowledge of the production process. The process parameters encompass those that relate to the attributes of the precursor raw materials and those that relate to the manufacturing process itself. During manufacturing, our method allows production operator to inspect the impacts of various settings of process parameters within their proven acceptable range with the purpose of choosing the most promising values in advance of the actual batch manufacture. The interaction between the human operator and the artificial intelligence system provides improved performance and quality. We successfully implemented the method on data provided by a pharmaceutical company for a particular product, a tablet, under development. We tested the accuracy of the method in comparison with some other machine learning approaches. The method is especially suitable for analyzing manufacturing processes characterized by a limited amount of data.

Artificial Intelligence, Expert Systems, Natural Language Interfaces, Knowledge Engineering and the Librarian.

ERIC Educational Resources Information Center

Davies, Jim

This paper begins by examining concepts of artificial intelligence (AI) and discusses various definitions of the concept that have been suggested in the literature. The nesting relationship of expert systems within the broader framework of AI is described, and expert systems are characterized as knowledge-based systems (KBS) which attempt to solve…

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

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

ERIC Educational Resources Information Center

Tennyson, Robert

1984-01-01

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

Artificial Intelligence 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

Bio-Intelligence: A Research Program Facilitating the Development of New Paradigms for Tomorrow's Patient Care

NASA Astrophysics Data System (ADS)

Phan, Sieu; Famili, Fazel; Liu, Ziying; Peña-Castillo, Lourdes

The advancement of omics technologies in concert with the enabling information technology development has accelerated biological research to a new realm in a blazing speed and sophistication. The limited single gene assay to the high throughput microarray assay and the laborious manual count of base-pairs to the robotic assisted machinery in genome sequencing are two examples to name. Yet even more sophisticated, the recent development in literature mining and artificial intelligence has allowed researchers to construct complex gene networks unraveling many formidable biological puzzles. To harness these emerging technologies to their full potential to medical applications, the Bio-intelligence program at the Institute for Information Technology, National Research Council Canada, aims to develop and exploit artificial intelligence and bioinformatics technologies to facilitate the development of intelligent decision support tools and systems to improve patient care - for early detection, accurate diagnosis/prognosis of disease, and better personalized therapeutic management.

Artificial intelligence against breast cancer (A.N.N.E.S-B.C.-Project).

PubMed

Parmeggiani, Domenico; Avenia, Nicola; Sanguinetti, Alessandro; Ruggiero, Roberto; Docimo, Giovanni; Siciliano, Mattia; Ambrosino, Pasquale; Madonna, Imma; Peltrini, Roberto; Parmeggiani, Umberto

2012-01-01

Our preliminary study examined the development of an advanced innovative technology with the objectives of--developing methodologies and algorithms for a Artificial Neural Network (ANN) system, improving mammography and ultra-sonography images interpretation;--creating autonomous software as a diagnostic tool for the physicians, allowing the possibility for the advanced application of databases using Artificial Intelligence (Expert System). Since 2004 550 F patients over 40 yrs old were divided in two groups: 1) 310 pts underwent echo every 6 months and mammography every year by expert radiologists. 2) 240 pts had the same screening program and were also examined by our diagnosis software, developed with ANN-ES technology by the Engineering Aircraft Research Project team. The information was continually updated and returned to the Expert System, defining the principal rules of automatic diagnosis. In the second group we selected: Expert radiologist decision; ANN-ES decision; Expert radiologists with ANN-ES decision. The second group had significantly better diagnosis for cancer and better specificity for breast lesions risk as well as the highest percentage account when the radiologist's decision was helped by the ANN software. The ANN-ES group was able to select, by anamnestic, diagnostic and genetic means, 8 patients for prophylactic surgery, finding 4 cancers in a very early stage. Although it is only a preliminary study, this innovative diagnostic tool seems to provide better positive and negative predictive value in cancer diagnosis as well as in breast risk lesion identification.

Artificial intelligence: a new approach for prescription and monitoring of hemodialysis therapy.

PubMed

Akl, A I; Sobh, M A; Enab, Y M; Tattersall, J

2001-12-01

The effect of dialysis on patients is conventionally predicted using a formal mathematical model. This approach requires many assumptions of the processes involved, and validation of these may be difficult. The validity of dialysis urea modeling using a formal mathematical model has been challenged. Artificial intelligence using neural networks (NNs) has been used to solve complex problems without needing a mathematical model or an understanding of the mechanisms involved. In this study, we applied an NN model to study and predict concentrations of urea during a hemodialysis session. We measured blood concentrations of urea, patient weight, and total urea removal by direct dialysate quantification (DDQ) at 30-minute intervals during the session (in 15 chronic hemodialysis patients). The NN model was trained to recognize the evolution of measured urea concentrations and was subsequently able to predict hemodialysis session time needed to reach a target solute removal index (SRI) in patients not previously studied by the NN model (in another 15 chronic hemodialysis patients). Comparing results of the NN model with the DDQ model, the prediction error was 10.9%, with a not significant difference between predicted total urea nitrogen (UN) removal and measured UN removal by DDQ. NN model predictions of time showed a not significant difference with actual intervals needed to reach the same SRI level at the same patient conditions, except for the prediction of SRI at the first 30-minute interval, which showed a significant difference (P = 0.001). This indicates the sensitivity of the NN model to what is called patient clearance time; the prediction error was 8.3%. From our results, we conclude that artificial intelligence applications in urea kinetics can give an idea of intradialysis profiling according to individual clinical needs. In theory, this approach can be extended easily to other solutes, making the NN model a step forward to achieving artificial-intelligent

Evolvable mathematical models: A new artificial Intelligence paradigm

NASA Astrophysics Data System (ADS)

Grouchy, Paul

We develop a novel Artificial Intelligence paradigm to generate autonomously artificial agents as mathematical models of behaviour. Agent/environment inputs are mapped to agent outputs via equation trees which are evolved in a manner similar to Symbolic Regression in Genetic Programming. Equations are comprised of only the four basic mathematical operators, addition, subtraction, multiplication and division, as well as input and output variables and constants. From these operations, equations can be constructed that approximate any analytic function. These Evolvable Mathematical Models (EMMs) are tested and compared to their Artificial Neural Network (ANN) counterparts on two benchmarking tasks: the double-pole balancing without velocity information benchmark and the challenging discrete Double-T Maze experiments with homing. The results from these experiments show that EMMs are capable of solving tasks typically solved by ANNs, and that they have the ability to produce agents that demonstrate learning behaviours. To further explore the capabilities of EMMs, as well as to investigate the evolutionary origins of communication, we develop NoiseWorld, an Artificial Life simulation in which interagent communication emerges and evolves from initially noncommunicating EMM-based agents. Agents develop the capability to transmit their x and y position information over a one-dimensional channel via a complex, dialogue-based communication scheme. These evolved communication schemes are analyzed and their evolutionary trajectories examined, yielding significant insight into the emergence and subsequent evolution of cooperative communication. Evolved agents from NoiseWorld are successfully transferred onto physical robots, demonstrating the transferability of EMM-based AIs from simulation into physical reality.

A Non-Cognitive Formal Approach to Knowledge Representation in Artificial Intelligence.

DTIC Science & Technology

1986-06-01

example, Duda and others translated production rules into a partitioned semantic network (73). Representations were also translated into production...153. Berlin: Springer-Verlag, 1982. 38. Blikle, Andrzej . "Equational Languages," Information and Control, 21: 134-147 (September 1972). 285 39. Ezawa...Conference on Artificial Intelligence, IJCAI-75. 115-121. William Kaufmann, Inc., Los Altos CA, 1975. 73. Duda , Richard 0. and others. "Semantic

Artificial pigs in space: using artificial intelligence and artificial life techniques to design animal housing.

PubMed

Stricklin, W R; de Bourcier, P; Zhou, J Z; Gonyou, H W

1998-10-01

Computer simulations have been used by us since the early 1970s to gain an understanding of the spacing and movement patterns of confined animals. The work has progressed from the early stages, in which we used randomly positioned points, to current investigations of animats (computer-simulated animals), which show low levels of learning via artificial neural networks. We have determined that 1) pens of equal floor area but of different shape result in different spatial and movement patterns for randomly positioned and moving animats; 2) when group size increases under constant density, freedom of movement approaches an asymptote at approximately six animats; 3) matching the number of animats with the number of corners results in optimal freedom of movement for small groups of animats; and 4) perimeter positioning occurs in groups of animats that maximize their distance to first- and second-nearest neighbors. Recently, we developed animats that move, compete for social dominance, and are motivated to obtain resources (food, resting sites, etc.). We are currently developing an animat that learns its behavior from the spatial and movement data collected on live pigs. The animat model is then used to pretest pen designs, followed by new pig spatial data fed into the animat model, resulting in a new pen design to be tested, and the steps are repeated. We believe that methodologies from artificial-life and artificial intelligence can contribute to the understanding of basic animal behavior principles, as well as to the solving of problems in production agriculture in areas such as animal housing 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.

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.

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

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1984-01-01

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

[Artificial intelligence to assist clinical diagnosis in medicine].

PubMed

Lugo-Reyes, Saúl Oswaldo; Maldonado-Colín, Guadalupe; Murata, Chiharu

2014-01-01

Medicine is one of the fields of knowledge that would most benefit from a closer interaction with Computer studies and Mathematics by optimizing complex, imperfect processes such as differential diagnosis; this is the domain of Machine Learning, a branch of Artificial Intelligence that builds and studies systems capable of learning from a set of training data, in order to optimize classification and prediction processes. In Mexico during the last few years, progress has been made on the implementation of electronic clinical records, so that the National Institutes of Health already have accumulated a wealth of stored data. For those data to become knowledge, they need to be processed and analyzed through complex statistical methods, as it is already being done in other countries, employing: case-based reasoning, artificial neural networks, Bayesian classifiers, multivariate logistic regression, or support vector machines, among other methodologies; to assist the clinical diagnosis of acute appendicitis, breast cancer and chronic liver disease, among a wide array of maladies. In this review we shift through concepts, antecedents, current examples and methodologies of machine learning-assisted clinical diagnosis.

Three Years of Using Robots in an Artificial Intelligence Course: Lessons Learned

ERIC Educational Resources Information Center

Kumar, Amruth N.

2004-01-01

We have been using robots in our artificial intelligence course since fall 2000. We have been using the robots for open-laboratory projects. The projects are designed to emphasize high-level knowledge-based AI algorithms. After three offerings of the course, we paused to analyze the collected data and to see if we could answer the following…

Artificial Intelligence Software Engineering (AISE) model

NASA Technical Reports Server (NTRS)

Kiss, Peter A.

1990-01-01

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