Fluid intelligence and psychosocial outcome: from logical problem solving to social adaptation.

Directory of Open Access Journals (Sweden)

David Huepe

Full Text Available While fluid intelligence has proved to be central to executive functioning, logical reasoning and other frontal functions, the role of this ability in psychosocial adaptation has not been well characterized.A random-probabilistic sample of 2370 secondary school students completed measures of fluid intelligence (Raven's Progressive Matrices, RPM and several measures of psychological adaptation: bullying (Delaware Bullying Questionnaire, domestic abuse of adolescents (Conflict Tactic Scale, drug intake (ONUDD, self-esteem (Rosenberg's Self Esteem Scale and the Perceived Mental Health Scale (Spanish adaptation. Lower fluid intelligence scores were associated with physical violence, both in the role of victim and victimizer. Drug intake, especially cannabis, cocaine and inhalants and lower self-esteem were also associated with lower fluid intelligence. Finally, scores on the perceived mental health assessment were better when fluid intelligence scores were higher.Our results show evidence of a strong association between psychosocial adaptation and fluid intelligence, suggesting that the latter is not only central to executive functioning but also forms part of a more general capacity for adaptation to social contexts.

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.

Enhanced situation awareness and decision making for an intelligent reconfigurable reactor power controller

International Nuclear Information System (INIS)

Kenney, S.J.; Edwards, R.M.

1996-01-01

A Learning Automata based intelligent reconfigurable controller has been adapted for use as a reactor power controller to achieve improved reactor temperature performance. The intelligent reconfigurable controller is capable of enforcing either a classical or an optimal reactor power controller based on control performance feedback. Four control performance evaluation measures: dynamically estimated average quadratic temperature error, power, rod reactivity and rod reactivity rate were developed to provide feedback to the control decision component of the intelligent reconfigurable controller. Fuzzy Logic and Neural Network controllers have been studied for inclusion in the bank of controllers that form the intermediate level of an enhanced intelligent reconfigurable reactor power controller (IRRPC). The increased number of alternatives available to the supervisory level of the IRRPC requires enhanced situation awareness. Additional performance measures have been designed and a method for synthesizing them into a single indication of the overall performance of the currently enforced reactor power controller has been conceptualized. Modification of the reward/penalty scheme implemented in the existing IRRPC to increase the quality of the supervisory level decision process has been studied. The logogen model of human memory (Morton, 1969) and individual controller design information could be used to allocate reward to the most appropriate controller. Methods for allocating supervisory level attention were also studied with the goal of maximizing learning rate

Intelligent power plant simulator for educational purposes

International Nuclear Information System (INIS)

Seifi, A.; Seifi, H.; Ansari, M. R.; Parsa Moghaddam, M.

2001-01-01

An Intelligent Tutoring System can be effectively employed for a power plant simulator so that the need for instructor in minimized. In this paper using the above concept as well as object oriented programming and SIMULINK Toolbox of MATLAB, an intelligent tutoring power plant simulator is proposed. Its successful application on a typical 11 MW power plant is demonstrated

Adaptive Intelligent Ventilation Noise Control, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — To address the NASA need for quiet on-orbit crew quarters (CQ), Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...

Adaptive Intelligent Ventilation Noise Control, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — To address NASA needs for quiet crew volumes in a space habitat, Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...

Map Matching for Intelligent Speed Adaptation

DEFF Research Database (Denmark)

Tradisauskas, Nerius; Juhl, Jens; Lahrmann, Harry

2007-01-01

The availability of Global Navigation Satellite Systems enables sophisticated vehicle guidance and advisory systems such as Intelligent Speed Adaptation (ISA) systems. In ISA systems, it is essential to be able to position vehicles within a road network. Because digital road networks as well as G...

Intelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning

CERN Document Server

Demetriadis, Stavros; Xhafa, Fatos

2012-01-01

Adaptation and personalization have been extensively studied in CSCL research community aiming to design intelligent systems that adaptively support eLearning processes and collaboration. Yet, with the fast development in Internet technologies, especially with the emergence of new data technologies and the mobile technologies, new opportunities and perspectives are opened for advanced adaptive and personalized systems. Adaptation and personalization are posing new research and development challenges to nowadays CSCL systems. In particular, adaptation should be focused in a multi-dimensional way (cognitive, technological, context-aware and personal). Moreover, it should address the particularities of both individual learners and group collaboration. As a consequence, the aim of this book is twofold. On the one hand, it discusses the latest advances and findings in the area of intelligent adaptive and personalized learning systems. On the other hand it analyzes the new implementation perspectives for intelligen...

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

Wind power systems. Applications of computational intelligence

Energy Technology Data Exchange (ETDEWEB)

Wang, Lingfeng [Toledo Univ., OH (United States). Dept. of Electrical Engineering and Computer Science; Singh, Chanan [Texas A and M Univ., College Station, TX (United States). Electrical and Computer Engineering Dept.; Kusiak, Andrew (eds.) [Iowa Univ., Iowa City, IA (United States). Mechanical and Industrial Engineering Dept.

2010-07-01

Renewable energy sources such as wind power have attracted much attention because they are environmentally friendly, do not produce carbon dioxide and other emissions, and can enhance a nation's energy security. For example, recently more significant amounts of wind power are being integrated into conventional power grids. Therefore, it is necessary to address various important and challenging issues related to wind power systems, which are significantly different from the traditional generation systems. This book is a resource for engineers, practitioners, and decision-makers interested in studying or using the power of computational intelligence based algorithms in handling various important problems in wind power systems at the levels of power generation, transmission, and distribution. Researchers have been developing biologically-inspired algorithms in a wide variety of complex large-scale engineering domains. Distinguished from the traditional analytical methods, the new methods usually accomplish the task through their computationally efficient mechanisms. Computational intelligence methods such as evolutionary computation, neural networks, and fuzzy systems have attracted much attention in electric power systems. Meanwhile, modern electric power systems are becoming more and more complex in order to meet the growing electricity market. In particular, the grid complexity is continuously enhanced by the integration of intermittent wind power as well as the current restructuring efforts in electricity industry. Quite often, the traditional analytical methods become less efficient or even unable to handle this increased complexity. As a result, it is natural to apply computational intelligence as a powerful tool to deal with various important and pressing problems in the current wind power systems. This book presents the state-of-the-art development in the field of computational intelligence applied to wind power systems by reviewing the most up

Adaptation of the Wechsler Intelligence Scale for Children-IV (WISC-IV) for Vietnam.

Science.gov (United States)

Dang, Hoang-Minh; Weiss, Bahr; Pollack, Amie; Nguyen, Minh Cao

2012-12-01

Intelligence testing is used for many purposes including identification of children for proper educational placement (e.g., children with learning disabilities, or intellectually gifted students), and to guide education by identifying cognitive strengths and weaknesses so that teachers can adapt their instructional style to students' specific learning styles. Most of the research involving intelligence tests has been conducted in highly developed Western countries, yet the need for intelligence testing is as or even more important in developing countries. The present study, conducted through the Vietnam National University Clinical Psychology CRISP Center , focused on the cultural adaptation of the WISC-IV intelligence test for Vietnam. We report on (a) the adaptation process including the translation, cultural analysis and modifications involved in adaptation, (b) present results of two pilot studies, and (c) describe collection of the standardization sample and results of analyses with the standardization sample, with the goal of sharing our experience with other researchers who may be involved in or interested in adapting or developing IQ tests for non-Western, non-English speaking cultures.

Intelligent Navigation for a Solar Powered Unmanned Underwater Vehicle

Directory of Open Access Journals (Sweden)

Francisco García-Córdova

2013-04-01

Full Text Available In this paper, an intelligent navigation system for an unmanned underwater vehicle powered by renewable energy and designed for shadow water inspection in missions of a long duration is proposed. The system is composed of an underwater vehicle, which tows a surface vehicle. The surface vehicle is a small boat with photovoltaic panels, a methanol fuel cell and communication equipment, which provides energy and communication to the underwater vehicle. The underwater vehicle has sensors to monitor the underwater environment such as sidescan sonar and a video camera in a flexible configuration and sensors to measure the physical and chemical parameters of water quality on predefined paths for long distances. The underwater vehicle implements a biologically inspired neural architecture for autonomous intelligent navigation. Navigation is carried out by integrating a kinematic adaptive neuro-controller for trajectory tracking and an obstacle avoidance adaptive neuro- controller. The autonomous underwater vehicle is capable of operating during long periods of observation and monitoring. This autonomous vehicle is a good tool for observing large areas of sea, since it operates for long periods of time due to the contribution of renewable energy. It correlates all sensor data for time and geodetic position. This vehicle has been used for monitoring the Mar Menor lagoon.

Advance in study of intelligent diagnostic method for nuclear power plant

International Nuclear Information System (INIS)

Zhou Gang; Yang Li

2008-01-01

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

OPUS One: An Intelligent Adaptive Learning Environment Using Artificial Intelligence Support

Science.gov (United States)

Pedrazzoli, Attilio

2010-06-01

AI based Tutoring and Learning Path Adaptation are well known concepts in e-Learning scenarios today and increasingly applied in modern learning environments. In order to gain more flexibility and to enhance existing e-learning platforms, the OPUS One LMS Extension package will enable a generic Intelligent Tutored Adaptive Learning Environment, based on a holistic Multidimensional Instructional Design Model (PENTHA ID Model), allowing AI based tutoring and adaptation functionality to existing Web-based e-learning systems. Relying on "real time" adapted profiles, it allows content- / course authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The concept presented combines a personalized level of surveillance, learning activity- and learning path adaptation suggestions to ensure the students learning motivation and learning success. The OPUS One concept allows to implement an advanced tutoring approach combining "expert based" e-tutoring with the more "personal" human tutoring function. It supplies the "Human Tutor" with precise, extended course activity data and "adaptation" suggestions based on predefined subject matter rules. The concept architecture is modular allowing a personalized platform configuration.

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

Research on intelligent power distribution system for spacecraft

Science.gov (United States)

Xia, Xiaodong; Wu, Jianju

2017-10-01

The power distribution system (PDS) mainly realizes the power distribution and management of the electrical load of the whole spacecraft, which is directly related to the success or failure of the mission, and hence is an important part of the spacecraft. In order to improve the reliability and intelligent degree of the PDS, and considering the function and composition of spacecraft power distribution system, this paper systematically expounds the design principle and method of the intelligent power distribution system based on SSPC, and provides the analysis and verification of the test data additionally.

Discussion on technical intelligence of nuclear power industry

International Nuclear Information System (INIS)

Chen Ming

2010-01-01

The very Paper introduces the contemporary challenges faced by the profession of technical intelligence on nuclear power, and expatiates the functions of technical intelligence such as sources of experience feedback, background information and supports for decision-making. Afterwards, the Paper explains characteristics of technical intelligence and its working methods, i.e., quantitative changes to reach qualitative changes, approve-negate-approve and oppositeness unity of comprehensiveness and limitation of technical intelligence. (authors)

Functional requirements for an intelligent RPC. [remote power controller for spaceborne electrical distribution system

Science.gov (United States)

Aucoin, B. M.; Heller, R. P.

1990-01-01

An intelligent remote power controller (RPC) based on microcomputer technology can implement advanced functions for the accurate and secure detection of all types of faults on a spaceborne electrical distribution system. The intelligent RPC will implement conventional protection functions such as overcurrent, under-voltage, and ground fault protection. Advanced functions for the detection of soft faults, which cannot presently be detected, can also be implemented. Adaptive overcurrent protection changes overcurrent settings based on connected load. Incipient and high-impedance fault detection provides early detection of arcing conditions to prevent fires, and to clear and reconfigure circuits before soft faults progress to a hard-fault condition. Power electronics techniques can be used to implement fault current limiting to prevent voltage dips during hard faults. It is concluded that these techniques will enhance the overall safety and reliability of the distribution system.

Intelligent and Adaptive Educational-Learning Systems Achievements and Trends

CERN Document Server

2013-01-01

The Smart Innovation, Systems and Technologies book series encompasses the topics of knowledge, intelligence, innovation and sustainability. The aim of the series is to make available a platform for the publication of books on all aspects of single and multi-disciplinary research on these themes in order to make the latest results available in a readily-accessible form.  This book is devoted to the “Intelligent and Adaptive Educational-Learning Systems”. It privileges works that highlight key achievements and outline trends to inspire future research.  After a rigorous revision process twenty manuscripts were accepted and organized into four parts as follows: ·     Modeling: The first part embraces five chapters oriented to: 1) shape the affective behavior; 2) depict the adaptive learning curriculum; 3) predict learning achievements; 4) mine learner models to outcome optimized and adaptive e-learning objects; 5) classify learning preferences of learners. ·     Content: The second part encompas...

Intelligent distributed control for nuclear power plants

International Nuclear Information System (INIS)

Klevans, E.H.

1993-01-01

This project was initiated in September 1989 as a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. There were two primary goals of this research project. The first goal was to combine diagnostics and control to achieve a highly automated power plant as described by M.A. Schultz. The second goal was to apply this research to develop a prototype demonstration on an actual power plant system, the EBR-2 steam plant. Described in this Final (Third Annual) Technical Progress Report is the accomplishment of the project's final milestone, an in-plant intelligent control experiment conducted on April 1, 1993. The development of the experiment included: simulation validation, experiment formulation and final programming, procedure development and approval, and experimental results. Other third year developments summarized in this report are: (1) a theoretical foundation for Reconfigurable Hybrid Supervisory Control, (2) a steam plant diagnostic system, (3) control console design tools and (4) other advanced and intelligent control

Intelligent engineering and technology for nuclear power plant operation

International Nuclear Information System (INIS)

Wang, P.P.; Gu, X.

1996-01-01

The Three-Mile-Island accident has drawn considerable attention by the engineering, scientific, management, financial, and political communities as well as society at large. This paper surveys possible causes of the accident studied by various groups. Research continues in this area with many projects aimed at specifically improving the performance and operation of a nuclear power plant using the contemporary technologies available. In addition to the known cause of the accident and suggest a strategy for coping with these problems in the future. With the increased use of intelligent methodologies called computational intelligence or soft-computing, a substantially larger collection of powerful tools are now available for our designers to use in order to tackle these sensitive and difficult issues. These intelligent methodologies consists of fuzzy logic, genetic algorithms, neural networks, artificial intelligence and expert systems, pattern recognition, machine intelligence, and fuzzy constraint networks. Using the Three-Mile-Island experience, this paper offers a set of specific recommendations for future designers to take advantage of the powerful tools of intelligent technologies that we are now able to master and encourages the adoption of a novel methodology called fuzzy constraint network

Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Intelligent Executive Computer Communication

Science.gov (United States)

1991-06-01

Proceedings of The National Conference on Artificial Intelligence , pages 181-184, The American Association for Aritificial Intelligence , Pittsburgh...Intermediary Resource: Intelligent Executive Computer Communication John Lyman and Carla J. Conaway University of California at Los Angeles for Contracting...Include Security Classification) Interim Report: Distributed Problem Solving: Adaptive Networks With a Computer Intermediary Resource: Intelligent

PowerPivot for Business Intelligence Using Excel and SharePoint

CERN Document Server

Ralston, Barry

2011-01-01

PowerPivot comprises a set of technologies for easy access to data mining and business intelligence analysis from Microsoft Excel and SharePoint. Power users and developers alike can create sophisticated, online analytic processing (OLAP) solutions using PowerPivot for Excel, and then share those solutions with other users via PowerPivot for SharePoint. Data can be pulled in from any of the leading database platforms, as well as from spreadsheets and flat files. PowerPivot for Business Intelligence Using Excel and SharePoint is your key to mastering PowerPivot. The book takes a scenario-based

Dynamic vulnerability assessment and intelligent control for sustainable power systems

CERN Document Server

Gonzalez-Longatt, Francisco

2018-01-01

Identifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short-term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks. Key features: Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management. Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability as essment methods, supported by the underpinning mathematics. Develops expertise in mitigation techniques using intelligent protect...

Colloquium paper: adaptive specializations, social exchange, and the evolution of human intelligence.

Science.gov (United States)

Cosmides, Leda; Barrett, H Clark; Tooby, John

2010-05-11

Blank-slate theories of human intelligence propose that reasoning is carried out by general-purpose operations applied uniformly across contents. An evolutionary approach implies a radically different model of human intelligence. The task demands of different adaptive problems select for functionally specialized problem-solving strategies, unleashing massive increases in problem-solving power for ancestrally recurrent adaptive problems. Because exchange can evolve only if cooperators can detect cheaters, we hypothesized that the human mind would be equipped with a neurocognitive system specialized for reasoning about social exchange. Whereas humans perform poorly when asked to detect violations of most conditional rules, we predicted and found a dramatic spike in performance when the rule specifies an exchange and violations correspond to cheating. According to critics, people's uncanny accuracy at detecting violations of social exchange rules does not reflect a cheater detection mechanism, but extends instead to all rules regulating when actions are permitted (deontic conditionals). Here we report experimental tests that falsify these theories by demonstrating that deontic rules as a class do not elicit the search for violations. We show that the cheater detection system functions with pinpoint accuracy, searching for violations of social exchange rules only when these are likely to reveal the presence of someone who intends to cheat. It does not search for violations of social exchange rules when these are accidental, when they do not benefit the violator, or when the situation would make cheating difficult.

Power quality control of an autonomous wind-diesel power system based on hybrid intelligent controller.

Science.gov (United States)

Ko, Hee-Sang; Lee, Kwang Y; Kang, Min-Jae; Kim, Ho-Chan

2008-12-01

Wind power generation is gaining popularity as the power industry in the world is moving toward more liberalized trade of energy along with public concerns of more environmentally friendly mode of electricity generation. The weakness of wind power generation is its dependence on nature-the power output varies in quite a wide range due to the change of wind speed, which is difficult to model and predict. The excess fluctuation of power output and voltages can influence negatively the quality of electricity in the distribution system connected to the wind power generation plant. In this paper, the authors propose an intelligent adaptive system to control the output of a wind power generation plant to maintain the quality of electricity in the distribution system. The target wind generator is a cost-effective induction generator, while the plant is equipped with a small capacity energy storage based on conventional batteries, heater load for co-generation and braking, and a voltage smoothing device such as a static Var compensator (SVC). Fuzzy logic controller provides a flexible controller covering a wide range of energy/voltage compensation. A neural network inverse model is designed to provide compensating control amount for a system. The system can be optimized to cope with the fluctuating market-based electricity price conditions to lower the cost of electricity consumption or to maximize the power sales opportunities from the wind generation plant.

Intelligent, Autonomous Electrical Power System Management and Distribution, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — EPS-MAESTRO (EPS Management through intelligent, AdaptivE, autonomouS, faulT identification and diagnosis, Reconfiguration/replanning/rescheduling Optimization)...

Artificial intelligence analysis of paraspinal power spectra.

Science.gov (United States)

Oliver, C W; Atsma, W J

1996-10-01

OBJECTIVE: As an aid to discrimination of sufferers with back pain an artificial intelligence neural network was constructed to differentiate paraspinal power spectra. DESIGN: Clinical investigation using surface electromyography. METHOD: The surface electromyogram power spectra from 60 subjects, 33 non-back-pain sufferers and 27 chronic back pain sufferers were used to construct a back propagation neural network that was then tested. Subjects were placed on a test frame in 30 degrees of lumbar forward flexion. An isometric load of two-thirds maximum voluntary contraction was held constant for 30 s whilst surface electromyograms were recorded at the level of the L(4-5). Paraspinal power spectra were calculated and loaded into the input layer of a three-layer back propagation network. The neural network classified the spectra into normal or back pain type. RESULTS: The back propagation neural was shown to have satisfactory convergence with a specificity of 79% and a sensitivity of 80%. CONCLUSIONS: Artificial intelligence neural networks appear to be a useful method of differentiating paraspinal power spectra in back-pain sufferers.

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.

Intelligent distributed control for nuclear power plants

International Nuclear Information System (INIS)

Klevans, E.H.

1992-01-01

This project was initiated in September 1989 as a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. The body of this Third Annual Technical Progress report summarizes the period from September 1991 to October 1992. There were two primary goals of this research project. The first goal was to combine diagnostics and control to achieve a highly automated power plant as described by M.A. Schultz. His philosophy, is to improve public perception of the safety of nuclear power plants by incorporating a high degree of automation where a greatly simplified operator control console minimizes the possibility of human error in power plant operations. To achieve this goal, a hierarchically distributed control system with automated responses to plant upset conditions was pursued in this research. The second goal was to apply this research to develop a prototype demonstration on an actual power plant system, the EBR-2 stem plant. Emphasized in this Third Annual Technical Progress Report is the continuing development of the in-plant intelligent control demonstration for the final project milestone and includes: simulation validation and the initial approach to experiment formulation

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)

The Relation between Intelligence and Adaptive Behavior: A Meta-Analysis

Science.gov (United States)

Alexander, Ryan M.

2017-01-01

Intelligence tests and adaptive behavior scales measure vital aspects of the multidimensional nature of human functioning. Assessment of each is a required component in the diagnosis or identification of intellectual disability, and both are frequently used conjointly in the assessment and identification of other developmental disabilities. The…

Intelligent Power Management of hybrid Wind/ Fuel Cell/ Energy Storage Power Generation System

OpenAIRE

A. Hajizadeh; F. Hassanzadeh

2013-01-01

This paper presents an intelligent power management strategy for hybrid wind/ fuel cell/ energy storage power generation system. The dynamic models of wind turbine, fuel cell and energy storage have been used for simulation of hybrid power system. In order to design power flow control strategy, a fuzzy logic control has been implemented to manage the power between power sources. The optimal operation of the hybrid power system is a main goal of designing power management strategy. The hybrid ...

Intelligent Power Control of DC Microgrid

DEFF Research Database (Denmark)

Hajizadeh, Amin; N. Soltani, Mohsen; Norum, Lars

2017-01-01

In this paper, an intelligent power management strategy is proposed for hybrid DC microgrid, including wind turbine, fuel cell and battery energy storage. The considered wind turbine has a permanent magnet synchronous generator (PMSG). In the considered structure, wind turbine operates as the main...... condition and fuel cell will not generate excessive power. The proposed control scheme is based on the fuzzy algorithm. All simulations in variant operational modes are performed by MATLAB/Simulink and results show the effectiveness of the proposed control strategy....

Intelligent control of non-linear dynamical system based on the adaptive neurocontroller

Science.gov (United States)

Engel, E.; Kovalev, I. V.; Kobezhicov, V.

2015-10-01

This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.

Artificial intelligence tool development and applications to nuclear power

International Nuclear Information System (INIS)

Naser, J.A.

1987-01-01

Two parallel efforts are being performed at the Electric Power Research Institute (EPRI) to help the electric utility industry take advantage of the expert system technology. The first effort is the development of expert system building tools, which are tailored to electric utility industry applications. The second effort is the development of expert system applications. These two efforts complement each other. The application development tests the tools and identifies additional tool capabilities that are required. The tool development helps define the applications that can be successfully developed. Artificial intelligence, as demonstrated by the developments described is being established as a credible technological tool for the electric utility industry. The challenge to transferring artificial intelligence technology and an understanding of its potential to the electric utility industry is to gain an understanding of the problems that reduce power plant performance and identify which can be successfully addressed using artificial intelligence

Intelligent Optical Systems Using Adaptive Optics

Science.gov (United States)

Clark, Natalie

2012-01-01

Until recently, the phrase adaptive optics generally conjured images of large deformable mirrors being integrated into telescopes to compensate for atmospheric turbulence. However, the development of smaller, cheaper devices has sparked interest for other aerospace and commercial applications. Variable focal length lenses, liquid crystal spatial light modulators, tunable filters, phase compensators, polarization compensation, and deformable mirrors are becoming increasingly useful for other imaging applications including guidance navigation and control (GNC), coronagraphs, foveated imaging, situational awareness, autonomous rendezvous and docking, non-mechanical zoom, phase diversity, and enhanced multi-spectral imaging. The active components presented here allow flexibility in the optical design, increasing performance. In addition, the intelligent optical systems presented offer advantages in size and weight and radiation tolerance.

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...

A Model of Intelligent Fault Diagnosis of Power Equipment Based on CBR

Directory of Open Access Journals (Sweden)

Gang Ma

2015-01-01

Full Text Available Nowadays the demand of power supply reliability has been strongly increased as the development within power industry grows rapidly. Nevertheless such large demand requires substantial power grid to sustain. Therefore power equipment’s running and testing data which contains vast information underpins online monitoring and fault diagnosis to finally achieve state maintenance. In this paper, an intelligent fault diagnosis model for power equipment based on case-based reasoning (IFDCBR will be proposed. The model intends to discover the potential rules of equipment fault by data mining. The intelligent model constructs a condition case base of equipment by analyzing the following four categories of data: online recording data, history data, basic test data, and environmental data. SVM regression analysis was also applied in mining the case base so as to further establish the equipment condition fingerprint. The running data of equipment can be diagnosed by such condition fingerprint to detect whether there is a fault or not. Finally, this paper verifies the intelligent model and three-ratio method based on a set of practical data. The resulting research demonstrates that this intelligent model is more effective and accurate in fault diagnosis.

Intelligent operation system for nuclear power plants

International Nuclear Information System (INIS)

Morioka, Toshihiko; Fukumoto, Akira; Suto, Osamu; Naito, Norio.

1987-01-01

Nuclear power plants consist of many systems and are operated by skillful operators with plenty of knowledge and experience of nuclear plants. Recently, plant automation or computerized operator support systems have come to be utilized, but the synthetic judgment of plant operation and management remains as human roles. Toshiba is of the opinion that the activities (planning, operation and maintenance) should be integrated, and man-machine interface should be human-friendly. We have begun to develop the intelligent operation system aiming at reducing the operator's role within the fundamental judgment through the use of artificial intelligence. (author)

Enhancing nuclear power plant performance through the use of artificial intelligence

International Nuclear Information System (INIS)

Maren, A.J.; Miller, L.F.; Tsoukalas, L.H.; Uhrig, R.E.; Upadhyaya, B.R.

1992-01-01

The objective of this research was to advance the state-of-the-art of applying artificial intelligence technology (both expert systems and neural networks) to enhancing the performance (safety, efficiency, control and management) of nuclear power plants. A second, but equally important objective, was to build a broadly based critical mass of expertise in the artificial intelligence field that can be brought to bear on the technology of nuclear power plants

Beginning Power BI with Excel 2013 self-service business intelligence using Power Pivot, Power View, Power Query, and Power Map

CERN Document Server

Clark, Dan

2014-01-01

Understanding your company's data has never been easier than with Microsoft's new Power BI package for Excel 2013. Consisting of four powerful tools-Power Pivot, Power View, Power Query and Power Maps-Power BI makes self-service business intelligence a reality for a wide range of users, bridging the traditional gap between Excel users, business analysts and IT experts and making it easier for everyone to work together to build the data models that can give you game-changing insights into your business. Beginning Power BI with Excel 2013 guides you step by step through the process of analyzin

An intelligent man-machine system for future nuclear power plants

International Nuclear Information System (INIS)

Takizawa, Yoji; Hattori, Yoshiaki; Itoh, Juichiro; Fukumoto, Akira

1994-01-01

The objective of the development of an intelligent man-machine system for future nuclear power plants is enhancement of operational reliability by applying recent advances in cognitive science, artificial intelligence, and computer technologies. To realize this objective, the intelligent man-machine system, aiming to support a knowledge-based decision making process in an operator's supervisory plant control tasks, consists of three main functions, i.e., a cognitive model-based advisor, a robust automatic sequence controller, and an ecological interface. These three functions have been integrated into a console-type nuclear power plant monitoring and control system as a validation test bed. The validation tests in which experienced operator crews participated were carried out in 1991 and 1992. The test results show the usefulness of the support functions and the validity of the system design approach

An Adaptive and Integrated Low-Power Framework for Multicore Mobile Computing

Directory of Open Access Journals (Sweden)

Jongmoo Choi

2017-01-01

Full Text Available Employing multicore in mobile computing such as smartphone and IoT (Internet of Things device is a double-edged sword. It provides ample computing capabilities required in recent intelligent mobile services including voice recognition, image processing, big data analysis, and deep learning. However, it requires a great deal of power consumption, which causes creating a thermal hot spot and putting pressure on the energy resource in a mobile device. In this paper, we propose a novel framework that integrates two well-known low-power techniques, DPM (Dynamic Power Management and DVFS (Dynamic Voltage and Frequency Scaling for energy efficiency in multicore mobile systems. The key feature of the proposed framework is adaptability. By monitoring the online resource usage such as CPU utilization and power consumption, the framework can orchestrate diverse DPM and DVFS policies according to workload characteristics. Real implementation based experiments using three mobile devices have shown that it can reduce the power consumption ranging from 22% to 79%, while affecting negligibly the performance of workloads.

Intelligent adaptive systems an interaction-centered design perspective

CERN Document Server

Hou, Ming; Burns, Catherine

2014-01-01

A synthesis of recent research and developments on intelligent adaptive systems from the HF (human factors) and HCI (human-computer interaction) domains, this book provides integrated design guidance and recommendations for researchers and system developers. It addresses a recognized lack of integration between the HF and HCI research communities, which has led to inconsistencies between the research approaches adopted, and a lack of exploitation of research from one field by the other. The book establishes design guidance through the review of conceptual frameworks, analytical methodologies,

Artificial Intelligence Application in Power Generation Industry: Initial considerations

Science.gov (United States)

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

2016-03-01

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

Intelligent distributed control for nuclear power plants

International Nuclear Information System (INIS)

Klevans, E.H.

1991-01-01

In September of 1989 work began on the DOE University Program grant DE-FG07-89ER12889. The grant provides support for a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. The body of this First Annual Technical Progress report summarizes the first year tasks while the appendices provide detailed information presented at conference meetings. One major addendum report, authored by M.A. Schultz, describes the ultimate goals and projected structure of an automatic distributed control system for EBR-2. The remaining tasks of the project develop specific implementations of various components required to demonstrate the intelligent distributed control concept

Digital power - Electricity gets intelligent; Digitalstrom - Strom wird intelligent

Energy Technology Data Exchange (ETDEWEB)

Lieberherr, M.; Staub, R.

2007-07-01

This article takes a look at the setting up of the 'Viagialla' digital power alliance on the 7{sup th} of July 2007 at the Swiss Federal Institute of Technology in Zurich, Switzerland. The name 'Viagialla' is derived from the Italian for 'the yellow way'. The idea behind the project - to encourage the work of young students on machines and new developments - is discussed. The alliance encourages the use of energy forms that are available in great abundance such as solar energy and wind, thus preventing the so-called 'power-gap' and making the construction of new nuclear power stations unnecessary. The name 'digital power' refers to a new method of transmitting data over power lines on the basis of a new microchip controller. This chip can even be placed in small terminal blocks thus allowing electrical apparatus to communicate with switches and other devices. In this way, the apparatus can be remotely controlled. The developers of the system hope that their system will enable 'intelligent living' and intercommunication between normal domestic devices. External communication over the Internet is also foreseen.

Hybrid intelligent monironing systems for thermal power plant trips

Science.gov (United States)

Barsoum, Nader; Ismail, Firas Basim

2012-11-01

Steam boiler is one of the main equipment in thermal power plants. If the steam boiler trips it may lead to entire shutdown of the plant, which is economically burdensome. Early boiler trips monitoring is crucial to maintain normal and safe operational conditions. In the present work two artificial intelligent monitoring systems specialized in boiler trips have been proposed and coded within the MATLAB environment. The training and validation of the two systems has been performed using real operational data captured from the plant control system of selected power plant. An integrated plant data preparation framework for seven boiler trips with related operational variables has been proposed for IMSs data analysis. The first IMS represents the use of pure Artificial Neural Network system for boiler trip detection. All seven boiler trips under consideration have been detected by IMSs before or at the same time of the plant control system. The second IMS represents the use of Genetic Algorithms and Artificial Neural Networks as a hybrid intelligent system. A slightly lower root mean square error was observed in the second system which reveals that the hybrid intelligent system performed better than the pure neural network system. Also, the optimal selection of the most influencing variables performed successfully by the hybrid intelligent system.

Cognitions as determinants of (mal)adaptive emotions and emotionally intelligent behavior in an organizational context.

Science.gov (United States)

Spörrle, Matthias; Welpe, Isabell M; Försterling, Friedrich

2006-01-01

This study applies the theoretical concepts of Rational Emotive Behavior Therapy (REBT; Ellis, 1962, 1994) to the analysis of functional and dysfunctional behaviour and emotions in the workplace and tests central assumptions of REBT in an organizational setting. We argue that Ellis' appraisal theory of emotion sheds light on some of the cognitive and emotional antecedents of emotional intelligence and emotionally intelligent behaviour. In an extension of REBT, we posit that adaptive emotions resulting from rational cognitions reflect more emotional intelligence than maladaptive emotions which result from irrational cognitions, because the former lead to functional behaviour. We hypothesize that semantically similar emotions (e.g. annoyance and rage) lead to different behavioural reactions and have a different functionality in an organizational context. The results of scenario experiments using organizational vignettes confirm the central assumptions of Ellis' appraisal theory and support our hypotheses of a correspondence between adaptive emotions and emotionally intelligent behaviour. Additionally, we find evidence that irrational job-related attitudes result in reduced work (but not life) satisfaction.

Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system.

Directory of Open Access Journals (Sweden)

Sidra Mumtaz

Full Text Available This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG. A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms.

Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system.

Science.gov (United States)

Mumtaz, Sidra; Khan, Laiq; Ahmed, Saghir; Bader, Rabiah

2017-01-01

This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV) system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms.

Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system

Science.gov (United States)

Khan, Laiq; Ahmed, Saghir; Bader, Rabiah

2017-01-01

This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV) system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms. PMID:28877191

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

Directory of Open Access Journals (Sweden)

Ajay Kumar Saxena

2002-05-01

Full Text Available Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives postulated by various groups emphasized the need of an intelligent group decision support system approach in this field. In this paper, an Integrated Multimedia based Intelligent Group Decision Support System (IM1GDSS is presented, and its main components are analyzed and discussed. In particular attention is focused on the Data Base, Model Base, Central Black Board (CBB and Multicriteria Futuristic Decision Process (MFDP module. The model base interacts with Electrical Power Network Load Forecasting and Planning (EPNLFP Module; Resource Optimization, Modeling and Simulation (ROMAS Module; Electrical Power Network Control and Evaluation Process (EPNCAEP Module, and MFDP Module through CBB for strategic planning, management control, operational planning and transaction processing. The richness of multimedia channels adds a totally new dimension in a group decision making for Electrical Power Network. The proposed IMIGDSS is a user friendly, highly interactive group decision making system, based on efficient intelligent and multimedia communication support for group discussions, retrieval of content and multi criteria decision analysis.

Intelligent Sensors for Integrated Systems Health Management (ISHM)

Science.gov (United States)

Schmalzel, John L.

2008-01-01

IEEE 1451 Smart Sensors contribute to a number of ISHM goals including cost reduction achieved through: a) Improved configuration management (TEDS); and b) Plug-and-play re-configuration. Intelligent Sensors are adaptation of Smart Sensors to include ISHM algorithms; this offers further benefits: a) Sensor validation. b) Confidence assessment of measurement, and c) Distributed ISHM processing. Space-qualified intelligent sensors are possible a) Size, mass, power constraints. b) Bus structure/protocol.

A multi-resolution envelope-power based model for speech intelligibility

DEFF Research Database (Denmark)

Jørgensen, Søren; Ewert, Stephan D.; Dau, Torsten

2013-01-01

The speech-based envelope power spectrum model (sEPSM) presented by Jørgensen and Dau [(2011). J. Acoust. Soc. Am. 130, 1475-1487] estimates the envelope power signal-to-noise ratio (SNRenv) after modulation-frequency selective processing. Changes in this metric were shown to account well...... to conditions with stationary interferers, due to the long-term integration of the envelope power, and cannot account for increased intelligibility typically obtained with fluctuating maskers. Here, a multi-resolution version of the sEPSM is presented where the SNRenv is estimated in temporal segments...... with a modulation-filter dependent duration. The multi-resolution sEPSM is demonstrated to account for intelligibility obtained in conditions with stationary and fluctuating interferers, and noisy speech distorted by reverberation or spectral subtraction. The results support the hypothesis that the SNRenv...

The dynamic interplay among EFL learners’ ambiguity tolerance, adaptability, cultural intelligence, learning approach, and language achievement

Directory of Open Access Journals (Sweden)

Shadi Alahdadi

2017-01-01

Full Text Available A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and language achievement as manifestations of the above competencies within a single model. The participants comprised one hundred eighty BA and MA Iranian university students studying English language teaching and translation. The instruments used in this study consisted of the translated versions of four questionnaires: second language tolerance of ambiguity scale, adaptability taken from emotional intelligence inventory, cultural intelligence (CQ inventory, and the revised study process questionnaire measuring surface and deep learning. The results estimated via structural equation modeling (SEM revealed that the proposed model containing the variables under study had a good fit with the data. It was found that all the variables except adaptability directly influenced language achievement with deep approach having the highest impact and ambiguity tolerance having the lowest influence. In addition, ambiguity tolerance was a positive and significant predictor of deep approach. CQ was found to be under the influence of both ambiguity tolerance and adaptability. The findings were discussed in the light of the yielded results.

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.

Application of MCU to intelligent interface of high precision magnet power supply

International Nuclear Information System (INIS)

Xu Ruinian; Li Deming

2004-01-01

Application of the high-capability MCU in the intelligent interface is introduced in this paper. A prototype of intelligent interface for high precision huge magnet power supply was developed successfully. This intelligent interface was composed of two parts: operation panel and main board, both of which adopt a MCU of PIC16F877 respectively. The interface has many advantages, such as small size, low cost and good interference immunity. (authors)

Applications of Fuzzy adaptive PID control in the thermal power plant denitration liquid ammonia evaporation

Directory of Open Access Journals (Sweden)

Li Jing

2016-01-01

Full Text Available For the control of the liquid level of liquid ammonia in thermal power plant’s ammonia vaporization room, traditional PID controller parameter tuning is difficult to adapt to complex control systems, the setting of the traditional PID controller parameters is difficult to adapt to the complex control system. For the disadvantage of bad parameter setting, poor performance and so on the fuzzy adaptive PID control is proposed. Fuzzy adaptive PID control combines the advantages of traditional PID technology and fuzzy control. By using the fuzzy controller to intelligent control the object, the performance of the PID controller is further improved, and the control precision of the system is improved[1]. The simulation results show that the fuzzy adaptive PID controller not only has the advantages of high accuracy of PID controller, but also has the characteristics of fast and strong adaptability of fuzzy controller. It realizes the optimization of PID parameters which are in the optimal state, and the maximum increase production efficiency, so that are more suitable for nonlinear dynamic system.

Low Power Multi-Hop Networking Analysis in Intelligent Environments.

Science.gov (United States)

Etxaniz, Josu; Aranguren, Gerardo

2017-05-19

Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license-free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide.

Examining the Role of Emotional Intelligence between Organizational Learning and Adaptive Performance in Indian Manufacturing Industries

Science.gov (United States)

Pradhan, Rabindra Kumar; Jena, Lalatendu Kesari; Singh, Sanjay Kumar

2017-01-01

Purpose: The purpose of this study is to examine the relationship between organisational learning and adaptive performance. Furthermore, the study investigates the moderating role of emotional intelligence in the perspective of organisational learning for addressing adaptive performance of executives employed in manufacturing organisations.…

The present status of artificial intelligence for nuclear power plants

International Nuclear Information System (INIS)

Suda, Kazunori; Yonekawa, Tuyoshi; Yoshikawa, Shinji; Hasegawa, Makoto

1999-03-01

JNC researches the development of distributed intelligence systems at autonomous plants and intelligent support system at nuclear power plant. This report describes the present status of artificial intelligence (AI) technologies for this research. The following are represented in this report: present research study for AI, Implementation of AI system and application of AI technologies in the field of industries, requirement for AI by industries, problems of social acceptance for AI. A development of AI systems has to be motivated both by current status of AI and requirement for AI. Furthermore a problem of social acceptance for AI technologies has to be solved for using AI systems in society. (author)

Improvement of Transient Stability in a Hybrid Power Multi-System Using a Designed NIDC (Novel Intelligent Damping Controller

Directory of Open Access Journals (Sweden)

Ting-Chia Ou

2017-04-01

Full Text Available This paper endeavors to apply a novel intelligent damping controller (NIDC for the static synchronous compensator (STATCOM to reduce the power fluctuations, voltage support and damping in a hybrid power multi-system. In this paper, we discuss the integration of an offshore wind farm (OWF and a seashore wave power farm (SWPF via a high-voltage, alternating current (HVAC electric power transmission line that connects the STATCOM and the 12-bus hybrid power multi-system. The hybrid multi-system consists of a battery energy storage system (BESS and a micro-turbine generation (MTG. The proposed NIDC consists of a designed proportional–integral–derivative (PID linear controller, an adaptive critic network and a proposed functional link-based novel recurrent fuzzy neural network (FLNRFNN. Test results show that the proposed controller can achieve better damping characteristics and effectively stabilize the network under unstable conditions.

Intelligent Anti Misoperation System for Power Grid Dispatching of Regions and Counties

Science.gov (United States)

Ji, Yuan; Zhang, Yunju; Zhou, Siming; Wang, Xiangdong; Ma, Jianwei

2018-01-01

With the power system of large capacity, large units, high voltage development trend, dispatching operations becoming more frequent, complex, and probability of mistakes are increasing. For the existing grid dispatching integrated system loss of anti-error function, single dispatching function, low efficiency, according to the existing conditions of Anshun Power Supply Bureau, the Intelligent anti misoperation system for power grid dispatching of regions and counties is designed, introduced the technologies such as the intelligent anti misoperation analysis, automatic process control, and interactive constraint, the system has the advantages of scientific, reasonable and efficient, and providing the technical support for anti misoperation of regions and counties.

Brief Report: Adaptation of the Italian Version of the Tromso Social Intelligence Scale to the Adolescent Population

Science.gov (United States)

Gini, Gianluca

2006-01-01

Social intelligence is a construct that has shown promising practical applications, but its use in research and applied settings has been limited by definitional problems and the complexity of most existing measures of social intelligence. The goal of the present study was to adapt the Italian version [Gini & Iotti (2004) "La Tromso…

Building an adaptive agent to monitor and repair the electrical power system of an orbital satellite

Science.gov (United States)

Tecuci, Gheorghe; Hieb, Michael R.; Dybala, Tomasz

1995-01-01

Over several years we have developed a multistrategy apprenticeship learning methodology for building knowledge-based systems. Recently we have developed and applied our methodology to building intelligent agents. This methodology allows a subject matter expert to build an agent in the same way in which the expert would teach a human apprentice. The expert will give the agent specific examples of problems and solutions, explanations of these solutions, or supervise the agent as it solves new problems. During such interactions, the agent learns general rules and concepts, continuously extending and improving its knowledge base. In this paper we present initial results on applying this methodology to build an intelligent adaptive agent for monitoring and repair of the electrical power system of an orbital satellite, stressing the interaction with the expert during apprenticeship learning.

An intelligent tutoring system for a power plant simulator

Energy Technology Data Exchange (ETDEWEB)

Seifi, H.; Seifi, A.R. [Tarbiat Modarres University, Tehran (Iran). Faculty of Engineering, Dept. of Electrical Engineers

2002-07-28

An intelligent tutoring system (ITS) is proposed for a power plant simulator. With a well designed ITS, the need for an instructor is minimized and the operator may readily and efficiently take, in real-time, the control of simulator with appropriate messages he(she) gets from the tutoring system. Using SIMULINK and based on object oriented programming (OOP) and C programming language, a fossil-fuelled power plant simulator with an ITS is proposed. Promising results are demonstrated for a typical power plant.

Cultural Intelligence and Social Adaptability: A Comparison between Iranian and Non-Iranian Dormitory Students of Isfahan University of Medical Sciences.

Science.gov (United States)

Soltani, Batoul; Keyvanara, Mahmoud

2013-01-01

At the modern age, to acquire knowledge and experience, the individuals with their own specific culture have to enter contexts with cultural diversity, adapt to different cultures and have social interactions to be able to have effective inter-cultural relationships.To have such intercultural associations and satisfy individual needs in the society, cultural intelligence and social adaptability are deemed as inevitable requirements, in particular for those who enter a quite different culture. Hence, the present study tries to compare the cultural intelligence and its aspects and social adaptability in Iranian and non-Iranian dormitory students of Isfahan University of Medical Sciences in 2012. The study was of descriptiveanalytical nature. The research population consisted of Iranian and non-Iranian students resided in the dormitories of Isfahan University of Medical Sciences which are 2500, totally. For Iranian students, two-stage sampling method was adopted. At the first stage, classified sampling and at the second stage, systematic random sampling was conducted. In this way, 441 students were selected. To form non-Iranian students' sample, consensus sampling method was applied and a sample of 37 students were obtained. The research data was collected by using Earley & Ang's Cultural Intelligence Questionnaire with the Cronbach's coefficient α of 76% and California Social Adaptability Standard Questionnaire with the Cronbach's coefficient α of over 70%. Then, the data were put into SPSS software to be analyzed. Finally, the results were presented by descriptive and inferential statistics methods. The study findings revealed that there was no statistically significant difference between cultural intelligence and cognitive aspect of cultural intelligence in Iranian and non-Iranian students (P≥0/05). However, Iranian and non-Iranian students statistically differed in terms of the following aspects of cultural intelligence: meta-cognitive aspect (61.8% for

Power cycling test and failure analysis of molded Intelligent Power IGBT Module under different temperature swing durations

DEFF Research Database (Denmark)

Choi, Uimin; Blaabjerg, Frede; Jørgensen, Søren

2016-01-01

on the lifetime of 600 V, 30 A, 3-phase molded Intelligent PowerModules (IPM) and their failuremechanismsare investigated. The study is based on the accelerated power cycling test results of 36 samples under 6 different conditions and tests are performed under realistic electrical conditions by an advanced power...

Emotional intelligence and features of social and psychological adaptation in adolescents with deviant behavior

Directory of Open Access Journals (Sweden)

Degtyarev A.V.,

2014-11-01

Full Text Available The problem of social-psychological adaptation of adolescents with deviant behavioral today is of particular relevance in relation to the current process of restructuring of educational institutions - the merging of general and specialized schools for adolescents with behavioral problems in a unified educational complexes. In these circumstances it is necessary to find an efficient tool that will simultaneously accelerate the process of adaptation and have a positive preventive effect. In this article, the author shows that such a tool can become the emotional intelligence as a construct that includes various abilities of the emotional sphere. The main hypothesis of the study was that the socio-psychological adaptation of adolescents with deviant behavior has its own characteristics, different from the norm group, and is interconnected with the components of emotional intelligence. The study was conducted on the basis of general education school № 2077 formed by the merger of five educational institutions: the former school № 738, № 703, № 702, № 7 and № 77. The study involved 222 teenagers from 14 to 16 years (111 girls and 111 boys.

An Intelligent Sensor for the Ultra-High-Frequency Partial Discharge Online Monitoring of Power Transformers

Directory of Open Access Journals (Sweden)

Jian Li

2016-05-01

Full Text Available Ultra-high-frequency (UHF partial discharge (PD online monitoring is an effective way to inspect potential faults and insulation defects in power transformers. The construction of UHF PD online monitoring system is a challenge because of the high-frequency and wide-frequency band of the UHF PD signal. This paper presents a novel, intelligent sensor for UHF PD online monitoring based on a new method, namely a level scanning method. The intelligent sensor can directly acquire the statistical characteristic quantities and is characterized by low cost, few data to output and transmit, Ethernet functionality, and small size for easy installation. The prototype of an intelligent sensor was made. Actual UHF PD experiments with three typical artificial defect models of power transformers were carried out in a laboratory, and the waveform recording method and intelligent sensor proposed were simultaneously used for UHF PD measurement for comparison. The results show that the proposed intelligent sensor is qualified for the UHF PD online monitoring of power transformers. Additionally, three methods to improve the performance of intelligent sensors were proposed according to the principle of the level scanning method.

An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

Energy Technology Data Exchange (ETDEWEB)

El Hariri, Mohamad [Florida Intl Univ., Miami, FL (United States); Faddel, Samy [Florida Intl Univ., Miami, FL (United States); Mohammed, Osama [Florida Intl Univ., Miami, FL (United States)

2017-11-01

Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted to verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.

Modelling traffic flows with intelligent cars and intelligent roads

NARCIS (Netherlands)

van Arem, Bart; Tampere, Chris M.J.; Malone, Kerry

2003-01-01

This paper addresses the modeling of traffic flows with intelligent cars and intelligent roads. It will describe the modeling approach MIXIC and review the results for different ADA systems: Adaptive Cruise Control, a special lane for Intelligent Vehicles, cooperative following and external speed

Fatigue distribution optimization for offshore wind farms using intelligent agent control

DEFF Research Database (Denmark)

Zhao, Rongyong; Shen, Wen Zhong; Knudsen, Torben

2012-01-01

with its neighbouring downwind turbines and organizes them adaptively into a wind delivery group along the wind direction. The agent attributes and the event structure are designed on the basis of the intelligent agent theory by using the unified modelling language. The control strategy of the intelligent......A novel control approach is proposed to optimize the fatigue distribution of wind turbines in a large‐scale offshore wind farm on the basis of an intelligent agent theory. In this approach, each wind turbine is considered to be an intelligent agent. The turbine at the farm boundary communicates...... coefficient for every wind turbine. The optimization is constrained such that the average fatigue for every turbine is smaller than what would be achieved by conventional dispatch and such that the total power loss of the wind farm is restricted to a few percent of the total power. This intelligent agent...

Experimental development of power reactor intelligent control

International Nuclear Information System (INIS)

Edwards, R.M.; Garcia, H.E.; Lee, K.Y.

1992-01-01

The US nuclear utility industry initiated an ambitious program to modernize the control systems at a minimum of ten existing nuclear power plants by the year 2000. That program addresses urgent needs to replace obsolete instrumentation and analog controls with highly reliable state-of-the-art computer-based digital systems. Large increases in functionality that could theoretically be achieved in a distributed digital control system are not an initial priority in the industry program but could be logically considered in later phases. This paper discusses the initial development of an experimental sequence for developing, testing, and verifying intelligent fault-accommodating control for commercial nuclear power plant application. The sequence includes an ultra-safe university research reactor (TRIGA) and a passively safe experimental power plant (Experimental Breeder Reactor 2)

LEARNING STYLES BASED ADAPTIVE INTELLIGENT TUTORING SYSTEMS: DOCUMENT ANALYSIS OF ARTICLES PUBLISHED BETWEEN 2001. AND 2016.

Directory of Open Access Journals (Sweden)

Amit Kumar

2017-12-01

Full Text Available Actualizing instructional intercessions to suit learner contrasts has gotten extensive consideration. Among these individual contrast factors, the observational confirmation in regards to the academic benefit of learning styles has been addressed, yet the examination on the issue proceeds. Late improvements in web-based executions have driven researchers to re-examine the learning styles in adaptive tutoring frameworks. Adaptivity in intelligent tutoring systems is strongly influenced by the learning style of a learner. This study involved extensive document analysis of adaptive tutoring systems based on learning styles. Seventy-eight studies in literature from 2001 to 2016 were collected and classified under select parameters such as main focus, purpose, research types, methods, types and levels of participants, field/area of application, learner modelling, data gathering tools used and research findings. The current studies reveal that majority of the studies defined a framework or architecture of adaptive intelligent tutoring system (AITS while others focused on impact of AITS on learner satisfaction and academic outcomes. Currents trends, gaps in literature and ications were discussed.

Adaptive Home System Using Wireless Sensor Network And Multi Agent System

OpenAIRE

Jayarani Kamble; Prof.Nandini Dhole

2014-01-01

Smart Home is an emerging technology growing continuously which includes number of new technologies which helps to improve human’s quality of living. This paper proposes an adaptive home system for optimum utilization of power, through Artificial Intelligence and Wireless Sensor network. Artificial Intelligence is a technology for developing adaptive system that can perceive the enviornmrnt, learn from the environment and can make decision using Rule based system.Zigbee is a w...

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

Embedded intelligent adaptive PI controller for an electromechanical system.

Science.gov (United States)

El-Nagar, Ahmad M

2016-09-01

In this study, an intelligent adaptive controller approach using the interval type-2 fuzzy neural network (IT2FNN) is presented. The proposed controller consists of a lower level proportional - integral (PI) controller, which is the main controller and an upper level IT2FNN which tuning on-line the parameters of a PI controller. The proposed adaptive PI controller based on IT2FNN (API-IT2FNN) is implemented practically using the Arduino DUE kit for controlling the speed of a nonlinear DC motor-generator system. The parameters of the IT2FNN are tuned on-line using back-propagation algorithm. The Lyapunov theorem is used to derive the stability and convergence of the IT2FNN. The obtained experimental results, which are compared with other controllers, demonstrate that the proposed API-IT2FNN is able to improve the system response over a wide range of system uncertainties. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

"Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

Science.gov (United States)

Taylor, Patrick C.; Baker, Noel C.

2015-01-01

Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.

Climate change, nuclear power, and the adaptation-mitigation dilemma

International Nuclear Information System (INIS)

Kopytko, Natalie; Perkins, John

2011-01-01

Many policy-makers view nuclear power as a mitigation for climate change. Efforts to mitigate and adapt to climate change, however, interact with existing and new nuclear power plants, and these installations must contend with dilemmas between adaptation and mitigation. This paper develops five criteria to assess the adaptation-mitigation dilemma on two major points: (1) the ability of nuclear power to adapt to climate change and (2) the potential for nuclear power operation to hinder climate change adaptation. Sea level rise models for nine coastal sites in the United States, a review of US Nuclear Regulatory Commission documents, and reports from France's nuclear regulatory agency provided insights into issues that have arisen from sea level rise, shoreline erosion, coastal storms, floods, and heat waves. Applying the criteria to inland and coastal nuclear power plants reveals several weaknesses. Safety stands out as the primary concern at coastal locations, while inland locations encounter greater problems with interrupted operation. Adapting nuclear power to climate change entails either increased expenses for construction and operation or incurs significant costs to the environment and public health and welfare. Mere absence of greenhouse gas emissions is not sufficient to assess nuclear power as a mitigation for climate change. - Research Highlights: → The adaptation-mitigation criteria reveal nuclear power's vulnerabilities. → Climate change adaptation could become too costly at many sites. → Nuclear power operation jeopardizes climate change adaptation. → Extreme climate events pose a safety challenge.

Enhancing nuclear power plant performance through the use of artificial intelligence

International Nuclear Information System (INIS)

Maren, A.J.; Miller, L.F.; Tsoukalas, L.H.; Uhrig, R.E.; Upadhyaya, B.R.

1990-01-01

The objective of this research is to advance the state-of-the-art of applying artificial intelligence technology (both expert systems and neural networks) to enhancing the performance (safety, efficiency, control and management) of nuclear power plants. A second, but equally important, objective is to build a broadly based critical mass of expertise in the artificial intelligence field that can be brought to bear on the technology of nuclear power plants. This means the production of graduates at the B.S., M.S., and Ph.D. levels in Nuclear Engineering and related fields. The research undertaken for this program is particularly appropriate for the M.S. theses and Ph.D. dissertations. A third objective is to transfer the technology developed to the ''nuclear power community,'' as well as the ''scientific and technological community,'' through publications in appropriate journals and proceedings and through presentations at national and international meetings

CRISP. Requirements Specifications of Intelligent ICT Simulation Tools for Power Applications

Energy Technology Data Exchange (ETDEWEB)

Warmer, C.J.; Kester, J.C.P.; Kamphuis, I.G. [ECN Energy in the Built Environment and Networks, Petten (Netherlands); Carlsson, P [EnerSearch, Malmoe (Sweden); Fontela, M. [Laboratory of Electrical Engineering LEG, Grenoble (France); Gustavsson, R. [Blekinge Institute of Technology BTH, Karlskrona (Sweden)

2003-10-15

This report, deliverable D2.1 in the CRISP project, serves as a preparation report for the development of simulation tools and prototype software which will be developed in forthcoming stages of the CRISP project. Application areas for these simulations are: fault detection and diagnosis, supply and demand matching and intelligent load shedding. The context in which these applications function is the power network with a high degree of distributed generation, including renewables. In order to control a so called distributed grid we can benefit from a high level of distributed control and intelligence. This requires, on top of the power system network, an information and communication network.. We argue that such a network should be seen as an enabler of distributed control and intelligence. The applications, through which control and intelligence is implemented, then form a third network layer, the service oriented network. Building upon this three-layered network model we derive in this report the requirements for a simulation tool and experiments which study new techniques for fault detection and diagnostics and for simulation tools and experiments implementing intelligent load shedding and supply and demand matching scenarios. We also look at future implementation of these services within the three-layered network model and the requirements that follow for the core information and communication network and for the service oriented network. These requirements, supported by the studies performed in the CRISP Workpackage 1, serve as a basis for development of the simulation tools in the tasks 2.2 to 2.4.

CRISP. Requirements Specifications of Intelligent ICT Simulation Tools for Power Applications

International Nuclear Information System (INIS)

Warmer, C.J.; Kester, J.C.P.; Kamphuis, I.G.; Carlsson, P; Fontela, M.; Gustavsson, R.

2003-10-01

This report, deliverable D2.1 in the CRISP project, serves as a preparation report for the development of simulation tools and prototype software which will be developed in forthcoming stages of the CRISP project. Application areas for these simulations are: fault detection and diagnosis, supply and demand matching and intelligent load shedding. The context in which these applications function is the power network with a high degree of distributed generation, including renewables. In order to control a so called distributed grid we can benefit from a high level of distributed control and intelligence. This requires, on top of the power system network, an information and communication network.. We argue that such a network should be seen as an enabler of distributed control and intelligence. The applications, through which control and intelligence is implemented, then form a third network layer, the service oriented network. Building upon this three-layered network model we derive in this report the requirements for a simulation tool and experiments which study new techniques for fault detection and diagnostics and for simulation tools and experiments implementing intelligent load shedding and supply and demand matching scenarios. We also look at future implementation of these services within the three-layered network model and the requirements that follow for the core information and communication network and for the service oriented network. These requirements, supported by the studies performed in the CRISP Workpackage 1, serve as a basis for development of the simulation tools in the tasks 2.2 to 2.4

Intelligent Component Monitoring for Nuclear Power Plants

International Nuclear Information System (INIS)

Tsoukalas, Lefteri

2010-01-01

Reliability and economy are two major concerns for a nuclear power generation system. Next generation nuclear power reactors are being developed to be more reliable and economic. An effective and efficient surveillance system can generously contribute toward this goal. Recent progress in computer systems and computational tools has made it necessary and possible to upgrade current surveillance/monitoring strategy for better performance. For example, intelligent computing techniques can be applied to develop algorithm that help people better understand the information collected from sensors and thus reduce human error to a new low level. Incidents incurred from human error in nuclear industry are not rare and have been proven costly. The goal of this project is to develop and test an intelligent prognostics methodology for predicting aging effects impacting long-term performance of nuclear components and systems. The approach is particularly suitable for predicting the performance of nuclear reactor systems which have low failure probabilities (e.g., less than 10 -6 year -1 ). Such components and systems are often perceived as peripheral to the reactor and are left somewhat unattended. That is, even when inspected, if they are not perceived to be causing some immediate problem, they may not be paid due attention. Attention to such systems normally involves long term monitoring and possibly reasoning with multiple features and evidence, requirements that are not best suited for humans.

Predicting speech intelligibility based on the signal-to-noise envelope power ratio after modulation-frequency selective processing

DEFF Research Database (Denmark)

Jørgensen, Søren; Dau, Torsten

2011-01-01

A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data. The ...... process provides a key measure of speech intelligibility. © 2011 Acoustical Society of America.......A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data....... The model estimates the speech-to-noise envelope power ratio, SNR env, at the output of a modulation filterbank and relates this metric to speech intelligibility using the concept of an ideal observer. Predictions were compared to data on the intelligibility of speech presented in stationary speech...

Can enriching emotional intelligence improve medical students' proactivity and adaptability during OB/GYN clerkships?

Science.gov (United States)

Guseh, Stephanie H; Chen, Xiaodong P; Johnson, Natasha R

2015-12-26

The purpose of this pilot study was to examine our hypothesis that enriching workplace emotional intelligence through resident coaches could improve third-year medical students' adaptability and proactivity on the Obstetrics and Gynecology clerkship. An observational pilot study was conducted in a teaching hospital. Fourteen 3rd year medical students from two cohorts of clerkships were randomly divided into two groups, and equally assigned to trained resident coaches and untrained resident coaches. Data was collected through onsite naturalistic observation of students' adaptability and proactivity in clinical settings using a checklist with a 4-point Likert scale (1=poor to 4=excellent). Wilcoxon rank-sum test was used to compare the differences between these two groups. A total of 280 data points were collected through onsite observations conducted by investigators. All (n=14) students' adaptability and proactivity performance significantly improved from an average of 3.04 to 3.45 (p=0.014) over 6-week clerkship. Overall, students with trained resident coaches adapted significantly faster and were more proactive in the obstetrics and gynecology clinical setting than the students with untrained coaches (3.31 vs. 3.24, p=0.019). Findings from our pilot study supported our hypothesis that enriching workplace emotional intelligence knowledge through resident coaches was able to help medical students adapt into obstetrics and gynecology clinical settings faster and become more proactive in learning. Clerkship programs can incorporate the concept of a resident coach in their curriculum to help bridge medical students into clinical settings and to help them engage in self-directed learning throughout the rotation.

Coordinated Scheme of Under-Frequency Load Shedding with Intelligent Appliances in a Cyber Physical Power System

Directory of Open Access Journals (Sweden)

Qi Wang

2016-08-01

Full Text Available The construction of a cyber physical system in a power grid provides more potential control strategies for the power grid. With the rapid employment of intelligent terminal equipment (e.g., smart meters and intelligent appliances in the environment of a smart grid, abundant dynamic response information could be introduced to support a secure and stable power system. Combining demand response technology with the traditional under-frequency load shedding (UFLS scheme, a new UFLS strategy-determining method involving intelligent appliances is put forward to achieve the coordinated control of quick response resources and the traditional control resources. Based on this method, intelligent appliances can be used to meet the regulatory requirements of system operation in advance and prevent significant frequency drop, thereby improving the flexibility and stability of the system. Time-domain simulation verifies the effectiveness of the scheme, which is able to mitigate frequency drop and reduce the amount of load shedding.

A generic architecture for an adaptive, interoperable and intelligent type 2 diabetes mellitus care system.

Science.gov (United States)

Uribe, Gustavo A; Blobel, Bernd; López, Diego M; Schulz, Stefan

2015-01-01

Chronic diseases such as Type 2 Diabetes Mellitus (T2DM) constitute a big burden to the global health economy. T2DM Care Management requires a multi-disciplinary and multi-organizational approach. Because of different languages and terminologies, education, experiences, skills, etc., such an approach establishes a special interoperability challenge. The solution is a flexible, scalable, business-controlled, adaptive, knowledge-based, intelligent system following a systems-oriented, architecture-centric, ontology-based and policy-driven approach. The architecture of real systems is described, using the basics and principles of the Generic Component Model (GCM). For representing the functional aspects of a system the Business Process Modeling Notation (BPMN) is used. The system architecture obtained is presented using a GCM graphical notation, class diagrams and BPMN diagrams. The architecture-centric approach considers the compositional nature of the real world system and its functionalities, guarantees coherence, and provides right inferences. The level of generality provided in this paper facilitates use case specific adaptations of the system. By that way, intelligent, adaptive and interoperable T2DM care systems can be derived from the presented model as presented in another publication.

Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

Directory of Open Access Journals (Sweden)

Jianzhou Wang

2014-01-01

Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

Power Adaptation Based on Truncated Channel Inversion for Hybrid FSO/RF Transmission With Adaptive Combining

KAUST Repository

Rakia, Tamer

2015-07-23

Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless communications. In this paper, we consider power adaptation strategies based on truncated channel inversion for the hybrid FSO/RF system employing adaptive combining. Specifically, we adaptively set the RF link transmission power when FSO link quality is unacceptable to ensure constant combined signal-to-noise ratio (SNR) at the receiver. Two adaptation strategies are proposed. One strategy depends on the received RF SNR, whereas the other one depends on the combined SNR of both links. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are obtained. Numerical examples show that the hybrid FSO/RF system with power adaptation achieves a considerable outage performance improvement over the conventional system.

Power Adaptation Based on Truncated Channel Inversion for Hybrid FSO/RF Transmission With Adaptive Combining

KAUST Repository

Rakia, Tamer; Hong-Chuan Yang; Gebali, Fayez; Alouini, Mohamed-Slim

2015-01-01

Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless communications. In this paper, we consider power adaptation strategies based on truncated channel inversion for the hybrid FSO/RF system employing adaptive combining. Specifically, we adaptively set the RF link transmission power when FSO link quality is unacceptable to ensure constant combined signal-to-noise ratio (SNR) at the receiver. Two adaptation strategies are proposed. One strategy depends on the received RF SNR, whereas the other one depends on the combined SNR of both links. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are obtained. Numerical examples show that the hybrid FSO/RF system with power adaptation achieves a considerable outage performance improvement over the conventional system.

Connections between political intelligence and power maintenance in Niccolo Machiavelli

Directory of Open Access Journals (Sweden)

Fábio Régio Bento

2015-07-01

Full Text Available The Prince, written in 1513 and published in 1531, four years after Niccolo Machiavelli's death (1469-1527, continues to be permanently reproposed, after more than five centuries of its inception, throughout a wide range of translations, not always coherent with the 1513 manuscript. In fact, as noted by Marques (2006, p. 41, Prince's Machiavelli is still presented as a “teacher of evil”. On the contrary to what the common sense affirms, however, the Florentine secretary was not Machiavellian. In this paper, through a direct study of The Prince in the Italian manuscript of 1513 (Machiavelli, 1988, and with the aid of translation from Maria Lucia Cumo (Maquiavel 1996, we shall analyze the connections in The Prince between political intelligence and virtuous maintenance of power, by claiming that The Prince is not an amoral  neither immoral book, but of political morality of the intelligent maintenance of power according to what Machiavelli understands as political virtues.

Can enriching emotional intelligence improve medical students’ proactivity and adaptability during OB/GYN clerkships?

Science.gov (United States)

Guseh, Stephanie H.; Chen, Xiaodong P.

2015-01-01

Objectives The purpose of this pilot study was to examine our hypothesis that enriching workplace emotional intelligence through resident coaches could improve third-year medical students’ adaptability and proactivity on the Obstetrics and Gynecology clerkship. Methods An observational pilot study was conducted in a teaching hospital. Fourteen 3rd year medical students from two cohorts of clerkships were randomly divided into two groups, and equally assigned to trained resident coaches and untrained resident coaches. Data was collected through onsite naturalistic observation of students’ adaptability and proactivity in clinical settings using a checklist with a 4-point Likert scale (1=poor to 4=excellent). Wilcoxon rank-sum test was used to compare the differences between these two groups. Results A total of 280 data points were collected through onsite observations conducted by investigators. All (n=14) students’ adaptability and proactivity performance significantly improved from an average of 3.04 to 3.45 (p=0.014) over 6-week clerkship. Overall, students with trained resident coaches adapted significantly faster and were more proactive in the obstetrics and gynecology clinical setting than the students with untrained coaches (3.31 vs. 3.24, p=0.019). Conclusions Findings from our pilot study supported our hypothesis that enriching workplace emotional intelligence knowledge through resident coaches was able to help medical students adapt into obstetrics and gynecology clinical settings faster and become more proactive in learning. Clerkship programs can incorporate the concept of a resident coach in their curriculum to help bridge medical students into clinical settings and to help them engage in self-directed learning throughout the rotation. PMID:26708233

Investigations on Incipient Fault Diagnosis of Power Transformer Using Neural Networks and Adaptive Neurofuzzy Inference System

Directory of Open Access Journals (Sweden)

Nandkumar Wagh

2014-01-01

Full Text Available Continuity of power supply is of utmost importance to the consumers and is only possible by coordination and reliable operation of power system components. Power transformer is such a prime equipment of the transmission and distribution system and needs to be continuously monitored for its well-being. Since ratio methods cannot provide correct diagnosis due to the borderline problems and the probability of existence of multiple faults, artificial intelligence could be the best approach. Dissolved gas analysis (DGA interpretation may provide an insight into the developing incipient faults and is adopted as the preliminary diagnosis tool. In the proposed work, a comparison of the diagnosis ability of backpropagation (BP, radial basis function (RBF neural network, and adaptive neurofuzzy inference system (ANFIS has been investigated and the diagnosis results in terms of error measure, accuracy, network training time, and number of iterations are presented.

Adaptive Artificial intelligence based fuzzy logic MPPTcontrol for stande-alone photovoltaic system under different atmospheric conditions

Directory of Open Access Journals (Sweden)

Zaghba Layachi

2015-08-01

Full Text Available there is an increased need for analysing the effect of atmospheric variables on photovoltaic (PV production and performance. The outputs from the different PV cells in different atmospheric conditions, such as irradiation and temperature , differ from each other evidencing knowledge deficiency in PV systems [14]. Maximum power point tracking (MPPT methods are used to maximize the PV array output power by tracking continuously the maximum power point (MPP. Among all MPPT methods existing in the literature, perturb and observe (P&O is the most commonly used for its simplicity and ease of implementation; however, it presents drawbacks such as slow response speed, oscillation around the MPP in steady state, and even tracking in wrong way under rapidly changing atmospheric conditions. In order to allow a functioning around the optimal point Mopt, we have inserted a DC-DC converter (Buck–Boost for a better matching between the PV and the load. This paper, we study the Maximum power point tracking using adaptive Intelligent fuzzy logic and conventional (P&O control for stande-alone photovoltaic Array system .In particular, the performances of the controllers are analyzed under variation weather conditions with are constant temperature and variable irradiation. The proposed system is simulated by using MATLAB-SIMULINK. According to the results, fuzzy logic controller has shown better performance during the optimization.

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

Science.gov (United States)

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

2014-04-01

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

Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

Science.gov (United States)

Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

1989-03-01

A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

The Dynamic Interplay among EFL Learners' Ambiguity Tolerance, Adaptability, Cultural Intelligence, Learning Approach, and Language Achievement

Science.gov (United States)

Alahdadi, Shadi; Ghanizadeh, Afsaneh

2017-01-01

A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and…

The adaptation of the electric power companies to the power market

International Nuclear Information System (INIS)

Otterstad, B.; Ottosen, R.

1993-02-01

This report describes the challenges met by the Norwegian electric power companies in adapting to a more market oriented business and their possibilities and strategies when facing the uncertainties on the market side. The main principles of adaptation to the market are described and various strategies are illustrated by means of simple calculations and figures. The theoretical basis for analyses of adaptation to the market and for pricing period contracts and options are discussed. The report concludes with a discussion of the de-regulation of the North American gas market and draws parallels to the Norwegian power market. 17 figs

Advanced and intelligent control in power electronics and drives

CERN Document Server

Blaabjerg, Frede; Rodríguez, José

2014-01-01

Power electronics and variable frequency drives are continuously developing multidisciplinary fields in electrical engineering, and it is practically not possible to write a book covering the entire area by one individual specialist. Especially by taking account the recent fast development in the neighboring fields like control theory, computational intelligence and signal processing, which all strongly influence new solutions in control of power electronics and drives. Therefore, this book is written by individual key specialist working on the area of modern advanced control methods which penetrates current implementation of power converters and drives. Although some of the presented methods are still not adopted by industry, they create new solutions with high further research and application potential. The material of the book is presented in the following three parts: Part I: Advanced Power Electronic Control in Renewable Energy Sources (Chapters 1-4), Part II: Predictive Control of Power Converters and D...

Intelligent distributed control for nuclear power plants

International Nuclear Information System (INIS)

Klevans, E.H.; Edwards, R.M.; Ray, A.; Lee, K.Y.; Garcia, H.E.: Chavez, C.M.; Turso, J.A.; BenAbdennour, A.

1991-01-01

In September of 1989 work began on the DOE University Program grant DE-FG07-89ER12889. The grant provides support for a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. The body of this Second Annual Technical Progress report covers the period from September 1990 to September 1991. It summarizes the second year accomplishments while the appendices provide detailed information presented at conference meetings. These are two primary goals of this research. The first is to combine diagnostics and control to achieve a highly automated power plant as described by M.A. Schultz, a project consultant during the first year of the project. This philosophy, as presented in the first annual technical progress report, is to improve public perception of the safety of nuclear power plants by incorporating a high degree automation where greatly simplified operator control console minimizes the possibility of human error in power plant operations. A hierarchically distributed control system with automated responses to plant upset conditions is the focus of our research to achieve this goal. The second goal is to apply this research to develop a prototype demonstration on an actual power plant system, the EBR-II steam plant

Design of intelligent power consumption optimization and visualization management platform for large buildings based on internet of things

Directory of Open Access Journals (Sweden)

Gong Shulan

2017-01-01

Full Text Available The buildings provide a significant contribution to total energy consumption and CO2 emission. It has been estimated that the development of an intelligent power consumption monitor and control system will result in about 30% savings in energy consumption. This design innovatively integrates the advanced technologies such as the internet of things, the internet, intelligent buildings and intelligent electricity which can offer open, efficient, convenient energy consumption detection platform in demand side and visual management demonstration application platform in power enterprises side. The system was created to maximize the effective and efficient the use of energy resource. It was development around sensor networks and intelligent gateway and the monitoring center software. This will realize the highly integration and comprehensive application in energy and information to meet the needs with intelligent buildings

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

OpenAIRE

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

2016-01-01

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

An artificial intelligence approach towards disturbance analysis in nuclear power plants

International Nuclear Information System (INIS)

Lindner, A.; Klebau, J.; Fielder, U.; Baldeweg, F.

1987-01-01

The scale and degree of sophistication of technological plants, e.g. nuclear power plants, have been essentially increased during the last decades. Conventional disturbance analysis systems have proved to work successfully in wellknown situations. But in cases of emergencies, the operator staff needs a more advanced assistance in realizing diagnosis and therapy control. The significance of introducing artificial intelligence methods in nuclear power technology is emphasized. Main features of the on-line disturbance analysis system SAAP-2 are reported about. It is being developed for application in nuclear power plants. 9 refs. (author)

Beyond adaptive-critic creative learning for intelligent mobile robots

Science.gov (United States)

Liao, Xiaoqun; Cao, Ming; Hall, Ernest L.

2001-10-01

Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning - imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it

The SP Theory of Intelligence as a Foundation for the Development of a General, Human-Level Thinking Machine

OpenAIRE

Wolff, J Gerard

2016-01-01

This paper summarises how the "SP theory of intelligence" and its realisation in the "SP computer model" simplifies and integrates concepts across artificial intelligence and related areas, and thus provides a promising foundation for the development of a general, human-level thinking machine, in accordance with the main goal of research in artificial general intelligence. The key to this simplification and integration is the powerful concept of "multiple alignment", borrowed and adapted from...

Intelligent PV Power Smoothing Control Using Probabilistic Fuzzy Neural Network with Asymmetric Membership Function

Directory of Open Access Journals (Sweden)

Faa-Jeng Lin

2017-01-01

Full Text Available An intelligent PV power smoothing control using probabilistic fuzzy neural network with asymmetric membership function (PFNN-AMF is proposed in this study. First, a photovoltaic (PV power plant with a battery energy storage system (BESS is introduced. The BESS consisted of a bidirectional DC/AC 3-phase inverter and LiFePO4 batteries. Then, the difference of the actual PV power and smoothed power is supplied by the BESS. Moreover, the network structure of the PFNN-AMF and its online learning algorithms are described in detail. Furthermore, the three-phase output currents of the PV power plant are converted to the dq-axis current components. The resulted q-axis current is the input of the PFNN-AMF power smoothing control, and the output is a smoothing PV power curve to achieve the effect of PV power smoothing. Comparing to the other smoothing methods, a minimum energy capacity of the BESS with a small fluctuation of the grid power can be achieved by the PV power smoothing control using PFNN-AMF. In addition, a personal computer- (PC- based PV power plant emulator and BESS are built for the experimentation. From the experimental results of various irradiance variation conditions, the effectiveness of the proposed intelligent PV power smoothing control can be verified.

The potential impact of intelligent power wheelchair use on social participation: perspectives of users, caregivers and clinicians.

Science.gov (United States)

Rushton, Paula W; Kairy, Dahlia; Archambault, Philippe; Pituch, Evelina; Torkia, Caryne; El Fathi, Anas; Stone, Paula; Routhier, François; Forget, Robert; Pineau, Joelle; Gourdeau, Richard; Demers, Louise

2015-05-01

To explore power wheelchair users', caregivers' and clinicians' perspectives regarding the potential impact of intelligent power wheelchair use on social participation. Semi-structured interviews were conducted with power wheelchair users (n = 12), caregivers (n = 4) and clinicians (n = 12). An illustrative video was used to facilitate discussion. The transcribed interviews were analyzed using thematic analysis. Three main themes were identified based on the experiences of the power wheelchair users, caregivers and clinicians: (1) increased social participation opportunities, (2) changing how social participation is experienced and (3) decreased risk of accidents during social participation. Findings from this study suggest that an intelligent power wheelchair would enhance social participation in a variety of important ways, thereby providing support for continued design and development of this assistive technology. An intelligent power wheelchair has the potential to: Increase social participation opportunities by overcoming challenges associated with navigating through crowds and small spaces. Change how social participation is experienced through "normalizing" social interactions and decreasing the effort required to drive a power wheelchair. Decrease the risk of accidents during social participation by reducing the need for dangerous compensatory strategies and minimizing the impact of the physical environment.

Intelligent power wheelchair use in long-term care: potential users' experiences and perceptions.

Science.gov (United States)

Rushton, Paula W; Mortenson, Ben W; Viswanathan, Pooja; Wang, Rosalie H; Miller, William C; Hurd Clarke, Laura

2017-10-01

Long-term care (LTC) residents with cognitive impairments frequently experience limited mobility and participation in preferred activities. Although a power wheelchair could mitigate some of these mobility and participation challenges, this technology is often not prescribed for this population due to safety concerns. An intelligent power wheelchair (IPW) system represents a potential intervention that could help to overcome these concerns. The purpose of this study was to explore a) how residents experienced an IPW that used three different modes of control and b) what perceived effect the IPW would have on their daily lives. We interviewed 10 LTC residents with mild or moderate cognitive impairment twice, once before and once after testing the IPW. Interviews were conducted using a semi-structured interview guide, audio recorded and transcribed verbatim for thematic analyses. Our analyses identified three overarching themes: (1) the difference an IPW would make, (2) the potential impact of the IPW on others and (3) IPW-related concerns. Findings from this study confirm the need for and potential benefits of IPW use in LTC. Future studies will involve testing IPW improvements based on feedback and insights from this study. Implications for rehabilitation Intelligent power wheelchairs may enhance participation and improve safety and feelings of well-being for long-term care residents with cognitive impairments. Intelligent power wheelchairs could potentially have an equally positive impact on facility staff, other residents, and family and friends by decreasing workload and increasing safety.

Generative Adversarial Networks Based Heterogeneous Data Integration and Its Application for Intelligent Power Distribution and Utilization

Directory of Open Access Journals (Sweden)

Yuanpeng Tan

2018-01-01

Full Text Available Heterogeneous characteristics of a big data system for intelligent power distribution and utilization have already become more and more prominent, which brings new challenges for the traditional data analysis technologies and restricts the comprehensive management of distribution network assets. In order to solve the problem that heterogeneous data resources of power distribution systems are difficult to be effectively utilized, a novel generative adversarial networks (GANs based heterogeneous data integration method for intelligent power distribution and utilization is proposed. In the proposed method, GANs theory is introduced to expand the distribution of completed data samples. Then, a so-called peak clustering algorithm is proposed to realize the finite open coverage of the expanded sample space, and repair those incomplete samples to eliminate the heterogeneous characteristics. Finally, in order to realize the integration of the heterogeneous data for intelligent power distribution and utilization, the well-trained discriminator model of GANs is employed to check the restored data samples. The simulation experiments verified the validity and stability of the proposed heterogeneous data integration method, which provides a novel perspective for the further data quality management of power distribution systems.

Forecasting the natural gas demand in China using a self-adapting intelligent grey model

International Nuclear Information System (INIS)

Zeng, Bo; Li, Chuan

2016-01-01

Reasonably forecasting demands of natural gas in China is of significance as it could aid Chinese government in formulating energy policies and adjusting industrial structures. To this end, a self-adapting intelligent grey prediction model is proposed in this paper. Compared with conventional grey models which have the inherent drawbacks of fixed structure and poor adaptability, the proposed new model can automatically optimize model parameters according to the real data characteristics of modeling sequence. In this study, the proposed new model, discrete grey model, even difference grey model and classical grey model were employed, respectively, to simulate China's natural gas demands during 2002–2010 and forecast demands during 2011–2014. The results show the new model has the best simulative and predictive precision. Finally, the new model is used to forecast China's natural gas demand during 2015–2020. The forecast shows the demand will grow rapidly over the next six years. Therefore, in order to maintain the balance between the supplies and the demands for the natural gas in the future, Chinese government needs to take some measures, such as importing huge amounts of natural gas from abroad, increasing the domestic yield, using more alternative energy, and reducing the industrial reliance on natural gas. - Highlights: • A self-adapting intelligent grey prediction model (SIGM) is proposed in this paper. • The SIGM has the advantage of working with exponential functions and linear functions. • The SIGM solves the drawbacks of fixed structure and poor adaptability of grey models. • The demand of natural gas in China is successfully forecasted using the SIGM model. • The study findings can help Chinese government reasonably formulate energy policies.

Advanced power cycler with intelligent monitoring strategy of IGBT module under test

DEFF Research Database (Denmark)

Choi, U. M.; Blaabjerg, F.; Iannuzzo, F.

2017-01-01

and diode, which for the wear-out condition monitoring are presented. This advanced power cycler allows to perform power cycling test cost-effectively under conditions close to real power converter applications. In addition, an intelligent monitoring strategy for the separation of package-related wear......-out failure mechanisms has been proposed. By means of the proposed method, the wear-out failure mechanisms of an IGBT module can be separated without any additional efforts during the power cycling tests. The validity and effectiveness of the proposed monitoring strategy are also verified by experiments....

Fault Diagnosis of Power Systems Using Intelligent Systems

Science.gov (United States)

Momoh, James A.; Oliver, Walter E. , Jr.

1996-01-01

The power system operator's need for a reliable power delivery system calls for a real-time or near-real-time Al-based fault diagnosis tool. Such a tool will allow NASA ground controllers to re-establish a normal or near-normal degraded operating state of the EPS (a DC power system) for Space Station Alpha by isolating the faulted branches and loads of the system. And after isolation, re-energizing those branches and loads that have been found not to have any faults in them. A proposed solution involves using the Fault Diagnosis Intelligent System (FDIS) to perform near-real time fault diagnosis of Alpha's EPS by downloading power transient telemetry at fault-time from onboard data loggers. The FDIS uses an ANN clustering algorithm augmented with a wavelet transform feature extractor. This combination enables this system to perform pattern recognition of the power transient signatures to diagnose the fault type and its location down to the orbital replaceable unit. FDIS has been tested using a simulation of the LeRC Testbed Space Station Freedom configuration including the topology from the DDCU's to the electrical loads attached to the TPDU's. FDIS will work in conjunction with the Power Management Load Scheduler to determine what the state of the system was at the time of the fault condition. This information is used to activate the appropriate diagnostic section, and to refine if necessary the solution obtained. In the latter case, if the FDIS reports back that it is equally likely that the faulty device as 'start tracker #1' and 'time generation unit,' then based on a priori knowledge of the system's state, the refined solution would be 'star tracker #1' located in cabinet ITAS2. It is concluded from the present studies that artificial intelligence diagnostic abilities are improved with the addition of the wavelet transform, and that when such a system such as FDIS is coupled to the Power Management Load Scheduler, a faulty device can be located and isolated

Power semiconductor device adaptive cooling assembly

NARCIS (Netherlands)

2011-01-01

The invention relates to a power semiconductor device (100) cooling assembly for cooling a power semiconductor device (100), wherein the assembly comprises an actively cooled heat sink (102) and a controller (208; 300), wherein the controller (208; 300) is adapted for adjusting the cooling

Intelligent robots for nuclear power plant inspection and surveillance

International Nuclear Information System (INIS)

Miyazawa, Tatsuo; Suzuki, Kazumi; Fujie, Hideo; Fujii, Masaaki; Asai, Takashi; Sugimoto, Hiroshi.

1986-01-01

Recently, the research and development of robotizing the patrol and works in nuclear power plants have been actively carried out since the TMI-2 accident in March, 1979. In this paper, among these robots, six examples of the movable robots, of which the working and movement were intellectualized by using information processing techniques and others, are reported, and their intellectualization is concretely discussed. In Japan, the development of the supporting system for nuclear power generation was carried out for five years from fiscal year 1980 as the project subsidized by the Ministry of International Trade and Industry, and during this period, the inspection robots for LWR plants were developed. The development of the robots for ultimate working as the large scale project of the Agency of Industrial Science and Technology aiming at further heightening the function is in progress as the eight-year project from fiscal year 1983. Monorail type automatic surveillance robots, system maintenance robots 'AMOOTY', variable crawler type intelligent movable robots, hybrid running type intelligent movable robots, monorail running type small checkup robots, and floor running type checkup and light work robots are reported. Sense information processing control and a robot language processor for expanding the function of autonomous control are outlined. (Kako, I.)

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

OpenAIRE

Ajay Kumar Saxena; S. 0. Bhatnagar; P. K Saxena

2002-01-01

Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives p...

Optimal reactive power and voltage control in distribution networks with distributed generators by fuzzy adaptive hybrid particle swarm optimisation method

DEFF Research Database (Denmark)

Chen, Shuheng; Hu, Weihao; Su, Chi

2015-01-01

A new and efficient methodology for optimal reactive power and voltage control of distribution networks with distributed generators based on fuzzy adaptive hybrid PSO (FAHPSO) is proposed. The objective is to minimize comprehensive cost, consisting of power loss and operation cost of transformers...... that the proposed method can search a more promising control schedule of all transformers, all capacitors and all distributed generators with less time consumption, compared with other listed artificial intelligent methods....... algorithm is implemented in VC++ 6.0 program language and the corresponding numerical experiments are finished on the modified version of the IEEE 33-node distribution system with two newly installed distributed generators and eight newly installed capacitors banks. The numerical results prove...

Adaptive robust polynomial regression for power curve modeling with application to wind power forecasting

DEFF Research Database (Denmark)

Xu, Man; Pinson, Pierre; Lu, Zongxiang

2016-01-01

of the lack of time adaptivity. In this paper, a refined local polynomial regression algorithm is proposed to yield an adaptive robust model of the time-varying scattered power curve for forecasting applications. The time adaptivity of the algorithm is considered with a new data-driven bandwidth selection......Wind farm power curve modeling, which characterizes the relationship between meteorological variables and power production, is a crucial procedure for wind power forecasting. In many cases, power curve modeling is more impacted by the limited quality of input data rather than the stochastic nature...... of the energy conversion process. Such nature may be due the varying wind conditions, aging and state of the turbines, etc. And, an equivalent steady-state power curve, estimated under normal operating conditions with the intention to filter abnormal data, is not sufficient to solve the problem because...

Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

International Nuclear Information System (INIS)

Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor

2017-01-01

Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the

Can enriching emotional intelligence improve medical students? proactivity and adaptability during OB/GYN clerkships?

OpenAIRE

Guseh, Stephanie H.; Chen, Xiaodong P.; Johnson, Natasha R.

2015-01-01

Objectives: The purpose of this pilot study was to examine our hypothesis that enriching workplace emotional intelligence through resident coaches could improve third-year medical students’ adaptability and proactivity on the Obstetrics and Gynecology clerkship. Methods: An observational pilot study was conducted in a teaching hospital. Fourteen 3rd year medical students from two cohorts of clerkships were randomly divided into two groups, and equally assigned to trained resident coaches and ...

CRISP. Intelligent load shedding. Deliverable 1.5

International Nuclear Information System (INIS)

Gajic, Z.; Karlsson, D.; Ullah, N.R.; Okuboye, S.; Andrieu, C.; Carlsson, P.

2005-08-01

Load shedding has been used to mitigate the consequences of large disturbances in electric power systems, since the beginning of the electrification era. The way to execute the load shedding, i.e. open a circuit breaker, has hardly developed at all for a 100-year period. The modern society dependence on reliable electricity supply is continuously increasing. This means that the consequences of traditional load shedding are not acceptable. In the meantime computer and communication technology has developed tremendously. There is also a trend to use more and more intelligent control and less hardware, such as lines and generators, to provide the required level of reliability for the electric supply. Especially in power systems, and parts of power systems, comprising distributed generation, there seems to be a great potential to improve the overall cost/benefit-ratio for the desired level of reliability, by the use of intelligent load shedding. Intelligent load shedding is a means to improve power system stability, by providing an adapted load control along the distribution network, in situations where the power system otherwise would go unstable. The work with intelligent load shedding in this work package results in various technical principles of dedicated algorithms. These algorithms intend to bring a support tool for the operating system during critical situations. The main aspects are evaluating the right amount and location of power response for a given disturbance, and evaluating the right time response expected in order to comply with an acceptable stability recover. This time response is a main object in order to define appropriate ICT network enabling such a reliable implementation. A main problem of the intelligent load shedding is how to choose load to shed conveniently and quickly. There is a technical problem of finding the right level and location of the load to shed, and also an economical problem of giving incentives in order to have enough remote

Development of Android Based Powered Intelligent Wheelchair for Quadriplegic Persons

Science.gov (United States)

Gupta, Ashutosh; Ghosh, Tathagata; Kumar, Pradeep; Bhawna, Shruthi. S.

2017-08-01

Several surveys give us the view that both children and adults benefit substantially from access towards independent mobility. With the inventions of technology, no individuals are satisfied with traditional manual operated machines. To accommodate population, researchers are using technology, originally developed for mobile robots to create ‘intelligent wheelchairs’. It’s a major challenge for quadriplegic persons as they really find it difficult to manipulate powered wheelchair during the activities of their daily living. As the Smartphone era has evolved with innovative android based applications, engineers are improving and trying to make such machines simple and cheap to the next level. In this paper, we present a development of android based powered intelligent wheelchair to assist the quadriplegic person by making them self sufficient in controlling the wheelchair. The wheels of the chair can be controlled by the voice or gesture movement or by touching the screen of the android app by the challenged persons. The system uses the Bluetooth communication to interface the microcontroller and the inbuilt sensors in the android Smartphone. According to the commands received from android phone, the kinematics of the wheels are controlled.

Adaptative Techniques to Reduce Power in Digital Circuits

Directory of Open Access Journals (Sweden)

Bharadwaj Amrutur

2011-07-01

Full Text Available CMOS chips are engineered with sufficient performance margins to ensure that they meet the target performance under worst case operating conditions. Consequently, excess power is consumed for most cases when the operating conditions are more benign. This article will review a suite of dynamic power minimization techniques, which have been recently developed to reduce power consumption based on actual operating conditions. We will discuss commonly used techniques like Dynamic Power Switching (DPS, Dynamic Voltage and Frequency Scaling (DVS and DVFS and Adaptive Voltage Scaling (AVS. Recent efforts to extend these to cover threshold voltage adaptation via Dynamic Voltage and Threshold Scaling (DVTS will also be presented. Computation rate is also adapted to actual work load requirements via dynamically changing the hardware parallelism or by controlling the number of operations performed. These will be explained with some examples from the application domains of media and wireless signal processing.

The development of advanced robotic technology. A study on the tele-existence and intelligent control of a robot system for nuclear power plants

Energy Technology Data Exchange (ETDEWEB)

Chung, Myung Jin; Byun, Jueng Nam; Kim, Jong Hwan; Lee, Ju Jang; Bang, Seok Won; Chu, Gil Hwan; Park, Jong Cheol; Choi, Jong Seok; Yang, Jung Min; Hong, Sun Ki [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

1995-07-01

To increase the efficiency of human intelligence it is required to develop an intelligent monitoring and system. In this research, we develop intelligent control methods related with tele-operation, tele-existence, real-time control technique, and intelligent control technique. Those are key techniques in tele-operation, especially for the repair and maintenance of nuclear power plants. The objective of this project is to develop of the tele-existence and intelligent control system for a robot used in the nuclear power plants. (author). 20 refs.

The added value of a gaming context and intelligent adaptation for a mobile application for vocabulary learning

NARCIS (Netherlands)

Sandberg, J.; Maris, M.; Hoogendoorn, P.

2014-01-01

Two groups participated in a study on the added value of a gaming context and intelligent adaptation for a mobile learning application. The control group worked at home for a fortnight with the original Mobile English Learning application (MEL-original) developed in a previous project. The

Reliability, construct and criterion-related validity of the Serbian adaptation of the trait emotional intelligence questionnaire (TEIQue

Directory of Open Access Journals (Sweden)

Jolić-Marjanović Zorana

2014-01-01

Full Text Available This paper presents evidence on the reliability and validity of the Serbian adaptation of the Trait Emotional Intelligence Questionnaire (TEIQue, an instrument designed to comprehensively assess emotional intelligence conceived as a constellation of emotionrelated self-perceptions. Study participants were 254 adults, who completed the Serbian TEIQue, NEO-FFI, MSCEIT, EQ-short, and RSPWB. The results indicate that the adapted TEIQue is a psychometrically sound assessment tool: internal consistencies were mostly acceptable at facet, generally good at factor, and excellent at whole-scale level; the fourfactor structure was confirmed by means of CFA; convergent-discriminant validity was established through meaningful associations with related constructs, indicating that trait EI is closely aligned with affect and self-efficacy related constructs from the realm of personality (i.e., E, N, C, and Empathy, but shows only moderate overlap with ability EI; finally, incremental validity was demonstrated in the prediction of psychological wellbeing, over and above the Big Five. [Projekat Ministarstva nauke Republike Srbije, br. 179018

Intelligence.

Science.gov (United States)

Sternberg, Robert J

2012-03-01

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

Intelligence

Science.gov (United States)

Sternberg, Robert J.

2012-01-01

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

Prediction of speech intelligibility based on a correlation metric in the envelope power spectrum domain

DEFF Research Database (Denmark)

Relano-Iborra, Helia; May, Tobias; Zaar, Johannes

A powerful tool to investigate speech perception is the use of speech intelligibility prediction models. Recently, a model was presented, termed correlation-based speechbased envelope power spectrum model (sEPSMcorr) [1], based on the auditory processing of the multi-resolution speech-based Envel...

The role of intelligence and feedback in children's strategy competence.

Science.gov (United States)

Luwel, Koen; Foustana, Ageliki; Papadatos, Yiannis; Verschaffel, Lieven

2011-01-01

A test-intervention-test study was conducted investigating the role of intelligence on four parameters of strategy competence in the context of a numerosity judgment task. Moreover, the effectiveness of two feedback types on these four parameters was tested. In the two test sessions, the choice/no-choice method was used to assess the strategy repertoire, frequency, efficiency, and adaptivity of a group of low-, average-, and high-intelligence children. During the intervention, half of the participants from each intelligence group were given outcome feedback (OFB), whereas the other half received strategy feedback (SFB). The pretest data showed large differences among the three intelligence groups on all four strategy parameters. These differences had disappeared at the posttest due to a particularly strong improvement on all strategy parameters in the low-intelligence group. Furthermore, it was found that SFB was more beneficial than OFB for all parameters involving strategy selection. These results indicate that intelligence plays an important role in children's strategy use and suggest that strategy feedback can be a powerful instructional tool, especially for low-intelligence children. Copyright © 2010 Elsevier Inc. All rights reserved.

A Fuzzy ANP Model Integrated with Benefits, Opportunities, Costs, and Risks to Prioritize Intelligent Power Grid Systems

Directory of Open Access Journals (Sweden)

Hsing Hung Chen

2013-01-01

Full Text Available Although growth of renewable energy is envisaged, many concerns are critical like the ability to maintain the balance between demands and supply and the variability, noncontrollability, and flexibility of the sources. Then, what will be the future concerns about the main composition of intelligent power grid systems in the future? There is no such research tackled before. Thus, this paper first finds critical success criteria of intelligent power grid systems and then constructs a multiple criteria and decision making model to help in identifying the suitable trends under complex economic performance, environmental impacts, and rapid technological and marketing changes. After empirical demonstration, the paper summarizes that the most suitable composition of future intelligent power grid systems should be constituted by “DHT” P2P grid, “C&D workflow” P2P scheduling, “GARCM” trustworthy P2P grid, and “multipurpose” grid applications in the future.

Outage Performance of Hybrid FSO/RF System with Low-Complexity Power Adaptation

KAUST Repository

Rakia, Tamer

2016-02-26

Hybrid free-space optical (FSO) / radio-frequency (RF) systems have emerged as a promising solution for high data- rate wireless communication systems. We consider truncated channel inversion based power adaptation strategy for coherent and non- coherent hybrid FSO/RF systems, employing an adaptive combining scheme. Specifically, we activate the RF link along with the FSO link when FSO link quality is unacceptable, and adaptively set RF transmission power to ensure constant combined signal-to-noise ratio at receiver terminal. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are derived. Numerical examples show that, the hybrid FSO/RF systems with power adaptation achieve considerable outage performance improvement over conventional hybrid FSO/RF systems without power adaptation. © 2015 IEEE.

Emotional Intelligence and Adaptive Success of Nurses Caring for People with Mental Retardation and Severe Behavior Problems

Science.gov (United States)

Gerits, Linda; Derksen, Jan J. L.; Verbruggen, Antoine B.

2004-01-01

The emotional intelligence profiles, gender differences, and adaptive success of 380 Dutch nurses caring for people with mental retardation and accompanying severe behavior problems are reported. Data were collected with the Bar-On Emotional Quotient Inventory, Utrecht-Coping List, Utrecht-Burnout Scale, MMPI-2, and GAMA. Absence due to illness…

ENGINEERING OF UNIVERSITY INTELLIGENT LEARNING SYSTEMS

Directory of Open Access Journals (Sweden)

Vasiliy M. Trembach

2016-01-01

Full Text Available In the article issues of engineering intelligent tutoring systems of University with adaptation are considered. The article also dwells on some modern approaches to engineering of information systems. It shows the role of engineering e-learning devices (systems in system engineering. The article describes the basic principles of system engineering and these principles are expanded regarding to intelligent information systems. The structure of intelligent learning systems with adaptation of the individual learning environments based on services is represented in the article.

Climate adaptation in power supply - status; Klimatilpasning i kraftforsyningen - statusrapport

Energy Technology Data Exchange (ETDEWEB)

Steen, Roger

2009-12-15

A survey of the now-status in the power supply when it comes to understanding possible climatic effects of power supply, the need for climate adaptation and motivation to adapt to climate change. (AG)

Short-Term Wind Electric Power Forecasting Using a Novel Multi-Stage Intelligent Algorithm

Directory of Open Access Journals (Sweden)

Haoran Zhao

2018-03-01

Full Text Available As the most efficient renewable energy source for generating electricity in a modern electricity network, wind power has the potential to realize sustainable energy supply. However, owing to its random and intermittent instincts, a high permeability of wind power into a power network demands accurate and effective wind energy prediction models. This study proposes a multi-stage intelligent algorithm for wind electric power prediction, which combines the Beveridge–Nelson (B-N decomposition approach, the Least Square Support Vector Machine (LSSVM, and a newly proposed intelligent optimization approach called the Grasshopper Optimization Algorithm (GOA. For data preprocessing, the B-N decomposition approach was employed to disintegrate the hourly wind electric power data into a deterministic trend, a cyclic term, and a random component. Then, the LSSVM optimized by the GOA (denoted GOA-LSSVM was applied to forecast the future 168 h of the deterministic trend, the cyclic term, and the stochastic component, respectively. Finally, the future hourly wind electric power values can be obtained by multiplying the forecasted values of these three trends. Through comparing the forecasting performance of this proposed method with the LSSVM, the LSSVM optimized by the Fruit-fly Optimization Algorithm (FOA-LSSVM, and the LSSVM optimized by Particle Swarm Optimization (PSO-LSSVM, it is verified that the established multi-stage approach is superior to other models and can increase the precision of wind electric power prediction effectively.

Real time Intelligent Control Laboratory (RT-ICL) of PowerLabDK for smart grid technology development

DEFF Research Database (Denmark)

Ostergaard, Jacob; Wu, Qiuwei; Garcia-Valle, Rodrigo

2012-01-01

This paper presents the Intelligent Control Laboratory (ICL) of the PowerLabDK and describes examples of ongoing research work utilizing the ICL. The ICL is comprised of a real time digital simulator (RTDS) with 5 racks, a full scale SCADA system and experimental control room with a link to the B......This paper presents the Intelligent Control Laboratory (ICL) of the PowerLabDK and describes examples of ongoing research work utilizing the ICL. The ICL is comprised of a real time digital simulator (RTDS) with 5 racks, a full scale SCADA system and experimental control room with a link...

Control of power plants and power systems. Proceedings

International Nuclear Information System (INIS)

Canales-Ruiz, R.

1996-01-01

The 88 papers in this volume constitute the proceedings of the International Federation of Automatic Control Symposium held in Mexico in 1995. The broad areas which they cover are: self tuning control; power plant operations; dynamic stability; fuzzy logic applications; power plants modelling; artificial intelligence applications; power plants simulation; voltage control; control of hydro electric units; state estimation; fault diagnosis and monitoring systems; system expansion and operation planning; security assessment; economic dispatch and optimal load flow; adaptive control; distribution; transient stability and preventive control; modelling and control of nuclear plant; knowledge data bases for automatic learning methods applied to power system dynamic security assessment; control of combined cycle units; power control centres. Separate abstracts have been prepared for the three papers relating to nuclear power plants. (UK)

Business Intelligence: Turning Knowledge into Power

Science.gov (United States)

Endsley, Krista

2009-01-01

Today, many school districts are turning to business intelligence tools to retrieve, organize, and share knowledge for faster analysis and more effective, guided decision making. Business intelligence (BI) tools are the technologies and applications that gather and report information to help an organization's leaders make better decisions. BI…

Intelligent computational systems for space applications

Science.gov (United States)

Lum, Henry; Lau, Sonie

Intelligent computational systems can be described as an adaptive computational system integrating both traditional computational approaches and artificial intelligence (AI) methodologies to meet the science and engineering data processing requirements imposed by specific mission objectives. These systems will be capable of integrating, interpreting, and understanding sensor input information; correlating that information to the "world model" stored within its data base and understanding the differences, if any; defining, verifying, and validating a command sequence to merge the "external world" with the "internal world model"; and, controlling the vehicle and/or platform to meet the scientific and engineering mission objectives. Performance and simulation data obtained to date indicate that the current flight processors baselined for many missions such as Space Station Freedom do not have the computational power to meet the challenges of advanced automation and robotics systems envisioned for the year 2000 era. Research issues which must be addressed to achieve greater than giga-flop performance for on-board intelligent computational systems have been identified, and a technology development program has been initiated to achieve the desired long-term system performance objectives.

Simulation Modeling of Intelligent Control Algorithms for Constructing Autonomous Power Supply Systems with Improved Energy Efficiency

Directory of Open Access Journals (Sweden)

Gimazov Ruslan

2018-01-01

Full Text Available The paper considers the issue of supplying autonomous robots by solar batteries. Low efficiency of modern solar batteries is a critical issue for the whole industry of renewable energy. The urgency of solving the problem of improved energy efficiency of solar batteries for supplying the robotic system is linked with the task of maximizing autonomous operation time. Several methods to improve the energy efficiency of solar batteries exist. The use of MPPT charge controller is one these methods. MPPT technology allows increasing the power generated by the solar battery by 15 – 30%. The most common MPPT algorithm is the perturbation and observation algorithm. This algorithm has several disadvantages, such as power fluctuation and the fixed time of the maximum power point tracking. These problems can be solved by using a sufficiently accurate predictive and adaptive algorithm. In order to improve the efficiency of solar batteries, autonomous power supply system was developed, which included an intelligent MPPT charge controller with the fuzzy logic-based perturbation and observation algorithm. To study the implementation of the fuzzy logic apparatus in the MPPT algorithm, in Matlab/Simulink environment, we developed a simulation model of the system, including solar battery, MPPT controller, accumulator and load. Results of the simulation modeling established that the use of MPPT technology had increased energy production by 23%; introduction of the fuzzy logic algorithm to MPPT controller had greatly increased the speed of the maximum power point tracking and neutralized the voltage fluctuations, which in turn reduced the power underproduction by 2%.

Adaptive Critic Nonlinear Robust Control: A Survey.

Science.gov (United States)

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

Development of an intelligent high-voltage direct-current power supply for nuclear detectors

International Nuclear Information System (INIS)

Zhao Xiuliang

1997-01-01

The operation and performances of a new type direct-current high-voltage power supply are described. The power supply with intelligent feature is controlled by a single-chip microcomputer (8031), and various kinds of output voltage can be preset. The output-voltage is monitored and regulated by the single-chip microcomputer and displayed by LED. The output voltage is stable when the load current is within the allowable limits

Decentralized Adaptive Overcurrent Protection for Medium Voltage Maritime Power Systems

DEFF Research Database (Denmark)

Ciontea, Catalin-Iosif; Bak, Claus Leth; Blaabjerg, Frede

2016-01-01

the entire electrical network and changes the relay settings accordingly, but this approach is not adequate for the maritime power systems. This paper propose a decentralized adaptive protection method, where each protection relay is able to identify by itself the network status without the need of a central...... control unit. The new adaptive protection method is based on communication between the overcurrent relays and the equipment that could affect the protection system, such as circuit breakers and generators. Using PSCAD, the proposed method is implemented in a test medium voltage maritime power system......More and more maritime applications as marine vessels and offshore platforms need an adaptive protection power system. However, the adaptive protection is yet to be implemented in the maritime sector. Usually, the adaptive protection implies the existence of a central control unit that monitors...

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.

Delivering organisational adaptation through legislative mechanisms: Evidence from the Adaptation Reporting Power (Climate Change Act 2008).

Science.gov (United States)

Jude, S R; Drew, G H; Pollard, S J T; Rocks, S A; Jenkinson, K; Lamb, R

2017-01-01

There is increasing recognition that organisations, particularly in key infrastructure sectors, are potentially vulnerable to climate change and extreme weather events, and require organisational responses to ensure they are resilient and adaptive. However, detailed evidence of how adaptation is facilitated, implemented and reported, particularly through legislative mechanisms is lacking. The United Kingdom Climate Change Act (2008), introduced the Adaptation Reporting Power, enabling the Government to direct so-called reporting authorities to report their climate change risks and adaptation plans. We describe the authors' unique role and experience supporting the Department for Environment, Food and Rural Affairs (Defra) during the Adaptation Reporting Power's first round. An evaluation framework, used to review the adaptation reports, is presented alongside evidence on how the process provides new insights into adaptation activities and triggered organisational change in 78% of reporting authorities, including the embedding of climate risk and adaptation issues. The role of legislative mechanisms and risk-based approaches in driving and delivering adaptation is discussed alongside future research needs, including the development of organisational maturity models to determine resilient and well adapting organisations. The Adaptation Reporting Power process provides a basis for similar initiatives in other countries, although a clear engagement strategy to ensure buy-in to the process and research on its long-term legacy, including the potential merits of voluntary approaches, is required. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

An Adaptive Critic Approach to Reference Model Adaptation

Science.gov (United States)

Krishnakumar, K.; Limes, G.; Gundy-Burlet, K.; Bryant, D.

2003-01-01

Neural networks have been successfully used for implementing control architectures for different applications. In this work, we examine a neural network augmented adaptive critic as a Level 2 intelligent controller for a C- 17 aircraft. This intelligent control architecture utilizes an adaptive critic to tune the parameters of a reference model, which is then used to define the angular rate command for a Level 1 intelligent controller. The present architecture is implemented on a high-fidelity non-linear model of a C-17 aircraft. The goal of this research is to improve the performance of the C-17 under degraded conditions such as control failures and battle damage. Pilot ratings using a motion based simulation facility are included in this paper. The benefits of using an adaptive critic are documented using time response comparisons for severe damage situations.

Heuristic decision model for intelligent nuclear power systems design

International Nuclear Information System (INIS)

Nassersharif, B.; Portal, M.G.; Gaeta, M.J.

1989-01-01

The objective of this project was to investigate intelligent nuclear power systems design. A theoretical model of the design process has been developed. A fundamental process in this model is the heuristic decision making for design (i.e., selection of methods, components, materials, etc.). Rule-based expert systems do not provide the completeness that is necessary to generate good design. A new method, based on the fuzzy set theory, has been developed and is presented here. A feedwater system knowledge base (KB) was developed for a prototype software experiment to benchmark the theory

How to Improve Artificial Intelligence through Web

OpenAIRE

Adrian Lupasc

2005-01-01

Intelligent agents, intelligent software applications and artificial intelligent applications from artificial intelligence service providers may make their way onto the Web in greater number as adaptive software, dynamic programming languages and Learning Algorithms are introduced into Web Services. The evolution of Web architecture may allow intelligent applications to run directly on the Web by introducing XML, RDF and logic layer. The Intelligent Wireless Web’s significant potential for ra...

Possible stimuli for strength and power adaptation : acute metabolic responses.

Science.gov (United States)

Crewther, Blair; Cronin, John; Keogh, Justin

2006-01-01

The metabolic response to resistance exercise, in particular lactic acid or lactate, has a marked influence upon the muscular environment, which may enhance the training stimulus (e.g. motor unit activation, hormones or muscle damage) and thereby contribute to strength and power adaptation. Hypertrophy schemes have resulted in greater lactate responses (%) than neuronal and dynamic power schemes, suggesting possible metabolic-mediated changes in muscle growth. Factors such as age, sex, training experience and nutrition may also influence the lactate responses to resistance exercise and thereafter, muscular adaptation. Although the importance of the mechanical and hormonal stimulus to strength and power adaptation is well recognised, the contribution of the metabolic stimulus is largely unknown. Relatively few studies for example, have examined metabolic change across neuronal and dynamic power schemes, and not withstanding the fact that those mechanisms underpinning muscular adaptation, in relation to the metabolic stimulus, remain highly speculative. Inconsistent findings and methodological limitations within research (e.g. programme design, sampling period, number of samples) make interpretation further difficult. We contend that strength and power research needs to investigate those metabolic mechanisms likely to contribute to weight-training adaptation. Further research is also needed to examine the metabolic responses to different loading schemes, as well as interactions across age, sex and training status, so our understanding of how to optimise strength and power development is improved.

Adaptive capture of expert knowledge

Energy Technology Data Exchange (ETDEWEB)

Barrett, C.L.; Jones, R.D. [Los Alamos National Lab., NM (United States); Hand, Un Kyong [Los Alamos National Lab., NM (United States)]|[US Navy (United States)

1995-05-01

A method is introduced that can directly acquire knowledge-engineered, rule-based logic in an adaptive network. This adaptive representation of the rule system can then replace the rule system in simulated intelligent agents and thereby permit further performance-based adaptation of the rule system. The approach described provides both weight-fitting network adaptation and potentially powerful rule mutation and selection mechanisms. Nonlinear terms are generated implicitly in the mutation process through the emergent interaction of multiple linear terms. By this method it is possible to acquire nonlinear relations that exist in the training data without addition of hidden layers or imposition of explicit nonlinear terms in the network. We smoothed and captured a set of expert rules with an adaptive network. The motivation for this was to (1) realize a speed advantage over traditional rule-based simulations; (2) have variability in the intelligent objects not possible by rule-based systems but provided by adaptive systems: and (3) maintain the understandability of rule-based simulations. A set of binary rules was smoothed and converted into a simple set of arithmetic statements, where continuous, non-binary rules are permitted. A neural network, called the expert network, was developed to capture this rule set, which it was able to do with zero error. The expert network is also capable of learning a nonmonotonic term without a hidden layer. The trained network in feedforward operation is fast running, compact, and traceable to the rule base.

Comparison of adaptive critic-based and classical wide-area controllers for power systems.

Science.gov (United States)

Ray, Swakshar; Venayagamoorthy, Ganesh Kumar; Chaudhuri, Balarko; Majumder, Rajat

2008-08-01

An adaptive critic design (ACD)-based damping controller is developed for a thyristor-controlled series capacitor (TCSC) installed in a power system with multiple poorly damped interarea modes. The performance of this ACD computational intelligence-based method is compared with two classical techniques, which are observer-based state-feedback (SF) control and linear matrix inequality LMI-H(infinity) robust control. Remote measurements are used as feedback signals to the wide-area damping controller for modulating the compensation of the TCSC. The classical methods use a linearized model of the system whereas the ACD method is purely measurement-based, leading to a nonlinear controller with fixed parameters. A comparative analysis of the controllers' performances is carried out under different disturbance scenarios. The ACD-based design has shown promising performance with very little knowledge of the system compared to classical model-based controllers. This paper also discusses the advantages and disadvantages of ACDs, SF, and LMI-H(infinity).

Professional adaptability of nuclear power plant operators

International Nuclear Information System (INIS)

He Xuhong; Huang Xiangrui

2006-01-01

The paper concerns in the results of analysis for nuclear power plant (NPP) operator job and analysis for human errors related NPP accidents. Based on the principle of ergonomics a full psychological selection system of the professional adaptability of NPP operators including cognitive ability, personality and psychological health was established. The application way and importance of the professional adaptability research are discussed. (authors)

Adaptive Rate Sampling and Filtering Based on Level Crossing Sampling

Directory of Open Access Journals (Sweden)

Saeed Mian Qaisar

2009-01-01

Full Text Available The recent sophistications in areas of mobile systems and sensor networks demand more and more processing resources. In order to maintain the system autonomy, energy saving is becoming one of the most difficult industrial challenges, in mobile computing. Most of efforts to achieve this goal are focused on improving the embedded systems design and the battery technology, but very few studies target to exploit the input signal time-varying nature. This paper aims to achieve power efficiency by intelligently adapting the processing activity to the input signal local characteristics. It is done by completely rethinking the processing chain, by adopting a non conventional sampling scheme and adaptive rate filtering. The proposed approach, based on the LCSS (Level Crossing Sampling Scheme presents two filtering techniques, able to adapt their sampling rate and filter order by online analyzing the input signal variations. Indeed, the principle is to intelligently exploit the signal local characteristics—which is usually never considered—to filter only the relevant signal parts, by employing the relevant order filters. This idea leads towards a drastic gain in the computational efficiency and hence in the processing power when compared to the classical techniques.

Intelligent power system data management systems (DBMS)

Energy Technology Data Exchange (ETDEWEB)

Middleton, A.; Macdonald, E. [GE Digital Energy, Markham, ON (Canada); Schreiner, Z. [Intelligent Process Solutions GmbH, Lindau (Germany); Bizjak, J. [Elektro Ljubljana d.d., Ljubljana (Slovenia)

2010-07-01

Network owners/operators from around the world have moved from electromechanical products to intelligent electronic devices (IEDs). Most networks have a multi-generation technology mix because protection assets have a normal application lifespan of between 10 and 40 years. Associated data capture and maintenance management regimes have therefore moved from paper based into digitized media, creating a significant increase in the volume of acquired data, such that there is now a mix of paper and digitized storage. Data is rarely consolidated or used for decision making in asset management processes once testing is completed, having a major impact on overall power system reliability. This paper presented the concept of intelligent operative maintenance management, now becoming more recognized in the industry. The concept was described as the management of operational data, resulting actions and responses, wherever and by whoever they are needed, without any additional overhead. The paper discussed new techniques of testing as well as planning and operative maintenance. The practical benefits of the new system were also presented, with particular reference to central management; simplification of routine protocols; secondary testing; and reduced cost of data handling. It was concluded that the main benefit from all of the techniques discussed in this paper is that experienced expert test engineers can focus more time upon making good, critical decisions to ensure that utilities maximize their customer service and safety regimes. 13 refs., 7 figs.

Modeling speech intelligibility based on the signal-to-noise envelope power ratio

DEFF Research Database (Denmark)

Jørgensen, Søren

of modulation frequency selectivity in the auditory processing of sound with a decision metric for intelligibility that is based on the signal-to-noise envelope power ratio (SNRenv). The proposed speech-based envelope power spectrum model (sEPSM) is demonstrated to account for the effects of stationary...... through three commercially available mobile phones. The model successfully accounts for the performance across the phones in conditions with a stationary speech-shaped background noise, whereas deviations were observed in conditions with “Traffic” and “Pub” noise. Overall, the results of this thesis...

Intelligent Optics Laboratory

Data.gov (United States)

Federal Laboratory Consortium — The Intelligent Optics Laboratory supports sophisticated investigations on adaptive and nonlinear optics; advancedimaging and image processing; ground-to-ground and...

Power adaptation for joint switched diversity and adaptive modulation schemes in spectrum sharing systems

KAUST Repository

Bouida, Zied

2012-09-01

Under the scenario of an underlay cognitive radio network, we propose in this paper an adaptive scheme using transmit power adaptation, switched transmit diversity, and adaptive modulation in order to improve the performance of existing switching efficient schemes (SES) and bandwidth efficient schemes (BES). Taking advantage of the channel reciprocity principle, we assume that the channel state information (CSI) of the interference link is available to the secondary transmitter. This information is then used by the secondary transmitter to adapt its transmit power, modulation constellation size, and used transmit branch. The goal of this joint adaptation is to minimize the average number of switched branches and the average system delay given the fading channel conditions, the required error rate performance, and a peak interference constraint to the primary receiver. We analyze the proposed scheme in terms of the average number of branch switching, average delay, and we provide a closed-form expression of the average bit error rate (BER). We demonstrate through numerical examples that the proposed scheme provides a compromise between the SES and the BES schemes. © 2012 IEEE.

Power adaptation for joint switched diversity and adaptive modulation schemes in spectrum sharing systems

KAUST Repository

Bouida, Zied; Tourki, Kamel; Ghrayeb, Ali A.; Qaraqe, Khalid A.; Alouini, Mohamed-Slim

2012-01-01

Under the scenario of an underlay cognitive radio network, we propose in this paper an adaptive scheme using transmit power adaptation, switched transmit diversity, and adaptive modulation in order to improve the performance of existing switching efficient schemes (SES) and bandwidth efficient schemes (BES). Taking advantage of the channel reciprocity principle, we assume that the channel state information (CSI) of the interference link is available to the secondary transmitter. This information is then used by the secondary transmitter to adapt its transmit power, modulation constellation size, and used transmit branch. The goal of this joint adaptation is to minimize the average number of switched branches and the average system delay given the fading channel conditions, the required error rate performance, and a peak interference constraint to the primary receiver. We analyze the proposed scheme in terms of the average number of branch switching, average delay, and we provide a closed-form expression of the average bit error rate (BER). We demonstrate through numerical examples that the proposed scheme provides a compromise between the SES and the BES schemes. © 2012 IEEE.

A Long-Distance RF-Powered Sensor Node with Adaptive Power Management for IoT Applications.

Science.gov (United States)

Pizzotti, Matteo; Perilli, Luca; Del Prete, Massimo; Fabbri, Davide; Canegallo, Roberto; Dini, Michele; Masotti, Diego; Costanzo, Alessandra; Franchi Scarselli, Eleonora; Romani, Aldo

2017-07-28

We present a self-sustained battery-less multi-sensor platform with RF harvesting capability down to -17 dBm and implementing a standard DASH7 wireless communication interface. The node operates at distances up to 17 m from a 2 W UHF carrier. RF power transfer allows operation when common energy scavenging sources (e.g., sun, heat, etc.) are not available, while the DASH7 communication protocol makes it fully compatible with a standard IoT infrastructure. An optimized energy-harvesting module has been designed, including a rectifying antenna (rectenna) and an integrated nano-power DC/DC converter performing maximum-power-point-tracking (MPPT). A nonlinear/electromagnetic co-design procedure is adopted to design the rectenna, which is optimized to operate at ultra-low power levels. An ultra-low power microcontroller controls on-board sensors and wireless protocol, to adapt the power consumption to the available detected power by changing wake-up policies. As a result, adaptive behavior can be observed in the designed platform, to the extent that the transmission data rate is dynamically determined by RF power. Among the novel features of the system, we highlight the use of nano-power energy harvesting, the implementation of specific hardware/software wake-up policies, optimized algorithms for best sampling rate implementation, and adaptive behavior by the node based on the power received.

A Long-Distance RF-Powered Sensor Node with Adaptive Power Management for IoT Applications

Directory of Open Access Journals (Sweden)

Matteo Pizzotti

2017-07-01

Full Text Available We present a self-sustained battery-less multi-sensor platform with RF harvesting capability down to −17 dBm and implementing a standard DASH7 wireless communication interface. The node operates at distances up to 17 m from a 2 W UHF carrier. RF power transfer allows operation when common energy scavenging sources (e.g., sun, heat, etc. are not available, while the DASH7 communication protocol makes it fully compatible with a standard IoT infrastructure. An optimized energy-harvesting module has been designed, including a rectifying antenna (rectenna and an integrated nano-power DC/DC converter performing maximum-power-point-tracking (MPPT. A nonlinear/electromagnetic co-design procedure is adopted to design the rectenna, which is optimized to operate at ultra-low power levels. An ultra-low power microcontroller controls on-board sensors and wireless protocol, to adapt the power consumption to the available detected power by changing wake-up policies. As a result, adaptive behavior can be observed in the designed platform, to the extent that the transmission data rate is dynamically determined by RF power. Among the novel features of the system, we highlight the use of nano-power energy harvesting, the implementation of specific hardware/software wake-up policies, optimized algorithms for best sampling rate implementation, and adaptive behavior by the node based on the power received.

Reconfigurable, Intelligently-Adaptive, Communication System, an SDR Platform

Science.gov (United States)

Roche, Rigoberto J.; Shalkhauser, Mary Jo; Hickey, Joseph P.; Briones, Janette C.

2016-01-01

The Space Telecommunications Radio System (STRS) provides a common, consistent framework to abstract the application software from the radio platform hardware. STRS aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. The NASA Glenn Research Center (GRC) team made a software defined radio (SDR) platform STRS compliant by adding an STRS operating environment and a field programmable gate array (FPGA) wrapper, capable of implementing each of the platforms interfaces, as well as a test waveform to exercise those interfaces. This effort serves to provide a framework toward waveform development onto an STRS compliant platform to support future space communication systems for advanced exploration missions. The use of validated STRS compliant applications provides tested code with extensive documentation to potentially reduce risk, cost and e ort in development of space-deployable SDRs. This paper discusses the advantages of STRS, the integration of STRS onto a Reconfigurable, Intelligently-Adaptive, Communication System (RIACS) SDR platform, and the test waveform and wrapper development e orts. The paper emphasizes the infusion of the STRS Architecture onto the RIACS platform for potential use in next generation flight system SDRs for advanced exploration missions.

Evolutionary Developmental Soft Robotics As a Framework to Study Intelligence and Adaptive Behavior in Animals and Plants

Directory of Open Access Journals (Sweden)

Francesco Corucci

2017-07-01

Full Text Available In this paper, a comprehensive methodology and simulation framework will be reviewed, designed in order to study the emergence of adaptive and intelligent behavior in generic soft-bodied creatures. By incorporating artificial evolutionary and developmental processes, the system allows to evolve complete creatures (brain, body, developmental properties, sensory, control system, etc. for different task environments. Whether the evolved creatures will resemble animals or plants is in general not known a priori, and depends on the specific task environment set up by the experimenter. In this regard, the system may offer a unique opportunity to explore differences and similarities between these two worlds. Different material properties can be simulated and optimized, from a continuum of soft/stiff materials, to the interconnection of heterogeneous structures, both found in animals and plants alike. The adopted genetic encoding and simulation environment are particularly suitable in order to evolve distributed sensory and control systems, which play a particularly important role in plants. After a general description of the system some case studies will be presented, focusing on the emergent properties of the evolved creatures. Particular emphasis will be on some unifying concepts that are thought to play an important role in the emergence of intelligent and adaptive behavior across both the animal and plant kingdoms, such as morphological computation and morphological developmental plasticity. Overall, with this paper, we hope to draw attention on set of tools, methodologies, ideas and results, which may be relevant to researchers interested in plant-inspired robotics and intelligence.

Knowledge Is Power for Medical Assistants: Crystallized and Fluid Intelligence As Predictors of Vocational Knowledge

Directory of Open Access Journals (Sweden)

Anne Moehring

2018-02-01

Full Text Available Medical education research has focused almost entirely on the education of future physicians. In comparison, findings on other health-related occupations, such as medical assistants, are scarce. With the current study, we wanted to examine the knowledge-is-power hypothesis in a real life educational setting and add to the sparse literature on medical assistants. Acquisition of vocational knowledge in vocational education and training (VET was examined for medical assistant students (n = 448. Differences in domain-specific vocational knowledge were predicted by crystallized and fluid intelligence in the course of VET. A multiple matrix design with 3 year-specific booklets was used for the vocational knowledge tests of the medical assistants. The unique and joint contributions of the predictors were investigated with structural equation modeling. Crystallized intelligence emerged as the strongest predictor of vocational knowledge at every stage of VET, while fluid intelligence only showed weak effects. The present results support the knowledge-is-power hypothesis, even in a broad and more naturalistic setting. This emphasizes the relevance of general knowledge for occupations, such as medical assistants, which are more focused on learning hands-on skills than the acquisition of academic knowledge.

Knowledge Is Power for Medical Assistants: Crystallized and Fluid Intelligence As Predictors of Vocational Knowledge.

Science.gov (United States)

Moehring, Anne; Schroeders, Ulrich; Wilhelm, Oliver

2018-01-01

Medical education research has focused almost entirely on the education of future physicians. In comparison, findings on other health-related occupations, such as medical assistants, are scarce. With the current study, we wanted to examine the knowledge-is-power hypothesis in a real life educational setting and add to the sparse literature on medical assistants. Acquisition of vocational knowledge in vocational education and training (VET) was examined for medical assistant students ( n = 448). Differences in domain-specific vocational knowledge were predicted by crystallized and fluid intelligence in the course of VET. A multiple matrix design with 3 year-specific booklets was used for the vocational knowledge tests of the medical assistants. The unique and joint contributions of the predictors were investigated with structural equation modeling. Crystallized intelligence emerged as the strongest predictor of vocational knowledge at every stage of VET, while fluid intelligence only showed weak effects. The present results support the knowledge-is-power hypothesis, even in a broad and more naturalistic setting. This emphasizes the relevance of general knowledge for occupations, such as medical assistants, which are more focused on learning hands-on skills than the acquisition of academic knowledge.

Optical Communication System for Remote Monitoring and Adaptive Control of Distributed Ground Sensors Exhibiting Collective Intelligence

Energy Technology Data Exchange (ETDEWEB)

Cameron, S.M.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

1998-11-01

Comprehensive management of the battle-space has created new requirements in information management, communication, and interoperability as they effect surveillance and situational awareness. The objective of this proposal is to expand intelligent controls theory to produce a uniquely powerful implementation of distributed ground-based measurement incorporating both local collective behavior, and interoperative global optimization for sensor fusion and mission oversight. By using a layered hierarchal control architecture to orchestrate adaptive reconfiguration of autonomous robotic agents, we can improve overall robustness and functionality in dynamic tactical environments without information bottlenecks. In this concept, each sensor is equipped with a miniaturized optical reflectance modulator which is interactively monitored as a remote transponder using a covert laser communication protocol from a remote mothership or operative. Robot data-sharing at the ground level can be leveraged with global evaluation criteria, including terrain overlays and remote imaging data. Information sharing and distributed intelli- gence opens up a new class of remote-sensing applications in which small single-function autono- mous observers at the local level can collectively optimize and measure large scale ground-level signals. AS the need for coverage and the number of agents grows to improve spatial resolution, cooperative behavior orchestrated by a global situational awareness umbrella will be an essential ingredient to offset increasing bandwidth requirements within the net. A system of the type described in this proposal will be capable of sensitively detecting, tracking, and mapping spatial distributions of measurement signatures which are non-stationary or obscured by clutter and inter- fering obstacles by virtue of adaptive reconfiguration. This methodology could be used, for example, to field an adaptive ground-penetrating radar for detection of underground structures in

Adaptive decoupled power control method for inverter connected DG

DEFF Research Database (Denmark)

Sun, Xiaofeng; Tian, Yanjun; Chen, Zhe

2014-01-01

an adaptive droop control method based on online evaluation of power decouple matrix for inverter connected distributed generations in distribution system. Traditional decoupled power control is simply based on line impedance parameter, but the load characteristics also cause the power coupling, and alter...

Evolutionary Psychology and Intelligence Research

Science.gov (United States)

Kanazawa, Satoshi

2010-01-01

This article seeks to unify two subfields of psychology that have hitherto stood separately: evolutionary psychology and intelligence research/differential psychology. I suggest that general intelligence may simultaneously be an evolved adaptation and an individual-difference variable. Tooby and Cosmides's (1990a) notion of random quantitative…

Adaptive control of a PWR core power using neural networks

International Nuclear Information System (INIS)

Arab-Alibeik, H.; Setayeshi, S.

2005-01-01

Reactor power control is important because of safety concerns and the call for regular and appropriate operation of nuclear power plants. It seems that the load-follow operation of these plants will be unavoidable in the future. Discrepancies between the real plant and the model used in controller design for load-follow operation encourage one to use auto-tuning and (or) adaptive techniques. Neural network technology shows great promise for addressing many problems in non-model-based adaptive control methods. Also, there has been a great attention to inverse control especially in the neural and fuzzy control context. Fortunately, online adaptation eliminates some limitations of inverse control and its shortcomings for real world applications. We use a neural adaptive inverse controller to control the power of a PWR reactor. The stability of the system and convergence of the controller parameters are guaranteed during online adaptation phase provided the controller is near the plant's real inverse after offline training period. The performance of the controller is verified using nonlinear simulations in diverse operating conditions

Prognostics-Enabled Power Supply for ADAPT Testbed, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — Ridgetop's role is to develop electronic prognostics for sensing power systems in support of NASA/Ames ADAPT testbed. The prognostic enabled power systems from...

A new approach to PWR power control using intelligent techniques

International Nuclear Information System (INIS)

Boroushaki, M.; Ghofrani, M.B.; Lucas, C.; Yazdanpanah, M.J.; Sadati, N.

2004-01-01

Improved load following capability is one of the main technical performances of advanced PWR(APWR). Controlling the nuclear reactor core during load following operation encounters some difficulties. These difficulties mainly arise from nuclear reactor core limitations in local power peaking, while the core is subject to large and sharp variation of local power density during transients. Axial offset (A.O) is the parameter usually used to represent of core power peaking, in form of a practical parameter. This paper, proposes a new intelligent approach to A.o control of PWR nuclear reactors core during load following operation. This method uses a neural network model of the core to predict the dynamic behavior of the core and a fuzzy critic based on the operator knowledge and experience for the purpose of decision-making during load following operations. Simulation results show that this method can use optimum control rod groups maneuver with variable overlapping and may improve the reactor load following capability

Envisioning engineering education and practice in the coming intelligence convergence era — a complex adaptive systems approach

Science.gov (United States)

Noor, Ahmed K.

2013-12-01

Some of the recent attempts for improving and transforming engineering education are reviewed. The attempts aim at providing the entry level engineers with the skills needed to address the challenges of future large-scale complex systems and projects. Some of the frontier sectors and future challenges for engineers are outlined. The major characteristics of the coming intelligence convergence era (the post-information age) are identified. These include the prevalence of smart devices and environments, the widespread applications of anticipatory computing and predictive / prescriptive analytics, as well as a symbiotic relationship between humans and machines. Devices and machines will be able to learn from, and with, humans in a natural collaborative way. The recent game changers in learnscapes (learning paradigms, technologies, platforms, spaces, and environments) that can significantly impact engineering education in the coming era are identified. Among these are open educational resources, knowledge-rich classrooms, immersive interactive 3D learning, augmented reality, reverse instruction / flipped classroom, gamification, robots in the classroom, and adaptive personalized learning. Significant transformative changes in, and mass customization of, learning are envisioned to emerge from the synergistic combination of the game changers and other technologies. The realization of the aforementioned vision requires the development of a new multidisciplinary framework of emergent engineering for relating innovation, complexity and cybernetics, within the future learning environments. The framework can be used to treat engineering education as a complex adaptive system, with dynamically interacting and communicating components (instructors, individual, small, and large groups of learners). The emergent behavior resulting from the interactions can produce progressively better, and continuously improving, learning environment. As a first step towards the realization of

Development of intelligent MPPT (maximum power point tracking) control for a grid-connected hybrid power generation system

International Nuclear Information System (INIS)

Hong, Chih-Ming; Ou, Ting-Chia; Lu, Kai-Hung

2013-01-01

A hybrid power control system is proposed in the paper, consisting of solar power, wind power, and a diesel-engine. To achieve a fast and stable response for the real power control, an intelligent controller was proposed, which consists of the Wilcoxon (radial basis function network) RBFN and the improved (Elman neural network) ENN for (maximum power point tracking) MPPT. The pitch angle control of wind power uses improved ENN controller, and the output is fed to the wind turbine to achieve the MPPT. The solar array is integrated with an RBFN control algorithm to track the maximum power. MATLAB (MATrix LABoratory)/Simulink was used to build the dynamic model and simulate the solar and diesel-wind hybrid power system. - Highlights: ► To achieve a fast and stable response for the real power control. ► The pitch control of wind power uses improved ENN (Elman neural network) controller to achieve the MPPT (maximum power point tracking). ► The RBFN (radial basis function network) can quickly and accurately track the maximum power output for PV (photovoltaic) array. ► MATLAB was used to build the dynamic model and simulate the hybrid power system. ► This method can reach the desired performance even under different load conditions

Revolutionary Intelligence: The Expanding Intelligence Role of the Iranian Revolutionary Guard Corps

Directory of Open Access Journals (Sweden)

Udit Banerjea

2015-09-01

Full Text Available The Iranian Revolutionary Guard Corps (IRGC is a military and paramilitary organization that is meant to defend the ideals of the Iranian Islamic Revolution in 1979. Since its formation, the IRGC has grown in influence and its intelligence role has expanded. This paper examines the role of the IRGC in Iran’s intelligence system through a comprehensive analysis of the organization of the IRGC’s intelligence arm, along with its operations and capabilities. In doing so, the scope, objectives, resources, customers, and sponsors of the IRGC’s intelligence activities are also analyzed. Additionally, this paper explores how the IRGC interacts with the government of Iran, the Ministry of Intelligence and Security (MOIS, other key internal stakeholders, and foreign client organizations. A key focus of this analysis is the evolution of the relationship between the IRGC and the MOIS and the growing influence of the IRGC in Iran’s intelligence community over the last decade. The paper concludes that the IRGC has now eclipsed the MOIS within Iran’s intelligence community and is one of the most powerful institutions in Iranian politics today, using its intelligence activities as its key means of maintaining power and influence within the country.

Intelligent speed adaptation as an assistive device for drivers with acquired brain injury

DEFF Research Database (Denmark)

Klarborg, Brith; Lahrmann, Harry Spaabæk; Agerholm, Niels

2012-01-01

Intelligent speed adaptation (ISA) was tested as an assistive device for drivers with an acquired brain injury (ABI). The study was part of the “Pay as You Speed” project (PAYS) and used the same equipment and technology as the main study (Lahrmann et al., in press-a, in press-b). Two drivers......, and in general they described driving with ISA as relaxed. ISA reduced the percentage of the total distance that was driven with a speed above the speed limit (PDA), but the subjects relapsed to their previous PDA level in Baseline 2. This suggests that ISA is more suited as a permanent assistive device (i...

2015 Chinese Intelligent Automation Conference

CERN Document Server

Li, Hongbo

2015-01-01

Proceedings of the 2015 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’15, held in Fuzhou, China. The topics include adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, reconfigurable control, etc. Engineers and researchers from academia, industry and the government can gain valuable insights into interdisciplinary solutions in the field of intelligent automation.

Intelligent decision aids for abnormal events in nuclear power plants

International Nuclear Information System (INIS)

Kafka, P.; Polke, H.

1988-01-01

German nuclear power plants are characterized by a high degree of automation, not only for normal operation but also for abnormal events. Therefore the role of the operating personnel is mainly a supervisory function. Nevertheless, for a spectrum of unexpected events the operating personnel have to react with manual recovery actions. In order to minimize human error in such recovery actions, different kinds of intelligent decision aid support the operators today. In this paper such aids are discussed and one of them is described in more detail. (author)

Risk and Disaster Management: From Planning and Expertise to Smart, Intelligent, and Adaptive Systems.

Science.gov (United States)

Benis, Arriel; Notea, Amos; Barkan, Refael

2018-01-01

"Disaster" means some surprising and misfortunate event. Its definition is broad and relates to complex environments. Medical Informatics approaches, methodologies and systems are used as a part of Disaster and Emergency Management systems. At the Holon Institute of Technology - HIT, Israel, in 2016 a National R&D Center: AFRAN was established to study the disaster's reduction aspects. The Center's designation is to investigate and produce new approaches, methodologies and to offer recommendations in the fields of disaster mitigation, preparedness, response and recovery and to disseminate disaster's knowledge. Adjoint to the Center a "Smart, Intelligent, and Adaptive Systems" laboratory (SIAS) was established with the goal to study the applications of Information and Communication Technologies (ICT) and Artificial Intelligence (AI) to Risk and Disaster Management (RDM). In this paper, we are redefining the concept of Disaster, pointing-out how ICT, AI, in the Big Data era, are central players in the RDM game. In addition we show the merit of the Center and lab combination to the benefit of the performed research projects.

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

The Need for Intelligent Control of Space Power Systems

Science.gov (United States)

May, Ryan David; Soeder, James F.; Beach, Raymond F.; McNelis, Nancy B.

2013-01-01

As manned spacecraft venture farther from Earth, the need for reliable, autonomous control of vehicle subsystems becomes critical. This is particularly true for the electrical power system which is critical to every other system. Autonomy can not be achieved by simple scripting techniques due to the communication latency times and the difficulty associated with failures (or combinations of failures) that need to be handled in as graceful a manner as possible to ensure system availability. Therefore an intelligent control system must be developed that can respond to disturbances and failures in a robust manner and ensure that critical system loads are served and all system constraints are respected.

SIMON [Semi-Intelligent Mobile Observing Navigator] combines radiation hardness with computer power

International Nuclear Information System (INIS)

Weber, P.J.; Vanecek, C.W.

1990-01-01

SIMON - the Semi-Intelligent Mobile Observing Navigator - has been under development at the US Department of Energy's (DoE's) Savannah River Laboratory for four years. The robot's on-board intelligence units are designed to be radiation-resistant, making it able to function for extended periods within a remotely operated facility. In its current form, SIMON is being developed by the laboratory's Robotics Group for use in the site's production reactors, but it can be adapted for use in any nuclear facility, including commercial reactors. The challenge for Savannah River Laboratory engineers was to eliminate the need for human inspection of certain components. To do this, they designed a robot that could do three things for reactor operators: measure radiation; measure temperature; and provide televised views inside the reactor facility. To be useful, the robot has to be extremely mobile, and its components had to be able to survive months without maintenance in the radiation, temperature and humidity encountered in nuclear facilities. The robot also had to be cost-effective. (author)

Integration of artificial intelligence systems for nuclear power plants surveillance and diagnostics

International Nuclear Information System (INIS)

Chetry, Moon K.

2012-01-01

The objective of this program is to design, construct operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feed water venture flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant heat rate, d) diagnosis of nuclear power plant transients

Adaptive control method for core power control in TRIGA Mark II reactor

Science.gov (United States)

Sabri Minhat, Mohd; Selamat, Hazlina; Subha, Nurul Adilla Mohd

2018-01-01

The 1MWth Reactor TRIGA PUSPATI (RTP) Mark II type has undergone more than 35 years of operation. The existing core power control uses feedback control algorithm (FCA). It is challenging to keep the core power stable at the desired value within acceptable error bands to meet the safety demand of RTP due to the sensitivity of nuclear research reactor operation. Currently, the system is not satisfied with power tracking performance and can be improved. Therefore, a new design core power control is very important to improve the current performance in tracking and regulate reactor power by control the movement of control rods. In this paper, the adaptive controller and focus on Model Reference Adaptive Control (MRAC) and Self-Tuning Control (STC) were applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, adaptive controller model, and control rods selection programming. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The adaptive control model was presented using Lyapunov method to ensure stable close loop system and STC Generalised Minimum Variance (GMV) Controller was not necessary to know the exact plant transfer function in designing the core power control. The performance between proposed adaptive control and FCA will be compared via computer simulation and analysed the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

ARTIFICIAL INTELLIGENT SYSTEM FOR MEASUREMENT OF HARMONIC POWERS

Directory of Open Access Journals (Sweden)

Jovitha Jerome

2017-11-01

Full Text Available The importance of the electric power quality (PQ demands new methodologies and measurement tools in the power industry for the analysis and measurement of the basic electric magnitudes necessary. This paper presents a new measurement procedure based on neural networks for the estimation of harmonic amplitudes of current/voltage and respective harmonic powers. The measurement scheme is built with two neural network modules. The first module is an adaptive linear neuron (ADALINE that is the kernel part of estimation of complex harmonic coefficients of the current/voltage. The second module is feedforward neural network that obtains the harmonic active/reactive powers. In order to perform digital simulation the Feedforward and Adaline neural network tools were developed in LabVIEW. This measurement algorithm was tested for the practical cases and found to be robust, computationally fast and efficient.

Overview of Intelligent Systems and Operations Development

Science.gov (United States)

Pallix, Joan; Dorais, Greg; Penix, John

2004-01-01

To achieve NASA's ambitious mission objectives for the future, aircraft and spacecraft will need intelligence to take the correct action in a variety of circumstances. Vehicle intelligence can be defined as the ability to "do the right thing" when faced with a complex decision-making situation. It will be necessary to implement integrated autonomous operations and low-level adaptive flight control technologies to direct actions that enhance the safety and success of complex missions despite component failures, degraded performance, operator errors, and environment uncertainty. This paper will describe the array of technologies required to meet these complex objectives. This includes the integration of high-level reasoning and autonomous capabilities with multiple subsystem controllers for robust performance. Future intelligent systems will use models of the system, its environment, and other intelligent agents with which it interacts. They will also require planners, reasoning engines, and adaptive controllers that can recommend or execute commands enabling the system to respond intelligently. The presentation will also address the development of highly dependable software, which is a key component to ensure the reliability of intelligent systems.

Dissolved Gas Analysis Principle-Based Intelligent Approaches to Fault Diagnosis and Decision Making for Large Oil-Immersed Power Transformers: A Survey

Directory of Open Access Journals (Sweden)

Lefeng Cheng

2018-04-01

Full Text Available Compared with conventional methods of fault diagnosis for power transformers, which have defects such as imperfect encoding and too absolute encoding boundaries, this paper systematically discusses various intelligent approaches applied in fault diagnosis and decision making for large oil-immersed power transformers based on dissolved gas analysis (DGA, including expert system (EPS, artificial neural network (ANN, fuzzy theory, rough sets theory (RST, grey system theory (GST, swarm intelligence (SI algorithms, data mining technology, machine learning (ML, and other intelligent diagnosis tools, and summarizes existing problems and solutions. From this survey, it is found that a single intelligent approach for fault diagnosis can only reflect operation status of the transformer in one particular aspect, causing various degrees of shortcomings that cannot be resolved effectively. Combined with the current research status in this field, the problems that must be addressed in DGA-based transformer fault diagnosis are identified, and the prospects for future development trends and research directions are outlined. This contribution presents a detailed and systematic survey on various intelligent approaches to faults diagnosing and decisions making of the power transformer, in which their merits and demerits are thoroughly investigated, as well as their improvement schemes and future development trends are proposed. Moreover, this paper concludes that a variety of intelligent algorithms should be combined for mutual complementation to form a hybrid fault diagnosis network, such that avoiding these algorithms falling into a local optimum. Moreover, it is necessary to improve the detection instruments so as to acquire reasonable characteristic gas data samples. The research summary, empirical generalization and analysis of predicament in this paper provide some thoughts and suggestions for the research of complex power grid in the new environment, as

Failure of Working Memory Training to Enhance Cognition or Intelligence

Science.gov (United States)

Thompson, Todd W.; Waskom, Michael L.; Garel, Keri-Lee A.; Cardenas-Iniguez, Carlos; Reynolds, Gretchen O.; Winter, Rebecca; Chang, Patricia; Pollard, Kiersten; Lala, Nupur; Alvarez, George A.; Gabrieli, John D. E.

2013-01-01

Fluid intelligence is important for successful functioning in the modern world, but much evidence suggests that fluid intelligence is largely immutable after childhood. Recently, however, researchers have reported gains in fluid intelligence after multiple sessions of adaptive working memory training in adults. The current study attempted to replicate and expand those results by administering a broad assessment of cognitive abilities and personality traits to young adults who underwent 20 sessions of an adaptive dual n-back working memory training program and comparing their post-training performance on those tests to a matched set of young adults who underwent 20 sessions of an adaptive attentional tracking program. Pre- and post-training measurements of fluid intelligence, standardized intelligence tests, speed of processing, reading skills, and other tests of working memory were assessed. Both training groups exhibited substantial and specific improvements on the trained tasks that persisted for at least 6 months post-training, but no transfer of improvement was observed to any of the non-trained measurements when compared to a third untrained group serving as a passive control. These findings fail to support the idea that adaptive working memory training in healthy young adults enhances working memory capacity in non-trained tasks, fluid intelligence, or other measures of cognitive abilities. PMID:23717453

Failure of working memory training to enhance cognition or intelligence.

Directory of Open Access Journals (Sweden)

Todd W Thompson

Full Text Available Fluid intelligence is important for successful functioning in the modern world, but much evidence suggests that fluid intelligence is largely immutable after childhood. Recently, however, researchers have reported gains in fluid intelligence after multiple sessions of adaptive working memory training in adults. The current study attempted to replicate and expand those results by administering a broad assessment of cognitive abilities and personality traits to young adults who underwent 20 sessions of an adaptive dual n-back working memory training program and comparing their post-training performance on those tests to a matched set of young adults who underwent 20 sessions of an adaptive attentional tracking program. Pre- and post-training measurements of fluid intelligence, standardized intelligence tests, speed of processing, reading skills, and other tests of working memory were assessed. Both training groups exhibited substantial and specific improvements on the trained tasks that persisted for at least 6 months post-training, but no transfer of improvement was observed to any of the non-trained measurements when compared to a third untrained group serving as a passive control. These findings fail to support the idea that adaptive working memory training in healthy young adults enhances working memory capacity in non-trained tasks, fluid intelligence, or other measures of cognitive abilities.

Overview of Intelligent Power Controller Development for Human Deep Space Exploration

Science.gov (United States)

Soeder, James F.; Dever, Timothy P.; McNelis, Anne M.; Beach, Raymond F.; Trase, Larry M.; May, Ryan D.

2014-01-01

Intelligent or autonomous control of an entire spacecraft is a major technology that must be developed to enable NASA to meet its human exploration goals. NASA's current long term human space platform, the International Space Station, is in low Earth orbit with almost continuous communication with the ground based mission control. This permits the near real-time control by the ground of all of the core systems including power. As NASA moves beyond low Earth orbit, the issues of communication time-lag and lack of communication bandwidth beyond geosynchronous orbit does not permit this type of operation. This paper presents the work currently ongoing at NASA to develop an architecture for an autonomous power control system as well as the effort to assemble that controller into the framework of the vehicle mission manager and other subsystem controllers to enable autonomous control of the complete spacecraft. Due to the common problems faced in both space power systems and terrestrial power system, the potential for spin-off applications of this technology for use in micro-grids located at the edge or user end of terrestrial power grids for peak power accommodation and reliability are described.

Performance analysis of joint diversity combining, adaptive modulation, and power control schemes

KAUST Repository

Qaraqe, Khalid A.

2011-01-01

Adaptive modulation and diversity combining represent very important adaptive solutions for future generations of wireless communication systems. Indeed, in order to improve the performance and the efficiency of these systems, these two techniques have been recently used jointly in new schemes named joint adaptive modulation and diversity combining (JAMDC) schemes. Considering the problem of finding low hardware complexity, bandwidth-efficient, and processing-power efficient transmission schemes for a downlink scenario and capitalizing on some of these recently proposed JAMDC schemes, we propose and analyze in this paper three joint adaptive modulation, diversity combining, and power control (JAMDCPC) schemes where a constant-power variable-rate adaptive modulation technique is used with an adaptive diversity combining scheme and a common power control process. More specifically, the modulation constellation size, the number of combined diversity paths, and the needed power level are jointly determined to achieve the highest spectral efficiency with the lowest possible processing power consumption quantified in terms of the average number of combined paths, given the fading channel conditions and the required bit error rate (BER) performance. In this paper, the performance of these three JAMDCPC schemes is analyzed in terms of their spectral efficiency, processing power consumption, and error-rate performance. Selected numerical examples show that these schemes considerably increase the spectral efficiency of the existing JAMDC schemes with a slight increase in the average number of combined paths for the low signal-to-noise ratio range while maintaining compliance with the BER performance and a low radiated power which yields to a substantial decrease in interference to co-existing users and systems. © 2011 IEEE.

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

Directory of Open Access Journals (Sweden)

Mehdi Neshat

2015-11-01

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

Predicting speech intelligibility based on a correlation metric in the envelope power spectrum domain

DEFF Research Database (Denmark)

Relaño-Iborra, Helia; May, Tobias; Zaar, Johannes

2016-01-01

A speech intelligibility prediction model is proposed that combines the auditory processing front end of the multi-resolution speech-based envelope power spectrum model [mr-sEPSM; Jørgensen, Ewert, and Dau (2013). J. Acoust. Soc. Am. 134(1), 436–446] with a correlation back end inspired by the sh...

Intelligent neural network and fuzzy logic control of industrial and power systems

Science.gov (United States)

Kuljaca, Ognjen

The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of

Swarm intelligence. A whole new way to think about business.

Science.gov (United States)

Bonabeau, E; Meyer, C

2001-05-01

What do ants and bees have to do with business? A great deal, it turns out. Individually, social insects are only minimally intelligent, and their work together is largely self-organized and unsupervised. Yet collectively they're capable of finding highly efficient solutions to difficult problems and can adapt automatically to changing environments. Over the past 20 years, the authors and other researchers have developed rigorous mathematical models to describe this phenomenon, which has been dubbed "swarm intelligence," and they are now applying them to business. Their research has already helped several companies develop more efficient ways to schedule factory equipment, divide tasks among workers, organize people, and even plot strategy. Emulating the way ants find the shortest path to a new food supply, for example, has led researchers at Hewlett-Packard to develop software programs that can find the most efficient way to route phone traffic over a telecommunications network. South-west Airlines has used a similar model to efficiently route cargo. To allocate labor, honeybees appear to follow one simple but powerful rule--they seem to specialize in a particular activity unless they perceive an important need to perform another function. Using that model, researchers at Northwestern University have devised a system for painting trucks that can automatically adapt to changing conditions. In the future, the authors speculate, a company might structure its entire business using the principles of swarm intelligence. The result, they believe, would be the ultimate self-organizing enterprise--one that could adapt quickly and instinctively to fast-changing markets.

Adaptation of thermal power plants: The (ir)relevance of climate (change) information

International Nuclear Information System (INIS)

Bogmans, Christian W.J.; Dijkema, Gerard P.J.; Vliet, Michelle T.H. van

2017-01-01

When does climate change information lead to adaptation? We analyze thermal power plant adaptation by means of investing in water-saving (cooling) technology to prevent a decrease in plant efficiency and load reduction. A comprehensive power plant investment model, forced with downscaled climate and hydrological projections, is then numerically solved to analyze the adaptation decisions of a selection of real power plants. We find that operators that base their decisions on current climatic conditions are likely to make identical choices and perform just as well as operators that are fully ‘informed’ about climate change. Where electricity supply is mainly generated by thermal power plants, heat waves, droughts and low river flow may impact electricity supply for decades to come. - Highlights: • We analyze adaptation to climate change by thermal power plants. • A numerical investment model is applied to a coal plant and a nuclear power plant. • The numerical analysis is based on climate and hydrological projections. • Climate change information has a relatively small effect on a power plant's NPV. • Uncertainty and no-regret benefits lower the value of climate change information.

Cellular computational generalized neuron network for frequency situational intelligence in a multi-machine power system.

Science.gov (United States)

Wei, Yawei; Venayagamoorthy, Ganesh Kumar

2017-09-01

To prevent large interconnected power system from a cascading failure, brownout or even blackout, grid operators require access to faster than real-time information to make appropriate just-in-time control decisions. However, the communication and computational system limitations of currently used supervisory control and data acquisition (SCADA) system can only deliver delayed information. However, the deployment of synchrophasor measurement devices makes it possible to capture and visualize, in near-real-time, grid operational data with extra granularity. In this paper, a cellular computational network (CCN) approach for frequency situational intelligence (FSI) in a power system is presented. The distributed and scalable computing unit of the CCN framework makes it particularly flexible for customization for a particular set of prediction requirements. Two soft-computing algorithms have been implemented in the CCN framework: a cellular generalized neuron network (CCGNN) and a cellular multi-layer perceptron network (CCMLPN), for purposes of providing multi-timescale frequency predictions, ranging from 16.67 ms to 2 s. These two developed CCGNN and CCMLPN systems were then implemented on two different scales of power systems, one of which installed a large photovoltaic plant. A real-time power system simulator at weather station within the Real-Time Power and Intelligent Systems (RTPIS) laboratory at Clemson, SC, was then used to derive typical FSI results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Use of artificial intelligence to enhance the safety of nuclear power plants

International Nuclear Information System (INIS)

Uhrig, R.E.

1989-01-01

In the operation of a nuclear power plant, the sheer magnitude of the number of process parameters and systems interactions poses difficulties for the operators, particularly during abnormal or emergency situations. Recovery from an upset situation depends upon the facility with which the available raw data can be converted into and assimilated as meaningful knowledge. Plant personnel are sometimes affected by stress and emotion, which may have varying degrees of influence on their performance. Expert systems can take some of the uncertainty and guesswork out of their decisions by providing expert advice and rapid access to a large information base. Application of artificial intelligence technologies, particularly expert systems, to control room activities in a nuclear power plant has the potential to reduce operator error and improve power plant safety and reliability

Use of artificial intelligence to enhance the safety of nuclear power plants

International Nuclear Information System (INIS)

Uhrig, R.E.

1988-01-01

In the operation of a nuclear power plant, the sheer magnitude of the number of process parameters and systems interactions poses difficulties for the operators, particularly during abnormal or emergency situations. Recovery from an upset situation depends upon the facility with which the available raw data can be converted into and assimilated as meaningful knowledge. Plant personnel are sometimes affected by stress and emotion, which may have varying degrees of influence on their performance. Expert systems can take some of the uncertainty and guesswork out of their decisions by providing expert advice and rapid access to a large information base. Application of artificial intelligence technologies, particularly expert systems, to control room activities in a nuclear power plant has the potential to reduce operator error and improve power plant safety and reliability. 12 refs

Intelligent system to control electric power distribution networks

Directory of Open Access Journals (Sweden)

Pablo CHAMOSO

2016-07-01

Full Text Available The use of high voltage power lines transport involves some risks that may be avoided with periodic reviews as imposed by law in most countries. The objective of this work is to reduce the number of these periodic reviews so that the maintenance cost of power lines is also reduced. To reduce the number of transmission towers (TT to be reviewed, a virtual organization (VO based system of agents is proposed in conjunction with different artificial intelligence methods and algorithms. This system is able to propose a sample of TT from a selected set to be reviewed and to ensure that the whole set will have similar values without needing to review all the TT. As a result, the system provides a software solution to manage all the review processes and all the TT of Spain, allowing the review companies to use the application either when they initiate a new review process for a whole line or area of TT, or when they want to place an entirely new set of TT, in which case the system would recommend the best place and the best type of structure to use.

Daily Average Wind Power Interval Forecasts Based on an Optimal Adaptive-Network-Based Fuzzy Inference System and Singular Spectrum Analysis

Directory of Open Access Journals (Sweden)

Zhongrong Zhang

2016-01-01

Full Text Available Wind energy has increasingly played a vital role in mitigating conventional resource shortages. Nevertheless, the stochastic nature of wind poses a great challenge when attempting to find an accurate forecasting model for wind power. Therefore, precise wind power forecasts are of primary importance to solve operational, planning and economic problems in the growing wind power scenario. Previous research has focused efforts on the deterministic forecast of wind power values, but less attention has been paid to providing information about wind energy. Based on an optimal Adaptive-Network-Based Fuzzy Inference System (ANFIS and Singular Spectrum Analysis (SSA, this paper develops a hybrid uncertainty forecasting model, IFASF (Interval Forecast-ANFIS-SSA-Firefly Alogorithm, to obtain the upper and lower bounds of daily average wind power, which is beneficial for the practical operation of both the grid company and independent power producers. To strengthen the practical ability of this developed model, this paper presents a comparison between IFASF and other benchmarks, which provides a general reference for this aspect for statistical or artificially intelligent interval forecast methods. The comparison results show that the developed model outperforms eight benchmarks and has a satisfactory forecasting effectiveness in three different wind farms with two time horizons.

Adaptive fuzzy controller based MPPT for photovoltaic systems

International Nuclear Information System (INIS)

Guenounou, Ouahib; Dahhou, Boutaib; Chabour, Ferhat

2014-01-01

Highlights: • We propose a fuzzy controller with adaptive output scaling factor as a maximum power point tracker of photovoltaic system. • The proposed controller integrates two different rule bases defined on error and change of error. • Our controller can track the maximum power point with better performances when compared to its conventional counterpart. - Abstract: This paper presents an intelligent approach to optimize the performances of photovoltaic systems. The system consists of a PV panel, a DC–DC boost converter, a maximum power point tracker controller and a resistive load. The key idea of the proposed approach is the use of a fuzzy controller with an adaptive gain as a maximum power point tracker. The proposed controller integrates two different rule bases. The first is used to adjust the duty cycle of the boost converter as in the case of a conventional fuzzy controller while the second rule base is designed for an online adjusting of the controller’s gain. The performances of the adaptive fuzzy controller are compared with those obtained using a conventional fuzzy controllers with different gains and in each case, the proposed controller outperforms its conventional counterpart

Neural network-based control of an intelligent solar Stirling pump

International Nuclear Information System (INIS)

Tavakolpour-Saleh, A.R.; Jokar, H.

2016-01-01

In this paper, an ANN (artificial neural network) control system is applied to a novel solar-powered active LTD (low temperature differential) Stirling pump. First, a mathematical description of the proposed Stirling pump is presented. Then, optimum operating frequencies of the converter corresponding to different operating conditions (i.e. different sink and source temperatures and water heads) are investigated using the proposed mathematical framework. It is found that the proposed complex mathematical scheme has a very slow convergence and thus, is not appropriate for real-time implementation of the model-based controller. Consequently, a NN (neural network) model with a lower complexity is proposed to learn the simulation data obtained from the mathematical model. The designed neural network controller is thus applied to a digital processor to effectively tune the converter frequency so that a maximum output power is acquired. Finally, the performance of the proposed mechatronic system is evaluated experimentally. The experimental results clearly demonstrate the feasibility of pumping water at low temperature difference under variable operating conditions using the proposed intelligent Stirling converter. - Highlights: • A novel intelligent solar-powered active LTD Stirling pump was introduced. • A neural network controller was used to tune the converter speed. • The intelligent converter was able to adapt itself to different operating conditions. • It was possible to excite the water column with its resonance mode. • Experimental results showed the effectiveness of the proposed converter.

Intelligent Control Framework for the Feeding System in the Biomass Power Plant

Directory of Open Access Journals (Sweden)

Sun Jin

2015-01-01

Full Text Available This paper proposes an intelligent control framework for biomass drying process with flue gases based on FLC (fuzzy logic controller and CAN (Controller Area Network bus. In the operation of a biomass drying process, in order to get the biomass with the set-point low moisture content dried by waste high temperature flue gases, it is necessary to intelligent control for the biomass flow rate. Use of an experiment with varied materials at different initial moisture contents enables acquisition of the biomass flow rates as initial setting values. Set the error between actual straw moisture content and set-point, and rate of change of error as two inputs. the biomass flow rate can be acquired by the fuzzy logic computing as the output. Since the length of dryer is more than twenty meters, the integration by the CAN bus can ensure real-time reliable data acquisition and processing. The control framework for biomass drying process can be applied to a variety of biomass, such as, cotton stalk, corn stalk, rice straw, wheat straw, sugar cane. It has strong potential for practical applications because of its advantages on intelligent providing the set-point low moisture content of biomass feedstock for power generation equipment.

Applications of Adaptive Learning Controller to Synthetic Aperture Radar.

Science.gov (United States)

1985-02-01

TERMS (Continue on retuerse if necessary and identify by block num ber) FIELD YGROUP SUB. GR. Adaptive control, aritificial intelligence , synthetic aetr1...application of Artificial Intelligence methods to Synthetic Aperture Radars (SARs) is investigated. It was shown that the neuron-like Adaptive Learning...wavelength Al SE!RI M RADAR DIVISION REFERENCES 1. Barto, A.G. and R.S. Sutton, Goal Seeking Components for Adaptive Intelligence : An Initial Assessment

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...

Design of intelligent comfort control system with human learning and minimum power control strategies

International Nuclear Information System (INIS)

Liang, J.; Du, R.

2008-01-01

This paper presents the design of an intelligent comfort control system by combining the human learning and minimum power control strategies for the heating, ventilating and air conditioning (HVAC) system. In the system, the predicted mean vote (PMV) is adopted as the control objective to improve indoor comfort level by considering six comfort related variables, whilst a direct neural network controller is designed to overcome the nonlinear feature of the PMV calculation for better performance. To achieve the highest comfort level for the specific user, a human learning strategy is designed to tune the user's comfort zone, and then, a VAV and minimum power control strategy is proposed to minimize the energy consumption further. In order to validate the system design, a series of computer simulations are performed based on a derived HVAC and thermal space model. The simulation results confirm the design of the intelligent comfort control system. In comparison to the conventional temperature controller, this system can provide a higher comfort level and better system performance, so it has great potential for HVAC applications in the future

Intelligent tutors for control center operator training

Energy Technology Data Exchange (ETDEWEB)

Vale, Z.A. [Porto Univ. (Portugal). Dept. of Electrical and Computer Engineering; Fernandes, M.F.; Marques, A. [Electricity of Portugal, Sacavem (Portugal)

1995-12-31

Power systems are presently remotely operated and controlled from control centers that receive on-line information about the power system state. Control center operators have very high-demanding tasks what makes their training a key issue for the performance of the whole power system. Simulators are usually used by electrical utilities for this purpose but they are very expensive applications and their use requires the preparation of the training sessions by qualified training staff which is a very time consuming task. Due to this, these simulators are only used a few times a year. Intelligent Tutoring Systems (ITS) provide some new possibilities for control center operator training making easier its use without much assistance of the teaching staff. On the other hand, an expert system in use in a control center can be adapted to an ITS to train operators without much effort. 18 refs

Development of an Intelligent Maximum Power Point Tracker Using an Advanced PV System Test Platform

DEFF Research Database (Denmark)

Spataru, Sergiu; Amoiridis, Anastasios; Beres, Remus Narcis

2013-01-01

The performance of photovoltaic systems is often reduced by the presence of partial shadows. The system efficiency and availability can be improved by a maximum power point tracking algorithm that is able to detect partial shadow conditions and to optimize the power output. This work proposes...... an intelligent maximum power point tracking method that monitors the maximum power point voltage and triggers a current-voltage sweep only when a partial shadow is detected, therefore minimizing power loss due to repeated current-voltage sweeps. The proposed system is validated on an advanced, flexible...... photovoltaic inverter system test platform that is able to reproduce realistic partial shadow conditions, both in simulation and on hardware test system....

Development of Intelligent Database Program for PSI/ISI Data Management of Nuclear Power Plant (Part II)

International Nuclear Information System (INIS)

Park, Un Su; Park, Ik Keun; Um, Byong Guk; Lee, Jong Po; Han, Chi Hyun

2000-01-01

In a previous paper, we have discussed the intelligent Windows 95-based data management program(IDPIN) which was developed for effective and efficient management of large amounts of pre-/in-service inspection(PSI/ISI) data of Kori nuclear power plants. The IDPIN program enables the prompt extraction of previously conducted PSI/ISI conditions and results so that the time-consuming data management, painstaking data processing and analysis of the past are avoided. In this study, the intelligent Windows based data management program(WS-IDPIN) has been developed as an effective data management of PSI/ISI data for the Wolsong nuclear power plants. The WS-IDPIN program includes the modules of comprehensive management and analysis of PSI/ISI results, statistical reliability assessment program of PSI/ISI results(depth and length sizing performance etc), standardization of UT report form and computerization of UT results. In addition, the program can be further developed as a unique PSI/ISI data management expert system which can be part of the PSI/ISI total support system for Korean nuclear power plants

A Novel Technique for Maximum Power Point Tracking of a Photovoltaic Based on Sensing of Array Current Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

Science.gov (United States)

El-Zoghby, Helmy M.; Bendary, Ahmed F.

2016-10-01

Maximum Power Point Tracking (MPPT) is now widely used method in increasing the photovoltaic (PV) efficiency. The conventional MPPT methods have many problems concerning the accuracy, flexibility and efficiency. The MPP depends on the PV temperature and solar irradiation that randomly varied. In this paper an artificial intelligence based controller is presented through implementing of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to obtain maximum power from PV. The ANFIS inputs are the temperature and cell current, and the output is optimal voltage at maximum power. During operation the trained ANFIS senses the PV current using suitable sensor and also senses the temperature to determine the optimal operating voltage that corresponds to the current at MPP. This voltage is used to control the boost converter duty cycle. The MATLAB simulation results shows the effectiveness of the ANFIS with sensing the PV current in obtaining the MPPT from the PV.

Learning for intelligent mobile robots

Science.gov (United States)

Hall, Ernest L.; Liao, Xiaoqun; Alhaj Ali, Souma M.

2003-10-01

Unlike intelligent industrial robots which often work in a structured factory setting, intelligent mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths. However, such machines have many potential applications in medicine, defense, industry and even the home that make their study important. Sensors such as vision are needed. However, in many applications some form of learning is also required. The purpose of this paper is to present a discussion of recent technical advances in learning for intelligent mobile robots. During the past 20 years, the use of intelligent industrial robots that are equipped not only with motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. However, relatively little has been done concerning learning. Adaptive and robust control permits one to achieve point to point and controlled path operation in a changing environment. This problem can be solved with a learning control. In the unstructured environment, the terrain and consequently the load on the robot"s motors are constantly changing. Learning the parameters of a proportional, integral and derivative controller (PID) and artificial neural network provides an adaptive and robust control. Learning may also be used for path following. Simulations that include learning may be conducted to see if a robot can learn its way through a cluttered array of obstacles. If a situation is performed repetitively, then learning can also be used in the actual application. To reach an even higher degree of autonomous operation, a new level of learning is required. Recently learning theories such as the adaptive critic have been proposed. In this type of learning a critic provides a grade to the controller of an action module such as a robot. The creative control process is used that is "beyond the adaptive critic." A

Intelligent Systems For Aerospace Engineering: An Overview

Science.gov (United States)

KrishnaKumar, K.

2003-01-01

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

Designing an Adaptive Nuero-Fuzzy Inference System for Evaluating the Business Intelligence System Implementation in Software Industry

Directory of Open Access Journals (Sweden)

Iman Raeesi Vanani

2015-03-01

Full Text Available The main goal of research is designing an adaptive nuero-fuzzy inference system for evaluating the implementation of business intelligence systems in software industry. Iranian software development organizations have been facing a lot of problems in case of implementing business intelligence systems. This system would be helpful in recognizing the conditions and prerequisites of success or failure. Organizations can recalculate the neuro-fuzzy system outputs with some considerations on various inputs to figure out which inputs have the most effect on the implementation outputs. By resolving the problems on inputs, organizations can achieve a better level of implementation success. The designed system has been trained by a data set and afterwards, it has been evaluated. The trained system has reached the error value of 0.08. Eventually, some recommendations have been provided for software development firms on the areas that might need more considerations and improvements.

Using FML and fuzzy technology in adaptive ambient intelligent environments

NARCIS (Netherlands)

Acampora, G.; Loia, V.

2005-01-01

Ambient Intelligence (AmI, shortly) gathers best re-sults from three key technologies, Ubiquitous Computing, Ubiq-uitous Communication, and Intelligent User Friendly Inter-faces. The functional and spatial distribution of tasks is a natu-ral thrust to employ multi-agent paradigm to design and

Adaptive electrothermal protection of power converters

Directory of Open Access Journals (Sweden)

Baraniuk G. A.

2017-06-01

Full Text Available Thermal management for power converters during normal operation and transient modes when electrical components are warmed up is an actual problem. This can be particularly important for converters with intermittent duty operation, e.g. power supplies for resistance welding. According to some research, nearly 60% of failures are temperature-induced, and for every 10°C temperature rise in operating environment the failure rate nearly doubles. In this paper, thermal motion of state equations eigenvalue is analysed. It is shown, that in semiconductor converters with an output smoothing filter it is appropriate to use thermal protection devices based on thermal normalisation of the converter filter and, while for cases when short circuits are possible it is appropriate to use a soft start system with thermal adaptation for soft start time factor. Based on these results, two systems of thermal protections operating for semiconductor power converters are introduced. Simulation of combined electromagnetic and thermal processes in buck converter operating with both thermal management systems in overlapping environments MATLAB/Simulink and PLECS showed the possibility to significantly reduce thermal shock on semiconductor components. Using the system of filter parameters normalisation decreases the temperature of the crystal from 210°C to 85°C, using the adaptive soft start system decreases the temperature from 180°C to 80°C. The simulation results are confirmed by tests on real devices.

Computational intelligence in nuclear engineering

International Nuclear Information System (INIS)

Uhrig, Robert E.; Hines, J. Wesley

2005-01-01

Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several Changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations

Incipient fault detection and power system protection for spaceborne systems

Science.gov (United States)

Russell, B. Don; Hackler, Irene M.

1987-01-01

A program was initiated to study the feasibility of using advanced terrestrial power system protection techniques for spacecraft power systems. It was designed to enhance and automate spacecraft power distribution systems in the areas of safety, reliability and maintenance. The proposed power management/distribution system is described as well as security assessment and control, incipient and low current fault detection, and the proposed spaceborne protection system. It is noted that the intelligent remote power controller permits the implementation of digital relaying algorithms with both adaptive and programmable characteristics.

Agent Based Control of Electric Power Systems with Distributed Generation

DEFF Research Database (Denmark)

Saleem, Arshad

and subsystems that are able to coordinate, communicate, cooperate, adapt to emerging situations and self organize in an intelligent way. At the same time, rapid development in information and and communication technologies (ICT) have brought new opportunities and elucidations. New Technologies and standards...... control strategies. The results have been discussed from case studies of multiagent based distributed control scenarios in electric power systems. The main contribution of this work is a proposal for system design methodology for application of intelligent agent technology in power systems....... Situation in Denmark is even more interesting, with a current 20% penetration of wind energy it is moving towards an ambitious goal of 50% penetration by the year 2050. Realization of these concepts requires that power systems should be of distributed nature { consisting of autonomous components...

E-learning environment as intelligent tutoring system

Science.gov (United States)

Nagyová, Ingrid

2017-07-01

The development of computers and artificial intelligence theory allow their application in the field of education. Intelligent tutoring systems reflect student learning styles and adapt the curriculum according to their individual needs. The building of intelligent tutoring systems requires not only the creation of suitable software, but especially the search and application of the rules enabling ICT to individually adapt the curriculum. The main idea of this paper is to attempt to specify the rules for dividing the students to systematically working students and more practically or pragmatically inclined students. The paper shows that monitoring the work of students in e-learning environment, analysis of various approaches to educational materials and correspondence assignments show different results for the defined groups of students.

Integration of artificial intelligence systems for nuclear power plant surveillance and diagnostics

International Nuclear Information System (INIS)

Uhrig, R.E.; Hines, J.W.; Nelson, W.R.

1998-01-01

The objective of this program is to design, construct, operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems, and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feedwater venturi flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant beat rate, d) diagnosis of nuclear power plant transients, and e) increase in thermal power through monitoring of DNBR (Departure from Nucleate Boiling Regime). To increase the likelihood of these individual systems being used in a nuclear power plant, they must be integrated into a single system that operates virtually autonomously, collecting, interpreting, and providing information to the operators in a simple and understandable format. (author)

Integration of artificial intelligence systems for nuclear power plant surveillance and diagnostics

Energy Technology Data Exchange (ETDEWEB)

Uhrig, R.E.; Hines, J.W.; Nelson, W.R.

1998-07-01

The objective of this program is to design, construct, operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems, and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feedwater venturi flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant beat rate, d) diagnosis of nuclear power plant transients, and e) increase in thermal power through monitoring of DNBR (Departure from Nucleate Boiling Regime). To increase the likelihood of these individual systems being used in a nuclear power plant, they must be integrated into a single system that operates virtually autonomously, collecting, interpreting, and providing information to the operators in a simple and understandable format. (author)

Intelligent Distributed Computing VI : Proceedings of the 6th International Symposium on Intelligent Distributed Computing

CERN Document Server

Badica, Costin; Malgeri, Michele; Unland, Rainer

2013-01-01

This book represents the combined peer-reviewed proceedings of the Sixth International Symposium on Intelligent Distributed Computing -- IDC~2012, of the International Workshop on Agents for Cloud -- A4C~2012 and of the Fourth International Workshop on Multi-Agent Systems Technology and Semantics -- MASTS~2012. All the events were held in Calabria, Italy during September 24-26, 2012. The 37 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: adaptive and autonomous distributed systems, agent programming, ambient assisted living systems, business process modeling and verification, cloud computing, coalition formation, decision support systems, distributed optimization and constraint satisfaction, gesture recognition, intelligent energy management in WSNs, intelligent logistics, machine learning, mobile agents, parallel and distributed computational intelligence, parallel evolutionary computing, trus...

Low-power adaptive filter based on RNS components

DEFF Research Database (Denmark)

Bernocchi, Gian Luca; Cardarilli, Gian Carlo; Del Re, Andrea

2007-01-01

In this paper a low-power implementation of an adaptive FIR filter is presented. The filter is designed to meet the constraints of channel equalization for fixed wireless communications that typically requires a large number of taps, but a serial updating of the filter coefficients, based...... on the least mean squares (LMS) algorithm, is allowed. Previous work showed that the use of the residue number system (RNS) for the variable FIR filter grants advantages both in area and power consumption. On the other hand, the use of a binary serial implementation of the adaptation algorithm eliminates...... the need for complex scaling circuits in RNS. The advantages in terms of area and speed of the presented filter, with respect to its two's complement counterpart, are evaluated for implementations in standard cells....

Hybrid power system intelligent operation and protection involving distributed architectures and pulsed loads

Science.gov (United States)

Mohamed, Ahmed

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available

Vision Guided Intelligent Robot Design And Experiments

Science.gov (United States)

Slutzky, G. D.; Hall, E. L.

1988-02-01

The concept of an intelligent robot is an important topic combining sensors, manipulators, and artificial intelligence to design a useful machine. Vision systems, tactile sensors, proximity switches and other sensors provide the elements necessary for simple game playing as well as industrial applications. These sensors permit adaption to a changing environment. The AI techniques permit advanced forms of decision making, adaptive responses, and learning while the manipulator provides the ability to perform various tasks. Computer languages such as LISP and OPS5, have been utilized to achieve expert systems approaches in solving real world problems. The purpose of this paper is to describe several examples of visually guided intelligent robots including both stationary and mobile robots. Demonstrations will be presented of a system for constructing and solving a popular peg game, a robot lawn mower, and a box stacking robot. The experience gained from these and other systems provide insight into what may be realistically expected from the next generation of intelligent machines.

Validation of the Serbian adaptation of the Trait Emotional Intelligence Questionnaire-Child Form (TEIQue-CF

Directory of Open Access Journals (Sweden)

Banjac Sonja

2016-01-01

Full Text Available This study investigated trait EI in childhood in a Serbian population by validating a Serbian adaptation of the Trait Emotional Intelligence Questionnaire - Child Form (TEIQue-CF. All 606 participants (Mage = 10.33, SD = 1.55 completed the TEIQue-CF, the Reading the Mind in the Eyes Test (revised version, and the Guess Who peer assessment. Data on academic achievement and truancy were also obtained. The Serbian TEIQue-CF demonstrated robust psychometric properties with satisfactory internal consistencies and extensive evidence of validity in relation to criteria such as emotion recognition, academic grades, truancy rates, and peer ratings. Factor analyses suggested a two-factor solution for the total sample, but a unifactorial structure for the two groups of younger children aged 8 to 9 and 10 to 11. Overall, the results corroborate the validity of the Serbian adaptation and the theoretical and practical importance of the construct of trait EI in children. [Projekat Ministarstva nauke Republike Srbije, br. 179018

A Statistical Model for Uplink Intercell Interference with Power Adaptation and Greedy Scheduling

KAUST Repository

Tabassum, Hina

2012-10-03

This paper deals with the statistical modeling of uplink inter-cell interference (ICI) considering greedy scheduling with power adaptation based on channel conditions. The derived model is implicitly generalized for any kind of shadowing and fading environments. More precisely, we develop a generic model for the distribution of ICI based on the locations of the allocated users and their transmit powers. The derived model is utilized to evaluate important network performance metrics such as ergodic capacity, average fairness and average power preservation numerically. Monte-Carlo simulation details are included to support the analysis and show the accuracy of the derived expressions. In parallel to the literature, we show that greedy scheduling with power adaptation reduces the ICI, average power consumption of users, and enhances the average fairness among users, compared to the case without power adaptation. © 2012 IEEE.

A Statistical Model for Uplink Intercell Interference with Power Adaptation and Greedy Scheduling

KAUST Repository

Tabassum, Hina; Yilmaz, Ferkan; Dawy, Zaher; Alouini, Mohamed-Slim

2012-01-01

This paper deals with the statistical modeling of uplink inter-cell interference (ICI) considering greedy scheduling with power adaptation based on channel conditions. The derived model is implicitly generalized for any kind of shadowing and fading environments. More precisely, we develop a generic model for the distribution of ICI based on the locations of the allocated users and their transmit powers. The derived model is utilized to evaluate important network performance metrics such as ergodic capacity, average fairness and average power preservation numerically. Monte-Carlo simulation details are included to support the analysis and show the accuracy of the derived expressions. In parallel to the literature, we show that greedy scheduling with power adaptation reduces the ICI, average power consumption of users, and enhances the average fairness among users, compared to the case without power adaptation. © 2012 IEEE.

Intelligent control for large-scale variable speed variable pitch wind turbines

Institute of Scientific and Technical Information of China (English)

Xinfang ZHANG; Daping XU; Yibing LIU

2004-01-01

Large-scale wind turbine generator systems have strong nonlinear multivariable characteristics with many uncertain factors and disturbances.Automatic control is crucial for the efficiency and reliability of wind turbines.On the basis of simplified and proper model of variable speed variable pitch wind turbines,the effective wind speed is estimated using extended Kalman filter.Intelligent control schemes proposed in the paper include two loops which operate in synchronism with each other.At below-rated wind speed,the inner loop adopts adaptive fuzzy control based on variable universe for generator torque regulation to realize maximum wind energy capture.At above-rated wind speed, a controller based on least square support vector machine is proposed to adjust pitch angle and keep rated output power.The simulation shows the effectiveness of the intelligent control.

Requirement analysis for autonomous systems and intelligent agents in future Danish electric power systems

DEFF Research Database (Denmark)

Saleem, Arshad; Lind, Morten

2010-01-01

we review innovative control architectures in electric power systems such as Microgrids, Virtual power plants and Cell based systems. We evaluate application of autonomous systems and intelligent agents in each of these control architectures particularly in the context of Denmark's strategic energy...... plans. The second part formulates a flexible control architecture for electric power systems with very high penetration of distributed generation. This control architecture is based upon the requirements identified in the first part. We also present development of a software framework to test......Denmark has already achieved a record of 20% penetration of wind power and now moving towards even higher targets with an increasing part of the electricity produced by distributed generators (DGs). In this paper we report work from a sub activity "subgrid design" of the EcoGrid.dk project. First...

Multi Agent System Based Adaptive Protection for Dispersed Generation Integrated Distribution Systems

DEFF Research Database (Denmark)

Liu, Leo; Rather, Zakir Hussain; Bak, Claus Leth

2013-01-01

The increasing penetration of dispersed generation (DG) brings challenges to conventional protection approaches of distribution system, mainly due to bi-directional power flow and variable fault current contribution from different generation technology-based DG units. Moreover, the trend......) is proposed. The adaptive protection intelligently adopts suitable settings for the variation of fault current from diversified DG units. Furthermore, the structure of mobile MAS with additional flexibility is capable of adapting the changes of system topology in a short period, e.g. radial/meshed, grid...

An adaptive control application in a large thermal combined power plant

International Nuclear Information System (INIS)

Kocaarslan, Ilhan; Cam, Ertugrul

2007-01-01

In this paper, an adaptive controller was applied to a 765 MW large thermal power plant to decrease operating costs, increase quality of generated electricity and satisfy environmental concerns. Since power plants may present several operating problems such as disturbances and severe effects at operating points, design of their controllers needs to be carried out adequately. For these reasons, first, a reduced mathematical model was developed under Computer Aided Analysis and Design Package for Control (CADACS), so that the results of the experimental model have briefly been discussed. Second, conventional PID and adaptive controllers were designed and implemented under the real-time environment of the CADACS software. Additionally, the design of the adaptive model-reference and conventional PID controllers used in the power plant for real-time control were theoretically presented. All processes were realized in real-time. Due to safety restrictions, a direct connection to the sensors and actuators of the plant was not allowed. Instead a coupling to the control system was realized. This offers, in addition, the usage of the supervisory functions of an industrial process computer system. Application of the controllers indicated that the proposed adaptive controller has better performances for rise and settling times of electrical power, and enthalpy outputs than the conventional PID controller does

Revisiting the Psychology of Intelligence Analysis: From Rational Actors to Adaptive Thinkers

Science.gov (United States)

Puvathingal, Bess J.; Hantula, Donald A.

2012-01-01

Intelligence analysis is a decision-making process rife with ambiguous, conflicting, irrelevant, important, and excessive information. The U.S. Intelligence Community is primed for psychology to lend its voice to the "analytic transformation" movement aimed at improving the quality of intelligence analysis. Traditional judgment and decision making…

Interference mitigation through adaptive power control in wireless sensor networks

NARCIS (Netherlands)

Chincoli, M.; Bacchiani, C.; Syed, Aly; Exarchakos, G.; Liotta, A.

2016-01-01

Adaptive transmission power control schemes have been introduced in wireless sensor networks to adjust energy consumption under different network conditions. This is a crucial goal, given the constraints under which sensor communications operate. Power reduction may however have counter-productive

2013 Chinese Intelligent Automation Conference

CERN Document Server

Deng, Zhidong

2013-01-01

Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation.   Zengqi Sun and Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

2013 Chinese Intelligent Automation Conference

CERN Document Server

Deng, Zhidong

2013-01-01

Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation. Zengqi Sun and Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

Special Issue on Intelligent Robots

Directory of Open Access Journals (Sweden)

Genci Capi

2013-08-01

Full Text Available The research on intelligent robots will produce robots that are able to operate in everyday life environments, to adapt their program according to environment changes, and to cooperate with other team members and humans. Operating in human environments, robots need to process, in real time, a large amount of sensory data—such as vision, laser, microphone—in order to determine the best action. Intelligent algorithms have been successfully applied to link complex sensory data to robot action. This editorial briefly summarizes recent findings in the field of intelligent robots as described in the articles published in this special issue.

Is adaptation of the word accentuation test of premorbid intelligence necessary for use among older, Spanish-speaking immigrants in the United States?

Science.gov (United States)

Schrauf, Robert W; Weintraub, Sandra; Navarro, Ellen

2006-05-01

Adaptations of the National Adult Reading Test (NART) for assessing premorbid intelligence in languages other than English requires (a) generating word-items that are rare and do not follow grapheme-to-phoneme mappings common in that language, and (b) subsequent validation against a cognitive battery normed on the population of interest. Such tests exist for Italy, France, Spain, and Argentina, all normed against national versions of the Wechsler Adult Intelligence Scale. Given the varieties of Spanish spoken in the United States, the adaptation of the Spanish Word Accentuation Test (WAT) requires re-validating the original word list, plus possible new items, against a cognitive battery that has been normed on Spanish-speakers from many countries. This study reports the generation of 55 additional words and revalidation in a sample of 80 older, Spanish-dominant immigrants. The Batería Woodcock-Muñoz Revisada (BWM-R), normed on Spanish speakers from six countries and five U.S. states, was used to establish criterion validity. The original WAT word list accounted for 77% of the variance in the BWM-R and 58% of the variance in Ravens Colored Progressive Matrices, suggesting that the unmodified list possesses adequate predictive validity as an indicator of intelligence. Regression equations are provided for estimating BWM-R and Ravens scores from WAT scores.

The person who eases your mind "Ibasyo" and emotional intelligence in interpersonal adaptation

Directory of Open Access Journals (Sweden)

Hiroshi Toyota

2009-11-01

Full Text Available The present study was carried out to examine the effect of the "Ibasyo" (the person who eases one's mind and emotional intelligence (EI on self-esteem and loneliness. Five hundred and eight Japanese undergraduates were asked to choose one of the alternatives (e. g., myself, mother, friend to answer the question "Who is the person that eases your mind?" Then, they were asked to rate items from scales corresponding to EI, self-esteem and loneliness. Multiple regression analyses indicated that both Ibasyo and EI explained 25% of loneliness, but only EI explained 25% of self-esteem. The analyses also showed differences of sub-abilities in EI that determined the level of loneliness and self-esteem among Ibasyo groups. These results are interpreted as showing the importance of EI in adaptation.

The highly intelligent virtual agents for modeling financial markets

Science.gov (United States)

Yang, G.; Chen, Y.; Huang, J. P.

2016-02-01

Researchers have borrowed many theories from statistical physics, like ensemble, Ising model, etc., to study complex adaptive systems through agent-based modeling. However, one fundamental difference between entities (such as spins) in physics and micro-units in complex adaptive systems is that the latter are usually with high intelligence, such as investors in financial markets. Although highly intelligent virtual agents are essential for agent-based modeling to play a full role in the study of complex adaptive systems, how to create such agents is still an open question. Hence, we propose three principles for designing high artificial intelligence in financial markets and then build a specific class of agents called iAgents based on these three principles. Finally, we evaluate the intelligence of iAgents through virtual index trading in two different stock markets. For comparison, we also include three other types of agents in this contest, namely, random traders, agents from the wealth game (modified on the famous minority game), and agents from an upgraded wealth game. As a result, iAgents perform the best, which gives a well support for the three principles. This work offers a general framework for the further development of agent-based modeling for various kinds of complex adaptive systems.

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

International Nuclear Information System (INIS)

Reifman, J.

1997-01-01

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

Qualitative Knowledge Representations for Intelligent Nuclear Power Plants

International Nuclear Information System (INIS)

Cha, Kyoungho; Huh, Young H.

1993-01-01

Qualitative Physics(QP) has systematically been approached to qualitative modeling of physical systems for recent two decades. Designing intelligent systems for NPP requires an efficient representation of qualitative knowledge about the behavior and structure of NPP or its components. A novel representation of qualitative knowledge also enables intelligent systems to derive meaningful conclusions from incomplete or uncertain knowledge of a plant behavior. We look mainly into representative QP works on nuclear applications and the representation of qualitative knowledge for the diagnostic model, the qualitative simulation of a mental model of NPP operator, and the qualitative interpretation of the measured raw data from NPP. We present the challenging areas for QP applications in nuclear industry. QP technology will make NPP more intelligent

Intelligent Augmented Reality Training for Motherboard Assembly

Science.gov (United States)

Westerfield, Giles; Mitrovic, Antonija; Billinghurst, Mark

2015-01-01

We investigate the combination of Augmented Reality (AR) with Intelligent Tutoring Systems (ITS) to assist with training for manual assembly tasks. Our approach combines AR graphics with adaptive guidance from the ITS to provide a more effective learning experience. We have developed a modular software framework for intelligent AR training…

An Adaptive Impedance Matching Network with Closed Loop Control Algorithm for Inductive Wireless Power Transfer.

Science.gov (United States)

Miao, Zhidong; Liu, Dake; Gong, Chen

2017-08-01

For an inductive wireless power transfer (IWPT) system, maintaining a reasonable power transfer efficiency and a stable output power are two most challenging design issues, especially when coil distance varies. To solve these issues, this paper presents a novel adaptive impedance matching network (IMN) for IWPT system. In our adaptive IMN IWPT system, the IMN is automatically reconfigured to keep matching with the coils and to adjust the output power adapting to coil distance variation. A closed loop control algorithm is used to change the capacitors continually, which can compensate mismatches and adjust output power simultaneously. The proposed adaptive IMN IWPT system is working at 125 kHz for 2 W power delivered to load. Comparing with the series resonant IWPT system and fixed IMN IWPT system, the power transfer efficiency of our system increases up to 31.79% and 60% when the coupling coefficient varies in a large range from 0.05 to 0.8 for 2 W output power.

An Adaptive Impedance Matching Network with Closed Loop Control Algorithm for Inductive Wireless Power Transfer

Science.gov (United States)

Miao, Zhidong; Liu, Dake

2017-01-01

For an inductive wireless power transfer (IWPT) system, maintaining a reasonable power transfer efficiency and a stable output power are two most challenging design issues, especially when coil distance varies. To solve these issues, this paper presents a novel adaptive impedance matching network (IMN) for IWPT system. In our adaptive IMN IWPT system, the IMN is automatically reconfigured to keep matching with the coils and to adjust the output power adapting to coil distance variation. A closed loop control algorithm is used to change the capacitors continually, which can compensate mismatches and adjust output power simultaneously. The proposed adaptive IMN IWPT system is working at 125 kHz for 2 W power delivered to load. Comparing with the series resonant IWPT system and fixed IMN IWPT system, the power transfer efficiency of our system increases up to 31.79% and 60% when the coupling coefficient varies in a large range from 0.05 to 0.8 for 2 W output power. PMID:28763011

Installation and evaluation of a nuclear power plant operator advisor based on artificial intelligence technology

International Nuclear Information System (INIS)

Hajek, B.K.; Miller, D.W.

1989-01-01

This report discusses the following topics on a Nuclear Power Plant operator advisor based on artificial Intelligence Technology; Workstation conversion; Software Conversion; V ampersand V Program Development Development; Simulator Interface Development; Knowledge Base Expansion; Dynamic Testing; Database Conversion; Installation at the Perry Simulator; Evaluation of Operator Interaction; Design of Man-Machine Interface; and Design of Maintenance Facility

Artificial intelligence in conceptual design of intelligent manufacturing systems: A state of the art review

OpenAIRE

Petrović, Milica M.; Miljković, Zoran Đ.; Babić, Bojan R.

2013-01-01

Intelligent manufacturing systems (IMS), as the highest class of flexible manufacturing systems, are able to adapt to market changes applying methods of artificial intelligence. This paper presents a detailed review of the following IMS functions: (i) process planning optimization, (ii) scheduling optimization, (iii) integrated process planning and scheduling, and (iv) mobile robot scheduling for internal material transport tasks. The research presented in this paper shows that improved perfo...

The subject to emotional intelligence training of changes of emotional intelligence research, and adolescence of Japan seen from overseas literature

OpenAIRE

中島, 正世; Nakajima, Masayo

2015-01-01

In this paper, the author have revealed the transition about the concept of emotional intelligence from overseas literature, and have tried to clarify the subject to the definition of emotional intelligence, the difference from similar concepts, the measuring method of emotional intelligence, the related element of emotional intelligence, and emotional intelligence training for the man-power development to current adolescence. As a result, the base element which constitutes emotional intellig...

Model-free adaptive control of advanced power plants

Science.gov (United States)

Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang

2015-08-18

A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

Plants : Adaptive behavior, root-brains, and minimal cognition

NARCIS (Netherlands)

Calvo Garzon, Paco; Keijzer, Fred

Plant intelligence has gone largely unnoticed within the field of animal and human adaptive behavior. In this context, we will introduce current work on plant intelligence as a new set of relevant phenomena that deserves attention and also discuss its potential relevance for the study of adaptive

Low-power, enhanced-gain adaptive-biasing-based Operational Transconductance Amplifiers

DEFF Research Database (Denmark)

Moradi, Farshad

A symmetrical PMOS OTA (Operational Transconductance Amplifier) is used to build an advanced rail-to-rail amplifier with improved DC-gain and reduced power consumption. By using the adaptive biasing circuit for two differential inputs, a low stand-by current can be achieved, reducing power...

SOCIO-PSYCHOLOGICAL ADAPTATION TO PROFESSIONAL ACTIVITY

Directory of Open Access Journals (Sweden)

V. Ivanov

2016-01-01

Full Text Available The article analyzes the factors of successful adaptation of employees to professional work in the new environment. Under the new conditions of professional development and employee having professional experience and young professional may encounter, with the presentation not only new professional requirements and tasks, but also new working conditions, the system of building relationships in the team, discovering with some discrepancies between obtained them in the learning process theoretical knowledge and skills available to the real practice of professional activities. At the level of interpersonal relations of the process of social cognition, is account of the special knowledge of the process of social facilities and construction of social reality, such an important parameter defi nes as "emotional intelligence" – construct is proposed for study in 1990 by American psychologists Peter Salovey and John Mayer. Initially, the concept of "emotional intelligence" was linked to the notion of social intelligence. The effectiveness of social and psychological adaptation to the professional activity can be enhanced through the development of emotional intelligence. Implementation of the basic functions of emotional intelligence improves communication efficiency, optimization of interpersonal relationships, social and psychological adaptation of personality.

Intelligent Balanced Device and its Sensing System for Beam Pumping Units

Directory of Open Access Journals (Sweden)

Hangxin WEI

2014-11-01

Full Text Available In order to save the energy of the beam pumping unit, the intelligent balanced device was developed. The device can adjust the position of the balanced-block automatically by the single chip microcomputer controller, and the fuzzy PD control algorithm was used to control the servo motor of the device. Since some signals should be inputted into the intelligent balanced device to calculate the balanced index of the pumping unit, the signals sensing system were designed. The sensing system includes the electric current sensor and voltage sensor of the main motor, the displacement sensor and the force sensor of the horse head. The sensing network has three layers: slave station, relay station and master station. The data transmission between them is based on ZigBee and GPRS method which can adapt the environment of the oil field. The results of application show that the intelligent balanced device and its sensing system can have the effect of reducing the power consumption, working reliability and communication efficiently.

Advanced intelligent computational technologies and decision support systems

CERN Document Server

Kountchev, Roumen

2014-01-01

This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.

Service-oriented architecture of adaptive, intelligent data acquisition and processing systems for long-pulse fusion experiments

International Nuclear Information System (INIS)

Gonzalez, J.; Ruiz, M.; Barrera, E.; Lopez, J.M.; Arcas, G. de; Vega, J.

2010-01-01

The data acquisition systems used in long-pulse fusion experiments need to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations, it is essential to employ software tools that allow for hot swap capabilities throughout the temporal evolution of the experiments. This is very important because processing needs are not equal during different phases of the experiment. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of a technology for implementing scalable data acquisition and processing systems based on PXI and CompactPCI hardware. In the ITMS platform, a set of software tools allows the user to define the processing algorithms associated with the different experimental phases using state machines driven by software events. These state machines are specified using the State Chart XML (SCXML) language. The software tools are developed using JAVA, JINI, an SCXML engine and several LabVIEW applications. Within this schema, it is possible to execute data acquisition and processing applications in an adaptive way. The power of SCXML semantics and the ability to work with XML user-defined data types allow for very easy programming of the ITMS platform. With this approach, the ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems based on a service-oriented model with the ability to easily implement remote participation applications.

Service-oriented architecture of adaptive, intelligent data acquisition and processing systems for long-pulse fusion experiments

Energy Technology Data Exchange (ETDEWEB)

Gonzalez, J. [Grupo de Investigacion en Instrumentacion y Acustica Aplicada. Universidad Politecnica de Madrid, Crta. Valencia Km-7 Madrid 28031 (Spain); Ruiz, M., E-mail: mariano.ruiz@upm.e [Grupo de Investigacion en Instrumentacion y Acustica Aplicada. Universidad Politecnica de Madrid, Crta. Valencia Km-7 Madrid 28031 (Spain); Barrera, E.; Lopez, J.M.; Arcas, G. de [Grupo de Investigacion en Instrumentacion y Acustica Aplicada. Universidad Politecnica de Madrid, Crta. Valencia Km-7 Madrid 28031 (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Madrid (Spain)

2010-07-15

The data acquisition systems used in long-pulse fusion experiments need to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations, it is essential to employ software tools that allow for hot swap capabilities throughout the temporal evolution of the experiments. This is very important because processing needs are not equal during different phases of the experiment. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of a technology for implementing scalable data acquisition and processing systems based on PXI and CompactPCI hardware. In the ITMS platform, a set of software tools allows the user to define the processing algorithms associated with the different experimental phases using state machines driven by software events. These state machines are specified using the State Chart XML (SCXML) language. The software tools are developed using JAVA, JINI, an SCXML engine and several LabVIEW applications. Within this schema, it is possible to execute data acquisition and processing applications in an adaptive way. The power of SCXML semantics and the ability to work with XML user-defined data types allow for very easy programming of the ITMS platform. With this approach, the ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems based on a service-oriented model with the ability to easily implement remote participation applications.

An Effective Wormhole Attack Defence Method for a Smart Meter Mesh Network in an Intelligent Power Grid

Directory of Open Access Journals (Sweden)

Jungtaek Seo

2012-08-01

Full Text Available Smart meters are one of the key components of intelligent power grids. Wireless mesh networks based on smart meters could provide customer-oriented information on electricity use to the operational control systems, which monitor power grid status and estimate electric power demand. Using this information, an operational control system could regulate devices within the smart grid in order to provide electricity in a cost-efficient manner. Ensuring the availability of the smart meter mesh network is therefore a critical factor in securing the soundness of an intelligent power system. Wormhole attacks can be one of the most difficult-to-address threats to the availability of mesh networks, and although many methods to nullify wormhole attacks have been tried, these have been limited by high computational resource requirements and unnecessary overhead, as well as by the lack of ability of such methods to respond to attacks. In this paper, an effective defense mechanism that both detects and responds to wormhole attacks is proposed. In the proposed system, each device maintains information on its neighbors, allowing each node to identify replayed packets. The effectiveness and efficiency of the proposed method is analyzed in light of additional computational message and memory complexities.

Military Intelligence : Telling Telling Truth to Power to Bewilderment

NARCIS (Netherlands)

Baudet, Floribert; Braat, E.C.; van Woensel, Jeoffrey; Wever, Aad

2017-01-01

This introductory chapter discusses 100 years of military intelligence and outlines the main changes that distinguish the post-Cold war period from the preceding one. This is characterised by a blurring of the boundaries between civilian and military intelligence, between investigative services and

Lifetime Maximizing Adaptive Power Control in Wireless Sensor Networks

National Research Council Canada - National Science Library

Sun, Fangting; Shayman, Mark

2006-01-01

...: adaptive power control. They focus on the sensor networks that consist of a sink and a set of homogeneous wireless sensor nodes, which are randomly deployed according to a uniform distribution...

Intelligence for embedded systems a methodological approach

CERN Document Server

Alippi, Cesare

2014-01-01

Addressing current issues of which any engineer or computer scientist should be aware, this monograph is a response to the need to adopt a new computational paradigm as the methodological basis for designing pervasive embedded systems with sensor capabilities. The requirements of this paradigm are to control complexity, to limit cost and energy consumption, and to provide adaptation and cognition abilities allowing the embedded system to interact proactively with the real world. The quest for such intelligence requires the formalization of a new generation of intelligent systems able to exploit advances in digital architectures and in sensing technologies. The book sheds light on the theory behind intelligence for embedded systems with specific focus on: ·        robustness (the robustness of a computational flow and its evaluation); ·        intelligence (how to mimic the adaptation and cognition abilities of the human brain), ·        the capacity to learn in non-stationary and evolv...

Research on intelligent monitor for 3D power distribution of reactor core

International Nuclear Information System (INIS)

Xia, Hong; Li, Bin; Liu, Jianxin

2014-01-01

Highlights: • Core power distribution of ex-core measurement system has been reconstructed. • Building up an artificial intelligence model for 3-D core power distribution. • Error of the experiments has been reduced to 0.76%. • Methods for improving the accuracy of the model have been obtained. - Abstract: A real-time monitor for 3D reactor power distribution is critical for nuclear safety and high efficiency of NPP’s operation as well as for optimizing the control system, especially when the nuclear power plant (NPP) works at a certain power level or it works in load following operation. This paper was based on analyzing the monitor for 3D reactor power distribution technologies used in modern NPPs. Furthermore, considering the latest research outcomes, the paper proposed a method based on using an ex-core neutron detector system and a neural network to set up a real time monitor system for reactor’s 3D power distribution supervision. The results of the experiments performed on a reactor simulation machine illustrated that the new monitor system worked very well for a certain burn-up range during the fuel cycle. In addition, this new model could reduce the errors associated with the fitting of the distribution effectively, and several optimization methods were also obtained to improve the accuracy of the simulation model

Traffic Route Modelling and Assignment with Intelligent Transport System

Directory of Open Access Journals (Sweden)

Kunicina Nadezhda

2014-12-01

Full Text Available The development of signal transmitting environment for multimodal traffic control will enhance the integration of emergency and specialized transport routing tools in usual traffic control paradigms - it is one of the opportunities offered by modern intelligent traffic control systems. The improvement of effective electric power use in public transport system is an advantage of Intelligent Transport System (ITS. The research is connected with the improvement of on-line traffic control and adaptation of special traffic lighting alternatives by ITS. The assignment of the nearest appropriate transport will be done by passenger request, but unlike information system, the transport planning is done on demand. The task can be solved with the help of modern technical methods and equipment, as well as by applying control paradigms of the distributed systems. The problem is solved with the help of calculations hyper-graph and scheduling theory. The goal of the research is to develop methods, which support scheduling of the emergency transport, using high performance computing.

Intelligent Control of UPFC for Enhancing Transient Stability on Multi-Machine Power Systems

Directory of Open Access Journals (Sweden)

Hassan Barati

2010-01-01

Full Text Available One of the benefit of FACTS devices is increase of stability in power systems with control active and reactive power at during the fault in power system. Although, the power system stabilizers (PSSs have been one of the most common controls used to damp out oscillations, this device may not produce enough damping especially to inter-area mode and therefore, there is an increasing interest in using FACTS devices to aid in damping of these oscillations. In This paper, UPFC is used for damping oscillations and to enhance the transient stability performance of power systems. The controller parameters are designed using an efficient version of the Takagi-Sugeno fuzzy control scheme. The function based Takagi-Sugeno-Kang (TSK fuzzy controller uses. For optimization parameters of fuzzy PI controller, the GA, PSO and HGAPSO algorithms are used. The computer simulation results, the effect of UPFC with conventional PI controller, fuzzy PI controller and intelligent controllers (GA, PSO and HGAPSO for damping the local-mode and inter-area mode of under large and small disturbances in the four-machine two-area power system evaluated and compared.

Resonant power converter comprising adaptive dead-time control

DEFF Research Database (Denmark)

2017-01-01

The invention relates in a first aspect to a resonant power converter comprising: a first power supply rail for receipt of a positive DC supply voltage and a second power supply rail for receipt of a negative DC supply voltage. The resonant power converter comprises a resonant network with an input...... terminal for receipt of a resonant input voltage from a driver circuit. The driver circuit is configured for alternatingly pulling the resonant input voltage towards the positive and negative DC supply voltages via first and second semiconductor switches, respectively, separated by intervening dead......-time periods in accordance with one or more driver control signals. A dead-time controller is configured to adaptively adjusting the dead-time periods based on the resonant input voltage....

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Science.gov (United States)

Bosworth, John T.; Williams-Hayes, Peggy S.

2010-01-01

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Adaptive Transcutaneous Power Transfer to Implantable Devices: A State of the Art Review.

Science.gov (United States)

Bocan, Kara N; Sejdić, Ervin

2016-03-18

Wireless energy transfer is a broad research area that has recently become applicable to implantable medical devices. Wireless powering of and communication with implanted devices is possible through wireless transcutaneous energy transfer. However, designing wireless transcutaneous systems is complicated due to the variability of the environment. The focus of this review is on strategies to sense and adapt to environmental variations in wireless transcutaneous systems. Adaptive systems provide the ability to maintain performance in the face of both unpredictability (variation from expected parameters) and variability (changes over time). Current strategies in adaptive (or tunable) systems include sensing relevant metrics to evaluate the function of the system in its environment and adjusting control parameters according to sensed values through the use of tunable components. Some challenges of applying adaptive designs to implantable devices are challenges common to all implantable devices, including size and power reduction on the implant, efficiency of power transfer and safety related to energy absorption in tissue. Challenges specifically associated with adaptation include choosing relevant and accessible parameters to sense and adjust, minimizing the tuning time and complexity of control, utilizing feedback from the implanted device and coordinating adaptation at the transmitter and receiver.

Adaptive Transcutaneous Power Transfer to Implantable Devices: A State of the Art Review

Directory of Open Access Journals (Sweden)

Kara N. Bocan

2016-03-01

Full Text Available Wireless energy transfer is a broad research area that has recently become applicable to implantable medical devices. Wireless powering of and communication with implanted devices is possible through wireless transcutaneous energy transfer. However, designing wireless transcutaneous systems is complicated due to the variability of the environment. The focus of this review is on strategies to sense and adapt to environmental variations in wireless transcutaneous systems. Adaptive systems provide the ability to maintain performance in the face of both unpredictability (variation from expected parameters and variability (changes over time. Current strategies in adaptive (or tunable systems include sensing relevant metrics to evaluate the function of the system in its environment and adjusting control parameters according to sensed values through the use of tunable components. Some challenges of applying adaptive designs to implantable devices are challenges common to all implantable devices, including size and power reduction on the implant, efficiency of power transfer and safety related to energy absorption in tissue. Challenges specifically associated with adaptation include choosing relevant and accessible parameters to sense and adjust, minimizing the tuning time and complexity of control, utilizing feedback from the implanted device and coordinating adaptation at the transmitter and receiver.

SAP Business Intelligence: Migración de COGNOS a SAP

OpenAIRE

Legorburu Cladera, Iñigo

2013-01-01

El objetivo del proyecto consiste en la migración de la herramienta de Business Intelligence de COGNOS a una nueva solución de Business Intelligence, que reduzca los costes y se adapte a las necesidades de la empresa. Este objetivo incluye la migración de todos los informes y cubos al nuevo Business Intelligence.

The Properties of Intelligent Human-Machine Interface

Directory of Open Access Journals (Sweden)

Alexander Alfimtsev

2012-04-01

Full Text Available Intelligent human-machine interfaces based on multimodal interaction are developed separately in different application areas. No unified opinion exists about the issue of what properties should these interfaces have to provide an intuitive and natural interaction. Having carried out an analytical survey of the papers that deal with intelligent interfaces a set of properties are presented, which are necessary for intelligent interface between an information system and a human: absolute response, justification, training, personification, adaptiveness, collectivity, security, hidden persistence, portability, filtering.

Leadership Institute: Building Leadership Capacity through Emotional Intelligence

Science.gov (United States)

Argabright, Karen J.; King, Jeff; Cochran, Graham R.; Chen, Claire Yueh-Ti

2013-01-01

Given the changing dynamics of society and the pressures on Extension organizations to adapt, leadership effectiveness has become a crucial element of success. The program presented here is designed to enhance individual emotional intelligence. Through in-depth engagement of the participants, they learn to apply dynamics of emotional intelligence,…

Mathematical Intelligence and Mathematical Creativity: A Causal Relationship

Science.gov (United States)

Tyagi, Tarun Kumar

2017-01-01

This study investigated the causal relationship between mathematical creativity and mathematical intelligence. Four hundred thirty-nine 8th-grade students, age ranged from 11 to 14 years, were included in the sample of this study by random cluster technique on which mathematical creativity and Hindi adaptation of mathematical intelligence test…

Neuro-Fuzzy Wavelet Based Adaptive MPPT Algorithm for Photovoltaic Systems

Directory of Open Access Journals (Sweden)

Syed Zulqadar Hassan

2017-03-01

Full Text Available An intelligent control of photovoltaics is necessary to ensure fast response and high efficiency under different weather conditions. This is often arduous to accomplish using traditional linear controllers, as photovoltaic systems are nonlinear and contain several uncertainties. Based on the analysis of the existing literature of Maximum Power Point Tracking (MPPT techniques, a high performance neuro-fuzzy indirect wavelet-based adaptive MPPT control is developed in this work. The proposed controller combines the reasoning capability of fuzzy logic, the learning capability of neural networks and the localization properties of wavelets. In the proposed system, the Hermite Wavelet-embedded Neural Fuzzy (HWNF-based gradient estimator is adopted to estimate the gradient term and makes the controller indirect. The performance of the proposed controller is compared with different conventional and intelligent MPPT control techniques. MATLAB results show the superiority over other existing techniques in terms of fast response, power quality and efficiency.

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...

Flexible Microgrid Power Quality Enhancement Using Adaptive Hybrid Voltage and Current Controller

DEFF Research Database (Denmark)

He, Jinwei; Li, Yun Wei; Blaabjerg, Frede

2014-01-01

-pass/bandpass filters in the DG unit digital controller. Moreover, phase-locked loops are not necessary as the microgrid frequency deviation can be automatically identified by the power control loop. Consequently, the proposed control method provides opportunities to reduce DG control complexity, without affecting......To accomplish superior harmonic compensation performance using distributed generation (DG) unit power electronics interfaces, an adaptive hybrid voltage and current controlled method (HCM) is proposed in this paper. It shows that the proposed adaptive HCM can reduce the numbers of low...... the harmonic compensation performance. Comprehensive simulated and experimental results from a single-phase microgrid are provided to verify the feasibility of the proposed adaptive HCM approach....

Flight Results of the NF-15B Intelligent Flight Control System (IFCS) Aircraft with Adaptation to a Longitudinally Destabilized Plant

Science.gov (United States)

Bosworth, John T.

2008-01-01

Adaptive flight control systems have the potential to be resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. The goal for the adaptive system is to provide an increase in survivability in the event that these extreme changes occur. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane. The adaptive element was incorporated into a dynamic inversion controller with explicit reference model-following. As a test the system was subjected to an abrupt change in plant stability simulating a destabilizing failure. Flight evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to stabilize the vehicle and reestablish good onboard reference model-following. Flight evaluation with the simulated destabilizing failure and adaptation engaged showed improvement in the vehicle stability margins. The convergent properties of this initial system warrant additional improvement since continued maneuvering caused continued adaptation change. Compared to the non-adaptive system the adaptive system provided better closed-loop behavior with improved matching of the onboard reference model. A detailed discussion of the flight results is presented.

ISHM-oriented adaptive fault diagnostics for avionics based on a distributed intelligent agent system

Science.gov (United States)

Xu, Jiuping; Zhong, Zhengqiang; Xu, Lei

2015-10-01

In this paper, an integrated system health management-oriented adaptive fault diagnostics and model for avionics is proposed. With avionics becoming increasingly complicated, precise and comprehensive avionics fault diagnostics has become an extremely complicated task. For the proposed fault diagnostic system, specific approaches, such as the artificial immune system, the intelligent agents system and the Dempster-Shafer evidence theory, are used to conduct deep fault avionics diagnostics. Through this proposed fault diagnostic system, efficient and accurate diagnostics can be achieved. A numerical example is conducted to apply the proposed hybrid diagnostics to a set of radar transmitters on an avionics system and to illustrate that the proposed system and model have the ability to achieve efficient and accurate fault diagnostics. By analyzing the diagnostic system's feasibility and pragmatics, the advantages of this system are demonstrated.

Army Intelligence Analysis: Transforming Army Intelligence Analysis Training and Doctrine to Serve the Reasonable Expectations and Needs of Echelons Corps and Below Commanders, Consumers, and Customers

National Research Council Canada - National Science Library

Lewis, George E., III

2005-01-01

... of intelligence professionals. Now, when faced with modern adaptive and complex asymmetric threats, the need for human analysis has risen to the forefront, but Army Intelligence is ill-equipped to deliver what commanders need...

Intelligent Monitoring System with High Temperature Distributed Fiberoptic Sensor for Power Plant Combustion Processes

Energy Technology Data Exchange (ETDEWEB)

Kwang Y. Lee; Stuart S. Yin; Andre Boehman

2006-09-26

The objective of the proposed work is to develop an intelligent distributed fiber optical sensor system for real-time monitoring of high temperature in a boiler furnace in power plants. Of particular interest is the estimation of spatial and temporal distributions of high temperatures within a boiler furnace, which will be essential in assessing and controlling the mechanisms that form and remove pollutants at the source, such as NOx. The basic approach in developing the proposed sensor system is three fold: (1) development of high temperature distributed fiber optical sensor capable of measuring temperatures greater than 2000 C degree with spatial resolution of less than 1 cm; (2) development of distributed parameter system (DPS) models to map the three-dimensional (3D) temperature distribution for the furnace; and (3) development of an intelligent monitoring system for real-time monitoring of the 3D boiler temperature distribution. Under Task 1, we have set up a dedicated high power, ultrafast laser system for fabricating in-fiber gratings in harsh environment optical fibers, successfully fabricated gratings in single crystal sapphire fibers by the high power laser system, and developed highly sensitive long period gratings (lpg) by electric arc. Under Task 2, relevant mathematical modeling studies of NOx formation in practical combustors have been completed. Studies show that in boiler systems with no swirl, the distributed temperature sensor may provide information sufficient to predict trends of NOx at the boiler exit. Under Task 3, we have investigated a mathematical approach to extrapolation of the temperature distribution within a power plant boiler facility, using a combination of a modified neural network architecture and semigroup theory. Given a set of empirical data with no analytic expression, we first developed an analytic description and then extended that model along a single axis.

colonial military intelligence in the zulu rebellion, 1906

African Journals Online (AJOL)

user

The colonial forces were well adapted to the local circumstances, but in one important respect they drew heavily on imperial experience, namely military field intelligence. .... There was a militia library, and for a while, militia orders listed new ..... intelligence called the questioning of women “a very difficult matter” in which a.

Road Nail: Experimental Solar Powered Intelligent Road Marking System

Science.gov (United States)

Samardžija, Dragan; Teslić, Nikola; Todorović, Branislav M.; Kovač, Erne; Isailović, Đorđe; Miladinović, Bojan

2012-03-01

Driving in low visibility conditions (night time, fog or heavy precipitation) is particularly challenging task with an increased probability of traffic accidents and possible injuries. Road Nail is a solar powered intelligent road marking system of wirelessly networked signaling devices that improve driver safety in low visibility conditions along hazardous roadways. Nails or signaling devices are autonomous nodes with capability to accumulate energy, exchange wireless messages, detect approaching vehicles and emit signalization light. We have built an experimental test-bed that consists of 20 nodes and a cellular gateway. Implementation details of the above system, including extensive measurements and performance evaluations in realistic field deployments are presented. A novel distributed network topology discovery scheme is proposed which integrates both sensor and wireless communication aspects, where nodes act autonomously. Finally, integration of the Road Nail system with the cellular network and the Internet is described.

Monitoring and operational support on nuclear power plants using an artificial intelligence system

International Nuclear Information System (INIS)

Bianchi, P.H.; Baptista Filho, B.D.

2009-01-01

The monitoring task in nuclear power plants is of crucial importance with respect to safety and efficient operation. The operators have a wide range of variables to observe and analyze; the quantity of variables and their behavior determine the time they have to take correct decisions. The complexity of such aspects in a nuclear power plant influences both, the plant operational efficiency and the general safety issues. This paper describes an experimental system developed by the authors which aims to assist the operators of nuclear power plants to take quick and safe decisions. The system maps the status of plant and helps the operators to make quick judgments by using artificial intelligence methods. The method makes use of a small set of monitored variables and presents a map of the plant status in a friendly manner. This system uses an architecture that has multiple self-organizing maps to perform these tasks. (author)

Monitoring and operational support on nuclear power plants using an artificial intelligence system

Energy Technology Data Exchange (ETDEWEB)

Bianchi, Paulo H.; Baptista Filho, Benedito D., E-mail: phbianchi@gmail.co, E-mail: bdbfilho@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2009-07-01

The monitoring task in nuclear power plants is of crucial importance with respect to safety and efficient operation. The operators have a wide range of variables to observe and analyze; the quantity of variables and their behavior determine the time they have to take correct decisions. The complexity of such aspects in a nuclear power plant influences both, the plant operational efficiency and the general safety issues. This paper describes an experimental system developed by the authors which aims to assist the operators of nuclear power plants to take quick and safe decisions. The system maps the status of plant and helps the operators to make quick judgments by using artificial intelligence methods. The method makes use of a small set of monitored variables and presents a map of the plant status in a friendly manner. This system uses an architecture that has multiple self-organizing maps to perform these tasks. (author)

Stupid Tutoring Systems, Intelligent Humans

Science.gov (United States)

Baker, Ryan S.

2016-01-01

The initial vision for intelligent tutoring systems involved powerful, multi-faceted systems that would leverage rich models of students and pedagogies to create complex learning interactions. But the intelligent tutoring systems used at scale today are much simpler. In this article, I present hypotheses on the factors underlying this development,…

Emotions and trait emotional intelligence among ultra-endurance runners.

Science.gov (United States)

Lane, Andrew M; Wilson, Mathew

2011-07-01

The aim of this study was to investigate relationships between trait emotional intelligence and emotional state changes over the course of an ultra-endurance foot race covering a route of approximately 175 miles (282 km) and held in set stages over six days. A repeated measures field design that sought to maintain ecological validity was used. Trait emotional intelligence was defined as a relatively stable concept that should predict adaptive emotional states experienced over the duration of the race and therefore associate with pleasant emotions during a 6-stage endurance event. Thirty-four runners completed a self-report measure of trait emotional intelligence before the event started. Participants reported emotional states before and after each of the six races. Repeated measures ANOVA results showed significant variations in emotions over time and a main effect for trait emotional intelligence. Runners high in self-report trait emotional intelligence also reported higher pleasant and lower unpleasant emotions than runners low in trait emotional intelligence. Findings lend support to the notion that trait emotional intelligence associates with adaptive psychological states, suggesting that it may be a key individual difference that explains why some athletes respond to repeated bouts of hard exercise better than others. Future research should test the effectiveness of interventions designed to enhance trait emotional intelligence and examine the attendant impact on emotional responses to intense exercise during multi-stage events. Copyright © 2011. Published by Elsevier Ltd.

Services oriented architecture for adaptive and intelligent data acquisition and processing systems in long pulse fusion experiments

Energy Technology Data Exchange (ETDEWEB)

Gonzalez, J.; Ruiz, M.; Barrera, E.; Lopez, J.M.; De Arcas, G. [Universidad Politecnica de Madrid (Spain); Vega, J. [Association EuratomCIEMAT para Fusion, Madrid (Spain)

2009-07-01

Data acquisition systems used in long pulse fusion experiments require to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations is essential to dispose software tools that allow hot swap capabilities throughout the temporal evolution of the experiments. This is very important because the processing needs are not equal in the different experiment's phases. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of technology for implementing scalable data acquisition and processing systems based in PXI and compact PCI hardware. In the ITMS platform a set of software tools allows the user to define the processing associated with the different experiment's phases using state machines driven by software events. These state machines are specified using State Chart XML (SCXML) language. The software tools are developed using: JAVA, JINI, a SCXML engine and several LabVIEW applications. With this schema it is possible to execute data acquisition and processing applications in an adaptive way. The powerful of SCXML semantics and the possibility of to work with XML user defined data types allow a very easy programming of ITMS platform. With this approach ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems, based in a services oriented model, with ease possibility for implement remote participation applications. (authors)

Development of an intelligent controller for power generators

International Nuclear Information System (INIS)

Maxted, Clive; Waller, Winston

2005-01-01

This paper is a description of the development of an embedded controller for high power industrial diesel generators. The aim of the project was to replace the existing discrete logic design by an intelligent versatile and user configurable control system. A prototype embedded PC controlled system was developed, capable of fully replacing the existing system, with a colour TFT display and keypad. Features include fully automatic generator control as before with status and alarm display and monitoring of engine parameters, along with data logging, remote communications and a means of analysing data. The unit was tested on the bench and on diesel generators for the core controlling functionality to prove compliance with the specifications. The results of the testing proved the unit's suitability as a replacement for the existing system in its intended environment. The significance of this study is that a low cost replacement solution has been found for an industrial application by transferring modern technological knowledge to a small business. The company are now able to build on the design and take it into production, reducing servicing and production costs

Optimization of Transformation Coefficients Using Direct Search and Swarm Intelligence

Directory of Open Access Journals (Sweden)

Manusov V.Z.

2017-04-01

Full Text Available This research considers optimization of tap position of transformers in power systems to reduce power losses. Now, methods based on heuristic rules and fuzzy logic, or methods that optimize parts of the whole system separately, are applied to this problem. The first approach requires expert knowledge about processes in the network. The second methods are not able to consider all the interrelations of system’s parts, while changes in segment affect the entire system. Both approaches are tough to implement and require adjustment to the tasks solved. It needs to implement algorithms that can take into account complex interrelations of optimized variables and self-adapt to optimization task. It is advisable to use algorithms given complex interrelations of optimized variables and independently adapting from optimization tasks. Such algorithms include Swarm Intelligence algorithms. Their main features are self-organization, which allows them to automatically adapt to conditions of tasks, and the ability to efficiently exit from local extremes. Thus, they do not require specialized knowledge of the system, in contrast to fuzzy logic. In addition, they can efficiently find quasi-optimal solutions converging to the global optimum. This research applies Particle Swarm Optimization algorithm (PSO. The model of Tajik power system used in experiments. It was found out that PSO is much more efficient than greedy heuristics and more flexible and easier to use than fuzzy logic. PSO allows reducing active power losses from 48.01 to 45.83 MW (4.5%. With al, the effect of using greedy heuristics or fuzzy logic is two times smaller (2.3%.

Social Representations of Intelligence

Directory of Open Access Journals (Sweden)

Elena Zubieta

2016-02-01

Full Text Available The article stresses the relationship between Explicit and Implicit theories of Intelligence. Following the line of common sense epistemology and the theory of Social Representations, a study was carried out in order to analyze naive’s explanations about Intelligence Definitions. Based on Mugny & Carugati (1989 research, a self-administered questionnaire was designed and filled in by 286 subjects. Results are congruent with the main hyphotesis postulated: A general overlap between explicit and implicit theories showed up. According to the results Intelligence appears as both, a social attribute related to social adaptation and as a concept defined in relation with contextual variables similar to expert’s current discourses. Nevertheless, conceptions based on “gifted ideology” still are present stressing the main axes of Intelligence debate: biological and sociological determinism. In the same sense, unfamiliarity and social identity are reaffirmed as organizing principles of social representation. The distance with the object -measured as the belief in intelligence differences as a solve/non solve problem- and the level of implication with the topic -teachers/no teachers- appear as discriminating elements at the moment of supporting specific dimensions. 

Optimized Adaptive Perturb and Observe Maximum Power Point Tracking Control for Photovoltaic Generation

Directory of Open Access Journals (Sweden)

Luigi Piegari

2015-04-01

Full Text Available The power extracted from PV arrays is usually maximized using maximum power point tracking algorithms. One of the most widely used techniques is the perturb & observe algorithm, which periodically perturbs the operating point of the PV array, sometime with an adaptive perturbation step, and compares the PV power before and after the perturbation. This paper analyses the most suitable perturbation step to optimize maximum power point tracking performance and suggests a design criterion to select the parameters of the controller. Using this proposed adaptive step, the MPPT perturb & observe algorithm achieves an excellent dynamic response by adapting the perturbation step to the actual operating conditions of the PV array. The proposed algorithm has been validated and tested in a laboratory using a dual input inductor push-pull converter. This particular converter topology is an efficient interface to boost the low voltage of PV arrays and effectively control the power flow when input or output voltages are variable. The experimental results have proved the superiority of the proposed algorithm in comparison of traditional perturb & observe and incremental conductance techniques.

Transmit Antenna Selection for Power Adaptive Underlay Cognitive Radio with Instantaneous Interference Constraint

KAUST Repository

Hanif, Muhammad

2017-03-31

The high hardware cost associated with multiple antennas at the secondary transmitter of an underlay cognitive radio (CR) can be reduced by antenna selection. This paper analyzes different power adaptive transmit antenna selection (TAS) schemes for an underlay CR, which ensure that the instantaneous interference caused by the secondary transmitter to the primary receiver is below a predetermined level. We consider the optimal continuous power adaptive TAS and present a low-complexity antenna and power level selection scheme, named sequential antenna and power level selection scheme (SAPS), for discrete power adaptation. Exact statistical characterizations of the signal-to-interference plus noise ratio at the secondary receiver are derived for the considered schemes. Based on the newly derived statistics, we prove that the considered schemes achieve the highest diversity order equaling the number of antennas at the secondary transmitter. Further, we also derive a closed-form expression of the ergodic capacity for the underlay CR with SAPS scheme. Finally, we show that the proposed scheme outperforms existing schemes in terms of ergodic capacity.

Sense-making for intelligence analysis on social media data

Science.gov (United States)

Pritzkau, Albert

2016-05-01

Social networks, in particular online social networks as a subset, enable the analysis of social relationships which are represented by interaction, collaboration, or other sorts of influence between people. Any set of people and their internal social relationships can be modelled as a general social graph. These relationships are formed by exchanging emails, making phone calls, or carrying out a range of other activities that build up the network. This paper presents an overview of current approaches to utilizing social media as a ubiquitous sensor network in the context of national and global security. Exploitation of social media is usually an interdisciplinary endeavour, in which the relevant technologies and methods are identified and linked in order ultimately demonstrate selected applications. Effective and efficient intelligence is usually accomplished in a combined human and computer effort. Indeed, the intelligence process heavily depends on combining a human's flexibility, creativity, and cognitive ability with the bandwidth and processing power of today's computers. To improve the usability and accuracy of the intelligence analysis we will have to rely on data-processing tools at the level of natural language. Especially the collection and transformation of unstructured data into actionable, structured data requires scalable computational algorithms ranging from Artificial Intelligence, via Machine Learning, to Natural Language Processing (NLP). To support intelligence analysis on social media data, social media analytics is concerned with developing and evaluating computational tools and frameworks to collect, monitor, analyze, summarize, and visualize social media data. Analytics methods are employed to extract of significant patterns that might not be obvious. As a result, different data representations rendering distinct aspects of content and interactions serve as a means to adapt the focus of the intelligence analysis to specific information

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)

The Application of Intelligent Building Technologies to Space Hotels

Science.gov (United States)

Fawkes, S.

This paper reports that over the last few years Intelligent Building technologies have matured and standardised. It compares the functions of command and control systems in future large space facilities such as space hotels to those commonly found in Intelligent Buildings and looks at how Intelligent Building technologies may be applied to space hotels. Many of the functions required in space hotels are the same as those needed in terrestrial buildings. The adaptation of standardised, low cost, Intelligent Building technologies would reduce capital costs and ease development of future space hotels. Other aspects of Intelligent Buildings may also provide useful models for the development and operation of space hotels.

A novel optimized hybrid fuzzy logic intelligent PID controller for an interconnected multi-area power system with physical constraints and boiler dynamics.

Science.gov (United States)

Gomaa Haroun, A H; Li, Yin-Ya

2017-11-01

In the fast developing world nowadays, load frequency control (LFC) is considered to be a most significant role for providing the power supply with good quality in the power system. To deliver a reliable power, LFC system requires highly competent and intelligent control technique. Hence, in this article, a novel hybrid fuzzy logic intelligent proportional-integral-derivative (FLiPID) controller has been proposed for LFC of interconnected multi-area power systems. A four-area interconnected thermal power system incorporated with physical constraints and boiler dynamics is considered and the adjustable parameters of the FLiPID controller are optimized using particle swarm optimization (PSO) scheme employing an integral square error (ISE) criterion. The proposed method has been established to enhance the power system performances as well as to reduce the oscillations of uncertainties due to variations in the system parameters and load perturbations. The supremacy of the suggested method is demonstrated by comparing the simulation results with some recently reported heuristic methods such as fuzzy logic proportional-integral (FLPI) and intelligent proportional-integral-derivative (PID) controllers for the same electrical power system. the investigations showed that the FLiPID controller provides a better dynamic performance and outperform compared to the other approaches in terms of the settling time, and minimum undershoots of the frequency as well as tie-line power flow deviations following a perturbation, in addition to perform appropriate settlement of integral absolute error (IAE). Finally, the sensitivity analysis of the plant is inspected by varying the system parameters and operating load conditions from their nominal values. It is observed that the suggested controller based optimization algorithm is robust and perform satisfactorily with the variations in operating load condition, system parameters and load pattern. Copyright © 2017 ISA. Published by

Artificial Intelligence in Astronomy

Science.gov (United States)

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

2010-12-01

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

Behavioral Adaptation and Acceptance

NARCIS (Netherlands)

Martens, M.H.; Jenssen, G.D.

2012-01-01

One purpose of Intelligent Vehicles is to improve road safety, throughput, and emissions. However, the predicted effects are not always as large as aimed for. Part of this is due to indirect behavioral changes of drivers, also called behavioral adaptation. Behavioral adaptation (BA) refers to

Proposition of a scheme for adaptive/intelligent analog-to-digital converters

International Nuclear Information System (INIS)

Vaidya, P.P.; Kataria, S.K.

2001-01-01

The paper proposes design of a new class of Analog to Digital Converters (ADC's) which we call as Intelligent ADC's with moving resolution. Unlike presently available ADC's which are designed for specific range of applications and give fixed resolution and conversion time, the intelligent ADC's described here can adjust their resolution during the process of conversion, depending upon nature of input signal to make optimum use of the hard-ware. It is possible to use an intelligent ADC to give resolution ranging from 8 bit to 16 bit and conversion time ranging from few nano sec. to few micro secs. These ADC's have significant advantages over conventional ones when used for nuclear pulse spectroscopy as well as for process control applications. (author)

The Role of Intelligence in Social Learning.

Science.gov (United States)

Vostroknutov, Alexander; Polonio, Luca; Coricelli, Giorgio

2018-05-02

Studies in cultural evolution have uncovered many types of social learning strategies that are adaptive in certain environments. The efficiency of these strategies also depends on the individual characteristics of both the observer and the demonstrator. We investigate the relationship between intelligence and the ways social and individual information is utilised to make decisions in an uncertain environment. We measure fluid intelligence and study experimentally how individuals learn from observing the choices of a demonstrator in a 2-armed bandit problem with changing probabilities of a reward. Participants observe a demonstrator with high or low fluid intelligence. In some treatments they are aware of the intelligence score of the demonstrator and in others they are not. Low fluid intelligence individuals imitate the demonstrator more when her fluid intelligence is known than when it is not. Conversely, individuals with high fluid intelligence adjust their use of social information, as the observed behaviour changes, independently of the knowledge of the intelligence of the demonstrator. We provide evidence that intelligence determines how social and individual information is integrated in order to make choices in a changing uncertain environment.

Adaptive control paradigm for photovoltaic and solid oxide fuel cell in a grid-integrated hybrid renewable energy system.

Science.gov (United States)

Mumtaz, Sidra; Khan, Laiq

2017-01-01

The hybrid power system (HPS) is an emerging power generation scheme due to the plentiful availability of renewable energy sources. Renewable energy sources are characterized as highly intermittent in nature due to meteorological conditions, while the domestic load also behaves in a quite uncertain manner. In this scenario, to maintain the balance between generation and load, the development of an intelligent and adaptive control algorithm has preoccupied power engineers and researchers. This paper proposes a Hermite wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control of photovoltaic (PV) systems to extract maximum power and a Hermite wavelet incorporated NeuroFuzzy indirect adaptive control of Solid Oxide Fuel Cells (SOFC) to obtain a swift response in a grid-connected hybrid power system. A comprehensive simulation testbed for a grid-connected hybrid power system (wind turbine, PV cells, SOFC, electrolyzer, battery storage system, supercapacitor (SC), micro-turbine (MT) and domestic load) is developed in Matlab/Simulink. The robustness and superiority of the proposed indirect adaptive control paradigm are evaluated through simulation results in a grid-connected hybrid power system testbed by comparison with a conventional PI (proportional and integral) control system. The simulation results verify the effectiveness of the proposed control paradigm.

Adaptive control paradigm for photovoltaic and solid oxide fuel cell in a grid-integrated hybrid renewable energy system

Science.gov (United States)

Khan, Laiq

2017-01-01

The hybrid power system (HPS) is an emerging power generation scheme due to the plentiful availability of renewable energy sources. Renewable energy sources are characterized as highly intermittent in nature due to meteorological conditions, while the domestic load also behaves in a quite uncertain manner. In this scenario, to maintain the balance between generation and load, the development of an intelligent and adaptive control algorithm has preoccupied power engineers and researchers. This paper proposes a Hermite wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control of photovoltaic (PV) systems to extract maximum power and a Hermite wavelet incorporated NeuroFuzzy indirect adaptive control of Solid Oxide Fuel Cells (SOFC) to obtain a swift response in a grid-connected hybrid power system. A comprehensive simulation testbed for a grid-connected hybrid power system (wind turbine, PV cells, SOFC, electrolyzer, battery storage system, supercapacitor (SC), micro-turbine (MT) and domestic load) is developed in Matlab/Simulink. The robustness and superiority of the proposed indirect adaptive control paradigm are evaluated through simulation results in a grid-connected hybrid power system testbed by comparison with a conventional PI (proportional and integral) control system. The simulation results verify the effectiveness of the proposed control paradigm. PMID:28329015

An adaptive signal-processing approach to online adaptive tutoring.

Science.gov (United States)

Bergeron, Bryan; Cline, Andrew

2011-01-01

Conventional intelligent or adaptive tutoring online systems rely on domain-specific models of learner behavior based on rules, deep domain knowledge, and other resource-intensive methods. We have developed and studied a domain-independent methodology of adaptive tutoring based on domain-independent signal-processing approaches that obviate the need for the construction of explicit expert and student models. A key advantage of our method over conventional approaches is a lower barrier to entry for educators who want to develop adaptive online learning materials.

The role of short-time intensity and envelope power for speech intelligibility and psychoacoustic masking.

Science.gov (United States)

Biberger, Thomas; Ewert, Stephan D

2017-08-01

The generalized power spectrum model [GPSM; Biberger and Ewert (2016). J. Acoust. Soc. Am. 140, 1023-1038], combining the "classical" concept of the power-spectrum model (PSM) and the envelope power spectrum-model (EPSM), was demonstrated to account for several psychoacoustic and speech intelligibility (SI) experiments. The PSM path of the model uses long-time power signal-to-noise ratios (SNRs), while the EPSM path uses short-time envelope power SNRs. A systematic comparison of existing SI models for several spectro-temporal manipulations of speech maskers and gender combinations of target and masker speakers [Schubotz et al. (2016). J. Acoust. Soc. Am. 140, 524-540] showed the importance of short-time power features. Conversely, Jørgensen et al. [(2013). J. Acoust. Soc. Am. 134, 436-446] demonstrated a higher predictive power of short-time envelope power SNRs than power SNRs using reverberation and spectral subtraction. Here the GPSM was extended to utilize short-time power SNRs and was shown to account for all psychoacoustic and SI data of the three mentioned studies. The best processing strategy was to exclusively use either power or envelope-power SNRs, depending on the experimental task. By analyzing both domains, the suggested model might provide a useful tool for clarifying the contribution of amplitude modulation masking and energetic masking.

Adaptive control of energy storage systems for power smoothing applications

DEFF Research Database (Denmark)

Meng, Lexuan; Dragicevic, Tomislav; Guerrero, Josep M.

2017-01-01

Energy storage systems (ESSs) are desired and widely applied for power smoothing especially in systems with renewable generation and pulsed loads. High-pass-filter (HPF) is commonly applied in those applications in which the HPF extracts the high frequency fluctuating power and uses...... that as the power reference for ESS. The cut-off frequency, as the critical parameter, actually decides the power/energy compensated by ESS. Practically the state-of-charge (SoC) of the ESS has to be limited for safety and life-cycle considerations. In this paper an adaptive cut-off frequency design is proposed...

Computational Intelligence in Image Processing

CERN Document Server

Siarry, Patrick

2013-01-01

Computational intelligence based techniques have firmly established themselves as viable, alternate, mathematical tools for more than a decade. They have been extensively employed in many systems and application domains, among these signal processing, automatic control, industrial and consumer electronics, robotics, finance, manufacturing systems, electric power systems, and power electronics. Image processing is also an extremely potent area which has attracted the atten­tion of many researchers who are interested in the development of new computational intelligence-based techniques and their suitable applications, in both research prob­lems and in real-world problems. Part I of the book discusses several image preprocessing algorithms; Part II broadly covers image compression algorithms; Part III demonstrates how computational intelligence-based techniques can be effectively utilized for image analysis purposes; and Part IV shows how pattern recognition, classification and clustering-based techniques can ...

Cross-layer combining of power control and adaptive modulation with truncated ARQ for cognitive radios

Institute of Scientific and Technical Information of China (English)

CHENG Shi-lun; YANG Zhen

2008-01-01

To maximize throughput and to satisfy users' requirements in cognitive radios, a cross-layer optimization problem combining adaptive modulation and power control at the physical layer and truncated automatic repeat request at the medium access control layer is proposed. Simulation results show the combination of power control, adaptive modulation, and truncated automatic repeat request can regulate transmitter powers and increase the total throughput effectively.

High impact data visualization with Power View, Power Map, and Power BI

CERN Document Server

Aspin, Adam

2014-01-01

High Impact Data Visualization with Power View, Power Map, and Power BI helps you take business intelligence delivery to a new level that is interactive, engaging, even fun, all while driving commercial success through sound decision-making. Learn to harness the power of Microsoft's flagship, self-service business intelligence suite to deliver compelling and interactive insight with remarkable ease. Learn the essential techniques needed to enhance the look and feel of reports and dashboards so that you can seize your audience's attention and provide them with clear and accurate information. Al

Climate and water resource change impacts and adaptation potential for US power supply

Science.gov (United States)

Miara, Ariel; Macknick, Jordan E.; Vörösmarty, Charles J.; Tidwell, Vincent C.; Newmark, Robin; Fekete, Balazs

2017-11-01

Power plants that require cooling currently (2015) provide 85% of electricity generation in the United States. These facilities need large volumes of water and sufficiently cool temperatures for optimal operations, and projected climate conditions may lower their potential power output and affect reliability. We evaluate the performance of 1,080 thermoelectric plants across the contiguous US under future climates (2035-2064) and their collective performance at 19 North American Electric Reliability Corporation (NERC) sub-regions. Joint consideration of engineering interactions with climate, hydrology and environmental regulations reveals the region-specific performance of energy systems and the need for regional energy security and climate-water adaptation strategies. Despite climate-water constraints on individual plants, the current power supply infrastructure shows potential for adaptation to future climates by capitalizing on the size of regional power systems, grid configuration and improvements in thermal efficiencies. Without placing climate-water impacts on individual plants in a broader power systems context, vulnerability assessments that aim to support adaptation and resilience strategies misgauge the extent to which regional energy systems are vulnerable. Climate-water impacts can lower thermoelectric reserve margins, a measure of systems-level reliability, highlighting the need to integrate climate-water constraints on thermoelectric power supply into energy planning, risk assessments, and system reliability management.

Certification Considerations for Adaptive Systems

Science.gov (United States)

Bhattacharyya, Siddhartha; Cofer, Darren; Musliner, David J.; Mueller, Joseph; Engstrom, Eric

2015-01-01

Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach.

Adaptive neuro-fuzzy inference system to improve the power quality of a split shaft microturbine power generation system

Science.gov (United States)

Oğuz, Yüksel; Üstün, Seydi Vakkas; Yabanova, İsmail; Yumurtaci, Mehmet; Güney, İrfan

2012-01-01

This article presents design of adaptive neuro-fuzzy inference system (ANFIS) for the turbine speed control for purpose of improving the power quality of the power production system of a split shaft microturbine. To improve the operation performance of the microturbine power generation system (MTPGS) and to obtain the electrical output magnitudes in desired quality and value (terminal voltage, operation frequency, power drawn by consumer and production power), a controller depended on adaptive neuro-fuzzy inference system was designed. The MTPGS consists of the microturbine speed controller, a split shaft microturbine, cylindrical pole synchronous generator, excitation circuit and voltage regulator. Modeling of dynamic behavior of synchronous generator driver with a turbine and split shaft turbine was realized by using the Matlab/Simulink and SimPowerSystems in it. It is observed from the simulation results that with the microturbine speed control made with ANFIS, when the MTPGS is operated under various loading situations, the terminal voltage and frequency values of the system can be settled in desired operation values in a very short time without significant oscillation and electrical production power in desired quality can be obtained.

The intelligent system for accident identification in nuclear power plant

International Nuclear Information System (INIS)

Hernandez, Jorge Luis.

1998-01-01

Accidental situations in NPP are of greet concern for operators, the facility, regulatory bodies and the environment. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making when initiator events with higher relative contribution to the reactor core damage occur. The intelligent System uses the results of the pre operational Probabilistic Safety Assessment and the Thermal hydraulic Safety Analyses of the NPP Juragua as source for building its knowledge base. The nucleus of the system is presented as a design of an intelligent hybrid system from the combination of the artificial intelligence techniques: fussy logic and artificial neural networks. The system works with variables from the process of the firsts circuit, second circuit and the containment and it is presented as a model for the integration of safety analyses in the process of decision making by the operator when tackling with accidental situations

Recent Advances in Intelligent Engineering Systems

CERN Document Server

Klempous, Ryszard; Araujo, Carmen

2012-01-01

This volume is a collection of 19 chapters on intelligent engineering systems written by respectable experts of the fields. The book consists of three parts. The first part is devoted to the foundational aspects of computational intelligence. It consists of 8 chapters that include studies in genetic algorithms, fuzzy logic connectives, enhanced intelligence in product models, nature-inspired optimization technologies, particle swarm optimization, evolution algorithms, model complexity of neural networks, and fitness landscape analysis. The second part contains contributions to intelligent computation in networks, presented in 5 chapters. The covered subjects include the application of self-organizing maps for early detection of denial of service attacks, combating security threats via immunity and adaptability in cognitive radio networks, novel modifications in WSN network design for improved SNR and reliability, a conceptual framework for the design of audio based cognitive infocommunication channels, and a ...

Computational Intelligence Agent-Oriented Modelling

Czech Academy of Sciences Publication Activity Database

Neruda, Roman

2006-01-01

Roč. 5, č. 2 (2006), s. 430-433 ISSN 1109-2777 R&D Projects: GA MŠk 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : multi-agent systems * adaptive agents * computational intelligence Subject RIV: IN - Informatics, Computer Science

Engineering Adaptive Web Applications

DEFF Research Database (Denmark)

Dolog, Peter

2007-01-01

suit the user profile the most. This paper summarizes the domain engineering framework for such adaptive web applications. The framework provides guidelines to develop adaptive web applications as members of a family. It suggests how to utilize the design artifacts as knowledge which can be used......Information and services on the web are accessible for everyone. Users of the web differ in their background, culture, political and social environment, interests and so on. Ambient intelligence was envisioned as a concept for systems which are able to adapt to user actions and needs....... With the growing amount of information and services, the web applications become natural candidates to adopt the concepts of ambient intelligence. Such applications can deal with divers user intentions and actions based on the user profile and can suggest the combination of information content and services which...

Requirement analysis for autonomous systems and intelligent ...

African Journals Online (AJOL)

user

Danish Power System and a requirement analysis for the use of intelligent agents and ..... tries to make an optimal islanding plan at this state and tries to blackstart. ... 4 Foundation for Physical Intelligent Agents (FIPA): http://www.fipa.org ...

Recent Advances on Hybrid Intelligent Systems

CERN Document Server

Melin, Patricia; Kacprzyk, Janusz

2013-01-01

This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algo...

Flexible Adaptation in Cognitive Radios

CERN Document Server

Li, Shujun

2013-01-01

This book provides an introduction to software-defined radio and cognitive radio, along with methodologies for applying knowledge representation, semantic web, logic reasoning and artificial intelligence to cognitive radio, enabling autonomous adaptation and flexible signaling. Readers from the wireless communications and software-defined radio communities will use this book as a reference to extend software-defined radio to cognitive radio, using the semantic technology described. Readers with a background in semantic web and artificial intelligence will find in this book the application of semantic web and artificial intelligence technologies to wireless communications. For readers in networks and network management, this book presents a new approach to enable interoperability, collaborative optimization and flexible adaptation of network components. Provides a comprehensive ontology covering the core concepts of wireless communications using a formal language; Presents the technical realization of using a ...

Cultural Intelligence (CQ) in MBA Curricula

Science.gov (United States)

Ahn, Mark J.; Ettner, Larry

2013-01-01

Purpose: The purpose of this paper is to investigate the role of cultural intelligence in MBA curricula. Shaping global corporate culture that manifests itself in powerful-shared values, group behavior, and persists despite changes in-group membership is decisive to organizational performance. In turn, cultural intelligence (CQ), defined, as an…

Proceedings of the sixth international symposium on methodologies for intelligent systems (Poster Session)

Energy Technology Data Exchange (ETDEWEB)

Harber, K.S. (ed.)

1991-09-01

This volume contains papers which have been selected for the poster Session at the Sixth International Symposium for Intelligent Systems held October 1991, The following major areas were covered: expert systems; intelligent databases; knowledge representation; learning and adaptive systems; and logic for artificial intelligence. Nineteen full papers are included. (GHH)

TO THE PROBLEM OF CORRELATION OF SOCIAL AND OTHER KINDS OF INTELLIGENCE

OpenAIRE

E. V. Grib

2017-01-01

The article considers the problem of the relationship of three types of intelligence: social, emotional and logical. Interest in social intelligence (SI) is determined by the need of society to reveal the "social capacity" of a person and develop them. Social intelligence is seen as a necessary condition for successful mastering of professional skills and adapt in a professional environment. Development of social intelligence becomes an important part of the educational process. Social intell...

Sex differences in fluid and crystalized intelligence focus on people with psychosis

OpenAIRE

Ćosović Vojislav; Todorović Nevena; Andrić-Petrović Sanja; Marić Nadja P.

2016-01-01

Introduction: Fluid intelligence is described as ability to rapidly solve novel problems and capacity to manage and easily adapt to new situations. Crystallized intelligence reflects ability to timely use lifetime-learned information and skills. Bearing in mind that intelligence is one of the impaired cognitive functions in psychosis, a question arises there are if any sex differences in patients, regarding total IQ, fluid or crystallized intelligence. Aim: To evaluate sex differences in psyc...

Cognitive radio adaptation for power consumption minimization using biogeography-based optimization

International Nuclear Information System (INIS)

Qi Pei-Han; Zheng Shi-Lian; Yang Xiao-Niu; Zhao Zhi-Jin

2016-01-01

Adaptation is one of the key capabilities of cognitive radio, which focuses on how to adjust the radio parameters to optimize the system performance based on the knowledge of the radio environment and its capability and characteristics. In this paper, we consider the cognitive radio adaptation problem for power consumption minimization. The problem is formulated as a constrained power consumption minimization problem, and the biogeography-based optimization (BBO) is introduced to solve this optimization problem. A novel habitat suitability index (HSI) evaluation mechanism is proposed, in which both the power consumption minimization objective and the quality of services (QoS) constraints are taken into account. The results show that under different QoS requirement settings corresponding to different types of services, the algorithm can minimize power consumption while still maintaining the QoS requirements. Comparison with particle swarm optimization (PSO) and cat swarm optimization (CSO) reveals that BBO works better, especially at the early stage of the search, which means that the BBO is a better choice for real-time applications. (paper)

Modeling of biological intelligence for SCM system optimization.

Science.gov (United States)

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

2012-01-01

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

Modeling of Biological Intelligence for SCM System Optimization

Directory of Open Access Journals (Sweden)

Shengyong Chen

2012-01-01

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

Modeling of Biological Intelligence for SCM System Optimization

Science.gov (United States)

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

2012-01-01

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

The adaption study of emotional intelligence inventory in sport

Directory of Open Access Journals (Sweden)

İlhan Adiloğulları

2015-12-01

Full Text Available Aim: The purpose of this study was to test the validity and reliability of the Turkish version of Emotional Intelligence Inventory in Sport (EIIS. Material and Methods: The emotional intelligence inventory in sport which have consists of nineteen items and five subscales, 157 female (age=20,10±1,95 and 247 male (age=21,25±2,18 in total 404 (age=20,80±2,17 participants completed. Respondents of the EIIS indicate the extent to which they agree with each statement on a five-point Likert scale, ranging from 1 (strongly disagree to 5 (strongly agree. Factor structures of the scale were tested by confirmatory factor analysis in AMOS programme. Results: The resulting factor is appropriate for the 19-item inventory value but is below the desired value of the item-total correlation values b4 and paragraphs are seen as loaded with low load factors. However, there was only one item with low factor loadings that was excluded from the inventory. It was obtained acceptable fit index values of inventory that confirming factor structures of Turkish version. Internal consistency coefficients of EIIS were found ranging from 0,69 (Appraisal of others emotions, 0,85 (Appraisal of own emotions, 0,67 (Emotional regulation 0,85 (Use of emotions and 0,61 (Social skills. Conclusion: Turkish version of the Emotional intelligence inventory in Sport is can be used for Turkish athletes.

An adaptive predictive controller and its applications in power stations

Energy Technology Data Exchange (ETDEWEB)

Yang Zhiyuan; Lu Huiming; Zhang Xinggao [North China Electric Power University, Beijing (China); Song Chunping [Tsinghua University, Beijing (China). Dept. of Thermal Energy Engineering

1999-07-01

Based on the objective function in the form of integration of generalized model error, a globally convergent model reference adaptive predictive control algorithm (MRAPC) containing inertia-time compensators is presented in this paper. MRAPC has been successfully applied to control important thermal process of more than 20 units in many Chinese power stations. In this paper three representative examples are described. Continual operation results for years demonstrate that MRAPC is a successful attempt for the practical applications of adaptive control techniques. (author)

Development of intelligent database program for PSI/ISI data management of nuclear power plant

International Nuclear Information System (INIS)

Um, Byong Guk; Park, Un Su; Park, Ik Keun; Park, Yun Won; Kang, Suk Chul

1998-01-01

An intelligent database program has been developed under fully compatible with windows 95 for the construction of total support system and the effective management of Pre-/In-Service Inspection data. Using the database program, it can be executed the analysis and multi-dimensional evaluation of the defects detected during PSI/ISI in the pipe and the pressure vessel of the nuclear power plants. And also it can be used to investigate the NDE data inspected repetitively and the contents of treatment, and to offer the fundamental data for application of evaluation data related to Fracture Mechanics Analysis(FMA). Furthermore, the PSI/ISI database loads and material properties can be utilized to secure the higher degree of safety, integrity, reliability, and life-prediction of components and systems in nuclear power plant.

Robots that can adapt like animals.

Science.gov (United States)

Cully, Antoine; Clune, Jeff; Tarapore, Danesh; Mouret, Jean-Baptiste

2015-05-28

Robots have transformed many industries, most notably manufacturing, and have the power to deliver tremendous benefits to society, such as in search and rescue, disaster response, health care and transportation. They are also invaluable tools for scientific exploration in environments inaccessible to humans, from distant planets to deep oceans. A major obstacle to their widespread adoption in more complex environments outside factories is their fragility. Whereas animals can quickly adapt to injuries, current robots cannot 'think outside the box' to find a compensatory behaviour when they are damaged: they are limited to their pre-specified self-sensing abilities, can diagnose only anticipated failure modes, and require a pre-programmed contingency plan for every type of potential damage, an impracticality for complex robots. A promising approach to reducing robot fragility involves having robots learn appropriate behaviours in response to damage, but current techniques are slow even with small, constrained search spaces. Here we introduce an intelligent trial-and-error algorithm that allows robots to adapt to damage in less than two minutes in large search spaces without requiring self-diagnosis or pre-specified contingency plans. Before the robot is deployed, it uses a novel technique to create a detailed map of the space of high-performing behaviours. This map represents the robot's prior knowledge about what behaviours it can perform and their value. When the robot is damaged, it uses this prior knowledge to guide a trial-and-error learning algorithm that conducts intelligent experiments to rapidly discover a behaviour that compensates for the damage. Experiments reveal successful adaptations for a legged robot injured in five different ways, including damaged, broken, and missing legs, and for a robotic arm with joints broken in 14 different ways. This new algorithm will enable more robust, effective, autonomous robots, and may shed light on the principles

Nuclear power and climate change: The cost of adaptation

International Nuclear Information System (INIS)

Pailiere, H.

2012-01-01

For more than a decade, the international community has been voicing concern over growing greenhouse gas (GHG) emissions, which are believed to be the largest contributor to global warming and more generally to climate change. According to the Intergovernmental Panel on Climate Change (IPCC), an increase in the frequency of heat waves and droughts is expected in many parts of the world, as is that of storms, flooding and cold episodes. The potential consequences of this projected climate change have prompted calls to reduce the use of fossil fuels and to promote low-carbon energy sources such as renewables and nuclear power. At the same time, there has also been growing concern that without a rapid decrease in GHG emissions, climate change could occur at such a scale that it will have a significant impact on major economic sectors including the power generation sector. Although the expanded use of renewables will reduce emissions from the power sector, it will also increase the dependence of distribution systems and electricity production on climatic conditions. Thermal power plants, such as fossil fuel and nuclear, will be affected primarily by the diminishing availability of water and the increasing likelihood of heat waves, which will have an impact on the cooling capabilities and power output of plants. In its 2012 edition of the World Energy Outlook, the IEA underlined the need to address an additional challenge, the water-energy nexus: water needs for energy production are set to grow at twice the rate of energy demands over the next decades. It has thus become clear that the availability of water for cooling will be an important criterion for assessing the viability of energy projects. Given the long operating life of nuclear reactors (60 years for Generation III designs), the possible impact of climate change on the operation and safety of nuclear power plants needs to be addressed at the design and siting stages in order to limit costly adaptation measures

PEAC: A Power-Efficient Adaptive Computing Technology for Enabling Swarm of Small Spacecraft and Deployable Mini-Payloads

Data.gov (United States)

National Aeronautics and Space Administration — This task is to develop and demonstrate a path-to-flight and power-adaptive avionics technology PEAC (Power Efficient Adaptive Computing). PEAC will enable emerging...

Circuit-Adaptive Challenge Balancing in Racing Games

NARCIS (Netherlands)

Rietveld, A.; Bakkes, S.; Roijers, D.

2014-01-01

In this paper, we propose a novel approach to challenge balancing in racing games: circuit-adaptive challenge balancing. We propose to automatically adapt the actual racing circuit - while it is being played - such that the performed circuit adaptations intelligently balance the challenge for all

Star Power: Providing for the Gifted & Talented. Module 3. Applications of Theories of Intelligence to the Gifted/Talented.

Science.gov (United States)

Heinemann, Alison; Mallis, Jackie

The document presents Module 3, applications of theories of intelligence to the gifted/talented, of the Star Power modules developed for school personnel who have an interest in or a need to explore the area of gifted and talented education. It is explained in an introductory section that the modules can be used for independent study, for small…

Motor modules during adaptation to walking in a powered ankle exoskeleton.

Science.gov (United States)

Jacobs, Daniel A; Koller, Jeffrey R; Steele, Katherine M; Ferris, Daniel P

2018-01-03

Modules of muscle recruitment can be extracted from electromyography (EMG) during motions, such as walking, running, and swimming, to identify key features of muscle coordination. These features may provide insight into gait adaptation as a result of powered assistance. The aim of this study was to investigate the changes (module size, module timing and weighting patterns) of surface EMG data during assisted and unassisted walking in an powered, myoelectric, ankle-foot orthosis (ankle exoskeleton). Eight healthy subjects wore bilateral ankle exoskeletons and walked at 1.2 m/s on a treadmill. In three training sessions, subjects walked for 40 min in two conditions: unpowered (10 min) and powered (30 min). During each session, we extracted modules of muscle recruitment via nonnegative matrix factorization (NNMF) from the surface EMG signals of ten muscles in the lower limb. We evaluated reconstruction quality for each muscle individually using R 2 and normalized root mean squared error (NRMSE). We hypothesized that the number of modules needed to reconstruct muscle data would be the same between conditions and that there would be greater similarity in module timings than weightings. Across subjects, we found that six modules were sufficient to reconstruct the muscle data for both conditions, suggesting that the number of modules was preserved. The similarity of module timings and weightings between conditions was greater then random chance, indicating that muscle coordination was also preserved. Motor adaptation during walking in the exoskeleton was dominated by changes in the module timings rather than module weightings. The segment number and the session number were significant fixed effects in a linear mixed-effect model for the increase in R 2 with time. Our results show that subjects walking in a exoskeleton preserved the number of modules and the coordination of muscles within the modules across conditions. Training (motor adaptation within the session and

Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989

Science.gov (United States)

Rodriguez, Guillermo (Editor)

1990-01-01

Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.

Speed regulating Effects of Incentive-based Intelligent Speed Adaptation in the short and medium term

DEFF Research Database (Denmark)

Agerholm, Niels

Speed regulating Effects of Incentive-based Intelligent Speed Adaptation in the short and medium term Despite massive improvements in vehicles’ safety equipment, more information and safer road network, inappropriate road safety is still causing that more than 250 people are killed and several...... thousands injured each year in Denmark. Until a few years ago the number of fatalities in most countries had decreased while the amount of traffic increased. However, this trend has been replaced by a more uncertain development towards a constant or even somewhat increasing risk. Inappropriate speeding...... is a central cause for the high number of fatalities on the roads. Despite speed limits, speed limit violating driving behaviour is still widespread in Denmark. Traditional solutions to prevent speed violation have been enforcement, information, and enhanced road design. It seems, however, hard to achieve...

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...

Power through Things: Following Traces of Collective Intelligence in Internet of Things

Directory of Open Access Journals (Sweden)

Monika Mačiulienė

2014-10-01

Full Text Available Purpose – it is becoming increasingly difficult to ignore the input Internet of Things (IoT has to offer in development of public, business and other societal structures. Therefore, paper seeks to determine the current state of knowledge in the field of IoT terms of wisdom creation and emergence of collective intelligence. First, we discuss concept of collective intelligence, then we define phenomena of IoT and identify areas of its application. Later, the author reviews how intelligent outputs of IoT are defined in scientific literature. These findings of theoretical investigation may shed some light on research field that is promising but still very vague.Design/methodology/approach – this article provides a general overview of IoT concept and its growing relation to collective intelligence. Methods of document analysis and content analysis were applied. Theoretical analysis enabled recognition of IoT phenomena in relation to wisdom creation and emergence of collective intelligence.Findings – general overview of the field revealed that new understanding of collective intelligence surfaces. Often intelligent behavior and decisions emerge from ever increasing cooperation between ‘things’ and humans. The variety of new concepts and authors trying to describe relationship of ‘things’ with each other and humans when creating intelligent outcomes revealed that this field is still in its very infancy and still needs considerable amount of industry and scientific efforts to be understood and executed.Research limitations – although the paper has successfully demonstrated that IoT provides vast amounts of data for people to process and create knowledge this could be considered only as initial phase in studying the field. IoT and its intelligent outcomes need more investigations in terms of real life case studies and industry reviews in order to create valid definitions, models and future guidelines. Practical implications – this

Development of Shunt-Type Three-Phase Active Power Filter with Novel Adaptive Control for Wind Generators

Directory of Open Access Journals (Sweden)

Ming-Hung Chen

2015-01-01

Full Text Available This paper proposes a new adaptive filter for wind generators that combines instantaneous reactive power compensation technology and current prediction controller, and therefore this system is characterized by low harmonic distortion, high power factor, and small DC-link voltage variations during load disturbances. The performance of the system was first simulated using MATLAB/Simulink, and the possibility of an adaptive digital low-pass filter eliminating current harmonics was confirmed in steady and transient states. Subsequently, a digital signal processor was used to implement an active power filter. The experimental results indicate, that for the rated operation of 2 kVA, the system has a total harmonic distortion of current less than 5.0% and a power factor of 1.0 on the utility side. Thus, the transient performance of the adaptive filter is superior to the traditional digital low-pass filter and is more economical because of its short computation time compared with other types of adaptive filters.

Development of Shunt-Type Three-Phase Active Power Filter with Novel Adaptive Control for Wind Generators.

Science.gov (United States)

Chen, Ming-Hung

2015-01-01

This paper proposes a new adaptive filter for wind generators that combines instantaneous reactive power compensation technology and current prediction controller, and therefore this system is characterized by low harmonic distortion, high power factor, and small DC-link voltage variations during load disturbances. The performance of the system was first simulated using MATLAB/Simulink, and the possibility of an adaptive digital low-pass filter eliminating current harmonics was confirmed in steady and transient states. Subsequently, a digital signal processor was used to implement an active power filter. The experimental results indicate, that for the rated operation of 2 kVA, the system has a total harmonic distortion of current less than 5.0% and a power factor of 1.0 on the utility side. Thus, the transient performance of the adaptive filter is superior to the traditional digital low-pass filter and is more economical because of its short computation time compared with other types of adaptive filters.

Systems with artificial intelligence in nuclear power plant operation

International Nuclear Information System (INIS)

Bastl, W.; Felkel, L.

1989-01-01

The authors first summarize some developments made by GRS teams which can be regarded as the precursors of systems with artificial intelligence, and explain the basic characteristics of artificial intelligence, referring in particular to possible applications in nuclear engineering. The systems described are arranged in four groups according to applicability as follows: plant diagnosis and failure analysis, information systems and operating systems, control systems, assessment and decision aids. The working principle of the systems is explained by some examples giving details of the database and the interference processes. (orig./DG) [de

Evolving Intelligent Systems Methodology and Applications

CERN Document Server

Angelov, Plamen; Kasabov, Nik

2010-01-01

From theory to techniques, the first all-in-one resource for EIS. There is a clear demand in advanced process industries, defense, and Internet and communication (VoIP) applications for intelligent yet adaptive/evolving systems. Evolving Intelligent Systems is the first self- contained volume that covers this newly established concept in its entirety, from a systematic methodology to case studies to industrial applications. Featuring chapters written by leading world experts, it addresses the progress, trends, and major achievements in this emerging research field, with a strong emphasis on th

Adaptive Distributed Intelligent Control Architecture for Future Propulsion Systems (Preprint)

National Research Council Canada - National Science Library

Behbahani, Alireza R

2007-01-01

.... Distributed control is potentially an enabling technology for advanced intelligent propulsion system concepts and is one of the few control approaches that is able to provide improved component...

Intelligence in children

Directory of Open Access Journals (Sweden)

Martín Nader

2015-09-01

Full Text Available Partial results of an investigation are presented whose primary objective is to adapt and to standardize the neurocognitive assessment battery C.A.S. of Das and Naglieri (1997 in a child sample. The test is an operationalization of a non traditional intelligence model (PASS that considers the intelligent behaviors as a group of four cognitive basic processes (planning, attention, simultaneous and successive processing. The objectives of this work are to obtain the psychometric properties of the instrument and also, to analyze if differences exist according to sex and age. The study type is crosswise - transactional. It was administered the CAS to 150 children residents in Buenos Aires among the ages of 6 to 12 years (population general non consultant and the WISC-III to a sample of 50 children. 

A Low Energy Intelligent Clustering Protocol for Wireless Sensor Network

DEFF Research Database (Denmark)

Li, Qiao; Cui, Lingguo; Zhang, Baihai

2010-01-01

LEACH (low-energy adaptive clustering hierarchy) is a well-known self-organizing, adaptive clustering protocol of wireless sensor networks. However it has some shortcomings when it faces such problems as the cluster construction and energy management. In this paper, LEICP (low energy intelligent...

Intelligent material systems - The dawn of a new materials age

International Nuclear Information System (INIS)

Rogers, C.A.

1993-01-01

The intelligent material system solution to such engineering problems as the design of a robotic arm borrows directly from biological analogs; materials that behave much as muscles do during contraction can be employed as induced strain actuators which work against the intrinsic structural impedance of the component. Unlike actual human arms, which are jointed, the intelligent structure may be a continuum. The adaptation of structural impedance may be regarded as the most fundamental and consequential concept in the field of intelligent material systems

Adaptive double-integral-sliding-mode-maximum-power-point tracker for a photovoltaic system

Directory of Open Access Journals (Sweden)

Bidyadhar Subudhi

2015-10-01

Full Text Available This study proposed an adaptive double-integral-sliding-mode-controller-maximum-power-point tracker (DISMC-MPPT for maximum-power-point (MPP tracking of a photovoltaic (PV system. The objective of this study is to design a DISMC-MPPT with a new adaptive double-integral-sliding surface in order that MPP tracking is achieved with reduced chattering and steady-state error in the output voltage or current. The proposed adaptive DISMC-MPPT possesses a very simple and efficient PWM-based control structure that keeps switching frequency constant. The controller is designed considering the reaching and stability conditions to provide robustness and stability. The performance of the proposed adaptive DISMC-MPPT is verified through both MATLAB/Simulink simulation and experiment using a 0.2 kW prototype PV system. From the obtained results, it is found out that this DISMC-MPPT is found to be more efficient compared with that of Tan's and Jiao's DISMC-MPPTs.

Optimizing managerial effectiveness through emotional intelligence

NARCIS (Netherlands)

Hur, Y.H.

2009-01-01

The idea that emotional competence is crucial for adaptation in various realms of life has fuelled numerous studies and social learning programs. Nonetheless, leadership research on emotional intelligence contexts is still limited and the construct is controversial on several grounds and includes a

Microcomputer Intelligence for Technical Training (MITT): The evolution of an intelligent tutoring system

Science.gov (United States)

Norton, Jeffrey E.; Wiederholt, Bradley J.; Johnson, William B.

1990-01-01

Microcomputer Intelligence for Technical Training (MITT) uses Intelligent Tutoring System (OTS) technology to deliver diagnostic training in a variety of complex technical domains. Over the past six years, MITT technology has been used to develop training systems for nuclear power plant diesel generator diagnosis, Space Shuttle fuel cell diagnosis, and message processing diagnosis for the Minuteman missile. Presented here is an overview of the MITT system, describing the evolution of the MITT software and the benefits of using the MITT system.

Some Principles of Intelligent Tutoring.

Science.gov (United States)

Ohlsson, Stellan

1986-01-01

Research on intelligent tutoring systems is discussed from the point of view of providing moment-by-moment adaptation of content and form of instruction to the changing cognitive needs of individual learners. Implications of this goal for cognitive diagnosis, subject matter analysis, teaching tactics, and teaching strategies are analyzed. (Author)

Towards intelligent automation of power plant design and operations: The role of interactive simulations and distributed expert systems

International Nuclear Information System (INIS)

Otaduy, P.J.

1992-01-01

The design process of a power plant can be viewed as machine- chromosome engineering: When the final layout is implemented, the lifetime operating characteristics, constraints, strengths, and weaknesses of the resulting power-plant-specimen are durably determined. Hence, the safety, operability, maneuverability, availability, maintenance requirements, and costs of a power plant are directly related to the goodness of its electromechanical-genes. This paper addresses the desirability of incorporating distributed computing, distributed object management, and multimedia technologies to power plant engineering, in particular, to design and operations. The promise these technologies have for enhancing the quality and amount of engineering knowledge available, concurrently, online, to plant designers, maintenance crews, and operators is put into perspective. The role that advanced interactive simulations and expert systems will play in the intelligent automation of power plant design and operations is discussed

Study of application of adaptive systems to the exploration of the solar system. Volume 1: Summary

Science.gov (United States)

1973-01-01

The field of artificial intelligence to identify practical applications to unmanned spacecraft used to explore the solar system in the decade of the 80s is examined. If an unmanned spacecraft can be made to adjust or adapt to the environment, to make decisions about what it measures and how it uses and reports the data, it can become a much more powerful tool for the science community in unlocking the secrets of the solar system. Within this definition of an adaptive spacecraft or system, there is a broad range of variability. In terms of sophistication, an adaptive system can be extremely simple or as complex as a chess-playing machine that learns from its mistakes.

Adaptive automatic generation control with superconducting magnetic energy storage in power systems

International Nuclear Information System (INIS)

Tripathy, S.C.; Balasubramanian, R.; Nair, P.S.C.

1992-01-01

An improved automatic generation control (AGC) employing self-tuning adaptive control for both main AGC loop and superconducting magnetic energy storage (SMES) is presented in this paper. Computer simulations on a two-area interconnected power system show that the proposed adaptive control scheme is very effective in damping out oscillations caused by load disturbances and its performance is quite insensitive to controller gain parameter changes of SMES. A comprehensive comparative performance evaluation of control schemes using adaptive and non-adaptive controllers in the main AGC and in the SMES control loops is presented. The improvement in performance brought in by the adaptive scheme is particularly pronounced for load changes of random magnitude and duration. The proposed controller can be easily implemented using microprocessors

Improving Emotional Intelligence through Personality Development: The Effect of the Smart Phone Application based Dharma Life Program on Emotional Intelligence.

Science.gov (United States)

Poonamallee, Latha; Harrington, Alex M; Nagpal, Manisha; Musial, Alec

2018-01-01

Emotional intelligence is established to predict success in leadership effectiveness in various contexts and has been linked to personality factors. This paper introduces Dharma Life Program, a novel approach to improving emotional intelligence by targeting maladaptive personality traits and triggering neuroplasticity through the use of a smart-phone application and mentoring. The program uses neuroplasticity to enable users to create a more adaptive application of their maladaptive traits, thus improving their emotional intelligence. In this study 26 participants underwent the Dharma Life Program in a leadership development setting. We assessed their emotional and social intelligence before and after the Dharma Life Program intervention using the Emotional and Social Competency Inventory (ESCI). The study found a significant improvement in the lowest three competencies and a significant improvement in almost all domains for the entire sample. Our findings suggest that the completion of the Dharma Life Program has a significant positive effect on Emotional and Social Competency scores and offers a new avenue for improving emotional intelligence competencies.

Adaptive semantics visualization

CERN Document Server

Nazemi, Kawa

2016-01-01

This book introduces a novel approach for intelligent visualizations that adapts the different visual variables and data processing to human’s behavior and given tasks. Thereby a number of new algorithms and methods are introduced to satisfy the human need of information and knowledge and enable a usable and attractive way of information acquisition. Each method and algorithm is illustrated in a replicable way to enable the reproduction of the entire “SemaVis” system or parts of it. The introduced evaluation is scientifically well-designed and performed with more than enough participants to validate the benefits of the methods. Beside the introduced new approaches and algorithms, readers may find a sophisticated literature review in Information Visualization and Visual Analytics, Semantics and information extraction, and intelligent and adaptive systems. This book is based on an awarded and distinguished doctoral thesis in computer science.

Genes, evolution and intelligence.

Science.gov (United States)

Bouchard, Thomas J

2014-11-01

I argue that the g factor meets the fundamental criteria of a scientific construct more fully than any other conception of intelligence. I briefly discuss the evidence regarding the relationship of brain size to intelligence. A review of a large body of evidence demonstrates that there is a g factor in a wide range of species and that, in the species studied, it relates to brain size and is heritable. These findings suggest that many species have evolved a general-purpose mechanism (a general biological intelligence) for dealing with the environments in which they evolved. In spite of numerous studies with considerable statistical power, we know of very few genes that influence g and the effects are very small. Nevertheless, g appears to be highly polygenic. Given the complexity of the human brain, it is not surprising that that one of its primary faculties-intelligence-is best explained by the near infinitesimal model of quantitative genetics.

Laser rangefinders for autonomous intelligent cruise control systems

Science.gov (United States)

Journet, Bernard A.; Bazin, Gaelle

1998-01-01

THe purpose of this paper is to show to what kind of application laser range-finders can be used inside Autonomous Intelligent Cruise Control systems. Even if laser systems present good performances the safety and technical considerations are very restrictive. As the system is used in the outside, the emitted average output power must respect the rather low level of 1A class. Obstacle detection or collision avoidance require a 200 meters range. Moreover bad weather conditions, like rain or fog, ar disastrous. We have conducted measurements on laser rangefinder using different targets and at different distances. We can infer that except for cooperative targets low power laser rangefinder are not powerful enough for long distance measurement. Radars, like 77 GHz systems, are better adapted to such cases. But in case of short distances measurement, range around 10 meters, with a minimum distance around twenty centimeters, laser rangefinders are really useful with good resolution and rather low cost. Applications can have the following of white lines on the road, the target being easily cooperative, detection of vehicles in the vicinity, that means car convoy traffic control or parking assistance, the target surface being indifferent at short distances.

Intelligent Instructional Systems in Military Training.

Science.gov (United States)

Fletcher, J.D.; Zdybel, Frank

Intelligent instructional systems can be distinguished from more conventional approaches by the automation of instructional interaction and choice of strategy. This approach promises to reduce the costs of instructional materials preparation and to increase the adaptability and individualization of the instruction delivered. Tutorial simulation…

Troubleshooting of signal power supply system for Shanghai metro line 7

Science.gov (United States)

Lu, Kaixia; Xiao, Jie

2018-03-01

With the rapid development of Urban Rail Transit Signal Technology, the demand of signal power supply system for signal equipment is higher and higher. The signal intelligent power supply panel is the main component of the urban rail traffic signal power supply system. Whether the intelligent power supply panel working or not is directly related to traffic safety. The maintenance of intelligent signal power supply panel is particularly important. Line 7 of Shanghai Metro adopts PMZG Signal Intelligent Power Supply Panel, which is produced by Beijing Jinyujiaxin Polytron Technologies Inc. Maintenance of power supply system mainly includes routine maintenance and troubleshooting. This article will make clear the routine maintenance contents of PMZG Signal Intelligent Power Supply Panel, and put forward the common fault information and troubleshooting methods of PMZG Signal Intelligent Power Supply Panel. In accordance with the steps of fault handling, the faults can be eliminated in the shortest possible time, and PMZG Signal Intelligent Power Supply Panel can be quickly restored to normal working state.

Intelligent control with implementation on the wind energy conversion system

International Nuclear Information System (INIS)

Basma, Mohamad Khalil

1997-05-01

In this thesis our main job is to compare intelligent control and conventional control algorithms, by applying each scheme to the same control problem. Based on simulation, we analyze and compare the results of applying fuzzy logic and neural networks controllers on a popular control problem: variable speed wind energy conversion system. The reason behind our choice is the challenging nature of the problem where the plant should be controlled to maximize the power generated, while respecting its hardware constraints under varying operating conditions and disturbances. We have shown the effectiveness of fuzzy logic exciter controller for the adopted wind energy generator when compared to a conventional PI exciter. It showed better performance in the whole operating range. However, in the high wind speeds region, both controllers were unable to deliver the rpm requirements. We proposed the use of neural network intelligent techniques to supply us the optimal pitch. Our aim was to develop a simple and reliable controller that can deliver this optimal output, while remaining adaptive to system uncertainties and disturbances. The proposed fuzzy controller with a neural pitch controller showed best dynamic and robust performance as compared to the adaptive pitch controller together with the PI exciter. This study has shown that artificial neural networks and fuzzy logic control algorithms can be implemented for real time control implementations. the neuro-fuzzy control approach is robust and its performance is superior to that of traditional control methods. (author)

Robust data reconciliation and outlier detection with swarm intelligence in a thermal reactor power calculation

Energy Technology Data Exchange (ETDEWEB)

Valdetaro, Eduardo Damianik, E-mail: valdtar@eletronuclear.gov.br [ELETRONUCLEAR - ELETROBRAS, Angra dos Reis, RJ (Brazil). Angra 2 Operating Dept.; Coordenacao dos Programas de Pos-Graduacao de Engenharia (PEN/COPPE/UFRJ), RJ (Brazil). Programa de Engenharia Nuclear; Schirru, Roberto, E-mail: schirru@lmp.ufrj.br [Coordenacao dos Programas de Pos-Graduacao de Engenharia (PEN/COPPE/UFRJ), RJ (Brazil). Programa de Engenharia Nuclear

2011-07-01

In Nuclear power plants, Data Reconciliation (DR) and Gross Errors Detection (GED) are techniques of increasing interest and are primarily used to keep mass and energy balance into account, which brings outcomes as a direct and indirect financial benefits. Data reconciliation is formulated by a constrained minimization problem, where the constraints correspond to energy and mass balance model. Statistical methods are used combined with the minimization of quadratic error form. Solving nonlinear optimization problem using conventional methods can be troublesome, because a multimodal function with differentiated solutions introduces some difficulties to search an optimal solution. Many techniques were developed to solve Data Reconciliation and Outlier Detection, some of them use, for example, Quadratic Programming, Lagrange Multipliers, Mixed-Integer Non Linear Programming and others use evolutionary algorithms like Genetic Algorithms (GA) and recently the use of the Particle Swarm Optimization (PSO) showed to be a potential tool as a global optimization algorithm when applied to data reconciliation. Robust Statistics is also increasing in interest and it is being used when measured data are contaminated by random errors and one can not assume the error is normally distributed, situation which reflects real problems situation. The aim of this work is to present a brief comparison between the classical data reconciliation technique and the robust data reconciliation and gross error detection with swarm intelligence procedure in calculating the thermal reactor power for a simplified heat circuit diagram of a steam turbine plant using real data obtained from Angra 2 Nuclear power plant. The main objective is to test the potential of the robust DR and GED method in a integrated framework using swarm intelligence and the three part redescending estimator of Hampel when applied to a real process condition. The results evaluate the potential use of the robust technique in

Robust data reconciliation and outlier detection with swarm intelligence in a thermal reactor power calculation

International Nuclear Information System (INIS)

Valdetaro, Eduardo Damianik; Coordenacao dos Programas de Pos-Graduacao de Engenharia; Schirru, Roberto

2011-01-01

In Nuclear power plants, Data Reconciliation (DR) and Gross Errors Detection (GED) are techniques of increasing interest and are primarily used to keep mass and energy balance into account, which brings outcomes as a direct and indirect financial benefits. Data reconciliation is formulated by a constrained minimization problem, where the constraints correspond to energy and mass balance model. Statistical methods are used combined with the minimization of quadratic error form. Solving nonlinear optimization problem using conventional methods can be troublesome, because a multimodal function with differentiated solutions introduces some difficulties to search an optimal solution. Many techniques were developed to solve Data Reconciliation and Outlier Detection, some of them use, for example, Quadratic Programming, Lagrange Multipliers, Mixed-Integer Non Linear Programming and others use evolutionary algorithms like Genetic Algorithms (GA) and recently the use of the Particle Swarm Optimization (PSO) showed to be a potential tool as a global optimization algorithm when applied to data reconciliation. Robust Statistics is also increasing in interest and it is being used when measured data are contaminated by random errors and one can not assume the error is normally distributed, situation which reflects real problems situation. The aim of this work is to present a brief comparison between the classical data reconciliation technique and the robust data reconciliation and gross error detection with swarm intelligence procedure in calculating the thermal reactor power for a simplified heat circuit diagram of a steam turbine plant using real data obtained from Angra 2 Nuclear power plant. The main objective is to test the potential of the robust DR and GED method in a integrated framework using swarm intelligence and the three part redescending estimator of Hampel when applied to a real process condition. The results evaluate the potential use of the robust technique in

Extending the applied software in the contemporary thermal power plants for increasing the intelligence of the automatic control system

Science.gov (United States)

Krokhin, G.; Pestunov, A.; Arakelyan, E.; Mukhin, V.

2017-11-01

During the last decades, there can be noticed an increase of interest concerning various aspects of intellectual diagnostics and management in thermal power engineering according the hybrid principle. It is conditioned by the fact that conservative static methods does not allow to reflect the actual power installation state adequately. In order to improve the diagnostics quality, we use various fuzzy systems apparatus. In this paper, we introduce the intellectual system, called SKAIS, which is intended for quick and precise diagnostics of thermal power equipment. This system was developed as the result of the research carried out by specialists from National Research University “Moscow Power Engineering Institute” and Novosibirsk State University of Economics and Management. It drastically increases the level of intelligence of the automatic power plant control system.

Computational intelligence for technology enhanced learning

Energy Technology Data Exchange (ETDEWEB)

Xhafa, Fatos [Polytechnic Univ. of Catalonia, Barcelona (Spain). Dept. of Languages and Informatics Systems; Caballe, Santi; Daradoumis, Thanasis [Open Univ. of Catalonia, Barcelona (Spain). Dept. of Computer Sciences Multimedia and Telecommunications; Abraham, Ajith [Machine Intelligence Research Labs (MIR Labs), Auburn, WA (United States). Scientific Network for Innovation and Research Excellence; Juan Perez, Angel Alejandro (eds.) [Open Univ. of Catalonia, Barcelona (Spain). Dept. of Information Sciences

2010-07-01

E-Learning has become one of the most wide spread ways of distance teaching and learning. Technologies such as Web, Grid, and Mobile and Wireless networks are pushing teaching and learning communities to find new and intelligent ways of using these technologies to enhance teaching and learning activities. Indeed, these new technologies can play an important role in increasing the support to teachers and learners, to shorten the time to learning and teaching; yet, it is necessary to use intelligent techniques to take advantage of these new technologies to achieve the desired support to teachers and learners and enhance learners' performance in distributed learning environments. The chapters of this volume bring advances in using intelligent techniques for technology enhanced learning as well as development of e-Learning applications based on such techniques and supported by technology. Such intelligent techniques include clustering and classification for personalization of learning, intelligent context-aware techniques, adaptive learning, data mining techniques and ontologies in e-Learning systems, among others. Academics, scientists, software developers, teachers and tutors and students interested in e-Learning will find this book useful for their academic, research and practice activity. (orig.)

Intelligent control of dynamic LED lighting; Intelligent styring af dynamisk LED belysning. Slutrapport

Energy Technology Data Exchange (ETDEWEB)

Thorseth, A.; Corell, D.; Hansen, Soeren S.; Dam-Hansen, C.; Petersen, Paul Michael

2013-01-15

The project has resulted in a prototype of a new intelligent lighting control system. The control system enables the end user to control his or her own local lighting environment (lighting zone) according to individual preferences and needs. The report provides a description of how the developed intelligent lighting system is composed and functions. The system is designed as a work lamp that enables dynamic change of the light color scheme according to a number of light control algorithms. It is specifically designed in relation to user tests of the intelligent lighting system, which is carried out in the final part of the project. An intelligent and advanced control of LED lighting was developed, which enables optimization of the user's light conditions in a given situation. Based on a number of known parameters, the system can control lighting so that at any time optimal light conditions are created, using a minimum of electric power. (LN)

Design of an Adaptive Power Regulation Mechanism and a Nozzle for a Hydroelectric Power Plant Turbine Test Rig

Science.gov (United States)

Mert, Burak; Aytac, Zeynep; Tascioglu, Yigit; Celebioglu, Kutay; Aradag, Selin; ETU Hydro Research Center Team

2014-11-01

This study deals with the design of a power regulation mechanism for a Hydroelectric Power Plant (HEPP) model turbine test system which is designed to test Francis type hydroturbines up to 2 MW power with varying head and flow(discharge) values. Unlike the tailor made regulation mechanisms of full-sized, functional HEPPs; the design for the test system must be easily adapted to various turbines that are to be tested. In order to achieve this adaptability, a dynamic simulation model is constructed in MATLAB/Simulink SimMechanics. This model acquires geometric data and hydraulic loading data of the regulation system from Autodesk Inventor CAD models and Computational Fluid Dynamics (CFD) analysis respectively. The dynamic model is explained and case studies of two different HEPPs are performed for validation. CFD aided design of the turbine guide vanes, which is used as input for the dynamic model, is also presented. This research is financially supported by Turkish Ministry of Development.

Relationship of emotional intelligence and health locus of control among female breast cancer patients in pakistan

International Nuclear Information System (INIS)

Naz, R.; Kamal, A.

2016-01-01

Objective: To investigate relationship between emotional intelligence and health locus of control in married women with breast cancer disease. Study Design: Cross sectional study. Place and Duration of Study: The data was collected from Nuclear Oncology and Radiology Institute (NORI Hospital) Islamabad (n=210) and from Combined Military Hospital (CMH) Rawalpindi (n=101). Data collection was completed between the period from Oct 2013 to Feb 2014. Patients and Methods: The sample was selected using non- probability sampling technique. Collected breast cancer patients sample was n= 311 whose age range was from 18-80 years. A biographical sheet that contain personal and disease information of patient, and two scales were used: Self Report Measure of Emotional Intelligence (Khan and Kamal, 2010), and Multidimensional Health Locus of Control (Wallston, Stein, and Smith, 1994) were used to assess the constructs explored in this study. Results: Results depict that there was significant positive correlation between emotional intelligence (EI), including its sub scales Emotional Self-Regulation Skills (ESRS), Emotional Self Awareness Skills (ESAS), and Interpersonal Skills Scale (ISS) with the Internal Health Locus of Control (IHLOC). Doctors Health Locus of Control (DHLOC) also have significant relationship to emotional intelligence's all sub divisions, whereas external health locus of control including Chance Health Locus of Control (CHLOC) and Powerful Other people Health Locus of Control (PHLOC) both are related to psychological distresses but it was observed in breast cancer population that chance was significantly correlated to ESAS, and ISS and powerful other people locus. Further on group comparison One Way Analysis of Variance (ANOVA) depicted no significant difference on disease stage groups. Conclusion: The strength factors of EI and HLOC are highlighted in current study. It was concluded that Emotional Intelligence (EI) and health locus of control (IHLOC, and

Hybrid Intelligent Warning System for Boiler tube Leak Trips

Directory of Open Access Journals (Sweden)

Singh Deshvin

2017-01-01

Full Text Available Repeated boiler tube leak trips in coal fired power plants can increase operating cost significantly. An early detection and diagnosis of boiler trips is essential for continuous safe operations in the plant. In this study two artificial intelligent monitoring systems specialized in boiler tube leak trips have been proposed. The first intelligent warning system (IWS-1 represents the use of pure artificial neural network system whereas the second intelligent warning system (IWS-2 represents merging of genetic algorithms and artificial neural networks as a hybrid intelligent system. The Extreme Learning Machine (ELM methodology was also adopted in IWS-1 and compared with traditional training algorithms. Genetic algorithm (GA was adopted in IWS-2 to optimize the ANN topology and the boiler parameters. An integrated data preparation framework was established for 3 real cases of boiler tube leak trip based on a thermal power plant in Malaysia. Both the IWSs were developed using MATLAB coding for training and validation. The hybrid IWS-2 performed better than IWS-1.The developed system was validated to be able to predict trips before the plant monitoring system. The proposed artificial intelligent system could be adopted as a reliable monitoring system of the thermal power plant boilers.

Static security-based available transfer capability using adaptive neuro fuzzy inference system

Energy Technology Data Exchange (ETDEWEB)

Venkaiah, C.; Vinod Kumar, D.M.

2010-07-01

In a deregulated power system, power transactions between a seller and a buyer can only be scheduled when there is sufficient available transfer capability (ATC). Internet-based, open access same-time information systems (OASIS) provide market participants with ATC information that is continuously updated in real time. Static security-based ATC can be computed for the base case system as well as for the critical line outages of the system. Since critical line outages are based on static security analysis, the computation of static security based ATC using conventional methods is both tedious and time consuming. In this study, static security-based ATC was computed for real-time applications using 3 artificial intelligent methods notably the back propagation algorithm (BPA), the radial basis function (RBF) neural network, and the adaptive neuro fuzzy inference system (ANFIS). An IEEE 24-bus reliability test system (RTS) and 75-bus practical system were used to test these 3 different intelligent methods. The results were compared with the conventional full alternating current (AC) load flow method for different transactions.

Static security-based available transfer capability using adaptive neuro fuzzy inference system

International Nuclear Information System (INIS)

Venkaiah, C.; Vinod Kumar, D.M.

2010-01-01

In a deregulated power system, power transactions between a seller and a buyer can only be scheduled when there is sufficient available transfer capability (ATC). Internet-based, open access same-time information systems (OASIS) provide market participants with ATC information that is continuously updated in real time. Static security-based ATC can be computed for the base case system as well as for the critical line outages of the system. Since critical line outages are based on static security analysis, the computation of static security based ATC using conventional methods is both tedious and time consuming. In this study, static security-based ATC was computed for real-time applications using 3 artificial intelligent methods notably the back propagation algorithm (BPA), the radial basis function (RBF) neural network, and the adaptive neuro fuzzy inference system (ANFIS). An IEEE 24-bus reliability test system (RTS) and 75-bus practical system were used to test these 3 different intelligent methods. The results were compared with the conventional full alternating current (AC) load flow method for different transactions.

Energy scavenging using piezoelectric sensors to power in pavement intelligent vehicle detection systems

Science.gov (United States)

Parhad, Ashutosh

Intelligent transportation systems use in-pavement inductive loop sensors to collect real time traffic data. This method is very expensive in terms of installation and maintenance. Our research is focused on developing advanced algorithms capable of generating high amounts of energy that can charge a battery. This electromechanical energy conversion is an optimal way of energy scavenging that makes use of piezoelectric sensors. The power generated is sufficient to run the vehicle detection module that has several sensors embedded together. To achieve these goals, we have developed a simulation module using software's like LabVIEW and Multisim. The simulation module recreates a practical scenario that takes into consideration vehicle weight, speed, wheel width and frequency of the traffic.

Adaptive co-channel interference cancelation for power-limited applications

KAUST Repository

Radaydeh, Redha Mahmoud Mesleh

2010-09-01

This paper proposes an adaptive co-channel interference -steering algorithm for highly correlated receive antenna channels with an aim of reducing the power consumption at the receiver. With this algorithm, the receiver activates as many antennas as necessary to maintain the residual total interference instantaneous power within a tolerable range, which can be set to guarantee a target performance level. The mode of operation does not require perfect knowledge of the statistical ordering of interfering signals instantaneous powers, which further reduces the complexity of implementation. It is shown that the arbitrary interference cancelation technique and no cancelation scenario can be studied as limiting cases of the proposed scheme. Analytical expressions for the statistics of the residual total interference instantaneous power are derived, which are then used to obtain results for the average number of active antennas and system outage performance. Numerical studies supported by simulations are presented to clarify the usefulness of the proposed scheme. ©2010 IEEE.

A novel approach to painting powered by Ambient Intelligence

Directory of Open Access Journals (Sweden)

N. Partarakis

2016-04-01

Full Text Available Today, many forms of art are influenced by the emergence of interactive technologies, including the mixing of physical media with digital technology for forming new hybrid works of art and the usage of mobile phones to create art projected on public spaces. Many artists and painters use digital technology to augment their work creatively and technically. Many believe that the time of transition from traditional analogue art to postmodern digital art that is, to an art grounded in codes rather than images has arrived*. The research work described in this paper contributes towards supporting, through the use of Ambient Intelligence technologies, traditional painters’ creativity, as well as methods and techniques of art masters. The paper presents the design, implementation and evaluation of an intelligent environment and its software infrastructure, to form a digitally augmented Art Workshop. Its practical deployment was conducted in an Ambient Intelligence (AmI simulation space and four feasibility studies were conducted. In each of these studies an oil painting was created following an alternative, yet accredited by artists, approach. The workshop was also evaluated with the involvement of real users and artists in the context of a user based usability study.

Research on intelligent power consumption strategy based on time-of-use pricing

Science.gov (United States)

Fu, Wei; Gong, Li; Chen, Heli; He, Yu

2017-06-01

In this paper, through the analysis of shortcomings of the current domestic and foreign household power consumption strategy: Passive way of power consumption, ignoring the different priority of electric equipment, neglecting the actual load pressure of the grid, ignoring the interaction with the user, to decrease the peak-valley difference and improve load curve in residential area by demand response (DR technology), an intelligent power consumption scheme based on time-of-use(TOU) pricing for household appliances is proposed. The main contribution of this paper is: (1) Three types of household appliance loads are abstracted from different operating laws of various household appliances, and the control models and DR strategies corresponding to these types are established. (2) The fuzzified processing for the information of TOU price, which is based on the time intervals, is performed to get the price priority, in accordance with such DR events as the maximum restricted load of DR, the time of DR and the duration of interruptible load and so on, the DR control rule and pre-scheduling mechanism are led in. (3) The dispatching sequence of household appliances in the control and scheduling queue are switched and controlled to implement the equilibrium of peak and valley loads. The equilibrium effects and economic benefits of power system by pre-scheduling and DR dispatching are compared and analyzed by simulation example, and the results show that using the proposed household appliance control (HAC) scheme the overall cost of consumers can be reduced and the power system load can be alleviated, so the proposed household appliance control (HAC) scheme is feasible and reasonable.

Long Term Analysis of Adaptive Low-Power Instrument Platform Power and Battery Performance

Science.gov (United States)

Edwards, T.; Bowman, J. R.; Clauer, C. R.

2017-12-01

Operation of the Autonomous Adaptive Low-Power Instrument Platform (AAL-PIP) by the Magnetosphere-Ionosphere Science Team (MIST) at Virginia Tech has been ongoing for about 10 years. These instrument platforms are deployed on the East Antarctic Plateau in remote locations that are difficult to access regularly. The systems have been designed to operate unattended for at least 5 years. During the Austral summer, the systems charge batteries using solar panels and power is provided by the batteries during the winter months. If the voltage goes below a critical level, the systems go into hibernation and wait for voltage from the solar panels to initiate a restart sequence to begin operation and battery charging. Our first system was deployed on the East Antarctic Plateau in 2008 and we report here on an analysis of the power and battery performance over multiple years and provide an estimate for how long these systems can operate before major battery maintenance must be performed.

Computational Intelligence and Decision Making Trends and Applications

CERN Document Server

Madureira, Ana; Marques, Viriato

2013-01-01

This book provides a general overview and original analysis of new developments and applications in several areas of Computational Intelligence and Information Systems. Computational Intelligence has become an important tool for engineers to develop and analyze novel techniques to solve problems in basic sciences such as physics, chemistry, biology, engineering, environment and social sciences.   The material contained in this book addresses the foundations and applications of Artificial Intelligence and Decision Support Systems, Complex and Biological Inspired Systems, Simulation and Evolution of Real and Artificial Life Forms, Intelligent Models and Control Systems, Knowledge and Learning Technologies, Web Semantics and Ontologies, Intelligent Tutoring Systems, Intelligent Power Systems, Self-Organized and Distributed Systems, Intelligent Manufacturing Systems and Affective Computing. The contributions have all been written by international experts, who provide current views on the topics discussed and pr...

Intelligent system for a remote diagnosis of a photovoltaic solar power plant

International Nuclear Information System (INIS)

Sanz-Bobi, M A; San Roque, A Muñoz; Marcos, A de; Bada, M

2012-01-01

Usually small and mid-sized photovoltaic solar power plants are located in rural areas and typically they operate unattended. Some technicians are in charge of the supervision of these plants and, if an alarm is automatically issued, they try to investigate the problem and correct it. Sometimes these anomalies are detected some hours or days after they begin. Also the analysis of the causes once the anomaly is detected can take some additional time. All these factors motivated the development of a methodology able to perform continuous and automatic monitoring of the basic parameters of a photovoltaic solar power plant in order to detect anomalies as soon as possible, to diagnose their causes, and to immediately inform the personnel in charge of the plant. The methodology proposed starts from the study of the most significant failure modes of a photovoltaic plant through a FMEA and using this information, its typical performance is characterized by the creation of its normal behaviour models. They are used to detect the presence of a failure in an incipient or current form. Once an anomaly is detected, an automatic and intelligent diagnosis process is started in order to investigate the possible causes. The paper will describe the main features of a software tool able to detect anomalies and to diagnose them in a photovoltaic solar power plant.

Crystallized and fluid intelligence of university students with intellectual disability who are fully integrated versus those who studied in adapted enrichment courses.

Science.gov (United States)

Lifshitz, Hefziba; Verkuilen, Jay; Shnitzer-Meirovich, Shlomit; Altman, Carmit

2018-01-01

Inclusion of people with intellectual disability (ID) in higher postsecondary academic education is on the rise. However, there are no scientific criteria for determining the eligibility for full inclusion of students with ID in university courses. This study focuses on two models of academic inclusion for students with ID: (a) separate adapted enrichment model: students with ID study in separate enrichment courses adapted to their level; (b) full inclusion model: students with ID are included in undergraduate courses, receive academic credits and are expected to accumulate the amount of credits for a B.A. (a) To examine whether crystallized and fluid intelligence and cognitive tests can serve as screening tests for determining the appropriate placement of students with ID for the adapted enrichment model versus the full inclusion model. (b) To examine the attitudes towards the program of students with ID in the inclusion model. The sample included 31 adults with ID: students with ID who were fully included (N = 10) and students with ID who participated in the adapted enrichment model (N = 21). Crystallized and fluid intelligence were examined (WAIS-III, Wechsler, 1997) and Hebrew abstract verbal tests (Glanz, 1989). Semi-structured interviews were conducted in order to examine the attitudes of students in the inclusion model towards the program. The ANOVAs indicate that the most prominent difference between the groups was in vocabulary, knowledge and working memory. ROC analysis, a fundamental tool for diagnostic test evaluation, was used to determine the students' eligibility for appropriate placement in the two models. Seven tests distinguished between the groups in terms of sensitivity and specificity. The interviews were analyzed according to three phases. The results indicate that students with ID are able to participate in undergraduate courses and achieve academic goals. The general IQ and idioms test seem to be best determiners for appropriate placement of

Adaptive collaborative governance of Nepal's community forests: shifting power, strenghtening livelihoods

NARCIS (Netherlands)

McDougall, C.L.

2015-01-01

Short Summary

Cynthia McDougall--PhD Dissertation

Knowledge, Technology, &Innovation Chairgroup (WASS)

Adaptive collaborative governance of Nepal’s community forests: Shifting power, strengthening livelihoods

Guiding rules for development of intelligent monitoring system of nuclear power plants

International Nuclear Information System (INIS)

Kitamura, M.; Furukawa, H.; Kozma, R.; Washio, T.

1996-01-01

General frameworks and major component techniques for intelligent monitoring of nuclear power plants are presented. The key concept, diversity-based design, is to provide advisory information through consensus of multiple agents, each performing operational decision-making by focusing on mutually different information obtained from the plant. The multi-agent design scheme allows to attain high credibility and tolerance against sensor failure in fault detection and causal reasoning. The advantage of the proposed scheme realized by multiple neural networks was clearly demonstrated through numerical experiments with anomalies in a pressurized water reactor. Relevant techniques are also introduced for diagnostic information evaluation in specified symptoms, and for remedial procedure synthesis. A new architecture for future implementation of the proposed scheme, worm-type multi-agent system, is also proposed as a promising candidate. (author)

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.

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

Development of Intelligent Database Program for PSI/ISI Data Management of Nuclear Power Plant

International Nuclear Information System (INIS)

Park, Un Su; Park, Ik Keun; Um, Byong Guk; Park, Yun Won; Kang, Suk Chul

1998-01-01

For an effective and efficient management of large amounts of preservice/inservice inspection(PSI/ISI) data in nuclear power plants, an intelligent Windows 95-based data management program was developed. This program enables the prompt extraction of previously conducted PSI/ISI conditions and results so that the time-consuming data management, painstaking data processing and analysis in the past are avoided. The program extracts, and the associated remedies. Furthermore, additional inspection data and comments can be easily added or deleted for subsequent PSI/ISI operation. Although the initial version of the program was applied to Kori nuclear power plant, this program can be equally applied to other nuclear power plant. And also this program can be used to offer the fundamental data for application of evaluation data related to fracture mechanics analysis(FMA), probabilistic reliability assessment(PRA) of PSI/ISI results, performance demonstration initiative(PDI) and risk-informed ISI based on probability of detection(POD) information of ultrasonic examination. Besides, the program can be further developed as a unique PSI/ISI data management expert system that can be apart of PSI/ISI data management expert system that can be a part of PSI/ISI Total Support System(TSS) for Korean nuclear power plants

A fully integrated, wide-load-range, high-power-conversion-efficiency switched capacitor DC-DC converter with adaptive bias comparator for ultra-low-power power management integrated circuit

Science.gov (United States)

Asano, Hiroki; Hirose, Tetsuya; Kojima, Yuta; Kuroki, Nobutaka; Numa, Masahiro

2018-04-01

In this paper, we present a wide-load-range switched-capacitor DC-DC buck converter with an adaptive bias comparator for ultra-low-power power management integrated circuit. The proposed converter is based on a conventional one and modified to operate in a wide load range by developing a load current monitor used in an adaptive bias comparator. Measurement results demonstrated that our proposed converter generates a 1.0 V output voltage from a 3.0 V input voltage at a load of up to 100 µA, which is 20 times higher than that of the conventional one. The power conversion efficiency was higher than 60% in the load range from 0.8 to 100 µA.

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.

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

Science.gov (United States)

Raskovic, Dejan

Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

Effects of acaoustic adaptation of classrooms on the quality of verbal communication

Directory of Open Access Journals (Sweden)

Witold Mikulski

2013-04-01

Full Text Available Background: Voice organ disorders among teachers are caused by excessive voice strain. One of the measures to reduce this strain is to decrease background noise when teaching. Increasing the acoustic absorption of the room is a technical measure for achieving this aim. The absorption level also improves speech intelligibility rated by the following parameters: room reverberation time and speech transmission index (STI. This article presents the effects of acoustic adaptation of classrooms on the quality of verbal communication, aimed at getting the speech intelligibility at the good or excellent level. Material and Methods: The article lists the criteria for evaluating classrooms in terms of the quality of verbal communication. The parameters were defined, using the measurement methods according to PN-EN ISO 3382-2:2010 and PN-EN 60268-16:2011. Acoustic adaptations were completed in two classrooms. Results: After completing acoustic adaptations the reverberation time for the frequency of 1 kHz was reduced: in room no. 1 from 1.45 s to 0.44 s and in room no. 2 from 1.03 s to 0.37 s (maximum 0.65 s. At the same time, the speech transmission index increased: in room no. 1 from 0.55 (satisfactory speech intelligibility to 0.75 (speech intelligibility close to excellent; in room no. 2 from 0.63 (good speech intelligibility to 0.80 (excellent speech intelligibility. Therefore, it can be stated that prior to completing acoustic adaptations room no. 1 did not comply and room no. 2 barely complied with the criterion (speech transmission index of 0.62. After completing acoustic adaptations both rooms meet the requirements. Med Pr 2013;64(2:207–215

Command Filtered Adaptive Fuzzy Neural Network Backstepping Control for Marine Power System

Directory of Open Access Journals (Sweden)

Xin Zhang

2014-01-01

Full Text Available In order to retrain chaotic oscillation of marine power system which is excited by periodic electromagnetism perturbation, a novel command-filtered adaptive fuzzy neural network backstepping control method is designed. First, the mathematical model of marine power system is established based on the two parallel nonlinear model. Then, main results of command-filtered adaptive fuzzy neural network backstepping control law are given. And the Lyapunov stability theory is applied to prove that the system can remain closed-loop asymptotically stable with this controller. Finally, simulation results indicate that the designed controller can suppress chaotic oscillation with fast convergence speed that makes the system return to the equilibrium point quickly; meanwhile, the parameter which induces chaotic oscillation can also be discriminated.

A DISTRIBUTED SMART HOME ARTIFICIAL INTELLIGENCE SYSTEM

DEFF Research Database (Denmark)

Lynggaard, Per

2013-01-01

A majority of the research performed today explore artificial intelligence in smart homes by using a centralized approach where a smart home server performs the necessary calculations. This approach has some disadvantages that can be overcome by shifting focus to a distributed approach where...... the artificial intelligence system is implemented as distributed as agents running parts of the artificial intelligence system. This paper presents a distributed smart home architecture that distributes artificial intelligence in smart homes and discusses the pros and cons of such a concept. The presented...... distributed model is a layered model. Each layer offers a different complexity level of the embedded distributed artificial intelligence. At the lowest layer smart objects exists, they are small cheap embedded microcontroller based smart devices that are powered by batteries. The next layer contains a more...

Modeling and control of sustainable power systems

CERN Document Server

Wang, Lingfeng

2011-01-01

The concept of the smart grid promises the world an efficient and intelligent approach of managing energy production, transportation, and consumption by incorporating intelligence, efficiency, and optimality into the power grid. Both energy providers and consumers can take advantage of the convenience, reliability, and energy savings achieved by real-time and intelligent energy management. To this end, the current power grid is experiencing drastic changes and upgrades. For instance, more significant green energy resources such as wind power and solar power are being integrated into the power

Biomimetics in Intelligent Sensor and Actuator Automation Systems

Science.gov (United States)

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

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

Speed adaptation in a powered transtibial prosthesis controlled with a neuromuscular model.

Science.gov (United States)

Markowitz, Jared; Krishnaswamy, Pavitra; Eilenberg, Michael F; Endo, Ken; Barnhart, Chris; Herr, Hugh

2011-05-27

Control schemes for powered ankle-foot prostheses would benefit greatly from a means to make them inherently adaptive to different walking speeds. Towards this goal, one may attempt to emulate the intact human ankle, as it is capable of seamless adaptation. Human locomotion is governed by the interplay among legged dynamics, morphology and neural control including spinal reflexes. It has been suggested that reflexes contribute to the changes in ankle joint dynamics that correspond to walking at different speeds. Here, we use a data-driven muscle-tendon model that produces estimates of the activation, force, length and velocity of the major muscles spanning the ankle to derive local feedback loops that may be critical in the control of those muscles during walking. This purely reflexive approach ignores sources of non-reflexive neural drive and does not necessarily reflect the biological control scheme, yet can still closely reproduce the muscle dynamics estimated from biological data. The resulting neuromuscular model was applied to control a powered ankle-foot prosthesis and tested by an amputee walking at three speeds. The controller produced speed-adaptive behaviour; net ankle work increased with walking speed, highlighting the benefits of applying neuromuscular principles in the control of adaptive prosthetic limbs.

Blindness in designing intelligent systems

Science.gov (United States)

Denning, Peter J.

1988-01-01

New investigations of the foundations of artificial intelligence are challenging the hypothesis that problem solving is the cornerstone of intelligence. New distinctions among three domains of concern for humans--description, action, and commitment--have revealed that the design process for programmable machines, such as expert systems, is based on descriptions of actions and induces blindness to nonanalytic action and commitment. Design processes focusing in the domain of description are likely to yield programs like burearcracies: rigid, obtuse, impersonal, and unable to adapt to changing circumstances. Systems that learn from their past actions, and systems that organize information for interpretation by human experts, are more likely to be successful in areas where expert systems have failed.

Design of an effective energy receiving adapter for microwave wireless power transmission application

Directory of Open Access Journals (Sweden)

Peng Xu

2016-10-01

Full Text Available In this paper, we demonstrate the viability of an energy receiving adapter in a 8×8 array form with high power reception efficiency with the resonator of artificial electromagnetic absorber being used as the element. Unlike the conventional reported rectifying antenna resonators, both the size of the element and the separations between the elements are electrically small in our design. The energy collecting process is explained with an equivalent circuit model, and a RF combining network is designed to combine the captured AC power from each element to one main terminal for AC-to-DC conversion. The energy receiving adapter yields a total reception efficiency of 67% (including the wave capture efficiency of 86% and the AC-to-DC conversion efficiency of 78%, which is quite promising for microwave wireless power transmission.

Open-source intelligence and privacy by design

NARCIS (Netherlands)

Koops, B.J.; Hoepman, J.H.; Leenes, R.

2013-01-01

As demonstrated by other papers on this issue, open-source intelligence (OSINT) by state authorities poses challenges for privacy protection and intellectual-property enforcement. A possible strategy to address these challenges is to adapt the design of OSINT tools to embed normative requirements,

Intelligent robotics can boost America's economic growth

Science.gov (United States)

Erickson, Jon D.

1994-01-01

A case is made for strategic investment in intelligent robotics as a part of the solution to the problem of improved global competitiveness for U.S. manufacturing, a critical industrial sector. Similar cases are made for strategic investments in intelligent robotics for field applications, construction, and service industries such as health care. The scope of the country's problems and needs is beyond the capability of the private sector alone, government alone, or academia alone to solve independently of the others. National cooperative programs in intelligent robotics are needed with the private sector supplying leadership direction and aerospace and non-aerospace industries conducting the development. Some necessary elements of such programs are outlined. The National Aeronautics and Space Administration (NASA) and the Lyndon B. Johnson Space Center (JSC) can be key players in such national cooperative programs in intelligent robotics for several reasons: (1) human space exploration missions require supervised intelligent robotics as enabling tools and, hence must develop supervised intelligent robotic systems; (2) intelligent robotic technology is being developed for space applications at JSC (but has a strong crosscutting or generic flavor) that is advancing the state of the art and is producing both skilled personnel and adaptable developmental infrastructure such as integrated testbeds; and (3) a NASA JSC Technology Investment Program in Robotics has been proposed based on commercial partnerships and collaborations for precompetitive, dual-use developments.

How to Improve Artificial Intelligence through Web

Directory of Open Access Journals (Sweden)

Adrian LUPASC

2005-10-01

Full Text Available Intelligent agents, intelligent software applications and artificial intelligent applications from artificial intelligence service providers maymake their way onto the Web in greater number as adaptive software, dynamic programming languages and Learning Algorithms are introduced intoWeb Services. The evolution of Web architecture may allow intelligent applications to run directly on the Web by introducing XML, RDF and logiclayer. The Intelligent Wireless Web’s significant potential for rapidly completing information transactions may take an important contribution toglobal worker productivity. Artificial intelligence can be defined as the study of the ways in which computers can be made to perform cognitivetasks. Examples of such tasks include understanding natural language statements, recognizing visual patterns or scenes, diagnosing diseases orillnesses, solving mathematical problems, performing financial analyses, learning new procedures for solving problems. The term expert system canbe considered to be a particular type of knowledge-based system. An expert system is a system in which the knowledge is deliberately represented“as it is”. Expert systems are applications that make decisions in real-life situations that would otherwise be performed by a human expert. They areprograms designed to mimic human performance at specialized, constrained problem-solving tasks. They are constructed as a collection of IF-THENproduction rules combined with a reasoning engine that applies those rules, either in a forward or backward direction, to specific problems.

Relation of intelligence to ego functioning in an adult psychiatric population.

Science.gov (United States)

Allen, J G; Coyne, L; David, E

1986-01-01

Wechsler Adult Intelligence Scale-Revised (WAIS-R) IQs and clinical ratings of 10 ego functions in a diagnostically heterogeneous sample of 60 adult psychiatric inpatients were correlated. With severity of pathology statistically controlled, higher intelligence was associated with more adequate ego functioning in several spheres: primary autonomous functions, thought processes, object relations, and mastery-competence. There were also some clinically meaningful differences between the Verbal and Performance IQs in the pattern of correlations. Extending Hartmann's original views, the authors employ an ethological framework to conceptualize intelligence in relation to the ego's role in adaptation, emphasizing that intelligence is an important-albeit neglected-aspect of ego functioning.

Reliability and efficiency upgrades of power systems operation by implementing intelligent electronic devices with synchrophasor measurement technology support

OpenAIRE

Mokeev Alexey

2017-01-01

This paper reviews issues of reliability and efficiency upgrades of power systems functions by means of a widespread implementation of intelligent electronic devices (IED) in various purposes supporting synchrophasor measurement technology. Thus, such issues as IED’s operational analysis in the conditions of electromagnetic and electromechanical transient processes and synthesis of digital filters that improve static and dynamic responses of these devices play an important role in their devel...

Introducing Spoken Dialogue Systems into Intelligent Environments

CERN Document Server

Heinroth, Tobias

2013-01-01

Introducing Spoken Dialogue Systems into Intelligent Environments outlines the formalisms of a novel knowledge-driven framework for spoken dialogue management and presents the implementation of a model-based Adaptive Spoken Dialogue Manager(ASDM) called OwlSpeak. The authors have identified three stakeholders that potentially influence the behavior of the ASDM: the user, the SDS, and a complex Intelligent Environment (IE) consisting of various devices, services, and task descriptions. The theoretical foundation of a working ontology-based spoken dialogue description framework, the prototype implementation of the ASDM, and the evaluation activities that are presented as part of this book contribute to the ongoing spoken dialogue research by establishing the fertile ground of model-based adaptive spoken dialogue management. This monograph is ideal for advanced undergraduate students, PhD students, and postdocs as well as academic and industrial researchers and developers in speech and multimodal interactive ...

Application of adaptive fuzzy control technology to pressure control of a pressurizer

Institute of Scientific and Technical Information of China (English)

YANG Ben-kun; BIAN Xin-qian; GUO Wei-lai

2005-01-01

A pressurizer is one of important equipment in a pressurized water reactor plant. It is used to maintain the pressure of primary coolant within allowed range because the sharp change of coolant pressure affects the security of reactor,therefor,the study of pressurizer's pressure control methods is very important. In this paper, an adaptive fuzzy controller is presented for pressure control of a pressurizer in a nuclear power plant. The controller can on-line tune fuzzy control rules and parameters by self-learning in the actual control process, which possesses the way of thinking like human to make a decision. The simulation results for a pressurized water reactor plant show that the adaptive fuzzy controller has optimum and intelligent characteristics, which prove the controller is effective.

Improving Emotional Intelligence through Personality Development: The Effect of the Smart Phone Application based Dharma Life Program on Emotional Intelligence

Directory of Open Access Journals (Sweden)

Latha Poonamallee

2018-02-01

Full Text Available Emotional intelligence is established to predict success in leadership effectiveness in various contexts and has been linked to personality factors. This paper introduces Dharma Life Program, a novel approach to improving emotional intelligence by targeting maladaptive personality traits and triggering neuroplasticity through the use of a smart-phone application and mentoring. The program uses neuroplasticity to enable users to create a more adaptive application of their maladaptive traits, thus improving their emotional intelligence. In this study 26 participants underwent the Dharma Life Program in a leadership development setting. We assessed their emotional and social intelligence before and after the Dharma Life Program intervention using the Emotional and Social Competency Inventory (ESCI. The study found a significant improvement in the lowest three competencies and a significant improvement in almost all domains for the entire sample. Our findings suggest that the completion of the Dharma Life Program has a significant positive effect on Emotional and Social Competency scores and offers a new avenue for improving emotional intelligence competencies.

Improving Emotional Intelligence through Personality Development: The Effect of the Smart Phone Application based Dharma Life Program on Emotional Intelligence

Science.gov (United States)

Poonamallee, Latha; Harrington, Alex M.; Nagpal, Manisha; Musial, Alec

2018-01-01

Emotional intelligence is established to predict success in leadership effectiveness in various contexts and has been linked to personality factors. This paper introduces Dharma Life Program, a novel approach to improving emotional intelligence by targeting maladaptive personality traits and triggering neuroplasticity through the use of a smart-phone application and mentoring. The program uses neuroplasticity to enable users to create a more adaptive application of their maladaptive traits, thus improving their emotional intelligence. In this study 26 participants underwent the Dharma Life Program in a leadership development setting. We assessed their emotional and social intelligence before and after the Dharma Life Program intervention using the Emotional and Social Competency Inventory (ESCI). The study found a significant improvement in the lowest three competencies and a significant improvement in almost all domains for the entire sample. Our findings suggest that the completion of the Dharma Life Program has a significant positive effect on Emotional and Social Competency scores and offers a new avenue for improving emotional intelligence competencies. PMID:29527182

Intelligence in Artificial Intelligence

OpenAIRE

Datta, Shoumen Palit Austin

2016-01-01

The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

Adaptations of renewable energy policies to unstable macroeconomic situations - case study: wind power in Brazil

Energy Technology Data Exchange (ETDEWEB)

Kissel, J.M. [Technical University, Berlin (Germany). Dept. of Renewable Energies; Federal University, Rio de Janeiro (Brazil); World Council for Renewable Energy, Rio de Janeiro (Brazil); Krauter, S.C.W. [Technical University, Berlin (Germany). Dept. of Renewable Energies; World Council for Renewable Energy, Rio de Janeiro (Brazil); State University of Ceara (Brazil). Dept. of Physics

2006-12-15

Despite the massive cost reduction in the last decade, wind power generation is generally still more expensive than conventional energy sources which benefit from the exclusion of externality costs in the price structure. Support policies for renewable energies guarantee the economic viability of this type of electrical power generation in many European countries. In Latin America, Brazil has become the pioneer state for renewable energy with the implementation of the PROINFA programme that supports, among other sources, wind power development of 1100 MW. This article presents an overview of the differences between the German and Brazilian wind power promotion policies with a special focus on how PROINFA can be adapted to the unstable macroeconomic situation of Brazil. The document specifically examines the adaptation of wind power promotion policies to large inflation and interest rates in Brazil. (author)

Adaptations of renewable energy policies to unstable macroeconomic situations-Case study: Wind power in Brazil

Energy Technology Data Exchange (ETDEWEB)

Kissel, Johannes M. [Department of Renewable Energies, Institute for Energy and Control Technology, Technical University Berlin (TUB), Sec. EM 4, Einsteinufer 11, D-10587 Berlin (Germany) and Federal University of Rio de Janeiro (UFRJ-COPPE), Programme for Energy Planning, Rio de Janeiro-RJ (Brazil) and World Council for Renewable Energy-Latin America - WCRE LA, c/o Rio Solar Ltda./PML, Av. Rio Branco, 25/18o andar, 20093-900 Rio de Janeiro-RJ (Brazil)]. E-mail: jo.kissel@gmx.net; Krauter, Stefan C.W. [Department of Renewable Energies, Institute for Energy and Control Technology, Technical University Berlin (TUB), Sec. EM 4, Einsteinufer 11, D-10587 Berlin (Germany) and World Council for Renewable Energy-Latin America (WCRE LA), c/o Rio Solar Ltda./PML, Av. Rio Branco, 25/18o andar, 20093-900 Rio de Janeiro-RJ (Brazil) and Department of Physics, State University of Ceara - UECE, Alternative Energy Group, Av. Paranjana 1700, Campus do Itaperi, Fortaleza 60740-000 CE (Brazil)]. E-mail: krauter@uece.br

2006-12-15

Despite the massive cost reduction in the last decade, wind power generation is generally still more expensive than conventional energy sources which benefit from the exclusion of externality costs in the price structure. Support policies for renewable energies guarantee the economic viability of this type of electrical power generation in many European countries. In Latin America, Brazil has become the pioneer state for renewable energy with the implementation of the PROINFA programme that supports, among other sources, wind power development of 1100 MW. This article presents an overview of the differences between the German and Brazilian wind power promotion policies with a special focus on how PROINFA can be adapted to the unstable macroeconomic situation of Brazil. The document specifically examines the adaptation of wind power promotion policies to large inflation and interest rates in Brazil.

Adaptations of renewable energy policies to unstable macroeconomic situations-Case study: Wind power in Brazil

International Nuclear Information System (INIS)

Kissel, Johannes M.; Krauter, Stefan C.W.

2006-01-01

Despite the massive cost reduction in the last decade, wind power generation is generally still more expensive than conventional energy sources which benefit from the exclusion of externality costs in the price structure. Support policies for renewable energies guarantee the economic viability of this type of electrical power generation in many European countries. In Latin America, Brazil has become the pioneer state for renewable energy with the implementation of the PROINFA programme that supports, among other sources, wind power development of 1100 MW. This article presents an overview of the differences between the German and Brazilian wind power promotion policies with a special focus on how PROINFA can be adapted to the unstable macroeconomic situation of Brazil. The document specifically examines the adaptation of wind power promotion policies to large inflation and interest rates in Brazil

Facilitating Multiple Intelligences Through Multimodal Learning Analytics

Directory of Open Access Journals (Sweden)

Ayesha PERVEEN

2018-01-01

Full Text Available This paper develops a theoretical framework for employing learning analytics in online education to trace multiple learning variations of online students by considering their potential of being multiple intelligences based on Howard Gardner’s 1983 theory of multiple intelligences. The study first emphasizes the need to facilitate students as multiple intelligences by online education systems and then suggests a framework of the advanced form of learning analytics i.e., multimodal learning analytics for tracing and facilitating multiple intelligences while they are engaged in online ubiquitous learning. As multimodal learning analytics is still an evolving area, it poses many challenges for technologists, educationists as well as organizational managers. Learning analytics make machines meet humans, therefore, the educationists with an expertise in learning theories can help technologists devise latest technological methods for multimodal learning analytics and organizational managers can implement them for the improvement of online education. Therefore, a careful instructional design based on a deep understanding of students’ learning abilities, is required to develop teaching plans and technological possibilities for monitoring students’ learning paths. This is how learning analytics can help design an adaptive instructional design based on a quick analysis of the data gathered. Based on that analysis, the academicians can critically reflect upon the quick or delayed implementation of the existing instructional design based on students’ cognitive abilities or even about the single or double loop learning design. The researcher concludes that the online education is multimodal in nature, has the capacity to endorse multiliteracies and, therefore, multiple intelligences can be tracked and facilitated through multimodal learning analytics in an online mode. However, online teachers’ training both in technological implementations and

An intelligent clustering based methodology for confusable diseases ...

African Journals Online (AJOL)

Journal of Computer Science and Its Application ... In this paper, an intelligent system driven by fuzzy clustering algorithm and Adaptive Neuro-Fuzzy Inference System for ... Data on patients diagnosed and confirmed by laboratory tests of viral ...

Multiple Intelligences and Perfectionism in Middle School Gifted Students

Directory of Open Access Journals (Sweden)

Süleyman KAHRAMAN

2016-12-01

Full Text Available In this study, the perfectionism levels of 181 sixth, seventh, and eighth grade gifted students’ were investigated in terms of multiple intelligences. In the study a relational screening model, Survey of Positive and Negative Perfectionism, developed by Kırdök (2004, was used to assess the level of the students’ positive and negative perfectionism. The Multiple Intelligences Inventory, developed by Saban (2001, was used to determine the students’ multiple intelligences, and a personal information form was implemented to obtain socio-demographic data. The results of the study showed that [verbal-linguistic intelligence, mathematical-logical intelligence, and intrapersonal intelligence] [intrapersonal intelligence, mathematical-logical intelligence, and verbal-linguistic intelligence] predicted 34% of the students’ perfectionism levels (p<.001. The explanatory power of the scores in multiple intelligences over negative perfectionism was not found to be statistically significant for any of the sub-dimensions. In order to develop gifted students’ positive perfectionism qualifications, assuming that multiple intelligences can be used as a tool, some suggestions were presented for researchers, counselors, and teachers.