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Sample records for artificial techniques controlling

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-07-01

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

  2. Artificial intelligence techniques in power systems

    Energy Technology Data Exchange (ETDEWEB)

    Laughton, M.A.

    1997-12-31

    Since the early to mid 1980s much of the effort in power systems analysis has turned away from the methodology of formal mathematical modelling which came from the fields of operations research, control theory and numerical analysis to the less rigorous techniques of artificial intelligence (AI). Today the main AI techniques found in power systems applications are those utilising the logic and knowledge representations of expert systems, fuzzy systems, artificial neural networks (ANN) and, more recently, evolutionary computing. These techniques will be outlined in this chapter and the power system applications indicated. (Author)

  3. Artificial intelligence techniques in Prolog

    CERN Document Server

    Shoham, Yoav

    1993-01-01

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

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

    Science.gov (United States)

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

    2003-01-01

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

  5. Dynamic Artificial Potential Fields for Autonomous Camera Control

    DEFF Research Database (Denmark)

    Burelli, Paolo; Jhala, Arnav Harish

    2009-01-01

    the implementation and evaluation of Artificial Potential Fields for automatic camera placement. We first describe the re- casting of the frame composition problem as a solution to a two particles suspended in an Artificial Potential Field. We demonstrate the application of this technique to control both camera...

  6. Sensorless Speed/Torque Control of DC Machine Using Artificial Neural Network Technique

    Directory of Open Access Journals (Sweden)

    Rakan Kh. Antar

    2017-12-01

    Full Text Available In this paper, Artificial Neural Network (ANN technique is implemented to improve speed and torque control of a separately excited DC machine drive. The speed and torque sensorless scheme based on ANN is estimated adaptively. The proposed controller is designed to estimate rotor speed and mechanical load torque as a Model Reference Adaptive System (MRAS method for DC machine. The DC drive system consists of four quadrant DC/DC chopper with MOSFET transistors, ANN, logic gates and routing circuits. The DC drive circuit is designed, evaluated and modeled by Matlab/Simulink in the forward and reverse operation modes as a motor and generator, respectively. The DC drive system is simulated at different speed values (±1200 rpm and mechanical torque (±7 N.m in steady state and dynamic conditions. The simulation results illustratethe effectiveness of the proposed controller without speed or torque sensors.

  7. Artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  8. Artificial Intelligence Techniques and Methodology

    OpenAIRE

    Carbonell, Jaime G.; Sleeman, Derek

    1982-01-01

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

  9. USE OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN QUALITY IMPROVING PROCESS

    OpenAIRE

    KALİTE İYİLEŞTİRME SÜRECİNDE YAPAY ZEKÃ KAYA; Orhan ENGİN

    2005-01-01

    Today, changing of competition conditions and customer preferences caused to happen many differences in the viewpoint of firms' quality studies. At the same time, improvements in computer technologies accelerated use of artificial intelligence. Artificial intelligence technologies are being used to solve many industry problems. In this paper, we investigated the use of artificial intelligence techniques to solve quality problems. The artificial intelligence techniques, which are used in quali...

  10. NEW TECHNIQUES APPLIED IN ECONOMICS. ARTIFICIAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    Constantin Ilie

    2009-05-01

    Full Text Available The present paper has the objective to inform the public regarding the use of new techniques for the modeling, simulate and forecast of system from different field of activity. One of those techniques is Artificial Neural Network, one of the artificial in

  11. An artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  12. Artificial Intelligence techniques for mission planning for mobile robots

    International Nuclear Information System (INIS)

    Martinez, J.M.; Nomine, J.P.

    1990-01-01

    This work focuses on Spatial Modelization Techniques and on Control Software Architectures, in order to deal efficiently with the Navigation and Perception problems encountered in Mobile Autonomous Robotics. After a brief survey of the current various approaches for these techniques, we expose ongoing simulation works for a specific mission in robotics. Studies in progress used for Spatial Reasoning are based on new approaches combining Artificial Intelligence and Geometrical techniques. These methods deal with the problem of environment modelization using three types of models: geometrical topological and semantic models at different levels. The decision making processes of control are presented as the result of cooperation between a group of decentralized agents that communicate by sending messages. (author)

  13. Discrete PID Tuning Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Petr DOLEŽEL

    2009-06-01

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

  14. APPLYING ARTIFICIAL INTELLIGENCE TECHNIQUES TO HUMAN-COMPUTER INTERFACES

    DEFF Research Database (Denmark)

    Sonnenwald, Diane H.

    1988-01-01

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

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

    Science.gov (United States)

    Mishra, D.; Goyal, P.

    2014-12-01

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

  16. Operation optimization of distributed generation using artificial intelligent techniques

    Directory of Open Access Journals (Sweden)

    Mahmoud H. Elkazaz

    2016-06-01

    Full Text Available Future smart grids will require an observable, controllable and flexible network architecture for reliable and efficient energy delivery. The use of artificial intelligence and advanced communication technologies is essential in building a fully automated system. This paper introduces a new technique for online optimal operation of distributed generation (DG resources, i.e. a hybrid fuel cell (FC and photovoltaic (PV system for residential applications. The proposed technique aims to minimize the total daily operating cost of a group of residential homes by managing the operation of embedded DG units remotely from a control centre. The target is formed as an objective function that is solved using genetic algorithm (GA optimization technique. The optimal settings of the DG units obtained from the optimization process are sent to each DG unit through a fully automated system. The results show that the proposed technique succeeded in defining the optimal operating points of the DGs that affect directly the total operating cost of the entire system.

  17. Artificial Intelligence Techniques: Applications for Courseware Development.

    Science.gov (United States)

    Dear, Brian L.

    1986-01-01

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

  18. Development of a Car Racing Simulator Game Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Marvin T. Chan

    2015-01-01

    Full Text Available This paper presents a car racing simulator game called Racer, in which the human player races a car against three game-controlled cars in a three-dimensional environment. The objective of the game is not to defeat the human player, but to provide the player with a challenging and enjoyable experience. To ensure that this objective can be accomplished, the game incorporates artificial intelligence (AI techniques, which enable the cars to be controlled in a manner that mimics natural driving. The paper provides a brief history of AI techniques in games, presents the use of AI techniques in contemporary video games, and discusses the AI techniques that were implemented in the development of Racer. A comparison of the AI techniques implemented in the Unity platform with traditional AI search techniques is also included in the discussion.

  19. Artificial intelligence techniques for voltage control

    Energy Technology Data Exchange (ETDEWEB)

    Ekwue, A.; Cheng, D.T.Y.; Macqueen, J.F.

    1997-12-31

    In electric power systems, the advantages of reactive power dispatching or optimisation include improved utilisation of reactive power sources and hence reduction in reactive power flows and real losses of the system; unloading of the system and equipment as a result of reactive flow reduction; the power factors of generation are improved and system security is enhanced; reduced voltage gradients and somewhat higher voltages which result across the system from improved operation; deferred capital investment is new reactive power sources as a result of improved utilisation of existing equipment; and for the National Grid Company plc (NGC), the main advantage is reduced out-of-merit operation. The problem of reactive power control has been studied and widely reported in the literature. Non-linear programming methods as well as linear programming techniques for constraint dispatch have been described. Static optimisation of reactive power sources by the use of sensitivity analysis was described by Kishore and Hill. Long range optimum var planning has been considered and the optimum amount and location of network reactive compensation so as to maintain the system voltage within the desired limits, while operating under normal and various insecurity states, have also been studied using several methods. The objective of this chapter is therefore to review conventional methods as well as AI techniques for reactive power control. (Author)

  20. Alpha efficiency under TL and OSL - A subtraction technique using OSL and TL to detect artificial irradiation

    International Nuclear Information System (INIS)

    Zink, A.J.C.; Dabis, S.; Porto, E.; Castaing, J.

    2010-01-01

    With the development of thermoluminescence (TL) and optically stimulated luminescence (OSL) to determine the authenticity of old ceramics, forgers use artificial irradiation by gamma ray to age modern productions. Besides fraudulent action, objects can be exposed to various sources of X-rays (e.g. radiography, security control at airports). For all these reasons, the determination of artificial irradiation is an important topic for dating art objects. The main technique to identify artificial irradiations is the subtraction technique. It is based on the fact that alpha efficiency varies according to the luminescence technique (fine grain, coarse grains, predose, OSL). Having observed a rather significant difference of alpha efficiency for TL and OSL, we propose a new subtraction technique using OSL and TL of fine grains.

  1. Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

    International Nuclear Information System (INIS)

    Ortiz R, J. M.; Martinez B, M. R.; Vega C, H. R.; Gallego D, E.; Lorente F, A.; Mendez V, R.; Los Arcos M, J. M.; Guerrero A, J. E.

    2011-01-01

    With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks (Ann) have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Ann still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning Ann parameters. In recent years the use of hybrid technologies, combining Ann and genetic algorithms, has been utilized to. In this work, several Ann topologies were trained and tested using Ann and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out. (Author)

  2. Event tree analysis using artificial intelligence techniques

    International Nuclear Information System (INIS)

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

    1985-01-01

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

  3. Applications of artificial intelligence to reactor and plant control

    International Nuclear Information System (INIS)

    Bernard, J.A.

    1989-01-01

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

  4. Utilization of artificial intelligence techniques for the Space Station power system

    Science.gov (United States)

    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.

  5. Implementation and Validation of Artificial Intelligence Techniques for Robotic Surgery

    OpenAIRE

    Aarshay Jain; Deepansh Jagotra; Vijayant Agarwal

    2014-01-01

    The primary focus of this study is implementation of Artificial Intelligence (AI) technique for developing an inverse kinematics solution for the Raven-IITM surgical research robot [1]. First, the kinematic model of the Raven-IITM robot was analysed along with the proposed analytical solution [2] for inverse kinematics problem. Next, The Artificial Neural Network (ANN) techniques was implemented. The training data for the same was careful selected by keeping manipulability constraints in mind...

  6. Chromatic changes to artificial irises produced using different techniques

    Science.gov (United States)

    Bannwart, Lisiane Cristina; Goiato, Marcelo Coelho; dos Santos, Daniela Micheline; Moreno, Amália; Pesqueira, Aldiéris Alves; Haddad, Marcela Filié; Andreotti, Agda Marobo; de Medeiros, Rodrigo Antonio

    2013-05-01

    Ocular prostheses are important determinants of their users' aesthetic recovery and self-esteem. Because of use, ocular prostheses longevity is strongly affected by instability of the iris color due to polymerization. The goal of this study is to examine how the color of the artificial iris button is affected by different techniques of artificial wear and by the application of varnish following polymerization of the colorless acrylic resin that covers the colored paint. We produce 60 samples (n=10) according to the wear technique applied: conventional technique without varnish (PE); conventional technique with varnish (PEV); technique involving a prefabricated cap without varnish (CA); technique involving a prefabricated cap with varnish (CAV); technique involving inverted painting without varnish (PI); and technique involving inverted painting with varnish (PIV). Color readings using a spectrophotometer are taken before and after polymerization. We submitted the data obtained to analyses of variance and Tukey's test (P<0.05). The color test shows significant changes after polymerization in all groups. The PE and PI techniques have clinically acceptable values of ΔE, independent of whether we apply varnish to protect the paint. The PI technique produces the least color change, whereas the PE and CA techniques significantly improve color stability.

  7. Artificial intelligence techniques for photovoltaic applications: A review

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, Adel [Department of Electronics, Faculty of Sciences Engineering, LAMEL Laboratory, Jijel University, Oulad-aissa, P.O. Box 98, Jijel 18000 (Algeria); Kalogirou, Soteris A. [Department of Mechanical Engineering and Materials Science and Engineering, Cyprus University of Technology, P.O. Box 50329, Limassol 3603 (Cyprus)

    2008-10-15

    Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more popular nowadays. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with nonlinear problems and once trained can perform prediction and generalization at high speed. AI-based systems are being developed and deployed worldwide in a wide variety of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. AI has been used in different sectors, such as engineering, economics, medicine, military, marine, etc. They have also been applied for modeling, identification, optimization, prediction, forecasting and control of complex systems. The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in photovoltaic systems application. Problems presented include three areas: forecasting and modeling of meteorological data, sizing of photovoltaic systems and modeling, simulation and control of photovoltaic systems. Published literature presented in this paper show the potential of AI as design tool in photovoltaic systems. (author)

  8. Leading research on artificial techniques controlling cellular function; Saibo zoshoku seigyo gijutsu no sendo kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    Advanced research and its applicability were surveyed to apply the advanced functional cells to industry. The basic target was set to develop, produce, control and utilize the functional cells, such as intelligent materials and self-regulation bioreactors. The regulation factors regarding apotosis, which is a process of cell suicide programmed within the cell itself of multicellular organisms, cell cycle and aging/ageless were investigated. Furthermore, the function of regulatory factors was investigated at the protein level. Injection of factors regulating cellular function and tissue engineering required for the regulation of cell proliferation were investigated. Tissue engineering is considered to be the intracellular regulation by gene transduction and the extracellular regulation by culture methods, such as coculture. Analysis methods for cell proliferation and function of living cells were investigated using the probes recognizing molecular structure. Novel biomaterials, artificial organ systems, cellular therapy and useful materials were investigated for utilizing the regulation techniques of cell proliferation. 425 refs., 85 figs., 9 tabs.

  9. Application of Artificial Intelligence and Data Mining Techniques to Financial Markets

    OpenAIRE

    Katarína Hilovska; Peter Koncz

    2012-01-01

    The aim of artificial intelligence is to discover mechanisms of adaptation in a changing environment with utilisation of intelligence, for instance in the ability to exclude unlikely solutions. Artificial intelligence methods have extensive application in different fields such as medicine, games, transportation, or heavy industry. This paper deals with interdisciplinary issues – interconnection of artificial intelligence and finance. The paper briefly describes techniques of data mining, expe...

  10. Application of artificial intelligence techniques to TRR operation

    International Nuclear Information System (INIS)

    Ho, L.; Tseng, C.; Chang, S.

    1986-01-01

    It has been over ten years since TRR had its initial critical. To collect the experiences of shift operators and technique staffs and transfer these experts' knowledge to a computer and build an expert system is a typical application of artificial intelligence techniques to nuclear business. The system can provide the correct information of TRR operation for shift personnel, new staffs and other technical people

  11. Power system stabilizers based on modern control techniques

    Energy Technology Data Exchange (ETDEWEB)

    Malik, O P; Chen, G P; Zhang, Y; El-Metwally, K [Calgary Univ., AB (Canada). Dept. of Electrical and Computer Engineering

    1994-12-31

    Developments in digital technology have made it feasible to develop and implement improved controllers based on sophisticated control techniques. Power system stabilizers based on adaptive control, fuzzy logic and artificial networks are being developed. Each of these control techniques possesses unique features and strengths. In this paper, the relative performance of power systems stabilizers based on adaptive control, fuzzy logic and neural network, both in simulation studies and real time tests on a physical model of a power system, is presented and compared to that of a fixed parameter conventional power system stabilizer. (author) 16 refs., 45 figs., 3 tabs.

  12. Evolution of an artificial neural network based autonomous land vehicle controller.

    Science.gov (United States)

    Baluja, S

    1996-01-01

    This paper presents an evolutionary method for creating an artificial neural network based autonomous land vehicle controller. The evolved controllers perform better in unseen situations than those trained with an error backpropagation learning algorithm designed for this task. In this paper, an overview of the previous connectionist based approaches to this task is given, and the evolutionary algorithms used in this study are described in detail. Methods for reducing the high computational costs of training artificial neural networks with evolutionary algorithms are explored. Error metrics specific to the task of autonomous vehicle control are introduced; the evolutionary algorithms guided by these error metrics reveal improved performance over those guided by the standard sum-squared error metric. Finally, techniques for integrating evolutionary search and error backpropagation are presented. The evolved networks are designed to control Carnegie Mellon University's NAVLAB vehicles in road following tasks.

  13. Computer Aided Automatic Control - CAAC artificial intelligence block

    Energy Technology Data Exchange (ETDEWEB)

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

    2000-07-01

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

  14. Artificial intelligence-based modeling and control of fluidized bed combustion

    Energy Technology Data Exchange (ETDEWEB)

    Ikonen, E.; Leppaekoski, K. (Univ. of Oulu, Dept. of Process and Environmental Engineering (Finland)). email: enso.ikonen@oulu.fi

    2009-07-01

    AI-inspired techniques have a lot to offer when developing methods for advanced identification, monitoring, control and optimization of industrial processes, such as power plants. Advanced control methods have been extensively examined in the research of the Power Plant Automation group at the Systems Engineering Laboratory, e.g., in fuel inventory modelling, combustion power control, modelling and control of flue gas oxygen, drum control, modelling and control of superheaters, or in optimization of flue-gas emissions. Most engineering approaches to artificial intelligence (AI) are characterized by two fundamental properties: the ability to learn from various sources and the ability to deal with plant complexity. Learning systems that are able to operate in uncertain environments based on incomplete information are commonly referred to as being intelligent. A number of other approaches exist, characterized by these properties, but not easily categorized as AI-systems. Advanced control methods (adaptive, predictive, multivariable, robust, etc.) are based on the availability of a model of the process to be controlled. Hence identification of processes becomes a key issue, leading to the use of adaptation and learning techniques. A typical learning control system concerns a selection of learning techniques applied for updating a process model, which in turn is used for the controller design. When design of learning control systems is complemented with concerns for dealing with uncertainties or vaguenesses in models, measurements, or even objectives, particularly close connections exist between advanced process control and methods of artificial intelligence and machine learning. Needs for advanced techniques are typically characterized by the desire to properly handle plant non-linearities, the multivariable nature of the dynamic problems, and the necessity to adapt to changing plant conditions. In the field of fluidized bed combustion (FBC) control, the many promising

  15. An application of artificial intelligence theory to reconfigurable flight control

    Science.gov (United States)

    Handelman, David A.

    1987-01-01

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

  16. Deairing Techniques for Double-Ended Centrifugal Total Artificial Heart Implantation.

    Science.gov (United States)

    Karimov, Jamshid H; Horvath, David J; Byram, Nicole; Sunagawa, Gengo; Grady, Patrick; Sinkewich, Martin; Moazami, Nader; Sale, Shiva; Golding, Leonard A R; Fukamachi, Kiyotaka

    2017-06-01

    The unique device architecture of the Cleveland Clinic continuous-flow total artificial heart (CFTAH) requires dedicated and specific air-removal techniques during device implantation in vivo. These procedures comprise special surgical techniques and intraoperative manipulations, as well as engineering design changes and optimizations to the device itself. The current study evaluated the optimal air-removal techniques during the Cleveland Clinic double-ended centrifugal CFTAH in vivo implants (n = 17). Techniques and pump design iterations consisted of developing a priming method for the device and the use of built-in deairing ports in the early cases (n = 5). In the remaining cases (n = 12), deairing ports were not used. Dedicated air-removal ports were not considered an essential design requirement, and such ports may represent an additional risk for pump thrombosis. Careful passive deairing was found to be an effective measure with a centrifugal pump of this design. In this report, the techniques and design changes that were made during this CFTAH development program to enable effective residual air removal and prevention of air embolism during in vivo device implantation are explained. © 2016 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  17. Determination of rock depth using artificial intelligence techniques

    Institute of Scientific and Technical Information of China (English)

    R. Viswanathan; Pijush Samui

    2016-01-01

    This article adopts three artificial intelligence techniques, Gaussian Process Regression (GPR), Least Square Support Vector Machine (LSSVM) and Extreme Learning Machine (ELM), for prediction of rock depth (d) at any point in Chennai. GPR, ELM and LSSVM have been used as regression techniques. Latitude and longitude are also adopted as inputs of the GPR, ELM and LSSVM models. The performance of the ELM, GPR and LSSVM models has been compared. The developed ELM, GPR and LSSVM models produce spatial variability of rock depth and offer robust models for the prediction of rock depth.

  18. Training Software in Artificial-Intelligence Computing Techniques

    Science.gov (United States)

    Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

    2005-01-01

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

  19. THE COMPUTATIONAL INTELLIGENCE TECHNIQUES FOR PREDICTIONS - ARTIFICIAL NEURAL NETWORKS

    OpenAIRE

    Mary Violeta Bar

    2014-01-01

    The computational intelligence techniques are used in problems which can not be solved by traditional techniques when there is insufficient data to develop a model problem or when they have errors.Computational intelligence, as he called Bezdek (Bezdek, 1992) aims at modeling of biological intelligence. Artificial Neural Networks( ANNs) have been applied to an increasing number of real world problems of considerable complexity. Their most important advantage is solving problems that are too c...

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

    International Nuclear Information System (INIS)

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

    1985-01-01

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

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

    International Nuclear Information System (INIS)

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

    1986-01-01

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

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

    African Journals Online (AJOL)

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

  3. Artificial intelligence techniques for sizing photovoltaic systems. A review

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, A. [Department of Electronics, Faculty of Science Engineering, LAMEL Laboratory, Jijel University, P.O. Box 98, Oulad Aissa, Jijel 18000 (Algeria); Kalogirou, S.A. [Department of Mechanical Engineering and Materials Science and Engineering, Cyprus University of Technology, P.O. Box 50329, Limassol 3603 (Cyprus); Hontoria, L. [Grupo Investigacion y Desarrollo en Energia Solar y Automatica, Dpto. de Electronica, E.P.S. Jaen, Universidad de Jaen, Avda., Madrid, 35, 23071 Jaen (Spain); Shaari, S. [Faculty of Applied Sciences, Universiti Teknologi MARA 40450 Shah Alam, Selangor (Malaysia)

    2009-02-15

    Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. AI-techniques have the following features: can learn from examples; are fault tolerant in the sense that they are able to handle noisy and incomplete data; are able to deal with non-linear problems; and once trained can perform prediction and generalization at high speed. AI-based systems are being developed and deployed worldwide in a myriad of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. AI have been used and applied in different sectors, such as engineering, economics, medicine, military, marine, etc. They have also been applied for modeling, identification, optimization, prediction, forecasting, and control of complex systems. The main objective of this paper is to present an overview of the AI-techniques for sizing photovoltaic (PV) systems: stand-alone PVs, grid-connected PV systems, PV-wind hybrid systems, etc. Published literature presented in this paper show the potential of AI as a design tool for the optimal sizing of PV systems. Additionally, the advantage of using an AI-based sizing of PV systems is that it provides good optimization, especially in isolated areas, where the weather data are not always available. (author)

  4. Automation of fusion first wall design using artificial intelligence technique

    International Nuclear Information System (INIS)

    Yoshimura, Shinobu; Yagawa, Genki; Mochizuki, Yoshihiko

    1990-01-01

    This paper describes the application of artificial intelligence techniques to a design automation of the fusion first wall to be operated in the complex environment where huge electromagnetic and thermal loading as well as heavy neutron irradiation occur. As a basic strategy of designing structure shape considering many coupled phenomena, an ordinary design procedure based on the generate and test strategy is adopted because of its simplicity and broad applicability. To automate the design procedure with maintaining its flexibility, extensibility and efficiency, artificial intelligence techniques are utilized in the following. An object-oriented knowledge representation technique is adopted to store knowledge modules, that is, objects, related to the first wall design, while a data-flow processing technique is utilized as an inference mechanism among the knowledge modules. These techniques realize the flexibility and extensibility of the system. Moreover, as an efficient design modification mechanism, which is essential in a design process, an empirical approach based on experts' empirical knowledge and a mathematical approach based on a kind of numerical sensitivity analysis are introduced. The developed system is applied to a simple example of the design of a two-dimensional model of the first wall with a cooling channel, and its fundamental performance is clearly demonstrated. (author)

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

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

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

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

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2003-01-01

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

  7. Artificial Intelligence techniques for big data analysis

    OpenAIRE

    Aditya Khatri

    2017-01-01

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

  8. Whispering galleries and the control of artificial atoms.

    Science.gov (United States)

    Forrester, Derek Michael; Kusmartsev, Feodor V

    2016-04-28

    Quantum computation using artificial-atoms, such as novel superconducting circuits, can be sensitively controlled by external electromagnetic fields. These fields and the self-fields attributable to the coupled artificial-atoms influence the amount of quantum correlation in the system. However, control elements that can operate without complete destruction of the entanglement of the quantum-bits are difficult to engineer. Here we investigate the possibility of using closely-spaced-linear arrays of metallic-elliptical discs as whispering gallery waveguides to control artificial-atoms. The discs confine and guide radiation through the array with small notches etched into their sides that act as scatterers. We focus on π-ring artificial-atoms, which can generate their own spontaneous fluxes. We find that the micro-discs of the waveguides can be excited by terahertz frequency fields to exhibit whispering-modes and that a quantum-phase-gate composed of π-rings can be operated under their influence. Furthermore, we gauge the level of entanglement through the concurrence measure and show that under certain magnetic conditions a series of entanglement sudden-deaths and revivals occur between the two qubits. This is important for understanding the stability and life-time of qubit operations using, for example, a phase gate in a hybrid of quantum technologies composed of control elements and artificial-atoms.

  9. The application of neural networks with artificial intelligence technique in the modeling of industrial processes

    International Nuclear Information System (INIS)

    Saini, K. K.; Saini, Sanju

    2008-01-01

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  10. Application of Artificial Intelligence Techniques for the Control of the Asynchronous Machine

    Directory of Open Access Journals (Sweden)

    F. Khammar

    2016-01-01

    Full Text Available The induction machine is experiencing a growing success for two decades by gradually replacing the DC machines and synchronous in many industrial applications. This paper is devoted to the study of advanced methods applied to the command of the asynchronous machine in order to obtain a system of control of high performance. While the criteria for response time, overtaking, and static error can be assured by the techniques of conventional control, the criterion of robustness remains a challenge for researchers. This criterion can be satisfied only by applying advanced techniques of command. After mathematical modeling of the asynchronous machine, it defines the control strategies based on the orientation of the rotor flux. The results of the different simulation tests highlight the properties of robustness of algorithms proposed and suggested to compare the different control strategies.

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

    International Nuclear Information System (INIS)

    Cain, D.G.

    1986-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jackson Phiri

    2011-08-01

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

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

    Science.gov (United States)

    1996-01-01

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

  14. Moderate hypothermia technique for chronic implantation of a total artificial heart in calves.

    Science.gov (United States)

    Karimov, Jamshid H; Grady, Patrick; Sinkewich, Martin; Sunagawa, Gengo; Dessoffy, Raymond; Byram, Nicole; Moazami, Nader; Fukamachi, Kiyotaka

    2017-06-01

    The benefit of whole-body hypothermia in preventing ischemic injury during cardiac surgical operations is well documented. However, application of hypothermia during in vivo total artificial heart implantation has not become widespread because of limited understanding of the proper techniques and restrictions implied by constitutional and physiological characteristics specific to each animal model. Similarly, the literature on hypothermic set-up in total artificial heart implantation has also been limited. Herein we present our experience using hypothermia in bovine models implanted with the Cleveland Clinic continuous-flow total artificial heart.

  15. Control system for solar tracking based on artificial vision; Sistema de control para seguimiento solar basado en vision artificial

    Energy Technology Data Exchange (ETDEWEB)

    Pacheco Ramirez, Jesus Horacio; Anaya Perez, Maria Elena; Benitez Baltazar, Victor Hugo [Universidad de onora, Hermosillo, Sonora (Mexico)]. E-mail: jpacheco@industrial.uson.mx; meanaya@industrial.uson.mx; vbenitez@industrial.uson.mx

    2010-11-15

    This work shows how artificial vision feedback can be applied to control systems. The control is applied to a solar panel in order to track the sun position. The algorithms to calculate the position of the sun and the image processing are developed in LabView. The responses obtained from the control show that it is possible to use vision for a control scheme in closed loop. [Spanish] El presente trabajo muestra la manera en la cual un sistema de control puede ser retroalimentado mediante vision artificial. El control es aplicado en un panel solar para realizar el seguimiento del sol a lo largo del dia. Los algoritmos para calcular la posicion del sol y para el tratamiento de la imagen fueron desarrollados en LabView. Las respuestas obtenidas del control muestran que es posible utilizar vision para un esquema de control en lazo cerrado.

  16. Advanced instrumentation and control techniques for nuclear power plants

    International Nuclear Information System (INIS)

    Hayakawa, Hiroyasu; Makino, Maomi

    1989-01-01

    Toshiba has been promoting the development and improvement of control and instrumentation (C and I) systems employing the latest technologies, to fulfill the requirements of nuclear power plants for increased reliability, the upgrading of functions, improved maintainability, and reasonable cost. Such development has been systematically performed based on a schematic view of integrated digital control and instrumentation systems, actively adopting state-of-the-art techniques such as the latest man-machine interfaces, digital and optical multiplexing techniques, and artificial intelligence. In addition, comprehensive feedback has been obtained from the accumulation of operating experience. This paper describes the purpose, contents and status of applications of representative newly-developed systems. (author)

  17. Developments in operator assistance techniques for nuclear power plant control and operation

    International Nuclear Information System (INIS)

    Poujol, A.; Papin, B.; Beltranda, G.; Soldermann, R.

    1989-01-01

    This paper describes an approach which has been developed in order to improve nuclear power plants control and monitoring in normal and abnormal situations. These developments take full advantage of the trend towards the computerization of control rooms in industrial continuous processes. This research program consists in a thorough exploration of different information processing techniques, ranking from the rather simple visual synthetization of informations on graphic displays to sophisticated Artificial Intelligence (AI) techniques. These techniques are put into application for the solving of man-machine interface problems in the different domains of plant operation

  18. Intelligent Switching Control of Pneumatic Artificial Muscle Manipulator

    Science.gov (United States)

    Ahn, Kyoung Kwan; Thanh, Tu Diep Cong; Ahn, Young Kong

    Problems with the control, oscillatory motion and compliance of pneumatic systems have prevented their widespread use in advanced robotics. However, their compactness, power/weight ratio, ease of maintenance and inherent safety are the factors that could potentially be exploited in sophisticated dexterous manipulator designs. These advantages have led to the development of novel actuators such as the McKibben Muscle, Rubber Actuator and Pneumatic Artificial Muscle Manipulators. However, some limitations still exist, such as deterioration of the performance of transient response due to the change of the external inertia load in the pneumatic artificial muscle manipulator. To overcome this problem, switching algorithm of control parameter using learning vector quantization neural network (LVQNN) is newly proposed, which estimates the external inertia load of the pneumatic artificial muscle manipulator. The effectiveness of the proposed control algorithm is demonstrated through experiments with different external inertia loads.

  19. LARA. Localization of an automatized refueling machine by acoustical sounding in breeder reactors - implementation of artificial intelligence techniques

    International Nuclear Information System (INIS)

    Lhuillier, C.; Malvache, P.

    1987-01-01

    The automatic control of the machine which handles the nuclear subassemblies in fast neutron reactors requires autonomous perception and decision tools. An acoustical device allows the machine to position in the work area. Artificial intelligence techniques are implemented to interpret the data: pattern recognition, scene analysis. The localization process is managed by an expert system. 6 refs.; 8 figs

  20. Artificial intelligence in robot control systems

    Science.gov (United States)

    Korikov, A.

    2018-05-01

    This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.

  1. Artificial intelligence techniques for scheduling Space Shuttle missions

    Science.gov (United States)

    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.

  2. Control performance of pneumatic artificial muscle

    Science.gov (United States)

    Saga, Norihiko; Chonan, Seiji

    2007-01-01

    The robot in the future will be lightened and, in addition, the complex tasks will be done by the consumption of less energy. To achieve this, the development of an artificial muscle actuator which is as soft as a human-being becomes indispensable. At present, the artificial muscle actuator used is the McKibben type, but the heat and mechanical loss of this actuator are large because of the friction caused by the expansion and contraction of the sleeve. Therefore, we developed the artificial muscle tube where the Carbon fiber of the high intensity had been built into the silicon tube. In this report, the results of the examined the mechanical property of silicone rubber is reported, and the shrinking characteristics, response characteristics, and control performance as a pneumatic actuator are reported.

  3. Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

    Energy Technology Data Exchange (ETDEWEB)

    Zarzalejo, L.F.; Ramirez, L.; Polo, J. [DER-CIEMAT, Madrid (Spain). Renewable Energy Dept.

    2005-07-01

    Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models. (author)

  4. Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

    International Nuclear Information System (INIS)

    Zarzalejo, Luis F.; Ramirez, Lourdes; Polo, Jesus

    2005-01-01

    Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models

  5. Effect of Instrumentation Techniques, Irrigant Solutions and Artificial accelerated Aging on Fiberglass Post Bond Strength to Intraradicular Dentin.

    Science.gov (United States)

    Santana, Fernanda Ribeiro; Soares, Carlos José; Silva, Júlio Almeida; Alencar, Ana Helena Gonçalves; Renovato, Sara Rodrigues; Lopes, Lawrence Gonzaga; Estrela, Carlos

    2015-07-01

    To evaluate the effect of instrumentation techniques, irrigant solutions and specimen aging on fiberglass posts bond strength to intraradicular dentine. A total of 120 bovine teeth were prepared and randomized into control and experimental groups resulting from three study factors (instrumentation techniques, irrigant solutions, specimen aging). Posts were cemented with RelyX U100. Samples were submitted to push-out test and failure mode was evaluated under a confocal microscope. In specimens submitted to water artificial aging, nickel-titanium rotary instruments group presented higher bond strength values in apical third irrigated with NaOCl or chlorhexi-dine. Irrigation with NaOCl resulted in higher bond strength than ozonated water. Artificial aging resulted in significant bond strength increase. Adhesive cement-dentin failure was prevalent in all the groups. Root canal preparation with NiTi instruments associated with NaOCl irrigation and ethylenediaminetetra acetic acid (EDTA) increased bond strength of fiberglass posts cemented with self-adhesive resin cement to intraradicular dentine. Water artificial aging significantly increased post-Clinical significance: The understanding of factors that may influence the optimal bond between post-cement and cement-dentin are essential to the success of endodontically treated tooth restoration.

  6. Artificial intelligence techniques for embryo and oocyte classification.

    Science.gov (United States)

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

    2013-01-01

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

  7. LFC based adaptive PID controller using ANN and ANFIS techniques

    Directory of Open Access Journals (Sweden)

    Mohamed I. Mosaad

    2014-12-01

    Full Text Available This paper presents an adaptive PID Load Frequency Control (LFC for power systems using Neuro-Fuzzy Inference Systems (ANFIS and Artificial Neural Networks (ANN oriented by Genetic Algorithm (GA. PID controller parameters are tuned off-line by using GA to minimize integral error square over a wide-range of load variations. The values of PID controller parameters obtained from GA are used to train both ANFIS and ANN. Therefore, the two proposed techniques could, online, tune the PID controller parameters for optimal response at any other load point within the operating range. Testing of the developed techniques shows that the adaptive PID-LFC could preserve optimal performance over the whole loading range. Results signify superiority of ANFIS over ANN in terms of performance measures.

  8. Fault diagnosis in nuclear power plants using an artificial neural network technique

    International Nuclear Information System (INIS)

    Chou, H.P.; Prock, J.; Bonfert, J.P.

    1993-01-01

    Application of artificial intelligence (AI) computational techniques, such as expert systems, fuzzy logic, and neural networks in diverse areas has taken place extensively. In the nuclear industry, the intended goal for these AI techniques is to improve power plant operational safety and reliability. As a computerized operator support tool, the artificial neural network (ANN) approach is an emerging technology that currently attracts a large amount of interest. The ability of ANNs to extract the input/output relation of a complicated process and the superior execution speed of a trained ANN motivated this study. The goal was to develop neural networks for sensor and process faults diagnosis with the potential of implementing as a component of a real-time operator support system LYDIA, early sensor and process fault detection and diagnosis

  9. Short-term Local Forecasting by Artificial Intelligence Techniques and Assess Related Social Effects from Heterogeneous Data

    OpenAIRE

    Gong, Bing

    2017-01-01

    This work aims to use the sophisticated artificial intelligence and statistic techniques to forecast pollution and assess its social impact. To achieve the target of the research, this study is divided into several research sub-objectives as follows: First research sub-objective: propose a framework for relocating and reconfiguring the existing pollution monitoring networks by using feature selection, artificial intelligence techniques, and information theory. Second research sub-objective: c...

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

    Science.gov (United States)

    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.

  11. Development of an Accident Diagnostic Scheme Using Artificial Intelligence Techniques (I)

    Energy Technology Data Exchange (ETDEWEB)

    Na, M. G.; Lee, S. H.; Kim, D. S.; No, Y. G.; Lee, S. W. [Chosun University, Gwangju (Korea, Republic of); Ahn, K. I. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2010-06-15

    As a means to effectively manage the severe nuclear accidents, it is important to identify and diagnose the accident initiating events during an initial short time interval after the accidents by observing the major controlling parameters. Main objective of this study is to develop the diagnostic approach for the accurate prediction of accident initiating events using artificial intelligence techniques. For this, first, a variety of artificial intelligence techniques such as Finn, Gmbh, and Sm were examined through this study. Among them, Sc and Gmbh model were assessed as a useful approach to predict the break location and the break size of Local. In order to verify the proposed algorithm, the 111 accident simulation data (based on Map) were applied to train the Sc and Gmbh models, and the test data was used to independently verify whether or not the SVC and GMDH models work well. The analysis of the maximum errors and RMS errors, and the performance of the GMDH according to the existence of measurement errors and SIS actuation showed that the proposed SVC and GMDH models can accurately classify the break locations and accurately predict the break size. As the time-integrated signals were used for inputs into the GMDH model within a period of 60 second after a reactor scram, the actuation of the safety systems such as safety injection system (SIS), auxiliary feed water system, and containment spray system, were not considered in this study. It is because the initial 60 second time-integrated signals were used and the safety systems usually start to actuate after a more than 60 second time delay after the reactor scram

  12. Development of an Accident Diagnostic Scheme Using Artificial Intelligence Techniques (I)

    International Nuclear Information System (INIS)

    Na, M. G.; Lee, S. H.; Kim, D. S.; No, Y. G.; Lee, S. W.; Ahn, K. I.

    2010-06-01

    As a means to effectively manage the severe nuclear accidents, it is important to identify and diagnose the accident initiating events during an initial short time interval after the accidents by observing the major controlling parameters. Main objective of this study is to develop the diagnostic approach for the accurate prediction of accident initiating events using artificial intelligence techniques. For this, first, a variety of artificial intelligence techniques such as Finn, Gmbh, and Sm were examined through this study. Among them, Sc and Gmbh model were assessed as a useful approach to predict the break location and the break size of Local. In order to verify the proposed algorithm, the 111 accident simulation data (based on Map) were applied to train the Sc and Gmbh models, and the test data was used to independently verify whether or not the SVC and GMDH models work well. The analysis of the maximum errors and RMS errors, and the performance of the GMDH according to the existence of measurement errors and SIS actuation showed that the proposed SVC and GMDH models can accurately classify the break locations and accurately predict the break size. As the time-integrated signals were used for inputs into the GMDH model within a period of 60 second after a reactor scram, the actuation of the safety systems such as safety injection system (SIS), auxiliary feed water system, and containment spray system, were not considered in this study. It is because the initial 60 second time-integrated signals were used and the safety systems usually start to actuate after a more than 60 second time delay after the reactor scram

  13. Current topics in glycemic control by wearable artificial pancreas or bedside artificial pancreas with closed-loop system.

    Science.gov (United States)

    Hanazaki, Kazuhiro; Munekage, Masaya; Kitagawa, Hiroyuki; Yatabe, Tomoaki; Munekage, Eri; Shiga, Mai; Maeda, Hiromichi; Namikawa, Tsutomu

    2016-09-01

    The incidence of diabetes is increasing at an unprecedented pace and has become a serious health concern worldwide during the last two decades. Despite this, adequate glycemic control using an artificial pancreas has not been established, although the 21st century has seen rapid developments in this area. Herein, we review current topics in glycemic control for both the wearable artificial pancreas for type 1 and type 2 diabetic patients and the bedside artificial pancreas for surgical diabetic patients. In type 1 diabetic patients, nocturnal hypoglycemia associated with insulin therapy remains a serious problem that could be addressed by the recent development of a wearable artificial pancreas. This smart phone-like device, comprising a real-time, continuous glucose monitoring system and insulin pump system, could potentially significantly reduce nocturnal hypoglycemia compared with conventional glycemic control. Of particular interest in this space are the recent inventions of a low-glucose suspend feature in the portable systems that automatically stops insulin delivery 2 h following a glucose sensor value <70 mg/dL and a bio-hormonal pump system consisting of insulin and glucagon pumps. Perioperative tight glycemic control using a bedside artificial pancreas with the closed-loop system has also proved safe and effective for not only avoiding hypoglycemia, but also for reducing blood glucose level variability resulting in good surgical outcomes. We hope that a more sophisticated artificial pancreas with closed-loop system will now be taken up for routine use worldwide, providing enormous relief for patients suffering from uncontrolled hyperglycemia, hypoglycemia, and/or variability in blood glucose concentrations.

  14. Inspection of an artificial heart by the neutron radiography technique

    International Nuclear Information System (INIS)

    Pugliesi, R.; Geraldo, L.P.; Andrade, M.L.G.; Menezes, M.O.; Pereira, M.A.S.; Maizato, M.J.S.

    1999-01-01

    The neutron radiography technique was employed to inspect an artificial heart prototype which is being developed to provide blood circulation for patients expecting heart transplant surgery. The radiographs have been obtained by the direct method with a gadolinium converter screen along with the double coated Kodak-AA emulsion film. The artificial heart consists of a flexible plastic membrane located inside a welded metallic cavity, which is employed for blood pumping purposes. The main objective of the present inspection was to identify possible damages in this plastic membrane, produced during the welding process of the metallic cavity. The obtained radiographs were digitized as well as analysed in a PC and the improved images clearly identify several damages in the plastic membrane, suggesting changes in the welding process

  15. Inspection of an artificial heart by the neutron radiography technique

    CERN Document Server

    Pugliesi, R; Andrade, M L G; Menezes, M O; Pereira, M A S; Maizato, M J S

    1999-01-01

    The neutron radiography technique was employed to inspect an artificial heart prototype which is being developed to provide blood circulation for patients expecting heart transplant surgery. The radiographs have been obtained by the direct method with a gadolinium converter screen along with the double coated Kodak-AA emulsion film. The artificial heart consists of a flexible plastic membrane located inside a welded metallic cavity, which is employed for blood pumping purposes. The main objective of the present inspection was to identify possible damages in this plastic membrane, produced during the welding process of the metallic cavity. The obtained radiographs were digitized as well as analysed in a PC and the improved images clearly identify several damages in the plastic membrane, suggesting changes in the welding process.

  16. Artificial lateral-line system for imaging dipole sources using Beamforming techniques

    NARCIS (Netherlands)

    Dagamseh, A.M.K.; Wiegerink, Remco J.; Lammerink, Theodorus S.J.; Krijnen, Gijsbertus J.M.

    In nature, fish have the ability to localize prey, school, navigate, etc. using the lateral-line organ [1]. Here we present the use of biomimetic artificial hair-based flow-sensors arranged as lateral-line system in combination with beamforming techniques for dipole source localization in air.

  17. Colonization of Lutzomyia shannoni (Diptera: Psychodidae) utilizing an artificial blood feeding technique.

    Science.gov (United States)

    Mann, Rajinder S; Kaufman, Phillip E

    2010-12-01

    Laboratory colonization of hematophagous insects must include an efficient method of blood feeding, preferably by artificial means. Strict rules for obtaining animal use permits, extensive animal maintenance costs, and indirect anesthesia effects on animal health warrant the development of an artificial membrane feeding technique for sand fly colonization in laboratories. An attempt was made to colonize Lutzomyia shannoni using an artificial blood feeding membrane to replace the use of live animals commonly used for sand fly blood-feeding purposes. Lutzomyia shannoni readily fed through a pig intestine membrane exposed at an angle of 45°. However, it did not feed through a chicken skin membrane. Olfactory attractants were unable to improve blood-feeding efficiency. Plaster of Paris was the most suitable oviposition substrate. Female L. shannoni adults laid no eggs on moist sand substrate. Sand fly adults held in groups of ten or more laid higher numbers of eggs than did individually maintained sand flies. Inclusion of the L. longipalpis oviposition hormone dodecanoic acid or the presence of previously laid eggs did not stimulate L. shannoni oviposition. The average L. shannoni egg, larval, and pupal duration were 9.3, 36.7, and 17.8 days, respectively. The addition of a 20% sugar solution improved adult female longevity. Females survived longer (14.8 days) than males (11.9 days). Lutzomyia shannoni was successfully colonized in the laboratory for up to four generations using this artificial membrane technique. © 2010 The Society for Vector Ecology.

  18. Control approach development for variable recruitment artificial muscles

    Science.gov (United States)

    Jenkins, Tyler E.; Chapman, Edward M.; Bryant, Matthew

    2016-04-01

    This study characterizes hybrid control approaches for the variable recruitment of fluidic artificial muscles with double acting (antagonistic) actuation. Fluidic artificial muscle actuators have been explored by researchers due to their natural compliance, high force-to-weight ratio, and low cost of fabrication. Previous studies have attempted to improve system efficiency of the actuators through variable recruitment, i.e. using discrete changes in the number of active actuators. While current variable recruitment research utilizes manual valve switching, this paper details the current development of an online variable recruitment control scheme. By continuously controlling applied pressure and discretely controlling the number of active actuators, operation in the lowest possible recruitment state is ensured and working fluid consumption is minimized. Results provide insight into switching control scheme effects on working fluids, fabrication material choices, actuator modeling, and controller development decisions.

  19. Contribution of artificial intelligence to operation

    International Nuclear Information System (INIS)

    Malvache, P.; Mourlevat, J.L.

    1993-01-01

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

  20. Redox control of molecular motion in switchable artificial nanoscale devices.

    Science.gov (United States)

    Credi, Alberto; Semeraro, Monica; Silvi, Serena; Venturi, Margherita

    2011-03-15

    The design, synthesis, and operation of molecular-scale systems that exhibit controllable motions of their component parts is a topic of great interest in nanoscience and a fascinating challenge of nanotechnology. The development of this kind of species constitutes the premise to the construction of molecular machines and motors, which in a not-too-distant future could find applications in fields such as materials science, information technology, energy conversion, diagnostics, and medicine. In the past 25 years the development of supramolecular chemistry has enabled the construction of an interesting variety of artificial molecular machines. These devices operate via electronic and molecular rearrangements and, like the macroscopic counterparts, they need energy to work as well as signals to communicate with the operator. Here we outline the design principles at the basis of redox switching of molecular motion in artificial nanodevices. Redox processes, chemically, electrically, or photochemically induced, can indeed supply the energy to bring about molecular motions. Moreover, in the case of electrically and photochemically induced processes, electrochemical and photochemical techniques can be used to read the state of the system, and thus to control and monitor the operation of the device. Some selected examples are also reported to describe the most representative achievements in this research area.

  1. An on-line gas control system using an artificial intelligence language: PROLOG II

    International Nuclear Information System (INIS)

    Lai, C.

    1990-01-01

    An application of Artificial Intelligence to a real physics experiment is presented. This allows comparison with classical programming techniques. The PROLOG language appears as a convenient on-line language, easily interfaced to the low level service routines, for which algorithmic languages can still be used. Steering modules have been written for a gas acquisition and analysis program, and for a control system with graphic human interface. This system includes safety rules and automatic action sequences

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

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  3. Artificial intelligence for the modeling and control of combustion processes: a review

    Energy Technology Data Exchange (ETDEWEB)

    Kalogirou, S.A. [Higher Technical Inst., Nicosia, Cyprus (Greece). Dept. of Mechanical Engineering

    2003-07-01

    Artificial intelligence (AI) systems are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems, and once trained can perform prediction and generalization at high speed. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing, and social/psychological sciences. They are particularly useful in system modeling such as in implementing complex mappings and system identification. Al systems comprise areas like, expert systems, artificial neural networks, genetic algorithms, fuzzy logic and various hybrid systems, which combine two or more techniques. The major objective of this paper is to illustrate how Al techniques might play an important role in modeling and prediction of the performance and control of combustion process. The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in the different disciplines of combustion engineering. The various applications of AI are presented in a thematic rather than a chronological or any other order. Problems presented include two main areas: combustion systems and internal combustion (IC) engines. Combustion systems include boilers, furnaces and incinerators modeling and emissions prediction, whereas, IC engines include diesel and spark ignition engines and gas engines modeling and control. Results presented in this paper, are testimony to the potential of Al as a design tool in many areas of combustion engineering. (author)

  4. Transport modeling: An artificial immune system approach

    Directory of Open Access Journals (Sweden)

    Teodorović Dušan

    2006-01-01

    Full Text Available This paper describes an artificial immune system approach (AIS to modeling time-dependent (dynamic, real time transportation phenomenon characterized by uncertainty. The basic idea behind this research is to develop the Artificial Immune System, which generates a set of antibodies (decisions, control actions that altogether can successfully cover a wide range of potential situations. The proposed artificial immune system develops antibodies (the best control strategies for different antigens (different traffic "scenarios". This task is performed using some of the optimization or heuristics techniques. Then a set of antibodies is combined to create Artificial Immune System. The developed Artificial Immune transportation systems are able to generalize, adapt, and learn based on new knowledge and new information. Applications of the systems are considered for airline yield management, the stochastic vehicle routing, and real-time traffic control at the isolated intersection. The preliminary research results are very promising.

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

    Directory of Open Access Journals (Sweden)

    Julia M. Núñez Tabale

    2016-12-01

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

  6. Leak detection and localization in natural and artificial dams using tracer techniques

    International Nuclear Information System (INIS)

    Molinari, J.

    1975-01-01

    Leak detection and localization procedures using often-unknown techniques of identification by natural or artificial tracers are reported. From the analysis of data supplied by natural tracers, or by artificial tracer methods which involve the direct observation of warning phenomena, it is possible to estimate the extent of the infiltrations, define their origin and under certain circumstances determine the main hydrodynamic flow parameters so that their development may be followed. The examples of application and interpretation were taken from the numerous studies carried out in this field by the CEA, where many original investigation methods have been employed [fr

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

    International Nuclear Information System (INIS)

    Plander, I.

    1987-01-01

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

  8. Myoelectric control of artificial limb inspired by quantum information processing

    International Nuclear Information System (INIS)

    Siomau, Michael; Jiang, Ning

    2015-01-01

    Precise and elegant coordination of a prosthesis across many degrees of freedom represents a significant challenge to efficient rehabilitation of people with limb deficiency. Processing the electrical neural signals collected from the surface of the remnant muscles of the stump is a common way to initiate and control the different movements available to the artificial limb. Based on the assumption that there are distinguishable and repeatable signal patterns among different types of muscular activation, the problem of prosthesis control reduces to one of pattern recognition. Widely accepted classical methods for pattern recognition, however, cannot provide simultaneous and proportional control of the artificial limb. Here we show that, in principle, quantum information processing of the neural signals allows us to overcome the above-mentioned difficulties, suggesting a very simple scheme for myoelectric control of artificial limb with advanced functionalities. (paper)

  9. Use of nuclear techniques in biological control

    International Nuclear Information System (INIS)

    Greany, Patrick D.; Carpenter, James E.

    2000-01-01

    As pointed out by Benbrook (1996), pest management is at a crossroads, and there is a great need for new, biointensive pest management strategies. Among these approaches, biological control is a keystone. However, because of increasing concerns about the introduction of exotic natural enemies of insect pests and weeds (Howarth 1991, Delfosse 1997), the overall thrust of biological control has moved toward augmentative biological control, involving releases of established natural enemy species (Knipling 1992). This in turn has created a need to develop more cost-effective mass rearing technologies for beneficial insects. Nuclear techniques could play an especially important role in augmentative biological control, not only in facilitating mass rearing, but in several other ways, as indicated below. Recognising the potential value for use of nuclear techniques in biological control, the Insect and Pest Control Section of the Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture, International Atomic Energy Agency, sponsored a Consultants' Group Meeting on this subject in April 1997. The Group produced a document entitled Use of Nuclear Techniques in Biological Control: Managing Pests, Facilitating Trade and Protecting the Environment. The consultants included the authors of this paper as well as Ernest Delfosse (at that time, with the USDA-APHIS National Biological Control Institute), Garry Hill (Intl. Institute for Biological Control), Sinthya Penn (Beneficial Insectary), and Felipe Jeronimo (USDA-APHIS PPQ, Guatemala). The remarks presented in this paper reflect the thoughts presented by these consultants and other participants at the IAEA-sponsored meeting. Several potential uses for nuclear techniques were identified by the Consultants' Group, including: 1) improvements in rearing media (either artificial diets or natural hosts/prey), 2) provision of sterilised natural prey to be used as food during shipment, to ameliorate concerns relating to the

  10. Multi-Layer Artificial Neural Networks Based MPPT-Pitch Angle Control of a Tidal Stream Generator

    Directory of Open Access Journals (Sweden)

    Khaoula Ghefiri

    2018-04-01

    Full Text Available Artificial intelligence technologies are widely investigated as a promising technique for tackling complex and ill-defined problems. In this context, artificial neural networks methodology has been considered as an effective tool to handle renewable energy systems. Thereby, the use of Tidal Stream Generator (TSG systems aim to provide clean and reliable electrical power. However, the power captured from tidal currents is highly disturbed due to the swell effect and the periodicity of the tidal current phenomenon. In order to improve the quality of the generated power, this paper focuses on the power smoothing control. For this purpose, a novel Artificial Neural Network (ANN is investigated and implemented to provide the proper rotational speed reference and the blade pitch angle. The ANN supervisor adequately switches the system in variable speed and power limitation modes. In order to recover the maximum power from the tides, a rotational speed control is applied to the rotor side converter following the Maximum Power Point Tracking (MPPT generated from the ANN block. In case of strong tidal currents, a pitch angle control is set based on the ANN approach to keep the system operating within safe limits. Two study cases were performed to test the performance of the output power. Simulation results demonstrate that the implemented control strategies achieve a smoothed generated power in the case of swell disturbances.

  11. Artificial Intelligence Techniques for Predicting and Mapping Daily Pan Evaporation

    Science.gov (United States)

    Arunkumar, R.; Jothiprakash, V.; Sharma, Kirty

    2017-09-01

    In this study, Artificial Intelligence techniques such as Artificial Neural Network (ANN), Model Tree (MT) and Genetic Programming (GP) are used to develop daily pan evaporation time-series (TS) prediction and cause-effect (CE) mapping models. Ten years of observed daily meteorological data such as maximum temperature, minimum temperature, relative humidity, sunshine hours, dew point temperature and pan evaporation are used for developing the models. For each technique, several models are developed by changing the number of inputs and other model parameters. The performance of each model is evaluated using standard statistical measures such as Mean Square Error, Mean Absolute Error, Normalized Mean Square Error and correlation coefficient (R). The results showed that daily TS-GP (4) model predicted better with a correlation coefficient of 0.959 than other TS models. Among various CE models, CE-ANN (6-10-1) resulted better than MT and GP models with a correlation coefficient of 0.881. Because of the complex non-linear inter-relationship among various meteorological variables, CE mapping models could not achieve the performance of TS models. From this study, it was found that GP performs better for recognizing single pattern (time series modelling), whereas ANN is better for modelling multiple patterns (cause-effect modelling) in the data.

  12. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system

    OpenAIRE

    Mohamed, Ahmed F.; Elarini, Mahdi M.; Othman, Ahmed M.

    2013-01-01

    One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) whic...

  13. Structural investigation and simulation of acoustic properties of some tellurite glasses using artificial intelligence technique

    International Nuclear Information System (INIS)

    Gaafar, M.S.; Abdeen, Mostafa A.M.; Marzouk, S.Y.

    2011-01-01

    Research highlights: → Simulation the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). → The glass network is strengthened by enhancing the linkage of Te-O chains. The tellurite network will also come to homogenization, because of uniform distribution of Nb 5+ ions among the Te-O chains, though some of the tellurium-oxide polyhedra still link each other in edge sharing. → Excellent agreements between the measured values and the predicted values were obtained for over 50 different tellurite glass compositions. → The model we designed gives a better agreement as compared with Makishima and Machenzie model. - Abstract: The developments in the field of industry raise the need for simulating the acoustic properties of glass materials before melting raw material oxides. In this paper, we are trying to simulate the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). The artificial neural network (ANN) technique is introduced in the current study to simulate and predict important parameters such as density, longitudinal and shear ultrasonic velocities and elastic moduli (longitudinal and shear moduli). The ANN results were found to be in successful good agreement with those experimentally measured parameters. Then the presented ANN model is used to predict the acoustic properties of some new tellurite glasses. For this purpose, four glass systems xNb 2 O 5 -(1 - x)TeO 2 , 0.1PbO-xNb 2 O 5 -(0.9 - x)TeO 2 , 0.2PbO-xNb 2 O 5 -(0.8 - x)TeO 2 and 0.05Bi 2 O 3 -xNb 2 O 5 -(0.95 - x)TeO 2 were prepared using melt quenching technique. The results of ultrasonic velocities and elastic moduli showed that the addition of Nb 2 O 5 as a network modifier provides oxygen ions to change [TeO 4 ] tbps into [TeO 3 ] tps.

  14. Structural investigation and simulation of acoustic properties of some tellurite glasses using artificial intelligence technique

    Energy Technology Data Exchange (ETDEWEB)

    Gaafar, M.S., E-mail: mohamed_s_gaafar@hotmail.com [Ultrasonic Department, National Institute for Standards, Giza (Egypt); Physics Department, Faculty of Science, Majmaah University, Zulfi (Saudi Arabia); Abdeen, Mostafa A.M., E-mail: mostafa_a_m_abdeen@hotmail.com [Dept. of Eng. Math. and Physics, Faculty of Eng., Cairo University, Giza (Egypt); Marzouk, S.Y., E-mail: samir_marzouk2001@yahoo.com [Arab Academy of Science and Technology, Al-Horria, Heliopolis, Cairo (Egypt)

    2011-02-24

    Research highlights: > Simulation the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). > The glass network is strengthened by enhancing the linkage of Te-O chains. The tellurite network will also come to homogenization, because of uniform distribution of Nb{sup 5+} ions among the Te-O chains, though some of the tellurium-oxide polyhedra still link each other in edge sharing. > Excellent agreements between the measured values and the predicted values were obtained for over 50 different tellurite glass compositions. > The model we designed gives a better agreement as compared with Makishima and Machenzie model. - Abstract: The developments in the field of industry raise the need for simulating the acoustic properties of glass materials before melting raw material oxides. In this paper, we are trying to simulate the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). The artificial neural network (ANN) technique is introduced in the current study to simulate and predict important parameters such as density, longitudinal and shear ultrasonic velocities and elastic moduli (longitudinal and shear moduli). The ANN results were found to be in successful good agreement with those experimentally measured parameters. Then the presented ANN model is used to predict the acoustic properties of some new tellurite glasses. For this purpose, four glass systems xNb{sub 2}O{sub 5}-(1 - x)TeO{sub 2}, 0.1PbO-xNb{sub 2}O{sub 5}-(0.9 - x)TeO{sub 2}, 0.2PbO-xNb{sub 2}O{sub 5}-(0.8 - x)TeO{sub 2} and 0.05Bi{sub 2}O{sub 3}-xNb{sub 2}O{sub 5}-(0.95 - x)TeO{sub 2} were prepared using melt quenching technique. The results of ultrasonic velocities and elastic moduli showed that the addition of Nb{sub 2}O{sub 5} as a network modifier provides oxygen ions to change [TeO{sub 4}] tbps into [TeO{sub 3}] tps.

  15. Software tool for resolution of inverse problems using artificial intelligence techniques: an application in neutron spectrometry

    International Nuclear Information System (INIS)

    Castaneda M, V. H.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Leon P, A. A.; Hernandez P, C. F.; Espinoza G, J. G.; Ortiz R, J. M.; Vega C, H. R.; Mendez, R.; Gallego, E.; Sousa L, M. A.

    2016-10-01

    The Taguchi methodology has proved to be highly efficient to solve inverse problems, in which the values of some parameters of the model must be obtained from the observed data. There are intrinsic mathematical characteristics that make a problem known as inverse. Inverse problems appear in many branches of science, engineering and mathematics. To solve this type of problem, researches have used different techniques. Recently, the use of techniques based on Artificial Intelligence technology is being explored by researches. This paper presents the use of a software tool based on artificial neural networks of generalized regression in the solution of inverse problems with application in high energy physics, specifically in the solution of the problem of neutron spectrometry. To solve this problem we use a software tool developed in the Mat Lab programming environment, which employs a friendly user interface, intuitive and easy to use for the user. This computational tool solves the inverse problem involved in the reconstruction of the neutron spectrum based on measurements made with a Bonner spheres spectrometric system. Introducing this information, the neural network is able to reconstruct the neutron spectrum with high performance and generalization capability. The tool allows that the end user does not require great training or technical knowledge in development and/or use of software, so it facilitates the use of the program for the resolution of inverse problems that are in several areas of knowledge. The techniques of Artificial Intelligence present singular veracity to solve inverse problems, given the characteristics of artificial neural networks and their network topology, therefore, the tool developed has been very useful, since the results generated by the Artificial Neural Network require few time in comparison to other techniques and are correct results comparing them with the actual data of the experiment. (Author)

  16. Artificial intelligence-based speed control of DTC induction motor drives - A comparative study

    Energy Technology Data Exchange (ETDEWEB)

    Gadoue, S.M.; Giaouris, D.; Finch, J.W. [School of Electrical, Electronic and Computer Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU (United Kingdom)

    2009-01-15

    The design of the speed controller greatly affects the performance of an electric drive. A common strategy to control an induction machine is to use direct torque control combined with a PI speed controller. These schemes require proper and continuous tuning and therefore adaptive controllers are proposed to replace conventional PI controllers to improve the drive's performance. This paper presents a comparison between four different speed controller design strategies based on artificial intelligence techniques; two are based on tuning of conventional PI controllers, the third makes use of a fuzzy logic controller and the last is based on hybrid fuzzy sliding mode control theory. To provide a numerical comparison between different controllers, a performance index based on speed error is assigned. All methods are applied to the direct torque control scheme and each control strategy has been tested for its robustness and disturbance rejection ability. (author)

  17. Artificial intelligence for the modeling and control of combustion processes: a review

    Energy Technology Data Exchange (ETDEWEB)

    Soteris A. Kalogirou, [Higher Technical Institute, Nicosia (Cyprus). Department of Mechanical Engineering

    2003-07-01

    Artificial intelligence (AI) systems are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems, and once trained can perform prediction and generalization at high speed. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing, and social/psychological sciences. They are particularly useful in system modeling such as in implementing complex mappings and system identification. AI systems comprise areas like, expert systems, artificial neural networks, genetic algorithms, fuzzy logic and various hybrid systems, which combine two or more techniques. The major objective of this paper is to illustrate how AI techniques might play an important role in modeling and prediction of the performance and control of combustion process. The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in the different disciplines of combustion engineering. The various applications of AI are presented in a thematic rather than a chronological or any other order. Problems presented include two main areas: combustion systems and internal combustion (IC) engines. Combustion systems include boilers, furnaces and incinerators modeling and emissions prediction, whereas, IC engines include diesel and spark ignition engines and gas engines modeling and control. Results presented in this paper, are testimony to the potential of AI as a design tool in many areas of combustion engineering. 109 refs., 31 figs., 11 tabs.

  18. A Review and Performance Investigation of NPCC Based UPQC by Using Various Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Venkata Rami Reddy K

    2017-03-01

    Full Text Available This paper presents a comprehensive review and performance investigation of Neutral Point Clamped Converter (NPCC based Unified Power Quality Conditioner (UPQC by using Artificial Intelligent (AI techniques. A Novel application of various levels of Diode Clamped Multi-Level Inverters [DCMLI] with Anti Phase Opposition and Disposition (APOD Pulse Width Modulation (PWM Scheme to Unified Power Quality Conditioner (UPQC. The Power Quality problem became a burning issues since the starting of high voltage AC transmission system. Hence, in this article it has been discussed to mitigate the PQ issues in high voltage AC systems through a three phase four wire Unified Power Quality Conditioner (UPQC under non-linear loads. The emphasised PQ problems such as voltage and current harmonics along with voltage sags and swells have also been discussed with improved performance. Also, it proposes to control the DCMLI based UPQC through conventional control schemes. Thus application of these control technique makes the system performance in par with the standards and also compared with existing system. The simulation results based on MATLAB/Simulink are discussed in detail to support the concept developed in the paper.

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

    Science.gov (United States)

    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…

  20. Application and evaluation of the artificial tritium tagging of moisture soil technique in hydrogeological research in Brazil

    International Nuclear Information System (INIS)

    Castro Rubio Poli, D. de.

    1989-01-01

    In this work, we apply and make an evaluation of the technique of artificial tritium tagging of moisture in many kinds of soils for the determination of rainfall infiltration in unsaturated zone. The purpose of this work is the determination of ground water recharge in order to assist in evaluation of sites for the disposal of radioactive wastes and also to assist in the evaluation of water resources. With this thesis, we intend to present a new choice for the measuring of local ground water recharge rate, due to availability of artificial tritium. From the experimental results obtained, we can conclude that the use of artificial tritium tagging method is an accurate, useful and probably the best available technique to determine ground water recharge. (author)

  1. Artificial Intelligence for Controlling Robotic Aircraft

    Science.gov (United States)

    Krishnakumar, Kalmanje

    2005-01-01

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

  2. Sensory feedback in artificial control of human mobility

    NARCIS (Netherlands)

    Veltink, Petrus H.

    1999-01-01

    Artificial motor control systems may reduce the handicap of motor impaired individuals. Sensors are essential components in feedback control of these systems and in the information exchange with the user. The objective of this paper is to give an overview of the applications of sensors in the

  3. Development and Physical Control Research on Prototype Artificial Leg

    Directory of Open Access Journals (Sweden)

    Fei Li

    2016-03-01

    Full Text Available To provide an ideal platform for research on intelligent bionic leg (IBL, this paper proposes a model of a biped robot with heterogeneous legs (BRHL. A prototype of an artificial leg is developed based on biological structure and motion principle analysis of human lower extremities. With regard to the driving sources, servomotors are chosen for the hip joint and ankle joint, while pneumatic muscle actuators (PMAs are chosen for the knee joint. The control system of the bionic artificial leg is designed and a physical experimental platform is established. The physical control experiments are done based on proportional-integral-derivative (PID control strategy. The experimental results show that such a system can realize the expected goals.

  4. Artificial proprioceptive feedback for myoelectric control.

    Science.gov (United States)

    Pistohl, Tobias; Joshi, Deepak; Ganesh, Gowrishankar; Jackson, Andrew; Nazarpour, Kianoush

    2015-05-01

    The typical control of myoelectric interfaces, whether in laboratory settings or real-life prosthetic applications, largely relies on visual feedback because proprioceptive signals from the controlling muscles are either not available or very noisy. We conducted a set of experiments to test whether artificial proprioceptive feedback, delivered noninvasively to another limb, can improve control of a two-dimensional myoelectrically-controlled computer interface. In these experiments, participants were required to reach a target with a visual cursor that was controlled by electromyogram signals recorded from muscles of the left hand, while they were provided with an additional proprioceptive feedback on their right arm by moving it with a robotic manipulandum. Provision of additional artificial proprioceptive feedback improved the angular accuracy of their movements when compared to using visual feedback alone but did not increase the overall accuracy quantified with the average distance between the cursor and the target. The advantages conferred by proprioception were present only when the proprioceptive feedback had similar orientation to the visual feedback in the task space and not when it was mirrored, demonstrating the importance of congruency in feedback modalities for multi-sensory integration. Our results reveal the ability of the human motor system to learn new inter-limb sensory-motor associations; the motor system can utilize task-related sensory feedback, even when it is available on a limb distinct from the one being actuated. In addition, the proposed task structure provides a flexible test paradigm by which the effectiveness of various sensory feedback and multi-sensory integration for myoelectric prosthesis control can be evaluated.

  5. Artificial vision in nuclear fuel fabrication

    International Nuclear Information System (INIS)

    Dorado, P.

    2007-01-01

    The development of artificial vision techniques opens a door to the optimization of industrial processes which the nuclear industry cannot miss out on. Backing these techniques represents a revolution in security and reliability in the manufacturing of a highly technological products as in nuclear fuel. Enusa Industrias Avanzadas S. A. has successfully developed and implemented the first automatic inspection equipment for pellets by artificial vision in the European nuclear industry which is nowadays qualified and is already developing the second generation of this machine. There are many possible applications for the techniques of artificial vision in the fuel manufacturing processes. Among the practices developed by Enusa Industrias Avanzadas are, besides the pellets inspection, the rod sealing drills detection and positioning in the BWR products and the sealing drills inspection in the PWR fuel. The use of artificial vision in the arduous and precise processes of full inspection will allow the absence of human error, the increase of control in the mentioned procedures, the reduction of doses received by the personnel, a higher reliability of the whole of the operations and an improvement in manufacturing costs. (Author)

  6. Application of artificial intelligence in process control

    CERN Document Server

    Krijgsman, A

    1993-01-01

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

  7. An artificial pancreas for automated blood glucose control in patients with Type 1 diabetes

    DEFF Research Database (Denmark)

    Schmidt, Signe; Boiroux, Dimitri; Ranjan, Ajenthen

    2015-01-01

    Automated glucose control in patients with Type 1 diabetes is much-coveted by patients, relatives and healthcare professionals. It is the expectation that a system for automated control, also know as an artificial pancreas, will improve glucose control, reduce the risk of diabetes complications...... and markedly improve patient quality of life. An artificial pancreas consists of portable devices for glucose sensing and insulin delivery which are controlled by an algorithm residing on a computer. The technology is still under development and currently no artificial pancreas is commercially available....... This review gives an introduction to recent progress, challenges and future prospects within the field of artificial pancreas research....

  8. Application and evaluation of the artificial tritium tagging of moisture soil technique in hydrogeological research in Brazil

    International Nuclear Information System (INIS)

    Castro Rubio Poli, D. de; Kimmelmann e Silva, A.A.

    1990-08-01

    In this work, we apply and make an evaluation the artificial tritium tagging technique of moisture in many kinds of soils for the determination of rainfall infiltration in unsaturated zone. The purpose of this work is the determination of ground water recharge in order to assist evaluating sites for radioactive waste disposal and water resources. From the experimental results obtained, we can conclude that the use of artificial tritium tagging method is an accurate, useful and probably the best available technique to determine ground water recharge. (author) [pt

  9. Artificial Life as an Aid to Astrobiology: Testing Life Seeking Techniques

    OpenAIRE

    Centler, F.; Dittrich, P.; Ku, L.; Matsumaru, N.; Pfaffmann, J.; Zauner, K.-P.

    2003-01-01

    Searching for signatures of fossil or present life in our solar system requires autonomous devices capable of investigating remote locations with limited assistance from earth. Here, we use an artificial chemistry model to create spatially complex chemical environments. An autonomous experimentation technique based on evolutionary computation is then employed to explore these environments with the aim of discovering the chemical signature of small patches of biota present in the simulation sp...

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

    Science.gov (United States)

    Palaniappan, Rajkumar; Sundaraj, Kenneth; Sundaraj, Sebastian

    2014-02-01

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

  11. Artificial neural network techniques to improve the ability of optical coherence tomography to detect optic neuritis.

    Science.gov (United States)

    Garcia-Martin, Elena; Herrero, Raquel; Bambo, Maria P; Ara, Jose R; Martin, Jesus; Polo, Vicente; Larrosa, Jose M; Garcia-Feijoo, Julian; Pablo, Luis E

    2015-01-01

    To analyze the ability of Spectralis optical coherence tomography (OCT) to detect multiple sclerosis (MS) and to distinguish MS eyes with antecedent optic neuritis (ON). To analyze the capability of artificial neural network (ANN) techniques to improve the diagnostic precision. MS patients and controls were enrolled (n = 217). OCT was used to determine the 768 retinal nerve fiber layer thicknesses. Sensitivity and specificity were evaluated to test the ability of OCT to discriminate between MS and healthy eyes, and between MS with and without antecedent ON using ANN. Using ANN technique multilayer perceptrons, OCT could detect MS with a sensitivity of 89.3%, a specificity of 87.6%, and a diagnostic precision of 88.5%. Compared with the OCT-provided parameters, the ANN had a better sensitivity-specificity balance. ANN technique improves the capability of Spectralis OCT to detect MS disease and to distinguish MS eyes with or without antecedent ON.

  12. Univariate and multivariate forecasting of hourly solar radiation with artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Sfetsos, A. [7 Pirsou Str., Athens (Greece); Coonick, A.H. [Imperial Coll. of Science Technology and Medicine, Dept. of Electrical and Electronic Engineering, London (United Kingdom)

    2000-07-01

    This paper introduces a new approach for the forecasting of mean hourly global solar radiation received by a horizontal surface. In addition to the traditional linear methods, several artificial-intelligence-based techniques are studied. These include linear, feed-forward, recurrent Elman and Radial Basis neural networks alongside the adaptive neuro-fuzzy inference scheme. The problem is examined initially for the univariate case, and is extended to include additional meteorological parameters in the process of estimating the optimum model. The results indicate that the developed artificial intelligence models predict the solar radiation time series more effectively compared to the conventional procedures based on the clearness index. The forecasting ability of some models can be further enhanced with the use of additional meteorological parameters. (Author)

  13. Efficacy of Blood Sources and Artificial Blood Feeding Methods in Rearing of Aedes aegypti (Diptera: Culicidae) for Sterile Insect Technique and Incompatible Insect Technique Approaches in Sri Lanka

    OpenAIRE

    Nayana Gunathilaka; Tharaka Ranathunge; Lahiru Udayanga; Wimaladharma Abeyewickreme

    2017-01-01

    Introduction Selection of the artificial membrane feeding technique and blood meal source has been recognized as key considerations in mass rearing of vectors. Methodology Artificial membrane feeding techniques, namely, glass plate, metal plate, and Hemotek membrane feeding method, and three blood sources (human, cattle, and chicken) were evaluated based on feeding rates, fecundity, and hatching rates of Aedes aegypti. Significance in the variations among blood feeding was investigated by one...

  14. Artificial intelligence utilization in power generation units control systems; Utilizacao de inteligencia artificial em sistemas de controle de unidades geradoras

    Energy Technology Data Exchange (ETDEWEB)

    Souza, G N [CEPEL, Rio de Janeiro, RJ (Brazil); Mendes, S B [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    1992-12-31

    To the implementation of the logics of control in a hydroelectric power plant artificial languages or complexes formalisms are used which cause error introduction in the description process of such logic. This work suggests the use of an intelligent and interactive system with interface in natural language to the control description as a solution to this problem. 28 refs., 3 figs.

  15. Artificial intelligence utilization in power generation units control systems; Utilizacao de inteligencia artificial em sistemas de controle de unidades geradoras

    Energy Technology Data Exchange (ETDEWEB)

    Souza, G.N. [CEPEL, Rio de Janeiro, RJ (Brazil); Mendes, S.B. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    1991-12-31

    To the implementation of the logics of control in a hydroelectric power plant artificial languages or complexes formalisms are used which cause error introduction in the description process of such logic. This work suggests the use of an intelligent and interactive system with interface in natural language to the control description as a solution to this problem. 28 refs., 3 figs.

  16. Fuzzy Controller Design Using Evolutionary Techniques for Twin Rotor MIMO System: A Comparative Study

    Directory of Open Access Journals (Sweden)

    H. A. Hashim

    2015-01-01

    Full Text Available This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO system (TRMS considering most promising evolutionary techniques. These are gravitational search algorithm (GSA, particle swarm optimization (PSO, artificial bee colony (ABC, and differential evolution (DE. In this study, the gains of four fuzzy proportional derivative (PD controllers for TRMS have been optimized using the considered techniques. The optimization techniques are developed to identify the optimal control parameters for system stability enhancement, to cancel high nonlinearities in the model, to reduce the coupling effect, and to drive TRMS pitch and yaw angles into the desired tracking trajectory efficiently and accurately. The most effective technique in terms of system response due to different disturbances has been investigated. In this work, it is observed that GSA is the most effective technique in terms of solution quality and convergence speed.

  17. Electrically controllable artificial PAN muscles

    Science.gov (United States)

    Salehpoor, Karim; Shahinpoor, Mohsen; Mojarrad, Mehran

    1996-02-01

    PAN muscles become electrically controllable and therefore the use of such artificial muscles in robotic structures and applications becomes more feasible. A muscle is designed such that it is exposed to either Na+ or Cl- ions effectively. Muscle contraction or expansion characteristics under the effect of the applied electric field are discussed.

  18. Calibration Technique of the Irradiated Thermocouple using Artificial Neural Network

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Jin Tae; Joung, Chang Young; Ahn, Sung Ho; Yang, Tae Ho; Heo, Sung Ho; Jang, Seo Yoon [KAERI, Daejeon (Korea, Republic of)

    2016-05-15

    To correct the signals, the degradation rate of sensors needs to be analyzed, and re-calibration of sensors should be followed periodically. In particular, because thermocouples instrumented in the nuclear fuel rod are degraded owing to the high neutron fluence generated from the nuclear fuel, the periodic re-calibration process is necessary. However, despite the re-calibration of the thermocouple, the measurement error will be increased until next re-calibration. In this study, based on the periodically calibrated temperature - voltage data, an interpolation technique using the artificial neural network will be introduced to minimize the calibration error of the C-type thermocouple under the irradiation test. The test result shows that the calculated voltages derived from the interpolation function have good agreement with the experimental sampling data, and they also accurately interpolate the voltages at arbitrary temperature and neutron fluence. That is, once the reference data is obtained by experiments, it is possible to accurately calibrate the voltage signal at a certain neutron fluence and temperature using an artificial neural network.

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

    CERN Document Server

    Liu, Chen-Ching; Edris, Abdel-Aty

    2016-01-01

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

  20. Artificial Leg Design and Control Research of a Biped Robot with Heterogeneous Legs Based on PID Control Algorithm

    Directory of Open Access Journals (Sweden)

    Hualong Xie

    2015-04-01

    Full Text Available A biped robot with heterogeneous legs (BRHL is proposed to provide an ideal test-bed for intelligent bionic legs (IBL. To make artificial leg gait better suited to a human, a four-bar mechanism is used as its knee joint, and a pneumatic artificial muscle (PAM is used as its driving source. The static mathematical model of PAM is established and the mechanical model of a single degree of freedom of a knee joint driven by PAM is analyzed. A control simulation of an artificial leg based on PID control algorithm is carried out and the simulation results indicate that the artificial leg can simulate precisely a normal human walking gait.

  1. Correlation between crystallographic computing and artificial intelligence research

    Energy Technology Data Exchange (ETDEWEB)

    Feigenbaum, E A [Stanford Univ., CA; Engelmore, R S; Johnson, C K

    1977-01-01

    Artificial intelligence research, as a part of computer science, has produced a variety of programs of experimental and applications interest: programs for scientific inference, chemical synthesis, planning robot control, extraction of meaning from English sentences, speech understanding, interpretation of visual images, and so on. The symbolic manipulation techniques used in artificial intelligence provide a framework for analyzing and coding the knowledge base of a problem independently of an algorithmic implementation. A possible application of artificial intelligence methodology to protein crystallography is described. 2 figures, 2 tables.

  2. Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Ferreira, F.J.O. [Instituto de Engenharia Nuclear, Cidade Universitaria, Rio de Janeiro, CEP 21945-970, Caixa Postal 68550 (Brazil)], E-mail: fferreira@ien.gov.br; Crispim, V.R.; Silva, A.X. [DNC/Poli, PEN COPPE CT, UFRJ Universidade Federal do Rio de Janeiro, CEP 21941-972, Caixa Postal 68509, Rio de Janeiro (Brazil)

    2010-06-15

    In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials.

  3. Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques

    International Nuclear Information System (INIS)

    Ferreira, F.J.O.; Crispim, V.R.; Silva, A.X.

    2010-01-01

    In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials.

  4. Novel technique for airless connection of artificial heart to vascular conduits.

    Science.gov (United States)

    Karimov, Jamshid H; Gao, Shengqiang; Dessoffy, Raymond; Sunagawa, Gengo; Sinkewich, Martin; Grady, Patrick; Sale, Shiva; Moazami, Nader; Fukamachi, Kiyotaka

    2017-12-01

    Successful implantation of a total artificial heart relies on multiple standardized procedures, primarily the resection of the native heart, and exacting preparation of the atrial and vascular conduits for pump implant and activation. Achieving secure pump connections to inflow/outflow conduits is critical to a successful outcome. During the connection process, however, air may be introduced into the circulation, traveling to the brain and multiple organs. Such air emboli block blood flow to these areas and are detrimental to long-term survival. A correctly managed pump-to-conduit connection prevents air from collecting in the pump and conduits. To further optimize pump-connection techniques, we have developed a novel connecting sleeve that enables airless connection of the Cleveland Clinic continuous-flow total artificial heart (CFTAH) to the conduits. In this brief report, we describe the connecting sleeve design and our initial results from two acute in vivo implantations using a scaled-down version of the CFTAH.

  5. Estimation Methodology for the Electricity Consumption with the Daylight- and Occupancy-Controlled Artificial Lighting

    DEFF Research Database (Denmark)

    Larsen, Olena Kalyanova; Jensen, Rasmus Lund; Strømberg, Ida Kristine

    2017-01-01

    Artificial lighting represents 15-30% of the total electricity consumption in buildings in Scandinavia. It is possible to avoid a large share of electricity use for lighting by application of daylight control systems for artificial lighting. Existing methodology for estimation of electricity...... consumption with application of such control systems in Norway is based on Norwegian standard NS 3031:2014 and can only provide results from a rough estimate. This paper aims to introduce a new estimation methodology for the electricity usage with the daylight- and occupancy-controlled artificial lighting...

  6. Designing artificial 2D crystals with site and size controlled quantum dots.

    Science.gov (United States)

    Xie, Xuejun; Kang, Jiahao; Cao, Wei; Chu, Jae Hwan; Gong, Yongji; Ajayan, Pulickel M; Banerjee, Kaustav

    2017-08-30

    Ordered arrays of quantum dots in two-dimensional (2D) materials would make promising optical materials, but their assembly could prove challenging. Here we demonstrate a scalable, site and size controlled fabrication of quantum dots in monolayer molybdenum disulfide (MoS 2 ), and quantum dot arrays with nanometer-scale spatial density by focused electron beam irradiation induced local 2H to 1T phase change in MoS 2 . By designing the quantum dots in a 2D superlattice, we show that new energy bands form where the new band gap can be controlled by the size and pitch of the quantum dots in the superlattice. The band gap can be tuned from 1.81 eV to 1.42 eV without loss of its photoluminescence performance, which provides new directions for fabricating lasers with designed wavelengths. Our work constitutes a photoresist-free, top-down method to create large-area quantum dot arrays with nanometer-scale spatial density that allow the quantum dots to interfere with each other and create artificial crystals. This technique opens up new pathways for fabricating light emitting devices with 2D materials at desired wavelengths. This demonstration can also enable the assembly of large scale quantum information systems and open up new avenues for the design of artificial 2D materials.

  7. Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

    Science.gov (United States)

    Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M. L.; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

    2016-07-01

    The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project ;The Hand Embodied; (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies.

  8. Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

    Science.gov (United States)

    Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M.L.; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

    2017-01-01

    The term ‘synergy’ – from the Greek synergia – means ‘working together’. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project “The Hand Embodied” (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies. PMID:26923030

  9. Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands.

    Science.gov (United States)

    Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M L; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

    2016-07-01

    The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project "The Hand Embodied" (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Computer automation and artificial intelligence

    International Nuclear Information System (INIS)

    Hasnain, S.B.

    1992-01-01

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

  11. Research and applications: Artificial intelligence

    Science.gov (United States)

    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.

  12. Artificial intelligence-based computer modeling tools for controlling slag foaming in electric arc furnaces

    Science.gov (United States)

    Wilson, Eric Lee

    Due to increased competition in a world economy, steel companies are currently interested in developing techniques that will allow for the improvement of the steelmaking process, either by increasing output efficiency or by improving the quality of their product, or both. Slag foaming is one practice that has been shown to contribute to both these goals. However, slag foaming is highly dynamic and difficult to model or control. This dissertation describes an effort to use artificial intelligence-based tools (genetic algorithms, fuzzy logic, and neural networks) to both model and control the slag foaming process. Specifically, a neural network is trained and tested on slag foaming data provided by a steel plant. This neural network model is then controlled by a fuzzy logic controller, which in turn is optimized by a genetic algorithm. This tuned controller is then installed at a steel plant and given control be a more efficient slag foaming controller than what was previously used by the steel plant.

  13. Using Weightless Neural Networks for Vergence Control in an Artificial Vision System

    Directory of Open Access Journals (Sweden)

    Karin S. Komati

    2003-01-01

    Full Text Available This paper presents a methodology we have developed and used to implement an artificial binocular vision system capable of emulating the vergence of eye movements. This methodology involves using weightless neural networks (WNNs as building blocks of artificial vision systems. Using the proposed methodology, we have designed several architectures of WNN-based artificial vision systems, in which images captured by virtual cameras are used for controlling the position of the ‘foveae’ of these cameras (high-resolution region of the images captured. Our best architecture is able to control the foveae vergence movements with average error of only 3.58 image pixels, which is equivalent to an angular error of approximately 0.629°.

  14. Mechanisms controlling the artificial aging of Al-Mg-Si Alloys

    International Nuclear Information System (INIS)

    Pogatscher, S.; Antrekowitsch, H.; Leitner, H.; Ebner, T.; Uggowitzer, P.J.

    2011-01-01

    Highlights: → Artificial aging of Al-Mg-Si alloys in the range of 150 and 250 deg. C. → We study precipitation kinetics caused by various thermal histories. → Natural pre-aging affects kinetics at low artificial aging temperatures. → Natural pre-aging promotes kinetics at high artificial aging temperatures. → A vacancy-prison mechanism explains the effect of natural pre-aging. - Abstract: In this study the artificial aging behavior of the Al-Mg-Si alloy AA 6061 was investigated in the temperature range 150-250 deg. C using atom probe tomography, hardness and resistivity measurements for various thermal histories. It was found that the precipitation kinetics and age-hardening response of artificial aging at temperatures below 210 deg. C are lowered by prior natural aging but enhanced above this temperature. An analysis of hardness data was used to evaluate the temperature dependence of precipitation kinetics and dissolution processes. Supported by theoretical considerations, it is assumed that artificial aging of Al-Mg-Si alloys is controlled via the concentration of mobile vacancies. The 'vacancy-prison mechanism' proposed determines the mobile vacancy concentration in the case of natural pre-aging by temperature-dependent dissolution of co-clusters and solute-vacancy interactions.

  15. Design and performance of heart assist or artificial heart control systems

    Science.gov (United States)

    Webb, J. A., Jr.; Gebben, V. D.

    1978-01-01

    The factors leading to the design of a controlled driving system for either a heart assist pump or artificial heart are discussed. The system provides square pressure waveform to drive a pneumatic-type blood pump. For assist usage the system uses an R-wave detector circuit that can detect the R-wave of the electrocardiogram in the presence of electrical disturbances. This circuit provides a signal useful for synchronizing an assist pump with the natural heart. It synchronizes a square wave circuit, the output of which is converted into square waveforms of pneumatic pressure suitable for driving both assist device and artificial heart. The pressure levels of the driving waveforms are controlled by means of feedback channels to maintain physiological regulation of the artificial heart's output flow. A more compact system that could achieve similar regulatory characteristics is also discussed.

  16. Artificial neural networks in variable process control: application in particleboard manufacture

    Energy Technology Data Exchange (ETDEWEB)

    Esteban, L. G.; Garcia Fernandez, F.; Palacios, P. de; Conde, M.

    2009-07-01

    Artificial neural networks are an efficient tool for modelling production control processes using data from the actual production as well as simulated or design of experiments data. In this study two artificial neural networks were combined with the control process charts and it was checked whether the data obtained by the networks were valid for variable process control in particleboard manufacture. The networks made it possible to obtain the mean and standard deviation of the internal bond strength of the particleboard within acceptable margins using known data of thickness, density, moisture content, swelling and absorption. The networks obtained met the acceptance criteria for test values from non-standard test methods, as well as the criteria for using these values in statistical process control. (Author) 47 refs.

  17. Electromyogram synergy control of a dexterous artificial hand to unscrew and screw objects.

    Science.gov (United States)

    Kent, Benjamin A; Karnati, Nareen; Engeberg, Erik D

    2014-03-21

    Due to their limited dexterity, it is currently not possible to use a commercially available prosthetic hand to unscrew or screw objects without using elbow and shoulder movements. For these tasks, prosthetic hands function like a wrench, which is unnatural and limits their use in tight working environments. Results from timed rotational tasks with human subjects demonstrate the clinical need for increased dexterity of prosthetic hands, and a clinically viable solution to this problem is presented for an anthropomorphic artificial hand. Initially, a human hand motion analysis was performed during a rotational task. From these data, human hand synergies were derived and mapped to an anthropomorphic artificial hand. The synergy for the artificial hand is controlled using conventional dual site electromyogram (EMG) signals. These EMG signals were mapped to the developed synergy to control four joints of the dexterous artificial hand simultaneously.Five limb absent and ten able-bodied test subjects participated in a comparison study to complete a timed rotational task as quickly as possible with their natural hands (except for one subject with a bilateral hand absence), eight commercially available prosthetic hands, and the proposed synergy controller. Each test subject used two to four different artificial hands. With the able-bodied subjects, the developed synergy controller reduced task completion time by 177% on average. The limb absent subjects completed the task faster on average than with their own prostheses by 46%. There was a statistically significant improvement in task completion time with the synergy controller for three of the four limb absent participants with integrated prostheses, and was not statistically different for the fourth. The proposed synergy controller reduced average task completion time compared to commercially available prostheses. Additionally, the synergy controller is able to function in a small workspace and requires less physical

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

    Science.gov (United States)

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

    2017-01-01

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

  19. ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    An artificial neural network(ANN) and a self-adjusting fuzzy logic controller(FLC) for modeling and control of gas tungsten arc welding(GTAW) process are presented. The discussion is mainly focused on the modeling and control of the weld pool depth with ANN and the intelligent control for weld seam tracking with FLC. The proposed neural network can produce highly complex nonlinear multi-variable model of the GTAW process that offers the accurate prediction of welding penetration depth. A self-adjusting fuzzy controller used for seam tracking adjusts the control parameters on-line automatically according to the tracking errors so that the torch position can be controlled accurately.

  20. Vibroacoustic Modeling of Mechanically Coupled Structures: Artificial Spring Technique Applied to Light and Heavy Mediums

    Directory of Open Access Journals (Sweden)

    L. Cheng

    1996-01-01

    Full Text Available This article deals with the modeling of vibrating structures immersed in both light and heavy fluids, and possible applications to noise control problems and industrial vessels containing fluids. A theoretical approach, using artificial spring systems to characterize the mechanical coupling between substructures, is extended to include fluid loading. A structure consisting of a plate-ended cylindrical shell and its enclosed acoustic cavity is analyzed. After a brief description of the proposed technique, a number of numerical results are presented. The analysis addresses the following specific issues: the coupling between the plate and the shell; the coupling between the structure and the enclosure; the possibilities and difficulties regarding internal soundproofing through modifications of the joint connections; and the effects of fluid loading on the vibration of the structure.

  1. Control Systems for Hyper-Redundant Robots Based on Artificial Potential Method

    Directory of Open Access Journals (Sweden)

    Mihaela Florescu

    2015-06-01

    Full Text Available This paper presents the control method of hyper-redundant robots based on the artificial potential approach. The principles of this method are shown and a suggestive example is offered. Then, the artificial potential method is applied to the case of a tentacle robot starting from the dynamic model of the robot. In addition, a series of results that are obtained through simulation is presented.

  2. Position control of a single pneumatic artificial muscle with hysteresis compensation based on modified Prandtl-Ishlinskii model.

    Science.gov (United States)

    Zang, Xizhe; Liu, Yixiang; Heng, Shuai; Lin, Zhenkun; Zhao, Jie

    2017-01-01

    High-performance position control of pneumatic artificial muscles is limited by their inherent nonlinearity and hysteresis. This study aims to model the length/pressure hysteresis of a single pneumatic artificial muscle and to realize its accurate position tracking control with forward hysteresis compensation. The classical Prandtl-Ishlinskii model is widely used in hysteresis modelling and compensation. But it is only effective for symmetric hysteresis. Therefore, a modified Prandtl-Ishlinskii model is built to characterize the asymmetric length/pressure hysteresis of a single pneumatic artificial muscle, by replacing the classical play operators with two more flexible elementary operators to independently describe the ascending branch and descending branch of hysteresis loops. On the basis, a position tracking controller, which is composed of cascade forward hysteresis compensation and simple proportional pressure controller, is designed for the pneumatic artificial muscle. Experiment results show that the MPI model can reproduce the length/pressure hysteresis of the pneumatic artificial muscle, and the proposed controller for the pneumatic artificial muscle can track the reference position signals with high accuracy. By modelling the length/pressure hysteresis with the modified Prandtl-Ishlinskii model and using its inversion for compensation, precise position control of a single pneumatic artificial muscle is achieved.

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

    Science.gov (United States)

    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...

  4. Artificial intelligence implementation in the APS process diagnostic

    Energy Technology Data Exchange (ETDEWEB)

    Guessasma, Sofiane; Salhi, Zahir; Montavon, Ghislain; Gougeon, Patrick; Coddet, Christian

    2004-07-25

    Thermal spray process is a technique of coating manufacturing implementing a wide variety of materials and processes. This technique is characterized by up to 150 processing parameters influencing the coating properties. The control of the coating quality is needed through the consideration of a robust methodology that takes into account the parameter interdependencies, the process variability and offers the ability to quantify the processing parameter-process response relationships. The aim of this work is to introduce a new approach based on artificial intelligence responding to these requirements. A detailed procedure is presented considering an artificial neural network (ANN) structure which encodes implicitly the physical phenomena governing the process. The implementation of such a structure was coupled to experimental results of an optic sensor controlling the powder particle fusion state before the coating formation. The optimization steps were discussed and the predicted results were compared to the experimental ones allowing the identification of the control factors.

  5. Artificial intelligence implementation in the APS process diagnostic

    International Nuclear Information System (INIS)

    Guessasma, Sofiane; Salhi, Zahir; Montavon, Ghislain; Gougeon, Patrick; Coddet, Christian

    2004-01-01

    Thermal spray process is a technique of coating manufacturing implementing a wide variety of materials and processes. This technique is characterized by up to 150 processing parameters influencing the coating properties. The control of the coating quality is needed through the consideration of a robust methodology that takes into account the parameter interdependencies, the process variability and offers the ability to quantify the processing parameter-process response relationships. The aim of this work is to introduce a new approach based on artificial intelligence responding to these requirements. A detailed procedure is presented considering an artificial neural network (ANN) structure which encodes implicitly the physical phenomena governing the process. The implementation of such a structure was coupled to experimental results of an optic sensor controlling the powder particle fusion state before the coating formation. The optimization steps were discussed and the predicted results were compared to the experimental ones allowing the identification of the control factors

  6. Use of artificial intelligence in nuclear power plants

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1990-01-01

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

  7. The artificial-free technique along the objective direction for the simplex algorithm

    International Nuclear Information System (INIS)

    Boonperm, Aua-aree; Sinapiromsaran, Krung

    2014-01-01

    The simplex algorithm is a popular algorithm for solving linear programming problems. If the origin point satisfies all constraints then the simplex can be started. Otherwise, artificial variables will be introduced to start the simplex algorithm. If we can start the simplex algorithm without using artificial variables then the simplex iterate will require less time. In this paper, we present the artificial-free technique for the simplex algorithm by mapping the problem into the objective plane and splitting constraints into three groups. In the objective plane, one of variables which has a nonzero coefficient of the objective function is fixed in terms of another variable. Then it can split constraints into three groups: the positive coefficient group, the negative coefficient group and the zero coefficient group. Along the objective direction, some constraints from the positive coefficient group will form the optimal solution. If the positive coefficient group is nonempty, the algorithm starts with relaxing constraints from the negative coefficient group and the zero coefficient group. We guarantee the feasible region obtained from the positive coefficient group to be nonempty. The transformed problem is solved using the simplex algorithm. Additional constraints from the negative coefficient group and the zero coefficient group will be added to the solved problem and use the dual simplex method to determine the new optimal solution. An example shows the effectiveness of our algorithm

  8. The artificial-free technique along the objective direction for the simplex algorithm

    Science.gov (United States)

    Boonperm, Aua-aree; Sinapiromsaran, Krung

    2014-03-01

    The simplex algorithm is a popular algorithm for solving linear programming problems. If the origin point satisfies all constraints then the simplex can be started. Otherwise, artificial variables will be introduced to start the simplex algorithm. If we can start the simplex algorithm without using artificial variables then the simplex iterate will require less time. In this paper, we present the artificial-free technique for the simplex algorithm by mapping the problem into the objective plane and splitting constraints into three groups. In the objective plane, one of variables which has a nonzero coefficient of the objective function is fixed in terms of another variable. Then it can split constraints into three groups: the positive coefficient group, the negative coefficient group and the zero coefficient group. Along the objective direction, some constraints from the positive coefficient group will form the optimal solution. If the positive coefficient group is nonempty, the algorithm starts with relaxing constraints from the negative coefficient group and the zero coefficient group. We guarantee the feasible region obtained from the positive coefficient group to be nonempty. The transformed problem is solved using the simplex algorithm. Additional constraints from the negative coefficient group and the zero coefficient group will be added to the solved problem and use the dual simplex method to determine the new optimal solution. An example shows the effectiveness of our algorithm.

  9. Modeling of the height control system using artificial neural networks

    Directory of Open Access Journals (Sweden)

    A. R Tahavvor

    2016-09-01

    action. The mechanical parts were computer-generated by engineering software in assembled, exploded and standard two-dimensional drawing required for the manufacturing process. Carrier and framework of control unit and actuator mainly designed to have the capability to support and hold the hardware and sensor assembly in an easy mountable fashion. This arrangement performed feasibility of the movement and allocating of control unit along the travel length of belt above the conveyor unit. In this work a multilayer perceptron network with different training algorithm was used and it is found that the backpropagation algorithm with Levenberge-Marquardt learning rule was the best choice for this analysis because of the accurate and faster training procedure. The Levenberg-Marquardt algorithm was an iterative technique that locates the minimum of a multivariate function that was expressed as the sum of squares of nonlinear real-valued functions. It has become a standard technique for non-linear least-squares problems, widely adopted in a broad spectrum of disciplines. LM can be thought of as a combination of steepest descent and the Gauss-Newton method. When the current solution was far from the correct one, the algorithm behaves like a steepest descent method: slow, but guaranteed to converge. When the current solution is close to the correct solution, it becomes a Gauss-Newton method. The Levenberg algorithm is: 1. Do an update as directed by the rule above. 2. Evaluate the error at the new parameter vector. 3. If the error has increased as a result the update, then retract the step (i.e. reset the weights to their previous values and increase l by a factor of 10 or some such significant factor, then goes to (1 and try an update again. 4. If the error has decreased as a result of the update, then accept the step (i.e. keep the weights at their new values and decrease l by a factor of 10 or so. Results and Discussion The study of multi artificial neural network learning

  10. Artificial Intelligence in Space Platforms.

    Science.gov (United States)

    1984-12-01

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

  11. Artificial Intelligence and Economic Theories

    OpenAIRE

    Marwala, Tshilidzi; Hurwitz, Evan

    2017-01-01

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

  12. Vibration control of an artificial muscle manipulator with a magnetorheological fluid brake

    Science.gov (United States)

    Tomori, H.; Midorikawa, Y.; Nakamura, T.

    2013-02-01

    Recently, proposed applications of robots require them to contact human safely. Therefore, we focus on pneumatic rubber artificial muscle. This actuator is flexible, light, and has high-power density. However, because the artificial muscle is flexible, it vibrates when there is a high load. Therefore, we paid attention to the magnetorheological (MR) fluid. We propose a control method of the MR brake considering energy of the manipulator system. By this control method, MR brake dissipates energy leading to vibration of the manipulator. In this paper, we calculated the energy and controlled the MR brake. And, we deliberated the proposal method by simulation using the dynamic model of the manipulator, and experiment.

  13. Median Sternotomy or Right Thoracotomy Techniques for Total Artificial Heart Implantation in Calves.

    Science.gov (United States)

    Karimov, Jamshid H; Moazami, Nader; Sunagawa, Gengo; Kobayashi, Mariko; Byram, Nicole; Sale, Shiva; Such, Kimberly A; Horvath, David J; Golding, Leonard A R; Fukamachi, Kiyotaka

    2016-10-01

    The choice of optimal operative access technique for mechanical circulatory support device implantation ensures successful postoperative outcomes. In this study, we retrospectively evaluated the median sternotomy and lateral thoracotomy incisions for placement of the Cleveland Clinic continuous-flow total artificial heart (CFTAH) in a bovine model. The CFTAH was implanted in 17 calves (Jersey calves; weight range, 77.0-93.9 kg) through a median sternotomy (n = 9) or right thoracotomy (n = 8) for elective chronic implantation periods of 14, 30, or 90 days. Similar preoperative preparation, surgical techniques, and postoperative care were employed. Implantation of the CFTAH was successfully performed in all cases. Both methods provided excellent surgical field visualization. After device connection, however, the median sternotomy approach provided better visualization of the anastomoses and surgical lines for hemostasis confirmation and repair due to easier device displacement, which is severely limited following right thoracotomy. All four animals sacrificed after completion of the planned durations (up to 90 days) were operated through full median sternotomy. Our data demonstrate that both approaches provide excellent initial field visualization. Full median sternotomy provides larger viewing angles at the anastomotic suture line after device connection to inflow and outflow ports. Copyright © 2015 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  14. Simulation and prediction for energy dissipaters and stilling basins design using artificial intelligence technique

    Directory of Open Access Journals (Sweden)

    Mostafa Ahmed Moawad Abdeen

    2015-12-01

    Full Text Available Water with large velocities can cause considerable damage to channels whose beds are composed of natural earth materials. Several stilling basins and energy dissipating devices have been designed in conjunction with spillways and outlet works to avoid damages in canals’ structures. In addition, lots of experimental and traditional mathematical numerical works have been performed to profoundly investigate the accurate design of these stilling basins and energy dissipaters. The current study is aimed toward introducing the artificial intelligence technique as new modeling tool in the prediction of the accurate design of stilling basins. Specifically, artificial neural networks (ANNs are utilized in the current study in conjunction with experimental data to predict the length of the hydraulic jumps occurred in spillways and consequently the stilling basin dimensions can be designed for adequate energy dissipation. The current study showed, in a detailed fashion, the development process of different ANN models to accurately predict the hydraulic jump lengths acquired from different experimental studies. The results obtained from implementing these models showed that ANN technique was very successful in simulating the hydraulic jump characteristics occurred in stilling basins. Therefore, it can be safely utilized in the design of these basins as ANN involves minimum computational and financial efforts and requirements compared with experimental work and traditional numerical techniques such as finite difference or finite elements.

  15. Efficacy of Blood Sources and Artificial Blood Feeding Methods in Rearing of Aedes aegypti (Diptera: Culicidae for Sterile Insect Technique and Incompatible Insect Technique Approaches in Sri Lanka

    Directory of Open Access Journals (Sweden)

    Nayana Gunathilaka

    2017-01-01

    Full Text Available Introduction. Selection of the artificial membrane feeding technique and blood meal source has been recognized as key considerations in mass rearing of vectors. Methodology. Artificial membrane feeding techniques, namely, glass plate, metal plate, and Hemotek membrane feeding method, and three blood sources (human, cattle, and chicken were evaluated based on feeding rates, fecundity, and hatching rates of Aedes aegypti. Significance in the variations among blood feeding was investigated by one-way ANOVA, cluster analysis of variance (ANOSIM, and principal coordinates (PCO analysis. Results. Feeding rates of Ae. aegypti significantly differed among the membrane feeding techniques as suggested by one-way ANOVA (p0.05. Conclusions. Metal plate method could be recommended as the most effective membrane feeding technique for mass rearing of Ae. aegypti, due to its high feeding rate and cost effectiveness. Cattle blood could be recommended for mass rearing Ae. aegypti.

  16. An example of the use of the DELPHI method: future prospects of artificial heart techniques in France

    International Nuclear Information System (INIS)

    Derian, Jean-Claude; Morize, Francoise; Vernejoul, Pierre de; Vial, Renee

    1971-01-01

    The artificial heart is still only a research project surrounded by numerous uncertainties which make it very difficult to estimate, at the moment, the possibilities for future development of this technique in France. A systematic analysis of the hazards which characterize this project has been undertaken in the following report: restricting these uncertainties has required a taking into account of opinions of specialists concerned with type of research or its upshot. We have achieved this by adapting an investigation technique which is still unusual in France, the DELPHI method. This adaptation has allowed the confrontation and statistical aggregation of the opinions given by a body of a hundred experts who were consulted through a program of sequential interrogations which studied in particular, the probable date of the research issue, the clinical cases which require the use of an artificial heart, as well as the probable future needs. After having taken into account the economic constraints, we can deduce from these results the probable amount of plutonium 238 needed in the hypothesis where isotopic generator would be retained for the energetics feeding of the artificial heart [fr

  17. The use of artificial intelligence techniques to improve the multiple payload integration process

    Science.gov (United States)

    Cutts, Dannie E.; Widgren, Brian K.

    1992-01-01

    A maximum return of science and products with a minimum expenditure of time and resources is a major goal of mission payload integration. A critical component then, in successful mission payload integration is the acquisition and analysis of experiment requirements from the principal investigator and payload element developer teams. One effort to use artificial intelligence techniques to improve the acquisition and analysis of experiment requirements within the payload integration process is described.

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

    International Nuclear Information System (INIS)

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

    1996-01-01

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

  19. IDENTIFICATION OF MARKS ON TIRES USING ARTIFICIAL VISION FOR QUALITY CONTROL

    Directory of Open Access Journals (Sweden)

    André P. Dias

    2015-03-01

    Full Text Available Tire inspection is presently done by workers who have as their main problems, besides identifying the defects, the time available for defect identification and the inherent costs. Companies can become more sustainable by adopting automated methods to perform such type of processes, such as artificial vision, with advantages both in the processing time and in the incurred costs. This paper addresses the development of an artificial vision system that aims to be an asset in the field of tyre inspection, having as main characteristics its execution speed and its reliability. The conjugation of these criteria is a prerequisite for this system to be able to be integrated in inspection machines. The paper focusses on the study of three image processing methods to be used in the identification of marks (red dots on tires. In this work was used the free Open Computer Vision artificial vision library to process the images acquired by a Basler matrix camera. Two different techniques, namely Background Subtraction and Hough Transform, were tested to implement the solution. After developing the artificial vision inspection application, tests were made to measure the performance of both methods and the results were promising: processing time was low and, simultaneous, the achieved accuracy is high.

  20. Mosquito Control Techniques Developed for the US Military

    Science.gov (United States)

    The USDA developed and field tested new techniques to reduce the risk to deployed military troops from vector-borne diseases. Some of the methods developed included (1) novel military personal protection methods, (2) barrier treatments of artificial materials and natural vegetation, and (3) ground a...

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

    Science.gov (United States)

    1983-06-06

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

  2. The artificial satellite observation chronograph controlled by single chip microcomputer.

    Science.gov (United States)

    Pan, Guangrong; Tan, Jufan; Ding, Yuanjun

    1991-06-01

    The instrument specifications, hardware structure, software design, and other characteristics of the chronograph mounting on a theodolite used for artificial satellite observation are presented. The instrument is a real time control system with a single chip microcomputer.

  3. Analysis and control of a parallel lower limb based on pneumatic artificial muscles

    Directory of Open Access Journals (Sweden)

    Feilong Jiang

    2016-12-01

    Full Text Available Most robots that are actuated by antagonistic pneumatic artificial muscles are controlled by various control algorithms that cannot adequately imitate the actual muscle distribution of human limbs. Other robots in which the distribution of pneumatic artificial muscle is similar to that of human limbs can only analyze the position of the robot using perceptual data instead of rational knowledge. In order to better imitate the movement of a human limb, the article proposes a humanoid lower limb in the form of a parallel mechanism where muscle is unevenly distributed. Next, the kinematic and dynamic movements of bionic hip joint are analyzed, where the joint movement is controlled by an observer-based fuzzy adaptive control algorithm as a whole rather than each individual pneumatic artificial muscle and parameters that are optimized by a neural network. Finally, experimental results are provided to confirm the effectiveness of the proposed method. We also document the role of muscle in trajectory tracking for the piriformis and musculi obturator internus in isobaric processes.

  4. A scenario for a genetically controlled fission of artificial vesicles

    DEFF Research Database (Denmark)

    Bönzli, Eva; Hadorn, Maik; Jørgensen, Mikkel Girke

    2011-01-01

    to vesicles (Hanczyc et al. 2003). In the present work, we developed a scenario how a genetically controlled fission of vesicles may be achieved by the synthesis of a special class of viral proteins within artificial vesicles. Because the authors already have a lot of experience in the water-in-oil emulsion...... be incorporated into vesicles, and therefore allow the synthesis of a large number of proteins (Noireaux et al. 2005). However, vesicle fission remains one of the upcoming challenges in the artificial cell project (Noireaux et al. 2011). So far, vesicle fission is implemented by applying mechanical stress...

  5. Real-lime logical game with artificial intelligence using planning techniques

    OpenAIRE

    Pilař, Pavel

    2013-01-01

    The goal of this work was to design and implement a logical game with artificial inteligence. In the game the player is trying to hold an opponent driven by artificial inteligence inside a given level for a given time by using various instruments. The artificial inteligence is implemented using planning. The work describes game principles, game design and subsequent implementation, including analysis of the chosen and alternative implementation options.

  6. Software tool for resolution of inverse problems using artificial intelligence techniques: an application in neutron spectrometry; Herramienta en software para resolucion de problemas inversos mediante tecnicas de inteligencia artificial: una aplicacion en espectrometria neutronica

    Energy Technology Data Exchange (ETDEWEB)

    Castaneda M, V. H.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Leon P, A. A.; Hernandez P, C. F.; Espinoza G, J. G.; Ortiz R, J. M.; Vega C, H. R. [Universidad Autonoma de Zacatecas, 98000 Zacatecas, Zac. (Mexico); Mendez, R. [CIEMAT, Departamento de Metrologia de Radiaciones Ionizantes, Laboratorio de Patrones Neutronicos, Av. Complutense 22, 28040 Madrid (Spain); Gallego, E. [Universidad Politecnica de Madrid, Departamento de Ingenieria Nuclear, C. Jose Gutierrez Abascal 2, 28006 Madrid (Spain); Sousa L, M. A. [Comision Nacional de Energia Nuclear, Centro de Investigacion de Tecnologia Nuclear, Av. Pte. Antonio Carlos 6627, Pampulha, 31270-901 Belo Horizonte, Minas Gerais (Brazil)

    2016-10-15

    The Taguchi methodology has proved to be highly efficient to solve inverse problems, in which the values of some parameters of the model must be obtained from the observed data. There are intrinsic mathematical characteristics that make a problem known as inverse. Inverse problems appear in many branches of science, engineering and mathematics. To solve this type of problem, researches have used different techniques. Recently, the use of techniques based on Artificial Intelligence technology is being explored by researches. This paper presents the use of a software tool based on artificial neural networks of generalized regression in the solution of inverse problems with application in high energy physics, specifically in the solution of the problem of neutron spectrometry. To solve this problem we use a software tool developed in the Mat Lab programming environment, which employs a friendly user interface, intuitive and easy to use for the user. This computational tool solves the inverse problem involved in the reconstruction of the neutron spectrum based on measurements made with a Bonner spheres spectrometric system. Introducing this information, the neural network is able to reconstruct the neutron spectrum with high performance and generalization capability. The tool allows that the end user does not require great training or technical knowledge in development and/or use of software, so it facilitates the use of the program for the resolution of inverse problems that are in several areas of knowledge. The techniques of Artificial Intelligence present singular veracity to solve inverse problems, given the characteristics of artificial neural networks and their network topology, therefore, the tool developed has been very useful, since the results generated by the Artificial Neural Network require few time in comparison to other techniques and are correct results comparing them with the actual data of the experiment. (Author)

  7. Crack identification based on synthetic artificial intelligent technique

    International Nuclear Information System (INIS)

    Shim, Mun Bo; Suh, Myung Won

    2001-01-01

    It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a Continuous Evolutionary Algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising

  8. Macrocell path loss prediction using artificial intelligence techniques

    Science.gov (United States)

    Usman, Abraham U.; Okereke, Okpo U.; Omizegba, Elijah E.

    2014-04-01

    The prediction of propagation loss is a practical non-linear function approximation problem which linear regression or auto-regression models are limited in their ability to handle. However, some computational Intelligence techniques such as artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFISs) have been shown to have great ability to handle non-linear function approximation and prediction problems. In this study, the multiple layer perceptron neural network (MLP-NN), radial basis function neural network (RBF-NN) and an ANFIS network were trained using actual signal strength measurement taken at certain suburban areas of Bauchi metropolis, Nigeria. The trained networks were then used to predict propagation losses at the stated areas under differing conditions. The predictions were compared with the prediction accuracy of the popular Hata model. It was observed that ANFIS model gave a better fit in all cases having higher R2 values in each case and on average is more robust than MLP and RBF models as it generalises better to a different data.

  9. Future applications of artificial intelligence to Mission Control Centers

    Science.gov (United States)

    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.

  10. Control of a Heavy-Lift Robotic Manipulator with Pneumatic Artificial Muscles

    Directory of Open Access Journals (Sweden)

    Ryan M. Robinson

    2014-04-01

    Full Text Available Lightweight, compliant actuators are particularly desirable in robotic systems intended for interaction with humans. Pneumatic artificial muscles (PAMs exhibit these characteristics and are capable of higher specific work than comparably-sized hydraulic actuators and electric motors. The objective of this work is to develop a control algorithm that can smoothly and accurately track the desired motions of a manipulator actuated by pneumatic artificial muscles. The manipulator is intended for lifting humans in nursing assistance or casualty extraction scenarios; hence, the control strategy must be capable of responding to large variations in payload over a large range of motion. The present work first investigates the feasibility of two output feedback controllers (proportional-integral-derivative and fuzzy logic, but due to the limitations of pure output feedback control, a model-based feedforward controller is developed and combined with output feedback to achieve improved closed-loop performance. The model upon which the controller is based incorporates the internal airflow dynamics, the physical parameters of the pneumatic muscles and the manipulator dynamics. Simulations were performed in order to validate the control algorithms, guide controller design and predict optimal gains. Using real-time interface software and hardware, the controllers were implemented and experimentally tested on the manipulator, demonstrating the improved capability.

  11. Photoluminescence characteristics of InAs quantum dots grown by STM/MBE site-control technique

    Energy Technology Data Exchange (ETDEWEB)

    Nishikawa, S.; Kohmoto, S.; Nakamura, H.; Ishikawa, T.; Asakawa, K.; Wada, O. [Femtosecond Technology Research Association, Tsukuba, Ibaraki (Japan). FESTA Lab.

    2001-03-08

    This paper describes micro-photoluminescence (PL) analysis of site-controlled QDs (SCQDs) grown using a novel in-situ MBE growth technique in which sites of self-assembled InAs QDs are controlled by forming nanometer deposits using a scanning tunneling microscope (STM) probe. We found from the temperature dependence of PL that the carrier collection at QDs at low temperature is limited by carrier diffusion in the wetting layer. The analysis of PL data considering this effect has indicated that individual QDs grown have high crystalline quality in spite of the addition of an artificial STM process during growth. (orig.)

  12. Measuring strategic control in artificial grammar learning.

    Science.gov (United States)

    Norman, Elisabeth; Price, Mark C; Jones, Emma

    2011-12-01

    In response to concerns with existing procedures for measuring strategic control over implicit knowledge in artificial grammar learning (AGL), we introduce a more stringent measurement procedure. After two separate training blocks which each consisted of letter strings derived from a different grammar, participants either judged the grammaticality of novel letter strings with respect to only one of these two grammars (pure-block condition), or had the target grammar varying randomly from trial to trial (novel mixed-block condition) which required a higher degree of conscious flexible control. Random variation in the colour and font of letters was introduced to disguise the nature of the rule and reduce explicit learning. Strategic control was observed both in the pure-block and mixed-block conditions, and even among participants who did not realise the rule was based on letter identity. This indicated detailed strategic control in the absence of explicit learning. Copyright © 2011 Elsevier Inc. All rights reserved.

  13. Efficacy of Blood Sources and Artificial Blood Feeding Methods in Rearing of Aedes aegypti (Diptera: Culicidae) for Sterile Insect Technique and Incompatible Insect Technique Approaches in Sri Lanka.

    Science.gov (United States)

    Gunathilaka, Nayana; Ranathunge, Tharaka; Udayanga, Lahiru; Abeyewickreme, Wimaladharma

    2017-01-01

    Selection of the artificial membrane feeding technique and blood meal source has been recognized as key considerations in mass rearing of vectors. Artificial membrane feeding techniques, namely, glass plate, metal plate, and Hemotek membrane feeding method, and three blood sources (human, cattle, and chicken) were evaluated based on feeding rates, fecundity, and hatching rates of Aedes aegypti . Significance in the variations among blood feeding was investigated by one-way ANOVA, cluster analysis of variance (ANOSIM), and principal coordinates (PCO) analysis. Feeding rates of Ae. aegypti significantly differed among the membrane feeding techniques as suggested by one-way ANOVA ( p feeding technique. Blood feeding rate of Ae. aegypti was higher with human blood followed by cattle and chicken blood, respectively. However, no significant difference was observed from the mosquitoes fed with cattle and human blood, in terms of fecundity, oviposition rate, and fertility as suggested by one-way ANOVA ( p > 0.05). Metal plate method could be recommended as the most effective membrane feeding technique for mass rearing of Ae. aegypti , due to its high feeding rate and cost effectiveness. Cattle blood could be recommended for mass rearing Ae. aegypti .

  14. Artificial intelligence techniques applied to the development of a decision-support system for diagnosing celiac disease.

    Science.gov (United States)

    Tenório, Josceli Maria; Hummel, Anderson Diniz; Cohrs, Frederico Molina; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

    2011-11-01

    Celiac disease (CD) is a difficult-to-diagnose condition because of its multiple clinical presentations and symptoms shared with other diseases. Gold-standard diagnostic confirmation of suspected CD is achieved by biopsying the small intestine. To develop a clinical decision-support system (CDSS) integrated with an automated classifier to recognize CD cases, by selecting from experimental models developed using intelligence artificial techniques. A web-based system was designed for constructing a retrospective database that included 178 clinical cases for training. Tests were run on 270 automated classifiers available in Weka 3.6.1 using five artificial intelligence techniques, namely decision trees, Bayesian inference, k-nearest neighbor algorithm, support vector machines and artificial neural networks. The parameters evaluated were accuracy, sensitivity, specificity and area under the ROC curve (AUC). AUC was used as a criterion for selecting the CDSS algorithm. A testing database was constructed including 38 clinical CD cases for CDSS evaluation. The diagnoses suggested by CDSS were compared with those made by physicians during patient consultations. The most accurate method during the training phase was the averaged one-dependence estimator (AODE) algorithm (a Bayesian classifier), which showed accuracy 80.0%, sensitivity 0.78, specificity 0.80 and AUC 0.84. This classifier was integrated into the web-based decision-support system. The gold-standard validation of CDSS achieved accuracy of 84.2% and k=0.68 (pdiagnosis. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  15. Second Order Sliding Mode Controller Design for Pneumatic Artificial Muscle

    OpenAIRE

    Ammar Al-Jodah; Laith Khames

    2018-01-01

    In this paper, first and second order sliding mode controllers are designed for a single link robotic arm actuated by two Pneumatic Artificial Muscles (PAMs). A new mathematical model for the arm has been developed based on the model of large scale pneumatic muscle actuator model. Uncertainty in parameters has been presented and tested for the two controllers. The simulation results of the second-order sliding mode controller proves to have a low tracking error and chattering effect as compar...

  16. Applications Of Artificial Intelligence In Control System Analysis And Design

    Science.gov (United States)

    Birdwell, J. D.

    1987-10-01

    To date, applications of artificial intelligence in control system analysis and design are primarily associated with the design process. These applications take the form of knowledge bases incorporating expertise on a design method, such as multivariable linear controller design, or on a field such as identification. My experience has demonstrated that, while such expert systems are useful, perhaps a greater benefit will come from applications in the maintenance of technical databases, as are found in real-time data acquisition systems, and of modeling and design databases, which represent the status of a computer-aided design process for a human user. This reflects the observation that computers are best at maintaining relations about large sets of objects, whereas humans are best at maintaining knowledge of depth, as occurs when a design option involving a sequence of steps is explored. This paper will discuss some of these issues, and will provide some examples which illustrate the potential of artificial intelligence.

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

    Science.gov (United States)

    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.

  18. Novel USDA Mosquito Control Techniques for the US Military

    Science.gov (United States)

    Novel techniques that we developed at the USDA to protect deployed military troops from the threat of vector-borne diseases are described. Some of the methods developed included (1) novel military personal protection methods, (2) barrier treatments of artificial materials and natural vegetation, and...

  19. Optimal fuel loading pattern design using artificial intelligence techniques

    International Nuclear Information System (INIS)

    Kim, Han Gon; Chang, Soon Heung; Lee, Byung Ho

    1993-01-01

    The Optimal Fuel Shuffling System (OFSS) is developed for optimal design of PWR fuel loading pattern. OFSS is a hybrid system that a rule based system, a fuzzy logic, and an artificial neural network are connected each other. The rule based system classifies loading patterns into two classes using several heuristic rules and a fuzzy rule. A fuzzy rule is introduced to achieve more effective and fast searching. Its membership function is automatically updated in accordance with the prediction results. The artificial neural network predicts core parameters for the patterns generated from the rule based system. The back-propagation network is used for fast prediction of core parameters. The artificial neural network and the fuzzy logic can be used as the tool for improvement of existing algorithm's capabilities. OFSS was demonstrated and validated for cycle 1 of Kori unit 1 PWR. (Author)

  20. Global Control of the Furuta Pendulum Using Artificial Neural Networks and Feedback of State Variables

    Directory of Open Access Journals (Sweden)

    Luisa F. Escobar-Dávila

    2013-06-01

    Full Text Available This paper presents the mathematical modeling of the Furuta Pendu-lum by power functions, taking into account the non linear own dynamics of the physical systems and considering the existing couplings between the electric and mechanic devices. A control process based on feedback of state variables (FSV for the equilibrium point is developed and two topics for the non linear zone are addressed. First of all, functions are implemented to represent the energetic states of the plant in a global way and the operation regions are established (“Swing up” zone, and later Artificial Neural Networks (ANN are employed to simulate the behavior of the energy functions. Finally, it is presented the combination between the control techniques, considering the own constrains of the actuators and sensors used, besides of this, a study is done in a simulated environment of the physical phenomena that may disturb system behavior, and the capacity, sensitivity and robustness of the controller is verified.

  1. Automatic diameter control system applied to the laser heated pedestal growth technique

    Directory of Open Access Journals (Sweden)

    Andreeta M.R.B.

    2003-01-01

    Full Text Available We described an automatic diameter control system (ADC, for the laser heated pedestal growth technique, that reduces the diameter fluctuations in oxide fibers grown from unreacted and non-sinterized pedestals, to less than 2% of the average fiber diameter, and diminishes the average diameter fluctuation, over the entire length of the fiber, to less than 1%. The ADC apparatus is based on an artificial vision system that controls the pulling speed and the height of the molten zone within a precision of 30 mum. We also show that this system can be used for periodic in situ axial doping the fiber. Pure and Cr3+ doped LaAlO3 and pure LiNbO3 were usedas model materials.

  2. Overload control of artificial gravity facility using spinning tether system for high eccentricity transfer orbits

    Science.gov (United States)

    Gou, Xing-wang; Li, Ai-jun; Tian, Hao-chang; Wang, Chang-qing; Lu, Hong-shi

    2018-06-01

    As the major part of space life supporting systems, artificial gravity requires further study before it becomes mature. Spinning tether system is a good alternative solution to provide artificial gravity for the whole spacecraft other than additional devices, and its longer tether length could significantly reduce spinning velocity and thus enhance comfortability. An approximated overload-based feedback method is proposed to provide estimated spinning velocity signals for controller, so that gravity level could be accurately controlled without complicated GPS modules. System behavior in high eccentricity transfer orbits is also studied to give a complete knowledge of the spinning stabilities. The application range of the proposed method is studied in various orbit cases and spinning velocities, indicating that it is accurate and reliable for most of the mission phases especially for the final constant gravity level phase. In order to provide stable gravity level for transfer orbit missions, a sliding mode controller based on estimated angular signals is designed for closed-loop control. Numerical results indicate that the combination of overload-based feedback and sliding mode controller could satisfy most of the long-term artificial gravity missions. It is capable of forming flexible gravity environment in relatively good accuracy even in the lowest possible orbital radiuses and high eccentricity orbits of crewed space missions. The proposed scheme provides an effective tether solution for the artificial gravity construction in interstellar travel.

  3. Voltage control of magnetic monopoles in artificial spin ice

    Science.gov (United States)

    Chavez, Andres C.; Barra, Anthony; Carman, Gregory P.

    2018-06-01

    Current research on artificial spin ice (ASI) systems has revealed unique hysteretic memory effects and mobile quasi-particle monopoles controlled by externally applied magnetic fields. Here, we numerically demonstrate a strain-mediated multiferroic approach to locally control the ASI monopoles. The magnetization of individual lattice elements is controlled by applying voltage pulses to the piezoelectric layer resulting in strain-induced magnetic precession timed for 180° reorientation. The model demonstrates localized voltage control to move the magnetic monopoles across lattice sites, in CoFeB, Ni, and FeGa based ASI’s. The switching is achieved at frequencies near ferromagnetic resonance and requires energies below 620 aJ. The results demonstrate that ASI monopoles can be efficiently and locally controlled with a strain-mediated multiferroic approach.

  4. Tracking control of a leg rehabilitation machine driven by pneumatic artificial muscles using composite fuzzy theory.

    Science.gov (United States)

    Chang, Ming-Kun

    2014-01-01

    It is difficult to achieve excellent tracking performance for a two-joint leg rehabilitation machine driven by pneumatic artificial muscles (PAMs) because the system has a coupling effect, highly nonlinear and time-varying behavior associated with gas compression, and the nonlinear elasticity of bladder containers. This paper therefore proposes a T-S fuzzy theory with supervisory control in order to overcome the above problems. The T-S fuzzy theory decomposes the model of a nonlinear system into a set of linear subsystems. In this manner, the controller in the T-S fuzzy model is able to use simple linear control techniques to provide a systematic framework for the design of a state feedback controller. Then the LMI Toolbox of MATLAB can be employed to solve linear matrix inequalities (LMIs) in order to determine controller gains based on the Lyapunov direct method. Moreover, the supervisory control can overcome the coupling effect for a leg rehabilitation machine. Experimental results show that the proposed controller can achieve excellent tracking performance, and guarantee robustness to system parameter uncertainties.

  5. Inseminación artificial de abejas reinas

    OpenAIRE

    Flores Serrano, J.M.; Padilla-Alvarez, F.; Ruiz, J.A.; Ruz, J.M.; Puerta Puerta, F.; Bustos Ruiz, M.; Campano Cabanes, Francisco

    1998-01-01

    The race commonly used by spanish beekeepers is Apis mellifera iberica. Up to date, any selection process has been carried out with this race, and a lot of characteristics in the colony can be improved. Artificial insemination is a technique used in order to control genetic origin, and open a way to control those tasks usefull for beekeepers, both productive (honey, pollen or royal jelly production...) o linked with behaviour (agresiveless, short tendency to swarming, natural resistance to di...

  6. Contamination Control Techniques

    Energy Technology Data Exchange (ETDEWEB)

    EBY, J.L.

    2000-05-16

    Welcome to a workshop on contamination Control techniques. This work shop is designed for about two hours. Attendee participation is encouraged during the workshop. We will address different topics within contamination control techniques; present processes, products and equipment used here at Hanford and then open the floor to you, the attendees for your input on the topics.

  7. Contamination Control Techniques

    International Nuclear Information System (INIS)

    EBY, J.L.

    2000-01-01

    Welcome to a workshop on contamination Control techniques. This work shop is designed for about two hours. Attendee participation is encouraged during the workshop. We will address different topics within contamination control techniques; present processes, products and equipment used here at Hanford and then open the floor to you, the attendees for your input on the topics

  8. 'From the moment of conception...': the Vatican instruction on artificial procreation techniques.

    Science.gov (United States)

    Coughlan, Michael J

    1988-10-01

    An analysis is presented of Instruction on Respect for Human Life in Its Origins and on the Dignity of Procreation, the official response of the Catholic Church to moral questions raised by the new reproductive technologies which sets down ethical guidelines for the treatment to be accorded human embryos and for procreative techniques from artificial insemination to surrogate motherhood. The document is viewed in the perspective of earlier Church pronouncements, such as The Declaration on Procured Abortion , and its definition of a person as an individual animated by a rational soul is explored in detail for its implications for discussions on the personhood of the human embryo.

  9. Use of artificial intelligence techniques for optimisation of co-combustion of coal with biomass

    Energy Technology Data Exchange (ETDEWEB)

    Tan, C.K.; Wilcox, S.J.; Ward, J. [University of Glamorgan, Pontypridd (United Kingdom). Division of Mechanical Engineering

    2006-03-15

    The optimisation of burner operation in conventional pulverised-coal-fired boilers for co-combustion applications represents a significant challenge This paper describes a strategic framework in which Artificial Intelligence (AI) techniques can be applied to solve such an optimisation problem. The effectiveness of the proposed system is demonstrated by a case study that simulates the co-combustion of coal with sewage sludge in a 500-kW pilot-scale combustion rig equipped with a swirl stabilised low-NOx burner. A series of Computational Fluid Dynamics (CFD) simulations were performed to generate data for different operating conditions, which were then used to train several Artificial Neural Networks (ANNs) to predict the co-combustion performance. Once trained, the ANNs were able to make estimations of unseen situations in a fraction of the time taken by the CFD simulation. Consequently, the networks were capable of representing the underlying physics of the CFD models and could be executed efficiently for a large number of iterations as required by optimisation techniques based on Evolutionary Algorithms (EAs). Four operating parameters of the burner, namely the swirl angles and flow rates of the secondary and tertiary combustion air were optimised with the objective of minimising the NOx and CO emissions as well as the unburned carbon at the furnace exit. The results suggest that ANNs combined with EAs provide a useful tool for optimising co-combustion processes.

  10. Artificial lifting supervision: successes solutions apply for 3.000 oil wells; Supervisao na elevacao artificial: uma solucao aplicada com sucesso em 3.000 pocos de petroleo

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Rutacio O. [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil); Souza, Rodrigo B. [RN TECNOLOGIA, Natal, RN (Brazil); Maitelli, Andre L. [Universidade Federal do Rio Grande do Norte, Natal, RN (Brazil)

    2008-07-01

    The gathering of information in industrial automation is essential to maintain and control the industrial processes. In the automation of oil wells, each artificial elevation method has its own variables to be monitored. Thus, several automation companies have developed specific controllers with its own communication protocol and supervisory software. However, in an ideal case, all information about oil elevation should be available in one single application. The SISAL is a SCADA system able to collect processes data and deliver them to the users or other system, regardless of the technique used for artificial elevation, controllers and connecting devices to the wells. This paper is about the application, progress and results using this software in PETROBRAS. (author)

  11. New control strategies for neuroprosthetic systems

    NARCIS (Netherlands)

    Crago, Patrick E.; Veltink, Petrus H.; Lan, Ning; Abbas, James J.; Kantor, Carole

    1996-01-01

    The availability of techniques to artificially excite paralyzed muscles opens enormous potential for restoring both upper and lower extremity movements with neuroprostheses. Neuroprostheses must stimulate muscle, and control and regulate the artificial movements produced. Control methods to

  12. Towards Realization of Intelligent Medical Treatment at Nanoscale by Artificial Microscopic Swarm Control Systems

    Directory of Open Access Journals (Sweden)

    Alireza Rowhanimanesh

    2017-07-01

    Full Text Available Background: In this paper, the novel concept of artificial microscopic swarm control systems is proposed as a promising approach towards realization of intelligent medical treatment at nanoscale. In this new paradigm, treatment is done autonomously at nanoscale within the patient’s body by the proposed swarm control systems.Methods: From control engineering perspective, medical treatment can be considered as a control problem, in which the ultimate goal is to find the best feasible way to change the state of diseased tissue from unhealthy to healthy in presence of uncertainty. Although a living tissue is a huge swarm of microscopic cells, nearly all of the common treatment methods are based on macroscopic centralized control paradigm. Inspired by natural microscopic swarm control systems such as nervous, endocrine and immune systems that work based on swarm control paradigm, medical treatment needs a paradigm shift from macroscopic centralized control to microscopic swarm control. An artificial microscopic swarm control system consists of a huge number of very simple autonomous microscopic agents that exploit swarm intelligence to realize sense, control (computing and actuation at nanoscale in local, distributed and decentralized manner. This control system can be designed based on mathematical analysis and computer simulation.Results: The proposed approach is used for treatment of atherosclerosis and cancer based on mathematical analysis and in-silico study.Conclusion: The notion of artificial microscopic swarm control systems opens new doors towards realization of autonomous and intelligent medical treatment at nanoscale within the patient’s body.

  13. Appraisal of artificial screening techniques of tomato to accurately reflect field performance of the late blight resistance.

    Directory of Open Access Journals (Sweden)

    Marzena Nowakowska

    Full Text Available Late blight (LB caused by the oomycete Phytophthora infestans continues to thwart global tomato production, while only few resistant cultivars have been introduced locally. In order to gain from the released tomato germplasm with LB resistance, we compared the 5-year field performance of LB resistance in several tomato cultigens, with the results of controlled conditions testing (i.e., detached leaflet/leaf, whole plant. In case of these artificial screening techniques, the effects of plant age and inoculum concentration were additionally considered. In the field trials, LA 1033, L 3707, L 3708 displayed the highest LB resistance, and could be used for cultivar development under Polish conditions. Of the three methods using controlled conditions, the detached leaf and the whole plant tests had the highest correlation with the field experiments. The plant age effect on LB resistance in tomato reported here, irrespective of the cultigen tested or inoculum concentration used, makes it important to standardize the test parameters when screening for resistance. Our results help show why other reports disagree on LB resistance in tomato.

  14. Artificial intelligence in nuclear power plants

    International Nuclear Information System (INIS)

    Haapanen, P.J.

    1990-01-01

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

  15. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2003-01-01

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

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

    Science.gov (United States)

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

    2009-09-01

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

  17. Artificial intelligence applications to nuclear reactor diagnostics

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  18. Research on reactor power controller based on artificial immune P and PID cascade control technology

    International Nuclear Information System (INIS)

    Cheng Shouyu; Peng Minjun; Liu Xinkai

    2014-01-01

    The Reactor Power control system usually adopts the traditional PID controller, the traditional PID controller can meet the operating requirements, but the control effect is not very good. In order to improve this condition, the paper proposes an immune P and PID cascade controller which based the immune mechanism of B-cell co-operating with T-cell, the nuclear power controller based on artificial immune is less reported. In order to verify and validate the control strategy, the designed controller debugs with the full-scope real-time simulation system of nuclear power plants. The simulation results shows that the immune controller can effectively improve the dynamic operating characteristics of the reactor system, and the immune controller is superior to the traditional PID controller in control performance. (authors)

  19. Artificial control of muscle by endoneural multi electrode stimulation and sensing

    NARCIS (Netherlands)

    Rutten, Wim; Bouwman, R.L.M.

    1991-01-01

    Artificial electrical stimulation of motor nerves for muscle control can be made selective by using intrafascicular micro electrode arrays which contact many individual or small groups of nerve fibres. If at the same time te electrode arrays could record afferent information from the stimulated

  20. Realizing three-dimensional artificial spin ice by stacking planar nano-arrays

    International Nuclear Information System (INIS)

    Chern, Gia-Wei; Reichhardt, Charles; Nisoli, Cristiano

    2014-01-01

    Artificial spin ice is a frustrated magnetic two-dimensional nano-material, recently employed to study variety of tailor-designed unusual collective behaviours. Recently proposed extensions to three dimensions are based on self-assembly techniques and allow little control over geometry and disorder. We present a viable design for the realization of a three-dimensional artificial spin ice with the same level of precision and control allowed by lithographic nano-fabrication of the popular two-dimensional case. Our geometry is based on layering already available two-dimensional artificial spin ice and leads to an arrangement of ice-rule-frustrated units, which is topologically equivalent to that of the tetrahedra in a pyrochlore lattice. Consequently, we show, it exhibits a genuine ice phase and its excitations are, as in natural spin ice materials, magnetic monopoles interacting via Coulomb law

  1. Active vibration control by robust control techniques

    International Nuclear Information System (INIS)

    Lohar, F.A.

    2001-01-01

    This paper studies active vibration control of multi-degree-of-freedom system. The control techniques considered are LTR, H/sup 2/ and H/sup infinite/. The results show that LTR controls the vibration but its respective settling time is higher than that of the other techniques. The control performance of H/sup infinite/ control is similar to that of H/sup 2/ control in the case of it weighting functions. However, H/sup infinite/ control is superior to H/sup 2/ control with respect to robustness, steady state error and settling time. (author)

  2. Second Order Sliding Mode Controller Design for Pneumatic Artificial Muscle

    Directory of Open Access Journals (Sweden)

    Ammar Al-Jodah

    2018-01-01

    Full Text Available In this paper, first and second order sliding mode controllers are designed for a single link robotic arm actuated by two Pneumatic Artificial Muscles (PAMs. A new mathematical model for the arm has been developed based on the model of large scale pneumatic muscle actuator model. Uncertainty in parameters has been presented and tested for the two controllers. The simulation results of the second-order sliding mode controller proves to have a low tracking error and chattering effect as compared to the first order one. The verification has been done by using MATLAB and Simulink software.

  3. Random fiber laser based on artificially controlled backscattering fibers.

    Science.gov (United States)

    Wang, Xiaoliang; Chen, Daru; Li, Haitao; She, Lijuan; Wu, Qiong

    2018-01-10

    The random fiber laser (RFL), which is a milestone in laser physics and nonlinear optics, has attracted considerable attention recently. Most previously reported RFLs are based on distributed feedback of Rayleigh scattering amplified through the stimulated Raman-Brillouin scattering effect in single-mode fibers, which require long-distance (tens of kilometers) single-mode fibers and high threshold, up to watt level, due to the extremely small Rayleigh scattering coefficient of the fiber. We proposed and demonstrated a half-open-cavity RFL based on a segment of an artificially controlled backscattering single-mode fiber with a length of 210 m, 310 m, or 390 m. A fiber Bragg grating with a central wavelength of 1530 nm and a segment of artificially controlled backscattering single-mode fiber fabricated by using a femtosecond laser form the half-open cavity. The proposed RFL achieves thresholds of 25 mW, 30 mW, and 30 mW, respectively. Random lasing at a wavelength of 1530 nm and extinction ratio of 50 dB is achieved when a segment of 5 m erbium-doped fiber is pumped by a 980 nm laser diode in the RFL. A novel RFL with many short cavities has been achieved with low threshold.

  4. Evaluation of artificial neural network techniques for flow forecasting in the River Yangtze, China

    Directory of Open Access Journals (Sweden)

    C. W. Dawson

    2002-01-01

    Full Text Available While engineers have been quantifying rainfall-runoff processes since the mid-19th century, it is only in the last decade that artificial neural network models have been applied to the same task. This paper evaluates two neural networks in this context: the popular multilayer perceptron (MLP, and the radial basis function network (RBF. Using six-hourly rainfall-runoff data for the River Yangtze at Yichang (upstream of the Three Gorges Dam for the period 1991 to 1993, it is shown that both neural network types can simulate river flows beyond the range of the training set. In addition, an evaluation of alternative RBF transfer functions demonstrates that the popular Gaussian function, often used in RBF networks, is not necessarily the ‘best’ function to use for river flow forecasting. Comparisons are also made between these neural networks and conventional statistical techniques; stepwise multiple linear regression, auto regressive moving average models and a zero order forecasting approach. Keywords: Artificial neural network, multilayer perception, radial basis function, flood forecasting

  5. Augmented Nonlinear Controller for Maximum Power-Point Tracking with Artificial Neural Network in Grid-Connected Photovoltaic Systems

    Directory of Open Access Journals (Sweden)

    Suliang Ma

    2016-11-01

    Full Text Available Photovoltaic (PV systems have non-linear characteristics that generate maximum power at one particular operating point. Environmental factors such as irradiance and temperature variations greatly affect the maximum power point (MPP. Diverse offline and online techniques have been introduced for tracking the MPP. Here, to track the MPP, an augmented-state feedback linearized (AFL non-linear controller combined with an artificial neural network (ANN is proposed. This approach linearizes the non-linear characteristics in PV systems and DC/DC converters, for tracking and optimizing the PV system operation. It also reduces the dependency of the designed controller on linearized models, to provide global stability. A complete model of the PV system is simulated. The existing maximum power-point tracking (MPPT and DC/DC boost-converter controller techniques are compared with the proposed ANN method. Two case studies, which simulate realistic circumstances, are presented to demonstrate the effectiveness and superiority of the proposed method. The AFL with ANN controller can provide good dynamic operation, faster convergence speed, and fewer operating-point oscillations around the MPP. It also tracks the global maxima under different conditions, especially irradiance-mutating situations, more effectively than the conventional methods. Detailed mathematical models and a control approach for a three-phase grid-connected intelligent hybrid system are proposed using MATLAB/Simulink.

  6. Position and Speed Control of Brushless DC Motors Using Sensorless Techniques and Application Trends

    Directory of Open Access Journals (Sweden)

    Jaime Gómez-Gil

    2010-07-01

    Full Text Available This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order and Artificial Neural Networks.

  7. Control of Three-Phase Grid-Connected Microgrids Using Artificial Neural Networks

    OpenAIRE

    Shuhui, L.; Fu, X.; Jaithwa, I.; Alonso, E.; Fairbank, M.; Wunsch, D. C.

    2015-01-01

    A microgrid consists of a variety of inverter-interfaced distributed energy resources (DERs). A key issue is how to control DERs within the microgrid and how to connect them to or disconnect them from the microgrid quickly. This paper presents a strategy for controlling inverter-interfaced DERs within a microgrid using an artificial neural network, which implements a dynamic programming algorithm and is trained with a new Levenberg-Marquardt backpropagation algorithm. Compared to conventional...

  8. In-plane pitch control of cholesteric liquid crystals by formation of artificial domains via patterned photopolymerization.

    Science.gov (United States)

    Yoshida, Hiroyuki; Miura, Yusuke; Tokuoka, Kazuki; Suzuki, Satoshi; Fujii, Akihiko; Ozaki, Masanori

    2008-11-10

    A controlled helix pitch modulation in the in-plane direction of a planarly aligned cholesteric liquid crystal cell is demonstrated by using photopolymerizable cholesteric liquid crystals. By fabricating artificial domains with a closed volume via two-photon excitation laser-lithography, the degree of pitch modulation could be controlled by adjusting the surface area to volume ratio of the domain. A pitch modulation of over 60 nm was realized by designing the shape of the artificial domain.

  9. A hybrid artificial neural network as a software sensor for optimal control of a wastewater treatment process.

    Science.gov (United States)

    Choi, D J; Park, H

    2001-11-01

    For control and automation of biological treatment processes, lack of reliable on-line sensors to measure water quality parameters is one of the most important problems to overcome. Many parameters cannot be measured directly with on-line sensors. The accuracy of existing hardware sensors is also not sufficient and maintenance problems such as electrode fouling often cause trouble. This paper deals with the development of software sensor techniques that estimate the target water quality parameter from other parameters using the correlation between water quality parameters. We focus our attention on the preprocessing of noisy data and the selection of the best model feasible to the situation. Problems of existing approaches are also discussed. We propose a hybrid neural network as a software sensor inferring wastewater quality parameter. Multivariate regression, artificial neural networks (ANN), and a hybrid technique that combines principal component analysis as a preprocessing stage are applied to data from industrial wastewater processes. The hybrid ANN technique shows an enhancement of prediction capability and reduces the overfitting problem of neural networks. The result shows that the hybrid ANN technique can be used to extract information from noisy data and to describe the nonlinearity of complex wastewater treatment processes.

  10. Artificial Leaf Based on Artificial Photosynthesis for Solar Fuel Production

    Science.gov (United States)

    2017-06-30

    collect light energy and separate charge for developing new types of nanobiodevices to construct ”artificial leaf” from solar to fuel. or Concept of...AFRL-AFOSR-JP-TR-2017-0054 Artificial Leaf Based on Artificial Photosynthesis for Solar Fuel Production Mamoru Nango NAGOYA INSTITUTE OF TECHNOLOGY...display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY)      30-06-2017 2

  11. Implantation technique of the 50-cm3 SynCardia Total Artificial Heart: does size make a difference?

    Science.gov (United States)

    Spiliopoulos, Sotirios; Guersoy, Dilek; Dimitriou, Alexandros Merkourios; Koerfer, Reiner; Tenderich, Gero

    2015-01-01

    Despite downsizing, implantation technique of the 50-cm(3) SynCardia Total Artificial Heart and settings of the Companion driver remain unchanged. Owing to the absence of de-airing nipples, de-airing procedure is even more crucial and has to be performed carefully. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

  12. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system.

    Science.gov (United States)

    Mohamed, Ahmed F; Elarini, Mahdi M; Othman, Ahmed M

    2014-05-01

    One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.

  13. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system

    Directory of Open Access Journals (Sweden)

    Ahmed F. Mohamed

    2014-05-01

    Full Text Available One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC. The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.

  14. Statistical Techniques for Project Control

    CERN Document Server

    Badiru, Adedeji B

    2012-01-01

    A project can be simple or complex. In each case, proven project management processes must be followed. In all cases of project management implementation, control must be exercised in order to assure that project objectives are achieved. Statistical Techniques for Project Control seamlessly integrates qualitative and quantitative tools and techniques for project control. It fills the void that exists in the application of statistical techniques to project control. The book begins by defining the fundamentals of project management then explores how to temper quantitative analysis with qualitati

  15. Exercise, Insulin Absorption Rates, and Artificial Pancreas Control

    Science.gov (United States)

    Frank, Spencer; Hinshaw, Ling; Basu, Rita; Basu, Ananda; Szeri, Andrew J.

    2016-11-01

    Type 1 Diabetes is characterized by an inability of a person to endogenously produce the hormone insulin. Because of this, insulin must be injected - usually subcutaneously. The size of the injected dose and the rate at which the dose reaches the circulatory system have a profound effect on the ability to control glucose excursions, and therefore control of diabetes. However, insulin absorption rates via subcutaneous injection are variable and depend on a number of factors including tissue perfusion, physical activity (vasodilation, increased capillary throughput), and other tissue geometric and physical properties. Exercise may also have a sizeable effect on the rate of insulin absorption, which can potentially lead to dangerous glucose levels. Insulin-dosing algorithms, as implemented in an artificial pancreas controller, should account accurately for absorption rate variability and exercise effects on insulin absorption. The aforementioned factors affecting insulin absorption will be discussed within the context of both fluid mechanics and data driven modeling approaches.

  16. Appropriate control time constant in relation to characteristics of the baroreflex vascular system in 1/R control of the total artificial heart.

    Science.gov (United States)

    Mizuta, Sora; Saito, Itsuro; Isoyama, Takashi; Hara, Shintaro; Yurimoto, Terumi; Li, Xinyang; Murakami, Haruka; Ono, Toshiya; Mabuchi, Kunihiko; Abe, Yusuke

    2017-09-01

    1/R control is a physiological control method of the total artificial heart (TAH) with which long-term survival was obtained with animal experiments. However, 1/R control occasionally diverged in the undulation pump TAH (UPTAH) animal experiment. To improve the control stability of the 1/R control, appropriate control time constant in relation to characteristics of the baroreflex vascular system was investigated with frequency analysis and numerical simulation. In the frequency analysis, data of five goats in which the UPTAH was implanted were analyzed with first Fourier transform technique to examine the vasomotion frequency. The numerical simulation was carried out repeatedly changing baroreflex parameters and control time constant using the elements-expanded Windkessel model. Results of the frequency analysis showed that the 1/R control tended to diverge when very low frequency band that was an indication of the vasomotion frequency was relative high. In numerical simulation, divergence of the 1/R control could be reproduced and the boundary curves between the divergence and convergence of the 1/R control varied depending on the control time constant. These results suggested that the 1/R control tended to be unstable when the TAH recipient had high reflex speed in the baroreflex vascular system. Therefore, the control time constant should be adjusted appropriately with the individual vasomotion frequency.

  17. Artificial intelligence in astronomy - a forecast.

    Science.gov (United States)

    Adorf, H. M.

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

  18. Artificial intelligence search techniques for optimization of the cold source geometry

    International Nuclear Information System (INIS)

    Azmy, Y.Y.

    1988-01-01

    Most optimization studies of cold neutron sources have concentrated on the numerical prediction or experimental measurement of the cold moderator optimum thickness which produces the largest cold neutron leakage for a given thermal neutron source. Optimizing the geometrical shape of the cold source, however, is a more difficult problem because the optimized quantity, the cold neutron leakage, is an implicit function of the shape which is the unknown in such a study. We draw an analogy between this problem and a state space search, then we use a simple Artificial Intelligence (AI) search technique to determine the optimum cold source shape based on a two-group, r-z diffusion model. We implemented this AI design concept in the computer program AID which consists of two modules, a physical model module and a search module, which can be independently modified, improved, or made more sophisticated. 7 refs., 1 fig

  19. Artificial intelligence search techniques for the optimization of cold source geometry

    International Nuclear Information System (INIS)

    Azmy, Y.Y.

    1988-01-01

    Most optimization studies of cold neutron sources have concentrated on the numerical prediction or experimental measurement of the cold moderator optimum thickness that produces the largest cold neutron leakage for a given thermal neutron source. Optimizing the geometric shape of the cold source, however, is a more difficult problem because the optimized quantity, the cold neutron leakage, is an implicit function of the shape, which is the unknown in such a study. An analogy is drawn between this problem and a state space search, then a simple artificial intelligence (AI) search technique is used to determine the optimum cold source shape based on a two-group, r-z diffusion model. This AI design concept was implemented in the computer program AID, which consists of two modules, a physical model module, and a search module, which can be independently modified, improved, or made more sophisticated

  20. Moorfields technique of donor cornea mounting for femtosecond-assisted keratoplasty: use of viscoelastic in the artificial anterior chamber.

    Science.gov (United States)

    Iovieno, Alfonso; Chowdhury, Vivek; Stevens, Julian D; Maurino, Vincenzo

    2012-07-01

    Appropriate mounting and cutting of the donor sclero-corneal cap is often cumbersome during femtosecond laser-assisted keratoplasty. The authors describe a technique for donor cornea femtosecond laser cutting using ophthalmic viscoelastic devices. The donor sclero-corneal cap is mounted on the artificial anterior chamber using a dispersive ophthalmic viscoelastic device instead of saline solution. The chances of artificial anterior chamber pressure loss, inadequate applanation, and fluid leaks are consistently reduced with the use of dispersive ophthalmic viscoelastic devices. The speed of donor femtosecond laser cutting is increased. The viscosity and elasticity of dispersive ophthalmic viscoelastic devices greatly assist the procedure with regard to ease of applanation, corneal endothelium protection, and decreased distortion of the applanated cornea. Copyright 2012, SLACK Incorporated.

  1. Light-Triggered Soft Artificial Muscles: Molecular-Level Amplification of Actuation Control Signals.

    Science.gov (United States)

    Dicker, Michael P M; Baker, Anna B; Iredale, Robert J; Naficy, Sina; Bond, Ian P; Faul, Charl F J; Rossiter, Jonathan M; Spinks, Geoffrey M; Weaver, Paul M

    2017-08-23

    The principle of control signal amplification is found in all actuation systems, from engineered devices through to the operation of biological muscles. However, current engineering approaches require the use of hard and bulky external switches or valves, incompatible with both the properties of emerging soft artificial muscle technology and those of the bioinspired robotic systems they enable. To address this deficiency a biomimetic molecular-level approach is developed that employs light, with its excellent spatial and temporal control properties, to actuate soft, pH-responsive hydrogel artificial muscles. Although this actuation is triggered by light, it is largely powered by the resulting excitation and runaway chemical reaction of a light-sensitive acid autocatalytic solution in which the actuator is immersed. This process produces actuation strains of up to 45% and a three-fold chemical amplification of the controlling light-trigger, realising a new strategy for the creation of highly functional soft actuating systems.

  2. Use of artificial intelligence techniques for visual inspection systems prototyping. Application to magnetoscopy

    International Nuclear Information System (INIS)

    Pallas, Christophe

    1987-01-01

    The automation of visual inspection is a complex task that requires collaboration between experts, for example inspection specialist, vision specialist. on-line operators. Solving such problems through prototyping promotes this collaboration: the use of a non specific programming environment allows rapid, concrete checking of method validity, thus leading incrementally to the final system. In this context, artificial intelligence techniques permit easy, extensible, and modular design of the prototype, together with heuristic solution building. We define and achieve the SPOR prototyping environment, based on object-oriented programming and rules-basis managing. The feasibility and the validity of an heuristic method for automated visual inspection in fluoroscopy have been proved through prototyping in SPOR. (author) [fr

  3. Artificial reef evaluation capabilities of Florida counties

    OpenAIRE

    Halusky, Joseph G.; Antonini, Gustavo A.; Seaman, William

    1993-01-01

    Florida's coastal county artificial reef sampling and data management programs are surveyed in this report. The survey describes the county level capability for artificial reef documentation and performance assessment based on their needs, interests, organizational structure and "in-situ" data collection and data management techniques. The. primary purpose of this study is to describe what staffing, training, techniques, organizational procedures and equipment are used by the c...

  4. Overnight Glucose Control with Dual- and Single-Hormone Artificial Pancreas in Type 1 Diabetes with Hypoglycemia Unawareness: A Randomized Controlled Trial.

    Science.gov (United States)

    Abitbol, Alexander; Rabasa-Lhoret, Remi; Messier, Virginie; Legault, Laurent; Smaoui, Mohamad; Cohen, Nathan; Haidar, Ahmad

    2018-03-01

    The dual-hormone (insulin and glucagon) artificial pancreas may be justifiable in some, but not all, patients. We sought to compare dual- and single-hormone artificial pancreas systems in patients with hypoglycemia unawareness and documented nocturnal hypoglycemia. We conducted a randomized crossover trial comparing the efficacy of dual- and single-hormone artificial pancreas systems in controlling plasma glucose levels over the course of one night's sleep. We recruited 18 adult participants with hypoglycemia unawareness and 17 participants with hypoglycemia awareness, all of whom had documented nocturnal hypoglycemia during 2 weeks of screening. Outcomes were calculated using plasma glucose. In participants with hypoglycemia unawareness, the median (interquartile range [IQR]) percentage of time that plasma glucose was below 4.0 mmol/L was 0% (0-0) on dual-hormone artificial pancreas nights and 0% (0-10) on single-hormone artificial pancreas nights (P = 0.20). Additionally, participants with hypoglycemia unawareness experienced two hypoglycemic events (dual-hormone artificial pancreas nights and three hypoglycemic events on single-hormone artificial pancreas nights. In participants with hypoglycemia awareness, the median (IQR) percentage of time that plasma glucose was below 4.0 mmol/L was 0% (0-0) on both dual- and single-hormone artificial pancreas nights. Hypoglycemia awareness participants experienced zero hypoglycemic events on dual-hormone artificial pancreas nights and one event on single-hormone artificial pancreas nights. In this study, dual-hormone and single-hormone systems performed equally well in preventing nocturnal hypoglycemia in participants with hypoglycemia unawareness. Longer studies over the course of multiple days and nights may be needed to explore possible specific benefits in this population. ClinicalTrials.gov No. NCT02282254.

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

    Indian Academy of Sciences (India)

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

  6. The implementation of artificial intelligence in control systems

    International Nuclear Information System (INIS)

    Koul, R.; Weygand, D.P.

    1987-01-01

    Some concepts of artificial intelligence are reviewed, particularly as they apply to control systems of accelerators. Logical representation and formal reasoning are discussed briefly, as well as production systems, which describe various systems based on the idea of condition-action pairs (productions). Procedural knowledge, which deals with routine activities that rarely require change, is described. Frames are defined, which provide a convenient structure for representing knowledge. Frames consist of information about objects. For a given frame there are various slots, and for each slot there are various facets, each containing various data. Direct analogical representation is defined as a class of representation which represents knowledge in a natural analog manner, allowing observation of facts in many cases to be achieved quickly and easily compared to deduction. Architecture of systems applied to accelerator control is then described

  7. [Artificial organs].

    Science.gov (United States)

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

    2017-01-01

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

  8. The control of artificial radio-elements of medical use in France

    International Nuclear Information System (INIS)

    Cohen, Y.

    1960-01-01

    Artificial radio-elements are sometimes used in hospitals or laboratories possessing specific equipment and certified staff. These radio-elements are produced within the Saclay Nuclear Centre, and, if they are aimed to a medical use, are submitted to a pharmaceutical control which the issue is addressed in this report. After a recall of the preparation of these radio-elements, the author describes physical controls (determination of radioactivity, measurement of colloidal particle size, impurity content), and biological controls performed on these radio-elements. Reprint of a paper published in Annales pharmaceutiques francaises, tom. XVII, p. 250-260, 1959

  9. Artificial Intelligence Techniques to Optimize the EDC/NHS-Mediated Immobilization of Cellulase on Eudragit L-100

    Directory of Open Access Journals (Sweden)

    Min-Chao He

    2012-06-01

    Full Text Available Two artificial intelligence techniques, namely artificial neural network (ANN and genetic algorithm (GA were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl carbodiimide (EDC concentration, N-hydroxysuccinimide (NHS concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the central composite design were used to train ANN by back-propagation algorithm, and the result showed that the trained ANN fitted the data accurately (correlation coefficient R2 = 0.99. Then a maximum immobilization efficiency of 88.76% was searched by genetic algorithm at a EDC concentration of 0.44%, NHS concentration of 0.37% and a coupling time of 2.22 h, where the experimental value was 87.97 ± 6.45%. The application of ANN based optimization by GA is quite successful.

  10. Development of a morphing technique for predicting the position and size of an artificial ear in hemifacial microsomia patients.

    Science.gov (United States)

    Coward, Trevor J; Richards, Robin; Scott, Brendan J J

    2014-01-01

    People with hemifacial microsomia may be missing an ear on the affected side of the face. The principal aim of the study was to develop a morphing technique and to determine whether it could be used to appropriately position an artificial ear, as well as to give an indication of prosthesis size in comparison with the natural ear. Comparisons also were made between the artificial ears being worn by the patients with their natural ears. Data from stereophotogrammetry images of the faces of 10 people were converted into stereolithographic format. Anthropometric points on the face and ear of the unaffected side were plotted. By a process of scaling, the distance between facial landmarks on the unaffected side was estimated for the affected side so as to identify where the morphed ear would be positioned once generated. Generally, the morphed ears appeared to be in acceptable positions. There was a statistically significant difference between the position of the morphed and natural ears (P = .011), as well as the artificial and natural ears (P = .001), but this was unlikely to have any clinical implications. There were no significant differences among the sizes of the natural, morphed, and artificial ears (P = .072). Morphing appears to offer a more precise way of planning the positioning and construction of an artificial ear on patients with hemifacial microsomia than traditional methods. Differences in facial shape on either side of the face may impact on the process. This requires further study.

  11. A program for assisting automatic generation control of the ELETRONORTE using artificial neural network; Um programa para assistencia ao controle automatico de geracao da Eletronorte usando rede neuronal artificial

    Energy Technology Data Exchange (ETDEWEB)

    Brito Filho, Pedro Rodrigues de; Nascimento Garcez, Jurandyr do [Para Univ., Belem, PA (Brazil). Centro Tecnologico; Charone, Junior, Wady [Centrais Eletricas do Nordeste do Brasil S.A. (ELETRONORTE), Belem, PA (Brazil)

    1994-12-31

    This work presents an application of artificial neural network as a support to decision making in the automatic generation control (AGC) of the ELETRONORTE. It uses a software to auxiliary in the decisions in real time of the AGC. (author) 2 refs., 6 figs., 1 tab.

  12. Cooling-load prediction by the combination of rough set theory and an artificial neural-network based on data-fusion technique

    International Nuclear Information System (INIS)

    Hou Zhijian; Lian Zhiwei; Yao Ye; Yuan Xinjian

    2006-01-01

    A novel method integrating rough sets (RS) theory and an artificial neural network (ANN) based on data-fusion technique is presented to forecast an air-conditioning load. Data-fusion technique is the process of combining multiple sensors data or related information to estimate or predict entity states. In this paper, RS theory is applied to find relevant factors to the load, which are used as inputs of an artificial neural-network to predict the cooling load. To improve the accuracy and enhance the robustness of load forecasting results, a general load-prediction model, by synthesizing multi-RSAN (MRAN), is presented so as to make full use of redundant information. The optimum principle is employed to deduce the weights of each RSAN model. Actual prediction results from a real air-conditioning system show that, the MRAN forecasting model is better than the individual RSAN and moving average (AMIMA) ones, whose relative error is within 4%. In addition, individual RSAN forecasting results are better than that of ARIMA

  13. Using the artificial neural network to control the steam turbine heating process

    International Nuclear Information System (INIS)

    Nowak, Grzegorz; Rusin, Andrzej

    2016-01-01

    Highlights: • Inverse Artificial Neural Network has a potential to control the start-up process of a steam turbine. • Two serial neural networks made it possible to model the rotor stress based of steam parameters. • An ANN with feedback enables transient stress modelling with good accuracy. - Abstract: Due to the significant share of renewable energy sources (RES) – wind farms in particular – in the power sector of many countries, power generation systems become sensitive to variable weather conditions. Under unfavourable changes in weather, ensuring required energy supplies involves hasty start-ups of conventional steam power units whose operation should be characterized by higher and higher flexibility. Controlling the process of power engineering machinery operation requires fast predictive models that will make it possible to analyse many parallel scenarios and select the most favourable one. This approach is employed by the algorithm for the inverse neural network control presented in this paper. Based on the current thermal state of the turbine casing, the algorithm controls the steam temperature at the turbine inlet to keep both the start-up rate and the safety of the machine at the allowable level. The method used herein is based on two artificial neural networks (ANN) working in series.

  14. FPGA controlled artificial vascular system

    Directory of Open Access Journals (Sweden)

    Laqua D.

    2015-09-01

    Full Text Available Monitoring the oxygen saturation of an unborn child is an invasive procedure, so far. Transabdominal fetal pulse oximetry is a promising method under research, used to estimate the oxygen saturation of a fetus noninvasively. Due to the nature of the method, the fetal information needs to be extracted from a mixed signal. To properly evaluate signal processing algorithms, a phantom modeling fetal and maternal blood circuits and tissue layers is necessary. This paper presents an improved hardware concept for an artificial vascular system, utilizing an FPGA based CompactRIO System from National Instruments. The experimental model to simulate the maternal and fetal blood pressure curve consists of two identical hydraulic circuits. Each of these circuits consists of a pre-pressure system and an artificial vascular system. Pulse curves are generated by proportional valves, separating these two systems. The dilation of the fetal and maternal artificial vessels in tissue substitutes is measured by transmissive and reflective photoplethysmography. The measurement results from the pressure sensors and the transmissive optical sensors are visualized to show the functionality of the pulse generating systems. The trigger frequency for the maternal valve was set to 1 per second, the fetal valve was actuated at 0.7 per second for validation. The reflective curve, capturing pulsations of the fetal and maternal circuit, was obtained with a high power LED (905 nm as light source. The results show that the system generates pulse curves, similar to its physiological equivalent. Further, the acquired reflective optical signal is modulated by the alternating diameter of the tubes of both circuits, allowing for tests of signal processing algorithms.

  15. Integrated Artificial Intelligence Approaches for Disease Diagnostics.

    Science.gov (United States)

    Vashistha, Rajat; Chhabra, Deepak; Shukla, Pratyoosh

    2018-06-01

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

  16. ANUBIS: artificial neuromodulation using a Bayesian inference system.

    Science.gov (United States)

    Smith, Benjamin J H; Saaj, Chakravarthini M; Allouis, Elie

    2013-01-01

    Gain tuning is a crucial part of controller design and depends not only on an accurate understanding of the system in question, but also on the designer's ability to predict what disturbances and other perturbations the system will encounter throughout its operation. This letter presents ANUBIS (artificial neuromodulation using a Bayesian inference system), a novel biologically inspired technique for automatically tuning controller parameters in real time. ANUBIS is based on the Bayesian brain concept and modifies it by incorporating a model of the neuromodulatory system comprising four artificial neuromodulators. It has been applied to the controller of EchinoBot, a prototype walking rover for Martian exploration. ANUBIS has been implemented at three levels of the controller; gait generation, foot trajectory planning using Bézier curves, and foot trajectory tracking using a terminal sliding mode controller. We compare the results to a similar system that has been tuned using a multilayer perceptron. The use of Bayesian inference means that the system retains mathematical interpretability, unlike other intelligent tuning techniques, which use neural networks, fuzzy logic, or evolutionary algorithms. The simulation results show that ANUBIS provides significant improvements in efficiency and adaptability of the three controller components; it allows the robot to react to obstacles and uncertainties faster than the system tuned with the MLP, while maintaining stability and accuracy. As well as advancing rover autonomy, ANUBIS could also be applied to other situations where operating conditions are likely to change or cannot be accurately modeled in advance, such as process control. In addition, it demonstrates one way in which neuromodulation could fit into the Bayesian brain framework.

  17. Characterization of ceramic materials using ultrasonic technique in the frequency domain and artificial networks

    International Nuclear Information System (INIS)

    Baroni, D.B.; Bittencourt, M.S.Q.; Pereira, C.M.N.A.

    2008-01-01

    The ceramic material characterization is very important to guarantee its mechanical properties. In the case of nuclear fuel (UO 2 ) the adequate porosity ensures its thermal efficiency and its structural integrity that contribute to the safety at nuclear power plants. The Ultrasound Laboratory of the Nuclear Engineering Institute (LABUS/IEN) has developed a technique to measure the porosity in ceramic materials. This technique uses ultrasound signal in the frequency domain and creates spectrum patterns related to the material porosity. Trained artificial neural networks recognizes these patterns and associates them to the porosities. In this work 20 pellets of Alumina were used with porosities in the same range used in the nuclear fuel (0.70% to 4.25%). In this case the used network was able to recognize the patterns of the pellets and to associate to the porosities with 100% of precision. It was possible to distinguished pellets with a difference of 0.01% of the porosity. (author)

  18. A new method of artificial latent fingerprint creation using artificial sweat and inkjet printer.

    Science.gov (United States)

    Hong, Sungwook; Hong, Ingi; Han, Aleum; Seo, Jin Yi; Namgung, Juyoung

    2015-12-01

    In order to study fingerprinting in the field of forensic science, it is very important to have two or more latent fingerprints with identical chemical composition and intensity. However, it is impossible to obtain identical fingerprints, in reality, because fingerprinting comes out slightly differently every time. A previous research study had proposed an artificial fingerprint creation method in which inkjet ink was replaced with amino acids and sodium chloride solution: the components of human sweat. But, this method had some drawbacks: divalent cations were not added while formulating the artificial sweat solution, and diluted solutions were used for creating weakly deposited latent fingerprint. In this study, a method was developed for overcoming the drawbacks of the methods used in the previous study. Several divalent cations were added in this study because the amino acid-ninhydrin (or some of its analogues) complex is known to react with divalent cations to produce a photoluminescent product; and, similarly, the amino acid-1,2-indanedione complex is known to be catalyzed by a small amount of zinc ions to produce a highly photoluminescent product. Also, in this study, a new technique was developed which enables to adjust the intensity when printing the latent fingerprint patterns. In this method, image processing software is used to control the intensity of the master fingerprint patterns, which adjusts the printing intensity of the latent fingerprints. This new method opened the way to produce a more realistic artificial fingerprint in various strengths with one artificial sweat working solution. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  19. Breast Cancer Diagnosis using Artificial Neural Networks with Extreme Learning Techniques

    OpenAIRE

    Chandra Prasetyo Utomo; Aan Kardiana; Rika Yuliwulandari

    2014-01-01

    Breast cancer is the second cause of dead among women. Early detection followed by appropriate cancer treatment can reduce the deadly risk. Medical professionals can make mistakes while identifying a disease. The help of technology such as data mining and machine learning can substantially improve the diagnosis accuracy. Artificial Neural Networks (ANN) has been widely used in intelligent breast cancer diagnosis. However, the standard Gradient-Based Back Propagation Artificial Neural Networks...

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

    Science.gov (United States)

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

    2007-10-01

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

  1. Artificial Intelligence in Autonomous Telescopes

    Science.gov (United States)

    Mahoney, William; Thanjavur, Karun

    2011-03-01

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

  2. Formation control of robotic swarm using bounded artificial forces.

    Science.gov (United States)

    Qin, Long; Zha, Yabing; Yin, Quanjun; Peng, Yong

    2013-01-01

    Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions.

  3. Heat input control in coke ovens battery using artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, R.; Kannan, C.; Sistla, S.; Kumar, D. [Tata Steel, Jamshedpur (India)

    2005-07-01

    Controlled heating is very essential for producing coke with certain desired properties. Controlled heating involves controlling the heat input into the battery dynamically depending on the various process parameters like current battery temperature, the set point of battery temperature, moisture in coal, ambient temperature, coal fineness, cake breakage etc. An artificial intelligence (AI) based heat input control has been developed in which currently some of the above mentioned process parameters are considered and used for calculating the pause time which is applied between reversal during the heating process. The AI based model currently considers 3 input variables, temperature deviation history, current deviation of the battery temperature from the target temperature and the actual heat input into the battery. Work is in progress to control the standard deviation of coke end temperature using this model. The new system which has been developed in-house has replaced Hoogovens supplied model. 7 figs.

  4. Detection of Anomalies in Hydrometric Data Using Artificial Intelligence Techniques

    Science.gov (United States)

    Lauzon, N.; Lence, B. J.

    2002-12-01

    This work focuses on the detection of anomalies in hydrometric data sequences, such as 1) outliers, which are individual data having statistical properties that differ from those of the overall population; 2) shifts, which are sudden changes over time in the statistical properties of the historical records of data; and 3) trends, which are systematic changes over time in the statistical properties. For the purpose of the design and management of water resources systems, it is important to be aware of these anomalies in hydrometric data, for they can induce a bias in the estimation of water quantity and quality parameters. These anomalies may be viewed as specific patterns affecting the data, and therefore pattern recognition techniques can be used for identifying them. However, the number of possible patterns is very large for each type of anomaly and consequently large computing capacities are required to account for all possibilities using the standard statistical techniques, such as cluster analysis. Artificial intelligence techniques, such as the Kohonen neural network and fuzzy c-means, are clustering techniques commonly used for pattern recognition in several areas of engineering and have recently begun to be used for the analysis of natural systems. They require much less computing capacity than the standard statistical techniques, and therefore are well suited for the identification of outliers, shifts and trends in hydrometric data. This work constitutes a preliminary study, using synthetic data representing hydrometric data that can be found in Canada. The analysis of the results obtained shows that the Kohonen neural network and fuzzy c-means are reasonably successful in identifying anomalies. This work also addresses the problem of uncertainties inherent to the calibration procedures that fit the clusters to the possible patterns for both the Kohonen neural network and fuzzy c-means. Indeed, for the same database, different sets of clusters can be

  5. Artificial Intelligence Based Control Power Optimization on Tailless Aircraft. [ARMD Seedling Fund Phase I

    Science.gov (United States)

    Gern, Frank; Vicroy, Dan D.; Mulani, Sameer B.; Chhabra, Rupanshi; Kapania, Rakesh K.; Schetz, Joseph A.; Brown, Derrell; Princen, Norman H.

    2014-01-01

    Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling large arrays of control devices on innovative air vehicles. Artificial neutral networks are inspired by biological nervous systems and neurocomputing has successfully been applied to a variety of complex optimization problems. This project investigates the potential of applying neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts to minimize control power, hinge moments, and actuator forces, while keeping system weights within acceptable limits. The main objective of this project is to develop a proof-of-concept process suitable to demonstrate the potential of using neurocomputing for optimizing actuation power for aircraft featuring multiple independently actuated control surfaces. A Nastran aeroservoelastic finite element model is used to generate a learning database of hinge moment and actuation power characteristics for an array of flight conditions and control surface deflections. An artificial neural network incorporating a genetic algorithm then uses this training data to perform control allocation optimization for the investigated aircraft configuration. The phase I project showed that optimization results for the sum of required hinge moments are improved by more than 12% over the best Nastran solution by using the neural network optimization process.

  6. Minimally Naturalistic Artificial Intelligence

    OpenAIRE

    Hansen, Steven Stenberg

    2017-01-01

    The rapid advancement of machine learning techniques has re-energized research into general artificial intelligence. While the idea of domain-agnostic meta-learning is appealing, this emerging field must come to terms with its relationship to human cognition and the statistics and structure of the tasks humans perform. The position of this article is that only by aligning our agents' abilities and environments with those of humans do we stand a chance at developing general artificial intellig...

  7. Artificial intelligence techniques applied to the development of a decision–support system for diagnosing celiac disease

    Science.gov (United States)

    Tenório, Josceli Maria; Hummel, Anderson Diniz; Cohrs, Frederico Molina; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

    2013-01-01

    Background Celiac disease (CD) is a difficult-to-diagnose condition because of its multiple clinical presentations and symptoms shared with other diseases. Gold-standard diagnostic confirmation of suspected CD is achieved by biopsying the small intestine. Objective To develop a clinical decision–support system (CDSS) integrated with an automated classifier to recognize CD cases, by selecting from experimental models developed using intelligence artificial techniques. Methods A web-based system was designed for constructing a retrospective database that included 178 clinical cases for training. Tests were run on 270 automated classifiers available in Weka 3.6.1 using five artificial intelligence techniques, namely decision trees, Bayesian inference, k-nearest neighbor algorithm, support vector machines and artificial neural networks. The parameters evaluated were accuracy, sensitivity, specificity and area under the ROC curve (AUC). AUC was used as a criterion for selecting the CDSS algorithm. A testing database was constructed including 38 clinical CD cases for CDSS evaluation. The diagnoses suggested by CDSS were compared with those made by physicians during patient consultations. Results The most accurate method during the training phase was the averaged one-dependence estimator (AODE) algorithm (a Bayesian classifier), which showed accuracy 80.0%, sensitivity 0.78, specificity 0.80 and AUC 0.84. This classifier was integrated into the web-based decision–support system. The gold-standard validation of CDSS achieved accuracy of 84.2% and k = 0.68 (p < 0.0001) with good agreement. The same accuracy was achieved in the comparison between the physician’s diagnostic impression and the gold standard k = 0. 64 (p < 0.0001). There was moderate agreement between the physician’s diagnostic impression and CDSS k = 0.46 (p = 0.0008). Conclusions The study results suggest that CDSS could be used to help in diagnosing CD, since the algorithm tested achieved excellent

  8. Applicability of statistical process control techniques

    NARCIS (Netherlands)

    Schippers, W.A.J.

    1998-01-01

    This paper concerns the application of Process Control Techniques (PCTs) for the improvement of the technical performance of discrete production processes. Successful applications of these techniques, such as Statistical Process Control Techniques (SPC), can be found in the literature. However, some

  9. Speed control of SR motor by self-tuning fuzzy PI controller with ...

    Indian Academy of Sciences (India)

    traditional controllers PI (Proportional Integral), PD (Proportional Derivative), ... In SRM control, non-linear techniques such as sliding mode, artificial neural network ..... Proc. of the 1st Int. Confer. on Machine Learning and Cybernetic, Beijing, ...

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

    Science.gov (United States)

    Busse, Carl

    1988-01-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  13. Computed Flow Through An Artificial Heart And Valve

    Science.gov (United States)

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

    1994-01-01

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

  14. Formation Control of Robotic Swarm Using Bounded Artificial Forces

    Science.gov (United States)

    Zha, Yabing; Peng, Yong

    2013-01-01

    Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions. PMID:24453809

  15. Formation Control of Robotic Swarm Using Bounded Artificial Forces

    Directory of Open Access Journals (Sweden)

    Long Qin

    2013-01-01

    Full Text Available Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions.

  16. Applying Space Technology to Enhance Control of an Artificial Arm for Children and Adults With Amputations

    Science.gov (United States)

    Atkins, Diane J.

    1998-01-01

    The first single function myoelectric prosthetic hand was introduced in the 1960's. This hand was controlled by the electric fields generated by muscle contractions in the residual limb of the amputee user. Electrodes and amplifiers, embedded in the prosthetic socket, measured these electric fields across the skin, which increase in amplitude as the individual contracts their muscle. When the myoelectric signal reached a certain threshold amplitude, the control unit activated a motor which opened or closed a hand-like prosthetic terminal device with a pincher grip. Late in the 1990's, little has changed. Most current myoelectric prostheses still operate in this same, single-function way. To better understand the limitations of the current single-function myoelectric hand and the needs of those who use them, The Institute for Rehabilitation and Research (TIRR), sponsored by the National Institutes of Health (NUH), surveyed approximately 2,500 individuals with upper limb loss [1]. When asked to identify specific features of their current myoelectric prostheses that needed improvement, the survey respondents overwhelmingly identified the lack of wrist and finger movement, as well as poor control capability. However, simply building a mechanism with individual finger and wrist motion is not enough. In the 1960's and 1970's, engineers built a number of more dexterous prosthetic hands. Unfortunately, these were rejected during clinical trials due to a difficult and distracting control interface. The goal of this project, "Applying Space Technology to Enhance Control of an Artificial Arm for Children and Adults with Amputations," was to lay the foundation for a multi-function, intuitive myoelectric control system which requires no conscious thought to move the hand. We built an extensive myoelectric signal database for six motions from ten amputee volunteers, We also tested a control system based on new artificial intelligence techniques on the data from two of these

  17. An artificial vision-based control system for automatic heliostat positioning offset correction in a central receiver solar power plant

    Energy Technology Data Exchange (ETDEWEB)

    Berenguel, M. [Universidad de Almeria, Dept. de Lenguajes y Computacion, La Canada Almeria (Spain); Rubio, F.R.; Lara, P.J.; Arahal, M.R.; Camacho, E.F.; Lopez, M. [Universidad de Sevilla, Dept. de Ingenieria de Sistemas y Automatica, Sevilla (Spain); Valverde, A. [Plataforma Solar de Almeria (PSA-CIEMAT), Tabernas (Almeria) (Spain)

    2004-07-01

    This paper presents the development of a simplified and automatic heliostat positioning offset correction control system using artificial vision techniques and common CCD devices. The heliostats of a solar power plant reflect solar radiation onto a receiver (in this case, a volumetric receiver) placed at the top of a tower in order to provide a desired energy flux distribution correlated with the coolant flow (in this case air mass flow) through the receiver, usually in an open loop control configuration. There exist error sources that increase the complexity of the control system, some of which are systematic ones, mainly due to tolerances, wrong mirror facets alignment (optical errors), errors due to the approximations made when calculating the solar position, etc., that produce errors (offsets) in the heliostat orientation (aiming point). The approximation adopted in this paper is based on the use of a B/W CCD camera to correct these deviations in an automatic way imitating the same procedure followed by the operators. The obtained images are used to estimate the distance between the sunbeam centroid projected by the heliostats and a target placed on the tower, this distance thus is used for low accuracy offset correction purposes. Basic threshold-based image processing techniques are used for automatic correction. (Author)

  18. Artificial intelligent techniques for optimizing water allocation in a reservoir watershed

    Science.gov (United States)

    Chang, Fi-John; Chang, Li-Chiu; Wang, Yu-Chung

    2014-05-01

    This study proposes a systematical water allocation scheme that integrates system analysis with artificial intelligence techniques for reservoir operation in consideration of the great uncertainty upon hydrometeorology for mitigating droughts impacts on public and irrigation sectors. The AI techniques mainly include a genetic algorithm and adaptive-network based fuzzy inference system (ANFIS). We first derive evaluation diagrams through systematic interactive evaluations on long-term hydrological data to provide a clear simulation perspective of all possible drought conditions tagged with their corresponding water shortages; then search the optimal reservoir operating histogram using genetic algorithm (GA) based on given demands and hydrological conditions that can be recognized as the optimal base of input-output training patterns for modelling; and finally build a suitable water allocation scheme through constructing an adaptive neuro-fuzzy inference system (ANFIS) model with a learning of the mechanism between designed inputs (water discount rates and hydrological conditions) and outputs (two scenarios: simulated and optimized water deficiency levels). The effectiveness of the proposed approach is tested on the operation of the Shihmen Reservoir in northern Taiwan for the first paddy crop in the study area to assess the water allocation mechanism during drought periods. We demonstrate that the proposed water allocation scheme significantly and substantially avails water managers of reliably determining a suitable discount rate on water supply for both irrigation and public sectors, and thus can reduce the drought risk and the compensation amount induced by making restrictions on agricultural use water.

  19. Experimental quantum control landscapes: Inherent monotonicity and artificial structure

    International Nuclear Information System (INIS)

    Roslund, Jonathan; Rabitz, Herschel

    2009-01-01

    Unconstrained searches over quantum control landscapes are theoretically predicted to generally exhibit trap-free monotonic behavior. This paper makes an explicit experimental demonstration of this intrinsic monotonicity for two controlled quantum systems: frequency unfiltered and filtered second-harmonic generation (SHG). For unfiltered SHG, the landscape is randomly sampled and interpolation of the data is found to be devoid of landscape traps up to the level of data noise. In the case of narrow-band-filtered SHG, trajectories are taken on the landscape to reveal a lack of traps. Although the filtered SHG landscape is trap free, it exhibits a rich local structure. A perturbation analysis around the top of these landscapes provides a basis to understand their topology. Despite the inherent trap-free nature of the landscapes, practical constraints placed on the controls can lead to the appearance of artificial structure arising from the resultant forced sampling of the landscape. This circumstance and the likely lack of knowledge about the detailed local landscape structure in most quantum control applications suggests that the a priori identification of globally successful (un)constrained curvilinear control variables may be a challenging task.

  20. Tadpole-like artificial micromotor

    Science.gov (United States)

    Liu, Limei; Liu, Mei; Su, Yajun; Dong, Yonggang; Zhou, Wei; Zhang, Lina; Zhang, Hui; Dong, Bin; Chi, Lifeng

    2015-01-01

    We describe a polymer-based artificial tadpole-like micromotor, which is fabricated through the electrospinning technique. By incorporating functional materials onto its surface or within its body, the resulting tadpole-like micromotor can not only move autonomously in an aqueous solution with a flexible tail, but also exhibit thermo- and magnetic responsive properties.We describe a polymer-based artificial tadpole-like micromotor, which is fabricated through the electrospinning technique. By incorporating functional materials onto its surface or within its body, the resulting tadpole-like micromotor can not only move autonomously in an aqueous solution with a flexible tail, but also exhibit thermo- and magnetic responsive properties. Electronic supplementary information (ESI) available: Experimental section, Fig. S1-S3 and Video S1-S4. See DOI: 10.1039/c4nr06621a

  1. [Total artificial heart].

    Science.gov (United States)

    Antretter, H; Dumfarth, J; Höfer, D

    2015-09-01

    To date the CardioWest™ total artificial heart is the only clinically available implantable biventricular mechanical replacement for irreversible cardiac failure. This article presents the indications, contraindications, implantation procedere and postoperative treatment. In addition to a overview of the applications of the total artificial heart this article gives a brief presentation of the two patients treated in our department with the CardioWest™. The clinical course, postoperative rehabilitation, device-related complications and control mechanisms are presented. The total artificial heart is a reliable implant for treating critically ill patients with irreversible cardiogenic shock. A bridge to transplantation is feasible with excellent results.

  2. Modelling and analysis of ozone concentration by artificial intelligent techniques for estimating air quality

    Science.gov (United States)

    Taylan, Osman

    2017-02-01

    High ozone concentration is an important cause of air pollution mainly due to its role in the greenhouse gas emission. Ozone is produced by photochemical processes which contain nitrogen oxides and volatile organic compounds in the lower atmospheric level. Therefore, monitoring and controlling the quality of air in the urban environment is very important due to the public health care. However, air quality prediction is a highly complex and non-linear process; usually several attributes have to be considered. Artificial intelligent (AI) techniques can be employed to monitor and evaluate the ozone concentration level. The aim of this study is to develop an Adaptive Neuro-Fuzzy inference approach (ANFIS) to determine the influence of peripheral factors on air quality and pollution which is an arising problem due to ozone level in Jeddah city. The concentration of ozone level was considered as a factor to predict the Air Quality (AQ) under the atmospheric conditions. Using Air Quality Standards of Saudi Arabia, ozone concentration level was modelled by employing certain factors such as; nitrogen oxide (NOx), atmospheric pressure, temperature, and relative humidity. Hence, an ANFIS model was developed to observe the ozone concentration level and the model performance was assessed by testing data obtained from the monitoring stations established by the General Authority of Meteorology and Environment Protection of Kingdom of Saudi Arabia. The outcomes of ANFIS model were re-assessed by fuzzy quality charts using quality specification and control limits based on US-EPA air quality standards. The results of present study show that the ANFIS model is a comprehensive approach for the estimation and assessment of ozone level and is a reliable approach to produce more genuine outcomes.

  3. Stochastic Feedforward Control Technique

    Science.gov (United States)

    Halyo, Nesim

    1990-01-01

    Class of commanded trajectories modeled as stochastic process. Advanced Transport Operating Systems (ATOPS) research and development program conducted by NASA Langley Research Center aimed at developing capabilities for increases in capacities of airports, safe and accurate flight in adverse weather conditions including shear, winds, avoidance of wake vortexes, and reduced consumption of fuel. Advances in techniques for design of modern controls and increased capabilities of digital flight computers coupled with accurate guidance information from Microwave Landing System (MLS). Stochastic feedforward control technique developed within context of ATOPS program.

  4. Analysis of tribological behaviour of zirconia reinforced Al-SiC hybrid composites using statistical and artificial neural network technique

    Science.gov (United States)

    Arif, Sajjad; Tanwir Alam, Md; Ansari, Akhter H.; Bilal Naim Shaikh, Mohd; Arif Siddiqui, M.

    2018-05-01

    The tribological performance of aluminium hybrid composites reinforced with micro SiC (5 wt%) and nano zirconia (0, 3, 6 and 9 wt%) fabricated through powder metallurgy technique were investigated using statistical and artificial neural network (ANN) approach. The influence of zirconia reinforcement, sliding distance and applied load were analyzed with test based on full factorial design of experiments. Analysis of variance (ANOVA) was used to evaluate the percentage contribution of each process parameters on wear loss. ANOVA approach suggested that wear loss be mainly influenced by sliding distance followed by zirconia reinforcement and applied load. Further, a feed forward back propagation neural network was applied on input/output date for predicting and analyzing the wear behaviour of fabricated composite. A very close correlation between experimental and ANN output were achieved by implementing the model. Finally, ANN model was effectively used to find the influence of various control factors on wear behaviour of hybrid composites.

  5. Design techniques for mutlivariable flight control systems

    Science.gov (United States)

    1981-01-01

    Techniques which address the multi-input closely coupled nature of advanced flight control applications and digital implementation issues are described and illustrated through flight control examples. The techniques described seek to exploit the advantages of traditional techniques in treating conventional feedback control design specifications and the simplicity of modern approaches for multivariable control system design.

  6. Random fiber lasers based on artificially controlled backscattering fibers

    Science.gov (United States)

    Chen, Daru; Wang, Xiaoliang; She, Lijuan; Qiang, Zexuan; Yu, Zhangwei

    2017-10-01

    The random fiber laser (RFL) which is a milestone in laser physics and nonlinear optics, has attracted considerable attention recently. Most previous RFLs are based on distributed feedback of Rayleigh scattering amplified through stimulated Raman/Brillouin scattering effect in single mode fibers, which required long-distance (tens of kilometers) single mode fibers and high threshold up to watt-level due to the extremely small Rayleigh scattering coefficient of the fiber. We proposed and demonstrated a half-open cavity RFL based on a segment of a artificially controlled backscattering SMF(ACB-SMF) with a length of 210m, 310m or 390m. A fiber Bragg grating with the central wavelength of 1530nm and a segment of ACB-SMF forms the half-open cavity. The proposed RFL achieves the threshold of 25mW, 30mW and 30mW, respectively. Random lasing at the wavelength of 1530nm and the extinction ratio of 50dB is achieved when a segment of 5m EDF is pumped by a 980nm LD in the RFL. Another half-open cavity RFL based on a segment of a artificially controlled backscattering EDF(ACBS-EDF) is also demonstrated without an ACB-SMF. The 3m ACB-EDF is fabricated by using the femtosecond laser with pulse energy of 0.34mJ which introduces about 50 reflectors in the EDF. Random lasing at the wavelength of 1530nm is achieved with the output power of 7.5mW and the efficiency of 1.88%. Two novel RFLs with much short cavities have been achieved with low threshold and high efficiency.

  7. Artificial recharge of groundwater and its role in water management

    Science.gov (United States)

    Kimrey, J.O.

    1989-01-01

    This paper summarizes and discusses the various aspects and methods of artificial recharge with particular emphasis on its uses and potential role in water management in the Arabian Gulf region. Artificial recharge occurs when man's activities cause more water to enter an aquifer, either under pumping or non-pumping conditions, than otherwise would enter the aquifer. Use of artificial recharge can be a practical means of dealing with problems of overdraft of groundwater. Methods of artificial recharge may be grouped under two broad types: (a) water spreading techniques, and (b) well-injection techniques. Successful use of artificial recharge requires a thorough knowledge of the physical and chemical characteristics of the aquifier system, and extensive onsite experimentation and tailoring of the artificial-recharge technique to fit the local or areal conditions. In general, water spreading techniques are less expensive than well injection and large quantities of water can be handled. Water spreading can also result in significant improvement in quality of recharge waters during infiltration and movement through the unsaturated zone and the receiving aquifer. In comparison, well-injection techniques are often used for emplacement of fresh recharge water into saline aquifer zones to form a manageable lens of fresher water, which may later be partially withdrawn for use or continue to be maintained as a barrier against salt-water encroachment. A major advantage in use of groundwater is its availability, on demand to wells, from a natural storage reservoir that is relatively safe from pollution and from damage by sabotage or other hostile action. However, fresh groundwater occurs only in limited quantities in most of the Arabian Gulf region; also, it is heavily overdrafted in many areas, and receives very little natural recharge. Good use could be made of artificial recharge by well injection in replenishing and managing aquifers in strategic locations if sources of

  8. Tokamak impurity-control techniques

    International Nuclear Information System (INIS)

    Schmidt, J.A.

    1980-01-01

    A brief review is given of the impurity-control functions in tokamaks, their relative merits and disadvantages and some prominent edge-interaction-control techniques, and there is a discussion of a new proposal, the particle scraper, and its potential advantages. (author)

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

    Indian Academy of Sciences (India)

    This study proposes an application of two techniques of artificial intelligence (AI) ... (2006) applied rainfall–runoff modeling using ANN ... in artificial intelligence, engineering and science .... usually be estimated from a sample of observations.

  10. Applications of Electromigration Techniques: Applications of Electromigration Techniques in Food Analysis

    Science.gov (United States)

    Wieczorek, Piotr; Ligor, Magdalena; Buszewski, Bogusław

    Electromigration techniques, including capillary electrophoresis (CE), are widely used for separation and identification of compounds present in food products. These techniques may also be considered as alternate and complementary with respect to commonly used analytical techniques, such as high-performance liquid chromatography (HPLC), or gas chromatography (GC). Applications of CE concern the determination of high-molecular compounds, like polyphenols, including flavonoids, pigments, vitamins, food additives (preservatives, antioxidants, sweeteners, artificial pigments) are presented. Also, the method developed for the determination of proteins and peptides composed of amino acids, which are basic components of food products, are studied. Other substances such as carbohydrates, nucleic acids, biogenic amines, natural toxins, and other contaminations including pesticides and antibiotics are discussed. The possibility of CE application in food control laboratories, where analysis of the composition of food and food products are conducted, is of great importance. CE technique may be used during the control of technological processes in the food industry and for the identification of numerous compounds present in food. Due to the numerous advantages of the CE technique it is successfully used in routine food analysis.

  11. Artificial Cochlear Sensory Epithelium with Functions of Outer Hair Cells Mimicked Using Feedback Electrical Stimuli

    Directory of Open Access Journals (Sweden)

    Tetsuro Tsuji

    2018-05-01

    Full Text Available We report a novel vibration control technique of an artificial auditory cochlear epithelium that mimics the function of outer hair cells in the organ of Corti. The proposed piezoelectric and trapezoidal membrane not only has the acoustic/electric conversion and frequency selectivity of the previous device developed mainly by one of the authors and colleagues, but also has a function to control local vibration according to sound stimuli. Vibration control is achieved by applying local electrical stimuli to patterned electrodes on an epithelium made using micro-electro-mechanical system technology. By choosing appropriate phase differences between sound and electrical stimuli, it is shown that it is possible to both amplify and dampen membrane vibration, realizing better control of the response of the artificial cochlea. To be more specific, amplification and damping are achieved when the phase difference between the membrane vibration by sound stimuli and electrical stimuli is zero and π , respectively. We also demonstrate that the developed control system responds automatically to a change in sound frequency. The proposed technique can be applied to mimic the nonlinear response of the outer hair cells in a cochlea, and to realize a high-quality human auditory system.

  12. Functional electrical stimulation controlled by artificial neural networks: pilot experiments with simple movements are promising for rehabilitation applications.

    Science.gov (United States)

    Ferrante, Simona; Pedrocchi, Alessandra; Iannò, Marco; De Momi, Elena; Ferrarin, Maurizio; Ferrigno, Giancarlo

    2004-01-01

    This study falls within the ambit of research on functional electrical stimulation for the design of rehabilitation training for spinal cord injured patients. In this context, a crucial issue is the control of the stimulation parameters in order to optimize the patterns of muscle activation and to increase the duration of the exercises. An adaptive control system (NEURADAPT) based on artificial neural networks (ANNs) was developed to control the knee joint in accordance with desired trajectories by stimulating quadriceps muscles. This strategy includes an inverse neural model of the stimulated limb in the feedforward line and a neural network trained on-line in the feedback loop. NEURADAPT was compared with a linear closed-loop proportional integrative derivative (PID) controller and with a model-based neural controller (NEUROPID). Experiments on two subjects (one healthy and one paraplegic) show the good performance of NEURADAPT, which is able to reduce the time lag introduced by the PID controller. In addition, control systems based on ANN techniques do not require complicated calibration procedures at the beginning of each experimental session. After the initial learning phase, the ANN, thanks to its generalization capacity, is able to cope with a certain range of variability of skeletal muscle properties.

  13. Artificial intelligence applications in offshore oil and gas production

    International Nuclear Information System (INIS)

    Attia, F.G.

    1994-01-01

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

  14. Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data

    Science.gov (United States)

    Jothiprakash, V.; Magar, R. B.

    2012-07-01

    SummaryIn this study, artificial intelligent (AI) techniques such as artificial neural network (ANN), Adaptive neuro-fuzzy inference system (ANFIS) and Linear genetic programming (LGP) are used to predict daily and hourly multi-time-step ahead intermittent reservoir inflow. To illustrate the applicability of AI techniques, intermittent Koyna river watershed in Maharashtra, India is chosen as a case study. Based on the observed daily and hourly rainfall and reservoir inflow various types of time-series, cause-effect and combined models are developed with lumped and distributed input data. Further, the model performance was evaluated using various performance criteria. From the results, it is found that the performances of LGP models are found to be superior to ANN and ANFIS models especially in predicting the peak inflows for both daily and hourly time-step. A detailed comparison of the overall performance indicated that the combined input model (combination of rainfall and inflow) performed better in both lumped and distributed input data modelling. It was observed that the lumped input data models performed slightly better because; apart from reducing the noise in the data, the better techniques and their training approach, appropriate selection of network architecture, required inputs, and also training-testing ratios of the data set. The slight poor performance of distributed data is due to large variations and lesser number of observed values.

  15. Design and motion control of bioinspired humanoid robot head from servo motors toward artificial muscles

    Science.gov (United States)

    Almubarak, Yara; Tadesse, Yonas

    2017-04-01

    The potential applications of humanoid robots in social environments, motivates researchers to design, and control biomimetic humanoid robots. Generally, people are more interested to interact with robots that have similar attributes and movements to humans. The head is one of most important part of any social robot. Currently, most humanoid heads use electrical motors, pneumatic actuators, and shape memory alloy (SMA) actuators for actuation. Electrical and pneumatic actuators take most of the space and would cause unsmooth motions. SMAs are expensive to use in humanoids. Recently, in many robotic projects, Twisted and Coiled Polymer (TCP) artificial muscles are used as linear actuators which take up little space compared to the motors. In this paper, we will demonstrate the designing process and motion control of a robotic head with TCP muscles. Servo motors and artificial muscles are used for actuating the head motion, which have been controlled by a cost efficient ARM Cortex-M7 based development board. A complete comparison between the two actuators is presented.

  16. Readings in artificial intelligence and software engineering

    CERN Document Server

    Rich, Charles

    1986-01-01

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

  17. Artificial Intelligence Techniques Applications for Power Disturbances Classification

    OpenAIRE

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

    2008-01-01

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

  18. Volume fraction prediction in biphasic flow using nuclear technique and artificial neural network

    International Nuclear Information System (INIS)

    Salgado, Cesar M.; Brandao, Luis E.B.

    2015-01-01

    The volume fraction is one of the most important parameters used to characterize air-liquid two-phase flows. It is a physical value to determine other parameters, such as the phase's densities and to determine the flow rate of each phase. These parameters are important to predict the flow pattern and to determine a mathematical model for the system. To study, for example, heat transfer and pressure drop. This work presents a methodology for volume fractions prediction in water-gas stratified flow regime using the nuclear technique and artificial intelligence. The volume fractions calculate in biphasic flow systems is complex and the analysis by means of analytical equations becomes very difficult. The approach is based on gamma-ray pulse height distributions pattern recognition by means of the artificial neural network. The detection system uses appropriate broad beam geometry, comprised of a ( 137 Cs) energy gamma-ray source and a NaI(Tl) scintillation detector in order measure transmitted beam whose the counts rates are influenced by the phases composition. These distributions are directly used by the network without any parameterization of the measured signal. The ideal and static theoretical models for stratified regime have been developed using MCNP-X code, which was used to provide training, test and validation data for the network. The detector also was modeled with this code and the results were compared to experimental photopeak efficiency measurements of radiation sources. The proposed network could obtain with satisfactory prediction of the volume fraction in water-gas system, demonstrating to be a promising approach for this purpose. (author)

  19. Volume fraction prediction in biphasic flow using nuclear technique and artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Salgado, Cesar M.; Brandao, Luis E.B., E-mail: otero@ien.gov.br, E-mail: brandao@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil)

    2015-07-01

    The volume fraction is one of the most important parameters used to characterize air-liquid two-phase flows. It is a physical value to determine other parameters, such as the phase's densities and to determine the flow rate of each phase. These parameters are important to predict the flow pattern and to determine a mathematical model for the system. To study, for example, heat transfer and pressure drop. This work presents a methodology for volume fractions prediction in water-gas stratified flow regime using the nuclear technique and artificial intelligence. The volume fractions calculate in biphasic flow systems is complex and the analysis by means of analytical equations becomes very difficult. The approach is based on gamma-ray pulse height distributions pattern recognition by means of the artificial neural network. The detection system uses appropriate broad beam geometry, comprised of a ({sup 137}Cs) energy gamma-ray source and a NaI(Tl) scintillation detector in order measure transmitted beam whose the counts rates are influenced by the phases composition. These distributions are directly used by the network without any parameterization of the measured signal. The ideal and static theoretical models for stratified regime have been developed using MCNP-X code, which was used to provide training, test and validation data for the network. The detector also was modeled with this code and the results were compared to experimental photopeak efficiency measurements of radiation sources. The proposed network could obtain with satisfactory prediction of the volume fraction in water-gas system, demonstrating to be a promising approach for this purpose. (author)

  20. DEVELOPING A HUMAN CONTROLLED MODEL FOR SAFE ARTIFICIAL INTELLIGENCE SYSTEMS

    OpenAIRE

    KÖSE, Utku

    2018-01-01

    Artificial Intelligence is known as one of the most effective research field of nowadays and the future. But rapid rise of Artificial Intelligence and its potential to solve all real world problems autonomously, it has caused also several anxieties. Some scientists think that intelligent systems can reach to a level, which is dangerous for the humankind so because of that some precautions should be taken. So, many sub-research fields like Machine Ethics or Artificial Intelligence Safety have ...

  1. Process sensors characterization based on noise analysis technique and artificial intelligence

    International Nuclear Information System (INIS)

    Mesquita, Roberto N. de; Perillo, Sergio R.P.; Santos, Roberto C. dos

    2005-01-01

    The time response of pressure and temperature sensors from the Reactor Protection System (RPS) is a requirement that must be satisfied in nuclear power plants, furthermore is an indicative of its degradation and its remaining life. The nuclear power industry and others have been eager to implement smart sensor technologies and digital instrumentation concepts to reduce manpower and effort currently spent on testing and calibration. Process parameters fluctuations during normal operation of a reactor are caused by random variations in neutron flux, heat transfer and other sources. The output sensor noise can be considered as the response of the system to an input representing the statistical nature of the underlying process which can be modeled using a time series model. Since the noise signal measurements are influenced by many factors, such as location of sensors, extraneous noise interference, and randomness in temperature and pressure fluctuation - the quantitative estimate of the time response using autoregressive noise modeling is subject to error. This technique has been used as means of sensor monitoring. In this work a set of pressure sensors installed in one experimental loop adapted from a flow calibration setup is used to test and analyze signals in a new approach using artificial intelligence techniques. A set of measurements of dynamic signals in different experimental conditions is used to distinguish and identify underlying process sources. A methodology that uses Blind Separation of Sources with a neural networks scheme is being developed to improve time response estimate reliability in noise analysis. (author)

  2. Process sensors characterization based on noise analysis technique and artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Mesquita, Roberto N. de; Perillo, Sergio R.P.; Santos, Roberto C. dos [Instituto de Pesquisas Energeticas e Nucleares (IPEN), Sao Paulo, SP (Brazil)]. E-mail: rnavarro@ipen.br; sperillo@ipen.br; rcsantos@ipen.br

    2005-07-01

    The time response of pressure and temperature sensors from the Reactor Protection System (RPS) is a requirement that must be satisfied in nuclear power plants, furthermore is an indicative of its degradation and its remaining life. The nuclear power industry and others have been eager to implement smart sensor technologies and digital instrumentation concepts to reduce manpower and effort currently spent on testing and calibration. Process parameters fluctuations during normal operation of a reactor are caused by random variations in neutron flux, heat transfer and other sources. The output sensor noise can be considered as the response of the system to an input representing the statistical nature of the underlying process which can be modeled using a time series model. Since the noise signal measurements are influenced by many factors, such as location of sensors, extraneous noise interference, and randomness in temperature and pressure fluctuation - the quantitative estimate of the time response using autoregressive noise modeling is subject to error. This technique has been used as means of sensor monitoring. In this work a set of pressure sensors installed in one experimental loop adapted from a flow calibration setup is used to test and analyze signals in a new approach using artificial intelligence techniques. A set of measurements of dynamic signals in different experimental conditions is used to distinguish and identify underlying process sources. A methodology that uses Blind Separation of Sources with a neural networks scheme is being developed to improve time response estimate reliability in noise analysis. (author)

  3. Use of Nuclear Techniques in Biological Control: Managing Pests, Facilitating Trade and Protecting the Environment. Report of a Consultants Group Meeting. Working Material

    International Nuclear Information System (INIS)

    1999-01-01

    High-priority opportunities are proposed for use of nuclear techniques to effect improved production and shipping of augmentative biological control agents. Proposed subprojects include use of ionizing radiation to improve the production of insect natural enemies on natural hosts/prey or on artificial diets. Other subprojects pertain to improving the ability to move beneficial organisms in international trade, and in using them in the field. Additional high priority activities were identified proposing use of nuclear techniques to produce sterile and/or substerile F-1 weed biological control agents to help evaluate potential impact on non-target species in the pre-release phase, integration of augmentative releases and F-1 sterility in IPM and area-wide pest management programmes, and utilization of by-products from SIT mass-rearing facilities in augmentative biological control programmes. (author)

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

    International Nuclear Information System (INIS)

    Kimura, Yoshitaka; Hasegawa, Keisuke; Ikezawa, Yoshio

    1990-01-01

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

  5. Formation and evaluation of artificial patinas over copper

    International Nuclear Information System (INIS)

    Rosales, B.M.; Moriena, G.

    1998-01-01

    The unprecise characteristic of the environmental parameters determines passive variable properties in the formed corrosion products out in the open. They were required at least three years by essaying in the atmospheres where the patina is naturally formed for a long term information disposition about its protector power, its stabilization velocity and its attack morphology suffered by the metal. In patinas formed in laboratory on the contrary, to get morphology and a defined chemical composition, allowing its accelerated formation and an uniform attack, with a reproducible and controllable metal corrosion velocity. The protective properties of the patinas formed on copper as like artificial way (blue, green, violet, and maroon) as natural way out in the open which were evaluated by means of different characterization techniques. It was applied potential kinetics polarizations, scanning electron microscopy (Sem) and surface analysis EDAX. The corrosion products composition was determined by X-ray diffraction and W spectroscopy. Starting from obtained results through different techniques it was concluded that the green patinas, as artificial as the naturally formed, as well as those of the best protector power. the others three ones present different failures as less adherence, high porosity and basic metal exfoliation. (Author)

  6. Enabling Autonomous Space Mission Operations with Artificial Intelligence

    Science.gov (United States)

    Frank, Jeremy

    2017-01-01

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

  7. Implanted artificial heart with radioisotope power source

    Energy Technology Data Exchange (ETDEWEB)

    Shumakov, V I; Griaznov, G M; Zhemchuzhnikov, G N; Kiselev, I M; Osipov, A P

    1983-02-01

    An atomic artificial heart for orthotopic implantation was developed with the following characteristics: volume, 1.2 L; weight, 1.5 kg; radioisotope power, 45 W; operating life, up to 5 years; hemodynamics, similar to natural hemodynamics. The artificial heart includes a thermal drive with systems for regulating power, feeding steam into the cylinders, return of the condensate to the steam generator, and delivery of power to the ventricles and heat container. The artificial heart is placed in an artificial pericardium partially filled with physiologic solution. It uses a steam engine with two operating cylinders that separately drive the left and right ventricles. There is no electronic control system in the proposed design. The operation of the heat engine is controlled, with preservation of autoregulation by the vascular system of the body. The separate drives for the ventricles is of primary importance as it provides for operation of the artificial heart through control of cardiac activity by venous return. Experimental testing on a hydromechanical bench demonstrated effective autoregulation.

  8. The influence of artificially increased hip and trunk stiffness on balance control in man.

    NARCIS (Netherlands)

    Grüneberg, C.; Bloem, B.R.; Honegger, F.; Allum, J.H.J.

    2004-01-01

    Lightweight corsets were used to produce mid-body stiffening, rendering the hip and trunk joints practically inflexible. To examine the effect of this artificially increased stiffness on balance control, we perturbed the upright stance of young subjects (20-34 years of age) while they wore one of

  9. Artificial Reefs

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — An artificial reef is a human-made underwater structure, typically built to promote marine life in areas with a generally featureless bottom, control erosion, block...

  10. Silica artificial opal incorporated with silver nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Li Wenjiang, E-mail: wjli@zju.edu.cn [Center for Optical and Electromagnetic Research, State Key Laboratory for Modern Optical Instrumentation, Zhejiang University, Joint Research Center of Photonics of the Royal Institute of Technology and Zhejiang University, Zijingang Campus, Room 210, East Building 5, Hangzhou 310058 (China); Sun Tan [Center for Optical and Electromagnetic Research, State Key Laboratory for Modern Optical Instrumentation, Zhejiang University, Joint Research Center of Photonics of the Royal Institute of Technology and Zhejiang University, Zijingang Campus, Room 210, East Building 5, Hangzhou 310058 (China)

    2009-07-15

    The silica artificial opal with a three-dimensional (3D) periodic structure was prepared using highly monodispersed silica microspheres by a force packing method in ITO glass cell. The silica artificial opal incorporated with silver nanoparticles was fabricated by the electroplating technique. The optical microscope images of the synthetic sample and the corresponding optical properties were measured after each treatment of electroplating-washing-drying circle. The transmission and reflection spectra presented a red shift, showing that the effective refractive index of the complex silver/silica opal increased after each electroplating. Combining the SEM images, it was seen that the silver nanoparticles could be directly deposited on the surface of silica spheres in the opaline structure. The silver/silica complex opal film could provide a simple way to tune the opal properties by controlling silver nanoparticles in the silica opal. The silver/silica opal crystal structures could be used for nano-photonic circuits, white-light LEDs or as photocatalysts.

  11. Silica artificial opal incorporated with silver nanoparticles

    International Nuclear Information System (INIS)

    Li Wenjiang; Sun Tan

    2009-01-01

    The silica artificial opal with a three-dimensional (3D) periodic structure was prepared using highly monodispersed silica microspheres by a force packing method in ITO glass cell. The silica artificial opal incorporated with silver nanoparticles was fabricated by the electroplating technique. The optical microscope images of the synthetic sample and the corresponding optical properties were measured after each treatment of electroplating-washing-drying circle. The transmission and reflection spectra presented a red shift, showing that the effective refractive index of the complex silver/silica opal increased after each electroplating. Combining the SEM images, it was seen that the silver nanoparticles could be directly deposited on the surface of silica spheres in the opaline structure. The silver/silica complex opal film could provide a simple way to tune the opal properties by controlling silver nanoparticles in the silica opal. The silver/silica opal crystal structures could be used for nano-photonic circuits, white-light LEDs or as photocatalysts.

  12. Practical controller design for ultra-precision positioning of stages with a pneumatic artificial muscle actuator

    Science.gov (United States)

    Tang, T. F.; Chong, S. H.

    2017-06-01

    This paper presents a practical controller design method for ultra-precision positioning of pneumatic artificial muscle actuator stages. Pneumatic artificial muscle (PAM) actuators are safe to use and have numerous advantages which have brought these actuators to wide applications. However, PAM exhibits strong non-linear characteristics, and these limitations lead to low controllability and limit its application. In practice, the non-linear characteristics of PAM mechanism are difficult to be precisely modeled, and time consuming to model them accurately. The purpose of the present study is to clarify a practical controller design method that emphasizes a simple design procedure that does not acquire plants parameters modeling, and yet is able to demonstrate ultra-precision positioning performance for a PAM driven stage. The practical control approach adopts continuous motion nominal characteristic trajectory following (CM NCTF) control as the feedback controller. The constructed PAM driven stage is in low damping characteristic and causes severe residual vibration that deteriorates motion accuracy of the system. Therefore, the idea to increase the damping characteristic by having an acceleration feedback compensation to the plant has been proposed. The effectiveness of the proposed controller was verified experimentally and compared with a classical PI controller in point-to-point motion. The experiment results proved that the CM NCTF controller demonstrates better positioning performance in smaller motion error than the PI controller. Overall, the CM NCTF controller has successfully to reduce motion error to 3µm, which is 88.7% smaller than the PI controller.

  13. Artificial Bone and Teeth through Controlled Ice Growth in Colloidal Suspensions

    International Nuclear Information System (INIS)

    Tomsia, Antoni P.; Saiz, Eduardo; Deville, Sylvain

    2007-01-01

    The formation of regular patterns is a common feature of many solidification processes involving cast materials. We describe here how regular patterns can be obtained in porous alumina and hydroxyapatite (HAP) by controlling the freezing of ceramic slurries followed by subsequent ice sublimation and sintering, leading to multilayered porous ceramic structures with homogeneous and well-defined architecture. These porous materials can be infiltrated with a second phase of choice to yield biomimetic nacre-like composites with improved mechanical properties, which could be used for artificial bone and teeth applications. Proper control of the solidification patterns provides powerful means of control over the final functional properties. We discuss the relationships between the experimental results, ice growth fundamentals, the physics of ice and the interaction between inert particles and the solidification front during directional freezing

  14. Control of an automated mobile manipulator using artificial immune system

    Science.gov (United States)

    Deepak, B. B. V. L.; Parhi, Dayal R.

    2016-03-01

    This paper addresses the coordination and control of a wheeled mobile manipulator (WMM) using artificial immune system. The aim of the developed methodology is to navigate the system autonomously and transport jobs and tools in manufacturing environments. This study integrates the kinematic structures of a four-axis manipulator and a differential wheeled mobile platform. The motion of the developed WMM is controlled by the complete system of parametric equation in terms of joint velocities and makes the robot to follow desired trajectories by the manipulator and platform within its workspace. The developed robot system performs its action intelligently according to the sensed environmental criteria within its search space. To verify the effectiveness of the proposed immune-based motion planner for WMM, simulations as well as experimental results are presented in various unknown environments.

  15. Technique of nuclear reactors controls; Technique des controles des reacteurs nucleaires

    Energy Technology Data Exchange (ETDEWEB)

    Weill, J [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1953-12-15

    This report deal about 'Techniques of control of the nuclear reactors' in the goal to achieve the control of natural uranium reactors and especially the one of Saclay. This work is mainly about the measurement into nuclear parameters and go further in the measurement of thermodynamic variables,etc... putting in relief the new features required on behalf of the detectors because of their use in the thermal neutrons flux. In the domain of nuclear measurement, we indicate the realizations and the results obtained with thermal neutron detectors and for the measurement of ionizations currents. We also treat the technical problem of the start-up of a reactor and of the reactivity measurement. We give the necessary details for the comprehension of all essential diagrams and plans put on, in particular, for the reactor of Saclay. (author) [French] Nous avons aborde le probleme de la ''Technique du Controle des reacteurs nucleaires'' dans le but de realiser le controle du reacteur de Saclay. C'est ainsi que nous avons ete amene a etudier le probleme dans son ensemble, tel qu'il se pose pour tout reacteur a uranium naturel. Ce travail traite principalement du domaine des mesures a caractere nucleaire et s'etend dans le domaine des mesures thermodynamque de niveaux, etc... mettant en relief les caracteristiques nouvelles exigees de la part des detecteurs du fait de leur utilisation dans le flux de neutrons thermiques. Dans le domaine de mesures nucleaires, nous indiquons principalement les realisations et les resultats obtenus pour les detecteurs de neutrons thermiques et pour la mesure de courants d'ionisations. Nous traitons egalement du probleme technique du demarrage d'un reacteur et du probleme de la mesure de la reactivite. Nous donnons les details necessaires a la comrehension de tous les schemas et plans de cablages essentiels mis au point, en particulier, pour le reacteur de Saclay. (auteur)

  16. Medical applications of artificial intelligence

    CERN Document Server

    Agah, Arvin

    2013-01-01

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

  17. Exploring Artificial Intelligence Utilizing BioArt

    OpenAIRE

    Simou , Panagiota; Tiligadis , Konstantinos; Alexiou , Athanasios

    2013-01-01

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

  18. Artificial intelligence and process management

    International Nuclear Information System (INIS)

    Epton, J.B.A.

    1989-01-01

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

  19. Human factors issues in the use of artificial intelligence in air traffic control. October 1990 Workshop

    Science.gov (United States)

    Hockaday, Stephen; Kuhlenschmidt, Sharon (Editor)

    1991-01-01

    The objective of the workshop was to explore the role of human factors in facilitating the introduction of artificial intelligence (AI) to advanced air traffic control (ATC) automation concepts. AI is an umbrella term which is continually expanding to cover a variety of techniques where machines are performing actions taken based upon dynamic, external stimuli. AI methods can be implemented using more traditional programming languages such as LISP or PROLOG, or they can be implemented using state-of-the-art techniques such as object-oriented programming, neural nets (hardware or software), and knowledge based expert systems. As this technology advances and as increasingly powerful computing platforms become available, the use of AI to enhance ATC systems can be realized. Substantial efforts along these lines are already being undertaken at the FAA Technical Center, NASA Ames Research Center, academic institutions, industry, and elsewhere. Although it is clear that the technology is ripe for bringing computer automation to ATC systems, the proper scope and role of automation are not at all apparent. The major concern is how to combine human controllers with computer technology. A wide spectrum of options exists, ranging from using automation only to provide extra tools to augment decision making by human controllers to turning over moment-by-moment control to automated systems and using humans as supervisors and system managers. Across this spectrum, it is now obvious that the difficulties that occur when tying human and automated systems together must be resolved so that automation can be introduced safely and effectively. The focus of the workshop was to further explore the role of injecting AI into ATC systems and to identify the human factors that need to be considered for successful application of the technology to present and future ATC systems.

  20. Integrated approach to model decomposed flow hydrograph using artificial neural network and conceptual techniques

    Science.gov (United States)

    Jain, Ashu; Srinivasulu, Sanaga

    2006-02-01

    This paper presents the findings of a study aimed at decomposing a flow hydrograph into different segments based on physical concepts in a catchment, and modelling different segments using different technique viz. conceptual and artificial neural networks (ANNs). An integrated modelling framework is proposed capable of modelling infiltration, base flow, evapotranspiration, soil moisture accounting, and certain segments of the decomposed flow hydrograph using conceptual techniques and the complex, non-linear, and dynamic rainfall-runoff process using ANN technique. Specifically, five different multi-layer perceptron (MLP) and two self-organizing map (SOM) models have been developed. The rainfall and streamflow data derived from the Kentucky River catchment were employed to test the proposed methodology and develop all the models. The performance of all the models was evaluated using seven different standard statistical measures. The results obtained in this study indicate that (a) the rainfall-runoff relationship in a large catchment consists of at least three or four different mappings corresponding to different dynamics of the underlying physical processes, (b) an integrated approach that models the different segments of the decomposed flow hydrograph using different techniques is better than a single ANN in modelling the complex, dynamic, non-linear, and fragmented rainfall runoff process, (c) a simple model based on the concept of flow recession is better than an ANN to model the falling limb of a flow hydrograph, and (d) decomposing a flow hydrograph into the different segments corresponding to the different dynamics based on the physical concepts is better than using the soft decomposition employed using SOM.

  1. Microsoft kinect-based artificial perception system for control of functional electrical stimulation assisted grasping.

    Science.gov (United States)

    Strbac, Matija; Kočović, Slobodan; Marković, Marko; Popović, Dejan B

    2014-01-01

    We present a computer vision algorithm that incorporates a heuristic model which mimics a biological control system for the estimation of control signals used in functional electrical stimulation (FES) assisted grasping. The developed processing software acquires the data from Microsoft Kinect camera and implements real-time hand tracking and object analysis. This information can be used to identify temporal synchrony and spatial synergies modalities for FES control. Therefore, the algorithm acts as artificial perception which mimics human visual perception by identifying the position and shape of the object with respect to the position of the hand in real time during the planning phase of the grasp. This artificial perception used within the heuristically developed model allows selection of the appropriate grasp and prehension. The experiments demonstrate that correct grasp modality was selected in more than 90% of tested scenarios/objects. The system is portable, and the components are low in cost and robust; hence, it can be used for the FES in clinical or even home environment. The main application of the system is envisioned for functional electrical therapy, that is, intensive exercise assisted with FES.

  2. Development of a technique for level measurement in pressure vessels using thermal probes and artificial neural networks

    International Nuclear Information System (INIS)

    Torres, Walmir Maximo

    2008-01-01

    A technique for level measurement in pressure vessels was developed using thermal probes with internal cooling and artificial neural networks (ANN's). This new concept of thermal probes was experimentally tested in an experimental facility (BETSNI) with two test sections, ST1 and ST2. Two different thermal probes were designed and constructed: concentric tubes probe and U tube probe. A data acquisition system (DAS) was assembled to record the experimental data during the tests. Steady state and transient level tests were carried out and the experimental data obtained were used as learning and recall data sets in the ANN's program RETRO-05 that simulate a multilayer perceptron with backpropagation. The results of the analysis show that the technique can be applied for level measurements in pressure vessel. The technique is applied for a less input temperature data than the initially designed to the probes. The technique is robust and can be used in case of lack of some temperature data. Experimental data available in literature from electrically heated thermal probe were also used in the ANN's analysis producing good results. The results of the ANN's analysis show that the technique can be improved and applied to level measurements in pressure vessels. (author)

  3. ARTIFICIAL INTELLIGENCE PLANNING TECHNIQUES FOR ADAPTIVE VIRTUAL COURSE CONSTRUCTION

    Directory of Open Access Journals (Sweden)

    NÉSTOR DARÍO DUQUE

    2011-01-01

    Full Text Available El artículo tiene como objetivo proponer un modelo de planificación para la adaptación de cursos virtuales, basado en técnicas de inteligencia artificial, en particular usando el enfoque de sistema multi-agente (SMA y métodos de planificación en inteligencia artificial. El diseño y la implementación por medio de un SMA pedagógico y la definición de un framework para especificar la estrategia de adaptación permiten incorporar diversos enfoques pedagógicos y tecnológicos, de acuerdo a los puntos de vista del equipo de trabajo, lo cual resulta en una implementación e instalación concreta. Se incorpora un novedoso pre-planificador que permite la transparencia y la neutralidad en el modelo propuesto y también ofrece soporte para traducir los elementos del curso a las especificaciones de un problema de planificación. La última sección muestra la plataforma experimental SICAD + (Sistema Inteligente de Cursos ADaptativos, a través de un enfoque multiagente, que valida el modelo propuesto.

  4. Bio-inspired online variable recruitment control of fluidic artificial muscles

    Science.gov (United States)

    Jenkins, Tyler E.; Chapman, Edward M.; Bryant, Matthew

    2016-12-01

    This paper details the creation of a hybrid variable recruitment control scheme for fluidic artificial muscle (FAM) actuators with an emphasis on maximizing system efficiency and switching control performance. Variable recruitment is the process of altering a system’s active number of actuators, allowing operation in distinct force regimes. Previously, FAM variable recruitment was only quantified with offline, manual valve switching; this study addresses the creation and characterization of novel, on-line FAM switching control algorithms. The bio-inspired algorithms are implemented in conjunction with a PID and model-based controller, and applied to a simulated plant model. Variable recruitment transition effects and chatter rejection are explored via a sensitivity analysis, allowing a system designer to weigh tradeoffs in actuator modeling, algorithm choice, and necessary hardware. Variable recruitment is further developed through simulation of a robotic arm tracking a variety of spline position inputs, requiring several levels of actuator recruitment. Switching controller performance is quantified and compared with baseline systems lacking variable recruitment. The work extends current variable recruitment knowledge by creating novel online variable recruitment control schemes, and exploring how online actuator recruitment affects system efficiency and control performance. Key topics associated with implementing a variable recruitment scheme, including the effects of modeling inaccuracies, hardware considerations, and switching transition concerns are also addressed.

  5. Measurement of lung tissue dynamics in artificially ventilated rats with optical coherence tomography

    Directory of Open Access Journals (Sweden)

    Schnabel Christian

    2017-09-01

    Full Text Available Diseases of lung tissue and the airways become a major task for medical care and health care systems in modern industrial countries in the future. Suitable treatment methods and strategies for lung support and artificial ventilation are of dare need. Besides the obvious importance as life-saving intervention, the effects of usually used over-pressure ventilation onto the sensitive alveolar tissue are insufficiently understood. Therefore, it is of great interest to characterize lung tissue during artificial ventilation at the alveolar level. Those measurements can be used to link micromechanics of alveolar structures to mechanical properties of the whole lung like compliance and resistance measured at the ventilator device. This can be done only in animal experiments due to the fact that imaging techniques used in human diagnostics like CT or MRT fail to resolve alveolar tissue structures. The disadvantage of high-resolution techniques like optical coherence tomography (OCT or intravital microscopy (IVM is the need of a surgical access to the lung due to the limitation in penetration depth of these techniques. Furthermore, imaging dynamic processes with high-resolution imaging techniques during uninterrupted artificial ventilation is a challenging task. In this study, we present a measurement setup for combined imaging of conventional pressure-controlled ventilated rats and the visualization of volume changes of alveolar structures during one cycle of breath. A custom-made OCT system in combination with a triggered scanning algorithm was used to acquire time-resolved 3D OCT image data. Furthermore, this system was combined with a self-adapting autofocus function for intravital microscopy to track the lung surface keeping the tissue in focal plane. The combination of new dynamic measurement modes for OCT and IVM allows new insights into alveolar tissue and will promote the understanding of mechanical behavior during artificial ventilation.

  6. Third-Order Spectral Techniques for the Diagnosis of Motor Bearing Condition Using Artificial Neural Networks

    Science.gov (United States)

    Yang, D.-M.; Stronach, A. F.; MacConnell, P.; Penman, J.

    2002-03-01

    This paper addresses the development of a novel condition monitoring procedure for rolling element bearings which involves a combination of signal processing, signal analysis and artificial intelligence methods. Seven approaches based on power spectrum, bispectral and bicoherence vibration analyses are investigated as signal pre-processing techniques for application in the diagnosis of a number of induction motor rolling element bearing conditions. The bearing conditions considered are a normal bearing and bearings with cage and inner and outer race faults. The vibration analysis methods investigated are based on the power spectrum, the bispectrum, the bicoherence, the bispectrum diagonal slice, the bicoherence diagonal slice, the summed bispectrum and the summed bicoherence. Selected features are extracted from the vibration signatures so obtained and these are used as inputs to an artificial neural network trained to identify the bearing conditions. Quadratic phase coupling (QPC), examined using the magnitude of bispectrum and bicoherence and biphase, is shown to be absent from the bearing system and it is therefore concluded that the structure of the bearing vibration signatures results from inter-modulation effects. In order to test the proposed procedure, experimental data from a bearing test rig are used to develop an example diagnostic system. Results show that the bearing conditions examined can be diagnosed with a high success rate, particularly when using the summed bispectrum signatures.

  7. Artificial neural network applications in ionospheric studies

    Directory of Open Access Journals (Sweden)

    L. R. Cander

    1998-06-01

    Full Text Available The ionosphere of Earth exhibits considerable spatial changes and has large temporal variability of various timescales related to the mechanisms of creation, decay and transport of space ionospheric plasma. Many techniques for modelling electron density profiles through entire ionosphere have been developed in order to solve the "age-old problem" of ionospheric physics which has not yet been fully solved. A new way to address this problem is by applying artificial intelligence methodologies to current large amounts of solar-terrestrial and ionospheric data. It is the aim of this paper to show by the most recent examples that modern development of numerical models for ionospheric monthly median long-term prediction and daily hourly short-term forecasting may proceed successfully applying the artificial neural networks. The performance of these techniques is illustrated with different artificial neural networks developed to model and predict the temporal and spatial variations of ionospheric critical frequency, f0F2 and Total Electron Content (TEC. Comparisons between results obtained by the proposed approaches and measured f0F2 and TEC data provide prospects for future applications of the artificial neural networks in ionospheric studies.

  8. Prediction of Monthly Summer Monsoon Rainfall Using Global Climate Models Through Artificial Neural Network Technique

    Science.gov (United States)

    Nair, Archana; Singh, Gurjeet; Mohanty, U. C.

    2018-01-01

    The monthly prediction of summer monsoon rainfall is very challenging because of its complex and chaotic nature. In this study, a non-linear technique known as Artificial Neural Network (ANN) has been employed on the outputs of Global Climate Models (GCMs) to bring out the vagaries inherent in monthly rainfall prediction. The GCMs that are considered in the study are from the International Research Institute (IRI) (2-tier CCM3v6) and the National Centre for Environmental Prediction (Coupled-CFSv2). The ANN technique is applied on different ensemble members of the individual GCMs to obtain monthly scale prediction over India as a whole and over its spatial grid points. In the present study, a double-cross-validation and simple randomization technique was used to avoid the over-fitting during training process of the ANN model. The performance of the ANN-predicted rainfall from GCMs is judged by analysing the absolute error, box plots, percentile and difference in linear error in probability space. Results suggest that there is significant improvement in prediction skill of these GCMs after applying the ANN technique. The performance analysis reveals that the ANN model is able to capture the year to year variations in monsoon months with fairly good accuracy in extreme years as well. ANN model is also able to simulate the correct signs of rainfall anomalies over different spatial points of the Indian domain.

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

    Science.gov (United States)

    1989-03-01

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

  10. Status and headway of the clinical application of artificial ligaments

    Directory of Open Access Journals (Sweden)

    Tianwu Chen

    2015-01-01

    Full Text Available The authors first reviewed the history of clinical application of artificial ligaments. Then, the status of clinical application of artificial ligaments was detailed. Some artificial ligaments possessed comparable efficacy to, and fewer postoperative complications than, allografts and autografts in ligament reconstruction, especially for the anterior cruciate ligament. At the end, the authors focused on the development of two types of artificial ligaments: polyethylene glycol terephthalate artificial ligaments and tissue-engineered ligaments. In conclusion, owing to the advancements in surgical techniques, materials processing, and weaving methods, clinical application of some artificial ligaments so far has demonstrated good outcomes and will become a trend in the future.

  11. Intelligent Lighting Control System

    OpenAIRE

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

    2014-01-01

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

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

    Science.gov (United States)

    McManus, John W.; Goodrich, Kenneth H.

    1989-01-01

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

  13. Artificial perches as a nucleation technique for restoration of a riparian environment: characterization of the seed rain and of natural regeneration

    Directory of Open Access Journals (Sweden)

    Aline Luiza Tomazi

    2010-09-01

    Full Text Available Riparian habitats are important to the maintenance of ecological processes and environmental services. However, a significant portion of the riparian vegetation in the Brazilian Atlantic forest has been removed in response to increasing human pressure. Therefore, the application of restoration techniques in these habitats becomes essential. In this context, a nucleation model with 18 artificial perches was evaluated for the restoration of a degraded riparian area in Gaspar, Santa Catarina, Brazil, by the characterization of the seed rain and natural regeneration. In two years we collected 21,864 seeds of 51 morphospecies, and recorded 42 colonizing species. Zoochoric seeds belonging to 15 plant families comprised 17% of the seed rain and 19.05% of the spontaneously regenerating plant species. Asteraceae and Poaceae were the most represented families. The artificial perches performed the nucleating function through the increase of zoochoric seed rain. However, possibly due to different barriers that were not evaluated in this study, part of these seeds was not recruited. We recommend the application of this technique for the attraction of dispersers in degraded areas similar to the study site.

  14. Artificial perches as a nucleation technique for restoration of a riparian environment: characterization of the seed rain and of natural regeneration.

    Directory of Open Access Journals (Sweden)

    Aline Luiza Tomazi

    2010-01-01

    Full Text Available Riparian habitats are important to the maintenance of ecological processes and environmental services. However, a significant portion of the riparian vegetation in the Brazilian Atlantic forest has been removed in response to increasing human pressure. Therefore, the application of restoration techniques in these habitats becomes essential. In this context, a nucleation model with 18 artificial perches was evaluated for the restoration of a degraded riparian area in Gaspar, Santa Catarina, Brazil, by the characterization of the seed rain and natural regeneration. In two years we collected 21,864 seeds of 51 morphospecies, and recorded 42 colonizing species. Zoochoric seeds belonging to 15 plant families comprised 17% of the seed rain and 19.05% of the spontaneously regenerating plant species. Asteraceae and Poaceae were the most represented families. The artificial perches performed the nucleating function through the increase of zoochoric seed rain. However, possibly due to different barriers that were not evaluated in this study, part of these seeds was not recruited. We recommend the application of this technique for the attraction of dispersers in degraded areas similar to the study site.

  15. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Wali, W A; Hassan, K H; Cullen, J D; Al-Shamma' a, A I; Shaw, A; Wylie, S R, E-mail: w.wali@2009.ljmu.ac.uk [Built Environment and Sustainable Technologies Institute (BEST), School of the Built Environment, Faculty of Technology and Environment Liverpool John Moores University, Byrom Street, Liverpool L3 3AF (United Kingdom)

    2011-08-17

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  16. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    International Nuclear Information System (INIS)

    Wali, W A; Hassan, K H; Cullen, J D; Al-Shamma'a, A I; Shaw, A; Wylie, S R

    2011-01-01

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  17. Optimal artificial neural network architecture selection for performance prediction of compact heat exchanger with the EBaLM-OTR technique

    Energy Technology Data Exchange (ETDEWEB)

    Wijayasekara, Dumidu, E-mail: wija2589@vandals.uidaho.edu [Department of Computer Science, University of Idaho, 1776 Science Center Drive, Idaho Falls, ID 83402 (United States); Manic, Milos [Department of Computer Science, University of Idaho, 1776 Science Center Drive, Idaho Falls, ID 83402 (United States); Sabharwall, Piyush [Idaho National Laboratory, Idaho Falls, ID (United States); Utgikar, Vivek [Department of Chemical Engineering, University of Idaho, Idaho Falls, ID 83402 (United States)

    2011-07-15

    Highlights: > Performance prediction of PCHE using artificial neural networks. > Evaluating artificial neural network performance for PCHE modeling. > Selection of over-training resilient artificial neural networks. > Artificial neural network architecture selection for modeling problems with small data sets. - Abstract: Artificial Neural Networks (ANN) have been used in the past to predict the performance of printed circuit heat exchangers (PCHE) with satisfactory accuracy. Typically published literature has focused on optimizing ANN using a training dataset to train the network and a testing dataset to evaluate it. Although this may produce outputs that agree with experimental results, there is a risk of over-training or over-learning the network rather than generalizing it, which should be the ultimate goal. An over-trained network is able to produce good results with the training dataset but fails when new datasets with subtle changes are introduced. In this paper we present EBaLM-OTR (error back propagation and Levenberg-Marquardt algorithms for over training resilience) technique, which is based on a previously discussed method of selecting neural network architecture that uses a separate validation set to evaluate different network architectures based on mean square error (MSE), and standard deviation of MSE. The method uses k-fold cross validation. Therefore in order to select the optimal architecture for the problem, the dataset is divided into three parts which are used to train, validate and test each network architecture. Then each architecture is evaluated according to their generalization capability and capability to conform to original data. The method proved to be a comprehensive tool in identifying the weaknesses and advantages of different network architectures. The method also highlighted the fact that the architecture with the lowest training error is not always the most generalized and therefore not the optimal. Using the method the testing

  18. Optimal artificial neural network architecture selection for performance prediction of compact heat exchanger with the EBaLM-OTR technique

    International Nuclear Information System (INIS)

    Wijayasekara, Dumidu; Manic, Milos; Sabharwall, Piyush; Utgikar, Vivek

    2011-01-01

    Highlights: → Performance prediction of PCHE using artificial neural networks. → Evaluating artificial neural network performance for PCHE modeling. → Selection of over-training resilient artificial neural networks. → Artificial neural network architecture selection for modeling problems with small data sets. - Abstract: Artificial Neural Networks (ANN) have been used in the past to predict the performance of printed circuit heat exchangers (PCHE) with satisfactory accuracy. Typically published literature has focused on optimizing ANN using a training dataset to train the network and a testing dataset to evaluate it. Although this may produce outputs that agree with experimental results, there is a risk of over-training or over-learning the network rather than generalizing it, which should be the ultimate goal. An over-trained network is able to produce good results with the training dataset but fails when new datasets with subtle changes are introduced. In this paper we present EBaLM-OTR (error back propagation and Levenberg-Marquardt algorithms for over training resilience) technique, which is based on a previously discussed method of selecting neural network architecture that uses a separate validation set to evaluate different network architectures based on mean square error (MSE), and standard deviation of MSE. The method uses k-fold cross validation. Therefore in order to select the optimal architecture for the problem, the dataset is divided into three parts which are used to train, validate and test each network architecture. Then each architecture is evaluated according to their generalization capability and capability to conform to original data. The method proved to be a comprehensive tool in identifying the weaknesses and advantages of different network architectures. The method also highlighted the fact that the architecture with the lowest training error is not always the most generalized and therefore not the optimal. Using the method the

  19. Study of the intelligent control robustness with respect to radiations induced faults

    International Nuclear Information System (INIS)

    Cheynet, Ph.

    1999-01-01

    The so-called intelligent control techniques, such as Artificial Neural Networks and Fuzzy Logic, are considered as being potentially robust. Their digital implementation gives compact and powerful solutions to some problems difficult to be tackled by classical techniques. Such approaches might be used for applications working in harsh environment (nuclear and space). The aim of this thesis is to study the robustness of artificial neural networks and fuzzy logic against Single Event Upset faults, in order to evaluate their viability and their efficiency for onboard spacecraft processes. A set of experiments have been performed on a neural network and a fuzzy controller, both implementing real space applications: texture analysis from satellite images and wheel control of a martian rover. An original method, allowing to increase the recognition rate of any artificial neural network has been developed and used on the studied network. Digital architectures implementing the two studied techniques in this thesis, have been boarded on two scientific satellites. One is in flight since one year, the other will be launched in the end of 1999. Obtained results, both from software simulations, hardware fault injections or particle accelerator tests, show that intelligent control techniques have a significant robustness against Single Event Upset faults. Data issued from the flight experiment confirm these properties, showing that some onboard spacecraft processes can be reliably executed by digital artificial neural networks. (author)

  20. Adaptive lighting controllers using smart sensors

    Science.gov (United States)

    Papantoniou, Sotiris; Kolokotsa, Denia; Kalaitzakis, Kostas; Cesarini, Davide Nardi; Cubi, Eduard; Cristalli, Cristina

    2016-07-01

    The aim of this paper is to present an advanced controller for artificial lights evaluated in several rooms in two European Hospitals located in Chania, Greece and Ancona, Italy. Fuzzy techniques have been used for the architecture of the controller. The energy efficiency of the controllers has been calculated by running the controller coupled with validated models of the RADIANCE back-wards ray tracing software. The input of the controller is the difference between the current illuminance value and the desired one, while the output is the change of the light level that should be applied in the artificial lights. Simulation results indicate significant energy saving potentials. Energy saving potential is calculated from the comparison of the current use of the artificial lights by the users and the proposed one. All simulation work has been conducted using Matlab and RADIANCE environment.

  1. Estimation of operational parameters for a direct injection turbocharged spark ignition engine by using regression analysis and artificial neural network

    Directory of Open Access Journals (Sweden)

    Tosun Erdi

    2017-01-01

    Full Text Available This study was aimed at estimating the variation of several engine control parameters within the rotational speed-load map, using regression analysis and artificial neural network techniques. Duration of injection, specific fuel consumption, exhaust gas at turbine inlet, and within the catalytic converter brick were chosen as the output parameters for the models, while engine speed and brake mean effective pressure were selected as independent variables for prediction. Measurements were performed on a turbocharged direct injection spark ignition engine fueled with gasoline. A three-layer feed-forward structure and back-propagation algorithm was used for training the artificial neural network. It was concluded that this technique is capable of predicting engine parameters with better accuracy than linear and non-linear regression techniques.

  2. Robust control technique for nuclear power plants

    International Nuclear Information System (INIS)

    Murphy, G.V.; Bailey, J.M.

    1989-03-01

    This report summarizes the linear quadratic Guassian (LQG) design technique with loop transfer recovery (LQG/LTR) for design of control systems. The concepts of return ratio, return difference, inverse return difference, and singular values are summarized. The LQG/LTR design technique allows the synthesis of a robust control system. To illustrate the LQG/LTR technique, a linearized model of a simple process has been chosen. The process has three state variables, one input, and one output. Three control system design methods are compared: LQG, LQG/LTR, and a proportional plus integral controller (PI). 7 refs., 20 figs., 6 tabs

  3. Dynamic Analysis of a Phytoplankton-Fish Model with Biological and Artificial Control

    OpenAIRE

    Wang, Yapei; Zhao, Min; Pan, Xinhong; Dai, Chuanjun

    2014-01-01

    We investigate a nonlinear model of the interaction between phytoplankton and fish, which uses a pair of semicontinuous systems with biological and artificial control. First, the existence of an order-1 periodic solution to the system is analyzed using a Poincaré map and a geometric method. The stability conditions of the order-1 periodic solution are obtained by a theoretical mathematical analysis. Furthermore, based on previous analysis, we investigate the bifurcation in the order-1 periodi...

  4. [Experimental study on novel hybrid artificial trachea transplantation].

    Science.gov (United States)

    Liu, Wenliang; Xiao, Peng; Liang, Hengxing; An, Ran; Cheng, Gang; Yu, Fenglei

    2014-04-01

    We developed and designed a new type of artificial trachea. The basic structure of the artificial trachea was polytetrafluoroethylene vascular prosthesis linked with titanium rings on both sides. Dualmesh was sutured on titanium rings. This experimentation follows the replacement of trachea in dogs with a combined artificial trachea to investigate the feasibility of this type of prosthesis. Sixteen dogs were implanted with the combined artificial trachea after resection of 5 cm of cervical trachea. The 5 cm-long trachea of dogs on the necks were resected and the reconstruction of the defect of the trachea was performed with trachea prosthesis. According to the method of trachea reconstruction, the models were divided into 2 groups, artificial trachea implantation group (the control group, n = 8) and group of artificial trachea implantation with growth factor (the experimental group, n = 8). Then computer tomography scan (CT), bronchoscope and pathologic examination were conducted periodically to observe the healing state of the hybrid artificial trachea. None of the dogs died during operation of cervical segmental trachea construction. But four dogs in the control group died of apnea in succession because artificial trachea was displaced and the lumen was obstructed, while 2 dogs died in the experimental group. In the first month there was granulation around anastomosis with slight stenosis. The rest of dogs were well alive until they were sacrificed 14 months later. The mean survival time of the experimental group was longer than that of the control group. The rate of infection, anastomotic dehiscence, severe stenosis and accidental death in the experimental group were lower than the control group (P anastomosis effectively but infections and split or displacement of the artificial trachea are still major problems affecting long-term survival of the animals. Application of growth factors to a certain extent promotes tissue healing by changing the local environment.

  5. Intelligent Prediction of Soccer Technical Skill on Youth Soccer Player's Relative Performance Using Multivariate Analysis and Artificial Neural Network Techniques

    OpenAIRE

    Abdullah, M. R; Maliki, A. B. H. M; Musa, R. M; Kosni, N. A; Juahir, H

    2016-01-01

    This study aims to predict the potential pattern of soccer technical skill on Malaysia youth soccer players relative performance using multivariate analysis and artificial neural network techniques. 184 male youth soccer players were recruited in Malaysia soccer academy (average age = 15.2±2.0) underwent to, physical fitness test, anthropometric, maturity, motivation and the level of skill related soccer. Unsupervised pattern recognition of principal component analysis (PCA) was used to ident...

  6. Employing Artificial Intelligence To Minimise Internet Fraud

    Directory of Open Access Journals (Sweden)

    Edward Wong Sek Khin

    2009-12-01

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

  7. Consistently Trained Artificial Neural Network for Automatic Ship Berthing Control

    Directory of Open Access Journals (Sweden)

    Y.A. Ahmed

    2015-09-01

    Full Text Available In this paper, consistently trained Artificial Neural Network controller for automatic ship berthing is discussed. Minimum time course changing manoeuvre is utilised to ensure such consistency and a new concept named ‘virtual window’ is introduced. Such consistent teaching data are then used to train two separate multi-layered feed forward neural networks for command rudder and propeller revolution output. After proper training, several known and unknown conditions are tested to judge the effectiveness of the proposed controller using Monte Carlo simulations. After getting acceptable percentages of success, the trained networks are implemented for the free running experiment system to judge the network’s real time response for Esso Osaka 3-m model ship. The network’s behaviour during such experiments is also investigated for possible effect of initial conditions as well as wind disturbances. Moreover, since the final goal point of the proposed controller is set at some distance from the actual pier to ensure safety, therefore a study on automatic tug assistance is also discussed for the final alignment of the ship with actual pier.

  8. Polymeric membrane materials for artificial organs.

    Science.gov (United States)

    Kawakami, Hiroyoshi

    2008-01-01

    Many polymeric materials have already been used in the field of artificial organs. However, the materials used in artificial organs are not necessarily created with the best material selectivity and materials design; therefore, the development of synthesized polymeric membrane materials for artificial organs based on well-defined designs is required. The approaches to the development of biocompatible polymeric materials fall into three categories: (1) control of physicochemical characteristics on material surfaces, (2) modification of material surfaces using biomolecules, and (3) construction of biomimetic membrane surfaces. This review will describe current issues regarding polymeric membrane materials for use in artificial organs.

  9. On-Line Tracking Controller for Brushless DC Motor Drives Using Artificial Neural Networks

    Science.gov (United States)

    Rubaai, Ahmed

    1996-01-01

    A real-time control architecture is developed for time-varying nonlinear brushless dc motors operating in a high performance drives environment. The developed control architecture possesses the capabilities of simultaneous on-line identification and control. The dynamics of the motor are modeled on-line and controlled using an artificial neural network, as the system runs. The control architecture combines the experience and dependability of adaptive tracking systems with potential and promise of the neural computing technology. The sensitivity of real-time controller to parametric changes that occur during training is investigated. Such changes are usually manifested by rapid changes in the load of the brushless motor drives. This sudden change in the external load is simulated for the sigmoidal and sinusoidal reference tracks. The ability of the neuro-controller to maintain reasonable tracking accuracy in the presence of external noise is also verified for a number of desired reference trajectories.

  10. Application of artificial intelligence to triple quadrupole mass spectrometry (TQMS)

    International Nuclear Information System (INIS)

    Wong, C.M.; Crawford, R.W.; Kehler, T.P.; Kunz, J.C.

    1984-01-01

    At Lawrence Livermore National Laboratory the authors have designed a totally computerized triple quadrupole mass spectrometer with the ultimate goal of using it as a prototype for ''knowledge-based'' instrument control. As an ''intelligent'' instrument, with its computer-based data acquisition and control system, it has the ability to learn and respond quickly. The intelligence is encoded in the system using the representation and rule-based reasoning heuristic techniques of Artificial Intelligence. These techniques are used to encode heuristic knowledge, or the intuition, formal and informal rules, and experiential knowledge that the human expert normally uses to make decisions and arrive at solutions in a specific domain problem. In this specific case, the knowledge the authors are encoding is a tuning procedure for the spectrometer, including heuristics to describe a self-adaptive, feedback control process for real-time optimization or tuning of the data acquisition procedure throughout the entire data collection process

  11. Artificial Diets for Mosquitoes

    Directory of Open Access Journals (Sweden)

    Kristina K. Gonzales

    2016-12-01

    Full Text Available Mosquito-borne diseases are responsible for more than a million human deaths every year. Modern mosquito control strategies such as sterile insect technique (SIT, release of insects carrying a dominant lethal (RIDL, population replacement strategies (PR, and Wolbachia-based strategies require the rearing of large numbers of mosquitoes in culture for continuous release over an extended period of time. Anautogenous mosquitoes require essential nutrients for egg production, which they obtain through the acquisition and digestion of a protein-rich blood meal. Therefore, mosquito mass production in laboratories and other facilities relies on vertebrate blood from live animal hosts. However, vertebrate blood is expensive to acquire and hard to store for longer times especially under field conditions. This review discusses older and recent studies that were aimed at the development of artificial diets for mosquitoes in order to replace vertebrate blood.

  12. Artificial neural networks for static security assessment

    Energy Technology Data Exchange (ETDEWEB)

    Niebur, D.; Fischl, R.

    1997-12-31

    A reliable, continuous supply of electric energy is essential for the functioning of today`s complex societies. Due to a combination of increasing energy consumption and impediments of various kinds to the extension of existing electric transmission networks, these power systems are operated closer and closer to their limits. This situation requires a significantly less conservative power system operation and control regime which, in turn, is possible only by monitoring the system state in much more detail than was necessary previously. Fortunately, the large quantity of information required can be provided in many cases through recent advances in telecommunications and computing techniques. There is, however, a lack of evaluation techniques required to extract the salient information and to use it for higher-order processing. Whilst the sheer quantity of available information is always a problem, this situation is aggravated in emergency situations when rapid decisions are required. Furthermore, the behaviour of power systems is highly non-linear. Monitoring and control involves several hundred variables which are only partly available by measurements. Load demands and dynamic loads are difficult to model. Therefore models appropriate for normal situations might become invalid in emergency situations. These problems provide important motivation to explore novel data processing and programming techniques from the vast pool of artificial intelligence techniques. The following section gives a short introduction to static security assessment. (Author)

  13. Artificial intelligence applied to process signal analysis

    Science.gov (United States)

    Corsberg, Dan

    1988-01-01

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

  14. Prediction of Marshall Parameters of Modified Bituminous Mixtures Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Sunil Khuntia

    2014-09-01

    Full Text Available This study presents the application of artificial neural networks (ANN and least square support vector machine (LS-SVM for prediction of Marshall parameters obtained from Marshall tests for waste polyethylene (PE modified bituminous mixtures. Waste polyethylene in the form of fibres processed from utilized milk packets has been used to modify the bituminous mixes in order to improve their engineering properties. Marshall tests were carried out on mix specimens with variations in polyethylene and bitumen contents. It has been observed that the addition of waste polyethylene results in the improvement of Marshall characteristics such as stability, flow value and air voids, used to evaluate a bituminous mix. The proposed neural network (NN model uses the quantities of ingredients used for preparation of Marshall specimens such as polyethylene, bitumen and aggregate in order to predict the Marshall stability, flow value and air voids obtained from the tests. Out of two techniques used, the NN based model is found to be compact, reliable and predictable when compared with LS-SVM model. A sensitivity analysis has been performed to identify the importance of the parameters considered.

  15. Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

    Science.gov (United States)

    Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

    2015-01-01

    Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

  16. Integrated control of the cooling system and surface openings using the artificial neural networks

    International Nuclear Information System (INIS)

    Moon, Jin Woo

    2015-01-01

    This study aimed at suggesting an indoor temperature control method that can provide a comfortable thermal environment through the integrated control of the cooling system and the surface openings. Four control logic were developed, employing different application levels of rules and artificial neural network models. Rule-based control methods represented the conventional approach while ANN-based methods were applied for the predictive and adaptive controls. Comparative performance tests for the conventional- and ANN-based methods were numerically conducted for the double-skin-facade building, using the MATLAB (Matrix Laboratory) and TRNSYS (Transient Systems Simulation) software, after proving the validity by comparing the simulation and field measurement results. Analysis revealed that the ANN-based controls of the cooling system and surface openings improved the indoor temperature conditions with increased comfortable temperature periods and decreased standard deviation of the indoor temperature from the center of the comfortable range. In addition, the proposed ANN-based logic effectively reduced the number of operating condition changes of the cooling system and surface openings, which can prevent system failure. The ANN-based logic, however, did not show superiority in energy efficiency over the conventional logic. Instead, they have increased the amount of heat removal by the cooling system. From the analysis, it can be concluded that the ANN-based temperature control logic was able to keep the indoor temperature more comfortably and stably within the comfortable range due to its predictive and adaptive features. - Highlights: • Integrated rule-based and artificial neural network based logics were developed. • A cooling device and surface openings were controlled in an integrated manner. • Computer simulation method was employed for comparative performance tests. • ANN-based logics showed the advanced features of thermal environment. • Rule

  17. Artificial intelligence techniques for automatic screening of amblyogenic factors.

    Science.gov (United States)

    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.

  18. Artificial hairy surfaces with a nearly perfect hydrophobic response.

    Science.gov (United States)

    Hsu, Shu-Hau; Sigmund, Wolfgang M

    2010-02-02

    A nearly perfect hydrophobic interface by dint of mimicking hairs of arthropods was achieved for the first time. These Gamma-shape artificial hairs were made via a membrane casting technique on polypropylene substrates. This extreme hydrophobicity merely arises from microstructure modification, and no further chemical treatments are needed. The ultralow adhesion to water droplets was evaluated through video assessment, and it is believed to be attributed to the mechanical response of the artificial hairs. The principle of this fabrication technique is accessible and is expected to be compatible with large-area fabrication of superhydrophobic interfaces.

  19. Artificial intelligence approaches to astronomical observation scheduling

    Science.gov (United States)

    Johnston, Mark D.; Miller, Glenn

    1988-01-01

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

  20. An Examination of Application of Artificial Neural Network in Cognitive Radios

    International Nuclear Information System (INIS)

    Salau, H Bello; Onwuka, E N; Aibinu, A M

    2013-01-01

    Recent advancement in software radio technology has led to the development of smart device known as cognitive radio. This type of radio fuses powerful techniques taken from artificial intelligence, game theory, wideband/multiple antenna techniques, information theory and statistical signal processing to create an outstanding dynamic behavior. This cognitive radio is utilized in achieving diverse set of applications such as spectrum sensing, radio parameter adaptation and signal classification. This paper contributes by reviewing different cognitive radio implementation that uses artificial intelligence such as the hidden markov models, metaheuristic algorithm and artificial neural networks (ANNs). Furthermore, different areas of application of ANNs and their performance metrics based approach are also examined

  1. An Examination of Application of Artificial Neural Network in Cognitive Radios

    Science.gov (United States)

    Bello Salau, H.; Onwuka, E. N.; Aibinu, A. M.

    2013-12-01

    Recent advancement in software radio technology has led to the development of smart device known as cognitive radio. This type of radio fuses powerful techniques taken from artificial intelligence, game theory, wideband/multiple antenna techniques, information theory and statistical signal processing to create an outstanding dynamic behavior. This cognitive radio is utilized in achieving diverse set of applications such as spectrum sensing, radio parameter adaptation and signal classification. This paper contributes by reviewing different cognitive radio implementation that uses artificial intelligence such as the hidden markov models, metaheuristic algorithm and artificial neural networks (ANNs). Furthermore, different areas of application of ANNs and their performance metrics based approach are also examined.

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

    Science.gov (United States)

    Tong, S. S.

    1986-01-01

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

  3. Digital image analysis in breast pathology-from image processing techniques to artificial intelligence.

    Science.gov (United States)

    Robertson, Stephanie; Azizpour, Hossein; Smith, Kevin; Hartman, Johan

    2018-04-01

    Breast cancer is the most common malignant disease in women worldwide. In recent decades, earlier diagnosis and better adjuvant therapy have substantially improved patient outcome. Diagnosis by histopathology has proven to be instrumental to guide breast cancer treatment, but new challenges have emerged as our increasing understanding of cancer over the years has revealed its complex nature. As patient demand for personalized breast cancer therapy grows, we face an urgent need for more precise biomarker assessment and more accurate histopathologic breast cancer diagnosis to make better therapy decisions. The digitization of pathology data has opened the door to faster, more reproducible, and more precise diagnoses through computerized image analysis. Software to assist diagnostic breast pathology through image processing techniques have been around for years. But recent breakthroughs in artificial intelligence (AI) promise to fundamentally change the way we detect and treat breast cancer in the near future. Machine learning, a subfield of AI that applies statistical methods to learn from data, has seen an explosion of interest in recent years because of its ability to recognize patterns in data with less need for human instruction. One technique in particular, known as deep learning, has produced groundbreaking results in many important problems including image classification and speech recognition. In this review, we will cover the use of AI and deep learning in diagnostic breast pathology, and other recent developments in digital image analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. A multiscale approach for modeling actuation response of polymeric artificial muscles.

    Science.gov (United States)

    Sharafi, Soodabeh; Li, Guoqiang

    2015-05-21

    Artificial muscles are emerging materials in the field of smart materials with applications in aerospace, robotic, and biomedical industries. Despite extensive experimental investigations in this field, there is a need for numerical modeling techniques that facilitate cutting edge research and development. This work aims at studying an artificial muscle made of twisted Nylon 6.6 fibers that are highly cold-drawn. A computationally efficient phenomenological thermo-mechanical constitutive model is developed in which several physical properties of the artificial muscles are incorporated to minimize the trial-and-error numerical curve fitting processes. Two types of molecular chains are considered at the micro-scale level that control training and actuation processes viz. (a) helically oriented chains which are structural switches that store a twisted shape in their low temperature phase and restore their random configuration during the thermal actuation process, and (b) entropic chains which are highly drawn chains that could actuate as soon as the muscle heats up, and saturates when coil contact temperature is reached. The thermal actuation response of the muscle over working temperatures has been elaborated in the Modeling section. The performance of the model is validated by available experiments in the literature. The model may provide a design platform for future artificial muscle developments.

  5. Embodied artificial agents for understanding human social cognition.

    Science.gov (United States)

    Wykowska, Agnieszka; Chaminade, Thierry; Cheng, Gordon

    2016-05-05

    In this paper, we propose that experimental protocols involving artificial agents, in particular the embodied humanoid robots, provide insightful information regarding social cognitive mechanisms in the human brain. Using artificial agents allows for manipulation and control of various parameters of behaviour, appearance and expressiveness in one of the interaction partners (the artificial agent), and for examining effect of these parameters on the other interaction partner (the human). At the same time, using artificial agents means introducing the presence of artificial, yet human-like, systems into the human social sphere. This allows for testing in a controlled, but ecologically valid, manner human fundamental mechanisms of social cognition both at the behavioural and at the neural level. This paper will review existing literature that reports studies in which artificial embodied agents have been used to study social cognition and will address the question of whether various mechanisms of social cognition (ranging from lower- to higher-order cognitive processes) are evoked by artificial agents to the same extent as by natural agents, humans in particular. Increasing the understanding of how behavioural and neural mechanisms of social cognition respond to artificial anthropomorphic agents provides empirical answers to the conundrum 'What is a social agent?' © 2016 The Authors.

  6. Artificial senses for characterization of food quality

    Institute of Scientific and Technical Information of China (English)

    HUANG Yan-bo; LAN Yu-bin; R.E. Lacey

    2004-01-01

    Food quality is of primary concern in the food industry and to the consumer. Systems that mimic human senses have been developed and applied to the characterization of food quality. The five primary senses are: vision, hearing, smell, taste and touch.In the characterization of food quality, people assess the samples sensorially and differentiate "good" from "bad" on a continuum.However, the human sensory system is subjective, with mental and physical inconsistencies, and needs time to work. Artificial senses such as machine vision, the electronic ear, electronic nose, electronic tongue, artificial mouth and even artificial the head have been developed that mimic the human senses. These artificial senses are coordinated individually or collectively by a pattern recognition technique, typically artificial neural networks, which have been developed based on studies of the mechanism of the human brain. Such a structure has been used to formulate methods for rapid characterization of food quality. This research presents and discusses individual artificial sensing systems. With the concept of multi-sensor data fusion these sensor systems can work collectively in some way. Two such fused systems, artificial mouth and artificial head, are described and discussed. It indicates that each of the individual systems has their own artificially sensing ability to differentiate food samples. It further indicates that with a more complete mimic of human intelligence the fused systems are more powerful than the individual systems in differentiation of food samples.

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

    International Nuclear Information System (INIS)

    Johnson, J.R.

    1988-01-01

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

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

    Science.gov (United States)

    Sayre, Scott Alan

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

  9. Artificial Neural Networks For Hadron Hadron Cross-sections

    International Nuclear Information System (INIS)

    ELMashad, M.; ELBakry, M.Y.; Tantawy, M.; Habashy, D.M.

    2011-01-01

    In recent years artificial neural networks (ANN ) have emerged as a mature and viable framework with many applications in various areas. Artificial neural networks theory is sometimes used to refer to a branch of computational science that uses neural networks as models to either simulate or analyze complex phenomena and/or study the principles of operation of neural networks analytically. In this work a model of hadron- hadron collision using the ANN technique is present, the hadron- hadron based ANN model calculates the cross sections of hadron- hadron collision. The results amply demonstrate the feasibility of such new technique in extracting the collision features and prove its effectiveness

  10. Robust Fault-Tolerant Control for Satellite Attitude Stabilization Based on Active Disturbance Rejection Approach with Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Fei Song

    2014-01-01

    Full Text Available This paper proposed a robust fault-tolerant control algorithm for satellite stabilization based on active disturbance rejection approach with artificial bee colony algorithm. The actuating mechanism of attitude control system consists of three working reaction flywheels and one spare reaction flywheel. The speed measurement of reaction flywheel is adopted for fault detection. If any reaction flywheel fault is detected, the corresponding fault flywheel is isolated and the spare reaction flywheel is activated to counteract the fault effect and ensure that the satellite is working safely and reliably. The active disturbance rejection approach is employed to design the controller, which handles input information with tracking differentiator, estimates system uncertainties with extended state observer, and generates control variables by state feedback and compensation. The designed active disturbance rejection controller is robust to both internal dynamics and external disturbances. The bandwidth parameter of extended state observer is optimized by the artificial bee colony algorithm so as to improve the performance of attitude control system. A series of simulation experiment results demonstrate the performance superiorities of the proposed robust fault-tolerant control algorithm.

  11. Integration of artificial intelligence and numerical optimization techniques for the design of complex aerospace systems

    International Nuclear Information System (INIS)

    Tong, S.S.; Powell, D.; Goel, S.

    1992-02-01

    A new software system called Engineous combines artificial intelligence and numerical methods for the design and optimization of complex aerospace systems. Engineous combines the advanced computational techniques of genetic algorithms, expert systems, and object-oriented programming with the conventional methods of numerical optimization and simulated annealing to create a design optimization environment that can be applied to computational models in various disciplines. Engineous has produced designs with higher predicted performance gains that current manual design processes - on average a 10-to-1 reduction of turnaround time - and has yielded new insights into product design. It has been applied to the aerodynamic preliminary design of an aircraft engine turbine, concurrent aerodynamic and mechanical preliminary design of an aircraft engine turbine blade and disk, a space superconductor generator, a satellite power converter, and a nuclear-powered satellite reactor and shield. 23 refs

  12. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

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

  13. The design and optimization for light-algae bioreactor controller based on Artificial Neural Network-Model Predictive Control

    Science.gov (United States)

    Hu, Dawei; Liu, Hong; Yang, Chenliang; Hu, Enzhu

    As a subsystem of the bioregenerative life support system (BLSS), light-algae bioreactor (LABR) has properties of high reaction rate, efficiently synthesizing microalgal biomass, absorbing CO2 and releasing O2, so it is significant for BLSS to provide food and maintain gas balance. In order to manipulate the LABR properly, it has been designed as a closed-loop control system, and technology of Artificial Neural Network-Model Predictive Control (ANN-MPC) is applied to design the controller for LABR in which green microalgae, Spirulina platensis is cultivated continuously. The conclusion is drawn by computer simulation that ANN-MPC controller can intelligently learn the complicated dynamic performances of LABR, and automatically, robustly and self-adaptively regulate the light intensity illuminating on the LABR, hence make the growth of microalgae in the LABR be changed in line with the references, meanwhile provide appropriate damping to improve markedly the transient response performance of LABR.

  14. Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques.

    Directory of Open Access Journals (Sweden)

    Hazlee Azil Illias

    Full Text Available It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN and particle swarm optimisation (PSO techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works.

  15. Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques.

    Science.gov (United States)

    Illias, Hazlee Azil; Chai, Xin Rui; Abu Bakar, Ab Halim; Mokhlis, Hazlie

    2015-01-01

    It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works.

  16. Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques

    Science.gov (United States)

    2015-01-01

    It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works. PMID:26103634

  17. Control of non-linear actuator of artificial muscles for the use in low-cost robotics prosthetics limbs

    Science.gov (United States)

    Anis Atikah, Nurul; Yeng Weng, Leong; Anuar, Adzly; Chien Fat, Chau; Sahari, Khairul Salleh Mohamed; Zainal Abidin, Izham

    2017-10-01

    Currently, the methods of actuating robotic-based prosthetic limbs are moving away from bulky actuators to more fluid materials such as artificial muscles. The main disadvantages of these artificial muscles are their high cost of manufacturing, low-force generation, cumbersome and complex controls. A recent discovery into using super coiled polymer (SCP) proved to have low manufacturing costs, high force generation, compact and simple controls. Nevertheless, the non-linear controls still exists due to the nature of heat-based actuation, which is hysteresis. This makes position control difficult. Using electrically conductive devices allows for very quick heating, but not quick cooling. This research tries to solve the problem by using peltier devices, which can effectively heat and cool the SCP, hence giving way to a more precise control. The peltier device does not actively introduce more energy to a volume of space, which the coiled heating does; instead, it acts as a heat pump. Experiments were conducted to test the feasibility of using peltier as an actuating method on different diameters of nylon fishing strings. Based on these experiments, the performance characteristics of the strings were plotted, which could be used to control the actuation of the string efficiently in the future.

  18. Adaptive control of two-wheeled mobile balance robot capable to adapt different surfaces using a novel artificial neural network–based real-time switching dynamic controller

    Directory of Open Access Journals (Sweden)

    Ali Unluturk

    2017-03-01

    Full Text Available In this article, a novel real-time artificial neural network–based adaptable switching dynamic controller is developed and practically implemented. It will be used for real-time control of two-wheeled balance robot which can balance itself upright position on different surfaces. In order to examine the efficiency of the proposed controller, a two-wheeled mobile balance robot is designed and a test platform for experimental setup is made for balance problem on different surfaces. In a developed adaptive controller algorithm which is capable to adapt different surfaces, mean absolute target angle deviation error, mean absolute target displacement deviation error and mean absolute controller output data are employed for surface estimation by using artificial neural network. In a designed two-wheeled mobile balance robot system, robot tilt angle is estimated via Kalman filter from accelerometer and gyroscope sensor signals. Furthermore, a visual robot control interface is developed in C++ software development environment so that robot controller parameters can be changed as desired. In addition, robot balance angle, linear displacement and controller output can be observed online on personal computer. According to the real-time experimental results, the proposed novel type controller gives more effective results than the classic ones.

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

    Directory of Open Access Journals (Sweden)

    Jeremy Straub

    2013-05-01

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

  20. Artificial Intelligence Techniques for Automatic Screening of Amblyogenic Factors

    Science.gov (United States)

    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

  1. Robust and Accurate Closed-Loop Control of McKibben Artificial Muscle Contraction with a Linear Single Integral Action

    Directory of Open Access Journals (Sweden)

    Bertrand Tondu

    2014-06-01

    Full Text Available We analyze the possibility of taking advantage of artificial muscle’s own stiffness and damping, and substituting it for a classic proportional-integral-derivative controller (PID controller an I controller. The advantages are that there would only be one parameter to tune and no need for a dynamic model. A stability analysis is proposed from a simple phenomenological artificial muscle model. Step and sinus-wave tracking responses performed with pneumatic McKibben muscles are reported showing the practical efficiency of the method to combine accuracy and load robustness. In the particular case of the McKibben artificial muscle technology, we suggest that the dynamic performances in stability and load robustness would result from the textile nature of its braided sleeve and its internal friction which do not obey Coulomb’s third law, as verified by preliminary reported original friction experiments. Comparisons are reported between three kinds of braided sleeves made of rayon yarns, plastic, and thin metal wires, whose similar closed-loop dynamic performances are highlighted. It is also experimentally shown that a sleeve braided with thin metal wires can give high accuracy performance, in step as in tracking response. This would be due to a low static friction coefficient combined with a kinetic friction exponentially increasing with speed in accordance with hydrodynamic lubrication theory applied to textile physics.

  2. Intelligent control systems 1990

    International Nuclear Information System (INIS)

    Shoureshi, R.

    1991-01-01

    The field of artificial intelligence (Al) has generated many useful ideas and techniques that can be integrated into the design of control systems. It is believed and, for special cases, has been demonstrated, that integration of Al into control systems would provide the necessary tools for solving many of the complex problems that present control techniques and Al algorithms are unable to do, individually. However, this integration requires the development of basic understanding and new fundamentals to provide scientific bases for achievement of its potential. This book presents an overview of some of the latest research studies in the area of intelligent control systems. These papers present techniques for formulation of intelligent control, and development of the rule-based control systems. Papers present applications of control systems in nuclear power plants and HVAC systems

  3. BP neural network tuned PID controller for position tracking of a pneumatic artificial muscle.

    Science.gov (United States)

    Fan, Jizhuang; Zhong, Jun; Zhao, Jie; Zhu, Yanhe

    2015-01-01

    Although Pneumatic Artificial Muscle (PAM) has a promising future in rehabilitation robots, it's difficult to realize accurate position control due to its highly nonlinear properties. This paper deals with position control of PAM. To describe the hysteresis inside PAM, a polynomial based phenomenological function is developed. Based on the phenomenological model for PAM and analysis of pressure dynamics within PAM, an adaptive cascade controller is proposed. Both outer loop and inner loop employ BP Neural Network tuned PID algorithm. The outer loop is to handle high nonlinearities and unmodeled dynamics of PAM, while the inner loop is responsible for nonlinearities caused by pressure dynamics. Experimental results show high tracking accuracy as compared with a convention PID controller. The proposed controller is effective in improving performance of PAM and will be implemented in a rehabilitation robot.

  4. Artificial Intelligence: Applications in Education.

    Science.gov (United States)

    Thorkildsen, Ron J.; And Others

    1986-01-01

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

  5. Survey of biochemical and oxidative profile in donkey foals suckled with one natural and one semi-artificial technique.

    Directory of Open Access Journals (Sweden)

    Pasquale De Palo

    Full Text Available Dairy donkey milking procedures require separating foals from their dams for a few hours a day. Artificial suckling in this species is a good technique for improving milk production and foal welfare. The aim of the work is to compare the effect of two different diets on donkey foals when separated from jennies for milking procedures with and without a milk replacer. Forty newborn Martina Franca donkey foals were subdivided into two experimental groups. Both groups were separated from their respective dams from 8.00to 20.00to allow the jennies to be milked. During the separation, all the foals had access ad libitum to water, hay and feed. During the separation period, one group had the availability of a mechanical milk replacer dispenser, so foals were partially artificially suckled (AS, while the other group had no milk replacer available, and so were totally naturally suckled (NS. The AS group had milk replacer availability until 120±7d of life. Both groups were naturally weaned at 168±7d. Blood samples were collected weekly starting from birth until two wks after weaning (i.e. at 182d, from all the foals included in the trial. Almost all the analytes were influenced by suckling technique and age of foals. Alanine-aminotransferase, aspartate-aminotransferase, alkaline phosphatase, NEFA, lipid hydroperoxides, serum proteins showed the greatest differences between the two experimental groups. Separating foals from their dams for 12hdaily for 24 weeks does not lead to pathological subclinical and metabolic conditions, thus confirming the high rusticity and resistance of the donkey.

  6. An Artificial Intelligence-Based Environment Quality Analysis System

    OpenAIRE

    Oprea , Mihaela; Iliadis , Lazaros

    2011-01-01

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

  7. The control of artificial radio-elements of medical use in France; Le controle des radioelements artificiels a usage medical en France

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, Y. [Commissariat a l' energie atomique et aux energies alternatives - CEA, Centre d' etudes nucleaires de Saclay, Service des Radio-elements artificiels (France)

    1960-07-01

    Artificial radio-elements are sometimes used in hospitals or laboratories possessing specific equipment and certified staff. These radio-elements are produced within the Saclay Nuclear Centre, and, if they are aimed to a medical use, are submitted to a pharmaceutical control which the issue is addressed in this report. After a recall of the preparation of these radio-elements, the author describes physical controls (determination of radioactivity, measurement of colloidal particle size, impurity content), and biological controls performed on these radio-elements. Reprint of a paper published in Annales pharmaceutiques francaises, tom. XVII, p. 250-260, 1959.

  8. Energy consumption control automation using Artificial Neural Networks and adaptive algorithms: Proposal of a new methodology and case study

    International Nuclear Information System (INIS)

    Benedetti, Miriam; Cesarotti, Vittorio; Introna, Vito; Serranti, Jacopo

    2016-01-01

    Highlights: • A methodology to enable energy consumption control automation is proposed. • The methodology is based on the use of Artificial Neural Networks. • A method to control the accuracy of the model over time is proposed. • Two methods to enable automatic retraining of the network are proposed. • Retraining methods are evaluated on their accuracy over time. - Abstract: Energy consumption control in energy intensive companies is always more considered as a critical activity to continuously improve energy performance. It undoubtedly requires a huge effort in data gathering and analysis, and the amount of these data together with the scarceness of human resources devoted to Energy Management activities who could maintain and update the analyses’ output are often the main barriers to its diffusion in companies. Advanced tools such as software based on machine learning techniques are therefore the key to overcome these barriers and allow an easy but accurate control. This type of systems is able to solve complex problems obtaining reliable results over time, but not to understand when the reliability of the results is declining (a common situation considering energy using systems, often undergoing structural changes) and to automatically adapt itself using a limited amount of training data, so that a completely automatic application is not yet available and the automatic energy consumption control using intelligent systems is still a challenge. This paper presents a whole new approach to energy consumption control, proposing a methodology based on Artificial Neural Networks (ANNs) and aimed at creating an automatic energy consumption control system. First of all, three different structures of neural networks are proposed and trained using a huge amount of data. Three different performance indicators are then used to identify the most suitable structure, which is implemented to create an energy consumption control tool. In addition, considering that

  9. Artificial Consciousness or Artificial Intelligence

    OpenAIRE

    Spanache Florin

    2017-01-01

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

  10. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    OpenAIRE

    Daniel-Petru GHENCEA; Miron ZAPCIU; Claudiu-Florinel BISU; Elena-Iuliana BOTEANU; Elena-Luminiţa OLTEANU

    2017-01-01

    The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic). The paper presents a prediction mode obtaining valid range of values f...

  11. Applying Artificial Intelligence and Internet Techniques in Rural Tourism Domain

    OpenAIRE

    Turcu, Cristina; Turcu, Cornel

    2017-01-01

    Society has become more dependent on automated intelligent systems, at the same time, these systems have become more and more complicated. Society's expectation regarding the capabilities and intelligence of such systems has also grown. We have become a more complicated society with more complicated problems. As the expectation of intelligent systems rises, we discover many more applications for artificial intelligence. Additionally, as the difficulty level and computational requirements of s...

  12. Distributed flow estimation and closed-loop control of an underwater vehicle with a multi-modal artificial lateral line.

    Science.gov (United States)

    DeVries, Levi; Lagor, Francis D; Lei, Hong; Tan, Xiaobo; Paley, Derek A

    2015-03-25

    Bio-inspired sensing modalities enhance the ability of autonomous vehicles to characterize and respond to their environment. This paper concerns the lateral line of cartilaginous and bony fish, which is sensitive to fluid motion and allows fish to sense oncoming flow and the presence of walls or obstacles. The lateral line consists of two types of sensing modalities: canal neuromasts measure approximate pressure gradients, whereas superficial neuromasts measure local flow velocities. By employing an artificial lateral line, the performance of underwater sensing and navigation strategies is improved in dark, cluttered, or murky environments where traditional sensing modalities may be hindered. This paper presents estimation and control strategies enabling an airfoil-shaped unmanned underwater vehicle to assimilate measurements from a bio-inspired, multi-modal artificial lateral line and estimate flow properties for feedback control. We utilize potential flow theory to model the fluid flow past a foil in a uniform flow and in the presence of an upstream obstacle. We derive theoretically justified nonlinear estimation strategies to estimate the free stream flowspeed, angle of attack, and the relative position of an upstream obstacle. The feedback control strategy uses the estimated flow properties to execute bio-inspired behaviors including rheotaxis (the tendency of fish to orient upstream) and station-holding (the tendency of fish to position behind an upstream obstacle). A robotic prototype outfitted with a multi-modal artificial lateral line composed of ionic polymer metal composite and embedded pressure sensors experimentally demonstrates the distributed flow sensing and closed-loop control strategies.

  13. Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas

    Directory of Open Access Journals (Sweden)

    Stamatina Zavitsanou

    2016-09-01

    Full Text Available Significant increases in processing power, coupled with the miniaturization of processing units operating at low power levels, has motivated the embedding of modern control systems into medical devices. The design of such embedded decision-making strategies for medical applications is driven by multiple crucial factors, such as: (i guaranteed safety in the presence of exogenous disturbances and unexpected system failures; (ii constraints on computing resources; (iii portability and longevity in terms of size and power consumption; and (iv constraints on manufacturing and maintenance costs. Embedded control systems are especially compelling in the context of modern artificial pancreas systems (AP used in glucose regulation for patients with type 1 diabetes mellitus (T1DM. Herein, a review of potential embedded control strategies that can be leveraged in a fully-automated and portable AP is presented. Amongst competing controllers, emphasis is provided on model predictive control (MPC, since it has been established as a very promising control strategy for glucose regulation using the AP. Challenges involved in the design, implementation and validation of safety-critical embedded model predictive controllers for the AP application are discussed in detail. Additionally, the computational expenditure inherent to MPC strategies is investigated, and a comparative study of runtime performances and storage requirements among modern quadratic programming solvers is reported for a desktop environment and a prototype hardware platform.

  14. Mode Choice Modeling Using Artificial Neural Networks

    OpenAIRE

    Edara, Praveen Kumar

    2003-01-01

    Artificial intelligence techniques have produced excellent results in many diverse fields of engineering. Techniques such as neural networks and fuzzy systems have found their way into transportation engineering. In recent years, neural networks are being used instead of regression techniques for travel demand forecasting purposes. The basic reason lies in the fact that neural networks are able to capture complex relationships and learn from examples and also able to adapt when new data becom...

  15. The relationship between strategic control and conscious structural knowledge in artificial grammar learning.

    Science.gov (United States)

    Norman, Elisabeth; Scott, Ryan B; Price, Mark C; Dienes, Zoltan

    2016-05-01

    We address Jacoby's (1991) proposal that strategic control over knowledge requires conscious awareness of that knowledge. In a two-grammar artificial grammar learning experiment all participants were trained on two grammars, consisting of a regularity in letter sequences, while two other dimensions (colours and fonts) varied randomly. Strategic control was measured as the ability to selectively apply the grammars during classification. For each classification, participants also made a combined judgement of (a) decision strategy and (b) relevant stimulus dimension. Strategic control was found for all types of decision strategy, including trials where participants claimed to lack conscious structural knowledge. However, strong evidence of strategic control only occurred when participants knew or guessed that the letter dimension was relevant, suggesting that strategic control might be associated with - or even causally requires - global awareness of the nature of the rules even though it does not require detailed knowledge of their content. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  16. INFLUENCE OF ELECTROACUPUNCTURE ON ARTIFICIAL ABORTION-INDUCED SIDE EFFECTS

    Institute of Scientific and Technical Information of China (English)

    田丽颖

    2001-01-01

    In the present study, the effect of electroecupuncture (EA) of acupoints of Ren, Spleen and Stomach Meridians on artificial abortion-induced side effects was observed in 100 artificial abortion women. In comparison with 45 artificial abortion women in the control group (who had not accepted EA treatment), EA possessed significant effects in relieving abdominal pain, reducing vaginal bleeding duration, lowering infection rate and infertility rate after artificial abortion operation.

  17. Active structural control with stable fuzzy PID techniques

    CERN Document Server

    Yu, Wen

    2016-01-01

    This book presents a detailed discussion of intelligent techniques to measure the displacement of buildings when they are subjected to vibration. It shows how these techniques are used to control active devices that can reduce vibration 60–80% more effectively than widely used passive anti-seismic systems. After introducing various structural control devices and building-modeling and active structural control methods, the authors propose offset cancellation and high-pass filtering techniques to solve some common problems of building-displacement measurement using accelerometers. The most popular control algorithms in industrial settings, PD/PID controllers, are then analyzed and then combined with fuzzy compensation. The stability of this combination is proven with standard weight-training algorithms. These conditions provide explicit methods for selecting PD/PID controllers. Finally, fuzzy-logic and sliding-mode control are applied to the control of wind-induced vibration. The methods described are support...

  18. Use of artificial neural networks as estimators and controllers

    Science.gov (United States)

    Concilio, Antonio; Sorrentino, A.

    1996-04-01

    Active noise control is one among the most promising applications of the so-called Smart Structures, because it ensures, or promises, lower weight, lower cost, more effectiveness and all what is desirable in a vehicle design process, with respect to the current solutions. More and more attention in the research world has been devoting to this argument, pushed by both political, economical and environmental reasons, the one connected to the others. Piezoceramic actuators, integrated into the structure, seem to offer the most fashionable and practical solutions among all the proposed architectures, [1-2]. As sensors, microphones demonstrated to be the most performing, above all because they give the most suitable representation of the field that has to be cancelled, [3-4]. This approach is known as Acousto-Structural Active Control, ASAC, [5]. However, according to Fuller's definition, [6] , an intelligent controller is needed to ensure the development of an "Intelligent Structure" . Its main characteristic should be represented by the capability of learning by examples, of following the structure during its evolution, of being the system "brain" . This peculiarity may be offered by Artificial Neural Networks (ANN's), [7-8]. They present other important features, like the capability, in principle, of treating non-linear as well as linear problems, [9], of identifying dynamic systems, [10], of properly acting as a controller. Then, such a net could integrate in itself the function of "system estimator" or "observer" ,and of interpolator - extrapolator and controller, contemporarily. The authors have been working on such subjects for a long time, proposing for instance ANN's as time-domain structural parameters estimators on a simple 2D element ( a framed plate), [11], as noise and vibration controllers in a FF system, [12-13], as materials damping parameters extractors from experimental data, [14]. All these applications were aimed at noise reduction problems. The

  19. State and data techniques for control of discontinuous systems

    International Nuclear Information System (INIS)

    Kisner, R.A.

    1986-01-01

    This paper describes a technique for structured analysis and design of automated control systems. The technique integrates control of continuous and discontinuous nuclear power plant subsystems and components. A hierarchical control system with distributed intelligence follows from applying the technique. Further, it can be applied to all phases of control system design. For simplicity, the example used in the paper is limited to phase 1 design (basic automatic control action), in which no maintenance, testing, or contingency capability is attempted. 11 figs

  20. A Review of Safety and Design Requirements of the Artificial Pancreas.

    Science.gov (United States)

    Blauw, Helga; Keith-Hynes, Patrick; Koops, Robin; DeVries, J Hans

    2016-11-01

    As clinical studies with artificial pancreas systems for automated blood glucose control in patients with type 1 diabetes move to unsupervised real-life settings, product development will be a focus of companies over the coming years. Directions or requirements regarding safety in the design of an artificial pancreas are, however, lacking. This review aims to provide an overview and discussion of safety and design requirements of the artificial pancreas. We performed a structured literature search based on three search components-type 1 diabetes, artificial pancreas, and safety or design-and extended the discussion with our own experiences in developing artificial pancreas systems. The main hazards of the artificial pancreas are over- and under-dosing of insulin and, in case of a bi-hormonal system, of glucagon or other hormones. For each component of an artificial pancreas and for the complete system we identified safety issues related to these hazards and proposed control measures. Prerequisites that enable the control algorithms to provide safe closed-loop control are accurate and reliable input of glucose values, assured hormone delivery and an efficient user interface. In addition, the system configuration has important implications for safety, as close cooperation and data exchange between the different components is essential.

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

    Directory of Open Access Journals (Sweden)

    Riddhi Doshi

    2017-06-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-04-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2002-07-01

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

  5. Artificial limb representation in amputees

    OpenAIRE

    van den Heiligenberg, FMZ; Orlov, T; Macdonald, SN; Duff, EP; Henderson Slater, JDE; Beckmann, CF; Johansen-Berg, H; Culham, JC; Makin, TR

    2018-01-01

    The human brain contains multiple hand-selective areas, in both the sensorimotor and visual systems. Could our brain repurpose neural resources, originally developed for supporting hand function, to represent and control artificial limbs? We studied individuals with congenital or acquired hand-loss (hereafter one-handers) using functional MRI. We show that the more one-handers use an artificial limb (prosthesis) in their everyday life, the stronger visual hand-selective areas in the lateral o...

  6. Development of a microcontroller-based automatic control system for the electrohydraulic total artificial heart.

    Science.gov (United States)

    Kim, H C; Khanwilkar, P S; Bearnson, G B; Olsen, D B

    1997-01-01

    An automatic physiological control system for the actively filled, alternately pumped ventricles of the volumetrically coupled, electrohydraulic total artificial heart (EHTAH) was developed for long-term use. The automatic control system must ensure that the device: 1) maintains a physiological response of cardiac output, 2) compensates for an nonphysiological condition, and 3) is stable, reliable, and operates at a high power efficiency. The developed automatic control system met these requirements both in vitro, in week-long continuous mock circulation tests, and in vivo, in acute open-chested animals (calves). Satisfactory results were also obtained in a series of chronic animal experiments, including 21 days of continuous operation of the fully automatic control mode, and 138 days of operation in a manual mode, in a 159-day calf implant.

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

    Science.gov (United States)

    Mann, N H; Brown, M D

    1991-04-01

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

  8. Control of a hybrid compensator in a power network by an artificial neural network

    Directory of Open Access Journals (Sweden)

    I. S. Shaw

    1998-07-01

    Full Text Available Increased interest in the elimination of distortion in electrical power networks has led to the development of various compensator topologies. The increasing cost of electrical energy necessitates the cost-effective operation of any of these topologies. This paper considers the development of an artificial neural network based controller, trained by means of the backpropagation method, that ensures the cost-effective operation of the hybrid compensator consisting of various converters and filters.

  9. Pre-optimization of radiotherapy treatment planning: an artificial neural network classification aided technique

    International Nuclear Information System (INIS)

    Hosseini-Ashrafi, M.E.; Bagherebadian, H.; Yahaqi, E.

    1999-01-01

    A method has been developed which, by using the geometric information from treatment sample cases, selects from a given data set an initial treatment plan as a step for treatment plan optimization. The method uses an artificial neural network (ANN) classification technique to select a best matching plan from the 'optimized' ANN database. Separate back-propagation ANN classifiers were trained using 50, 60 and 77 examples for three groups of treatment case classes (up to 21 examples from each class were used). The performance of the classifiers in selecting the correct treatment class was tested using the leave-one-out method; the networks were optimized with respect their architecture. For the three groups used in this study, successful classification fractions of 0.83, 0.98 and 0.93 were achieved by the optimized ANN classifiers. The automated response of the ANN may be used to arrive at a pre-plan where many treatment parameters may be identified and therefore a significant reduction in the steps required to arrive at the optimum plan may be achieved. Treatment planning 'experience' and also results from lengthy calculations may be used for training the ANN. (author)

  10. Projecting impacts of climate change on water availability using artificial neural network techniques

    Science.gov (United States)

    Swain, Eric D.; Gomez-Fragoso, Julieta; Torres-Gonzalez, Sigfredo

    2017-01-01

    Lago Loíza reservoir in east-central Puerto Rico is one of the primary sources of public water supply for the San Juan metropolitan area. To evaluate and predict the Lago Loíza water budget, an artificial neural network (ANN) technique is trained to predict river inflows. A method is developed to combine ANN-predicted daily flows with ANN-predicted 30-day cumulative flows to improve flow estimates. The ANN application trains well for representing 2007–2012 and the drier 1994–1997 periods. Rainfall data downscaled from global circulation model (GCM) simulations are used to predict 2050–2055 conditions. Evapotranspiration is estimated with the Hargreaves equation using minimum and maximum air temperatures from the downscaled GCM data. These simulated 2050–2055 river flows are input to a water budget formulation for the Lago Loíza reservoir for comparison with 2007–2012. The ANN scenarios require far less computational effort than a numerical model application, yet produce results with sufficient accuracy to evaluate and compare hydrologic scenarios. This hydrologic tool will be useful for future evaluations of the Lago Loíza reservoir and water supply to the San Juan metropolitan area.

  11. Natural - synthetic - artificial!

    DEFF Research Database (Denmark)

    Nielsen, Peter E

    2010-01-01

    The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life.......The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life....

  12. Optimizing sliver quality using Artificial Neural Networks in ring spinning

    Directory of Open Access Journals (Sweden)

    Samar Ahmed Mohsen Abd-Ellatif

    2013-12-01

    Full Text Available Sliver evenness is a very important parameter affecting the quality of the yarn produced. Therefore, controlling the sliver evenness is of major importance. Auto-levelers mounted on modern Drawing Frames should be accurately adjusted to help to achieve this task. The Leveling Action Point (LAP is one of the important auto-leveling parameters which highly influence the evenness of the slivers produced. Its adjustment is therefore of a crucial importance. In this research work, Artificial Neural Networks are applied to predict the optimum value of the LAP under different productions and material conditions. Five models are developed and tested for their ability to predict the optimum value of the LAP from the most influencing fiber and process parameters. As a final step, a statistical multiple regression model was developed to conduct a comparison between the performance of the developed Artificial Neural Network model and the currently applied statistical techniques.

  13. Counseling, Artificial Intelligence, and Expert Systems.

    Science.gov (United States)

    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…

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

    OpenAIRE

    Straub, Jeremy; Huber, Justin

    2013-01-01

    An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (p...

  15. Light + architecture. Daylight - artificial light - energy; Licht + Architektur. Tageslicht - Kunstlicht - Energie

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2009-07-01

    The symposium intends to provide scientific and technical fundamentals for room lighting with daylight. Daylight deflection systems and artificial light control systems were analyzed for this purpose, and a catalogue of criteria was established. Planners were given tools for projecting daylight control systems. Builder-owners received the fundamentals for economic assessment of combined daylight and artificial light illumination systems, while industrial producers obtained information for further development to maturity and for marketing of daylight-dependent artificial light control systems. (GL)

  16. Advanced Instrumentation and control techniques for nuclear power plants

    International Nuclear Information System (INIS)

    Mori, Nobuyuki; Makino, Maomi; Naito, Norio

    1992-01-01

    Toshiba has been promoting the development of an advanced instrumentation and control system for nuclear power plants to fulfill the requirements for increased reliability, improved functionality and maintainability, and more competitive economic performance. This system integrates state-of-the-art technologies such as those for the latest man-machine interface, digital processing, optical multiplexing signal transmission, human engineering, and artificial intelligence. Such development has been systematically accomplished based on a schematic view of integrated digital control and instrumentation systems, and the development of whole systems has now been completed. This paper describes the purpose, design philosophy, and contents of newly developed systems, then considers the future trends of advanced man-machine systems. (author)

  17. Application of an artificial neural network and morphing techniques in the redesign of dysplastic trochlea.

    Science.gov (United States)

    Cho, Kyung Jin; Müller, Jacobus H; Erasmus, Pieter J; DeJour, David; Scheffer, Cornie

    2014-01-01

    Segmentation and computer assisted design tools have the potential to test the validity of simulated surgical procedures, e.g., trochleoplasty. A repeatable measurement method for three dimensional femur models that enables quantification of knee parameters of the distal femur is presented. Fifteen healthy knees are analysed using the method to provide a training set for an artificial neural network. The aim is to use this artificial neural network for the prediction of parameter values that describe the shape of a normal trochlear groove geometry. This is achieved by feeding the artificial neural network with the unaffected parameters of a dysplastic knee. Four dysplastic knees (Type A through D) are virtually redesigned by way of morphing the groove geometries based on the suggested shape from the artificial neural network. Each of the four resulting shapes is analysed and compared to its initial dysplastic shape in terms of three anteroposterior dimensions: lateral, central and medial. For the four knees the trochlear depth is increased, the ventral trochlear prominence reduced and the sulcus angle corrected to within published normal ranges. The results show a lateral facet elevation inadequate, with a sulcus deepening or a depression trochleoplasty more beneficial to correct trochlear dysplasia.

  18. Optimization an optimal artificial diet for the predatory bug Orius sauteri (hemiptera: anthocoridae.

    Directory of Open Access Journals (Sweden)

    Xiao-Ling Tan

    Full Text Available BACKGROUND: The flower bug Orius sauteri is an important polyphagous predator that is widely used for the biological control of mites and aphids. However, the optimal conditions for mass rearing of this insect are still unclear, thus limiting its application. METHODOLOGY: In this study, we investigated the optimal ingredients of an artificial diet for raising O. sauteri using a microencapsulation technique. The ingredients included egg yolk (vitellus, whole-pupa homogenate of the Tussah silk moth (Antheraea paphia, honey, sucrose, rapeseed (Brassica napus pollen and sinkaline. We tested 25 combinations of the above ingredients using an orthogonal experimental design. Using statistical analysis, we confirmed the main effect factors amongst the components, and selected five optimal combinations based on different biological and physiological characters. PRINCIPAL FINDINGS: The results showed that, although different artificial diet formats significantly influenced the development and reproductive ability of O. sauteri, the complete development of O. sauteri to sexual maturity could only be achieved by optimizing the artificial diet according to specific biological characters. In general, pupae of A. paphia had more influence on O sauteri development than did artificial components. The results of a follow-up test of locomotory and respiratory capacity indicated that respiratory quotient, metabolic rate and average creeping speed were all influenced by different diets. Furthermore, the field evaluations of mating preference, predatory consumption and population dispersion also demonstrated the benefits that could be provided by optimal artificial diets. CONCLUSIONS: A microencapsulated artificial diet overcame many of the difficulties highlighted by previous studies on the mass rearing of O. sauteri. Optimization of the microencapsulated artificial diet directly increased the biological and physiological characters investigated. Successive

  19. Driver electronics design and control for a total artificial heart linear motor.

    Science.gov (United States)

    Unthan, Kristin; Cuenca-Navalon, Elena; Pelletier, Benedikt; Finocchiaro, Thomas; Steinseifer, Ulrich

    2018-01-27

    For any implantable device size and efficiency are critical properties. Thus, a linear motor for a Total Artificial Heart was optimized with focus on driver electronics and control strategies. Hardware requirements were defined from power supply and motor setup. Four full bridges were chosen for the power electronics. Shunt resistors were set up for current measurement. Unipolar and bipolar switching for power electronics control were compared regarding current ripple and power losses. Here, unipolar switching showed smaller current ripple and required less power to create the necessary motor forces. Based on calculations for minimal power losses Lorentz force was distributed to the actor's four coils. The distribution was determined as ratio of effective magnetic flux through each coil, which was captured by a force test rig. Static and dynamic measurements under physiological conditions analyzed interaction of control and hardware and all efficiencies were over 89%. In conclusion, the designed electronics, optimized control strategy and applied current distribution create the required motor force and perform optimal under physiological conditions. The developed driver electronics and control offer optimized size and efficiency for any implantable or portable device with multiple independent motor coils. Graphical Abstract ᅟ.

  20. The development of an artificial organic networks toolkit for LabVIEW.

    Science.gov (United States)

    Ponce, Hiram; Ponce, Pedro; Molina, Arturo

    2015-03-15

    Two of the most challenging problems that scientists and researchers face when they want to experiment with new cutting-edge algorithms are the time-consuming for encoding and the difficulties for linking them with other technologies and devices. In that sense, this article introduces the artificial organic networks toolkit for LabVIEW™ (AON-TL) from the implementation point of view. The toolkit is based on the framework provided by the artificial organic networks technique, giving it the potential to add new algorithms in the future based on this technique. Moreover, the toolkit inherits both the rapid prototyping and the easy-to-use characteristics of the LabVIEW™ software (e.g., graphical programming, transparent usage of other softwares and devices, built-in programming event-driven for user interfaces), to make it simple for the end-user. In fact, the article describes the global architecture of the toolkit, with particular emphasis in the software implementation of the so-called artificial hydrocarbon networks algorithm. Lastly, the article includes two case studies for engineering purposes (i.e., sensor characterization) and chemistry applications (i.e., blood-brain barrier partitioning data model) to show the usage of the toolkit and the potential scalability of the artificial organic networks technique. © 2015 Wiley Periodicals, Inc.

  1. An Artificially Intelligent Technique to Generate Synthetic Geomechanical Well Logs for the Bakken Formation

    Directory of Open Access Journals (Sweden)

    George Parapuram

    2018-03-01

    Full Text Available Artificially intelligent and predictive modelling of geomechanical properties is performed by creating supervised machine learning data models utilizing artificial neural networks (ANN and will predict geomechanical properties from basic and commonly used conventional well logs such as gamma ray, and bulk density. The predictive models were created by following the approach on a large volume of data acquired from 112 wells containing the Bakken Formation in North Dakota. The studied wells cover a large surface area of the formation containing the five main producing counties in North Dakota: Burke, Mountrail, McKenzie, Dunn, and Williams. Thus, with a large surface area being analyzed in this research, there is confidence with a high degree of certainty that an extensive representation of the Bakken Formation is modelled, by training neural networks to work on varying properties from the different counties containing the Bakken Formation in North Dakota. Shear wave velocity of 112 wells is also analyzed by regression methods and neural networks, and a new correlation is proposed for the Bakken Formation. The final goal of the research is to achieve supervised artificial neural network models that predict geomechanical properties of future wells with an accuracy of at least 90% for the Upper and Middle Bakken Formation. Thus, obtaining these logs by generating it from statistical and artificially intelligent methods shows a potential for significant improvements in performance, efficiency, and profitability for oil and gas operators.

  2. Application of Meta-Heuristic Hybrid Artificial Intelligence Techniques for Modeling of Bonding Strength of Plywood Panels

    Directory of Open Access Journals (Sweden)

    Cenk Demirkır

    2014-04-01

    Full Text Available Plywood, which is one of the most important wood based panels, has many usage areas changing from traffic signs to building constructions in many countries. It is known that the high quality plywood panel manufacturing has been achieved with a good bonding under the optimum pressure conditions depending on adhesive type. This is a study of determining the using possibilities of modern meta-heuristic hybrid artificial intelligence techniques such as IKE and AANN methods for prediction of bonding strength of plywood panels. This study has composed of two main parts as experimental and analytical. Scots pine, maritime pine and European black pine logs were used as wood species. The pine veneers peeled at 32°C and 50°C were dried at 110°C, 140°C and 160°C temperatures. Phenol formaldehyde and melamine urea formaldehyde resins were used as adhesive types. EN 314-1 standard was used to determine the bonding shear strength values of plywood panels in experimental part of this study. Then the intuitive k-nearest neighbor estimator (IKE and adaptive artificial neural network (AANN were used to estimate bonding strength of plywood panels. The best estimation performance was obtained from MA metric for k-value=10. The most effective factor on bonding strength was determined as adhesive type. Error rates were determined less than 5% for both of the IKE and AANN. It may be recommended that proposed methods could be used in applying to estimation of bonding strength values of plywood panels.

  3. Biologically inspired technologies using artificial muscles

    Science.gov (United States)

    Bar-Cohen, Yoseph

    2005-01-01

    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 response mechanism and develop effective processing and characterization techniques. The field is still in its emerging state and robust materials are still not readily available however in recent years significant progress has been made and commercial products have already started to appear. This paper covers the current state of- the-art and challenges to making artificial muscles and their potential biomimetic applications.

  4. Artificial Neural Network Based Model of Photovoltaic Cell

    Directory of Open Access Journals (Sweden)

    Messaouda Azzouzi

    2017-03-01

    Full Text Available This work concerns the modeling of a photovoltaic system and the prediction of the sensitivity of electrical parameters (current, power of the six types of photovoltaic cells based on voltage applied between terminals using one of the best known artificial intelligence technique which is the Artificial Neural Networks. The results of the modeling and prediction have been well shown as a function of number of iterations and using different learning algorithms to obtain the best results. 

  5. Biologically inspired technologies using artificial muscles

    Science.gov (United States)

    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.

  6. Building Explainable Artificial Intelligence Systems

    National Research Council Canada - National Science Library

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

    2006-01-01

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

  7. Artificial Intelligence Applications to Videodisc Technology

    OpenAIRE

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

    1985-01-01

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

  8. Advanced controls for light sources

    Science.gov (United States)

    Biedron, S. G.; Edelen, A. L.; Milton, S. V.

    2016-09-01

    We present a summary of our team's recent efforts in developing adaptive, artificial intelligence-inspired techniques specifically to address several control challenges that arise in machines/systems including those in particle accelerator systems. These techniques can readily be adapted to other systems such as lasers, beamline optics, etc… We are not at all suggesting that we create an autonomous system, but create a system with an intelligent control system, that can continually use operational data to improve itself and combines both traditional and advanced techniques. We believe that the system performance and reliability can be increased based on our findings. Another related point is that the controls sub-system of an overall system is usually not the heart of the system architecture or design process. More bluntly, often times all of the peripheral systems are considered as secondary to the main system components in the architecture design process because it is assumed that the controls system will be able to "fix" challenges found later with the sub-systems for overall system operation. We will show that this is not always the case and that it took an intelligent control application to overcome a sub-system's challenges. We will provide a recent example of such a "fix" with a standard controller and with an artificial intelligence-inspired controller. A final related point to be covered is that of system adaptation for requirements not original to a system's original design.

  9. Intelligent system for lighting control in smart cities

    OpenAIRE

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

    2017-01-01

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

  10. Indian contribution to applications of artificially injected tritium in hydrological investigations

    International Nuclear Information System (INIS)

    Datta, P.S.

    1982-01-01

    The paper gives a brief description on significance of groundwater hydrology and sets it in the context of radioisotopic investigations. The topics described pertain to potential applications of artificially injected tritium in local or regional scale to determine water movement in the unsaturated zone, rate of infiltration, groundwater recharge, direction and velocity of groundwater, interconnection of groundwater bodies, dispersion of pollutants, etc. The Indian contribution on these topics is incorporated giving informations on techniques adopted and the major findings and conclusions of the experiments conducted. Merits and demerits of each technique have also been described. Some aspects deserving urgent consideration are outlined to gain maximum benefits from the applications of artificially injected tritium tracer techniques in hydrology. (author)

  11. Artificial intelligence tools decision support systems in condition monitoring and diagnosis

    CERN Document Server

    Galar Pascual, Diego

    2015-01-01

    Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource: Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques Considers the merits of each technique as well as the issues associated with real-life application Covers classification methods, from neural networks to Bayesian and support vector machines Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB® code for algorithm testing Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

  12. Artificial intelligence in nuclear power plants. Vol. 2

    International Nuclear Information System (INIS)

    Haapanen, P.J.

    1990-01-01

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

  13. Challenges and Recent Progress in the Development of a Closed-loop Artificial Pancreas.

    Science.gov (United States)

    Bequette, B Wayne

    2012-12-01

    Pursuit of a closed-loop artificial pancreas that automatically controls the blood glucose of individuals with type 1 diabetes has intensified during the past six years. Here we discuss the recent progress and challenges in the major steps towards a closed-loop system. Continuous insulin infusion pumps have been widely available for over two decades, but "smart pump" technology has made the devices easier to use and more powerful. Continuous glucose monitoring (CGM) technology has improved and the devices are more widely available. A number of approaches are currently under study for fully closed-loop systems; most manipulate only insulin, while others manipulate insulin and glucagon. Algorithms include on-off (for prevention of overnight hypoglycemia), proportional-integral-derivative (PID), model predictive control (MPC) and fuzzy logic based learning control. Meals cause a major "disturbance" to blood glucose, and we discuss techniques that our group has developed to predict when a meal is likely to be consumed and its effect. We further examine both physiology and device-related challenges, including insulin infusion set failure and sensor signal attenuation. Finally, we discuss the next steps required to make a closed-loop artificial pancreas a commercial reality.

  14. Fluid-driven origami-inspired artificial muscles

    Science.gov (United States)

    Li, Shuguang; Vogt, Daniel M.; Rus, Daniela; Wood, Robert J.

    2017-12-01

    Artificial muscles hold promise for safe and powerful actuation for myriad common machines and robots. However, the design, fabrication, and implementation of artificial muscles are often limited by their material costs, operating principle, scalability, and single-degree-of-freedom contractile actuation motions. Here we propose an architecture for fluid-driven origami-inspired artificial muscles. This concept requires only a compressible skeleton, a flexible skin, and a fluid medium. A mechanical model is developed to explain the interaction of the three components. A fabrication method is introduced to rapidly manufacture low-cost artificial muscles using various materials and at multiple scales. The artificial muscles can be programed to achieve multiaxial motions including contraction, bending, and torsion. These motions can be aggregated into systems with multiple degrees of freedom, which are able to produce controllable motions at different rates. Our artificial muscles can be driven by fluids at negative pressures (relative to ambient). This feature makes actuation safer than most other fluidic artificial muscles that operate with positive pressures. Experiments reveal that these muscles can contract over 90% of their initial lengths, generate stresses of ˜600 kPa, and produce peak power densities over 2 kW/kg—all equal to, or in excess of, natural muscle. This architecture for artificial muscles opens the door to rapid design and low-cost fabrication of actuation systems for numerous applications at multiple scales, ranging from miniature medical devices to wearable robotic exoskeletons to large deployable structures for space exploration.

  15. Acoustic emission condition monitoring of a nuclear power plant check valve using artificial neural networks

    International Nuclear Information System (INIS)

    Lee, Joon Hyun; Lee, Min Rae; Kim, Jung Teak

    2005-01-01

    In this study, an advanced condition monitoring technique based on acoustic emission (AE) detection and artificial neural networks was applied to a check valve, one of the components being used extensively in a safety system of a nuclear power plant (Npp). AE testing for a check valve under controlled flow loop conditions was performed to detect and evaluate disk movement for valve degradation such as wear and leakage due to foreign object interference in a check valve. It is clearly demonstrated that the evaluation of different types of failure modes such as disk wear and check valve leakage were successful by systematically analyzing the characteristics of various AE parameters. It is also shown that the leak size can be determined with an artificial neural network

  16. Applications of artificial intelligence technology to wastewater treatment fields in China

    Institute of Scientific and Technical Information of China (English)

    QING Xiao-xia; WANG Bo; MENG De-tao

    2005-01-01

    Current applications of artificial intelligence technology to wastewater treatment in China are summarized. Wastewater treatment plants use expert system mainly in the operation decision-making and fault diagnosis of system operation, use artificial neuron network for system modeling, water quality forecast and soft measure, and use fuzzy control technology for the intelligence control of wastewater treatment process. Finally, the main problems in applying artificial intelligence technology to wastewater treatment in China are analyzed.

  17. The Development of Radiation hardened tele-robot system - Development of artificial force reflection control for teleoperated mobile robots

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Ju Jang; Hong, Sun Gi; Kang, Young Hoon; Kim, Min Soeng [Korea Advanced Institute of Science and Technology, Taejon (Korea)

    1999-04-01

    One of the most important issues in teleoperation is to provide the sense of telepresence so as to conduct the task more reliably. In particular, teleoperated mobile robots are needed to have some kinds of backup system when the operator is blind for remote situation owing to the failure of vision system. In the first year, the idea of artificial force reflection was researched to enhance the reliability of operation when the mobile robot travels on the plain ground. In the second year, we extend previous results to help the teleoperator even when the robot climbs stairs. Finally, we apply the developed control algorithms to real experiments. The artificial force reflection method has two modes; traveling on the plain ground and climbing stairs. When traveling on the plain ground, the force information is artificially generated by using the range data from the environment while generating the impulse force when climbing stairs. To verify the validity of our algorithm, we develop the simulator which consists of the joystick and the visual display system. Through some experiments using this system, we confirm the validity and effectiveness of our new idea of artificial force reflection in the teleoperated mobile robot. 11 refs., 30 figs. (Author)

  18. Distinguishing of artificial irradiation by α dose: a method of discriminating imitations of ancient pottery

    International Nuclear Information System (INIS)

    Wang Weida; Xia Junding; Zhou Zhixin; Leung, P.L.

    2003-01-01

    If a modern pottery is artificially irradiated by γ-rays of 60 Co source, the modern will become ancient when the pottery is dated by the thermoluminescence technique. For distinguishing artificial irradiation a study was made. Meanwhile the 'fine-grain' and 'pre-dose' techniques were used respectively for measurement of the paleodose in a fine-grain sample from the same pottery. If the paleodose measured by the fine-grain technique is greater than that by the pre-dose techniques, we can affirm that the difference between two paleodoses is due to α dose and this paleodose containing α component results from natural radiation, the pottery therefore is ancient. If two paleodoses are equal approximately, i.e. α dose is not included in the paleodose, the paleodose comes from artificial γ irradiation and the pottery is an imitation

  19. A novel technique for active vibration control, based on optimal

    Indian Academy of Sciences (India)

    In the last few decades, researchers have proposed many control techniques to suppress unwanted vibrations in a structure. In this work, a novel and simple technique is proposed for the active vibration control. In this technique, an optimal tracking control is employed to suppress vibrations in a structure by simultaneously ...

  20. Artificial intelligence aid to efficient plant operations

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  1. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

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

  2. Fuzzy logic and neural networks in artificial intelligence and pattern recognition

    Science.gov (United States)

    Sanchez, Elie

    1991-10-01

    With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

  3. Wains: a pattern-seeking artificial life species.

    Science.gov (United States)

    de Buitléir, Amy; Russell, Michael; Daly, Mark

    2012-01-01

    We describe the initial phase of a research project to develop an artificial life framework designed to extract knowledge from large data sets with minimal preparation or ramp-up time. In this phase, we evolved an artificial life population with a new brain architecture. The agents have sufficient intelligence to discover patterns in data and to make survival decisions based on those patterns. The species uses diploid reproduction, Hebbian learning, and Kohonen self-organizing maps, in combination with novel techniques such as using pattern-rich data as the environment and framing the data analysis as a survival problem for artificial life. The first generation of agents mastered the pattern discovery task well enough to thrive. Evolution further adapted the agents to their environment by making them a little more pessimistic, and also by making their brains more efficient.

  4. Fault detection and diagnosis using statistical control charts and artificial neural networks

    International Nuclear Information System (INIS)

    Leger, R.P.; Garland, W.J.; Poehlman, W.F.S.

    1995-01-01

    In order to operate a successful plant or process, continuous improvement must be made in the areas of safety, quality and reliability. Central to this continuous improvement is the early or proactive detection and correct diagnosis of process faults. This research examines the feasibility of using Cumulative Summation (CUSUM) Control Charts and artificial neural networks together for fault detection and diagnosis (FDD). The proposed FDD strategy was tested on a model of the heat transport system of a CANDU nuclear reactor. The results of the investigation indicate that a FDD system using CUSUM Control Charts and a Radial Basis Function (RBF) neural network is not only feasible but also of promising potential. The control charts and neural network are linked together by using a characteristic fault signature pattern for each fault which is to be detected and diagnosed. When tested, the system was able to eliminate all false alarms at steady state, promptly detect 6 fault conditions and correctly diagnose 5 out of the 6 faults. The diagnosis for the sixth fault was inconclusive. (author). 9 refs., 6 tabs., 7 figs

  5. An artificial ecosystem model used in the study of social, economic and technological dynamics: An artificial electrical energy market

    International Nuclear Information System (INIS)

    Arjona, D.

    1998-01-01

    This paper will present the artificial ecosystem as a tool, in the development of multi agent models for the simulation of economic and technological dynamics (as well as other possible applications). This tool is based on the mechanics of an artificial society and consists of autonomous artificial agents that interact with individuals that have different characteristics and behavior and other that have a similar conduct to their own. Initial conditions are assumed not to be controllable, however they can be influenced. The importance of the concept of the ecosystem is in understanding great units in the light of their own components which are relevant for the analysis and become interdependent among themselves and with other essential components that hold the total operation of the system. Ideas for the development of a simulation model based on autonomous intelligent agents are presented. These agents will have a brain that is based on artificial intelligence technologies. The Sand Kings Simulation Model, an artificial ecosystem model developed by the author, is described as well as the application of artificial intelligence to this artificial life model. An application to a real life problem is also offered as an artificial energy market that is currently being developed by the author is described

  6. The Potential of AI Techniques for Remote Sensing

    Science.gov (United States)

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

    1984-01-01

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

  7. Artificial Consciousness or Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Spanache Florin

    2017-05-01

    Full Text Available Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus automatic. But conscience is above these differences because it is neither conditioned by the self-preservation of autonomy, because a conscience is something that you use to help your neighbor, nor automatic, because one’s conscience is tested by situations which are not similar or subject to routine. So, artificial intelligence is only in science-fiction literature similar to an autonomous conscience-endowed being. In real life, religion with its notions of redemption, sin, expiation, confession and communion will not have any meaning for a machine which cannot make a mistake on its own.

  8. Active load control techniques for wind turbines.

    Energy Technology Data Exchange (ETDEWEB)

    van Dam, C.P. (University of California, Davis, CA); Berg, Dale E.; Johnson, Scott J. (University of California, Davis, CA)

    2008-07-01

    This report provides an overview on the current state of wind turbine control and introduces a number of active techniques that could be potentially used for control of wind turbine blades. The focus is on research regarding active flow control (AFC) as it applies to wind turbine performance and loads. The techniques and concepts described here are often described as 'smart structures' or 'smart rotor control'. This field is rapidly growing and there are numerous concepts currently being investigated around the world; some concepts already are focused on the wind energy industry and others are intended for use in other fields, but have the potential for wind turbine control. An AFC system can be broken into three categories: controls and sensors, actuators and devices, and the flow phenomena. This report focuses on the research involved with the actuators and devices and the generated flow phenomena caused by each device.

  9. Measure of pore size in micro filtration polymeric membrane using ultrasonic technique and artificial neural networks

    International Nuclear Information System (INIS)

    Lucas, Carla de Souza

    2009-01-01

    This work presents a study of the pore size in micro filtration polymeric membranes, used in the nuclear area for the filtration of radioactive liquid effluent, in the residual water treatment of the petrochemical industry, in the electronic industry for the ultrapure water production for the manufacture of conductors and laundering of microcircuits and in many other processes of separation. Diverse processes for measures of pores sizes in membranes exist, amongst these, electronic microscopy, of bubble point and mercury intrusion porosimetry, however the majority of these uses destructive techniques, of high cost or great time of analysis. The proposal of this work is to measure so great of pore being used ultrasonic technique in the time domain of the frequency and artificial neural networks. A receiving/generator of ultrasonic pulses, a immersion transducer of 25 MHz was used, a tank of immersion and microporous membranes of pores sizes of 0,2 μm, 0,4 μm, 0,6 μm, 8 μm, 10 μm and 12 μm. The ultrasonic signals after to cover the membrane, come back to the transducer (emitting/receiving) bringing information of the interaction of the signal with the membranes. These signals had been used for the training of neural networks, and these had supplied the necessary precision the distinction of the same ones. Soon after, technique with the one of electronic microscopy of sweepings was made the comparison of this. The experiment showed very resulted next to the results gotten with the MEV, what it indicated that the studied technique is ideal for measure of pore size in membranes for being not destructive and of this form to be able to be used also on-line of production. (author)

  10. Operant Conditioning: A Minimal Components Requirement in Artificial Spiking Neurons Designed for Bio-Inspired Robot’s Controller

    Directory of Open Access Journals (Sweden)

    André eCyr

    2014-07-01

    Full Text Available We demonstrate the operant conditioning (OC learning process within a basic bio-inspired robot controller paradigm, using an artificial spiking neural network (ASNN with minimal component count as artificial brain. In biological agents, OC results in behavioral changes that are learned from the consequences of previous actions, using progressive prediction adjustment triggered by reinforcers. In a robotics context, virtual and physical robots may benefit from a similar learning skill when facing unknown environments with no supervision. In this work, we demonstrate that a simple ASNN can efficiently realise many OC scenarios. The elementary learning kernel that we describe relies on a few critical neurons, synaptic links and the integration of habituation and spike-timing dependent plasticity (STDP as learning rules. Using four tasks of incremental complexity, our experimental results show that such minimal neural component set may be sufficient to implement many OC procedures. Hence, with the described bio-inspired module, OC can be implemented in a wide range of robot controllers, including those with limited computational resources.

  11. Two applications of airtightness control techniques on big assemblies

    CERN Document Server

    Devallan, C; Marcellin, J

    1973-01-01

    Deals with two airtightness control techniques respectively applied on intersecting storage rings (ISR) at CERN in Geneva and on a liquid methane storage tank. These two big assemblies called for two different control techniques which use helium and ammonia respectively as tracer gas. Existing practical leakage detection techniques to meet industrial needs are discussed at the end of the article. (2 refs).

  12. Equilibria of a charged artificial satellite subject to gravitational and Lorentz torques

    International Nuclear Information System (INIS)

    Abdel-Aziz, Yehia A.; Shoaib, Muhammad

    2014-01-01

    The attitude dynamics of a rigid artificial satellite subject to a gravity gradient and Lorentz torques in a circular orbit are considered. Lorentz torque is developed on the basis of the electrodynamic effects of the Lorentz force acting on the charged satellite's surface. We assume that the satellite is moving in a Low Earth Orbit in the geomagnetic field, which is considered to be a dipole. Our model of torque due to the Lorentz force is developed for an artificial satellite with a general shape, and the nonlinear differential equations of Euler are used to describe its attitude orientation. All equilibrium positions are determined and conditions for their existence are obtained. The numerical results show that the charge q and radius ρ 0 of the center of charge for the satellite provide a certain type of semi-passive control for the attitude of the satellite. The technique for this kind of control would be to increase or decrease the electrostatic screening on the satellite. The results obtained confirm that the change in charge can affect the magnitude of the Lorentz torque, which can also affect control of the satellite. Moreover, the relationship between magnitude of the Lorentz torque and inclination of the orbit is investigated. (research papers)

  13. Equilibria of a charged artificial satellite subject to gravitational and Lorentz torques

    Science.gov (United States)

    Abdel-Aziz, Yehia A.; Shoaib, Muhammad

    2014-07-01

    The attitude dynamics of a rigid artificial satellite subject to a gravity gradient and Lorentz torques in a circular orbit are considered. Lorentz torque is developed on the basis of the electrodynamic effects of the Lorentz force acting on the charged satellite's surface. We assume that the satellite is moving in a Low Earth Orbit in the geomagnetic field, which is considered to be a dipole. Our model of torque due to the Lorentz force is developed for an artificial satellite with a general shape, and the nonlinear differential equations of Euler are used to describe its attitude orientation. All equilibrium positions are determined and conditions for their existence are obtained. The numerical results show that the charge q and radius ρ0 of the center of charge for the satellite provide a certain type of semi-passive control for the attitude of the satellite. The technique for this kind of control would be to increase or decrease the electrostatic screening on the satellite. The results obtained confirm that the change in charge can affect the magnitude of the Lorentz torque, which can also affect control of the satellite. Moreover, the relationship between magnitude of the Lorentz torque and inclination of the orbit is investigated.

  14. Application of artificial neural networks with backpropagation technique in the financial data

    Science.gov (United States)

    Jaiswal, Jitendra Kumar; Das, Raja

    2017-11-01

    The propensity of applying neural networks has been proliferated in multiple disciplines for research activities since the past recent decades because of its powerful control with regulatory parameters for pattern recognition and classification. It is also being widely applied for forecasting in the numerous divisions. Since financial data have been readily available due to the involvement of computers and computing systems in the stock market premises throughout the world, researchers have also developed numerous techniques and algorithms to analyze the data from this sector. In this paper we have applied neural network with backpropagation technique to find the data pattern from finance section and prediction for stock values as well.

  15. State and data techniques for control of discontinuous systems

    International Nuclear Information System (INIS)

    Kisner, R.A.

    1986-01-01

    The need for automated control systems becomes clear as the complexity of nuclear power plants increases and economic incentives demand higher plant availability. A control system with intelligence distributed throughout its controllers allows reduction in operator workload, perhaps reduction in crew size, and potentially a reduction in on-line human error. In automated systems of this kind, each controller should be capable of making decisions and carrying out a plan of action. This paper describes a technique for structured analysis and design of automated control systems. The technique integrates control of continuous and discontinuous nuclear power plant subsystems and components. A hierarchical control system with distributed intelligence follows from applying the technique. Further, it can be applied to all phases of control system design. For simplicity, the example used in the paper is limited to phase I design (basic automatic control action), in which no maintenance, testing, or contingency capability is attempted

  16. Anti-tick monoclonal antibody applied by artificial capillary feeding in Rhipicephalus (Boophilus) microplus females.

    Science.gov (United States)

    Gonsioroski, Andressa Varella; Bezerra, Isis Abel; Utiumi, Kiyoko Uemura; Driemeier, David; Farias, Sandra Estrazulas; da Silva Vaz, Itabajara; Masuda, Aoi

    2012-04-01

    The tick Rhipicephalus microplus is an ectoparasite harmful to livestock, a vector of disease agents that affects meat and milk production. However, resistance to acaricides reflects the need for alternative tick control methods, among which vaccines have gained increasing relevance. In this scenario, monoclonal antibodies can be used to identify and characterize antigens that can be used as vaccine immunogens. Capillary tube artificial feeding of partially engorged R. microplus females with monoclonal antibodies against proteins from the gut of tick were used to test the effects of immunoglobulins in the physiology of the parasite. The results of artificial feeding showed that female ticks over 25mg and under 60 mg in weight performed better in the artificial feeding process, with a 94-168% weight increase after 24h of feeding. Results showed that artificial feeding of ticks proved to be a viable technique to study the effects of antibodies or drugs in the physiology of the parasite. One monoclonal antibody (BrBm2) induced decreased oviposition. Moreover, the antigen recognized by BrBm2 was identified as a 27-kDa protein and immunolabeled on digestive vesicles membranes of digestive cells of partially and fully engorged females. Copyright © 2012 Elsevier Inc. All rights reserved.

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

    OpenAIRE

    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

    2017-01-01

    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 priv...

  18. Artificial immune system algorithm in VLSI circuit configuration

    Science.gov (United States)

    Mansor, Mohd. Asyraf; Sathasivam, Saratha; Kasihmuddin, Mohd Shareduwan Mohd

    2017-08-01

    In artificial intelligence, the artificial immune system is a robust bio-inspired heuristic method, extensively used in solving many constraint optimization problems, anomaly detection, and pattern recognition. This paper discusses the implementation and performance of artificial immune system (AIS) algorithm integrated with Hopfield neural networks for VLSI circuit configuration based on 3-Satisfiability problems. Specifically, we emphasized on the clonal selection technique in our binary artificial immune system algorithm. We restrict our logic construction to 3-Satisfiability (3-SAT) clauses in order to outfit with the transistor configuration in VLSI circuit. The core impetus of this research is to find an ideal hybrid model to assist in the VLSI circuit configuration. In this paper, we compared the artificial immune system (AIS) algorithm (HNN-3SATAIS) with the brute force algorithm incorporated with Hopfield neural network (HNN-3SATBF). Microsoft Visual C++ 2013 was used as a platform for training, simulating and validating the performances of the proposed network. The results depict that the HNN-3SATAIS outperformed HNN-3SATBF in terms of circuit accuracy and CPU time. Thus, HNN-3SATAIS can be used to detect an early error in the VLSI circuit design.

  19. Coating membranes for a sorbent-based artificial liver: adsorption characteristics

    NARCIS (Netherlands)

    de Koning, H. W.; Chamuleau, R. A.; Bantjes, A.

    1982-01-01

    Techniques are described for the coating of sorbents to be used in an artificial liver support system based on mixed sorbent bed hemoperfusion. Activated charcoal has been coated with cellulose acetate (CA) by solvent evaporation. With Amberlite XAD-4, the Wurster technique was used for coating with

  20. Fluid-driven origami-inspired artificial muscles.

    Science.gov (United States)

    Li, Shuguang; Vogt, Daniel M; Rus, Daniela; Wood, Robert J

    2017-12-12

    Artificial muscles hold promise for safe and powerful actuation for myriad common machines and robots. However, the design, fabrication, and implementation of artificial muscles are often limited by their material costs, operating principle, scalability, and single-degree-of-freedom contractile actuation motions. Here we propose an architecture for fluid-driven origami-inspired artificial muscles. This concept requires only a compressible skeleton, a flexible skin, and a fluid medium. A mechanical model is developed to explain the interaction of the three components. A fabrication method is introduced to rapidly manufacture low-cost artificial muscles using various materials and at multiple scales. The artificial muscles can be programed to achieve multiaxial motions including contraction, bending, and torsion. These motions can be aggregated into systems with multiple degrees of freedom, which are able to produce controllable motions at different rates. Our artificial muscles can be driven by fluids at negative pressures (relative to ambient). This feature makes actuation safer than most other fluidic artificial muscles that operate with positive pressures. Experiments reveal that these muscles can contract over 90% of their initial lengths, generate stresses of ∼600 kPa, and produce peak power densities over 2 kW/kg-all equal to, or in excess of, natural muscle. This architecture for artificial muscles opens the door to rapid design and low-cost fabrication of actuation systems for numerous applications at multiple scales, ranging from miniature medical devices to wearable robotic exoskeletons to large deployable structures for space exploration. Copyright © 2017 the Author(s). Published by PNAS.

  1. An ankle-foot orthosis powered by artificial pneumatic muscles.

    Science.gov (United States)

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

    2005-05-01

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

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

    Science.gov (United States)

    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.

  3. A comparative study of the detectability of TMJ radiographic techniques for artificial mandibular condylar lesions

    International Nuclear Information System (INIS)

    Jeong, Hee Jeong; Jung, Yeon Hwa; Cho, Bong Hae

    1997-01-01

    The purpose of this study was to evaluate the detectability of various radiographic techniques for mandibular condylar lesions. Erosive lesion, osteophyte and flattening were formed on the artificial mandibular condyle, and panoramic, transcranial, transorbital radiography, lateral and frontal tomography were taken. The results were as follows; 1. The detectability for erosive lesions was superior in the order of frontal tomography (96%), lateral tomography (78%), transorbital (59%), transcranial (56%) and panoramic (48%) radiography. 2. The location of erosive lesion that showed the highest detectability was the medial third in panoramic, the lateral third in transcranial, the central portion of anteroposterior direction in transorbital, the central portion of mediolateral direction and the posterior third in lateral tomography. Frontal tomography disclosed all erosive lesions except one anterolateral lesion. 3. The detectability of osteophyte was 100% in lateral tomography, 78% in transcranial and 56% in panoramic radiography. 4. For flattening, lateral tomography showed the flattened condyle, but both panoramic and transcranial views showed only decreased bone density without the change of condylar shape.

  4. Mechanical characterization of PVA hydrogel to be used as artificial joint cartilage reinforced by irradiation techniques

    International Nuclear Information System (INIS)

    Bavaresco, Vanessa Petrilli; Zavaglia, Cecilia A.C.; Reis, Marcelo de Carvalho

    2002-01-01

    Crosslinked networks of polyvinyl alcohol (PVA) produced from PVA aqueous solution and induced by radiation has been recently developed, and their mechanical properties have been studied. These materials are too fragile to be useful for artificial joint cartilage applications, unless reinforced in some way. In this work, the mechanical resistance of PVA hydrogel produced by irradiation techniques was studied. Polyvinyl alcohol films from 15 and 20% w/w aqueous solutions were acetalized by immersing it in an acetalization bath containing aqueous formaldehyde, sulfuric acid and sodium sulfate anhydrous (60:50:300 g) at 60 deg C. The acetalized samples were irradiated (Dynamitron (E = 1,5 MeV)) with 25, 50, 75, 100 kGy doses. Hydrogel samples were characterized by indentation creep test and water swelling. The results obtained in this study suggest the improving of the mechanical properties of the hydrogel by the combination of acetalization and electron beam irradiation, without decreasing in the swelling properties. (author)

  5. Artificial neural network control of sab dc/dc converter

    International Nuclear Information System (INIS)

    Mahar, M.A.; Abro, M.R.; Larik, A.S.

    2009-01-01

    The latest development of power semiconductor devices enable the modern power electronic converters to withstand high voltage and high power applications. Power electronic converters are mostly periodic variable structure systems due to their switched operations. The main drawback of these converters is the generation of oscillations which are developed during the operation of the converters under nonlinear situations. To handle these nonlinearities, various researchers have proposed different control techniques. Power electronic designers are devoting in the further development of converter topologies and their control techniques. SAB (Single Active Bridge) DC/DC converter is a new topology recently introduced by Demetriades. This topology is used in high voltage and high power applications. Because of its smart features, SAB converter has recently drawn attention of many researchers. However, during the operation of SAB converter severe oscillations are generated. In this research work, a novel NNC (Neural Network Controller) model is developed for SAB converter to minimize oscillations generated during its operation. NNC is believed to be an advanced nonlinear and robust controller which has the ability to map the nonlinear behaviour in a negligible response time. The performance of SAB converter with NNC is tested under dynamic region by considering the reference voltage variation and duty ratio variation. The SAB converter is implemented and simulated in MATLAB/Simulink. The simulated results are presented. (author)

  6. Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN Technique

    Directory of Open Access Journals (Sweden)

    Awatif Soaded Alsaqqar

    2016-06-01

    Full Text Available In this research an Artificial Neural Network (ANN technique was applied for the prediction of Ryznar Index (RI of the flowing water from WTPs in Al-Karakh side (left side in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3 have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For Al-Dora WTP, ANN 3 model could be used as R was 92.8%.

  7. Artificial locomotion control

    DEFF Research Database (Denmark)

    Azevedo, Christine; Poignet, Philippe; Espiau, Bernard

    2004-01-01

    of postural and walking control; use of evolutive optimization objectives; on-line event handling and environment adaptation and anticipation. This leads to the synthesis of an original control scheme based on non-linear model predictive control: Trajectory Free NMPC. The movement is specified implicitly......This paper concerns the simultaneous synthesis and control of walking gaits for biped robots. The goal is to propose an adaptable and reactive control law for two-legged machines. The problem is addressed with human locomotion as a reference. The starting point of our work is an analysis of human...... walking from descriptive (biomechanics) as well as explicative (neuroscience and physiology) points of view, the objective being to stress the relevant elements for the approach of robot control. The adopted principles are then: no joint trajectory tracking; explicit distinction and integration...

  8. Improvement in separation of isolated muons and pions at low pT in ATLAS hadron calorimeter using artificial neural networks technique

    International Nuclear Information System (INIS)

    Astvatsaturov, A.; Budagov, Yu.; Chirikov-Zorin, I.; Shigaev, V.; Paplevka, A.; Sushkov, S.; Bosman, M.; Nessi, M.

    1995-01-01

    Advantages of artificial neural networks techniques in handling data from highly granulated ATLAS hadron calorimeter (HC) are shown in application to isolated π/μ separation task in the range 3 T T muons have a significant probability to be absorbed in the calorimeter and therefore they cannot be reliably registered by the muon detector. The comparative analysis of main characteristics is presented for several neural net discriminators and a linear threshold discriminator operating on energy deposition in the last depth of HC. The analysis is based on MC data obtained with ATLAS simulation programs. 9 refs., 12 figs

  9. Modular design of artificial tissue homeostasis: robust control through synthetic cellular heterogeneity.

    Directory of Open Access Journals (Sweden)

    Miles Miller

    Full Text Available Synthetic biology efforts have largely focused on small engineered gene networks, yet understanding how to integrate multiple synthetic modules and interface them with endogenous pathways remains a challenge. Here we present the design, system integration, and analysis of several large scale synthetic gene circuits for artificial tissue homeostasis. Diabetes therapy represents a possible application for engineered homeostasis, where genetically programmed stem cells maintain a steady population of β-cells despite continuous turnover. We develop a new iterative process that incorporates modular design principles with hierarchical performance optimization targeted for environments with uncertainty and incomplete information. We employ theoretical analysis and computational simulations of multicellular reaction/diffusion models to design and understand system behavior, and find that certain features often associated with robustness (e.g., multicellular synchronization and noise attenuation are actually detrimental for tissue homeostasis. We overcome these problems by engineering a new class of genetic modules for 'synthetic cellular heterogeneity' that function to generate beneficial population diversity. We design two such modules (an asynchronous genetic oscillator and a signaling throttle mechanism, demonstrate their capacity for enhancing robust control, and provide guidance for experimental implementation with various computational techniques. We found that designing modules for synthetic heterogeneity can be complex, and in general requires a framework for non-linear and multifactorial analysis. Consequently, we adapt a 'phenotypic sensitivity analysis' method to determine how functional module behaviors combine to achieve optimal system performance. We ultimately combine this analysis with Bayesian network inference to extract critical, causal relationships between a module's biochemical rate-constants, its high level functional behavior in

  10. Modular design of artificial tissue homeostasis: robust control through synthetic cellular heterogeneity.

    Science.gov (United States)

    Miller, Miles; Hafner, Marc; Sontag, Eduardo; Davidsohn, Noah; Subramanian, Sairam; Purnick, Priscilla E M; Lauffenburger, Douglas; Weiss, Ron

    2012-01-01

    Synthetic biology efforts have largely focused on small engineered gene networks, yet understanding how to integrate multiple synthetic modules and interface them with endogenous pathways remains a challenge. Here we present the design, system integration, and analysis of several large scale synthetic gene circuits for artificial tissue homeostasis. Diabetes therapy represents a possible application for engineered homeostasis, where genetically programmed stem cells maintain a steady population of β-cells despite continuous turnover. We develop a new iterative process that incorporates modular design principles with hierarchical performance optimization targeted for environments with uncertainty and incomplete information. We employ theoretical analysis and computational simulations of multicellular reaction/diffusion models to design and understand system behavior, and find that certain features often associated with robustness (e.g., multicellular synchronization and noise attenuation) are actually detrimental for tissue homeostasis. We overcome these problems by engineering a new class of genetic modules for 'synthetic cellular heterogeneity' that function to generate beneficial population diversity. We design two such modules (an asynchronous genetic oscillator and a signaling throttle mechanism), demonstrate their capacity for enhancing robust control, and provide guidance for experimental implementation with various computational techniques. We found that designing modules for synthetic heterogeneity can be complex, and in general requires a framework for non-linear and multifactorial analysis. Consequently, we adapt a 'phenotypic sensitivity analysis' method to determine how functional module behaviors combine to achieve optimal system performance. We ultimately combine this analysis with Bayesian network inference to extract critical, causal relationships between a module's biochemical rate-constants, its high level functional behavior in isolation, and

  11. Developed adaptive neuro-fuzzy algorithm to control air conditioning ...

    African Journals Online (AJOL)

    The paper developed artificial intelligence technique adaptive neuro-fuzzy controller for air conditioning systems at different pressures. The first order Sugeno fuzzy inference system was implemented and utilized for modeling and controller design. In addition, the estimation of the heat transfer rate and water mass flow rate ...

  12. Reduction of herbivorous fish pressure can facilitate focal algal species forestation on artificial structures.

    Science.gov (United States)

    Gianni, Fabrizio; Bartolini, Fabrizio; Airoldi, Laura; Mangialajo, Luisa

    2018-07-01

    Coastal areas have been transformed worldwide by urbanization, so that artificial structures are now widespread. Current coastal development locally depletes many native marine species, while offering limited possibilities for their expansion. Eco-engineering interventions intend to identify ways to facilitate the presence of focal species and their associated functions on artificial habitats. An important but overlooked factor controlling restoration operations is overgrazing by herbivores. The aim of this study was to quantify the effects of different potential feeders on Cystoseira amentacea, a native canopy-forming alga of the Mediterranean infralittoral fringe, and test whether manipulation of grazing pressure can facilitate the human-guided installation of this focal species on coastal structures. Results of laboratory tests and field experiments revealed that Sarpa salpa, the only strictly native herbivorous fish in the Western Mediterranean Sea, can be a very effective grazer of C. amentacea in artificial habitats, up to as far as the infralittoral fringe, which is generally considered less accessible to fishes. S. salpa can limit the success of forestation operations in artificial novel habitats, causing up to 90% of Cystoseira loss after a few days. Other grazers, such as limpets and crabs, had only a moderate impact. Future engineering operations,intended to perform forestation of canopy-forming algae on artificial structures, should consider relevant biotic factors, such as fish overgrazing, identifying cost-effective techniques to limit their impact, as is the usual practice in restoration programmes on land. Copyright © 2018 Elsevier Ltd. All rights reserved.

  13. Side-scan sonar techniques for the characterization of physical properties of artificial benthic habitats

    Directory of Open Access Journals (Sweden)

    Wen-Miin Tian

    2011-01-01

    Full Text Available Side-scan sonar observations conducted at Mito artificial habitat site in the southwest coast off Taiwan, documented the locations of both concrete cubic blocks (more than 10,000 units and scrapped steel boats (39 units deployed previously. Based on their geographic locations, the concrete cubic artificial reefs could be grouped into 14 reef sets. About 30% of the reefs were deployed out of the promulgated site area. For the purpose of artificial habitat site identification and fishery resources management, a database structure was designed to accommodate types and positions of reefs, information of reef sets, bathymetric contours, textures of bottom sediments and geomorphological characteristics. The effectiveness of Mito artificial habitat site was evaluated to be positive after the deployment of both concrete block reefs and steel boat reefs.Observações com sonar de varredura lateral ao largo de Mito na costa sudoeste de Taiwan, revelou a localização de mais de 10.000 blocos de concreto e 39 embarcações de ferro assentados previamente como recifes artificiais. Com base nas imagens obtidas, os cubos de concreto formam 14 grupos separados. Cerca de 30% das unidades de concreto foram assentadas fora das áreas previstas. Para a identificacão correta dos recifes artificiais e manejo adequado dos recursos pesqueiros, foi organizada uma base de dados com informações sobre forma, materiais e posição, e arranjo espacial das unidades recifais, bem como dados de batimetria, natureza do sedimento do fundo e geomorfologia. A eficiência dos recifes artificiais de Mito foi avaliada positivamente após o assentamento tanto das unidades de concreto quanto das embarcações de ferro.

  14. Establishing structure-property correlations and classification of base oils using statistical techniques and artificial neural networks

    International Nuclear Information System (INIS)

    Kapur, G.S.; Sastry, M.I.S.; Jaiswal, A.K.; Sarpal, A.S.

    2004-01-01

    The present paper describes various classification techniques like cluster analysis, principal component (PC)/factor analysis to classify different types of base stocks. The API classification of base oils (Group I-III) has been compared to a more detailed NMR derived chemical compositional and molecular structural parameters based classification in order to point out the similarities of the base oils in the same group and the differences between the oils placed in different groups. The detailed compositional parameters have been generated using 1 H and 13 C nuclear magnetic resonance (NMR) spectroscopic methods. Further, oxidation stability, measured in terms of rotating bomb oxidation test (RBOT) life, of non-conventional base stocks and their blends with conventional base stocks, has been quantitatively correlated with their 1 H NMR and elemental (sulphur and nitrogen) data with the help of multiple linear regression (MLR) and artificial neural networks (ANN) techniques. The MLR based model developed using NMR and elemental data showed a high correlation between the 'measured' and 'estimated' RBOT values for both training (R=0.859) and validation (R=0.880) data sets. The ANN based model, developed using fewer number of input variables (only 1 H NMR data) also showed high correlation between the 'measured' and 'estimated' RBOT values for training (R=0.881), validation (R=0.860) and test (R=0.955) data sets

  15. Politetrafluorene suture used as artificial mitral chord: mechanical properties and surgical implications.

    Science.gov (United States)

    Caimmi, Philippe P; Sabbatini, Maurizio; Fusaro, Luca; Cannas, Mario

    2017-12-01

    Novel surgical approach to repair degenerative mitral regurgitation such as transapical chordae tendineae replacement and "loop in loop" in loop techniques, need of artificial chordae longer than that used in the older techniques of chordae tendineae replacement. This difference in length has been reported as potential critical point for durability of artificial chordae. In the present paper we have investigated the elastic behavior of different diameter and length politetrafluorene (PTFE) suture threads as substitute of native chordae, to identify their reliability to use as long artificial chordae. PTFE suture threads with different diameters were investigated in their mechanical properties at different length from 2 to 14 cm, by a servo hydraulic testing machine, to test the elastic properties of the sample in their use as mitral chordae substitutes. Our study shows that the chordae length is an important parameter that can change the performance of chordae itself. The analysis of elastic/properties of suture threads specimen, reveals that long PTFE chords have an optimal mechanical behavior in which elongation is accompanied by a safe elastic properties that make them well resistance during multiple tractions. In conclusion the use of PTFE as an artificial chordae may represent a valid choice in case of insertion of artificial chordae with extra anatomic length.

  16. The digital geometric phase technique applied to the deformation evaluation of MEMS devices

    International Nuclear Information System (INIS)

    Liu, Z W; Xie, H M; Gu, C Z; Meng, Y G

    2009-01-01

    Quantitative evaluation of the structure deformation of microfabricated electromechanical systems is of importance for the design and functional control of microsystems. In this investigation, a novel digital geometric phase technique was developed to meet the deformation evaluation requirement of microelectromechanical systems (MEMS). The technique is performed on the basis of regular artificial lattices, instead of a natural atom lattice. The regular artificial lattices with a pitch ranging from micrometer to nanometer will be directly fabricated on the measured surface of MEMS devices by using a focused ion beam (FIB). Phase information can be obtained from the Bragg filtered images after fast Fourier transform (FFT) and inverse fast Fourier transform (IFFT) of the scanning electronic microscope (SEM) images. Then the in-plane displacement field and the local strain field related to the phase information will be evaluated. The obtained results show that the technique can be well applied to deformation measurement with nanometer sensitivity and stiction force estimation of a MEMS device

  17. Light and architecture. Daylight - artificial light - energy; Licht und Architektur. Tageslicht - Kunstlicht - Energie

    Energy Technology Data Exchange (ETDEWEB)

    Wambsganss, M. (ed.) [ip5 ingenieurpartnerschaft, Karlsruhe (Germany)]|[Fachhochschule Rosenheim (Germany)

    2007-07-01

    The symposium intends to provide scientific and technical fundamentals for room lighting with daylight. Daylight deflection systems and artificial light control systems were analyzed for this purpose, and a catalogue of criteria was established. Planners were given tools for projecting daylight control systems. Builder-owners received the fundamentals for economic assessment of combined daylight and artificial light illumination systems, while industrial producers obtained information for further development to maturity and for marketing of daylight-dependent artificial light control systems. (GL)

  18. Methodological vs. strategic control in artificial grammar learning: A commentary on Norman, Price and Jones (2011).

    Science.gov (United States)

    Jiménez, Luis

    2011-12-01

    Norman et al. (2011) reported that participants exposed in succession to two artificial grammars could be able to learn implicitly about them, and could apply their knowledge strategically to select which string corresponds to one of these two grammars. In this commentary, I identify an artifact that could account for the learning obtained not only in this study, but also in some previous studies using the same procedures. I claim that more methodological control is needed before jumping to conclusions on the kind of strategic control that could be achieved unconsciously. Copyright © 2011 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    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.

  20. Artificial intelligence applied to fuel management in BWR type reactors; Inteligencia artificial aplicada a la administracion de combustible en reactores BWR

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz S, J.J

    1998-10-01

    In this work two techniques of artificial intelligence, neural networks and genetic algorithms were applied to a practical problem of nuclear fuel management; the determination of the optimal fuel reload for a BWR type reactor. This is an important problem in the design of the operation cycle of the reactor. As a result of the application of these techniques, comparable or even better reloads proposals than those given by expert companies in the subject were obtained. Additionally, two other simpler problems in reactor physics were solved: the determination of the axial power profile and the prediction of the value of some variables of interest at the end of the operation cycle of the reactor. Neural networks and genetic algorithms have been applied to solve many problems of engineering because of their versatility but they have been rarely used in the area of fuel management. The results obtained in this thesis indicates the convenience of undertaking further work on this area and suggest the application of these techniques of artificial intelligence to the solution of other problems in nuclear reactor physics. (Author)

  1. Artificial fingerprint recognition by using optical coherence tomography with autocorrelation analysis

    Science.gov (United States)

    Cheng, Yezeng; Larin, Kirill V.

    2006-12-01

    Fingerprint recognition is one of the most widely used methods of biometrics. This method relies on the surface topography of a finger and, thus, is potentially vulnerable for spoofing by artificial dummies with embedded fingerprints. In this study, we applied the optical coherence tomography (OCT) technique to distinguish artificial materials commonly used for spoofing fingerprint scanning systems from the real skin. Several artificial fingerprint dummies made from household cement and liquid silicone rubber were prepared and tested using a commercial fingerprint reader and an OCT system. While the artificial fingerprints easily spoofed the commercial fingerprint reader, OCT images revealed the presence of them at all times. We also demonstrated that an autocorrelation analysis of the OCT images could be potentially used in automatic recognition systems.

  2. An example of the use of the DELPHI method: future prospects of artificial heart techniques in France; Un exemple d'utilisation de la methode DELPHI: perspectives de developpement en France des techniques de coeur artificiel

    Energy Technology Data Exchange (ETDEWEB)

    Derian, Jean-Claude [Commissariat a l' energie atomique et aux energies alternatives - CEA, Centre d' Etudes Nucleaires de Fontenay-aux-Roses, Departement des Programmes, Section des Etudes Economiques Generales (France); Morize, Francoise [Commissariat a l' energie atomique et aux energies alternatives - CEA, Centre d' Etudes Nucleaires de Saclay, Institut National des Sciences et Techniques Nucleaires (France); Vernejoul, Pierre de [Faculte de Medecine Necker - Enfants Malades (France); Service Hospitalier Frederic Joliot (France); Vial, Renee [Direction de Protection et Surete Radiologiques (France)

    1971-07-01

    The artificial heart is still only a research project surrounded by numerous uncertainties which make it very difficult to estimate, at the moment, the possibilities for future development of this technique in France. A systematic analysis of the hazards which characterize this project has been undertaken in the following report: restricting these uncertainties has required a taking into account of opinions of specialists concerned with type of research or its upshot. We have achieved this by adapting an investigation technique which is still unusual in France, the DELPHI method. This adaptation has allowed the confrontation and statistical aggregation of the opinions given by a body of a hundred experts who were consulted through a program of sequential interrogations which studied in particular, the probable date of the research issue, the clinical cases which require the use of an artificial heart, as well as the probable future needs. After having taken into account the economic constraints, we can deduce from these results the probable amount of plutonium 238 needed in the hypothesis where isotopic generator would be retained for the energetics feeding of the artificial heart [French] Le coeur artificiel n'est encore actuellement qu'un projet de recherche auquel sont attachees de nombreuses incertitudes qui rendent difficile l'appreciation des possibilites de developpement futures de cette technique en France. Une analyse systematique des aleas qui caracterisent ce projet est entreprise dans l'etude ci-apres: circonscrire ces aleas necessite la prise en compte d'opinions emanant des specialistes concernes par cette recherche ou par son issue: c'est ce qui a ete realise en adaptant une methodologie non classique en France, la methode DELPHI. Cette adaptation a permis la confrontation et l'agregation statistique des opinions fournies par un college d'une centaine d'experts consultes par un programme d'interrogations sequentielles, envisageant en particulier les

  3. Optical effects of different colors of artificial gingiva on ceramic crowns.

    Science.gov (United States)

    Wang, Jian; Lin, Jin; Gil, Mindy; Da Silva, John D; Wright, Robert; Ishikawa-Nagai, Shigemi

    2013-08-01

    The interaction between gingival color and the shade of ceramic restorations has never been fully studied. The purpose of this study is to investigate the optical effects of altering artificial gingival color on the ceramic crown shade in the cervical area. Thirty-one all-ceramic crowns of different shades were used in this study with six different artificial gingival colors. Using a spectrophotometer (Crystaleye(®) Olympus, Japan), we measured the shade of crowns in cervical areas with each of six different artificial gingiva. The crown color measured in the presence of pink artificial gingiva (control) was compared with the crown color with five other artificial gingiva. color difference values ΔE* were calculated and compared between the control group and test groups and the correlation of the artificial gingival color with the crown color was also assessed. Significant differences were found in the mean L* and a* values of all-ceramic crowns at the cervical regions in all six gingival color groups (pcolors of artificial gingiva generated clinically detectable shade differences in the cervical region of ceramic crowns. Copyright © 2013. Published by Elsevier Ltd.

  4. A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242

    Directory of Open Access Journals (Sweden)

    Ahmed R. J. Almusawi

    2016-01-01

    Full Text Available This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot’s joint angles.

  5. A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)

    Science.gov (United States)

    Dülger, L. Canan; Kapucu, Sadettin

    2016-01-01

    This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot's joint angles. PMID:27610129

  6. A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242).

    Science.gov (United States)

    Almusawi, Ahmed R J; Dülger, L Canan; Kapucu, Sadettin

    2016-01-01

    This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot's joint angles.

  7. Neural Networks for Modeling and Control of Particle Accelerators

    Science.gov (United States)

    Edelen, A. L.; Biedron, S. G.; Chase, B. E.; Edstrom, D.; Milton, S. V.; Stabile, P.

    2016-04-01

    Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. The purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

  8. Artificial Intelligence and Spacecraft Power Systems

    Science.gov (United States)

    Dugel-Whitehead, Norma R.

    1997-01-01

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

  9. Preliminary Experimental Results on the Technique of Artificial River Replenishment to Mitigate Sediment Loss Downstream Dams

    Science.gov (United States)

    Franca, M. J.; Battisacco, E.; Schleiss, A. J.

    2014-12-01

    The transport of sediments by water throughout the river basins, from the steep slopes of the upstream regions to the sea level, is recognizable important to keep the natural conditions of rivers with a role on their ecology processes. Over the last decades, a reduction on the supply of sand and gravel has been observed downstream dams existing in several alpine rivers. Many studies highlight that the presence of a dam strongly modifies the river behavior in the downstream reach, in terms of morphology and hydrodynamics, with consequences on local ecology. Sediment deficit, bed armoring, river incision and bank instability are the main effects which affect negatively the aquatic habitats and the water quality. One of the proposed techniques to solve the problem of sediment deficit downstream dams, already adopted in few Japanese and German rivers although on an unsatisfactory fashion, is the artificial replenishment of these. Generally, it was verified that the erosion of the replenishments was not satisfactory and the transport rate was not enough to move the sediments to sufficient downstream distances. In order to improve and to provide an engineering answer to make this technique more applicable, a series of laboratory tests are ran as preparatory study to understand the hydrodynamics of the river flow when the replenishment technique is applied. Erodible volumes, with different lengths and submergence conditions, reproducing sediment replenishments volumes, are positioned along a channel bank. Different geometrical combinations of erodible sediment volumes are tested as well on the experimental flume. The first results of the experimental research, concerning erosion time evolution, the influence of discharge and the distance travelled by the eroded sediments, will be presented and discussed.

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

    Science.gov (United States)

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

    2018-02-01

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

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

    Science.gov (United States)

    Bartlett, Roger

    2006-12-15

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

  12. Exploring expressivity and emotion with artificial voice and speech technologies.

    Science.gov (United States)

    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.

  13. Expertik: Experience with Artificial Intelligence and Mobile Computing

    Directory of Open Access Journals (Sweden)

    José Edward Beltrán Lozano

    2013-06-01

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

  14. Identification of cataract and post-cataract surgery optical images using artificial intelligence techniques.

    Science.gov (United States)

    Acharya, Rajendra Udyavara; Yu, Wenwei; Zhu, Kuanyi; Nayak, Jagadish; Lim, Teik-Cheng; Chan, Joey Yiptong

    2010-08-01

    Human eyes are most sophisticated organ, with perfect and interrelated subsystems such as retina, pupil, iris, cornea, lens and optic nerve. The eye disorder such as cataract is a major health problem in the old age. Cataract is formed by clouding of lens, which is painless and developed slowly over a long period. Cataract will slowly diminish the vision leading to the blindness. At an average age of 65, it is most common and one third of the people of this age in world have cataract in one or both the eyes. A system for detection of the cataract and to test for the efficacy of the post-cataract surgery using optical images is proposed using artificial intelligence techniques. Images processing and Fuzzy K-means clustering algorithm is applied on the raw optical images to detect the features specific to three classes to be classified. Then the backpropagation algorithm (BPA) was used for the classification. In this work, we have used 140 optical image belonging to the three classes. The ANN classifier showed an average rate of 93.3% in detecting normal, cataract and post cataract optical images. The system proposed exhibited 98% sensitivity and 100% specificity, which indicates that the results are clinically significant. This system can also be used to test the efficacy of the cataract operation by testing the post-cataract surgery optical images.

  15. Artificial Satellites and How to Observe Them

    CERN Document Server

    Schmude, Jr , Richard

    2012-01-01

    Astronomers' Observing Guides provide up-to-date information for amateur astronomers who want to know all about what it is they are observing. This is the basis for the first part of the book. The second part details observing techniques for practical astronomers, working with a range of different instruments. Every amateur astronomer sees "stars" that aren't natural objects steadily slide across the background of the sky. Artificial satellites can be seen on any night, and some are as bright as the planets. But can you identify which satellite or spent launch vehicle casing you are seeing? Do you know how to image it? Artificial Satellites and How to Observe Them describes all of the different satellites that can be observed, including communication, scientific, spy satellites, and of course, the International Space Station. Richard Schmude describes how to recognize them and even how to predict their orbits. The book tells how to observe artificial satellites with the unaided eye, binoculars and with telesc...

  16. Engineering a Light-Attenuating Artificial Iris

    Science.gov (United States)

    Shareef, Farah J.; Sun, Shan; Kotecha, Mrignayani; Kassem, Iris; Azar, Dimitri; Cho, Michael

    2016-01-01

    Purpose Discomfort from light exposure leads to photophobia, glare, and poor vision in patients with congenital or trauma-induced iris damage. Commercial artificial iris lenses are static in nature to provide aesthetics without restoring the natural iris's dynamic response to light. A new photo-responsive artificial iris was therefore developed using a photochromic material with self-adaptive light transmission properties and encased in a transparent biocompatible polymer matrix. Methods The implantable artificial iris was designed and engineered using Photopia, a class of photo-responsive materials (termed naphthopyrans) embedded in polyethylene. Photopia was reshaped into annular disks that were spin-coated with polydimethylsiloxane (PDMS) to form our artificial iris lens of controlled thickness. Results Activated by UV and blue light in approximately 5 seconds with complete reversal in less than 1 minute, the artificial iris demonstrates graded attenuation of up to 40% of visible and 60% of UV light. There optical characteristics are suitable to reversibly regulate the incident light intensity. In vitro cell culture experiments showed up to 60% cell death within 10 days of exposure to Photopia, but no significant cell death observed when cultured with the artificial iris with protective encapsulation. Nuclear magnetic resonance spectroscopy confirmed these results as there was no apparent leakage of potentially toxic photochromic material from the ophthalmic device. Conclusions Our artificial iris lens mimics the functionality of the natural iris by attenuating light intensity entering the eye with its rapid reversible change in opacity and thus potentially providing an improved treatment option for patients with iris damage. PMID:27116547

  17. Engineering a Light-Attenuating Artificial Iris.

    Science.gov (United States)

    Shareef, Farah J; Sun, Shan; Kotecha, Mrignayani; Kassem, Iris; Azar, Dimitri; Cho, Michael

    2016-04-01

    Discomfort from light exposure leads to photophobia, glare, and poor vision in patients with congenital or trauma-induced iris damage. Commercial artificial iris lenses are static in nature to provide aesthetics without restoring the natural iris's dynamic response to light. A new photo-responsive artificial iris was therefore developed using a photochromic material with self-adaptive light transmission properties and encased in a transparent biocompatible polymer matrix. The implantable artificial iris was designed and engineered using Photopia, a class of photo-responsive materials (termed naphthopyrans) embedded in polyethylene. Photopia was reshaped into annular disks that were spin-coated with polydimethylsiloxane (PDMS) to form our artificial iris lens of controlled thickness. Activated by UV and blue light in approximately 5 seconds with complete reversal in less than 1 minute, the artificial iris demonstrates graded attenuation of up to 40% of visible and 60% of UV light. There optical characteristics are suitable to reversibly regulate the incident light intensity. In vitro cell culture experiments showed up to 60% cell death within 10 days of exposure to Photopia, but no significant cell death observed when cultured with the artificial iris with protective encapsulation. Nuclear magnetic resonance spectroscopy confirmed these results as there was no apparent leakage of potentially toxic photochromic material from the ophthalmic device. Our artificial iris lens mimics the functionality of the natural iris by attenuating light intensity entering the eye with its rapid reversible change in opacity and thus potentially providing an improved treatment option for patients with iris damage.

  18. Scientific approaches and techniques for negotiation : a game theoretic and artificial intelligence perspective

    NARCIS (Netherlands)

    E.H. Gerding (Enrico); D.D.B. van Bragt; J.A. La Poutré (Han)

    2000-01-01

    textabstractDue to the rapid growth of electronic environments (such as the Internet) much research is currently being performed on autonomous trading mechanisms. This report contains an overview of the current literature on negotiations in the fields of game theory and artificial intelligence (AI).

  19. Inteligência Artificial: uma aplicação em uma indústria de processo contínuo Artificial Intelligence: an application in a continuous process industry

    Directory of Open Access Journals (Sweden)

    Miguel Afonso Sellitto

    2002-12-01

    Full Text Available Este trabalho descreve uma aplicação da lógica fuzzy de controle e do CBR (Raciocínio Baseado em Casos na indústria de processo contínuo. Essas técnicas são discutidas dentro do campo de conhecimentos da Inteligência Artificial, associadas ao processo de tomada de decisões empresariais. A Inteligência Artificial é apontada como um campo de conhecimentos que pode apoiar a tomada de decisões de um modo mais simples e mais preciso do que outros métodos, tais como a modelagem e a gestão por indicadores. As etapas para a construção de um sistema especialista, construído principalmente a partir de experiências empíricas humanas, também são discutidas. O trabalho se encerra apresentando uma rotina de tomada de decisão em um processo termoquímico na indústria cimenteira conduzida por um sistema especialista baseado em CBR e lógica fuzzy, e uma discussão sobre resultados comparados com operadores humanos nas mesmas condições.This paper describes an application of the fuzzy logic control and CBR in the continuous process industry. The techniques are discussed inside the larger branch of knowledge called Artificial Intelligence (AI, which can be related with the decision-making process in companies. Artificial Intelligence is pinpointed as a science that can support decisions in an easier and more precisely way than others methods as models and process indicators management. The steps for the erection of an Expert System, built mainly from human empirical experiences, are also discussed. The paper comes to an end by presenting a decision-making routine in a thermochemical process, in the cement industry, as performed by an Expert System decision-maker, based in CBR and fuzzy logic, and leading to a discussion about results and performance gains, in comparison with human-guided action in the same process.

  20. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    Directory of Open Access Journals (Sweden)

    Daniel-Petru GHENCEA

    2017-06-01

    Full Text Available The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic. The paper presents a prediction mode obtaining valid range of values for spindles with similar characteristics based on measured data sets from a few spindles test without additional measures being required. Extracting polynomial functions of graphs resulting from simultaneous measurements and predict the dynamics of the two features with multi-objective criterion is the main advantage of this method.

  1. Active noise control technique and its application on ships

    Directory of Open Access Journals (Sweden)

    CHEN Kean

    2017-08-01

    Full Text Available Due to the rapid development during past three decades, Active Noise Control(ANC has become a highly complementary noise control approach in comparison with traditional approaches, and has formed a complete system including basic theory, investigation approach, key techniques and system implementation. Meanwhile, substantial progress has been achieved in such fields as the practical application, industrialization development and commercial popularization of ANC, and this developed technique provides a practical and feasible choice for the active control of ship noise. In this review paper, its sound field analysis, system setup and key techniques are summarized, typical examples of ANC-based engineering applications including control of cabin noise and duct noise are briefly described, and a variety of forefronts and problems associated with the applications of ANC in ship noise control, such as active sound absorption, active sound insulation and smart acoustic structure, are subsequently discussed.

  2. Implementation of a model reference adaptive control system using neural network to control a fast breeder reactor evaporator

    International Nuclear Information System (INIS)

    Ugolini, D.; Yoshikawa, S.; Endou, A.

    1994-01-01

    Artificial intelligence is foreseen as the base for new control systems aimed to replace traditional controllers and to assist and eventually advise plant operators. This paper discusses the development of an indirect model reference adaptive control (MRAC) system, using the artificial neural network (ANN) technique, and its implementation to control the outlet steam temperature of a sodium to water evaporator. The ANN technique is applied in the identification and in the control process of the indirect MRAC system. The emphasis is placed on demonstrating the efficacy of the indirect MRAC system in controlling the outlet steam temperature of the evaporator, and on showing the important function covered by the ANN technique. An important characteristic of this control system is that it relays only on some selected input variables and output variables of the evaporator model. These are the variables that can be actually measured or calculated in a real environment. The results obtained applying the indirect MRAC system to control the evaporator model are quite remarkable. The outlet temperature of the steam is almost perfectly kept close to its desired set point, when the evaporator is forced to depart from steady state conditions, either due to the variation of some input variables or due to the alteration of some of its internal parameters. The results also show the importance of the role played by the ANN technique in the overall control action. The connecting weights of the ANN nodes self adjust to follow the modifications which may occur in the characteristic of the evaporator model during a transient. The efficiency and the accuracy of the control action highly depends on the on-line identification process of the ANN, which is responsible for upgrading the connecting weights of the ANN nodes. (J.P.N.)

  3. Electrophotometric observations of artificial satellites

    International Nuclear Information System (INIS)

    Vovchyk, Yeva; Blagodyr, Yaroslav; Kraynyuk, Gennadiy; Bilinsky, Andriy; Lohvynenko, Alexander; Klym, Bogdan; Pochapsky, Yevhen

    2004-01-01

    Problems associated with polarimetric observations of low Earth orbit artificial satellites as important solar system objects are discussed. The instrumentation (the optical and mechanical parts, the control and drive electronics, and the application software) for performing such observations is also described

  4. Artificial skin and patient simulator comprising the artificial skin

    NARCIS (Netherlands)

    2011-01-01

    The invention relates to an artificial skin (10, 12, 14), and relates to a patient simulator (100) comprising the artificial skin. The artificial skin is a layered structure comprising a translucent cover layer (20) configured for imitating human or animal skin, and comprising a light emitting layer

  5. Neuro-prosthetic interplay. Comment on "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by M. Santello et al.

    Science.gov (United States)

    Schieber, Marc H.

    2016-07-01

    Control of the human hand has been both difficult to understand scientifically and difficult to emulate technologically. The article by Santello and colleagues in the current issue of Physics of Life Reviews[1] highlights the accelerating pace of interaction between the neuroscience of controlling body movement and the engineering of robotic hands that can be used either autonomously or as part of a motor neuroprosthesis, an artificial body part that moves under control from a human subject's own nervous system. Motor neuroprostheses typically involve a brain-computer interface (BCI) that takes signals from the subject's nervous system or muscles, interprets those signals through a decoding algorithm, and then applies the resulting output to control the artificial device.

  6. Antithrombotic artificial organs

    Energy Technology Data Exchange (ETDEWEB)

    Takamatsu, T; Fukada, E; Saegusa, M; Hasegawa, T

    1971-07-12

    A new antithrombotic material useful for making artificial organs (artificial blood vessel, artificial heart, etc.) can be prepared by graft-polymerizing an acrylic ester (methyl methacrylate, methyl acrylate, ethyl acrylate, etc.) with a synthetic fiber (teflon, etc.). The graft-polymerization can be carried out by means of gamma radiation with cobalt 60 (dose rate 2.6x10/sup 3/ r/min., total dose 8x10/sup 4/ to 3.5x10/sup 5/ r). A graft ratio of 5 to 80% is attainable. In one example, a tubular sample made of teflon fiber having an inner diameter of 5 to 10 mm was immersed into methyl methacrylate in an ampoule in the absence of air and exposed to cobalt 60 gamma ray at the dose rate of 3.18x10/sup 3/ rad/min. After extraction with acetone, the sample was dried. The total dose was 3.5x10/sup 5/ rad and the graft ratio was ca. 25%. The sample was transplanted to vena cava of dog. No formation of thrombus was observed by autopsy (4 months after the transplantation). In control (teflon tube not graft-polymerized) thrombus was observed by autopsy 7 days after the transplantation.

  7. Object oriented programming techniques applied to device access and control

    International Nuclear Information System (INIS)

    Goetz, A.; Klotz, W.D.; Meyer, J.

    1992-01-01

    In this paper a model, called the device server model, has been presented for solving the problem of device access and control faced by all control systems. Object Oriented Programming techniques were used to achieve a powerful yet flexible solution. The model provides a solution to the problem which hides device dependancies. It defines a software framework which has to be respected by implementors of device classes - this is very useful for developing groupware. The decision to implement remote access in the root class means that device servers can be easily integrated in a distributed control system. A lot of the advantages and features of the device server model are due to the adoption of OOP techniques. The main conclusion that can be drawn from this paper is that 1. the device access and control problem is adapted to being solved with OOP techniques, 2. OOP techniques offer a distinct advantage over traditional programming techniques for solving the device access problem. (J.P.N.)

  8. Artificial Intelligence.

    Science.gov (United States)

    Information Technology Quarterly, 1985

    1985-01-01

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

  9. Artificial neural networks for automation of Rutherford backscattering spectroscopy experiments and data analysis

    International Nuclear Information System (INIS)

    Barradas, N.P.; Vieira, A.; Patricio, R.

    2002-01-01

    We present an algorithm based on artificial neural networks able to determine optimized experimental conditions for Rutherford backscattering measurements of Ge-implanted Si. The algorithm can be implemented for any other element implanted into a lighter substrate. It is foreseeable that the method developed in this work can be applied to still many other systems. The algorithm presented is a push-button black box, and does not require any human intervention. It is thus suited for automated control of an experimental setup, given an interface to the relevant hardware. Once the experimental conditions are optimized, the algorithm analyzes the final data obtained, and determines the desired parameters. The method is thus also suited for automated analysis of the data. The algorithm presented can be easily extended to other ion beam analysis techniques. Finally, it is suggested how the artificial neural networks required for automated control and analysis of experiments could be automatically generated. This would be suited for automated generation of the required computer code. Thus could RBS be done without experimentalists, data analysts, or programmers, with only technicians to keep the machines running

  10. Artificial organs: recent progress in artificial hearing and vision.

    Science.gov (United States)

    Ifukube, Tohru

    2009-01-01

    Artificial sensory organs are a prosthetic means of sending visual or auditory information to the brain by electrical stimulation of the optic or auditory nerves to assist visually impaired or hearing-impaired people. However, clinical application of artificial sensory organs, except for cochlear implants, is still a trial-and-error process. This is because how and where the information transmitted to the brain is processed is still unknown, and also because changes in brain function (plasticity) remain unknown, even though brain plasticity plays an important role in meaningful interpretation of new sensory stimuli. This article discusses some basic unresolved issues and potential solutions in the development of artificial sensory organs such as cochlear implants, brainstem implants, artificial vision, and artificial retinas.

  11. Artificial intelligence and dynamic systems for geophysical applications

    CERN Document Server

    Gvishiani, Alexei

    2002-01-01

    The book presents new clustering schemes, dynamical systems and pattern recognition algorithms in geophysical, geodynamical and natural hazard applications. The original mathematical technique is based on both classical and fuzzy sets models. Geophysical and natural hazard applications are mostly original. However, the artificial intelligence technique described in the book can be applied far beyond the limits of Earth science applications. The book is intended for research scientists, tutors, graduate students, scientists in geophysics and engineers

  12. New computing techniques in physics research

    International Nuclear Information System (INIS)

    Perret-Gallix, D.; Wojcik, W.

    1990-01-01

    These proceedings relate in a pragmatic way the use of methods and techniques of software engineering and artificial intelligence in high energy and nuclear physics. Such fundamental research can only be done through the design, the building and the running of equipments and systems among the most complex ever undertaken by mankind. The use of these new methods is mandatory in such an environment. However their proper integration in these real applications raise some unsolved problems. Their solution, beyond the research field, will lead to a better understanding of some fundamental aspects of software engineering and artificial intelligence. Here is a sample of subjects covered in the proceedings : Software engineering in a multi-users, multi-versions, multi-systems environment, project management, software validation and quality control, data structure and management object oriented languages, multi-languages application, interactive data analysis, expert systems for diagnosis, expert systems for real-time applications, neural networks for pattern recognition, symbolic manipulation for automatic computation of complex processes

  13. Geochemical characterization of oceanic basalts using artificial neural network

    Digital Repository Service at National Institute of Oceanography (India)

    Das, P.; Iyer, S.D.

    method is specifically needed to identify the OFB as normal (N-MORB), enriched (E-MORB) and ocean island basalts (OIB). Artificial Neural Network (ANN) technique as a supervised Learning Vector Quantisation (LVQ) is applied to identify the inherent...

  14. Evaluation of Different Techniques of Active Thermography for Quantification of Artificial Defects in Fiber-Reinforced Composites Using Thermal and Phase Contrast Data Analysis

    Science.gov (United States)

    Maierhofer, Christiane; Röllig, Mathias; Gower, Michael; Lodeiro, Maria; Baker, Graham; Monte, Christian; Adibekyan, Albert; Gutschwager, Berndt; Knazowicka, Lenka; Blahut, Ales

    2018-05-01

    For assuring the safety and reliability of components and constructions in energy applications made of fiber-reinforced polymers (e.g., blades of wind turbines and tidal power plants, engine chassis, flexible oil and gas pipelines) innovative non-destructive testing methods are required. Within the European project VITCEA complementary methods (shearography, microwave, ultrasonics and thermography) have been further developed and validated. Together with partners from the industry, test specimens have been constructed and selected on-site containing different artificial and natural defect artefacts. As base materials, carbon and glass fibers in different orientations and layering embedded in different matrix materials (epoxy, polyamide) have been considered. In this contribution, the validation of flash and lock-in thermography to these testing problems is presented. Data analysis is based on thermal contrasts and phase evaluation techniques. Experimental data are compared to analytical and numerical models. Among others, the influence of two different types of artificial defects (flat bottom holes and delaminations) with varying diameters and depths and of two different materials (CFRP and GFRP) with unidirectional and quasi-isotropic fiber alignment is discussed.

  15. Artificial Promoters for Metabolic Optimization

    DEFF Research Database (Denmark)

    Jensen, Peter Ruhdal; Hammer, Karin

    1998-01-01

    In this article, we review some of the expression systems that are available for Metabolic Control Analysis and Metabolic Engineering, and examine their advantages and disadvantages in different contexts. In a recent approach, artificial promoters for modulating gene expression in micro-organisms...

  16. Marine litter prediction by artificial intelligence

    International Nuclear Information System (INIS)

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

    2004-01-01

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

  17. Marine litter prediction by artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-03-01

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

  18. Feeding Supplementation And Radioimmunoassay (RIA) Technique For The Improvement Of artificial Insemination (AI) Efficiency

    International Nuclear Information System (INIS)

    Tjiptosumirat, Totti; Supandi, Dadang; Firsoni

    2002-01-01

    Recent research activities have showed that RIA techniques may be use as a tool in the improvement of dairy cattle AI in . Cisurupan district, Garut. Although already indicate in the previous research, with a small number of dairy cattle tested, a more in depth study on the utilization of RIA for the improvement of AI efficiency is still required. It is indicated from the previous experiment results that administration of feeding supplementation might improved the efficiency of reproductive performance of dairy cattle. The current Study is a continuation from the previous study with a larger number of dairy cattle and wider area covered. The experiment is aimed to monitor the impact of feeding supplementation on the reproductive performance of dairy cattle using Artificial Insemination Database Application (AIDA) and RIA technique. Result from this study indicated that feeding supplementation improved conception rate between pre-supplemented and post-supplemented dairy cattle; 25% vs 40%, respectively, therefore improve ratio of Service per Conception of 4.0 vs 2.3, respectively for pre-supplemented and post-supplemented dairy cattle. Result of this experiment also showed that RIA might be use as an effective tool in monitoring the early failure of AI compared to if just relying on the conventional method, the rectal palpation. However, due to an increase in milk production as a result of feeding supplementation, tanners tend to lengthen the lactation period from 10.20 ± 0.5 months to 11.8 ± 0.6 months, respectively in dairy cattle pre-supplemented and post-supplemented. It can be conclude from this study that supplementation feeding improve reproductive performance. However, even AIDA and RIA may be of effective tool in monitoring the reproductive performance of dairy cattle, as an holistic approach for an improvement dairy farm management is still required due to other factors play important role for AI efficiency

  19. A quality by design approach using artificial intelligence techniques to control the critical quality attributes of ramipril tablets manufactured by wet granulation.

    Science.gov (United States)

    Aksu, Buket; Paradkar, Anant; de Matas, Marcel; Özer, Özgen; Güneri, Tamer; York, Peter

    2013-02-01

    Quality by design (QbD) is an essential part of the modern approach to pharmaceutical quality. This study was conducted in the framework of a QbD project involving ramipril tablets. Preliminary work included identification of the critical quality attributes (CQAs) and critical process parameters (CPPs) based on the quality target product profiles (QTPPs) using the historical data and risk assessment method failure mode and effect analysis (FMEA). Compendial and in-house specifications were selected as QTPPs for ramipril tablets. CPPs that affected the product and process were used to establish an experimental design. The results thus obtained can be used to facilitate definition of the design space using tools such as design of experiments (DoE), the response surface method (RSM) and artificial neural networks (ANNs). The project was aimed at discovering hidden knowledge associated with the manufacture of ramipril tablets using a range of artificial intelligence-based software, with the intention of establishing a multi-dimensional design space that ensures consistent product quality. At the end of the study, a design space was developed based on the study data and specifications, and a new formulation was optimized. On the basis of this formulation, a new laboratory batch formulation was prepared and tested. It was confirmed that the explored formulation was within the design space.

  20. Assist-as-Needed Control of a Robotic Orthosis Actuated by Pneumatic Artificial Muscle for Gait Rehabilitation

    Directory of Open Access Journals (Sweden)

    Quy-Thinh Dao

    2018-03-01

    Full Text Available Rehabilitation robots are designed to help patients improve their recovery from injury by supporting them to perform repetitive and systematic training sessions. These robots are not only able to guide the subjects’ lower-limb to a designate trajectory, but also estimate their disability and adapt the compliance accordingly. In this research, a new control strategy for a high compliant lower-limb rehabilitation orthosis system named AIRGAIT is developed. The AIRGAIT orthosis is powered by pneumatic artificial muscle actuators. The trajectory tracking controller based on a modified computed torque control which employs a fractional derivative is proposed for the tracking purpose. In addition, a new method is proposed for compliance control of the robotic orthosis which results in the successful implementation of the assist-as-needed training strategy. Finally, various subject-based experiments are carried out to verify the effectiveness of the developed control system.