Farmers' perception of risk in cultivating hybrid rice in Bangladesh ...

African Journals Online (AJOL)

Although there is an enormous potential for improving adoption of hybrid rice in Bangladesh, it is going through some difficulties in practice. Understanding farmers' perception about difficulties is critical to successful promotion. The present study was conducted to analyze farmers' perception of risk in cultivating hybrid rice ...

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 ...

An analysis of Turkish students' perception of intelligence from primary school to university

OpenAIRE

Beyaztas, Dilek Ilhan; Hymer, Barry

2016-01-01

The aim of this descriptive study was to determine the features of intelligence perceptions according to age, gender, class level, school success level and university departments. Two different scales by Dweck (2000) for both adults and children were translated into Turkish. These scales were then applied to 1350 Turkish students ranging from 4th grade primary school to 4th year university. Results showed that student scores relating to the perception that intelligence is an unchangeable feat...

DIAGNOSIS WINDOWS PROBLEMS BASED ON HYBRID INTELLIGENCE SYSTEMS

Directory of Open Access Journals (Sweden)

SAFWAN O. HASOON

2013-10-01

Full Text Available This paper describes the artificial intelligence technologies by integrating Radial Basis Function networks with expert systems to construct a robust hybrid system. The purpose of building the hybrid system is to give recommendations to repair the operating system (Windows problems and troubleshoot the problems that can be repaired. The neural network has unique characteristics which it can complete the uncompleted data, the expert system can't deal with data that is incomplete, but using the neural network individually has some disadvantages which it can't give explanations and recommendations to the problems. The expert system has the ability to explain and give recommendations by using the rules and the human expert in some conditions. Therefore, we have combined the two technologies. The paper will explain the integration methods between the two technologies and which method is suitable to be used in the proposed hybrid system.

Nature-inspired design of hybrid intelligent systems

CERN Document Server

Castillo, Oscar; Kacprzyk, Janusz

2017-01-01

This book highlights recent advances in the design of hybrid intelligent systems based on nature-inspired optimization and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction, and optimization of complex problems. The book is divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book’s third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as...

The Relationship between Emotional Intelligence and Perception of Job Performance among Nurses in North West of Iran.

Science.gov (United States)

Vahidi, Maryam; Namdar Areshtanab, Hossein; Arshadi Bostanabad, Mohammad

2016-01-01

Emotional intelligence skills help nurses to cope with the emotional demands of healthcare environment. The aim of this study was to identify the relationship between emotional intelligence and perception of job performance among nurses. Using a correlational descriptive design with stratified random sampling, 338 registered nurses from teaching hospitals in North West of Iran were surveyed. Emotional intelligence and perception of job performance were measured using validated self-report measures. The collected data were analyzed through descriptive and inferential methods using SPSS/13. The mean of nurses' emotional intelligence and their perception of job performance was, respectively, 235.83 ± 37.98 and 157.63 ± 33.23. There was no significant relationship between nurses' emotional intelligence and their perception of job performance. Although there was a significant relationship between intrapersonal subscale of emotional intelligence and job performance, there was none with other subscales. In order to get rid of the physical and psychological effects of stressful work in wards, it seems that nurses just do routine activities and refuse working closely with the patients. It seems that fitting the patient to nurse ratio, dividing work between nurses, and supporting each other are necessary.

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.

A Hybrid Computational Intelligence Approach Combining Genetic Programming And Heuristic Classification for Pap-Smear Diagnosis

DEFF Research Database (Denmark)

Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

2001-01-01

The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come...

A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting

International Nuclear Information System (INIS)

Su, Zhongyue; Wang, Jianzhou; Lu, Haiyan; Zhao, Ge

2014-01-01

Highlights: • A new hybrid model is developed for wind speed forecasting. • The model is based on the Kalman filter and the ARIMA. • An intelligent optimization method is employed in the hybrid model. • The new hybrid model has good performance in western China. - Abstract: Forecasting the wind speed is indispensable in wind-related engineering studies and is important in the management of wind farms. As a technique essential for the future of clean energy systems, reducing the forecasting errors related to wind speed has always been an important research subject. In this paper, an optimized hybrid method based on the Autoregressive Integrated Moving Average (ARIMA) and Kalman filter is proposed to forecast the daily mean wind speed in western China. This approach employs Particle Swarm Optimization (PSO) as an intelligent optimization algorithm to optimize the parameters of the ARIMA model, which develops a hybrid model that is best adapted to the data set, increasing the fitting accuracy and avoiding over-fitting. The proposed method is subsequently examined on the wind farms of western China, where the proposed hybrid model is shown to perform effectively and steadily

Perception of Creativity and Game Intelligence in Soccer

Science.gov (United States)

Leso, Gustavo; Dias, Gonçalo; Ferreira, José Pedro; Gama, José; Couceiro, Micael S.

2017-01-01

A questionnaire was used to investigate the perception of creativity and game intelligence of coaches (n = 34, mean age 28.6 with an average of 14.3 years of experience) and players (n = 118, belonging to the ranks U-15 and U-19). Analyses indicated that there were statistically significant differences in most creative concepts inherent in the…

Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

Directory of Open Access Journals (Sweden)

Yuehjen E. Shao

2014-01-01

Full Text Available Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone’s health. Although there are several ways to measure the body fat percentage (BFP, the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR, artificial neural network (ANN, multivariate adaptive regression splines (MARS, and support vector regression (SVR techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models.

Intelligent sizing of a series hybrid electric power-train system based on Chaos-enhanced accelerated particle swarm optimization

International Nuclear Information System (INIS)

Zhou, Quan; Zhang, Wei; Cash, Scott; Olatunbosun, Oluremi; Xu, Hongming; Lu, Guoxiang

2017-01-01

Highlights: • A novel algorithm for hybrid electric powertrain intelligent sizing is introduced and applied. • The proposed CAPSO algorithm is capable of finding the real optimal result with much higher reputation. • Logistic mapping is the most effective strategy to build CAPSO. • The CAPSO gave more reliable results and increased the efficiency by 1.71%. - Abstract: This paper firstly proposed a novel HEV sizing method using the Chaos-enhanced Accelerated Particle Swarm Optimization (CAPSO) algorithm and secondly provided a demonstration on sizing a series hybrid electric powertrain with investigations of chaotic mapping strategies to achieve the global optimization. In this paper, the intelligent sizing of a series hybrid electric powertrain is formulated as an integer multi-objective optimization issue by modelling the powertrain system. The intelligent sizing mechanism based on APSO is then introduced, and 4 types of the most effective chaotic mapping strategy are investigated to upgrade the standard APSO into CAPSO algorithms for intelligent sizing. The evaluation of the intelligent sizing systems based on standard APSO and CAPSOs are then performed. The Monte Carlo analysis and reputation evaluation indicate that the CAPSO outperforms the standard APSO for finding the real optimal sizing result with much higher reputation, and CAPSO with logistic mapping strategy is the most effective algorithm for HEV powertrain components intelligent sizing. In addition, this paper also performs the sensitivity analysis and Pareto analysis to help engineers customize the intelligent sizing system.

Modeling, control, and simulation of grid connected intelligent hybrid battery/photovoltaic system using new hybrid fuzzy-neural method.

Science.gov (United States)

Rezvani, Alireza; Khalili, Abbas; Mazareie, Alireza; Gandomkar, Majid

2016-07-01

Nowadays, photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is its dependence on weather conditions. Therefore, battery energy storage (BES) can be considered to assist for a stable and reliable output from PV generation system for loads and improve the dynamic performance of the whole generation system in grid connected mode. In this paper, a novel topology of intelligent hybrid generation systems with PV and BES in a DC-coupled structure is presented. Each photovoltaic cell has a specific point named maximum power point on its operational curve (i.e. current-voltage or power-voltage curve) in which it can generate maximum power. Irradiance and temperature changes affect these operational curves. Therefore, the nonlinear characteristic of maximum power point to environment has caused to development of different maximum power point tracking techniques. In order to capture the maximum power point (MPP), a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. Obtained results represent the effectiveness and superiority of the proposed method, and the average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison to the conventional methods. It has the advantages of robustness, fast response and good performance. A detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

The relationship of speech intelligibility with hearing sensitivity, cognition, and perceived hearing difficulties varies for different speech perception tests

Science.gov (United States)

Heinrich, Antje; Henshaw, Helen; Ferguson, Melanie A.

2015-01-01

Listeners vary in their ability to understand speech in noisy environments. Hearing sensitivity, as measured by pure-tone audiometry, can only partly explain these results, and cognition has emerged as another key concept. Although cognition relates to speech perception, the exact nature of the relationship remains to be fully understood. This study investigates how different aspects of cognition, particularly working memory and attention, relate to speech intelligibility for various tests. Perceptual accuracy of speech perception represents just one aspect of functioning in a listening environment. Activity and participation limits imposed by hearing loss, in addition to the demands of a listening environment, are also important and may be better captured by self-report questionnaires. Understanding how speech perception relates to self-reported aspects of listening forms the second focus of the study. Forty-four listeners aged between 50 and 74 years with mild sensorineural hearing loss were tested on speech perception tests differing in complexity from low (phoneme discrimination in quiet), to medium (digit triplet perception in speech-shaped noise) to high (sentence perception in modulated noise); cognitive tests of attention, memory, and non-verbal intelligence quotient; and self-report questionnaires of general health-related and hearing-specific quality of life. Hearing sensitivity and cognition related to intelligibility differently depending on the speech test: neither was important for phoneme discrimination, hearing sensitivity alone was important for digit triplet perception, and hearing and cognition together played a role in sentence perception. Self-reported aspects of auditory functioning were correlated with speech intelligibility to different degrees, with digit triplets in noise showing the richest pattern. The results suggest that intelligibility tests can vary in their auditory and cognitive demands and their sensitivity to the challenges that

Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

Energy Technology Data Exchange (ETDEWEB)

Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)

2011-02-15

In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

International Nuclear Information System (INIS)

Catalao, J.P.S.; Pousinho, H.M.I.; Mendes, V.M.F.

2011-01-01

In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

Optimisation of Software-Defined Networks Performance Using a Hybrid Intelligent System

Directory of Open Access Journals (Sweden)

Ann Sabih

2017-06-01

Full Text Available This paper proposes a novel intelligent technique that has been designed to optimise the performance of Software Defined Networks (SDN. The proposed hybrid intelligent system has employed integration of intelligence-based optimisation approaches with the artificial neural network. These heuristic optimisation methods include Genetic Algorithms (GA and Particle Swarm Optimisation (PSO. These methods were utilised separately in order to select the best inputs to maximise SDN performance. In order to identify SDN behaviour, the neural network model is trained and applied. The maximal optimisation approach has been identified using an analytical approach that considered SDN performance and the computational time as objective functions. Initially, the general model of the neural network was tested with unseen data before implementing the model using GA and PSO to determine the optimal performance of SDN. The results showed that the SDN represented by Artificial Neural Network ANN, and optmised by PSO, generated a better configuration with regards to computational efficiency and performance index.

Hybrid Intelligent Control for Submarine Stabilization

Directory of Open Access Journals (Sweden)

Minghui Wang

2013-05-01

Full Text Available Abstract While sailing near the sea surface, submarines will often undergo rolling motion caused by wave disturbance. Fierce rolling motion seriously affects their normal operation and even threatens their security. We propose a new control method for roll stabilization. This paper studies hybrid intelligent control combining a fuzzy control, a neural network and extension control technology. Every control strategy can achieve the ideal control effect within the scope of its effective control. The neuro-fuzzy control strategy is used to improve the robustness of the controller. The speed control strategy and the course control strategy are conducted to extend the control range. The paper also proposes the design of the controller and carries out the simulation experiment in different sea conditions. The simulation results show that the control method proposed can indeed effectively improve the control performance of submarine stabilization.

Emotional Intelligence, Communication Competence, and Student Perceptions of Team Social Cohesion

Science.gov (United States)

Troth, Ashlea C.; Jordan, Peter J.; Lawrence, Sandra A.

2012-01-01

Students generally report poor experiences of group work in university settings. This study examines whether individual student perceptions of team social cohesion are determined by their level of emotional intelligence (EI) and whether this relationship is mediated by their communication skills. Business students (N = 273) completed the 16-item…

Appearing smart: the impression management of intelligence, person perception accuracy, and behavior in social interaction.

Science.gov (United States)

Murphy, Nora A

2007-03-01

Intelligence is an important trait that affects everyday social interaction. The present research utilized the ecological perspective of social perception to investigate the impression management of intelligence and strangers' evaluations of targets' intelligence levels. The ability to effectively portray an impression of intelligence to outside judges as well as interaction partners was appraised and the effect of impression management on the accurate judgment of intelligence was assessed. In addition, targets' behavior was studied in relation to impression management, perceived intelligence, and actual measured intelligence. Impression-managing targets appeared more intelligent to video judges but not to their interaction partner as compared to controls. The intelligence quotient (IQ) of impression-managing targets was more accurately judged than controls' IQ. Impression-managing targets displayed distinct nonverbal behavioral patterns that differed from controls. Looking while speaking was a key behavior: It significantly correlated with IQ, was successfully manipulated by impression-managing targets, and contributed to higher perceived intelligence ratings.

A Correlational Study Examining Demonstrated Emotional Intelligence and Perceptions of School Climate

Science.gov (United States)

Anderson, Chris James

2016-01-01

A quantitative study with a correlational design, this research investigated whether certified teachers' ratings of their school leader's demonstrated emotional intelligence behaviors correlated with the teacher's perceptions of school climate. A sample of 42 graduate and post baccalaureate students from a Mid-Atlantic region college accessed a…

Listener Perception of Monopitch, Naturalness, and Intelligibility for Speakers with Parkinson's Disease

Science.gov (United States)

Anand, Supraja; Stepp, Cara E.

2015-01-01

Purpose: Given the potential significance of speech naturalness to functional and social rehabilitation outcomes, the objective of this study was to examine the effect of listener perceptions of monopitch on speech naturalness and intelligibility in individuals with Parkinson's disease (PD). Method: Two short utterances were extracted from…

The relationship of speech intelligibility with hearing sensitivity, cognition, and perceived hearing difficulties varies for different speech perception tests

Directory of Open Access Journals (Sweden)

Antje eHeinrich

2015-06-01

Full Text Available Listeners vary in their ability to understand speech in noisy environments. Hearing sensitivity, as measured by pure-tone audiometry, can only partly explain these results, and cognition has emerged as another key concept. Although cognition relates to speech perception, the exact nature of the relationship remains to be fully understood. This study investigates how different aspects of cognition, particularly working memory and attention, relate to speech intelligibility for various tests.Perceptual accuracy of speech perception represents just one aspect of functioning in a listening environment. Activity and participation limits imposed by hearing loss, in addition to the demands of a listening environment, are also important and may be better captured by self-report questionnaires. Understanding how speech perception relates to self-reported aspects of listening forms the second focus of the study.Forty-four listeners aged between 50-74 years with mild SNHL were tested on speech perception tests differing in complexity from low (phoneme discrimination in quiet, to medium (digit triplet perception in speech-shaped noise to high (sentence perception in modulated noise; cognitive tests of attention, memory, and nonverbal IQ; and self-report questionnaires of general health-related and hearing-specific quality of life.Hearing sensitivity and cognition related to intelligibility differently depending on the speech test: neither was important for phoneme discrimination, hearing sensitivity alone was important for digit triplet perception, and hearing and cognition together played a role in sentence perception. Self-reported aspects of auditory functioning were correlated with speech intelligibility to different degrees, with digit triplets in noise showing the richest pattern. The results suggest that intelligibility tests can vary in their auditory and cognitive demands and their sensitivity to the challenges that auditory environments pose on

Swarm Intelligence for Optimizing Hybridized Smoothing Filter in Image Edge Enhancement

Science.gov (United States)

Rao, B. Tirumala; Dehuri, S.; Dileep, M.; Vindhya, A.

In this modern era, image transmission and processing plays a major role. It would be impossible to retrieve information from satellite and medical images without the help of image processing techniques. Edge enhancement is an image processing step that enhances the edge contrast of an image or video in an attempt to improve its acutance. Edges are the representations of the discontinuities of image intensity functions. For processing these discontinuities in an image, a good edge enhancement technique is essential. The proposed work uses a new idea for edge enhancement using hybridized smoothening filters and we introduce a promising technique of obtaining best hybrid filter using swarm algorithms (Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO)) to search for an optimal sequence of filters from among a set of rather simple, representative image processing filters. This paper deals with the analysis of the swarm intelligence techniques through the combination of hybrid filters generated by these algorithms for image edge enhancement.

Non-Newtonian Aspects of Artificial Intelligence

Science.gov (United States)

Zak, Michail

2016-05-01

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

Intelligent perception control based on a blackboard architecture

International Nuclear Information System (INIS)

Taibi, I.; Koenig, A.; Vacherand, F.

1991-01-01

In this paper, is described the intelligent perception control system GESPER which is presently equipped with a set of three cameras, a telemeter and a camera associated with a structured strip light. This system is of great interest for all our robotic applications as it is capable of autonomously planning, triggering acquisitions, integrating and interpreting multisensory data. The GESPER architecture, based on the blackboard model, provides a generic development method for indoor and outdoor perception. The modularity and the independence of the knowledge sources make the software evolving easily without breaking down the architecture. New sensors and/or new data processing can be integrated by the addition of new knowledge sources that modelize them. At present, first results are obtained in our testbed hall which simulates the nuclear plant as gives similar experimental conditions. Our ongoing research concerns the improvement of fusion algorithms and the embedding of the whole system (hardware and software) on target robots and distributed architecture

ARTIFICIAL NEURAL NETWORKS BASED GEARS MATERIAL SELECTION HYBRID INTELLIGENT SYSTEM

Institute of Scientific and Technical Information of China (English)

X.C. Li; W.X. Zhu; G. Chen; D.S. Mei; J. Zhang; K.M. Chen

2003-01-01

An artificial neural networks(ANNs) based gear material selection hybrid intelligent system is established by analyzing the individual advantages and weakness of expert system (ES) and ANNs and the applications in material select of them. The system mainly consists of tow parts: ES and ANNs. By being trained with much data samples,the back propagation (BP) ANN gets the knowledge of gear materials selection, and is able to inference according to user input. The system realizes the complementing of ANNs and ES. Using this system, engineers without materials selection experience can conveniently deal with gear materials selection.

Rhythm Perception and Its Role in Perception and Learning of Dysrhythmic Speech.

Science.gov (United States)

Borrie, Stephanie A; Lansford, Kaitlin L; Barrett, Tyson S

2017-03-01

The perception of rhythm cues plays an important role in recognizing spoken language, especially in adverse listening conditions. Indeed, this has been shown to hold true even when the rhythm cues themselves are dysrhythmic. This study investigates whether expertise in rhythm perception provides a processing advantage for perception (initial intelligibility) and learning (intelligibility improvement) of naturally dysrhythmic speech, dysarthria. Fifty young adults with typical hearing participated in 3 key tests, including a rhythm perception test, a receptive vocabulary test, and a speech perception and learning test, with standard pretest, familiarization, and posttest phases. Initial intelligibility scores were calculated as the proportion of correct pretest words, while intelligibility improvement scores were calculated by subtracting this proportion from the proportion of correct posttest words. Rhythm perception scores predicted intelligibility improvement scores but not initial intelligibility. On the other hand, receptive vocabulary scores predicted initial intelligibility scores but not intelligibility improvement. Expertise in rhythm perception appears to provide an advantage for processing dysrhythmic speech, but a familiarization experience is required for the advantage to be realized. Findings are discussed in relation to the role of rhythm in speech processing and shed light on processing models that consider the consequence of rhythm abnormalities in dysarthria.

Assessing the Therapeutic Environment in Hybrid Models of Treatment: Prisoner Perceptions of Staff

Science.gov (United States)

Kubiak, Sheryl Pimlott

2009-01-01

Hybrid treatment models within prisons are staffed by both criminal justice and treatment professionals. Because these models may be indicative of future trends, examining the perceptions of prisoners/participants may provide important information. This study examines the perceptions of male and female inmates in three prisons, comparing those in…

Ruhsal Zeka ve Çalışma Algısı Üzerine Bir Analiz(The Analysis on Spiritual Intelligence and Working Perception

Directory of Open Access Journals (Sweden)

Ümmühan YİĞİT SEYFİ

2016-12-01

Full Text Available In today’s world, companies have mosaic organization structure in that employees with different cultures and generations work together. In this structure, to sustain existence of the companies with their employees as a whole, it is important to improve spiritual intelligence of employees. Spiritual intelligence is a kind of connective thinking that provides holistic approach. Spiritual intelligence is being aware of who you are and is living life with this awareness. This research is designed to understand the nature of the relationships between spiritual intelligence and working perception. First of all the related literature were examined aiming for research purpose. The survey instrument through which the research were conducted consists of ‘The Spiritual Intelligence Self-Report Inventory (SISRI-24, Work Mentality(IGA Questionnaire. The data were analyzed using Statistical Package for Social Sciences (SPSS 22. After profiles were determined benefiting from demographic data of the sample, the reliability and validity of the instruments, factor analysis were performed. Correlation, regression, t-test and ANOVA techniques have been used to analyse the data. Results of the study indicate that there is a statistically significant positive relationship between spiritual intelligence and work perception and established model was adopted. The increase in spiritual intelligence level positively affects the work perception.

Hybrid intelligent control concepts for optimal data fusion

Science.gov (United States)

Llinas, James

1994-02-01

In the post-Cold War era, Naval surface ship operations will be largely conducted in littoral waters to support regional military missions of all types, including humanitarian and evacuation activities, and amphibious mission execution. Under these conditions, surface ships will be much more isolated and vulnerable to a variety of threats, including maneuvering antiship missiles. To deal with these threats, the optimal employment of multiple shipborne sensors for maximum vigilance is paramount. This paper characterizes the sensor management problem as one of intelligent control, identifies some of the key issues in controller design, and presents one approach to controller design which is soon to be implemented and evaluated. It is argued that the complexity and hierarchical nature of problem formulation demands a hybrid combination of knowledge-based methods and scheduling techniques from 'hard' real-time systems theory for its solution.

The Correlation between Teachers' Perceptions about Principal's Emotional Intelligence and Organizational Climate and Job Satisfaction of Teachers of State Senior High School in Gunungsitoli Nias, Indonesia

Science.gov (United States)

Waruwu, Binahati

2015-01-01

This study is aimed at finding out the significant correlation between: (1) teachers' perceptions about principal's emotional intelligence and job satisfaction of teachers, (2) organizational climate and job satisfaction of teachers, and (3) teachers' perceptions about principal's emotional intelligence and organizational climate and job…

Hybrid intelligent methodology to design translation invariant morphological operators for Brazilian stock market prediction.

Science.gov (United States)

Araújo, Ricardo de A

2010-12-01

This paper presents a hybrid intelligent methodology to design increasing translation invariant morphological operators applied to Brazilian stock market prediction (overcoming the random walk dilemma). The proposed Translation Invariant Morphological Robust Automatic phase-Adjustment (TIMRAA) method consists of a hybrid intelligent model composed of a Modular Morphological Neural Network (MMNN) with a Quantum-Inspired Evolutionary Algorithm (QIEA), which searches for the best time lags to reconstruct the phase space of the time series generator phenomenon and determines the initial (sub-optimal) parameters of the MMNN. Each individual of the QIEA population is further trained by the Back Propagation (BP) algorithm to improve the MMNN parameters supplied by the QIEA. Also, for each prediction model generated, it uses a behavioral statistical test and a phase fix procedure to adjust time phase distortions observed in stock market time series. Furthermore, an experimental analysis is conducted with the proposed method through four Brazilian stock market time series, and the achieved results are discussed and compared to results found with random walk models and the previously introduced Time-delay Added Evolutionary Forecasting (TAEF) and Morphological-Rank-Linear Time-lag Added Evolutionary Forecasting (MRLTAEF) methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

Employees High in Personal Intelligence Differ From Their Colleagues in Workplace Perceptions and Behavior.

Science.gov (United States)

Mayer, John D; Lortie, Brendan; Panter, A T; Caruso, David R

2018-05-02

Personal intelligence (PI) involves the ability to recognize, reason, and use information about personality to understand oneself and other people. Employees in two studies (Ns = 394, 482) completed the Test of Personal Intelligence (TOPI; e.g., Mayer, Panter, & Caruso, 2017a) and assessments of workplace perception and behavior. Higher PI was associated with higher perceived workplace support and lower counterproductive work behavior. These relationships continued to hold after controlling for other key variables. The results indicate the TOPI, although still in research trials, shows promise as a screening device for selecting employees and targeting individuals for training.

Skill Learning for Intelligent Robot by Perception-Action Integration: A View from Hierarchical Temporal Memory

Directory of Open Access Journals (Sweden)

Xinzheng Zhang

2017-01-01

Full Text Available Skill learning autonomously through interactions with the environment is a crucial ability for intelligent robot. A perception-action integration or sensorimotor cycle, as an important issue in imitation learning, is a natural mechanism without the complex program process. Recently, neurocomputing model and developmental intelligence method are considered as a new trend for implementing the robot skill learning. In this paper, based on research of the human brain neocortex model, we present a skill learning method by perception-action integration strategy from the perspective of hierarchical temporal memory (HTM theory. The sequential sensor data representing a certain skill from a RGB-D camera are received and then encoded as a sequence of Sparse Distributed Representation (SDR vectors. The sequential SDR vectors are treated as the inputs of the perception-action HTM. The HTM learns sequences of SDRs and makes predictions of what the next input SDR will be. It stores the transitions of the current perceived sensor data and next predicted actions. We evaluated the performance of this proposed framework for learning the shaking hands skill on a humanoid NAO robot. The experimental results manifest that the skill learning method designed in this paper is promising.

An Analysis of Turkish Students' Perception of Intelligence from Primary School to University

Science.gov (United States)

Beyaztas, Dilek Ilhan; Hymer, Barry

2018-01-01

The aim of this descriptive study was to determine the features of intelligence perceptions according to age, gender, class level, school success level and university departments. Two different scales by Dweck (2000) for both adults and children were translated into Turkish. These scales were then applied to 1350 Turkish students ranging from…

Development of hybrid artificial intelligent based handover decision algorithm

Directory of Open Access Journals (Sweden)

A.M. Aibinu

2017-04-01

Full Text Available The possibility of seamless handover remains a mirage despite the plethora of existing handover algorithms. The underlying factor responsible for this has been traced to the Handover decision module in the Handover process. Hence, in this paper, the development of novel hybrid artificial intelligent handover decision algorithm has been developed. The developed model is made up of hybrid of Artificial Neural Network (ANN based prediction model and Fuzzy Logic. On accessing the network, the Received Signal Strength (RSS was acquired over a period of time to form a time series data. The data was then fed to the newly proposed k-step ahead ANN-based RSS prediction system for estimation of prediction model coefficients. The synaptic weights and adaptive coefficients of the trained ANN was then used to compute the k-step ahead ANN based RSS prediction model coefficients. The predicted RSS value was later codified as Fuzzy sets and in conjunction with other measured network parameters were fed into the Fuzzy logic controller in order to finalize handover decision process. The performance of the newly developed k-step ahead ANN based RSS prediction algorithm was evaluated using simulated and real data acquired from available mobile communication networks. Results obtained in both cases shows that the proposed algorithm is capable of predicting ahead the RSS value to about ±0.0002 dB. Also, the cascaded effect of the complete handover decision module was also evaluated. Results obtained show that the newly proposed hybrid approach was able to reduce ping-pong effect associated with other handover techniques.

Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm

Science.gov (United States)

Asaithambi, Sasikumar; Rajappa, Muthaiah

2018-05-01

In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

Pre-Service English as a Foreign Language Teachers' Perceptions of the Relationship between Multiple Intelligences and Foreign Language Learning

Science.gov (United States)

Savas, Perihan

2012-01-01

The relationship between intelligence, language, and learning is a challenging field of study. One way to study how this relationship occurs and works is to investigate the perceptions of advanced language learners. Therefore, this paper reports a study that was conducted to explore 160 pre-service English language teachers' perceptions about…

Hybrid Intelligent Control Method to Improve the Frequency Support Capability of Wind Energy Conversion Systems

Directory of Open Access Journals (Sweden)

Shin Young Heo

2015-10-01

Full Text Available This paper presents a hybrid intelligent control method that enables frequency support control for permanent magnet synchronous generators (PMSGs wind turbines. The proposed method for a wind energy conversion system (WECS is designed to have PMSG modeling and full-scale back-to-back insulated-gate bipolar transistor (IGBT converters comprising the machine and grid side. The controller of the machine side converter (MSC and the grid side converter (GSC are designed to achieve maximum power point tracking (MPPT based on an improved hill climb searching (IHCS control algorithm and de-loaded (DL operation to obtain a power margin. Along with this comprehensive control of maximum power tracking mode based on the IHCS, a method for kinetic energy (KE discharge control of the supporting primary frequency control scheme with DL operation is developed to regulate the short-term frequency response and maintain reliable operation of the power system. The effectiveness of the hybrid intelligent control method is verified by a numerical simulation in PSCAD/EMTDC. Simulation results show that the proposed approach can improve the frequency regulation capability in the power system.

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

OpenAIRE

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

2017-01-01

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

Sensor Systems for Vehicle Environment Perception in a Highway Intelligent Space System

Science.gov (United States)

Tang, Xiaofeng; Gao, Feng; Xu, Guoyan; Ding, Nenggen; Cai, Yao; Ma, Mingming; Liu, Jianxing

2014-01-01

A Highway Intelligent Space System (HISS) is proposed to study vehicle environment perception in this paper. The nature of HISS is that a space sensors system using laser, ultrasonic or radar sensors are installed in a highway environment and communication technology is used to realize the information exchange between the HISS server and vehicles, which provides vehicles with the surrounding road information. Considering the high-speed feature of vehicles on highways, when vehicles will be passing a road ahead that is prone to accidents, the vehicle driving state should be predicted to ensure drivers have road environment perception information in advance, thereby ensuring vehicle driving safety and stability. In order to verify the accuracy and feasibility of the HISS, a traditional vehicle-mounted sensor system for environment perception is used to obtain the relative driving state. Furthermore, an inter-vehicle dynamics model is built and model predictive control approach is used to predict the driving state in the following period. Finally, the simulation results shows that using the HISS for environment perception can arrive at the same results detected by a traditional vehicle-mounted sensors system. Meanwhile, we can further draw the conclusion that using HISS to realize vehicle environment perception can ensure system stability, thereby demonstrating the method's feasibility. PMID:24834907

New Intelligent Transmission Concept for Hybrid Mobile Robot Speed Control

Directory of Open Access Journals (Sweden)

Nazim Mir-Nasiri

2008-11-01

Full Text Available This paper presents a new concept of a mobile robot speed control by using two degree of freedom gear transmission. The developed intelligent speed controller utilizes a gear box which comprises of epicyclic gear train with two inputs, one coupled with the engine shaft and another with the shaft of a variable speed dc motor. The net output speed is a combination of the two input speeds and is governed by the transmission ratio of the planetary gear train. This new approach eliminates the use of a torque converter which is otherwise an indispensable part of all available automatic transmissions, thereby reducing the power loss that occurs in the box during the fluid coupling. By gradually varying the speed of the dc motor a stepless transmission has been achieved. The other advantages of the developed controller are pulling over and reversing the vehicle, implemented by intelligent mixing of the dc motor and engine speeds. This approach eliminates traditional braking system in entire vehicle design. The use of two power sources, IC engine and battery driven DC motor, utilizes the modern idea of hybrid vehicles. The new mobile robot speed controller is capable of driving the vehicle even in extreme case of IC engine failure, for example, due to gas depletion..

New Intelligent Transmission Concept for Hybrid Mobile Robot Speed Control

Directory of Open Access Journals (Sweden)

Nazim Mir-Nasiri

2005-09-01

Full Text Available This paper presents a new concept of a mobile robot speed control by using two degree of freedom gear transmission. The developed intelligent speed controller utilizes a gear box which comprises of epicyclic gear train with two inputs, one coupled with the engine shaft and another with the shaft of a variable speed dc motor. The net output speed is a combination of the two input speeds and is governed by the transmission ratio of the planetary gear train. This new approach eliminates the use of a torque converter which is otherwise an indispensable part of all available automatic transmissions, thereby reducing the power loss that occurs in the box during the fluid coupling. By gradually varying the speed of the dc motor a stepless transmission has been achieved. The other advantages of the developed controller are pulling over and reversing the vehicle, implemented by intelligent mixing of the dc motor and engine speeds. This approach eliminates traditional braking system in entire vehicle design. The use of two power sources, IC engine and battery driven DC motor, utilizes the modern idea of hybrid vehicles. The new mobile robot speed controller is capable of driving the vehicle even in extreme case of IC engine failure, for example, due to gas depletion.

Perceived intelligence is associated with measured intelligence in men but not women.

Science.gov (United States)

Kleisner, Karel; Chvátalová, Veronika; Flegr, Jaroslav

2014-01-01

The ability to accurately assess the intelligence of other persons finds its place in everyday social interaction and should have important evolutionary consequences. We used static facial photographs of 40 men and 40 women to test the relationship between measured IQ, perceived intelligence, and facial shape. Both men and women were able to accurately evaluate the intelligence of men by viewing facial photographs. In addition to general intelligence, figural and fluid intelligence showed a significant relationship with perceived intelligence, but again, only in men. No relationship between perceived intelligence and IQ was found for women. We used geometric morphometrics to determine which facial traits are associated with the perception of intelligence, as well as with intelligence as measured by IQ testing. Faces that are perceived as highly intelligent are rather prolonged with a broader distance between the eyes, a larger nose, a slight upturn to the corners of the mouth, and a sharper, pointing, less rounded chin. By contrast, the perception of lower intelligence is associated with broader, more rounded faces with eyes closer to each other, a shorter nose, declining corners of the mouth, and a rounded and massive chin. By contrast, we found no correlation between morphological traits and real intelligence measured with IQ test, either in men or women. These results suggest that a perceiver can accurately gauge the real intelligence of men, but not women, by viewing their faces in photographs; however, this estimation is possibly not based on facial shape. Our study revealed no relation between intelligence and either attractiveness or face shape.

Perceived Intelligence Is Associated with Measured Intelligence in Men but Not Women

Science.gov (United States)

Kleisner, Karel; Chvátalová, Veronika; Flegr, Jaroslav

2014-01-01

Background The ability to accurately assess the intelligence of other persons finds its place in everyday social interaction and should have important evolutionary consequences. Methodology/Principal Findings We used static facial photographs of 40 men and 40 women to test the relationship between measured IQ, perceived intelligence, and facial shape. Both men and women were able to accurately evaluate the intelligence of men by viewing facial photographs. In addition to general intelligence, figural and fluid intelligence showed a significant relationship with perceived intelligence, but again, only in men. No relationship between perceived intelligence and IQ was found for women. We used geometric morphometrics to determine which facial traits are associated with the perception of intelligence, as well as with intelligence as measured by IQ testing. Faces that are perceived as highly intelligent are rather prolonged with a broader distance between the eyes, a larger nose, a slight upturn to the corners of the mouth, and a sharper, pointing, less rounded chin. By contrast, the perception of lower intelligence is associated with broader, more rounded faces with eyes closer to each other, a shorter nose, declining corners of the mouth, and a rounded and massive chin. By contrast, we found no correlation between morphological traits and real intelligence measured with IQ test, either in men or women. Conclusions These results suggest that a perceiver can accurately gauge the real intelligence of men, but not women, by viewing their faces in photographs; however, this estimation is possibly not based on facial shape. Our study revealed no relation between intelligence and either attractiveness or face shape. PMID:24651120

The application of hybrid artificial intelligence systems for forecasting

Science.gov (United States)

Lees, Brian; Corchado, Juan

1999-03-01

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

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

Solving Unconstrained Global Optimization Problems via Hybrid Swarm Intelligence Approaches

Directory of Open Access Journals (Sweden)

Jui-Yu Wu

2013-01-01

Full Text Available Stochastic global optimization (SGO algorithms such as the particle swarm optimization (PSO approach have become popular for solving unconstrained global optimization (UGO problems. The PSO approach, which belongs to the swarm intelligence domain, does not require gradient information, enabling it to overcome this limitation of traditional nonlinear programming methods. Unfortunately, PSO algorithm implementation and performance depend on several parameters, such as cognitive parameter, social parameter, and constriction coefficient. These parameters are tuned by using trial and error. To reduce the parametrization of a PSO method, this work presents two efficient hybrid SGO approaches, namely, a real-coded genetic algorithm-based PSO (RGA-PSO method and an artificial immune algorithm-based PSO (AIA-PSO method. The specific parameters of the internal PSO algorithm are optimized using the external RGA and AIA approaches, and then the internal PSO algorithm is applied to solve UGO problems. The performances of the proposed RGA-PSO and AIA-PSO algorithms are then evaluated using a set of benchmark UGO problems. Numerical results indicate that, besides their ability to converge to a global minimum for each test UGO problem, the proposed RGA-PSO and AIA-PSO algorithms outperform many hybrid SGO algorithms. Thus, the RGA-PSO and AIA-PSO approaches can be considered alternative SGO approaches for solving standard-dimensional UGO problems.

Beyond AI: Multi-Intelligence (MI) Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

OpenAIRE

Stephen Fox

2017-01-01

Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI) are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, t...

The Effects of Textisms on Learning, Study Time, and Instructional Perceptions in an Online Artificial Intelligence Instructional Module

Science.gov (United States)

Beasley, Robert; Bryant, Nathan L.; Dodson, Phillip T.; Entwistle, Kevin C.

2013-01-01

The purpose of this study was to investigate the effects of textisms (i.e., abbreviated spellings, acronyms, and other shorthand notations) on learning, study time, and instructional perceptions in an online artificial intelligence instructional module. The independent variable in this investigation was experimental condition. For the control…

Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm

International Nuclear Information System (INIS)

Lazzús, Juan A.; Rivera, Marco; López-Caraballo, Carlos H.

2016-01-01

A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. - Highlights: • PSO–ACO combined particle swarm optimization with ant colony optimization. • This study is the first research of PSO–ACO to estimate parameters of chaotic systems. • PSO–ACO algorithm can identify the parameters of the three-dimensional Lorenz system with low deviations. • PSO–ACO is a very powerful tool for the parameter estimation on other chaotic system.

Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm

Energy Technology Data Exchange (ETDEWEB)

Lazzús, Juan A., E-mail: jlazzus@dfuls.cl; Rivera, Marco; López-Caraballo, Carlos H.

2016-03-11

A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. - Highlights: • PSO–ACO combined particle swarm optimization with ant colony optimization. • This study is the first research of PSO–ACO to estimate parameters of chaotic systems. • PSO–ACO algorithm can identify the parameters of the three-dimensional Lorenz system with low deviations. • PSO–ACO is a very powerful tool for the parameter estimation on other chaotic system.

Public perception related to a hydrogen hybrid internal combustion engine transit bus demonstration and hydrogen fuel

International Nuclear Information System (INIS)

Hickson, Allister; Phillips, Al; Morales, Gene

2007-01-01

Hydrogen has been widely considered as a potentially viable alternative to fossil fuels for use in transportation. In addition to price competitiveness with fossil fuels, a key to its adoption will be public perceptions of hydrogen technologies and hydrogen fuel. This paper examines public perceptions of riders of a hydrogen hybrid internal combustion engine bus and hydrogen as a fuel source

Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

Science.gov (United States)

Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

2015-01-01

The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches. PMID:25734182

Progress and Challenge of Artificial Intelligence

Institute of Scientific and Technical Information of China (English)

Zhong-Zhi Shi; Nan-Ning Zheng

2006-01-01

Artificial Intelligence (AI) is generally considered to be a subfield of computer science, that is concerned to attempt simulation, extension and expansion of human intelligence. Artificial intelligence has enjoyed tremendous success over the last fifty years. In this paper we only focus on visual perception, granular computing, agent computing, semantic grid. Human-level intelligence is the long-term goal of artificial intelligence. We should do joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. A new cross discipline intelligence science is undergoing a rapid development. Future challenges are given in final section.

Intelligent controller of a flexible hybrid robot machine for ITER assembly and maintenance

International Nuclear Information System (INIS)

Al-saedi, Mazin I.; Wu, Huapeng; Handroos, Heikki

2014-01-01

Highlights: • Studying flexible multibody dynamic of hybrid parallel robot. • Investigating fuzzy-PD controller to control a hybrid flexible hydraulically driven robot. • Investigating ANFIS-PD controller to control a hybrid flexible robot. Compare to traditional PID this method gives better performance. • Using the equilibrium of reaction forces between the parallel and serial parts of hybrid robot to control the serial part hydraulically driven. - Abstract: The assembly and maintenance of International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. To fulfill the tasks in ITER application, this paper presents a hybrid redundant manipulator with four DOFs provided by serial kinematic axes and six DOFs by parallel mechanism. Thus, in machining, to achieve greater end-effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. In this paper, the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two control schemes have been investigated: (1) fuzzy-PID self tuning controller composed of the conventional PID control and with fuzzy logic; (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel robot based on rod position predictions. The obtained results of the fuzzy-PID and ANFIS-PID self tuning controller can reduce more tracking errors than the conventional PID controller. Subsequently, the serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should

Intelligent controller of a flexible hybrid robot machine for ITER assembly and maintenance

Energy Technology Data Exchange (ETDEWEB)

Al-saedi, Mazin I., E-mail: mazin.al-saedi@lut.fi; Wu, Huapeng; Handroos, Heikki

2014-10-15

Highlights: • Studying flexible multibody dynamic of hybrid parallel robot. • Investigating fuzzy-PD controller to control a hybrid flexible hydraulically driven robot. • Investigating ANFIS-PD controller to control a hybrid flexible robot. Compare to traditional PID this method gives better performance. • Using the equilibrium of reaction forces between the parallel and serial parts of hybrid robot to control the serial part hydraulically driven. - Abstract: The assembly and maintenance of International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. To fulfill the tasks in ITER application, this paper presents a hybrid redundant manipulator with four DOFs provided by serial kinematic axes and six DOFs by parallel mechanism. Thus, in machining, to achieve greater end-effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. In this paper, the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two control schemes have been investigated: (1) fuzzy-PID self tuning controller composed of the conventional PID control and with fuzzy logic; (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel robot based on rod position predictions. The obtained results of the fuzzy-PID and ANFIS-PID self tuning controller can reduce more tracking errors than the conventional PID controller. Subsequently, the serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should

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.

REVIEW OF HEART DISEASE PREDICTION SYSTEM USING DATA MINING AND HYBRID INTELLIGENT TECHNIQUES

Directory of Open Access Journals (Sweden)

R. Chitra

2013-07-01

Full Text Available The Healthcare industry generally clinical diagnosis is done mostly by doctor’s expertise and experience. Computer Aided Decision Support System plays a major role in medical field. With the growing research on heart disease predicting system, it has become important to categories the research outcomes and provides readers with an overview of the existing heart disease prediction techniques in each category. Neural Networks are one of many data mining analytical tools that can be utilized to make predictions for medical data. From the study it is observed that Hybrid Intelligent Algorithm improves the accuracy of the heart disease prediction system. The commonly used techniques for Heart Disease Prediction and their complexities are summarized in this paper.

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.

Social intelligence, human intelligence and niche construction.

Science.gov (United States)

Sterelny, Kim

2007-04-29

This paper is about the evolution of hominin intelligence. I agree with defenders of the social intelligence hypothesis in thinking that externalist models of hominin intelligence are not plausible: such models cannot explain the unique cognition and cooperation explosion in our lineage, for changes in the external environment (e.g. increasing environmental unpredictability) affect many lineages. Both the social intelligence hypothesis and the social intelligence-ecological complexity hybrid I outline here are niche construction models. Hominin evolution is hominin response to selective environments that earlier hominins have made. In contrast to social intelligence models, I argue that hominins have both created and responded to a unique foraging mode; a mode that is both social in itself and which has further effects on hominin social environments. In contrast to some social intelligence models, on this view, hominin encounters with their ecological environments continue to have profound selective effects. However, though the ecological environment selects, it does not select on its own. Accidents and their consequences, differential success and failure, result from the combination of the ecological environment an agent faces and the social features that enhance some opportunities and suppress others and that exacerbate some dangers and lessen others. Individuals do not face the ecological filters on their environment alone, but with others, and with the technology, information and misinformation that their social world provides.

The Innovative Approaches to Packaging – Comparison Analysis of Intelligent and Active Packaging Perceptions in Slovakia

Directory of Open Access Journals (Sweden)

Loucanova Erika

2017-06-01

Full Text Available Packaging has always served a practical function - to hold goods together and protect it when moving toward the customer through distribution channel. Today packaging is also a container for promoting the product and making it easier and safer to use. The sheer importance of packaging functions is still growing and consequently the interest of the company is to access to the packaging more innovative and creative. The paper deals with the innovative approaches to packaging resulting in the creation of packaging with interactive active features in the form of active and intelligent packaging. Using comparative analysis, we monitored the perception of the active packaging functions in comparison to intelligent packaging function among different age categories. We identified the age categories which are most interested in these functions.

Instrumental intelligent test of food sensory quality as mimic of human panel test combining multiple cross-perception sensors and data fusion

International Nuclear Information System (INIS)

Ouyang, Qin; Zhao, Jiewen; Chen, Quansheng

2014-01-01

Highlights: • To develop a novel instrumental intelligent test methodology for food sensory analysis. • A novel data fusion was used in instrumental intelligent test methodology. • Linear and nonlinear tools were comparatively used for modeling. • The instrumental test methodology can be imitative of human test behavior. - Abstract: Instrumental test of food quality using perception sensors instead of human panel test is attracting massive attention recently. A novel cross-perception multi-sensors data fusion imitating multiple mammal perception was proposed for the instrumental test in this work. First, three mimic sensors of electronic eye, electronic nose and electronic tongue were used in sequence for data acquisition of rice wine samples. Then all data from the three different sensors were preprocessed and merged. Next, three cross-perception variables i.e., color, aroma and taste, were constructed using principal components analysis (PCA) and multiple linear regression (MLR) which were used as the input of models. MLR, back-propagation artificial neural network (BPANN) and support vector machine (SVM) were comparatively used for modeling, and the instrumental test was achieved for the comprehensive quality of samples. Results showed the proposed cross-perception multi-sensors data fusion presented obvious superiority to the traditional data fusion methodologies, also achieved a high correlation coefficient (>90%) with the human panel test results. This work demonstrated that the instrumental test based on the cross-perception multi-sensors data fusion can actually mimic the human test behavior, therefore is of great significance to ensure the quality of products and decrease the loss of the manufacturers

Instrumental intelligent test of food sensory quality as mimic of human panel test combining multiple cross-perception sensors and data fusion

Energy Technology Data Exchange (ETDEWEB)

Ouyang, Qin; Zhao, Jiewen; Chen, Quansheng, E-mail: qschen@ujs.edu.cn

2014-09-02

Highlights: • To develop a novel instrumental intelligent test methodology for food sensory analysis. • A novel data fusion was used in instrumental intelligent test methodology. • Linear and nonlinear tools were comparatively used for modeling. • The instrumental test methodology can be imitative of human test behavior. - Abstract: Instrumental test of food quality using perception sensors instead of human panel test is attracting massive attention recently. A novel cross-perception multi-sensors data fusion imitating multiple mammal perception was proposed for the instrumental test in this work. First, three mimic sensors of electronic eye, electronic nose and electronic tongue were used in sequence for data acquisition of rice wine samples. Then all data from the three different sensors were preprocessed and merged. Next, three cross-perception variables i.e., color, aroma and taste, were constructed using principal components analysis (PCA) and multiple linear regression (MLR) which were used as the input of models. MLR, back-propagation artificial neural network (BPANN) and support vector machine (SVM) were comparatively used for modeling, and the instrumental test was achieved for the comprehensive quality of samples. Results showed the proposed cross-perception multi-sensors data fusion presented obvious superiority to the traditional data fusion methodologies, also achieved a high correlation coefficient (>90%) with the human panel test results. This work demonstrated that the instrumental test based on the cross-perception multi-sensors data fusion can actually mimic the human test behavior, therefore is of great significance to ensure the quality of products and decrease the loss of the manufacturers.

Hybrid Applications Of Artificial Intelligence

Science.gov (United States)

Borchardt, Gary C.

1988-01-01

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

Hybrid soft computing approaches research and applications

CERN Document Server

Dutta, Paramartha; Chakraborty, Susanta

2016-01-01

The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis,  (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.

Speech perception, production and intelligibility in French-speaking children with profound hearing loss and early cochlear implantation after congenital cytomegalovirus infection.

Science.gov (United States)

Laccourreye, L; Ettienne, V; Prang, I; Couloigner, V; Garabedian, E-N; Loundon, N

2015-12-01

To analyze speech in children with profound hearing loss following congenital cytomegalovirus (cCMV) infection with cochlear implantation (CI) before the age of 3 years. In a cohort of 15 children with profound hearing loss, speech perception, production and intelligibility were assessed before and 3 years after CI; variables impacting results were explored. Post-CI, median word recognition was 74% on closed-list and 48% on open-list testing; 80% of children acquired speech production; and 60% were intelligible for all listeners or listeners attentive to lip-reading and/or aware of the child's hearing loss. Univariate analysis identified 3 variables (mean post-CI hearing threshold, bilateral vestibular areflexia, and brain abnormality on MRI) with significant negative impact on the development of speech perception, production and intelligibility. CI showed positive impact on hearing and speech in children with post-cCMV profound hearing loss. Our study demonstrated the key role of maximizing post-CI hearing gain. A few children had insufficient progress, especially in case of bilateral vestibular areflexia and/or brain abnormality on MRI. This led us to suggest that balance rehabilitation and speech therapy should be intensified in such cases. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

A hybrid flight control for a simulated raptor-30 v2 helicopter

International Nuclear Information System (INIS)

Khizer, A.N.

2015-01-01

This paper presents a hybrid flight control system for a single rotor simulated Raptor-30 V2 helicopter. Hybrid intelligent control system, combination of the conventional and intelligent control methodologies, is applied to small model helicopter. The proposed hybrid control used PID as a traditional control and fuzzy as an intelligent control so as to take the maximum advantage of advanced control theory. The helicopter model used; comes from X-Plane flight simulator and their hybrid flight control system was simulated using MATLAB/SIMULINK in a simulation platform. X-Plane is also used to visualize the performance of this proposed autopilot design. Through a series of numerous experiments, the operation of hybrid control system was investigated. Results verified that the proposed hybrid control has an excellent performance at hovering flight mode. (author)

Multi-objective decoupling algorithm for active distance control of intelligent hybrid electric vehicle

Science.gov (United States)

Luo, Yugong; Chen, Tao; Li, Keqiang

2015-12-01

The paper presents a novel active distance control strategy for intelligent hybrid electric vehicles (IHEV) with the purpose of guaranteeing an optimal performance in view of the driving functions, optimum safety, fuel economy and ride comfort. Considering the complexity of driving situations, the objects of safety and ride comfort are decoupled from that of fuel economy, and a hierarchical control architecture is adopted to improve the real-time performance and the adaptability. The hierarchical control structure consists of four layers: active distance control object determination, comprehensive driving and braking torque calculation, comprehensive torque distribution and torque coordination. The safety distance control and the emergency stop algorithms are designed to achieve the safety and ride comfort goals. The optimal rule-based energy management algorithm of the hybrid electric system is developed to improve the fuel economy. The torque coordination control strategy is proposed to regulate engine torque, motor torque and hydraulic braking torque to improve the ride comfort. This strategy is verified by simulation and experiment using a forward simulation platform and a prototype vehicle. The results show that the novel control strategy can achieve the integrated and coordinated control of its multiple subsystems, which guarantees top performance of the driving functions and optimum safety, fuel economy and ride comfort.

Swarm Intelligence-Based Smart Energy Allocation Strategy for Charging Stations of Plug-In Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Imran Rahman

2015-01-01

Full Text Available Recent researches towards the use of green technologies to reduce pollution and higher penetration of renewable energy sources in the transportation sector have been gaining popularity. In this wake, extensive participation of plug-in hybrid electric vehicles (PHEVs requires adequate charging allocation strategy using a combination of smart grid systems and smart charging infrastructures. Daytime charging stations will be needed for daily usage of PHEVs due to the limited all-electric range. Intelligent energy management is an important issue which has already drawn much attention of researchers. Most of these works require formulation of mathematical models with extensive use of computational intelligence-based optimization techniques to solve many technical problems. In this paper, gravitational search algorithm (GSA has been applied and compared with another member of swarm family, particle swarm optimization (PSO, considering constraints such as energy price, remaining battery capacity, and remaining charging time. Simulation results obtained for maximizing the highly nonlinear objective function evaluate the performance of both techniques in terms of best fitness.

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

Directory of Open Access Journals (Sweden)

Daniel-Petru GHENCEA

2017-06-01

Full Text Available The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic. The paper presents a prediction mode obtaining valid range of values for spindles with similar characteristics based on measured data sets from a few spindles test without additional measures being required. Extracting polynomial functions of graphs resulting from simultaneous measurements and predict the dynamics of the two features with multi-objective criterion is the main advantage of this method.

International Conference on Computational Intelligence 2015

CERN Document Server

Saha, Sujan

2017-01-01

This volume comprises the proceedings of the International Conference on Computational Intelligence 2015 (ICCI15). This book aims to bring together work from leading academicians, scientists, researchers and research scholars from across the globe on all aspects of computational intelligence. The work is composed mainly of original and unpublished results of conceptual, constructive, empirical, experimental, or theoretical work in all areas of computational intelligence. Specifically, the major topics covered include classical computational intelligence models and artificial intelligence, neural networks and deep learning, evolutionary swarm and particle algorithms, hybrid systems optimization, constraint programming, human-machine interaction, computational intelligence for the web analytics, robotics, computational neurosciences, neurodynamics, bioinspired and biomorphic algorithms, cross disciplinary topics and applications. The contents of this volume will be of use to researchers and professionals alike....

Emergent web intelligence advanced information retrieval

CERN Document Server

Badr, Youakim; Abraham, Ajith; Hassanien, Aboul-Ella

2010-01-01

Web Intelligence explores the impact of artificial intelligence and advanced information technologies representing the next generation of Web-based systems, services, and environments, and designing hybrid web systems that serve wired and wireless users more efficiently. Multimedia and XML-based data are produced regularly and in increasing way in our daily digital activities, and their retrieval must be explored and studied in this emergent web-based era. 'Emergent Web Intelligence: Advanced information retrieval, provides reviews of the related cutting-edge technologies and insights. It is v

A hybrid optical switch architecture to integrate IP into optical networks to provide flexible and intelligent bandwidth on demand for cloud computing

Science.gov (United States)

Yang, Wei; Hall, Trevor J.

2013-12-01

The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users. As a consequence, the nature of the Internet traffic has been fundamentally transformed from a pure packet-based pattern to today's predominantly flow-based pattern. Cloud computing has also brought about an unprecedented growth in the Internet traffic. In this paper, a hybrid optical switch architecture is presented to deal with the flow-based Internet traffic, aiming to offer flexible and intelligent bandwidth on demand to improve fiber capacity utilization. The hybrid optical switch is capable of integrating IP into optical networks for cloud-based traffic with predictable performance, for which the delay performance of the electronic module in the hybrid optical switch architecture is evaluated through simulation.

Configurable intelligent optimization algorithm design and practice in manufacturing

CERN Document Server

Tao, Fei; Laili, Yuanjun

2014-01-01

Presenting the concept and design and implementation of configurable intelligent optimization algorithms in manufacturing systems, this book provides a new configuration method to optimize manufacturing processes. It provides a comprehensive elaboration of basic intelligent optimization algorithms, and demonstrates how their improvement, hybridization and parallelization can be applied to manufacturing. Furthermore, various applications of these intelligent optimization algorithms are exemplified in detail, chapter by chapter. The intelligent optimization algorithm is not just a single algorit

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.

Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation

Directory of Open Access Journals (Sweden)

Ahmed Hussein

2018-01-01

Full Text Available Self-driving cars are attracting significant attention during the last few years, which makes the technology advances jump fast and reach a point of having a number of automated vehicles on the roads. Therefore, the necessity of cooperative driving for these automated vehicles is exponentially increasing. One of the main issues in the cooperative driving world is the Multirobot Task Allocation (MRTA problem. This paper addresses the MRTA problem, specifically for the problem of vehicles and requests allocation. The objective is to introduce a hybrid optimization-based approach to solve the problem of multiple intelligent vehicles requests allocation as an instance of MRTA problem, to find not only a feasible solution, but also an optimized one as per the objective function. Several test scenarios were implemented in order to evaluate the efficiency of the proposed approach. These scenarios are based on well-known benchmarks; thus a comparative study is conducted between the obtained results and the suboptimal results. The analysis of the experimental results shows that the proposed approach was successful in handling various scenarios, especially with the increasing number of vehicles and requests, which displays the proposed approach efficiency and performance.

A Survey of the Effect of Leader's Social Intelligence on Employee's Perception of Interpersonal Justice: The Mediating Role of Shared Leadership

Science.gov (United States)

Nazarpoori, Amirhooshang

2017-01-01

The purpose of this study was to investigate the effect of a leader's social intelligence (SI) on an employee's perception of interpersonal justice by considering the mediating role of shared leadership. Conceptual model and research hypotheses have been developed by the Marlowe's SI model (1986), and the theory of shared leadership and…

Emotional intelligence, risk perception in abstinent cocaine dependent individuals.

Science.gov (United States)

Romero-Ayuso, Dulce; Mayoral-Gontán, Yolanda; Triviño-Juárez, José-Matías

2016-01-01

Cocaine is now responsible for the second-highest number of cessation intervention requests. In this study we analyze the different skills of emotional intelligence in cocaine- dependent patients maintaining abstinence. The Mayer- Salovey-Caruso Emotional Intelligence Test (MSCEIT) and the Balloon Analogue Risk Task (BART) were administered to 50 subjects (25 individuals with no history of drug use and 25 individuals in treatment at the Addictive Behaviors Unit in a state of withdrawal at the time of evaluation). The results showed differences between these groups in overall emotional intelligence quotient, strategic emotional intelligence, understanding emotions and emotional management. Cocaine-addicted participants showed difficulties in analyzing complex emotions and regulating their emotional response, aspects that can interfere with interactions in daily life.

Intelligence, Academic Self-Concept, and Information Literacy: The Role of Adequate Perceptions of Academic Ability in the Acquisition of Knowledge about Information Searching

Science.gov (United States)

Rosman, Tom; Mayer, Anne-Kathrin; Krampen, Günter

2015-01-01

Introduction: The present paper argues that adequate self-perceptions of academic ability are essential for students' realization of their intellectual potential, thereby fostering learning of complex skills, e.g., information-seeking skills. Thus, academic self-concept should moderate the relationship between intelligence and information…

2nd International Conference on Intelligent Computing, Communication & Devices

CERN Document Server

Popentiu-Vladicescu, Florin

2017-01-01

The book presents high quality papers presented at 2nd International Conference on Intelligent Computing, Communication & Devices (ICCD 2016) organized by Interscience Institute of Management and Technology (IIMT), Bhubaneswar, Odisha, India, during 13 and 14 August, 2016. The book covers all dimensions of intelligent sciences in its three tracks, namely, intelligent computing, intelligent communication and intelligent devices. intelligent computing track covers areas such as intelligent and distributed computing, intelligent grid and cloud computing, internet of things, soft computing and engineering applications, data mining and knowledge discovery, semantic and web technology, hybrid systems, agent computing, bioinformatics, and recommendation systems. Intelligent communication covers communication and network technologies, including mobile broadband and all optical networks that are the key to groundbreaking inventions of intelligent communication technologies. This covers communication hardware, soft...

Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

Science.gov (United States)

Boonjing, Veera; Intakosum, Sarun

2016-01-01

This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span. PMID:27974883

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

Medical applications of artificial intelligence

CERN Document Server

Agah, Arvin

2013-01-01

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

FIVE PHASE PENTAGON HYBRID STEPPER MOTOR INTELLIGENT HALF/FULL DRIVER

Directory of Open Access Journals (Sweden)

Alexandru Morar

2017-06-01

Full Text Available Stepper motors are very well suited for positioning applications since they can achieve very good positional accuracy without complicated feedback loops associated with servo systems. In this paper, an intelligent five-phase stepper motor driver of business card size proposed. Constant current chopping technique was applied for the purposes of high torque, high velocity and high efficiency. The driver was designed to drive a middle-sized hybrid stepper motor with wire current rating from 0.4 to 1.5A. An up-to-dated translator of five-phase stepping motor was used to drive the gates of N- channel MOSFET array. The resolution in full/half mode is 0.72/0.36 degrees/step. Moreover, an automatic power down circuit was used to limit the power consuming as the motor stops. Additionally, a self-testing program embedded in a 80C31-CPU (PCL838 can self-test whether the driver is normal or not. This embedded program including linear acceleration and deceleration routines also can serve as a positioning controller. The dimension of this driver is approximate 70x65x35 millimeters, which is smaller than a business card. Experimental results demonstrate that the responses of the driver can reach 60 kilo pulses per second

Intelligent computing systems emerging application areas

CERN Document Server

Virvou, Maria; Jain, Lakhmi

2016-01-01

This book at hand explores emerging scientific and technological areas in which Intelligent Computing Systems provide efficient solutions and, thus, may play a role in the years to come. It demonstrates how Intelligent Computing Systems make use of computational methodologies that mimic nature-inspired processes to address real world problems of high complexity for which exact mathematical solutions, based on physical and statistical modelling, are intractable. Common intelligent computational methodologies are presented including artificial neural networks, evolutionary computation, genetic algorithms, artificial immune systems, fuzzy logic, swarm intelligence, artificial life, virtual worlds and hybrid methodologies based on combinations of the previous. The book will be useful to researchers, practitioners and graduate students dealing with mathematically-intractable problems. It is intended for both the expert/researcher in the field of Intelligent Computing Systems, as well as for the general reader in t...

Multi-objective swarm intelligence theoretical advances and applications

CERN Document Server

Jagadev, Alok; Panda, Mrutyunjaya

2015-01-01

The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO.       

Artificial intelligence in nanotechnology.

Science.gov (United States)

Sacha, G M; Varona, P

2013-11-15

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

Artificial intelligence in nanotechnology

Science.gov (United States)

Sacha, G. M.; Varona, P.

2013-11-01

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

Artificial intelligence in nanotechnology

International Nuclear Information System (INIS)

Sacha, G M; Varona, P

2013-01-01

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

Signal Corps and Military Intelligence Officer Perceptions of a Multifunctional Branch Merger

Science.gov (United States)

2015-06-12

Ordnance Branch OPMS Officer Personnel Management System ORSA Operations Research—Systems Analysis OSINT Open Source Intelligence PME Primary...HUMINT), Geospatial Intelligence (GEOINT), and Open Source Intelligence ( OSINT ). The broad scope of what is expected from Military Intelligence...and assessment dimensions (SIGINT, MASINT, TECHINT, OSINT , etc.) It is recommended that the Military Intelligence Branch more accurately define which

System for intelligent teleoperation research

International Nuclear Information System (INIS)

Orlando, N.E.

1983-01-01

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

Overall intelligent hybrid control system for a fossil-fuel power unit

Energy Technology Data Exchange (ETDEWEB)

Garduno-Ramirez, Raul

2000-08-01

This research present a methodology to design a generalized overall unit control system for a fossil fuel power unit (FFPU), and develops a minimum prototype to demonstrate its feasibility. Toward the above goal, the associated research project was undertaken as a technology innovation process with its two ends identified as follows. First, it is recognized that the coordinated control strategies constitute the uppermost control level in current FFPUs, and so, are responsible for driving the boiler-turbine-generator set as a single entity. Second, a FFPU is envisioned as a complex process, subject to multiple changing operating conditions, that should perform as an intelligent system, for which an advanced integral control concept is needed. Therefore, as an outcome of the innovation process, a generalized unit control concept that extends the capabilities of current coordinated control schemes is proposed. This concept is presented as the Intelligent Coordinated Control System (ICCS) paradigm, which establishes an open reference framework for the development of overall unit control schemes. The ICCS's system goals are identified using power plant process engineering concepts, and intelligent control systems engineering concepts are used to identify main tasks and to achieve system functional decomposition. A software engineering agency concept is used to identify and group agents according to their knowledge and purpose interactions. The resultant ICCS structure is an open set of functionally grouped agent clusters in a two-level hierarchical system. The upper level, mainly characterized for knowledge-driven processes, performs the supervisory functions needed to provide self governing operation characteristics, while the lower level, mainly characterized for data-driven processes, performs the fast reactive behavior functions necessary for hybrid real-time control and protection. Developed through several stages, the ICCS-MP finally implements a two

Artificial intelligence and information-control systems of robots - 87

International Nuclear Information System (INIS)

Plander, I.

1987-01-01

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

The Weighted Support Vector Machine Based on Hybrid Swarm Intelligence Optimization for Icing Prediction of Transmission Line

Directory of Open Access Journals (Sweden)

Xiaomin Xu

2015-01-01

Full Text Available Not only can the icing coat on transmission line cause the electrical fault of gap discharge and icing flashover but also it will lead to the mechanical failure of tower, conductor, insulators, and others. It will bring great harm to the people’s daily life and work. Thus, accurate prediction of ice thickness has important significance for power department to control the ice disaster effectively. Based on the analysis of standard support vector machine, this paper presents a weighted support vector machine regression model based on the similarity (WSVR. According to the different importance of samples, this paper introduces the weighted support vector machine and optimizes its parameters by hybrid swarm intelligence optimization algorithm with the particle swarm and ant colony (PSO-ACO, which improves the generalization ability of the model. In the case study, the actual data of ice thickness and climate in a certain area of Hunan province have been used to predict the icing thickness of the area, which verifies the validity and applicability of this proposed method. The predicted results show that the intelligent model proposed in this paper has higher precision and stronger generalization ability.

Perceptions of the use of intelligent information access systems in university level active learning activities among teachers of biomedical subjects.

Science.gov (United States)

Aparicio, Fernando; Morales-Botello, María Luz; Rubio, Margarita; Hernando, Asunción; Muñoz, Rafael; López-Fernández, Hugo; Glez-Peña, Daniel; Fdez-Riverola, Florentino; de la Villa, Manuel; Maña, Manuel; Gachet, Diego; Buenaga, Manuel de

2018-04-01

Student participation and the use of active methodologies in classroom learning are being increasingly emphasized. The use of intelligent systems can be of great help when designing and developing these types of activities. Recently, emerging disciplines such as 'educational data mining' and 'learning analytics and knowledge' have provided clear examples of the importance of the use of artificial intelligence techniques in education. The main objective of this study was to gather expert opinions regarding the benefits of using complementary methods that are supported by intelligent systems, specifically, by intelligent information access systems, when processing texts written in natural language and the benefits of using these methods as companion tools to the learning activities that are employed by biomedical and health sciences teachers. Eleven teachers of degree courses who belonged to the Faculties of Biomedical Sciences (BS) and Health Sciences (HS) of a Spanish university in Madrid were individually interviewed. These interviews were conducted using a mixed methods questionnaire that included 66 predefined close-ended and open-ended questions. In our study, three intelligent information access systems (i.e., BioAnnote, CLEiM and MedCMap) were successfully used to evaluate the teacher's perceptions regarding the utility of these systems and their different methods in learning activities. All teachers reported using active learning methods in the classroom, most of which were computer programs that were used for initially designing and later executing learning activities. All teachers used case-based learning methods in the classroom, with a specific emphasis on case reports written in Spanish and/or English. In general, few or none of the teachers were familiar with the technical terms related to the technologies used for these activities such as "intelligent systems" or "concept/mental maps". However, they clearly realized the potential applicability of such

Perception of synthetic speech produced automatically by rule: Intelligibility of eight text-to-speech systems.

Science.gov (United States)

Greene, Beth G; Logan, John S; Pisoni, David B

1986-03-01

We present the results of studies designed to measure the segmental intelligibility of eight text-to-speech systems and a natural speech control, using the Modified Rhyme Test (MRT). Results indicated that the voices tested could be grouped into four categories: natural speech, high-quality synthetic speech, moderate-quality synthetic speech, and low-quality synthetic speech. The overall performance of the best synthesis system, DECtalk-Paul, was equivalent to natural speech only in terms of performance on initial consonants. The findings are discussed in terms of recent work investigating the perception of synthetic speech under more severe conditions. Suggestions for future research on improving the quality of synthetic speech are also considered.

Perception of synthetic speech produced automatically by rule: Intelligibility of eight text-to-speech systems

Science.gov (United States)

GREENE, BETH G.; LOGAN, JOHN S.; PISONI, DAVID B.

2012-01-01

We present the results of studies designed to measure the segmental intelligibility of eight text-to-speech systems and a natural speech control, using the Modified Rhyme Test (MRT). Results indicated that the voices tested could be grouped into four categories: natural speech, high-quality synthetic speech, moderate-quality synthetic speech, and low-quality synthetic speech. The overall performance of the best synthesis system, DECtalk-Paul, was equivalent to natural speech only in terms of performance on initial consonants. The findings are discussed in terms of recent work investigating the perception of synthetic speech under more severe conditions. Suggestions for future research on improving the quality of synthetic speech are also considered. PMID:23225916

Teachers and Students' Perceptions of a Hybrid Sport Education and Teaching for Personal and Social Responsibility Learning Unit

Science.gov (United States)

Fernandez-Rio, Javier; Menendez-Santurio, Jose Ignacio

2017-01-01

Purpose: The purpose of this study was to assess students and teachers' perceptions concerning their participation in an educational kickboxing learning unit based on a hybridization of two pedagogical models: Sport Education and Teaching for Personal and Social Responsibility. Method: Seventy-one students and three physical education teachers…

Intelligence for Human-Assistant Planetary Surface Robots

Science.gov (United States)

Hirsh, Robert; Graham, Jeffrey; Tyree, Kimberly; Sierhuis, Maarten; Clancey, William J.

2006-01-01

The central premise in developing effective human-assistant planetary surface robots is that robotic intelligence is needed. The exact type, method, forms and/or quantity of intelligence is an open issue being explored on the ERA project, as well as others. In addition to field testing, theoretical research into this area can help provide answers on how to design future planetary robots. Many fundamental intelligence issues are discussed by Murphy [2], including (a) learning, (b) planning, (c) reasoning, (d) problem solving, (e) knowledge representation, and (f) computer vision (stereo tracking, gestures). The new "social interaction/emotional" form of intelligence that some consider critical to Human Robot Interaction (HRI) can also be addressed by human assistant planetary surface robots, as human operators feel more comfortable working with a robot when the robot is verbally (or even physically) interacting with them. Arkin [3] and Murphy are both proponents of the hybrid deliberative-reasoning/reactive-execution architecture as the best general architecture for fully realizing robot potential, and the robots discussed herein implement a design continuously progressing toward this hybrid philosophy. The remainder of this chapter will describe the challenges associated with robotic assistance to astronauts, our general research approach, the intelligence incorporated into our robots, and the results and lessons learned from over six years of testing human-assistant mobile robots in field settings relevant to planetary exploration. The chapter concludes with some key considerations for future work in this area.

Probabilistic modelling and analysis of stand-alone hybrid power systems

International Nuclear Information System (INIS)

Lujano-Rojas, Juan M.; Dufo-López, Rodolfo; Bernal-Agustín, José L.

2013-01-01

As a part of the Hybrid Intelligent Algorithm, a model based on an ANN (artificial neural network) has been proposed in this paper to represent hybrid system behaviour considering the uncertainty related to wind speed and solar radiation, battery bank lifetime, and fuel prices. The Hybrid Intelligent Algorithm suggests a combination of probabilistic analysis based on a Monte Carlo simulation approach and artificial neural network training embedded in a genetic algorithm optimisation model. The installation of a typical hybrid system was analysed. Probabilistic analysis was used to generate an input–output dataset of 519 samples that was later used to train the ANNs to reduce the computational effort required. The generalisation ability of the ANNs was measured in terms of RMSE (Root Mean Square Error), MBE (Mean Bias Error), MAE (Mean Absolute Error), and R-squared estimators using another data group of 200 samples. The results obtained from the estimation of the expected energy not supplied, the probability of a determined reliability level, and the estimation of expected value of net present cost show that the presented model is able to represent the main characteristics of a typical hybrid power system under uncertain operating conditions. - Highlights: • This paper presents a probabilistic model for stand-alone hybrid power system. • The model considers the main sources of uncertainty related to renewable resources. • The Hybrid Intelligent Algorithm has been applied to represent hybrid system behaviour. • The installation of a typical hybrid system was analysed. • The results obtained from the study case validate the presented model

Multiple Intelligences in Online, Hybrid, and Traditional Business Statistics Courses

Science.gov (United States)

Lopez, Salvador; Patron, Hilde

2012-01-01

According to Howard Gardner, Professor of Cognition and Education at Harvard University, intelligence of humans cannot be measured with a single factor such as the IQ level. Instead, he and others have suggested that humans have different types of intelligence. This paper examines whether students registered in online or mostly online courses have…

Predictors of effective leadership in industry - should engineering education focus on traditional intelligence, personality, or emotional intelligence?

Science.gov (United States)

Lappalainen, Pia

2015-03-01

Despite the changing global and industrial conditions requiring new approaches to leadership, management training as part of higher engineering education still remains understudied. The subsequent gap in engineering education calls for research on today's leader requirements and pedagogy supporting the inclusion of management competence in higher engineering education. Previous organisation and management studies have, on a general level, established the importance of managerial qualities for industrial performance, but the nature and make-up of these qualifications has not been adequately analysed. To fill the related research gap, the present work embarked on a quantitative empirical effort to identify predictors of successful leadership in engineering. In particular, this study investigated relationships between perceived leader performance and three dimensions of managerial capability: (1) mathematical-logical intelligence, (2) personality, and (3) socio-emotional intelligence. This work complemented previous research by resorting to both self-reports and other-reports: the results acquired from the managerial sample were compared to subordinate perceptions as measured through an emotive intelligence other-report and a general managerial competence multi-source appraisal. The sample comprised 80 superiors and 354 subordinates operating in seven organisations in engineering industries. The results from the quantitative measurements signalled the strongest correlation for socio-emotional intelligence and certain personality dimensions with successful leadership. Mathematical-logical intelligence demonstrated no correlation with subordinate perceptions of good leadership. These findings lay the foundation for the incorporation of socio-emotive skills into higher engineering education.

3rd Workshop on "Combinations of Intelligent Methods and Applications"

CERN Document Server

Palade, Vasile

2013-01-01

The combination of different intelligent methods is a very active research area in Artificial Intelligence (AI). The aim is to create integrated or hybrid methods that benefit from each of their components.  The 3rd Workshop on “Combinations of Intelligent Methods and Applications” (CIMA 2012) was intended to become a forum for exchanging experience and ideas among researchers and practitioners who are dealing with combining intelligent methods either based on first principles or in the context of specific applications. CIMA 2012 was held in conjunction with the 22nd European Conference on Artificial Intelligence (ECAI 2012).This volume includes revised versions of the papers presented at CIMA 2012.  .

Hybrid platform. Economical hybrid drive for commercial vehicles; Hybrid Plattform. Wirtschaftlicher Hybridantrieb fuer Nutzfahrzeuge

Energy Technology Data Exchange (ETDEWEB)

Wallner, S.; Lamke, M.; Mohr, M.; Sedlacek, M.; Speck, F.D. [ZF Friedrichshafen AG, Friedrichshafen (Germany)

2011-07-01

Up to now, hybrid systems have been adapted to their specific requirements in the various applications for trucks, buses as well as mobile and building machines. From a technical point of view, this does indeed result in optimized hybrid drives for each single vehicle application, but due to small volumes, such single developments are critical from a business point of view. ZF Friedrichshafen AG is providing a solution to the technical and economical requirements of the cost-sensitive CV segment in the form of a modular CV parallel hybrid platform composed of a hybrid module system, an inverter, a battery system, and a hybrid software integrated into the overall vehicle. Thanks to the intelligent combination of assemblies and the use of as many identical parts as possible, platforms are realized which cover power ranges between 60 and 120 kW, voltage ranges between 350 and 650 V, and battery capacities between 2 and 4 kWh. The dimensions of the platform elements are such that integration into the diverse commercial vehicle applications is made easy. The hybrid software required for the vehicle-specific functions is also configurable for the mentioned CV applications. (orig.)

The Relation of Teachers' Emotional Intelligence and Students' Social Skills to Students' Emotional and Behavioral Difficulties: A Study of Preschool Teachers' Perceptions

Science.gov (United States)

Poulou, Maria S.

2017-01-01

The present study used hierarchical linear modeling to examine predictors of students' emotional and behavioral difficulties in preschool classrooms. Specifically, the study examined (a) the link between teachers' perceptions of their own emotional intelligence and students' emotional and behavioral difficulties, (b) the link between teachers'…

Introducing a Novel Hybrid Artificial Intelligence Algorithm to Optimize Network of Industrial Applications in Modern Manufacturing

Directory of Open Access Journals (Sweden)

Aydin Azizi

2017-01-01

Full Text Available Recent advances in modern manufacturing industries have created a great need to track and identify objects and parts by obtaining real-time information. One of the main technologies which has been utilized for this need is the Radio Frequency Identification (RFID system. As a result of adopting this technology to the manufacturing industry environment, RFID Network Planning (RNP has become a challenge. Mainly RNP deals with calculating the number and position of antennas which should be deployed in the RFID network to achieve full coverage of the tags that need to be read. The ultimate goal of this paper is to present and evaluate a way of modelling and optimizing nonlinear RNP problems utilizing artificial intelligence (AI techniques. This effort has led the author to propose a novel AI algorithm, which has been named “hybrid AI optimization technique,” to perform optimization of RNP as a hard learning problem. The proposed algorithm is composed of two different optimization algorithms: Redundant Antenna Elimination (RAE and Ring Probabilistic Logic Neural Networks (RPLNN. The proposed hybrid paradigm has been explored using a flexible manufacturing system (FMS, and results have been compared with Genetic Algorithm (GA that demonstrates the feasibility of the proposed architecture successfully.

Optimizing Armed Forces Capabilities for Hybrid Warfare – New Challenge for Slovak Armed Forces

Directory of Open Access Journals (Sweden)

Peter PINDJÁK

2015-09-01

Full Text Available The paper deals with the optimization of military capabilities of the Slovak Armed Forces for conducting operations in a hybrid conflict, which represents one of the possible scenarios of irregular warfare. Whereas in the regular warfare adversaries intend to eliminate the centers of gravity of each other, most often command and control structures, in irregular conflicts, the center of gravity shifts towards the will and cognitive perception of the target population. Hybrid warfare comprises a thoroughly planned combination of conventional military approaches and kinetic operations with subversive, irregular activities, including information and cyber operations. These efforts are often accompanied by intensified activities of intelligence services, special operation forces, and even mercenary and other paramilitary groups. The development of irregular warfare capabilities within the Slovak Armed Forces will require a progressive transformation process that may turn the armed forces into a modern and adaptable element of power, capable of deployment in national and international crisis management operations.

Intelligent judgements over health risks in a spatial agent-based model.

Science.gov (United States)

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of

Cultural Intelligence and Leadership Style in the Education Sector

Science.gov (United States)

Aldhaheri, Ali

2017-01-01

Purpose: Schools in UAE are multicultural in nature. In this context, cultural intelligence (CQ) is a tool, which can increase an individual's ability to interact with people outside his/her culture. The purpose of this paper is to explore the perceptions of the school leaders regarding the key influences of cultural intelligence on their ability…

Students' perception towards the problem based learning tutorial session in a system-based hybrid curriculum.

Science.gov (United States)

Al-Drees, Abdulmajeed A; Khalil, Mahmoud S; Irshad, Mohammad; Abdulghani, Hamza M

2015-03-01

To evaluate students' perception towards the problem based learning (PBL) session in a system-based hybrid curriculum. We conducted a cross-sectional study in the College of Medicine, King Saud University, Saudi Arabia at the end of the 2012-2013 academic year. The survey questionnaire was self-administered, and examined perceptions of PBL session benefits, appropriate running of sessions, and tutor's roles. Out of 510 students, 275 (53.9%) completed the questionnaire. Most of the students reported that PBL sessions were helpful in understanding basic sciences concepts (p=0.04). In addition, they agreed that PBL sessions increased their knowledge of basic sciences (p=0.01). Most students reported that PBL sessions encouraged self-directed learning, collaborative learning, and improved decision making skills. However, 54.5% of students reported lack of proper training before starting the PBL sessions, and only 25.1% of students agreed that the teaching staff are well prepared to run the sessions. Most students used the internet (93.1%), lecture notes (76.7%), and books (64.4%) as learning resources. Most students reported repetition of topics between PBL sessions and lectures (p=0.07). The study highlighted the significant role of PBL in a system-based hybrid curriculum and helped students improve their knowledge and different learning skills. Students and staff training is required before the utilizing the PBL as an instructional method.

Emotional intelligence is a second-stratum factor of intelligence: evidence from hierarchical and bifactor models.

Science.gov (United States)

MacCann, Carolyn; Joseph, Dana L; Newman, Daniel A; Roberts, Richard D

2014-04-01

This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.

Introduction to the SP theory of intelligence

OpenAIRE

Wolff, J Gerard

2018-01-01

This article provides a brief introduction to the "Theory of Intelligence" and its realisation in the "SP Computer Model". The overall goal of the SP programme of research, in accordance with long-established principles in science, has been the simplification and integration of observations and concepts across artificial intelligence, mainstream computing, mathematics, and human learning, perception, and cognition. In broad terms, the SP system is a brain-like system that takes in "New" infor...

2nd International Conference on Robot Intelligence Technology and Applications

CERN Document Server

Matson, Eric; Myung, Hyun; Xu, Peter; Karray, Fakhri

2014-01-01

We are facing a new technological challenge on how to store and retrieve knowledge and manipulate intelligence for autonomous services by intelligent systems which should be capable of carrying out real world tasks autonomously. To address this issue, robot researchers have been developing intelligence technology (InT) for “robots that think” which is in the focus of this book. The book covers all aspects of intelligence from perception at sensor level and reasoning at cognitive level to behavior planning at execution level for each low level segment of the machine. It also presents the technologies for cognitive reasoning, social interaction with humans, behavior generation, ability to cooperate with other robots, ambience awareness, and an artificial genome that can be passed on to other robots. These technologies are to materialize cognitive intelligence, social intelligence, behavioral intelligence, collective intelligence, ambient intelligence and genetic intelligence. The book aims at serving resear...

4th International Conference on Robot Intelligence Technology and Applications

CERN Document Server

Karray, Fakhri; Jo, Jun; Sincak, Peter; Myung, Hyun

2017-01-01

This book covers all aspects of robot intelligence from perception at sensor level and reasoning at cognitive level to behavior planning at execution level for each low level segment of the machine. It also presents the technologies for cognitive reasoning, social interaction with humans, behavior generation, ability to cooperate with other robots, ambience awareness, and an artificial genome that can be passed on to other robots. These technologies are to materialize cognitive intelligence, social intelligence, behavioral intelligence, collective intelligence, ambient intelligence and genetic intelligence. The book aims at serving researchers and practitioners with a timely dissemination of the recent progress on robot intelligence technology and its applications, based on a collection of papers presented at the 4th International Conference on Robot Intelligence Technology and Applications (RiTA), held in Bucheon, Korea, December 14 - 16, 2015. For better readability, this edition has the total of 49 article...

3rd International Conference on Robot Intelligence Technology and Applications

CERN Document Server

Yang, Weimin; Jo, Jun; Sincak, Peter; Myung, Hyun

2015-01-01

This book covers all aspects of robot intelligence from perception at sensor level and reasoning at cognitive level to behavior planning at execution level for each low level segment of the machine. It also presents the technologies for cognitive reasoning, social interaction with humans, behavior generation, ability to cooperate with other robots, ambience awareness, and an artificial genome that can be passed on to other robots. These technologies are to materialize cognitive intelligence, social intelligence, behavioral intelligence, collective intelligence, ambient intelligence and genetic intelligence. The book aims at serving researchers and practitioners with a timely dissemination of the recent progress on robot intelligence technology and its applications, based on a collection of papers presented at the 3rd International Conference on Robot Intelligence Technology and Applications (RiTA), held in Beijing, China, November 6 - 8, 2014. For better readability, this edition has the total 74 papers group...

Assessing multiple intelligences in elementary-school students

Science.gov (United States)

Strecker, Catherine Hunt

The purpose of this qualitative case study was to gain a clear understanding of the manner in which fourth-grade students attending a Kansas elementary school learn when engaged in science activities grounded in H. Gardner's book, Frames of mind the theory of multiple intelligences (1983). The significance of this research lies in the discovery of the difference between teaching practice grounded in multiple intelligences versus that based upon traditional theory. Teacher self-perceptions with regard to the effectiveness of their instruction and student assessment within the classroom were also explored. The research evaluated the overall effectiveness of both traditional curriculum delivery and that rooted in the concept of multiple intelligences.

The Effect of Background Noise on Intelligibility of Dysphonic Speech

Science.gov (United States)

Ishikawa, Keiko; Boyce, Suzanne; Kelchner, Lisa; Powell, Maria Golla; Schieve, Heidi; de Alarcon, Alessandro; Khosla, Sid

2017-01-01

Purpose: The aim of this study is to determine the effect of background noise on the intelligibility of dysphonic speech and to examine the relationship between intelligibility in noise and an acoustic measure of dysphonia--cepstral peak prominence (CPP). Method: A study of speech perception was conducted using speech samples from 6 adult speakers…

Image perception and image processing

International Nuclear Information System (INIS)

Wackenheim, A.

1987-01-01

The author develops theoretical and practical models of image perception and image processing, based on phenomenology and structuralism and leading to original perception: fundamental for a positivistic approach of research work for the development of artificial intelligence that will be able in an automated system fo 'reading' X-ray pictures. (orig.) [de

Image perception and image processing

Energy Technology Data Exchange (ETDEWEB)

Wackenheim, A.

1987-01-01

The author develops theoretical and practical models of image perception and image processing, based on phenomenology and structuralism and leading to original perception: fundamental for a positivistic approach of research work for the development of artificial intelligence that will be able in an automated system fo 'reading' X-ray pictures.

Optimal sensor placement for large structures using the nearest neighbour index and a hybrid swarm intelligence algorithm

International Nuclear Information System (INIS)

Lian, Jijian; He, Longjun; Ma, Bin; Peng, Wenxiang; Li, Huokun

2013-01-01

Research on optimal sensor placement (OSP) has become very important due to the need to obtain effective testing results with limited testing resources in health monitoring. In this study, a new methodology is proposed to select the best sensor locations for large structures. First, a novel fitness function derived from the nearest neighbour index is proposed to overcome the drawbacks of the effective independence method for OSP for large structures. This method maximizes the contribution of each sensor to modal observability and simultaneously avoids the redundancy of information between the selected degrees of freedom. A hybrid algorithm combining the improved discrete particle swarm optimization (DPSO) with the clonal selection algorithm is then implemented to optimize the proposed fitness function effectively. Finally, the proposed method is applied to an arch dam for performance verification. The results show that the proposed hybrid swarm intelligence algorithm outperforms a genetic algorithm with decimal two-dimension array encoding and DPSO in the capability of global optimization. The new fitness function is advantageous in terms of sensor distribution and ensuring a well-conditioned information matrix and orthogonality of modes, indicating that this method may be used to provide guidance for OSP in various large structures. (paper)

Gender differences in emotion perception and self-reported emotional intelligence: A test of the emotion sensitivity hypothesis.

Science.gov (United States)

Fischer, Agneta H; Kret, Mariska E; Broekens, Joost

2018-01-01

Previous meta-analyses and reviews on gender differences in emotion recognition have shown a small to moderate female advantage. However, inconsistent evidence from recent studies has raised questions regarding the implications of different methodologies, stimuli, and samples. In the present research based on a community sample of more than 5000 participants, we tested the emotional sensitivity hypothesis, stating that women are more sensitive to perceive subtle, i.e. low intense or ambiguous, emotion cues. In addition, we included a self-report emotional intelligence test in order to examine any discrepancy between self-perceptions and actual performance for both men and women. We used a wide range of stimuli and models, displaying six different emotions at two different intensity levels. In order to better tap sensitivity for subtle emotion cues, we did not use a forced choice format, but rather intensity measures of different emotions. We found no support for the emotional sensitivity account, as both genders rated the target emotions as similarly intense at both levels of stimulus intensity. Men, however, more strongly perceived non-target emotions to be present than women. In addition, we also found that the lower scores of men in self-reported EI was not related to their actual perception of target emotions, but it was to the perception of non-target emotions.

Gender differences in emotion perception and self-reported emotional intelligence: A test of the emotion sensitivity hypothesis

Science.gov (United States)

Kret, Mariska E.; Broekens, Joost

2018-01-01

Previous meta-analyses and reviews on gender differences in emotion recognition have shown a small to moderate female advantage. However, inconsistent evidence from recent studies has raised questions regarding the implications of different methodologies, stimuli, and samples. In the present research based on a community sample of more than 5000 participants, we tested the emotional sensitivity hypothesis, stating that women are more sensitive to perceive subtle, i.e. low intense or ambiguous, emotion cues. In addition, we included a self-report emotional intelligence test in order to examine any discrepancy between self-perceptions and actual performance for both men and women. We used a wide range of stimuli and models, displaying six different emotions at two different intensity levels. In order to better tap sensitivity for subtle emotion cues, we did not use a forced choice format, but rather intensity measures of different emotions. We found no support for the emotional sensitivity account, as both genders rated the target emotions as similarly intense at both levels of stimulus intensity. Men, however, more strongly perceived non-target emotions to be present than women. In addition, we also found that the lower scores of men in self-reported EI was not related to their actual perception of target emotions, but it was to the perception of non-target emotions. PMID:29370198

Recent advances in swarm intelligence and evolutionary computation

CERN Document Server

2015-01-01

This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference f...

Segmental intelligibility of synthetic speech produced by rule.

Science.gov (United States)

Logan, J S; Greene, B G; Pisoni, D B

1989-08-01

This paper reports the results of an investigation that employed the modified rhyme test (MRT) to measure the segmental intelligibility of synthetic speech generated automatically by rule. Synthetic speech produced by ten text-to-speech systems was studied and compared to natural speech. A variation of the standard MRT was also used to study the effects of response set size on perceptual confusions. Results indicated that the segmental intelligibility scores formed a continuum. Several systems displayed very high levels of performance that were close to or equal to scores obtained with natural speech; other systems displayed substantially worse performance compared to natural speech. The overall performance of the best system, DECtalk--Paul, was equivalent to the data obtained with natural speech for consonants in syllable-initial position. The findings from this study are discussed in terms of the use of a set of standardized procedures for measuring intelligibility of synthetic speech under controlled laboratory conditions. Recent work investigating the perception of synthetic speech under more severe conditions in which greater demands are made on the listener's processing resources is also considered. The wide range of intelligibility scores obtained in the present study demonstrates important differences in perception and suggests that not all synthetic speech is perceptually equivalent to the listener.

Segmental intelligibility of synthetic speech produced by rule

Science.gov (United States)

Logan, John S.; Greene, Beth G.; Pisoni, David B.

2012-01-01

This paper reports the results of an investigation that employed the modified rhyme test (MRT) to measure the segmental intelligibility of synthetic speech generated automatically by rule. Synthetic speech produced by ten text-to-speech systems was studied and compared to natural speech. A variation of the standard MRT was also used to study the effects of response set size on perceptual confusions. Results indicated that the segmental intelligibility scores formed a continuum. Several systems displayed very high levels of performance that were close to or equal to scores obtained with natural speech; other systems displayed substantially worse performance compared to natural speech. The overall performance of the best system, DECtalk—Paul, was equivalent to the data obtained with natural speech for consonants in syllable-initial position. The findings from this study are discussed in terms of the use of a set of standardized procedures for measuring intelligibility of synthetic speech under controlled laboratory conditions. Recent work investigating the perception of synthetic speech under more severe conditions in which greater demands are made on the listener’s processing resources is also considered. The wide range of intelligibility scores obtained in the present study demonstrates important differences in perception and suggests that not all synthetic speech is perceptually equivalent to the listener. PMID:2527884

Hybrid neural intelligent system to predict business failure in small-to-medium-size enterprises.

Science.gov (United States)

Borrajo, M Lourdes; Baruque, Bruno; Corchado, Emilio; Bajo, Javier; Corchado, Juan M

2011-08-01

During the last years there has been a growing need of developing innovative tools that can help small to medium sized enterprises to predict business failure as well as financial crisis. In this study we present a novel hybrid intelligent system aimed at monitoring the modus operandi of the companies and predicting possible failures. This system is implemented by means of a neural-based multi-agent system that models the different actors of the companies as agents. The core of the multi-agent system is a type of agent that incorporates a case-based reasoning system and automates the business control process and failure prediction. The stages of the case-based reasoning system are implemented by means of web services: the retrieval stage uses an innovative weighted voting summarization of self-organizing maps ensembles-based method and the reuse stage is implemented by means of a radial basis function neural network. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented.

Intelligent system for accident identification in NPP

International Nuclear Information System (INIS)

Hernandez, J.L.

1998-01-01

Accidental situations in NPP are great concern for operators, the facility, regulatory bodies and the environmental. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making 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 Analysis 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 from the combination of the artificial intelligence techniques fuzzy logic and artificial neural networks. The system works with variables from the process of the first 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

Hybrid, plug-in hybrid, or electric—What do car buyers want?

International Nuclear Information System (INIS)

Axsen, Jonn; Kurani, Kenneth S.

2013-01-01

We use a survey to compare consumers’ stated interest in conventional gasoline (CV), hybrid (HEV), plug-in hybrid (PHEV) and pure electric vehicles (EV) of varying designs and prices. Data are from 508 households representing new vehicle buyers in San Diego County, California in 2011. The mixed-mode survey collected information about access to residential recharge infrastructure, three days of driving patterns, and desired vehicle designs and motivations via design games. Across the higher and lower price scenarios, a majority of consumers designed and selected some form of PHEV for their next new vehicle, smaller numbers designed an HEV or a conventional vehicle, and only a few percent designed an EV. Of those who did not design an EV, the most frequent concerns with EVs were limited range, charger availability, and higher vehicle purchase prices. Positive interest in HEVs, PHEVs and EVs was associated with vehicle images of intelligence, responsibility, and support of the environment and nation (United States). The distribution of vehicle designs suggests that cheaper, smaller battery PHEVs may achieve more short-term market success than larger battery PHEVs or EV. New car buyers’ present interests align with less expensive first steps in a transition to electric-drive vehicles. - Highlights: • We assess consumer interest in various electric-drive vehicle designs. • Web-based design games completed by 508 households from San Diego, California. • Plug-in hybrids are most popular, followed by hybrids and conventional vehicles. • Only a few percent opted for a pure electric vehicle. • Electric-drive associated with intelligence, responsibility, and environment

Motivation and emotional intelligence in high school students

Directory of Open Access Journals (Sweden)

José Domínguez-Alonso

2016-11-01

Full Text Available This study explores the motivational and emotional intelligence level of students in Obligatory Secondary Education, and the relationship between the two essential components of an individual's personality. It has worked from a quantitative methodology with a sample of 500 students from public secondary schools, using the questionnaire motivation and learning strategies (CMEA and Spanish version of the Trait goal-Mood Scale (TMMS-24. The results show a good motivational level in all factors with an adequate perception and understanding emotional regulation (intrinsic goals, tasks value, control beliefs, self-efficacy for performance anxiety and extrinsic goals, with an adequate perception, regulation and understanding emotional. In addition, they denote a positive and significant correlation of both, except in the factors that make emotional intelligence, and they are as follows: anxiety, understanding and regulation. In conclusion, both motivation and emotional intelligence are likely to be trained and improved in the field of education, with a capacity to put in place social skills and make the most of each adolescent.

Relationship between emotional intelligence and organizational citizenship behavior.

Science.gov (United States)

Turnipseed, David L; Vandewaa, Elizabeth A

2012-06-01

This study evaluated hypothesized positive linkages between organizational citizenship behavior and the emotional intelligence dimensions of perception, using emotion, understanding emotion, and management of emotion, involving two samples. Sample 1 comprised 334 employed college students, 52% male, with a mean age of 23.4 yr., who worked an average of 29.6 hr. per week. Sample 2 comprised 72 professors, 81% female, with a mean age of 47 yr. Measures were the Emotional Intelligence Scale and the Organizational Citizenship Behavior Scale. Results of hierarchical multiple regressions indicated a positive link between organizational citizenship behavior and emotional intelligence. There were differences between the samples. In Sample 1, each of the emotional intelligence dimensions were positively linked to citizenship behavior: using and managing emotion were the greatest contributors. In Sample 2, managing emotion was the only contributor. Emotional intelligence had the strongest relationship with citizenship behavior directed at individuals.

Optimization of the core configuration design using a hybrid artificial intelligence algorithm for research reactors

International Nuclear Information System (INIS)

Hedayat, Afshin; Davilu, Hadi; Barfrosh, Ahmad Abdollahzadeh; Sepanloo, Kamran

2009-01-01

To successfully carry out material irradiation experiments and radioisotope productions, a high thermal neutron flux at irradiation box over a desired life time of a core configuration is needed. On the other hand, reactor safety and operational constraints must be preserved during core configuration selection. Two main objectives and two safety and operational constraints are suggested to optimize reactor core configuration design. Suggested parameters and conditions are considered as two separate fitness functions composed of two main objectives and two penalty functions. This is a constrained and combinatorial type of a multi-objective optimization problem. In this paper, a fast and effective hybrid artificial intelligence algorithm is introduced and developed to reach a Pareto optimal set. The hybrid algorithm is composed of a fast and elitist multi-objective genetic algorithm (GA) and a fast fitness function evaluating system based on the cascade feed forward artificial neural networks (ANNs). A specific GA representation of core configuration and also special GA operators are introduced and used to overcome the combinatorial constraints of this optimization problem. A software package (Core Pattern Calculator 1) is developed to prepare and reform required data for ANNs training and also to revise the optimization results. Some practical test parameters and conditions are suggested to adjust main parameters of the hybrid algorithm. Results show that introduced ANNs can be trained and estimate selected core parameters of a research reactor very quickly. It improves effectively optimization process. Final optimization results show that a uniform and dense diversity of Pareto fronts are gained over a wide range of fitness function values. To take a more careful selection of Pareto optimal solutions, a revision system is introduced and used. The revision of gained Pareto optimal set is performed by using developed software package. Also some secondary operational

Optimization of the core configuration design using a hybrid artificial intelligence algorithm for research reactors

Energy Technology Data Exchange (ETDEWEB)

Hedayat, Afshin, E-mail: ahedayat@aut.ac.i [Department of Nuclear Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, P.O. Box 15875-4413, Tehran (Iran, Islamic Republic of); Reactor Research and Development School, Nuclear Science and Technology Research Institute (NSTRI), End of North Karegar Street, P.O. Box 14395-836, Tehran (Iran, Islamic Republic of); Davilu, Hadi [Department of Nuclear Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, P.O. Box 15875-4413, Tehran (Iran, Islamic Republic of); Barfrosh, Ahmad Abdollahzadeh [Department of Computer Engineering, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, P.O. Box 15875-4413, Tehran (Iran, Islamic Republic of); Sepanloo, Kamran [Reactor Research and Development School, Nuclear Science and Technology Research Institute (NSTRI), End of North Karegar Street, P.O. Box 14395-836, Tehran (Iran, Islamic Republic of)

2009-12-15

To successfully carry out material irradiation experiments and radioisotope productions, a high thermal neutron flux at irradiation box over a desired life time of a core configuration is needed. On the other hand, reactor safety and operational constraints must be preserved during core configuration selection. Two main objectives and two safety and operational constraints are suggested to optimize reactor core configuration design. Suggested parameters and conditions are considered as two separate fitness functions composed of two main objectives and two penalty functions. This is a constrained and combinatorial type of a multi-objective optimization problem. In this paper, a fast and effective hybrid artificial intelligence algorithm is introduced and developed to reach a Pareto optimal set. The hybrid algorithm is composed of a fast and elitist multi-objective genetic algorithm (GA) and a fast fitness function evaluating system based on the cascade feed forward artificial neural networks (ANNs). A specific GA representation of core configuration and also special GA operators are introduced and used to overcome the combinatorial constraints of this optimization problem. A software package (Core Pattern Calculator 1) is developed to prepare and reform required data for ANNs training and also to revise the optimization results. Some practical test parameters and conditions are suggested to adjust main parameters of the hybrid algorithm. Results show that introduced ANNs can be trained and estimate selected core parameters of a research reactor very quickly. It improves effectively optimization process. Final optimization results show that a uniform and dense diversity of Pareto fronts are gained over a wide range of fitness function values. To take a more careful selection of Pareto optimal solutions, a revision system is introduced and used. The revision of gained Pareto optimal set is performed by using developed software package. Also some secondary operational

Exploring the role of brain oscillations in speech perception in noise: Intelligibility of isochronously retimed speech

Directory of Open Access Journals (Sweden)

Vincent Aubanel

2016-08-01

Full Text Available A growing body of evidence shows that brain oscillations track speech. This mechanism is thought to maximise processing efficiency by allocating resources to important speech information, effectively parsing speech into units of appropriate granularity for further decoding. However, some aspects of this mechanism remain unclear. First, while periodicity is an intrinsic property of this physiological mechanism, speech is only quasi-periodic, so it is not clear whether periodicity would present an advantage in processing. Second, it is still a matter of debate which aspect of speech triggers or maintains cortical entrainment, from bottom-up cues such as fluctuations of the amplitude envelope of speech to higher level linguistic cues such as syntactic structure. We present data from a behavioural experiment assessing the effect of isochronous retiming of speech on speech perception in noise. Two types of anchor points were defined for retiming speech, namely syllable onsets and amplitude envelope peaks. For each anchor point type, retiming was implemented at two hierarchical levels, a slow time scale around 2.5 Hz and a fast time scale around 4 Hz. Results show that while any temporal distortion resulted in reduced speech intelligibility, isochronous speech anchored to P-centers (approximated by stressed syllable vowel onsets was significantly more intelligible than a matched anisochronous retiming, suggesting a facilitative role of periodicity defined on linguistically motivated units in processing speech in noise.

Intelligent System for Diagnosis of a Three-Phase Separator

Directory of Open Access Journals (Sweden)

Irina Ioniţă

2016-03-01

Full Text Available Intelligent systems for diagnosis have been used in a variety of domains: financial evaluation, credit scoring problem, identification of software and hardware problems of mechanical and electronic equipment, medical diagnosis, fault detection in gas-oil production plants etc. The goal of diagnosis systems is to classify the observed symptoms as being caused by some diagnosis class while advising systems perform such a classification and offer corrective remedies (recommendations. The current paper discuss the opportunity to combine more intelligent techniques and methodologies (intelligent agents, data mining and expert systems to increase the accuracy of results obtained from the diagnosis of a three-phase separator. The results indicate that the diagnosis hybrid system benefits from the advantages of each module component: intelligent agent module, data mining module and expert system module.

Measurement of ability emotional intelligence: results for two new tests.

Science.gov (United States)

Austin, Elizabeth J

2010-08-01

Emotional intelligence (EI) has attracted considerable interest amongst both individual differences researchers and those in other areas of psychology who are interested in how EI relates to criteria such as well-being and career success. Both trait (self-report) and ability EI measures have been developed; the focus of this paper is on ability EI. The associations of two new ability EI tests with psychometric intelligence, emotion perception, and the Mayer-Salovey-Caruso EI test (MSCEIT) were examined. The new EI tests were the Situational Test of Emotion Management (STEM) and the Situational Test of Emotional Understanding (STEU). Only the STEU and the MSCEIT Understanding Emotions branch were significantly correlated with psychometric intelligence, suggesting that only understanding emotions can be regarded as a candidate new intelligence component. These understanding emotions tests were also positively correlated with emotion perception tests, and STEM and STEU scores were positively correlated with MSCEIT total score and most branch scores. Neither the STEM nor the STEU were significantly correlated with trait EI tests, confirming the distinctness of trait and ability EI. Taking the present results as a starting-point, approaches to the development of new ability EI tests and models of EI are suggested.

An intelligent hybrid scheme for optimizing parking space: A Tabu metaphor and rough set based approach

Directory of Open Access Journals (Sweden)

Soumya Banerjee

2011-03-01

Full Text Available Congested roads, high traffic, and parking problems are major concerns for any modern city planning. Congestion of on-street spaces in official neighborhoods may give rise to inappropriate parking areas in office and shopping mall complex during the peak time of official transactions. This paper proposes an intelligent and optimized scheme to solve parking space problem for a small city (e.g., Mauritius using a reactive search technique (named as Tabu Search assisted by rough set. Rough set is being used for the extraction of uncertain rules that exist in the databases of parking situations. The inclusion of rough set theory depicts the accuracy and roughness, which are used to characterize uncertainty of the parking lot. Approximation accuracy is employed to depict accuracy of a rough classification [1] according to different dynamic parking scenarios. And as such, the hybrid metaphor proposed comprising of Tabu Search and rough set could provide substantial research directions for other similar hard optimization problems.

The Class Initiatives of Intelligence Rhetoric: Implications of Racism for Scientific Inquiry.

Science.gov (United States)

Hall, Ronald E.

2002-01-01

Asserts that in a society that is not totalitarian, class disparities are enabled institutionally by science. A capital driven nation that associates intelligence with class and race can determine overall quality of life. Thus, perception of intelligence is an extremely powerful tool for reinforcing class. Suggests that in order to be better…

Original article Functioning of memory and attention processes in children with intelligence below average

Directory of Open Access Journals (Sweden)

Aneta Rita Borkowska

2014-05-01

Full Text Available BACKGROUND The aim of the research was to assess memorization and recall of logically connected and unconnected material, coded graphically and linguistically, and the ability to focus attention, in a group of children with intelligence below average, compared to children with average intelligence. PARTICIPANTS AND PROCEDURE The study group included 27 children with intelligence below average. The control group consisted of 29 individuals. All of them were examined using the authors’ experimental trials and the TUS test (Attention and Perceptiveness Test. RESULTS Children with intelligence below average memorized significantly less information contained in the logical material, demonstrated lower ability to memorize the visual material, memorized significantly fewer words in the verbal material learning task, achieved lower results in such indicators of the visual attention process pace as the number of omissions and mistakes, and had a lower pace of perceptual work, compared to children with average intelligence. CONCLUSIONS The results confirm that children with intelligence below average have difficulties with memorizing new material, both logically connected and unconnected. The significantly lower capacity of direct memory is independent of modality. The results of the study on the memory process confirm the hypothesis about lower abilities of children with intelligence below average, in terms of concentration, work pace, efficiency and perception.

Application of artificial intelligence (AI) methods for designing and analysis of reconfigurable cellular manufacturing system (RCMS)

CSIR Research Space (South Africa)

Xing, B

2009-12-01

Full Text Available This work focuses on the design and control of a novel hybrid manufacturing system: Reconfigurable Cellular Manufacturing System (RCMS) by using Artificial Intelligence (AI) approach. It is hybrid as it combines the advantages of Cellular...

EMOTIONAL INTELLIGENCE AND PARENTING STYLES INFLUENCE ON ADOLESCENT GIRLS

OpenAIRE

A V Krasnov

2016-01-01

Foreign psychologists believe that parenting may influence children’s development of emotional intelligence. However, little research has been done in this area. In view of the reviewed literature and given the scarcity of data, we conducted an exploratory study in an as yet unexplored field. The present study aims at examining relationships between the parenting practices and adolescents’ emotional intelligence. 74 students (17-18 years, females) were surveyed to assess their perception of p...

A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

Science.gov (United States)

Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

2016-01-01

Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

Towards Sustainable Smart Homes by a Hierarchical Hybrid Architecture of an Intelligent Agent

Directory of Open Access Journals (Sweden)

K. Yang

2016-10-01

Full Text Available A smart home can be realized by the provision of services, such as building control, automation and security implemented in accordance with a user’s request. One of the important issues is how to respond quickly and appropriately to a user’s request in a “dynamic environment”. An intelligent agent infers the user’s intention and provides the intact service. This paper proposes a smart home agent system based on a hierarchical hybrid architecture of a user intention model, which models the user intention as a hierarchical structure and implements it in a dynamic environment. The conventional rule-based approach needs to obtain all information before it is executed, which requires a large number of rules and is hardly scalable as the control objects are increasing. On the other hand, the proposed system consists of several modules that construct a hierarchical user intention model. The smart home system needs to take account of the information, such as time, state of device and state of the home, in addition to users’ intention. We evaluate the performance of the proposed system in a dynamic environment and conduct a blind test with seven subjects to measure the satisfaction of service, resulting in the average score of 81.46.

Person Perception in Childhood and Adolescence.

Science.gov (United States)

Livesley, W. J.; Bromley, D. B.

The development of person perception or understanding of self and others is the theme of this psychology textbook. An extensive review of research on impression formation is followed by a thorough description of a study of person perception in children. Variables such as age, sex, and intelligence are studied in terms of their relationship to the…

Mobile Intelligent Autonomous Systems

OpenAIRE

Jitendra R. Raol; Ajith Gopal

2010-01-01

Mobile intelligent autonomous systems (MIAS) is a fast emerging research area. Although it can be regarded as a general R&D area, it is mainly directed towards robotics. Several important subtopics within MIAS research are:(i) perception and reasoning, (ii) mobility and navigation,(iii) haptics and teleoperation, (iv) image fusion/computervision, (v) modelling of manipulators, (vi) hardware/software architectures for planning and behaviour learning leadingto robotic architecture, (vii) ve...

Perceptions of Usefulness: Using the Holland Code Theory, Multiple Intelligences Theory, and Role Model Identification to Determine a Career Niche in the Fashion Industry for First-Quarter Fashion Students

Science.gov (United States)

Green, Crystal D.

2010-01-01

This action research study investigated the perceptions that student participants had on the development of a career exploration model and a career exploration project. The Holland code theory was the primary assessment used for this research study, in addition to the Multiple Intelligences theory and the identification of a role model for the…

Emotional intelligence and locus of control of adult patients with ...

African Journals Online (AJOL)

2011-03-15

Mar 15, 2011 ... Keywords: breast cancer, treatment, positive psychology, emotional intelligence, locus of control ... branches are organised in a hierarchy with perception of ..... Asian. Development Bank Knowledge Solutions [serial online].

Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazil

Directory of Open Access Journals (Sweden)

Edison Conde Perez dos Santos

2017-12-01

Full Text Available This study involves an assessment of various artificial intelligence-related techniques which aim to produce a more robust system for sediment transport modeling. The intelligent systems developed in this research are directly applicable to academic knowledge and use data from a report on "water circulation assessment in the “Linguado” Channel and Babitonga Bay ,”Santa Catarina”, Brazil, developed by  Military Engineering Institute (IME. The solution employed for sediment transport was built using an intelligent system from the conception of two hybrid models. The first was a Neuro-Fuzzy (ANFIS hybrid model for the study of hydrodynamic behavior, aiming to determine flow rate in the channel. The second was a fuzzy genetic model, able to assess sediment transport in the “Linguado” Channel. The study's conclusion compares the different effects involved in the dredging equilibrium in the “Linguado” Channel according to this hybrid model with the results obtained using a finite element model in the MIKE21® software.

The intelligent system for accident identification in NPP

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

Event-triggered hybrid control based on multi-Agent systems for Microgrids

DEFF Research Database (Denmark)

Dou, Chun-xia; Liu, Bin; Guerrero, Josep M.

2014-01-01

This paper is focused on a multi-agent system based event-triggered hybrid control for intelligently restructuring the operating mode of an microgrid (MG) to ensure the energy supply with high security, stability and cost effectiveness. Due to the microgrid is composed of different types...... of distributed energy resources, thus it is typical hybrid dynamic network. Considering the complex hybrid behaviors, a hierarchical decentralized coordinated control scheme is firstly constructed based on multi-agent sys-tem, then, the hybrid model of the microgrid is built by using differential hybrid Petri...

Investigation of in-vehicle speech intelligibility metrics for normal hearing and hearing impaired listeners

Science.gov (United States)

Samardzic, Nikolina

The effectiveness of in-vehicle speech communication can be a good indicator of the perception of the overall vehicle quality and customer satisfaction. Currently available speech intelligibility metrics do not account in their procedures for essential parameters needed for a complete and accurate evaluation of in-vehicle speech intelligibility. These include the directivity and the distance of the talker with respect to the listener, binaural listening, hearing profile of the listener, vocal effort, and multisensory hearing. In the first part of this research the effectiveness of in-vehicle application of these metrics is investigated in a series of studies to reveal their shortcomings, including a wide range of scores resulting from each of the metrics for a given measurement configuration and vehicle operating condition. In addition, the nature of a possible correlation between the scores obtained from each metric is unknown. The metrics and the subjective perception of speech intelligibility using, for example, the same speech material have not been compared in literature. As a result, in the second part of this research, an alternative method for speech intelligibility evaluation is proposed for use in the automotive industry by utilizing a virtual reality driving environment for ultimately setting targets, including the associated statistical variability, for future in-vehicle speech intelligibility evaluation. The Speech Intelligibility Index (SII) was evaluated at the sentence Speech Receptions Threshold (sSRT) for various listening situations and hearing profiles using acoustic perception jury testing and a variety of talker and listener configurations and background noise. In addition, the effect of individual sources and transfer paths of sound in an operating vehicle to the vehicle interior sound, specifically their effect on speech intelligibility was quantified, in the framework of the newly developed speech intelligibility evaluation method. Lastly

Modelling the Interaction Levels in HCI Using an Intelligent Hybrid System with Interactive Agents: A Case Study of an Interactive Museum Exhibition Module in Mexico

Directory of Open Access Journals (Sweden)

Ricardo Rosales

2018-03-01

Full Text Available Technology has become a necessity in our everyday lives and essential for completing activities we typically take for granted; technologies can assist us by completing set tasks or achieving desired goals with optimal affect and in the most efficient way, thereby improving our interactive experiences. This paper presents research that explores the representation of user interaction levels using an intelligent hybrid system approach with agents. We evaluate interaction levels of Human-Computer Interaction (HCI with the aim of enhancing user experiences. We consider the description of interaction levels using an intelligent hybrid system to provide a decision-making system to an agent that evaluates interaction levels when using interactive modules of a museum exhibition. The agents represent a high-level abstraction of the system, where communication takes place between the user, the exhibition and the environment. In this paper, we provide a means to measure the interaction levels and natural behaviour of users, based on museum user-exhibition interaction. We consider that, by analysing user interaction in a museum, we can help to design better ways to interact with exhibition modules according to the properties and behaviour of the users. An interaction-evaluator agent is proposed to achieve the most suitable representation of the interaction levels with the aim of improving user interactions to offer the most appropriate directions, services, content and information, thereby improving the quality of interaction experienced between the user-agent and exhibition-agent.

Advances in Reasoning-Based Image Processing Intelligent Systems Conventional and Intelligent Paradigms

CERN Document Server

Nakamatsu, Kazumi

2012-01-01

The book puts special stress on the contemporary techniques for reasoning-based image processing and analysis: learning based image representation and advanced video coding; intelligent image processing and analysis in medical vision systems; similarity learning models for image reconstruction; visual perception for mobile robot motion control, simulation of human brain activity in the analysis of video sequences; shape-based invariant features extraction; essential of paraconsistent neural networks, creativity and intelligent representation in computational systems. The book comprises 14 chapters. Each chapter is a small monograph, representing resent investigations of authors in the area. The topics of the chapters cover wide scientific and application areas and complement each-other very well. The chapters’ content is based on fundamental theoretical presentations, followed by experimental results and comparison with similar techniques. The size of the chapters is well-ballanced which permits a thorough ...

A MURI Center for Intelligent Biomimetic Image Processing and Classification

Science.gov (United States)

2007-11-01

times, labeled "plage" or "open space" or "natural", the system learns to associate multiple classes with a given input. Testbed image examples have shown...brain color perception and category learning. Commentary on "Coordinating perceptually grounded categories through language " by Luc Steels and Tony...Symposium on Computational Intelligence (ISCI), Kosice, Slovakia, June 2002. 9. Carpenter, G.A., Award from the Slovak Artificial Intelligence Society, 2002

Hybrid Taguchi DNA Swarm Intelligence for Optimal Inverse Kinematics Redundancy Resolution of Six-DOF Humanoid Robot Arms

Directory of Open Access Journals (Sweden)

Hsu-Chih Huang

2014-01-01

Full Text Available This paper presents a hybrid Taguchi deoxyribonucleic acid (DNA swarm intelligence for solving the inverse kinematics redundancy problem of six degree-of-freedom (DOF humanoid robot arms. The inverse kinematics problem of the multi-DOF humanoid robot arm is redundant and has no general closed-form solutions or analytical solutions. The optimal joint configurations are obtained by minimizing the predefined performance index in DNA algorithm for real-world humanoid robotics application. The Taguchi method is employed to determine the DNA parameters to search for the joint solutions of the six-DOF robot arms more efficiently. This approach circumvents the disadvantage of time-consuming tuning procedure in conventional DNA computing. Simulation results are conducted to illustrate the effectiveness and merit of the proposed methods. This Taguchi-based DNA (TDNA solver outperforms the conventional solvers, such as geometric solver, Jacobian-based solver, genetic algorithm (GA solver and ant, colony optimization (ACO solver.

Trait Emotional Intelligence and the Big Five: A Study on Italian Children and Preadolescents

Science.gov (United States)

Russo, Paolo Maria; Mancini, Giacomo; Trombini, Elena; Baldaro, Bruno; Mavroveli, Stella; Petrides, K. V.

2012-01-01

Trait emotional intelligence (EI) is a constellation of emotion-related self-perceptions located at the lower levels of personality hierarchies. This article examines the validity of the Trait Emotional Intelligence Questionnaire-Child Form and investigates its relationships with Big Five factors and cognitive ability. A total of 690 children (317…

Intelligent System Design Using Hyper-Heuristics

Directory of Open Access Journals (Sweden)

Nelishia Pillay

2015-07-01

Full Text Available Determining the most appropriate search method or artificial intelligence technique to solve a problem is not always evident and usually requires implementation of the different approaches to ascertain this. In some instances a single approach may not be sufficient and hybridization of methods may be needed to find a solution. This process can be time consuming. The paper proposes the use of hyper-heuristics as a means of identifying which method or combination of approaches is needed to solve a problem. The research presented forms part of a larger initiative aimed at using hyper-heuristics to develop intelligent hybrid systems. As an initial step in this direction, this paper investigates this for classical artificial intelligence uninformed and informed search methods, namely depth first search, breadth first search, best first search, hill-climbing and the A* algorithm. The hyper-heuristic determines the search or combination of searches to use to solve the problem. An evolutionary algorithm hyper-heuristic is implemented for this purpose and its performance is evaluated in solving the 8-Puzzle, Towers of Hanoi and Blocks World problems. The hyper-heuristic employs a generational evolutionary algorithm which iteratively refines an initial population using tournament selection to select parents, which the mutation and crossover operators are applied to for regeneration. The hyper-heuristic was able to identify a search or combination of searches to produce solutions for the twenty 8-Puzzle, five Towers of Hanoi and five Blocks World problems. Furthermore, admissible solutions were produced for all problem instances.

Disturbance observer-based adaptive sliding mode hybrid projective ...

Indian Academy of Sciences (India)

Ayub Khan

2018-04-21

Apr 21, 2018 ... systems, the effect of external disturbances, energy fluc- tuation and other such ...... When we apply the above proposed strategy to achieve hybrid projective ..... ory and intelligent control (Springer, 2016) pp. 681–. 697.

Students’ perceptions and satisfaction level of hybrid problem-based learning for 16 years in Kyungpook National University School of Medicine, Korea

Directory of Open Access Journals (Sweden)

Sanghee Yeo

2016-03-01

Full Text Available Purpose: Kyungpook National University School of Medicine has been implementing hybrid problem-based learning (PBL since 1999. The aim of this study was to investigate the changes in the students’ perceptions and satisfaction levels of hybrid PBL. Methods: The target period of our study was from 1999 to 2014, and target subjects were second-year medical students in Kyungpook National University School of Medicine. The survey was conducted at the end of semester. We had a focused interview with group leaders and some volunteer students. Results: As for the scores regarding students’ overall satisfaction with PBL, there was significant improvement in 2005 compared to 2002, but the scores decreased and no differences between the survey years noted after 2005. The students’ preference ratio for the once a week PBL sessions, tutor presence, synchronization of contents, and arrangement of PBL sessions and related lectures was 60%–80%, 50%–90%, 52%–96%, and 78%–93%, respectively. Conclusion: In order to increase students’ satisfaction with hybrid PBL and to improve the perception of it, firstly, it is necessary to arrange the date and the time of PBL sessions so that students can concentrate on PBL. Secondly, PBL cases should be selected and arranged to be well synchronized with the ongoing lectures. Finally, it is important to create a safe atmosphere so that students can engage actively in PBL sessions.

Perception of Students' Intelligence Malleability and Potential for Future Success: Unfavourable Beliefs towards Girls

Science.gov (United States)

Verniers, Catherine; Martinot, Delphine

2015-01-01

Background: Endorsing an entity theory of intelligence has negative effects on students' academic trajectories. Research focused on students' personal theories of intelligence has shown that girls are more likely than boys to hold an entity theory of intelligence. However, no study has examined the possibility of a gender stereotype basis for this…

A functional look at goal orientations : their role for self-estimates of intelligence and performance

NARCIS (Netherlands)

Bipp, T.; Steinmayr, R.; Spinath, B.

2012-01-01

Building on the notion that motivation energizes and directs resources in achievement situations, we argue that goal orientations affect perceptions of own intelligence and that the effect of goals on performance is partly mediated by self-estimates of intelligence. Studies 1 (n = 89) and 2 (n =

What Predicts Children's Fixed and Growth Intelligence Mind-Sets? Not Their Parents' Views of Intelligence but Their Parents' Views of Failure.

Science.gov (United States)

Haimovitz, Kyla; Dweck, Carol S

2016-06-01

Children's intelligence mind-sets (i.e., their beliefs about whether intelligence is fixed or malleable) robustly influence their motivation and learning. Yet, surprisingly, research has not linked parents' intelligence mind-sets to their children's. We tested the hypothesis that a different belief of parents-their failure mind-sets-may be more visible to children and therefore more prominent in shaping their beliefs. In Study 1, we found that parents can view failure as debilitating or enhancing, and that these failure mind-sets predict parenting practices and, in turn, children's intelligence mind-sets. Study 2 probed more deeply into how parents display failure mind-sets. In Study 3a, we found that children can indeed accurately perceive their parents' failure mind-sets but not their parents' intelligence mind-sets. Study 3b showed that children's perceptions of their parents' failure mind-sets also predicted their own intelligence mind-sets. Finally, Study 4 showed a causal effect of parents' failure mind-sets on their responses to their children's hypothetical failure. Overall, parents who see failure as debilitating focus on their children's performance and ability rather than on their children's learning, and their children, in turn, tend to believe that intelligence is fixed rather than malleable. © The Author(s) 2016.

Perception, Action, and Consciousness

DEFF Research Database (Denmark)

What is the relationship between perception and action, between an organism and its environment, in explaining consciousness? These are issues at the heart of philosophy of mind and the cognitive sciences. This book explores the relationship between perception and action from a variety of interdi......What is the relationship between perception and action, between an organism and its environment, in explaining consciousness? These are issues at the heart of philosophy of mind and the cognitive sciences. This book explores the relationship between perception and action from a variety...... of interdisciplinary perspectives, ranging from theoretical discussion of concepts to findings from recent scientific studies. It incorporates contributions from leading philosophers, psychologists, neuroscientists, and an artificial intelligence theorist. The contributions take a range of positions with respect...

A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals.

Science.gov (United States)

Castañón-Puga, Manuel; Salazar, Abby Stephanie; Aguilar, Leocundo; Gaxiola-Pacheco, Carelia; Licea, Guillermo

2015-12-02

The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs). This approach takes advantage of wireless local area networks (WLANs) over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi-Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information.

A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals

Directory of Open Access Journals (Sweden)

Manuel Castañón–Puga

2015-12-01

Full Text Available The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs. This approach takes advantage of wireless local area networks (WLANs over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi–Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information.

Hybrid Disease Diagnosis Using Multiobjective Optimization with Evolutionary Parameter Optimization

Directory of Open Access Journals (Sweden)

MadhuSudana Rao Nalluri

2017-01-01

Full Text Available With the widespread adoption of e-Healthcare and telemedicine applications, accurate, intelligent disease diagnosis systems have been profoundly coveted. In recent years, numerous individual machine learning-based classifiers have been proposed and tested, and the fact that a single classifier cannot effectively classify and diagnose all diseases has been almost accorded with. This has seen a number of recent research attempts to arrive at a consensus using ensemble classification techniques. In this paper, a hybrid system is proposed to diagnose ailments using optimizing individual classifier parameters for two classifier techniques, namely, support vector machine (SVM and multilayer perceptron (MLP technique. We employ three recent evolutionary algorithms to optimize the parameters of the classifiers above, leading to six alternative hybrid disease diagnosis systems, also referred to as hybrid intelligent systems (HISs. Multiple objectives, namely, prediction accuracy, sensitivity, and specificity, have been considered to assess the efficacy of the proposed hybrid systems with existing ones. The proposed model is evaluated on 11 benchmark datasets, and the obtained results demonstrate that our proposed hybrid diagnosis systems perform better in terms of disease prediction accuracy, sensitivity, and specificity. Pertinent statistical tests were carried out to substantiate the efficacy of the obtained results.

Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

Directory of Open Access Journals (Sweden)

Montri Inthachot

2016-01-01

Full Text Available This study investigated the use of Artificial Neural Network (ANN and Genetic Algorithm (GA for prediction of Thailand’s SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid’s prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span.

A Proposed Business Intelligent Framework for Recommender Systems

Directory of Open Access Journals (Sweden)

Sitalakshmi Venkatraman

2017-11-01

Full Text Available In this Internet age, recommender systems (RS have become popular, offering new opportunities and challenges to the business world. With a continuous increase in global competition, e-businesses, information portals, social networks and more, websites are required to become more user-centric and rely on the presence and role of RS in assisting users in better decision making. However, with continuous changes in user interests and consumer behavior patterns that are influenced by easy access to vast information and social factors, raising the quality of recommendations has become a challenge for recommender systems. There is a pressing need for exploring hybrid models of the five main types of RS, namely collaborative, demographic, utility, content and knowledge based approaches along with advancements in Big Data (BD to become more context-aware of the technology and social changes and to behave intelligently. There is a gap in literature with a research focus in this direction. This paper takes a step to address this by exploring a new paradigm of applying business intelligence (BI concepts to RS for intelligently responding to user changes and business complexities. A BI based framework adopting a hybrid methodology for RS is proposed with a focus on enhancing the RS performance. Such a business intelligent recommender system (BIRS can adopt On-line Analytical Processing (OLAP tools and performance monitoring metrics using data mining techniques of BI to enhance its own learning, user profiling and predictive models for making a more useful set of personalised recommendations to its users. The application of the proposed framework to a B2C e-commerce case example is presented.

The Role of Emotional Intelligence in Entrepreneurs' Perceptions of Success : An Exploratory Study

NARCIS (Netherlands)

Shah-Zhou, Haibo; Maria Bojica, Ana

2017-01-01

This study contributes to the entrepreneurship literature by introducing emotional intelligence (EI) as an additional factor that explains how entrepreneurs perceive their own success. Using survey data from a sample of Dutch entrepreneurs, we find that emotionally intelligent entrepreneurs are more

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

4th Workshop on Combinations of Intelligent Methods and Applications

CERN Document Server

Palade, Vasile; Prentzas, Jim

2016-01-01

This volume includes extended and revised versions of the papers presented at the 4th Workshop on “Combinations of Intelligent Methods and Applications” (CIMA 2014) which was intended to become a forum for exchanging experience and ideas among researchers and practitioners dealing with combinations of different intelligent methods in Artificial Intelligence. The aim is to create integrated or hybrid methods that benefit from each of their components. Some of the existing presented efforts combine soft computing methods (fuzzy logic, neural networks and genetic algorithms). Another stream of efforts integrates case-based reasoning or machine learning with soft-computing methods. Some of the combinations have been more widely explored, like neuro-symbolic methods, neuro-fuzzy methods and methods combining rule-based and case-based reasoning. CIMA 2014 was held in conjunction with the 26th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2014). .

Basic research on intelligent robotic systems operating in hostile environments: New developments at ORNL

International Nuclear Information System (INIS)

Barhen, J.; Babcock, S.M.; Hamel, W.R.; Oblow, E.M.; Saridis, G.N.; deSaussure, G.; Solomon, A.D.; Weisbin, C.R.

1984-01-01

Robotics and artificial intelligence research carried out within the Center for Engineering Systems Advanced Research (CESAR) is presented. Activities focus on the development and demonstration of a comprehensive methodological framework for intelligent machines operating in unstructured hostile environments. Areas currently being addressed include mathematical modeling of robot dynamics, real-time control, ''world'' modeling, machine perception and strategy planning

Hospital-based nurses' perceptions of the adoption of Web 2.0 tools for knowledge sharing, learning, social interaction and the production of collective intelligence.

Science.gov (United States)

Lau, Adela S M

2011-11-11

Web 2.0 provides a platform or a set of tools such as blogs, wikis, really simple syndication (RSS), podcasts, tags, social bookmarks, and social networking software for knowledge sharing, learning, social interaction, and the production of collective intelligence in a virtual environment. Web 2.0 is also becoming increasingly popular in e-learning and e-social communities. The objectives were to investigate how Web 2.0 tools can be applied for knowledge sharing, learning, social interaction, and the production of collective intelligence in the nursing domain and to investigate what behavioral perceptions are involved in the adoption of Web 2.0 tools by nurses. The decomposed technology acceptance model was applied to construct the research model on which the hypotheses were based. A questionnaire was developed based on the model and data from nurses (n = 388) were collected from late January 2009 until April 30, 2009. Pearson's correlation analysis and t tests were used for data analysis. Intention toward using Web 2.0 tools was positively correlated with usage behavior (r = .60, P Web 2.0 tools and enable them to better plan the strategy of implementation of Web 2.0 tools for knowledge sharing, learning, social interaction, and the production of collective intelligence.

Hospital-Based Nurses’ Perceptions of the Adoption of Web 2.0 Tools for Knowledge Sharing, Learning, Social Interaction and the Production of Collective Intelligence

Science.gov (United States)

2011-01-01

Background Web 2.0 provides a platform or a set of tools such as blogs, wikis, really simple syndication (RSS), podcasts, tags, social bookmarks, and social networking software for knowledge sharing, learning, social interaction, and the production of collective intelligence in a virtual environment. Web 2.0 is also becoming increasingly popular in e-learning and e-social communities. Objectives The objectives were to investigate how Web 2.0 tools can be applied for knowledge sharing, learning, social interaction, and the production of collective intelligence in the nursing domain and to investigate what behavioral perceptions are involved in the adoption of Web 2.0 tools by nurses. Methods The decomposed technology acceptance model was applied to construct the research model on which the hypotheses were based. A questionnaire was developed based on the model and data from nurses (n = 388) were collected from late January 2009 until April 30, 2009. Pearson’s correlation analysis and t tests were used for data analysis. Results Intention toward using Web 2.0 tools was positively correlated with usage behavior (r = .60, P Web 2.0 tools and enable them to better plan the strategy of implementation of Web 2.0 tools for knowledge sharing, learning, social interaction, and the production of collective intelligence. PMID:22079851

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

Science.gov (United States)

Moore, Gwendolyn B.; And Others

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

EMOTIONAL INTELLIGENCE AND PARENTING STYLES INFLUENCE ON ADOLESCENT GIRLS

Directory of Open Access Journals (Sweden)

A V Krasnov

2016-12-01

Full Text Available Foreign psychologists believe that parenting may influence children’s development of emotional intelligence. However, little research has been done in this area. In view of the reviewed literature and given the scarcity of data, we conducted an exploratory study in an as yet unexplored field. The present study aims at examining relationships between the parenting practices and adolescents’ emotional intelligence. 74 students (17-18 years, females were surveyed to assess their perception of parenting styles and their own emotional intelligence. Spearman’s rank correlation coefficients showed that adolescents’ emotional intelligence correlated with one of maternal parenting styles (positive attitude and four of paternal parenting styles (positive attitude, directivity, autonomy, incoherence. Positive interest of parents positively correlated with adolescents’ ability for understanding their own emotions. Paternal positive interest positively correlated with adolescents’ ability for managing their own emotions and emotional intelligence. Paternal directivity positively correlated with adolescents’ ability for understanding emotions (their own and other people’s. Paternal autonomy negatively correlated with adolescents’ emotional intelligence and ability for understanding other people’s emotions. Paternalincoherence negatively correlated with adolescents’ ability for understanding and managing their own emotions.

Hybrid Swarm Intelligence Energy Efficient Clustered Routing Algorithm for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Rajeev Kumar

2016-01-01

Full Text Available Currently, wireless sensor networks (WSNs are used in many applications, namely, environment monitoring, disaster management, industrial automation, and medical electronics. Sensor nodes carry many limitations like low battery life, small memory space, and limited computing capability. To create a wireless sensor network more energy efficient, swarm intelligence technique has been applied to resolve many optimization issues in WSNs. In many existing clustering techniques an artificial bee colony (ABC algorithm is utilized to collect information from the field periodically. Nevertheless, in the event based applications, an ant colony optimization (ACO is a good solution to enhance the network lifespan. In this paper, we combine both algorithms (i.e., ABC and ACO and propose a new hybrid ABCACO algorithm to solve a Nondeterministic Polynomial (NP hard and finite problem of WSNs. ABCACO algorithm is divided into three main parts: (i selection of optimal number of subregions and further subregion parts, (ii cluster head selection using ABC algorithm, and (iii efficient data transmission using ACO algorithm. We use a hierarchical clustering technique for data transmission; the data is transmitted from member nodes to the subcluster heads and then from subcluster heads to the elected cluster heads based on some threshold value. Cluster heads use an ACO algorithm to discover the best route for data transmission to the base station (BS. The proposed approach is very useful in designing the framework for forest fire detection and monitoring. The simulation results show that the ABCACO algorithm enhances the stability period by 60% and also improves the goodput by 31% against LEACH and WSNCABC, respectively.

Key performance indicators (KPIs) and priority setting in using the multi-attribute approach for assessing sustainable intelligent buildings

Energy Technology Data Exchange (ETDEWEB)

ALwaer, H. [The University of Dundee, School of Architecture, Matthew Building, 13 Perth Road, Dundee DD1 4HT (United Kingdom); Clements-Croome, D.J. [School of Construction Management and Engineering, The University of Reading, Whiteknights, PO Box 219, Reading RG6 6AW (United Kingdom)

2010-04-15

The main objectives of this paper are to: firstly, identify key issues related to sustainable intelligent buildings (environmental, social, economic and technological factors); develop a conceptual model for the selection of the appropriate KPIs; secondly, test critically stakeholder's perceptions and values of selected KPIs intelligent buildings; and thirdly develop a new model for measuring the level of sustainability for sustainable intelligent buildings. This paper uses a consensus-based model (Sustainable Built Environment Tool- SuBETool), which is analysed using the analytical hierarchical process (AHP) for multi-criteria decision-making. The use of the multi-attribute model for priority setting in the sustainability assessment of intelligent buildings is introduced. The paper commences by reviewing the literature on sustainable intelligent buildings research and presents a pilot-study investigating the problems of complexity and subjectivity. This study is based upon a survey perceptions held by selected stakeholders and the value they attribute to selected KPIs. It is argued that the benefit of the new proposed model (SuBETool) is a 'tool' for 'comparative' rather than an absolute measurement. It has the potential to provide useful lessons from current sustainability assessment methods for strategic future of sustainable intelligent buildings in order to improve a building's performance and to deliver objective outcomes. Findings of this survey enrich the field of intelligent buildings in two ways. Firstly, it gives a detailed insight into the selection of sustainable building indicators, as well as their degree of importance. Secondly, it tesst critically stakeholder's perceptions and values of selected KPIs intelligent buildings. It is concluded that the priority levels for selected criteria is largely dependent on the integrated design team, which includes the client, architects, engineers and facilities managers

A new type of hybrid vehicle in Japan; Un nouveau type de vehicule hybride au Japon

Energy Technology Data Exchange (ETDEWEB)

Henry, P.

2004-04-01

During the 37. edition of the Tokyo Motor Show in October 2003, several fuel cell hybrid vehicles were presented by Japanese car makers who grant considerable budgets to develop less polluting vehicles. The trend chosen by Japanese car manufacturers concerns the hybrid system combining fuel cell and battery. Stress has been put also on intelligent systems for navigation and safety but also on the design and comfort. However, even if the environment protection is the main challenge of the Japanese automotive industry, the driving pleasure remains the most profitable medium-term market to be exploitable by industrialists. (J.S.)

13th International Conference Intelligent Autonomous Systems

CERN Document Server

Michael, Nathan; Berns, Karsten; Yamaguchi, Hiroaki

2016-01-01

This book describes the latest research accomplishments, innovations, and visions in the field of robotics as presented at the 13th International Conference on Intelligent Autonomous Systems (IAS), held in Padua in July 2014, by leading researchers, engineers, and practitioners from across the world. The contents amply confirm that robots, machines, and systems are rapidly achieving intelligence and autonomy, mastering more and more capabilities such as mobility and manipulation, sensing and perception, reasoning, and decision making. A wide range of research results and applications are covered, and particular attention is paid to the emerging role of autonomous robots and intelligent systems in industrial production, which reflects their maturity and robustness. The contributions have been selected through a rigorous peer-review process and contain many exciting and visionary ideas that will further galvanize the research community, spurring novel research directions. The series of biennial IAS conferences ...

The role of spiritual intelligence in employees’ withdrawal behaviors in physical education organization

Directory of Open Access Journals (Sweden)

Davoud Noroozi

2015-03-01

Full Text Available Spiritual intelligence is the mind’s capacity to handle substantial and spiritual aspects of life. According to previous studies, spiritual intelligence can be effective in reducing the withdrawal behavior of employees. This study investigated the effect of spiritual intelligence on employees’ withdrawal behavior in Ardabil Physical Education organization. The statistical population of this study included all the employees of Physical Education organization of Ardabil (N=60. Descriptive Statistics, Pearson Correlation, and Linear Regression Analyses were used to assess the association between spiritual intelligence and withdrawal behaviors. The results of the study revealed that spiritual intelligence had positive and significant effect on reducing employees’ withdrawal behavior. The findings supported that spiritual intelligence training as a new psychological and religious construction may reduce psychological and physical withdrawal behaviors and improve the employees’ perception of themselves.

Artificial intelligence and finite element modelling for monitoring flood defence structures

NARCIS (Netherlands)

Pyayt, A.L.; Mokhov, I.I.; Kozionov, A.; Kusherbaeva, V.; Melnikova, N.B.; Krzhizhanovskaya, V.V.; Meijer, R.J.

2011-01-01

We present a hybrid approach to monitoring the stability of flood defence structures equipped with sensors. This approach combines the finite element modelling with the artificial intelligence for real-time signal processing and anomaly detection. This combined method has been developed for the

Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review

International Nuclear Information System (INIS)

Laghari, J.A.; Mokhlis, H.; Karimi, M.; Bakar, A.H.A.; Mohamad, Hasmaini

2014-01-01

Highlights: • Unintentional and intentional islanding, their causes, and solutions are presented. • Remote, passive, active and hybrid islanding detection techniques are discussed. • The limitation of these techniques in accurately detect islanding are discussed. • Computational intelligence techniques ability in detecting islanding is discussed. • Review of ANN, fuzzy logic control, ANFIS, Decision tree techniques is provided. - Abstract: Accurate and fast islanding detection of distributed generation is highly important for its successful operation in distribution networks. Up to now, various islanding detection technique based on communication, passive, active and hybrid methods have been proposed. However, each technique suffers from certain demerits that cause inaccuracies in islanding detection. Computational intelligence based techniques, due to their robustness and flexibility in dealing with complex nonlinear systems, is an option that might solve this problem. This paper aims to provide a comprehensive review of computational intelligence based techniques applied for islanding detection of distributed generation. Moreover, the paper compares the accuracies of computational intelligence based techniques over existing techniques to provide a handful of information for industries and utility researchers to determine the best method for their respective system

Duo: A Human/Wearable Hybrid for Learning About Common Manipulate Objects

National Research Council Canada - National Science Library

Kemp, Charles C

2002-01-01

... with them. Duo is a human/wearable hybrid that is designed to learn about this important domain of human intelligence by interacting with natural manipulable objects in unconstrained environments...

Intelligent optimization to integrate a plug-in hybrid electric vehicle smart parking lot with renewable energy resources and enhance grid characteristics

International Nuclear Information System (INIS)

Fazelpour, Farivar; Vafaeipour, Majid; Rahbari, Omid; Rosen, Marc A.

2014-01-01

Highlights: • The proposed algorithms handled design steps of an efficient parking lot of PHEVs. • Optimizations are performed with 1 h intervals to find optimum charging rates. • Multi-objective optimization is performed to find the optimum size and site of DG. • Optimal sizing of a PV–wind–diesel HRES is attained. • Charging rates are optimized intelligently during peak and off-peak times. - Abstract: Widespread application of plug-in hybrid electric vehicles (PHEVs) as an important part of smart grids requires drivers and power grid constraints to be satisfied simultaneously. We address these two challenges with the presence of renewable energy and charging rate optimization in the current paper. First optimal sizing and siting for installation of a distributed generation (DG) system is performed through the grid considering power loss minimization and voltage enhancement. Due to its benefits, the obtained optimum site is considered as the optimum location for constructing a movie theater complex equipped with a PHEV parking lot. To satisfy the obtained size of DG, an on-grid hybrid renewable energy system (HRES) is chosen. In the next set of optimizations, optimal sizing of the HRES is performed to minimize the energy cost and to find the best number of decision variables, which are the number of the system’s components. Eventually, considering demand uncertainties due to the unpredictability of the arrival and departure times of the vehicles, time-dependent charging rate optimizations of the PHEVs are performed in 1 h intervals for the 24-h of a day. All optimization problems are performed using genetic algorithms (GAs). The outcome of the proposed optimization sets can be considered as design steps of an efficient grid-friendly parking lot of PHEVs. The results indicate a reduction in real power losses and improvement in the voltage profile through the distribution line. They also show the competence of the utilized energy delivery method in

Body, thought, being-human and artificial intelligence: Merleau ...

African Journals Online (AJOL)

The focus then shifts to Merleau-Ponty in order to demonstrate the remarkable extent to which his understanding of human embodiment and related issues such as perception and creativity, paved the way for the work of, among others, Lyotard, and anticipated the critique of artificial intelligence on the part of the latter.

Intelligence Level Performance Standards Research for Autonomous Vehicles.

Science.gov (United States)

Bostelman, Roger B; Hong, Tsai H; Messina, Elena

2015-01-01

United States and European safety standards have evolved to protect workers near Automatic Guided Vehicles (AGV's). However, performance standards for AGV's and mobile robots have only recently begun development. Lessons can be learned from research and standards efforts for mobile robots applied to emergency response and military applications. Research challenges, tests and evaluations, and programs to develop higher intelligence levels for vehicles can also used to guide industrial AGV developments towards more adaptable and intelligent systems. These other efforts also provide useful standards development criteria for AGV performance test methods. Current standards areas being considered for AGVs are for docking, navigation, obstacle avoidance, and the ground truth systems that measure performance. This paper provides a look to the future with standards developments in both the performance of vehicles and the dynamic perception systems that measure intelligent vehicle performance.

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

1st International Conference on Advanced Intelligent System and Informatics

CERN Document Server

Hassanien, Aboul; El-Bendary, Nashwa; Dey, Nilanjan

2016-01-01

The conference topics address different theoretical and practical aspects, and implementing solutions for intelligent systems and informatics disciplines including bioinformatics, computer science, medical informatics, biology, social studies, as well as robotics research. The conference also discuss and present solutions to the cloud computing and big data mining which are considered hot research topics. The conference papers discussed different topics – techniques, models, methods, architectures, as well as multi aspect, domain-specific, and new solutions for the above disciplines. The accepted papers have been grouped into five parts: Part I—Intelligent Systems and Informatics, addressing topics including, but not limited to, medical application, predicting student performance, action classification, and detection of dead stained microscopic cells, optical character recognition, plant identification, rehabilitation of disabled people. Part II—Hybrid Intelligent Systems, addressing topics including, b...

The role of Trait Emotional Intelligence and social and emotional skills in students’ emotional and behavioural strengths and difficulties: A study of Greek adolescents’ perceptions.

Directory of Open Access Journals (Sweden)

Maria S. Poulou

2010-11-01

Full Text Available The emergence of the Trait Emotional Intelligence construct shifted the interest in personality research to the investigation of the effect of global personality characteristics on behaviour. A second body of research in applied settings, the Social and Emotional Learning movement, emphasized the cultivation of emotional and social skills for positive relationships in a school environment. In this paper we investigate the role of both personality traits and social and emotional skills, in the occurrence of emotional and behavioural strengths and difficulties, according to adolescent students’ self-perceptions. Five hundred and fifty-nine students from state secondary schools in Greece, aged 12-14 years old, completed The Trait Emotional Intelligence Questionnaire-Adolescent Short Form, The Matson Evaluation of Social Skills with Youngsters, and The Strengths and Difficulties Questionnaire. It was found that students with higher Trait Emotional Intelligence and stronger social and emotional skills were less likely to present emotional, conduct, hyperactivity and peer difficulties and more likely to present prosocial behaviour. Gender was a significant factor for emotional difficulties and grade for peer difficulties. The paper describes the underlying mechanisms of students’ emotional and behavioural strengths and difficulties, and provides practical implications for educators to improve the quality of students’ lives in schools.

3Es System Optimization under Uncertainty Using Hybrid Intelligent Algorithm: A Fuzzy Chance-Constrained Programming Model

Directory of Open Access Journals (Sweden)

Jiekun Song

2016-01-01

Full Text Available Harmonious development of 3Es (economy-energy-environment system is the key to realize regional sustainable development. The structure and components of 3Es system are analyzed. Based on the analysis of causality diagram, GDP and industrial structure are selected as the target parameters of economy subsystem, energy consumption intensity is selected as the target parameter of energy subsystem, and the emissions of COD, ammonia nitrogen, SO2, and NOX and CO2 emission intensity are selected as the target parameters of environment system. Fixed assets investment of three industries, total energy consumption, and investment in environmental pollution control are selected as the decision variables. By regarding the parameters of 3Es system optimization as fuzzy numbers, a fuzzy chance-constrained goal programming (FCCGP model is constructed, and a hybrid intelligent algorithm including fuzzy simulation and genetic algorithm is proposed for solving it. The results of empirical analysis on Shandong province of China show that the FCCGP model can reflect the inherent relationship and evolution law of 3Es system and provide the effective decision-making support for 3Es system optimization.

The Influence of Social Intelligence on Effective Music Teaching

Science.gov (United States)

Juchniewicz, Jay

2010-01-01

The purpose of this study was to investigate the influence of social intelligence on effective music teaching. Forty teachers from "exemplary programs" and "more challenging programs" across band, chorus, orchestra, and general public school music programs were administered the Interpersonal Perception Task-15 (IPT-15). In addition, 84 external…

Intelligent model-based diagnostics for vehicle health management

Science.gov (United States)

Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

2003-08-01

The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

Beam-column joint shear prediction using hybridized deep learning neural network with genetic algorithm

Science.gov (United States)

Mundher Yaseen, Zaher; Abdulmohsin Afan, Haitham; Tran, Minh-Tung

2018-04-01

Scientifically evidenced that beam-column joints are a critical point in the reinforced concrete (RC) structure under the fluctuation loads effects. In this novel hybrid data-intelligence model developed to predict the joint shear behavior of exterior beam-column structure frame. The hybrid data-intelligence model is called genetic algorithm integrated with deep learning neural network model (GA-DLNN). The genetic algorithm is used as prior modelling phase for the input approximation whereas the DLNN predictive model is used for the prediction phase. To demonstrate this structural problem, experimental data is collected from the literature that defined the dimensional and specimens’ properties. The attained findings evidenced the efficitveness of the hybrid GA-DLNN in modelling beam-column joint shear problem. In addition, the accurate prediction achived with less input variables owing to the feasibility of the evolutionary phase.

Maze learning by a hybrid brain-computer system.

Science.gov (United States)

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-13

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Maze learning by a hybrid brain-computer system

Science.gov (United States)

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-01

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Design and realization of intelligent tourism service system based on voice interaction

Science.gov (United States)

Hu, Lei-di; Long, Yi; Qian, Cheng-yang; Zhang, Ling; Lv, Guo-nian

2008-10-01

Voice technology is one of the important contents to improve the intelligence and humanization of tourism service system. Combining voice technology, the paper concentrates on application needs and the composition of system to present an overall intelligent tourism service system's framework consisting of presentation layer, Web services layer, and tourism application service layer. On the basis, the paper further elaborated the implementation of the system and its key technologies, including intelligent voice interactive technology, seamless integration technology of multiple data sources, location-perception-based guides' services technology, and tourism safety control technology. Finally, according to the situation of Nanjing tourism, a prototype of Tourism Services System is realized.

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 ...

Development of X-Y servo pneumatic-piezoelectric hybrid actuators for position control with high response, large stroke and nanometer accuracy.

Science.gov (United States)

Chiang, Mao-Hsiung

2010-01-01

This study aims to develop a X-Y dual-axial intelligent servo pneumatic-piezoelectric hybrid actuator for position control with high response, large stroke (250 mm, 200 mm) and nanometer accuracy (20 nm). In each axis, the rodless pneumatic actuator serves to position in coarse stroke and the piezoelectric actuator compensates in fine stroke. Thus, the overall control systems of the single axis become a dual-input single-output (DISO) system. Although the rodless pneumatic actuator has relatively larger friction force, it has the advantage of mechanism for multi-axial development. Thus, the X-Y dual-axial positioning system is developed based on the servo pneumatic-piezoelectric hybrid actuator. In addition, the decoupling self-organizing fuzzy sliding mode control is developed as the intelligent control strategies. Finally, the proposed novel intelligent X-Y dual-axial servo pneumatic-piezoelectric hybrid actuators are implemented and verified experimentally.

Development of X-Y Servo Pneumatic-Piezoelectric Hybrid Actuators for Position Control with High Response, Large Stroke and Nanometer Accuracy

Directory of Open Access Journals (Sweden)

Mao-Hsiung Chiang

2010-03-01

Full Text Available This study aims to develop a X-Y dual-axial intelligent servo pneumatic-piezoelectric hybrid actuator for position control with high response, large stroke (250 mm, 200 mm and nanometer accuracy (20 nm. In each axis, the rodless pneumatic actuator serves to position in coarse stroke and the piezoelectric actuator compensates in fine stroke. Thus, the overall control systems of the single axis become a dual-input single-output (DISO system. Although the rodless pneumatic actuator has relatively larger friction force, it has the advantage of mechanism for multi-axial development. Thus, the X-Y dual-axial positioning system is developed based on the servo pneumatic-piezoelectric hybrid actuator. In addition, the decoupling self-organizing fuzzy sliding mode control is developed as the intelligent control strategies. Finally, the proposed novel intelligent X-Y dual-axial servo pneumatic-piezoelectric hybrid actuators are implemented and verified experimentally.

Modeling of Agile Intelligent Manufacturing-oriented Production Scheduling System

Institute of Scientific and Technical Information of China (English)

Zhong-Qi Sheng; Chang-Ping Tang; Ci-Xing Lv

2010-01-01

Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper.

14th International Conference on Intelligent Autonomous Systems

CERN Document Server

Hosoda, Koh; Menegatti, Emanuele; Shimizu, Masahiro; Wang, Hesheng

2017-01-01

This book describes the latest research advances, innovations, and visions in the field of robotics as presented by leading researchers, engineers, and practitioners from around the world at the 14th International Conference on Intelligent Autonomous Systems (IAS-14), held in Shanghai, China in July 2016. The contributions amply demonstrate that robots, machines and systems are rapidly achieving intelligence and autonomy, attaining more and more capabilities such as mobility and manipulation, sensing and perception, reasoning, and decision-making. They cover a wide range of research results and applications, and particular attention is paid to the emerging role of autonomous robots and intelligent systems in industrial production, which reflects their maturity and robustness. The contributions were selected by means of a rigorous peer-review process and highlight many exciting and visionary ideas that will further galvanize the research community and spur novel research directions. The series of biennial IAS ...

Can a new smile make you look more intelligent and successful?

Science.gov (United States)

Beall, Anne E

2007-04-01

A smile has a tremendous impact on perceptions of one's attractiveness and one's personality. Previous psychological research has shown that attractive people are perceived as more successful, intelligent, and friendly. Research extends these findings by demonstrating that teeth alone can have an impact on overall attractiveness and perceptions of personality attributes. The results of the study discussed in this article extend the attractiveness research and demonstrate that one's smile is an important part of the physical attractiveness stereotype. One's smile clearly plays a significant role in the perception that others have of our appearance and our personality.

Depression In Gifted Intelligence As Compared With Normal Persons

Directory of Open Access Journals (Sweden)

Raeisi F

2004-08-01

Full Text Available Background: Depression is a common problem and reduces function of persons. Evaluation of this matter in Gifted Intelligence– because superior their beneficial ness– have more importance. Our aim in this study is to determine relative frequency of depression in Gifted Intelligence as compared with Normal persons. Materials and Methods: In the context of a case – control study 90 Normal volunteers and 56 very superior volunteers – aged between 20 and 30 years, so that matched in respect of gender – were investigated by Beck Depression Inventory. IQ identification was performed by both Wechsler Adult Intelligence scaling and Ravens progressive Matrices. Results: out of 90 Normal persons, 36 were depressed (40% and among 56 Gifted Intelligence, 35 were depressed. (62.5% In other words relative frequency of depression in Gifted Intelligence– with significant differences– is more.(P<0.05. Conclusion: Although Gifted Intelligence have more ability in opposition to stress- because higher level of IQ-but in this study was observed that prevalence of depression in Gifted Intelligence is more. This finding may be by reason of higher perception of them and the result of it– actually– more meeting of stress.

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

Directory of Open Access Journals (Sweden)

Yongcheng Li

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

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

Science.gov (United States)

Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

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

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

Science.gov (United States)

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

2015-01-01

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

Chimpanzee social intelligence: selfishness, altruism, and the mother-infant bond.

Science.gov (United States)

Hirata, Satoshi

2009-01-01

To better understand the human mind from an evolutionary perspective, a great deal of research has focused on the closest living relative of humans, the chimpanzee, using various approaches, including studies of social intelligence. Here, I review recent research related to several aspects of social intelligence, including deception, understanding of perception and intention, social learning, trading, cooperation, and regard for others. Many studies have demonstrated that chimpanzees are proficient in using their social intelligence for selfish motives to benefit from their interactions with others. In contrast, it is not yet clear whether chimpanzees engage in prosocial behaviors that benefit others; however, chimpanzee mother-infant interactions indicate the possibility of such behaviors. Therefore, I propose that chimpanzees possess rudimentary traits of human mental competence not only in terms of theory of mind in a broader sense but also in terms of prosociality involving regard for others. Mother-infant interactions appear to be particularly important to understanding the manifestation of social intelligence from an evolutionary perspective.

Intelligent Energy Management for Plug-in Hybrid Electric Vehicles: The Role of ITS Infrastructure in Vehicle Electrification Gestion énergétique intelligente pour véhicules électriques hybrides rechargeables : rôle de l’infrastructure de systèmes de transport intelligents (STI dans l’électrification des véhicules

Directory of Open Access Journals (Sweden)

Marano V.

2012-08-01

Full Text Available The desire to reduce carbon emissions due to transportation sources has led over the past decade to the development of new propulsion technologies, focused on vehicle electrification (including hybrid, plug-in hybrid and battery electric vehicles. These propulsion technologies, along with advances in telecommunication and computing power, have the potential of making passenger and commercial vehicles more energy efficient and environment friendly. In particular, energy management algorithms are an integral part of plug-in vehicles and are very important for achieving the performance benefits. The optimal performance of energy management algorithms depends strongly on the ability to forecast energy demand from the vehicle. Information available about environment (temperature, humidity, wind, road grade, etc. and traffic (traffic density, traffic lights, etc., is very important in operating a vehicle at optimal efficiency. This article outlines some current technologies that can help achieving this optimum efficiency goal. In addition to information available from telematic and geographical information systems, knowledge of projected vehicle charging demand on the power grid is necessary to build an intelligent energy management controller for future plug-in hybrid and electric vehicles. The impact of charging millions of vehicles from the power grid could be significant, in the form of increased loading of power plants, transmission and distribution lines, emissions and economics (information are given and discussed for the US case. Therefore, this effect should be considered in an intelligent way by controlling/scheduling the charging through a communication based distributed control. Le désir de réduire les émissions de carbone issues des sources de transport a conduit durant la dernière décennie au développement de nouvelles technologies de propulsion, axées sur l’électrification des véhicules (comprenant les véhicules �

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

It's All About Me: The Role of the Self in Predicting Leadership Perceptions

OpenAIRE

Robson, Victoria Elizabeth

2007-01-01

The present study examined the role of oneâ s own self-perceptions of leadership in predicting both leadership prototypes and leadership perceptions of others. Additionally, this study explored gender differences in leadership prototypes and perceptions of leadership. Participants completed a measure of their own self-perceptions of their leadership traits (i.e., sensitivity, intelligence, dedication, and dynamism) and an instrument that assessed their leadership prototypes (i.e., sensitivit...

From humans to computers cognition through visual perception

CERN Document Server

Alexandrov, Viktor Vasilievitch

1991-01-01

This book considers computer vision to be an integral part of the artificial intelligence system. The core of the book is an analysis of possible approaches to the creation of artificial vision systems, which simulate human visual perception. Much attention is paid to the latest achievements in visual psychology and physiology, the description of the functional and structural organization of the human perception mechanism, the peculiarities of artistic perception and the expression of reality. Computer vision models based on these data are investigated. They include the processes of external d

Student Perceptions of High-Achieving Classmates

Science.gov (United States)

Händel, Marion; Vialle, Wilma; Ziegler, Albert

2013-01-01

The reported study investigated students' perceptions of their high-performing classmates in terms of intelligence, social skills, and conscientiousness in different school subjects. The school subjects for study were examined with regard to cognitive, physical, and gender-specific issues. The results show that high academic achievements in…

The Contribution of Auditory and Cognitive Factors to Intelligibility of Words and Sentences in Noise.

Science.gov (United States)

Heinrich, Antje; Knight, Sarah

2016-01-01

Understanding the causes for speech-in-noise (SiN) perception difficulties is complex, and is made even more difficult by the fact that listening situations can vary widely in target and background sounds. While there is general agreement that both auditory and cognitive factors are important, their exact relationship to SiN perception across various listening situations remains unclear. This study manipulated the characteristics of the listening situation in two ways: first, target stimuli were either isolated words, or words heard in the context of low- (LP) and high-predictability (HP) sentences; second, the background sound, speech-modulated noise, was presented at two signal-to-noise ratios. Speech intelligibility was measured for 30 older listeners (aged 62-84) with age-normal hearing and related to individual differences in cognition (working memory, inhibition and linguistic skills) and hearing (PTA(0.25-8 kHz) and temporal processing). The results showed that while the effect of hearing thresholds on intelligibility was rather uniform, the influence of cognitive abilities was more specific to a certain listening situation. By revealing a complex picture of relationships between intelligibility and cognition, these results may help us understand some of the inconsistencies in the literature as regards cognitive contributions to speech perception.

The relationship between intelligence and training gains is moderated by training strategy.

Science.gov (United States)

Lee, Hyunkyu; Boot, Walter R; Baniqued, Pauline L; Voss, Michelle W; Prakash, Ruchika Shaurya; Basak, Chandramallika; Kramer, Arthur F

2015-01-01

We examined the relationship between training regimen and fluid intelligence in the learning of a complex video game. Fifty non-game-playing young adults were trained on a game called Space Fortress for 30 hours with one of two training regimens: (1) Hybrid Variable-Priority Training (HVT), with part-task training and a focus on improving specific skills and managing task priorities, and (2) Full Emphasis Training (FET) in which participants practiced the whole game to obtain the highest overall score. Fluid intelligence was measured with the Raven's Progressive Matrix task before training. With FET, fluid intelligence was positively associated with learning, suggesting that intellectual ability played a substantial role in determining individual differences in training success. In contrast, with HVT, fluid intelligence was not associated with learning, suggesting that individual differences in fluid intelligence do not factor into training success in a regimen that emphasizes component tasks and flexible task coordination. By analyzing training effects in terms of individual differences and training regimens, the current study offers a training approach that minimizes the potentially limiting effect of individual differences.

Artificial Intelligence and Moral intelligence

OpenAIRE

Laura Pana

2008-01-01

We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined,...

The Factor Structure of Trait Emotional Intelligence in Hong Kong Adolescents

Science.gov (United States)

Mavroveli, Stella; Siu, Angela F. Y.

2012-01-01

Background: Trait emotional intelligence ("trait EI" or "trait emotional self-efficacy") refers to individuals' emotion-related self-perceptions (Petrides, Furnham, & Mavroveli, 2007). A growing number of studies are looking at cross-cultural differences in the structure of the construct. Aims: This study investigates the…

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....

MAS Based Event-Triggered Hybrid Control for Smart Microgrids

DEFF Research Database (Denmark)

Dou, Chunxia; Liu, Bin; Guerrero, Josep M.

2013-01-01

This paper is focused on an advanced control for autonomous microgrids. In order to improve the performance regarding security and stability, a hierarchical decentralized coordinated control scheme is proposed based on multi-agents structure. Moreover, corresponding to the multi-mode and the hybrid...... haracteristics of microgrids, an event-triggered hybrid control, including three kinds of switching controls, is designed to intelligently reconstruct operation mode when the security stability assessment indexes or the constraint conditions are violated. The validity of proposed control scheme is demonstrated...

Exploring the validity of the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) with established emotions measures.

Science.gov (United States)

Roberts, Richard D; Schulze, Ralf; O'Brien, Kristin; MacCann, Carolyn; Reid, John; Maul, Andy

2006-11-01

Emotions measures represent an important means of obtaining construct validity evidence for emotional intelligence (EI) tests because they have the same theoretical underpinnings. Additionally, the extent to which both emotions and EI measures relate to intelligence is poorly understood. The current study was designed to address these issues. Participants (N = 138) completed the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT), two emotions measures, as well as four intelligence tests. Results provide mixed support for the model hypothesized to underlie the MSCEIT, with emotions research and EI measures failing to load on the same factor. The emotions measures loaded on the same factor as intelligence measures. The validity of certain EI components (in particular, Emotion Perception), as currently assessed, appears equivocal. Copyright 2006 APA, all rights reserved.

STAR- A SIMPLE TOOL FOR AUTOMATED REASONING SUPPORTING HYBRID APPLICATIONS OF ARTIFICIAL INTELLIGENCE (UNIX VERSION)

Science.gov (United States)

Borchardt, G. C.

1994-01-01

The Simple Tool for Automated Reasoning program (STAR) is an interactive, interpreted programming language for the development and operation of artificial intelligence (AI) application systems. STAR provides an environment for integrating traditional AI symbolic processing with functions and data structures defined in compiled languages such as C, FORTRAN and PASCAL. This type of integration occurs in a number of AI applications including interpretation of numerical sensor data, construction of intelligent user interfaces to existing compiled software packages, and coupling AI techniques with numerical simulation techniques and control systems software. The STAR language was created as part of an AI project for the evaluation of imaging spectrometer data at NASA's Jet Propulsion Laboratory. Programming in STAR is similar to other symbolic processing languages such as LISP and CLIP. STAR includes seven primitive data types and associated operations for the manipulation of these structures. A semantic network is used to organize data in STAR, with capabilities for inheritance of values and generation of side effects. The AI knowledge base of STAR can be a simple repository of records or it can be a highly interdependent association of implicit and explicit components. The symbolic processing environment of STAR may be extended by linking the interpreter with functions defined in conventional compiled languages. These external routines interact with STAR through function calls in either direction, and through the exchange of references to data structures. The hybrid knowledge base may thus be accessed and processed in general by either side of the application. STAR is initially used to link externally compiled routines and data structures. It is then invoked to interpret the STAR rules and symbolic structures. In a typical interactive session, the user enters an expression to be evaluated, STAR parses the input, evaluates the expression, performs any file input

Intelligent Personal Supercomputer for Solving Scientific and Technical Problems

Directory of Open Access Journals (Sweden)

Khimich, O.M.

2016-09-01

Full Text Available New domestic intellіgent personal supercomputer of hybrid architecture Inparkom_pg for the mathematical modeling of processes in the defense industry, engineering, construction, etc. was developed. Intelligent software for the automatic research and tasks of computational mathematics with approximate data of different structures was designed. Applied software to provide mathematical modeling problems in construction, welding and filtration processes was implemented.

Prediction of Compressional, Shear, and Stoneley Wave Velocities from Conventional Well Log Data Using a Committee Machine with Intelligent Systems

Science.gov (United States)

Asoodeh, Mojtaba; Bagheripour, Parisa

2012-01-01

Measurement of compressional, shear, and Stoneley wave velocities, carried out by dipole sonic imager (DSI) logs, provides invaluable data in geophysical interpretation, geomechanical studies and hydrocarbon reservoir characterization. The presented study proposes an improved methodology for making a quantitative formulation between conventional well logs and sonic wave velocities. First, sonic wave velocities were predicted from conventional well logs using artificial neural network, fuzzy logic, and neuro-fuzzy algorithms. Subsequently, a committee machine with intelligent systems was constructed by virtue of hybrid genetic algorithm-pattern search technique while outputs of artificial neural network, fuzzy logic and neuro-fuzzy models were used as inputs of the committee machine. It is capable of improving the accuracy of final prediction through integrating the outputs of aforementioned intelligent systems. The hybrid genetic algorithm-pattern search tool, embodied in the structure of committee machine, assigns a weight factor to each individual intelligent system, indicating its involvement in overall prediction of DSI parameters. This methodology was implemented in Asmari formation, which is the major carbonate reservoir rock of Iranian oil field. A group of 1,640 data points was used to construct the intelligent model, and a group of 800 data points was employed to assess the reliability of the proposed model. The results showed that the committee machine with intelligent systems performed more effectively compared with individual intelligent systems performing alone.

Original Framework for Optimizing Hybrid Energy Supply

Directory of Open Access Journals (Sweden)

Amevi Acakpovi

2016-01-01

Full Text Available This paper proposes an original framework for optimizing hybrid energy systems. The recent growth of hybrid energy systems in remote areas across the world added to the increasing cost of renewable energy has triggered the inevitable development of hybrid energy systems. Hybrid energy systems always pose a problem of optimization of cost which has been approached with different perspectives in the recent past. This paper proposes a framework to guide the techniques of optimizing hybrid energy systems in general. The proposed framework comprises four stages including identification of input variables for energy generation, establishment of models of energy generation by individual sources, development of artificial intelligence, and finally summation of selected sources. A case study of a solar, wind, and hydro hybrid system was undertaken with a linear programming approach. Substantial results were obtained with regard to how load requests were constantly satisfied while minimizing the cost of electricity. The developed framework gained its originality from the fact that it has included models of individual sources of energy that even make the optimization problem more complex. This paper also has impacts on the development of policies which will encourage the integration and development of renewable energies.

Speech intelligibility problems of Sudanese learners of English : an experimental approach

NARCIS (Netherlands)

Tajeldin Ali, Ezzeldin Mahmoud

2011-01-01

This is a study on the pronunciation and perception of English sounds and words by university students of English in Sudan, whose native language is Sudanese Arabic. The study aims to establish the intelligibility of Sudanese-Arabic (SA) accented English for native English (British and American)

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

Science.gov (United States)

Goertzel, Ben

2014-12-01

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

Intelligence Naturelle et Intelligence Artificielle

OpenAIRE

Dubois, Daniel

2011-01-01

Cet article présente une approche systémique du concept d’intelligence naturelle en ayant pour objectif de créer une intelligence artificielle. Ainsi, l’intelligence naturelle, humaine et animale non-humaine, est une fonction composée de facultés permettant de connaître et de comprendre. De plus, l'intelligence naturelle reste indissociable de la structure, à savoir les organes du cerveau et du corps. La tentation est grande de doter les systèmes informatiques d’une intelligence artificielle ...

Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied Agents

Directory of Open Access Journals (Sweden)

Eric Aaron

2016-11-01

Full Text Available Intelligent embodied robots are integrated systems: As they move continuously through their environments, executing behaviors and carrying out tasks, components for low-level and high-level intelligence are integrated in the robot's cognitive system, and cognitive and physical processes combine to create their behavior. For a modeling framework to enable the design and analysis of such integrated intelligence, the underlying representations in the design of the robot should be dynamically sensitive, capable of reflecting both continuous motion and micro-cognitive influences, while also directly representing the necessary beliefs and intentions for goal-directed behavior. In this paper, a dynamical intention-based modeling framework is presented that satisfies these criteria, along with a hybrid dynamical cognitive agent (HDCA framework for employing dynamical intentions in embodied agents. This dynamical intention-HDCA (DI-HDCA modeling framework is a fusion of concepts from spreading activation networks, hybrid dynamical system models, and the BDI (belief-desire-intention theory of goal-directed reasoning, adapted and employed unconventionally to meet entailments of environment and embodiment. The paper presents two kinds of autonomous agent learning results that demonstrate dynamical intentions and the multi-faceted integration they enable in embodied robots: with a simulated service robot in a grid-world office environment, reactive-level learning minimizes reliance on deliberative-level intelligence, enabling task sequencing and action selection to be distributed over both deliberative and reactive levels; and with a simulated game of Tag, the cognitive-physical integration of an autonomous agent enables the straightforward learning of a user-specified strategy during gameplay, without interruption to the game. In addition, the paper argues that dynamical intentions are consistent with cognitive theory underlying goal-directed behavior, and

Review of the Optimal Design on a Hybrid Renewable Energy System

Directory of Open Access Journals (Sweden)

Wu Yuan-Kang

2016-01-01

Full Text Available Hybrid renewable energy systems, combining various kinds of technologies, have shown relatively high capabilities to solve reliability problems and have reduced cost challenges. The use of hybrid electricity generation/storage technologies is reasonable to overcome related shortcomings. While the hybrid renewable energy system is attractive, its design, specifically the determination of the size of PV, wind, and diesel power generators and the size of energy storage system in each power station, is very challenging. Therefore, this paper will focus on the system planning and operation of hybrid generation systems, and several corresponding topics and papers by using intelligent computing methods will be reviewed. They include typical case studies, modeling and system simulation, control and management, reliability and economic studies, and optimal design on a reliable hybrid generation system.

Is Hybrid Education and Videoconferencing the Wave of the Future for Online Courses?

Science.gov (United States)

Popma, Joe

2012-01-01

A comprehensive literature review examines the effectiveness of hybrid education utilizing videoconferencing. The observations and perceptions of both students and the instructor participating in a hybrid pilot program will be discussed. Discussion highlights the value of hybrid education within the context of the students' busy schedules and…

Blinded by Beauty: Attractiveness Bias and Accurate Perceptions of Academic Performance.

Science.gov (United States)

Talamas, Sean N; Mavor, Kenneth I; Perrett, David I

2016-01-01

Despite the old adage not to 'judge a book by its cover', facial cues often guide first impressions and these first impressions guide our decisions. Literature suggests there are valid facial cues that assist us in assessing someone's health or intelligence, but such cues are overshadowed by an 'attractiveness halo' whereby desirable attributions are preferentially ascribed to attractive people. The impact of the attractiveness halo effect on perceptions of academic performance in the classroom is concerning as this has shown to influence students' future performance. We investigated the limiting effects of the attractiveness halo on perceptions of actual academic performance in faces of 100 university students. Given the ambiguity and various perspectives on the definition of intelligence and the growing consensus on the importance of conscientiousness over intelligence in predicting actual academic performance, we also investigated whether perceived conscientiousness was a more accurate predictor of academic performance than perceived intelligence. Perceived conscientiousness was found to be a better predictor of actual academic performance when compared to perceived intelligence and perceived academic performance, and accuracy was improved when controlling for the influence of attractiveness on judgments. These findings emphasize the misleading effect of attractiveness on the accuracy of first impressions of competence, which can have serious consequences in areas such as education and hiring. The findings also have implications for future research investigating impression accuracy based on facial stimuli.

The Effect of Surgeon Empathy and Emotional Intelligence on Patient Satisfaction

Science.gov (United States)

Weng, Hui-Ching; Steed, James F.; Yu, Shang-Won; Liu, Yi-Ten; Hsu, Chia-Chang; Yu, Tsan-Jung; Chen, Wency

2011-01-01

We investigated the associations of surgeons' emotional intelligence and surgeons' empathy with patient-surgeon relationships, patient perceptions of their health, and patient satisfaction before and after surgical procedures. We used multi-source approaches to survey 50 surgeons and their 549 outpatients during initial and follow-up visits.…

Unethical and inept? The influence of moral information on perceptions of competence.

Science.gov (United States)

Stellar, Jennifer E; Willer, Robb

2018-02-01

While moral character heavily influences global evaluations of others (Goodwin, Piazza, & Rozin, 2014), its causal effect on perceptions of others' competence (i.e., one's knowledge, skills, and abilities) is less clear. We found that people readily use information about another's morality when judging their competence, despite holding folk intuitions that these domains are independent. Across 6 studies (n = 1,567), including 2 preregistered experiments, participants judged targets who committed hypothetical transgressions (Studies 1 and 3), cheated on lab tasks (Study 2), acted selfishly in economic games (Study 4), and received low morality ratings from coworkers (Study 5 and 6) as less competent than control or moral targets. These findings were specific to morality and were not the result of incidentally manipulating impressions of warmth (Study 4), nor were they fully explained by a general halo effect (Studies 2 and 3). We hypothesized that immoral targets are seen as less competent because their immoral actions led them to be viewed as low in social intelligence. Studies 4 and 5 supported this prediction, demonstrating that social intelligence was a more reliable mediator than perceptions of self-control or general intelligence. An experimental test of this mediation argument found that presenting targets as highly socially intelligent eliminated the negative effect of immoral information on judgments of competence (Study 6). These results suggest that information about a person's moral character readily influences perceptions of their competence. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Synthesis and assessment methods for an edge-alignment-free hybrid image

Science.gov (United States)

Sripian, Peeraya; Yamaguchi, Yasushi

2017-07-01

A hybrid image allows multiple image interpretations to be modulated by the viewing distance. It can be constructed on the basis of the multiscale perceptual mechanisms of the human visual system by combining the low and high spatial frequencies of two different images. The hybrid image was introduced as an experimental tool for visual recognition study in terms of spatial frequency perception. To produce a compelling hybrid image, the original hybrid image synthesis method could only use similar shapes of source images that were aligned in the edges. If any two different images can be hybrid, it would be beneficial as a new experimental tool. In addition, there is no measure for the actual perception of spatial frequency, whether a single spatial frequency or both spatial frequencies are perceived from the hybrid stimulus. This paper describes two methods for synthesizing a hybrid image from dissimilar shape images or unaligned images; this hybrid image is known as an "edge-alignment-free hybrid image." A noise-inserted method can be done by intentionally inserting and enhancing noises into the high-frequency image. With this method, the low-frequency blobs are covered with high-frequency noises when viewed up close. A color-inserted method uses complementary color gratings in the background of the high-frequency image to emphasize the high-frequency image when viewed up close, whereas the gratings disappear when viewed from far away. To ascertain that our approach successfully separates the spatial frequency at each viewing distance, we measured this property using our proposed assessment method. Our proposed method allows the experimenter to quantify the probability of perceiving both spatial frequencies and a single spatial frequency in a hybrid image. The experimental results confirmed that our proposed synthesis methods successfully hid the low-frequency image and emphasized the high-frequency image at a close viewing distance. At the same time, the

THE RELATIONSHIP BETWEEN TURKISH EFL STATE SCHOOL TEACHERS' CULTURAL INTELLIGENCE AND THEIR PROFESSIONAL WELL-BEING

Directory of Open Access Journals (Sweden)

İ. EFE EFEOĞLU

2017-09-01

Full Text Available Cultural intelligence is described as the ability of a person to behave adequately in culturally diverse environments. It involves comprehending the effects of cultural background on the attitudes of people for auspicious participation in any social setting. Cultural intelligence may be positively and significantly correlated with professional well-being among English as foreign language (EFL teachers. So, the present study sought to investigate the correlation between Turkish EFL state school teachers' cultural intelligence and their professional well-being. A sample including 120 EFL state school teachers completed two questionnaires: (1 Cultural Intelligence Scale developed by Cultural Intelligence Center (2005; and (2 the Scale of Teacher Perception of Professional Well-Being developed by Yildirim, Arastaman and Dasci (2016. The results of the study indicated significant correlations between Turkish EFL state school teachers' cultural intelligence and their professional well-being. This study may help English Language Teaching (ELT departments to implement materials to their curriculum for aiding EFL teachers in terms of developing cultural intelligence. Furthermore, this paper makes a unique contribution to the area of cultural intelligence by identifying whether there is a relationship between cultural intelligence and professional well-being.

Optimizing acoustical conditions for speech intelligibility in classrooms

Science.gov (United States)

Yang, Wonyoung

High speech intelligibility is imperative in classrooms where verbal communication is critical. However, the optimal acoustical conditions to achieve a high degree of speech intelligibility have previously been investigated with inconsistent results, and practical room-acoustical solutions to optimize the acoustical conditions for speech intelligibility have not been developed. This experimental study validated auralization for speech-intelligibility testing, investigated the optimal reverberation for speech intelligibility for both normal and hearing-impaired listeners using more realistic room-acoustical models, and proposed an optimal sound-control design for speech intelligibility based on the findings. The auralization technique was used to perform subjective speech-intelligibility tests. The validation study, comparing auralization results with those of real classroom speech-intelligibility tests, found that if the room to be auralized is not very absorptive or noisy, speech-intelligibility tests using auralization are valid. The speech-intelligibility tests were done in two different auralized sound fields---approximately diffuse and non-diffuse---using the Modified Rhyme Test and both normal and hearing-impaired listeners. A hybrid room-acoustical prediction program was used throughout the work, and it and a 1/8 scale-model classroom were used to evaluate the effects of ceiling barriers and reflectors. For both subject groups, in approximately diffuse sound fields, when the speech source was closer to the listener than the noise source, the optimal reverberation time was zero. When the noise source was closer to the listener than the speech source, the optimal reverberation time was 0.4 s (with another peak at 0.0 s) with relative output power levels of the speech and noise sources SNS = 5 dB, and 0.8 s with SNS = 0 dB. In non-diffuse sound fields, when the noise source was between the speaker and the listener, the optimal reverberation time was 0.6 s with

Human management and hybridization shape treegourd fruits in the Brazilian Amazon Basin.

Science.gov (United States)

Ambrósio Moreira, Priscila; Mariac, Cédric; Zekraoui, Leila; Couderc, Marie; Rodrigues, Doriane Picanço; Clement, Charles R; Vigouroux, Yves

2017-07-01

Local people's perceptions of cultivated and wild agrobiodiversity, as well as their management of hybridization are still understudied in Amazonia. Here we analyze domesticated treegourd ( Crescentia cujete ), whose versatile fruits have technological, symbolic, and medicinal uses. A wild relative ( C. amazonica ) of the cultivated species grows spontaneously in Amazonian flooded forests. We demonstrated, using whole chloroplast sequences and nuclear microsatellites, that the two species are strongly differentiated. Nonetheless, they hybridize readily throughout Amazonia and the proportions of admixture correlate with fruit size variation of cultivated trees. New morphotypes arise from hybridization, which are recognized by people and named as local varieties. Small hybrid fruits are used to make the important symbolic rattle ( maracá ), suggesting that management of hybrid trees is an ancient human practice in Amazonia. Effective conservation of Amazonian agrobiodiversity needs to incorporate this interaction between wild and cultivated populations that is managed by smallholder families. Beyond treegourd, our study clearly shows that hybridization plays an important role in tree crop phenotypic diversification and that the integration of molecular analyses and farmers' perceptions of diversity help disentangle crop domestication history.

The impact of emotional intelligent leadership on staff nurse empowerment: the moderating effect of span of control.

Science.gov (United States)

Lucas, Victoria; Laschinger, Heather K Spence; Wong, Carol A

2008-11-01

To test a model linking nurses' perceptions of their nurse manager's emotionally intelligent leadership style and nurses' structural empowerment, and the impact of nurse manager span of control (number of direct reports) on the emotional intelligence/empowerment relationship. Hospital restructuring in the 1990s resulted in a dramatic reduction in nurse manager positions, yet nurse managers are critical to empowering nurses for professional practice. A descriptive correlational survey design was used to test the hypothesized model in two community hospitals in Ontario. Two hundred and three nurses from two hospitals returned useable questionnaires (68% response rate). Span of control was a significant moderator of the relationship between nurses perceptions of their managers' emotionally intelligent behaviour and feelings of workplace empowerment. The results suggest that even managers with strong emotional intelligence may not be able to empower their staff if their span of control is large. Every effort must be made to ensure that managers have reasonable spans of control that allow them to develop and use the leadership skill necessary for empowering their staff to practice to the full scope of their professional role.

Innovative intelligent technology of distance learning for visually impaired people

Science.gov (United States)

Samigulina, Galina; Shayakhmetova, Assem; Nuysuppov, Adlet

2017-12-01

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

Innovative intelligent technology of distance learning for visually impaired people

Directory of Open Access Journals (Sweden)

Samigulina Galina

2017-12-01

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

The perception of animacy and intelligence based on a robot's embodiment

NARCIS (Netherlands)

Bartneck, C.; Kanda, T.; Mubin, O.; Al Mahmud, A.

2007-01-01

Robots exhibit life-like behavior by performing intelligent actions. To enhance human-robot interaction it is necessary to investigate and understand how end-users perceive such animate behavior. In this paper, we report an experiment to investigate how people perceived different robot embodiments

The intelligibility of Chinese-accented English to Korean and American students at a U.S. university

DEFF Research Database (Denmark)

Hardman, Jocelyn

2017-01-01

This study investigated the intelligibility of Chinese and American graduate students to their Korean and American peers. A psycholinguistic word-recognition-in-noise study investigated the effects on intelligibility of speakers’ L1 and segmental pronunciation accuracy and how this varied...... international and American university students should receive the linguistic perception training necessary to accommodate the range of accent diversity that has become an integral part of academia today.  ...

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.

A cognitive robotics system: the symbolic and sub-symbolic robotic intelligence control system (SS-RICS)

Science.gov (United States)

Kelley, Troy D.; Avery, Eric

2010-04-01

This paper will detail the progress on the development of the Symbolic and Subsymbolic Robotics Intelligence Control System (SS-RICS). The system is a goal oriented production system, based loosely on the cognitive architecture, the Adaptive Control of Thought-Rational (ACT-R) some additions and changes. We have found that in order to simulate complex cognition on a robot, many aspects of cognition (long term memory (LTM), perception) needed to be in place before any generalized intelligent behavior can be produced. In working with ACT-R, we found that it was a good instantiation of working memory, but that we needed to add other aspects of cognition including LTM and perception to have a complete cognitive system. Our progress to date will be noted and the challenges that remain will be addressed.

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

Science.gov (United States)

Cipresso, Pietro; Riva, Giuseppe

2015-01-01

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

Time Series Analysis and Forecasting for Wind Speeds Using Support Vector Regression Coupled with Artificial Intelligent Algorithms

Directory of Open Access Journals (Sweden)

Ping Jiang

2015-01-01

Full Text Available Wind speed/power has received increasing attention around the earth due to its renewable nature as well as environmental friendliness. With the global installed wind power capacity rapidly increasing, wind industry is growing into a large-scale business. Reliable short-term wind speed forecasts play a practical and crucial role in wind energy conversion systems, such as the dynamic control of wind turbines and power system scheduling. In this paper, an intelligent hybrid model for short-term wind speed prediction is examined; the model is based on cross correlation (CC analysis and a support vector regression (SVR model that is coupled with brainstorm optimization (BSO and cuckoo search (CS algorithms, which are successfully utilized for parameter determination. The proposed hybrid models were used to forecast short-term wind speeds collected from four wind turbines located on a wind farm in China. The forecasting results demonstrate that the intelligent hybrid models outperform single models for short-term wind speed forecasting, which mainly results from the superiority of BSO and CS for parameter optimization.

STAR- A SIMPLE TOOL FOR AUTOMATED REASONING SUPPORTING HYBRID APPLICATIONS OF ARTIFICIAL INTELLIGENCE (DEC VAX VERSION)

Science.gov (United States)

Borchardt, G. C.

1994-01-01

The Simple Tool for Automated Reasoning program (STAR) is an interactive, interpreted programming language for the development and operation of artificial intelligence (AI) application systems. STAR provides an environment for integrating traditional AI symbolic processing with functions and data structures defined in compiled languages such as C, FORTRAN and PASCAL. This type of integration occurs in a number of AI applications including interpretation of numerical sensor data, construction of intelligent user interfaces to existing compiled software packages, and coupling AI techniques with numerical simulation techniques and control systems software. The STAR language was created as part of an AI project for the evaluation of imaging spectrometer data at NASA's Jet Propulsion Laboratory. Programming in STAR is similar to other symbolic processing languages such as LISP and CLIP. STAR includes seven primitive data types and associated operations for the manipulation of these structures. A semantic network is used to organize data in STAR, with capabilities for inheritance of values and generation of side effects. The AI knowledge base of STAR can be a simple repository of records or it can be a highly interdependent association of implicit and explicit components. The symbolic processing environment of STAR may be extended by linking the interpreter with functions defined in conventional compiled languages. These external routines interact with STAR through function calls in either direction, and through the exchange of references to data structures. The hybrid knowledge base may thus be accessed and processed in general by either side of the application. STAR is initially used to link externally compiled routines and data structures. It is then invoked to interpret the STAR rules and symbolic structures. In a typical interactive session, the user enters an expression to be evaluated, STAR parses the input, evaluates the expression, performs any file input

The Dimensions of Organizational Intelligence in Romanian Companies – A Human Capital Perspective

Directory of Open Access Journals (Sweden)

Viorel Lefter

2008-10-01

Full Text Available The paper discusses the perceptions of organizational intelligence dimensions in Romanian companies, taking into account the degree of awareness employees have, in relation to this concept, and the overall investments in R&D at the industry level. Starting from the concept of organizational intelligence, the way it is defined in recent literature, we establish seven dimensions which are relevant for its analysis, and test them on a relevant sample, random stratified, of Romanian companies, reflecting the structure of Romanian economy, and all the layers of company size. We examine, thus, the correlation between the quality of the organizational human capital (the individual intelligence and the learning processes, at the organizational level. The results of the study can be further expanded to analyses of the regions of development, by correlating the dimensions of the organizational intelligence with the macro-economic, developmental indicators.

An intelligent switch with back-propagation neural network based hybrid power system

Science.gov (United States)

Perdana, R. H. Y.; Fibriana, F.

2018-03-01

The consumption of conventional energy such as fossil fuels plays the critical role in the global warming issues. The carbon dioxide, methane, nitrous oxide, etc. could lead the greenhouse effects and change the climate pattern. In fact, 77% of the electrical energy is generated from fossil fuels combustion. Therefore, it is necessary to use the renewable energy sources for reducing the conventional energy consumption regarding electricity generation. This paper presents an intelligent switch to combine both energy resources, i.e., the solar panels as the renewable energy with the conventional energy from the State Electricity Enterprise (PLN). The artificial intelligence technology with the back-propagation neural network was designed to control the flow of energy that is distributed dynamically based on renewable energy generation. By the continuous monitoring on each load and source, the dynamic pattern of the intelligent switch was better than the conventional switching method. The first experimental results for 60 W solar panels showed the standard deviation of the trial at 0.7 and standard deviation of the experiment at 0.28. The second operation for a 900 W of solar panel obtained the standard deviation of the trial at 0.05 and 0.18 for the standard deviation of the experiment. Moreover, the accuracy reached 83% using this method. By the combination of the back-propagation neural network with the observation of energy usage of the load using wireless sensor network, each load can be evenly distributed and will impact on the reduction of conventional energy usage.

Development of a hybrid system of artificial neural networks and ...

African Journals Online (AJOL)

Development of a hybrid system of artificial neural networks and artificial bee colony algorithm for prediction and modeling of customer choice in the market. ... attempted to present a new method for the modeling and prediction of customer choice in the market using the combination of artificial intelligence and data mining.

Identification of key factors in consumers' adoption behavior of intelligent medical terminals based on a hybrid modified MADM model for product improvement.

Science.gov (United States)

Liu, Yupeng; Chen, Yifei; Tzeng, Gwo-Hshiung

2017-09-01

As a new application technology of the Internet of Things (IoT), intelligent medical treatment has attracted the attention of both nations and industries through its promotion of medical informatisation, modernisation, and intelligentisation. Faced with a wide variety of intelligent medical terminals, consumers may be affected by various factors when making purchase decisions. To examine and evaluate the key influential factors (and their interrelationships) of consumer adoption behavior for improving and promoting intelligent medical terminals toward achieving set aspiration level in each dimension and criterion. A hybrid modified Multiple Attribute Decision-Making (MADM) model was used for this study, based on three components: (1) the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique, to build an influential network relationship map (INRM) at both 'dimensions' and 'criteria' levels; (2) the DEMATEL-based analytic network process (DANP) method, to determine the interrelationships and influential weights among the criteria and identify the source-influential factors; and (3) the modified Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, to evaluate and improve for reducing the performance gaps to meet the consumers' needs for continuous improvement and sustainable products-development. First, a consensus on the influential factors affecting consumers' adoption of intelligent medical terminals was collected from experts' opinion in practical experience. Next, the interrelationships and influential weights of DANP among dimensions/criteria based on the DEMATEL technique were determined. Finally, two intelligent medicine bottles (AdhereTech, A 1 alternative; and Audio/Visual Alerting Pillbox, A 2 alternative) were reviewed as the terminal devices to verify the accuracy of the MADM model and evaluate its performance on each criterion for improving the total certification gaps by systematics according to the modified VIKOR method

An intelligent and interactive carpet role of design in a textile innovation project

NARCIS (Netherlands)

Deckers, E.J.L.; Stouw, van der B.; Peutz, J.

2012-01-01

This paper presents an ongoing innovation project on the development of an intelligent and interactive carpet called PeR+, short for Perception Rug Plus. This design-research project is a collaboration between an international flooring company, DESSO, and the Department of Industrial Design at the

Theory of the Quantum Dot Hybrid Qubit

Science.gov (United States)

Friesen, Mark

2015-03-01

The quantum dot hybrid qubit, formed from three electrons in two quantum dots, combines the desirable features of charge qubits (fast manipulation) and spin qubits (long coherence times). The hybridized spin and charge states yield a unique energy spectrum with several useful properties, including two different operating regimes that are relatively immune to charge noise due to the presence of optimal working points or ``sweet spots.'' In this talk, I will describe dc and ac-driven gate operations of the quantum dot hybrid qubit. I will analyze improvements in the dephasing that are enabled by the sweet spots, and I will discuss the outlook for quantum hybrid qubits in terms of scalability. This work was supported in part by ARO (W911NF-12-0607), NSF (PHY-1104660), the USDOD, and the Intelligence Community Postdoctoral Research Fellowship Program. The views and conclusions contained in this presentation are those of the authors and should not be interpreted as representing the official policies or endorsements, either expressed or implied, of the US government.

Hybrid Predictive Control for Dynamic Transport Problems

CERN Document Server

Núñez, Alfredo A; Cortés, Cristián E

2013-01-01

Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from the area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed-integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: ●hybrid predictive control (HPC) ...

Blinded by Beauty: Attractiveness Bias and Accurate Perceptions of Academic Performance

Science.gov (United States)

Talamas, Sean N.; Mavor, Kenneth I.; Perrett, David I.

2016-01-01

Despite the old adage not to ‘judge a book by its cover’, facial cues often guide first impressions and these first impressions guide our decisions. Literature suggests there are valid facial cues that assist us in assessing someone’s health or intelligence, but such cues are overshadowed by an ‘attractiveness halo’ whereby desirable attributions are preferentially ascribed to attractive people. The impact of the attractiveness halo effect on perceptions of academic performance in the classroom is concerning as this has shown to influence students’ future performance. We investigated the limiting effects of the attractiveness halo on perceptions of actual academic performance in faces of 100 university students. Given the ambiguity and various perspectives on the definition of intelligence and the growing consensus on the importance of conscientiousness over intelligence in predicting actual academic performance, we also investigated whether perceived conscientiousness was a more accurate predictor of academic performance than perceived intelligence. Perceived conscientiousness was found to be a better predictor of actual academic performance when compared to perceived intelligence and perceived academic performance, and accuracy was improved when controlling for the influence of attractiveness on judgments. These findings emphasize the misleading effect of attractiveness on the accuracy of first impressions of competence, which can have serious consequences in areas such as education and hiring. The findings also have implications for future research investigating impression accuracy based on facial stimuli. PMID:26885976

The role of mindfulness and spiritual intelligence in students' mental health

Directory of Open Access Journals (Sweden)

Ebrahim Nemati

2017-06-01

Full Text Available Studies show that mental disorders are highly prevalent among students. Therefore, the present study aimed to examine the role of mindfulness and spiritual intelligence in the students’ mental health studying at university of medical sciences. The study population included all undergraduate and medicine students. A total of 393 female and male students (193 medical and 200 non-medical students were selected through randomly. General Health Questionnaire (GHQ and spiritual intelligence and mindfulness questionnaire were used to evaluate the participants. The results revealed the negative correlation of mental health with mindfulness and spiritual intelligence and a positive correlation between mindfulness and dimensions of spiritual intelligence. Also, the dimension of spiritual life (43.1% and mindfulness (31% had a significant negative effect on the explained variance of the students’ mental health. Analysis of variance showed that the scales of mindfulness, perception of existence, somatic symptoms, and anxiety were higher among women. Therefore, the students can be more capable of coping with existing traumas and pressures by boosting their spirituality, consciousness, and mindfulness.

Normalizing difference: Emotional intelligence and diversity management competence in healthcare managers

Directory of Open Access Journals (Sweden)

Adebukola E. Oyewunmi

2018-05-01

Full Text Available Purpose: Diversity is synonymous with difference. The diverse workforce presents an array of complexities which necessitates the deployment of specific managerial competencies. Empirical evidences have indicated the role of emotional intelligence in the enhancement of abilities. Thus, this study investigated the relationship between emotional intelligence and diversity management competency amongst healthcare managers in Southwest Nigeria.  Design: The descriptive survey method was adopted for the study. A total of 360 respondents completed the structured questionnaire titled Emotional Intelligence and Diversity Management Competency Questionnaire (EIDMCQ. Data was analyzed using descriptive and inferential statistics such as, Multiple Regression Analyses and Pearson Product Moment Correlation Statistical methods.  Findings: A positive correlation was found between emotional intelligence and diversity management competency. Gender, ethnicity, and age, did not moderate the relationship between emotional intelligence and diversity management competency.  Practical Implications: As difference is the reality of modern organizations, it is important to conceptualize it as normal and positive. Emotional intelligence is recommended as a critical tool to normalize the individual perceptions of difference. The re-assessment of the functions of managers must be followed by total commitment to capacity building in emotional intelligence, as well as the re-engineering of organizational and national cultures to promote equal opportunities, inclusion and diversity leveraging.  Originality/value: This study pioneers research on emotional intelligence and diversity management competency in Nigeria’s public healthcare sector. It conceptualizes diversity management on an individual- managerial level. Practical interventions are provided to enhance the application of specific competencies to optimize a diverse workplace.

Emotional Intelligence and Self-Esteem as Predictors of Teacher Self-Efficacy

Science.gov (United States)

Sahin, Harun

2017-01-01

Teacher self-efficacy is related to teachers or pre-service teachers feeling competent in their profession. The purpose of this study is to examine the relationship between the pre-service teachers' self-efficacy perceptions and their emotional intelligence and self-esteem. The study group of the current research comprised a total of 212…

Abstraction in artificial intelligence and complex systems

CERN Document Server

Saitta, Lorenza

2013-01-01

Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences.  After discussing the characterizing properties of abstraction, a formal model, the K

Neural network control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle

Science.gov (United States)

Harmon, Frederick G.

2005-11-01

Parallel hybrid-electric propulsion systems would be beneficial for small unmanned aerial vehicles (UAVs) used for military, homeland security, and disaster-monitoring missions. The benefits, due to the hybrid and electric-only modes, include increased time-on-station and greater range as compared to electric-powered UAVs and stealth modes not available with gasoline-powered UAVs. This dissertation contributes to the research fields of small unmanned aerial vehicles, hybrid-electric propulsion system control, and intelligent control. A conceptual design of a small UAV with a parallel hybrid-electric propulsion system is provided. The UAV is intended for intelligence, surveillance, and reconnaissance (ISR) missions. A conceptual design reveals the trade-offs that must be considered to take advantage of the hybrid-electric propulsion system. The resulting hybrid-electric propulsion system is a two-point design that includes an engine primarily sized for cruise speed and an electric motor and battery pack that are primarily sized for a slower endurance speed. The electric motor provides additional power for take-off, climbing, and acceleration and also serves as a generator during charge-sustaining operation or regeneration. The intelligent control of the hybrid-electric propulsion system is based on an instantaneous optimization algorithm that generates a hyper-plane from the nonlinear efficiency maps for the internal combustion engine, electric motor, and lithium-ion battery pack. The hyper-plane incorporates charge-depletion and charge-sustaining strategies. The optimization algorithm is flexible and allows the operator/user to assign relative importance between the use of gasoline, electricity, and recharging depending on the intended mission. A MATLAB/Simulink model was developed to test the control algorithms. The Cerebellar Model Arithmetic Computer (CMAC) associative memory neural network is applied to the control of the UAVs parallel hybrid

Fuzzy-Based Adaptive Hybrid Burst Assembly Technique for Optical Burst Switched Networks

Directory of Open Access Journals (Sweden)

Abubakar Muhammad Umaru

2014-01-01

Full Text Available The optical burst switching (OBS paradigm is perceived as an intermediate switching technology for future all-optical networks. Burst assembly that is the first process in OBS is the focus of this paper. In this paper, an intelligent hybrid burst assembly algorithm that is based on fuzzy logic is proposed. The new algorithm is evaluated against the traditional hybrid burst assembly algorithm and the fuzzy adaptive threshold (FAT burst assembly algorithm via simulation. Simulation results show that the proposed algorithm outperforms the hybrid and the FAT algorithms in terms of burst end-to-end delay, packet end-to-end delay, and packet loss ratio.

Wearable computer for mobile augmented-reality-based controlling of an intelligent robot

Science.gov (United States)

Turunen, Tuukka; Roening, Juha; Ahola, Sami; Pyssysalo, Tino

2000-10-01

An intelligent robot can be utilized to perform tasks that are either hazardous or unpleasant for humans. Such tasks include working in disaster areas or conditions that are, for example, too hot. An intelligent robot can work on its own to some extent, but in some cases the aid of humans will be needed. This requires means for controlling the robot from somewhere else, i.e. teleoperation. Mobile augmented reality can be utilized as a user interface to the environment, as it enhances the user's perception of the situation compared to other interfacing methods and allows the user to perform other tasks while controlling the intelligent robot. Augmented reality is a method that combines virtual objects into the user's perception of the real world. As computer technology evolves, it is possible to build very small devices that have sufficient capabilities for augmented reality applications. We have evaluated the existing wearable computers and mobile augmented reality systems to build a prototype of a future mobile terminal- the CyPhone. A wearable computer with sufficient system resources for applications, wireless communication media with sufficient throughput and enough interfaces for peripherals has been built at the University of Oulu. It is self-sustained in energy, with enough operating time for the applications to be useful, and uses accurate positioning systems.

Influence of the Risk-Contributing Factors on the Financing of the Investment Project for Building of Intelligent Buildings

OpenAIRE

Voytolovskiy Nikolay; Trebukhin Anatoliy; Shoshinov Vitaly

2017-01-01

This article provides the generic classification of risks of the investment projects for the construction of intelligent buildings which differ by the detachment of the subjective perception of risk by the investor. Risk and uncertainty were justified as system characteristics of the investment projects for the construction of intelligent buildings. Characteristics of the development was given in the context of project management. Methodical schemes of the development of the investment projec...

The Porsche Panamera S E-Hybrid drivetrain; Der Antriebsstrang des Porsche Panamera S E-Hybrid

Energy Technology Data Exchange (ETDEWEB)

Semmler, D.; Kerner, J.; Spiegel, L.; Bitsche, O.; Rauner, T.; Stache, I.; Marques, M. [Dr. Ing. h.c. F. Porsche AG, Weissach (Germany)

2013-08-01

With the new Panamera S E-Hybrid, Porsche presents the first standard plug-in hybrid concept for the luxury sector. The drivetrain represents a consistent further development of the full-hybrid vehicles already successful on the market. However, it has been updated to achieve the lowest possible fuel consumption and to meet future emission laws before they even take effect. It was possible to increase the performance and efficiency of the hybrid components, significantly improving both electric performance as well as the electric range. A large part of that is due to the new electric machine. In the same installation space, we have managed to more than double the power to 70 kW. A new intelligent operating strategy also allows us to meet the EU6 exhaust gas limits. In addition to the efficiency improvement measures, the lithium-ion battery with its 9.4 kWh capacity especially contributes to the car's enhanced range. Thanks to the higher energy density of the new cell technology, the battery only needs a little more installation space in comparison with the Panamera S Hybrid. In pure electric operation, the vehicle reaches a top speed of 135 km/h (limited) and has an electric range of 36 kilometres in the NEDC profile. Typical Porsche performance is provided by the system power of 416 hp (306 kW). In NEDC standard consumption, the E-Hybrid's 3.1 l/100 km and CO{sub 2} emissions of 71 g/km have stayed attractively economical. (orig.)

Intelligent Virtual Reality and its Impact on Spatial Skills and Academic Achievements

Directory of Open Access Journals (Sweden)

Esther Zaretsky

2005-08-01

Full Text Available It is known that the training of intelligent virtual reality, through the use of computer games, can improve spatial skills especially visualization and enhances academic achievements. Through an experiment of using Tetris software, two objectives were achieved: developing spatial as well as intelligence skills and enhancing academic achievements, focusing on mathematics. This study followed studies dealing with the impact on putting the learner into action in 3d space software. During teaching a transition from 2d to 3d spatial perception and operation occurred. A positive transfer from 3d virtual reality rotation training to structural induction skills, by means of mental imaging, was also achieved. At the same time the motivation for learning was enhanced, without using extrinsic reinforcements. The duration of concentration while using the intelligent software increased gradually up to 60 minutes.

A New Dimension of Business Intelligence: Location-based Intelligence

OpenAIRE

Zeljko Panian

2012-01-01

Through the course of this paper we define Locationbased Intelligence (LBI) which is outgrowing from process of amalgamation of geolocation and Business Intelligence. Amalgamating geolocation with traditional Business Intelligence (BI) results in a new dimension of BI named Location-based Intelligence. LBI is defined as leveraging unified location information for business intelligence. Collectively, enterprises can transform location data into business intelligence applic...

Intelligence analysis – the royal discipline of Competitive Intelligence

Directory of Open Access Journals (Sweden)

František Bartes

2011-01-01

Full Text Available The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in business practice, is the “forecasting of the future”. That is forecasting about the future, which forms the basis for strategic decisions made by the company’s top management. To implement that requirement in corporate practice, the author perceives Competitive Intelligence as a systemic application discipline. This approach allows him to propose a “Work Plan” for Competitive Intelligence as a fundamental standardized document to steer Competitive Intelligence team activities. The author divides the Competitive Intelligence team work plan into five basic parts. Those parts are derived from the five-stage model of the intelligence cycle, which, in the author’s opinion, is more appropriate for complicated cases of Competitive Intelligence.

Cross-Cultural Adaptation of the Intelligibility in Context Scale for South Africa

Science.gov (United States)

Pascoe, Michelle; McLeod, Sharynne

2016-01-01

The Intelligibility in Context Scale (ICS) is a screening questionnaire that focuses on parents' perceptions of children's speech in different contexts. Originally developed in English, it has been translated into 60 languages and the validity and clinical utility of the scale has been documented in a range of countries. In South Africa, there are…

Performing Intelligible Genders through Violence: Bullying as Gender Practice and Heteronormative Control

Science.gov (United States)

Carrera-Fernández, María Victoria; Lameiras-Fernández, María; Rodríguez-Castro, Yolanda

2018-01-01

The purpose of the present study was to analyse adolescents' perception of bullying and particularly of the ways intelligible masculinities and femininities are performed through violence in the framework of Queer Theory. We conducted a qualitative study using focus groups. The sample was composed of 93 Spanish adolescents (48 girls and 45 boys,…

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

Science.gov (United States)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

Predicting athletic success motivation using mental skin and emotional intelligence and its components in male athletes.

Science.gov (United States)

Kajbafnezhad, H; Ahadi, H; Heidarie, A; Askari, P; Enayati, M

2012-10-01

The aim of this study was to predict athletic success motivation by mental skills, emotional intelligence and its components. The research sample consisted of 153 male athletes who were selected through random multistage sampling. The subjects completed the Mental Skills Questionnaire, Bar-On Emotional Intelligence questionnaire and the perception of sport success questionnaire. Data were analyzed using Pearson correlation coefficient and multiple regressions. Regression analysis shows that between the two variables of mental skill and emotional intelligence, mental skill is the best predictor for athletic success motivation and has a better ability to predict the success rate of the participants. Regression analysis results showed that among all the components of emotional intelligence, self-respect had a significantly higher ability to predict athletic success motivation. The use of psychological skills and emotional intelligence as an mediating and regulating factor and organizer cause leads to improved performance and can not only can to help athletes in making suitable and effective decisions for reaching a desired goal.

Spiritual Intelligence, Emotional Intelligence and Auditor’s Performance

OpenAIRE

Hanafi, Rustam

2010-01-01

The objective of this research was to investigate empirical evidence about influence audi-tor spiritual intelligence on the performance with emotional intelligence as a mediator variable. Linear regression models are developed to examine the hypothesis and path analysis. The de-pendent variable of each model is auditor performance, whereas the independent variable of model 1 is spiritual intelligence, of model 2 are emotional intelligence and spiritual intelligence. The parameters were estima...

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.

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...

Intelligence analysis – the royal discipline of Competitive Intelligence

OpenAIRE

František Bartes

2011-01-01

The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in busines...

Ensemble of hybrid genetic algorithm for two-dimensional phase unwrapping

Science.gov (United States)

Balakrishnan, D.; Quan, C.; Tay, C. J.

2013-06-01

The phase unwrapping is the final and trickiest step in any phase retrieval technique. Phase unwrapping by artificial intelligence methods (optimization algorithms) such as hybrid genetic algorithm, reverse simulated annealing, particle swarm optimization, minimum cost matching showed better results than conventional phase unwrapping methods. In this paper, Ensemble of hybrid genetic algorithm with parallel populations is proposed to solve the branch-cut phase unwrapping problem. In a single populated hybrid genetic algorithm, the selection, cross-over and mutation operators are applied to obtain new population in every generation. The parameters and choice of operators will affect the performance of the hybrid genetic algorithm. The ensemble of hybrid genetic algorithm will facilitate to have different parameters set and different choice of operators simultaneously. Each population will use different set of parameters and the offspring of each population will compete against the offspring of all other populations, which use different set of parameters. The effectiveness of proposed algorithm is demonstrated by phase unwrapping examples and advantages of the proposed method are discussed.

Validation of the Child and Adolescent Social Perception Measure.

Science.gov (United States)

Koning, Cyndie; Magill-Evans, Joyce

2001-01-01

Compared 32 adolescent boys who had social skills deficits consistent with Asperger's Disorder to 29 controls matched on age and intelligence quotient. Significant differences were found between groups on Child and Adolescent Social Perception Measure scores, and the validity of the instrument was supported. (Contains 37 references.) (JOW)

Drawing as Driver of Creativity: Nurturing an Intelligence of Seeing in Art Students

Science.gov (United States)

Riley, Howard

2017-01-01

The article reasserts the primacy of drawing as a driver of creativity within art schools. It reviews specific aspects of visual perception theory and visual communication theory relevant to a pedagogical strategy as a means of nurturing an "intelligence of seeing" in art students. The domain of drawing is theorised as a…

An Intelligent Inference System for Robot Hand Optimal Grasp Preshaping

Directory of Open Access Journals (Sweden)

Cabbar Veysel Baysal

2010-11-01

Full Text Available This paper presents a novel Intelligent Inference System (IIS for the determination of an optimum preshape for multifingered robot hand grasping, given object under a manipulation task. The IIS is formed as hybrid agent architecture, by the synthesis of object properties, manipulation task characteristics, grasp space partitioning, lowlevel kinematical analysis, evaluation of contact wrench patterns via fuzzy approximate reasoning and ANN structure for incremental learning. The IIS is implemented in software with a robot hand simulation.

Accent, Intelligibility, and the Role of the Listener: Perceptions of English-Accented German by Native German Speakers

Science.gov (United States)

Hayes-Harb, Rachel; Watzinger-Tharp, Johanna

2012-01-01

We explore the relationship between accentedness and intelligibility, and investigate how listeners' beliefs about nonnative speech interact with their accentedness and intelligibility judgments. Native German speakers and native English learners of German produced German sentences, which were presented to 12 native German speakers in accentedness…

Perceptions of University Instructors When Listening to International Student Speech

Science.gov (United States)

Sheppard, Beth; Elliott, Nancy; Baese-Berk, Melissa

2017-01-01

Intensive English Program (IEP) Instructors and content faculty both listen to international students at the university. For these two groups of instructors, this study compared perceptions of international student speech by collecting comprehensibility ratings and transcription samples for intelligibility scores. No significant differences were…

Intelligent system for accident identification in NPP; Sistema inteligente para la identificacion de accidentes en centrales nucleares

Energy Technology Data Exchange (ETDEWEB)

Hernandez, J L [Centro Nacional de Seguridad Nuclear, La Habana (Cuba)

1999-12-31

Accidental situations in NPP are great concern for operators, the facility, regulatory bodies and the environmental. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making 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 Analysis 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 from the combination of the artificial intelligence techniques fuzzy logic and artificial neural networks. The system works with variables from the process of the first 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

Modeling level change in Lake Urmia using hybrid artificial intelligence approaches

Science.gov (United States)

Esbati, M.; Ahmadieh Khanesar, M.; Shahzadi, Ali

2017-06-01

The investigation of water level fluctuations in lakes for protecting them regarding the importance of these water complexes in national and regional scales has found a special place among countries in recent years. The importance of the prediction of water level balance in Lake Urmia is necessary due to several-meter fluctuations in the last decade which help the prevention from possible future losses. For this purpose, in this paper, the performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the lake water level balance has been studied. In addition, for the training of the adaptive neuro-fuzzy inference system, particle swarm optimization (PSO) and hybrid backpropagation-recursive least square method algorithm have been used. Moreover, a hybrid method based on particle swarm optimization and recursive least square (PSO-RLS) training algorithm for the training of ANFIS structure is introduced. In order to have a more fare comparison, hybrid particle swarm optimization and gradient descent are also applied. The models have been trained, tested, and validated based on lake level data between 1991 and 2014. For performance evaluation, a comparison is made between these methods. Numerical results obtained show that the proposed methods with a reasonable error have a good performance in water level balance prediction. It is also clear that with continuing the current trend, Lake Urmia will experience more drop in the water level balance in the upcoming years.

The use of technology in the promotion of children’s emotional intelligence : the multimedia program “Developing Emotional Intelligence”

OpenAIRE

D'Amico, Antonella

2018-01-01

"Developing Emotional Intelligence” is an Italian language multimedia tool created for children between 8 and 12 years of age. The software is based on the four ‘branches’ of model of emotional intelligence proposed by Mayer and Salovey and aims to evaluate and improve abilities in perception of emotions; using emotion to facilitate thought; understanding emotions; and managing emotions. In the software, four characters represent the four branches of emotional intelligence and ...

Intelligent Facades in Buildings Facades of local Office Buildings - Case Study

Directory of Open Access Journals (Sweden)

Al-Qaraghuli Anwar Subhi

2016-01-01

Full Text Available In order to meet the functional performance and requirements on the environmental, ecological, social and aesthetical aspects, it became a necessity to develop another options of building that would be more efficient in the provision of those requirements, so a new generation have appeared called “Smart Buildings” or “Intelligent Buildings” with their sophisticated parts and various details, one of those essential parts is the “Intelligent Façade” for it’s being the essential and primary defensive line for the building against the environmental and climatic variations.This research focused on presenting the most clearly and comprehensive perception of the intelligent façades, in a manner that serves the ability of the designer to apply them in his designs or while developing an existing façades in local (Iraqi office buildings.To achieve such goal, it has been a necessity to adopt a descriptive and analytical Method for the previous knowledge and take a sequential researching steps, the first step was to build a comprehensive theoretical framework by defining the intelligent façade. Down to abstracting three main vocabularies of the theoretical framework represented by: integrated intelligent façade design, intelligent façade techniques, and effective response.The next research steps focused on applying the vocabularies of the theoretical framework on the elected local office buildings that have been adopted the matter of intelligent façades in one of their forms, and then analyze/discuss the results of the applicable study, to be able to draw the final conclusions, and by this the research presented a determined recommendations.

Web Intelligence and Artificial Intelligence in Education

Science.gov (United States)

Devedzic, Vladan

2004-01-01

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

Artificial Intelligence and Moral intelligence

Directory of Open Access Journals (Sweden)

Laura Pana

2008-07-01

Full Text Available We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined, even unpredictable conduct, 2- entities endowed with diverse or even multiple intelligence forms, like moral intelligence, 3- open and, even, free-conduct performing systems (with specific, flexible and heuristic mechanisms and procedures of decision, 4 – systems which are open to education, not just to instruction, 5- entities with “lifegraphy”, not just “stategraphy”, 6- equipped not just with automatisms but with beliefs (cognitive and affective complexes, 7- capable even of reflection (“moral life” is a form of spiritual, not just of conscious activity, 8 – elements/members of some real (corporal or virtual community, 9 – cultural beings: free conduct gives cultural value to the action of a ”natural” or artificial being. Implementation of such characteristics does not necessarily suppose efforts to design, construct and educate machines like human beings. The human moral code is irremediably imperfect: it is a morality of preference, of accountability (not of responsibility and a morality of non-liberty, which cannot be remedied by the invention of ethical systems, by the circulation of ideal values and by ethical (even computing education. But such an imperfect morality needs perfect instruments for its implementation: applications of special logic fields; efficient psychological (theoretical and technical attainments to endow the machine not just with intelligence, but with conscience and even spirit; comprehensive technical

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.

Intelligible Artificial Intelligence

OpenAIRE

Weld, Daniel S.; Bansal, Gagan

2018-01-01

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

Application of Meta-Heuristic Hybrid Artificial Intelligence Techniques for Modeling of Bonding Strength of Plywood Panels

Directory of Open Access Journals (Sweden)

Cenk Demirkır

2014-04-01

Full Text Available Plywood, which is one of the most important wood based panels, has many usage areas changing from traffic signs to building constructions in many countries. It is known that the high quality plywood panel manufacturing has been achieved with a good bonding under the optimum pressure conditions depending on adhesive type. This is a study of determining the using possibilities of modern meta-heuristic hybrid artificial intelligence techniques such as IKE and AANN methods for prediction of bonding strength of plywood panels. This study has composed of two main parts as experimental and analytical. Scots pine, maritime pine and European black pine logs were used as wood species. The pine veneers peeled at 32°C and 50°C were dried at 110°C, 140°C and 160°C temperatures. Phenol formaldehyde and melamine urea formaldehyde resins were used as adhesive types. EN 314-1 standard was used to determine the bonding shear strength values of plywood panels in experimental part of this study. Then the intuitive k-nearest neighbor estimator (IKE and adaptive artificial neural network (AANN were used to estimate bonding strength of plywood panels. The best estimation performance was obtained from MA metric for k-value=10. The most effective factor on bonding strength was determined as adhesive type. Error rates were determined less than 5% for both of the IKE and AANN. It may be recommended that proposed methods could be used in applying to estimation of bonding strength values of plywood panels.

Naturalist Intelligence Among the Other Multiple Intelligences [In Bulgarian

Directory of Open Access Journals (Sweden)

R. Genkov

2007-09-01

Full Text Available The theory of multiple intelligences was presented by Gardner in 1983. The theory was revised later (1999 and among the other intelligences a naturalist intelligence was added. The criteria for distinguishing of the different types of intelligences are considered. While Gardner restricted the analysis of the naturalist intelligence with examples from the living nature only, the present paper considered this problem on wider background including objects and persons of the natural sciences.

Artificial intelligence

CERN Document Server

Hunt, Earl B

1975-01-01

Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

Intelligence Ethics:

DEFF Research Database (Denmark)

Rønn, Kira Vrist

2016-01-01

Questions concerning what constitutes a morally justified conduct of intelligence activities have received increased attention in recent decades. However, intelligence ethics is not yet homogeneous or embedded as a solid research field. The aim of this article is to sketch the state of the art...... of intelligence ethics and point out subjects for further scrutiny in future research. The review clusters the literature on intelligence ethics into two groups: respectively, contributions on external topics (i.e., the accountability of and the public trust in intelligence agencies) and internal topics (i.......e., the search for an ideal ethical framework for intelligence actions). The article concludes that there are many holes to fill for future studies on intelligence ethics both in external and internal discussions. Thus, the article is an invitation – especially, to moral philosophers and political theorists...

#%Applications of artificial intelligence in intelligent manufacturing: a review

Institute of Scientific and Technical Information of China (English)

#

2017-01-01

#%Based on research into the applications of artificial intelligence (AI) technology in the manufacturing industry in recent years, we analyze the rapid development of core technologies in the new era of 'Internet plus AI', which is triggering a great change in the models, means, and ecosystems of the manufacturing industry, as well as in the development of AI. We then propose new models, means, and forms of intelligent manufacturing, intelligent manufacturing system architecture, and intelligent man-ufacturing technology system, based on the integration of AI technology with information communications, manufacturing, and related product technology. Moreover, from the perspectives of intelligent manufacturing application technology, industry, and application demonstration, the current development in intelligent manufacturing is discussed. Finally, suggestions for the appli-cation of AI in intelligent manufacturing in China are presented.

Intelligent Hybrid Control Strategy for Trajectory Tracking of Robot Manipulators

Directory of Open Access Journals (Sweden)

Yi Zuo

2008-01-01

Full Text Available We address the problem of robust tracking control using a PD-plus-feedforward controller and an intelligent adaptive robust compensator for a rigid robotic manipulator with uncertain dynamics and external disturbances. A key feature of this scheme is that soft computer methods are used to learn the upper bound of system uncertainties and adjust the width of the boundary layer base. In this way, the prior knowledge of the upper bound of the system uncertainties does need not to be required. Moreover, chattering can be effectively eliminated, and asymptotic error convergence can be guaranteed. Numerical simulations and experiments of two-DOF rigid robots are presented to show effectiveness of the proposed scheme.

The Multifaceted Nature of Mentors' Authentic Leadership and Mentees' Emotional Intelligence: A Critical Perspective

Science.gov (United States)

Shapira-Lishchinsky, Orly; Levy-Gazenfrantz, Tania

2016-01-01

The aim of the study was to investigate, from a critical perspective, mentees' perceptions regarding the persons they view as their influential mentors--whether they regard them as authentic leaders and whether these mentors affect the development of mentees' emotional intelligence (EI). Using a sample of 62 teacher-mentees from different school…

An Innovative Thinking-Based Intelligent Information Fusion Algorithm

Directory of Open Access Journals (Sweden)

Huimin Lu

2013-01-01

Full Text Available This study proposes an intelligent algorithm that can realize information fusion in reference to the relative research achievements in brain cognitive theory and innovative computation. This algorithm treats knowledge as core and information fusion as a knowledge-based innovative thinking process. Furthermore, the five key parts of this algorithm including information sense and perception, memory storage, divergent thinking, convergent thinking, and evaluation system are simulated and modeled. This algorithm fully develops innovative thinking skills of knowledge in information fusion and is a try to converse the abstract conception of brain cognitive science to specific and operable research routes and strategies. Furthermore, the influences of each parameter of this algorithm on algorithm performance are analyzed and compared with those of classical intelligent algorithms trough test. Test results suggest that the algorithm proposed in this study can obtain the optimum problem solution by less target evaluation times, improve optimization effectiveness, and achieve the effective fusion of information.

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.

A review on experimental design for pollutants removal in water treatment with the aid of artificial intelligence.

Science.gov (United States)

Fan, Mingyi; Hu, Jiwei; Cao, Rensheng; Ruan, Wenqian; Wei, Xionghui

2018-06-01

Water pollution occurs mainly due to inorganic and organic pollutants, such as nutrients, heavy metals and persistent organic pollutants. For the modeling and optimization of pollutants removal, artificial intelligence (AI) has been used as a major tool in the experimental design that can generate the optimal operational variables, since AI has recently gained a tremendous advance. The present review describes the fundamentals, advantages and limitations of AI tools. Artificial neural networks (ANNs) are the AI tools frequently adopted to predict the pollutants removal processes because of their capabilities of self-learning and self-adapting, while genetic algorithm (GA) and particle swarm optimization (PSO) are also useful AI methodologies in efficient search for the global optima. This article summarizes the modeling and optimization of pollutants removal processes in water treatment by using multilayer perception, fuzzy neural, radial basis function and self-organizing map networks. Furthermore, the results conclude that the hybrid models of ANNs with GA and PSO can be successfully applied in water treatment with satisfactory accuracies. Finally, the limitations of current AI tools and their new developments are also highlighted for prospective applications in the environmental protection. Copyright © 2018 Elsevier Ltd. All rights reserved.

Intelligence and psychosocial functioning during long-term growth hormone therapy in children born small for gestational age.

Science.gov (United States)

van Pareren, Yvonne K; Duivenvoorden, Hugo J; Slijper, Froukje S M; Koot, Hans M; Hokken-Koelega, Anita C S

2004-11-01

Short stature is not the only problem faced by small for gestational age (SGA) children. Being born SGA has also been associated with lowered intelligence, poor academic performance, low social competence, and behavioral problems. Although GH treatment in short children born SGA can result in a normalization of height during childhood, the effect of GH treatment on intelligence and psychosocial functioning remains to be investigated. We show the longitudinal results of a randomized, double-blind, GH-dose response study initiated in 1991 to follow growth, intelligence quotient (IQ), and psychosocial functioning in SGA children during long-term GH treatment. Patients were assigned to one of two treatment groups (1 or 2 mg GH/m(2) body surface.d, or approximately 0.035 or 0.07 mg/kg.d). Intelligence and psychosocial functioning were evaluated at start of GH treatment (n = 74), after 2 yr of GH treatment (n = 76), and in 2001 (n = 53). IQ was assessed by a short-form Wechsler Intelligence Scale for Children-Revised or Wechsler Adult Intelligence Scale (Block-design and Vocabulary subtests). Behavioral problems were measured by the Achenbach Child Behavior Checklist or Young Adult Behavior Checklist, and self-perception was measured by the Harter Self-Perception Profile. Mean (sem) birth length sd score was -3.6 (0.2), mean age and height at start was 7.4 (0.2) yr and -3.0 (0.1) sd score, respectively, mean duration of GH treatment was 8.0 (0.2) yr, and mean age in 2001 was 16.5 (0.3) yr. After 2 yr of GH treatment, 96% of both GH groups showed a height gain sd score of 1 sd from the start of treatment or more, resulting in a normal height (i.e. height >/= -2.0 sd for age and sex) in 70% of the children. In 2001, 48 (91%) of the 53 children participating in this study had reached a normal height. Block-design s-score and the estimated total IQ significantly increased (P growth in adolescents born SGA, IQ, behavior, and self-perception showed a significant improvement

Trends in ambient intelligent systems the role of computational intelligence

CERN Document Server

Khan, Mohammad; Abraham, Ajith

2016-01-01

This book demonstrates the success of Ambient Intelligence in providing possible solutions for the daily needs of humans. The book addresses implications of ambient intelligence in areas of domestic living, elderly care, robotics, communication, philosophy and others. The objective of this edited volume is to show that Ambient Intelligence is a boon to humanity with conceptual, philosophical, methodical and applicative understanding. The book also aims to schematically demonstrate developments in the direction of augmented sensors, embedded systems and behavioral intelligence towards Ambient Intelligent Networks or Smart Living Technology. It contains chapters in the field of Ambient Intelligent Networks, which received highly positive feedback during the review process. The book contains research work, with in-depth state of the art from augmented sensors, embedded technology and artificial intelligence along with cutting-edge research and development of technologies and applications of Ambient Intelligent N...

Impact of adoption of yoga way of life on the emotional intelligence of managers

Directory of Open Access Journals (Sweden)

Hasmukh Adhia

2010-03-01

Full Text Available The popular perception that a high intelligence quotient (IQ is not necessarily a good predictor of professional and personal success has led to a growing interest in understanding the role of emotional intelligence (EI in improving the performance of business managers. This paper studies the impact of the yoga way of life on EI using data collected from 60 managers in a business enterprise and reports enhanced EI as a result of the practice of yoga. The results indicate the importance of yoga as an integral element in improving managerial performance in organisations and the need to further explore this construct in greater detail.

An intelligent hybrid system for surface coal mine safety analysis

Energy Technology Data Exchange (ETDEWEB)

Lilic, N.; Obradovic, I.; Cvjetic, A. [University of Belgrade, Belgrade (Serbia)

2010-06-15

Analysis of safety in surface coal mines represents a very complex process. Published studies on mine safety analysis are usually based on research related to accidents statistics and hazard identification with risk assessment within the mining industry. Discussion in this paper is focused on the application of AI methods in the analysis of safety in mining environment. Complexity of the subject matter requires a high level of expert knowledge and great experience. The solution was found in the creation of a hybrid system PROTECTOR, whose knowledge base represents a formalization of the expert knowledge in the mine safety field. The main goal of the system is the estimation of mining environment as one of the significant components of general safety state in a mine. This global goal is subdivided into a hierarchical structure of subgoals where each subgoal can be viewed as the estimation of a set of parameters (gas, dust, climate, noise, vibration, illumination, geotechnical hazard) which determine the general mine safety state and category of hazard in mining environment. Both the hybrid nature of the system and the possibilities it offers are illustrated through a case study using field data related to an existing Serbian surface coal mine.

Speech intelligibility enhancement after maxillary denture treatment and its impact on quality of life.

Science.gov (United States)

Knipfer, Christian; Riemann, Max; Bocklet, Tobias; Noeth, Elmar; Schuster, Maria; Sokol, Biljana; Eitner, Stephan; Nkenke, Emeka; Stelzle, Florian

2014-01-01

Tooth loss and its prosthetic rehabilitation significantly affect speech intelligibility. However, little is known about the influence of speech deficiencies on oral health-related quality of life (OHRQoL). The aim of this study was to investigate whether speech intelligibility enhancement through prosthetic rehabilitation significantly influences OHRQoL in patients wearing complete maxillary dentures. Speech intelligibility by means of an automatic speech recognition system (ASR) was prospectively evaluated and compared with subjectively assessed Oral Health Impact Profile (OHIP) scores. Speech was recorded in 28 edentulous patients 1 week prior to the fabrication of new complete maxillary dentures and 6 months thereafter. Speech intelligibility was computed based on the word accuracy (WA) by means of an ASR and compared with a matched control group. One week before and 6 months after rehabilitation, patients assessed themselves for OHRQoL. Speech intelligibility improved significantly after 6 months. Subjects reported a significantly higher OHRQoL after maxillary rehabilitation with complete dentures. No significant correlation was found between the OHIP sum score or its subscales to the WA. Speech intelligibility enhancement achieved through the fabrication of new complete maxillary dentures might not be in the forefront of the patients' perception of their quality of life. For the improvement of OHRQoL in patients wearing complete maxillary dentures, food intake and mastication as well as freedom from pain play a more prominent role.

Intelligent Electric Power Systems with Active-Adaptive Electric Networks: Challenges for Simulation Tools

Directory of Open Access Journals (Sweden)

Ufa Ruslan A.

2015-01-01

Full Text Available The motivation of the presented research is based on the needs for development of new methods and tools for adequate simulation of intelligent electric power systems with active-adaptive electric networks (IES including Flexible Alternating Current Transmission System (FACTS devices. The key requirements for the simulation were formed. The presented analysis of simulation results of IES confirms the need to use a hybrid modelling approach.

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

Science.gov (United States)

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

2010-03-01

Project MLeXAI (Machine Learning eXperiences in Artificial Intelligence (AI)) seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense - a simple real-time strategy game and Checkers - a classic turn-based board game. From the instructors' prospective, we examine aspects of design and implementation as well as the challenges and rewards of using the curricula. We explore students' responses to the projects via the results of a common survey. Finally, we compare the student perceptions from the game-based projects to non-game based projects from the first phase of Project MLeXAI.

Neuro-Fuzzy Prediction of Cooperation Interaction Profile of Flexible Road Train Based on Hybrid Automaton Modeling

Directory of Open Access Journals (Sweden)

Banjanovic-Mehmedovic Lejla

2016-01-01

Full Text Available Accurate prediction of traffic information is important in many applications in relation to Intelligent Transport systems (ITS, since it reduces the uncertainty of future traffic states and improves traffic mobility. There is a lot of research done in the field of traffic information predictions such as speed, flow and travel time. The most important research was done in the domain of cooperative intelligent transport system (C-ITS. The goal of this paper is to introduce the novel cooperation behaviour profile prediction through the example of flexible Road Trains useful road cooperation parameter, which contributes to the improvement of traffic mobility in Intelligent Transportation Systems. This paper presents an approach towards the control and cooperation behaviour modelling of vehicles in the flexible Road Train based on hybrid automaton and neuro-fuzzy (ANFIS prediction of cooperation profile of the flexible Road Train. Hybrid automaton takes into account complex dynamics of each vehicle as well as discrete cooperation approach. The ANFIS is a particular class of the ANN family with attractive estimation and learning potentials. In order to provide statistical analysis, RMSE (root mean square error, coefficient of determination (R2 and Pearson coefficient (r, were utilized. The study results suggest that ANFIS would be an efficient soft computing methodology, which could offer precise predictions of cooperative interactions between vehicles in Road Train, which is useful for prediction mobility in Intelligent Transport systems.

Advanced intelligent systems

CERN Document Server

Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul

2014-01-01

Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...

Optimized Hybrid Renewable Energy System of Isolated Islands in Smart-Grid Scenario - A Case Study in Indian Context

OpenAIRE

Aurobi Das; V. Balakrishnan

2012-01-01

This paper focuses on the integration of hybrid renewable energy resources available in remote isolated islands of Sundarban-24 Parganas-South of Eastern part of India to National Grid of conventional power supply to give a Smart-Grid scenario. Before grid-integration, feasibility of optimization of hybrid renewable energy system is monitored through an Intelligent Controller proposed to be installed at Moushuni Island of Sundarban. The objective is to ensure the reliability and efficiency of...

Competitive Intelligence.

Science.gov (United States)

Bergeron, Pierrette; Hiller, Christine A.

2002-01-01

Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…

A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

Directory of Open Access Journals (Sweden)

P. Amudha

2015-01-01

Full Text Available Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC with Enhanced Particle Swarm Optimization (EPSO to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup’99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different.

Visuospatial perception in children born preterm with no major neurological disorders.

Science.gov (United States)

Butcher, Phillipa R; Bouma, Anke; Stremmelaar, Elisabeth F; Bos, Arend F; Smithson, Michael; Van Braeckel, Koenraad N J A

2012-11-01

Many investigations have found deficits in visuospatial perception in children born preterm, however, it is not clear whether the deficits are specific to visuospatial perception or the consequences of deficits in other functional areas, which often accompany preterm birth. This study investigated whether children born preterm show a specific deficit in visuospatial perception. Fifty-six 7- to 11-year-old preterm born children (gestational age children completed four computerized tasks tapping different levels and types of visuospatial perception. Accuracy and speed of responses were recorded. Task formats were designed to reduce demands on attentional deployment. Measures of intelligence and parental education were included in the analysis. Children born preterm performed less accurately and/or less rapidly on all tasks. Their poorer performance did not reflect differences in speed-accuracy trade-off. Parental education and IQ, both significantly lower in the preterm children, contributed positively to performance on all tasks. IQ mediated the association between preterm birth and visuospatial performance on the most cognitively demanding task. Children born preterm performed more poorly than full-term controls on four visuospatial perceptual tasks. Although intelligence and parental education were also associated with performance, preterm birth contributed independently of these factors on three of four tasks. Many children born preterm are thus multiply disadvantaged on visuospatial tasks: the lower IQ scores and parental educational levels frequently found in this group increase the deficit associated with preterm birth. (c) 2012 APA, all rights reserved.

Recent advances in knowledge-based paradigms and applications enhanced applications using hybrid artificial intelligence techniques

CERN Document Server

Jain, Lakhmi

2014-01-01

This book presents carefully selected contributions devoted to the modern perspective of AI research and innovation. This collection covers several areas of applications and motivates new research directions. The theme across all chapters combines several domains of AI research , Computational Intelligence and Machine Intelligence including an introduction to  the recent research and models. Each of the subsequent chapters reveals leading edge research and innovative solution that employ AI techniques with an applied perspective. The problems include classification of spatial images, early smoke detection in outdoor space from video images, emergent segmentation from image analysis, intensity modification in images, multi-agent modeling and analysis of stress. They all are novel pieces of work and demonstrate how AI research contributes to solutions for difficult real world problems that benefit the research community, industry and society.

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

Science.gov (United States)

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

2018-01-01

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

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

Directory of Open Access Journals (Sweden)

Kun Guo

2018-04-01

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

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

Science.gov (United States)

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

2018-04-26

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

A Hybrid Three Layer Architecture for Fire Agent Management in Rescue Simulation Environment

Directory of Open Access Journals (Sweden)

Alborz Geramifard

2005-06-01

Full Text Available This paper presents a new architecture called FAIS for implementing intelligent agents cooperating in a special Multi Agent environment, namely the RoboCup Rescue Simulation System. This is a layered architecture which is customized for solving fire extinguishing problem. Structural decision making algorithms are combined with heuristic ones in this model, so it's a hybrid architecture.

Improvement of intelligibility of ideal binary-masked noisy speech by adding background noise.

Science.gov (United States)

Cao, Shuyang; Li, Liang; Wu, Xihong

2011-04-01

When a target-speech/masker mixture is processed with the signal-separation technique, ideal binary mask (IBM), intelligibility of target speech is remarkably improved in both normal-hearing listeners and hearing-impaired listeners. Intelligibility of speech can also be improved by filling in speech gaps with un-modulated broadband noise. This study investigated whether intelligibility of target speech in the IBM-treated target-speech/masker mixture can be further improved by adding a broadband-noise background. The results of this study show that following the IBM manipulation, which remarkably released target speech from speech-spectrum noise, foreign-speech, or native-speech masking (experiment 1), adding a broadband-noise background with the signal-to-noise ratio no less than 4 dB significantly improved intelligibility of target speech when the masker was either noise (experiment 2) or speech (experiment 3). The results suggest that since adding the noise background shallows the areas of silence in the time-frequency domain of the IBM-treated target-speech/masker mixture, the abruption of transient changes in the mixture is smoothed and the perceived continuity of target-speech components becomes enhanced, leading to improved target-speech intelligibility. The findings are useful for advancing computational auditory scene analysis, hearing-aid/cochlear-implant designs, and understanding of speech perception under "cocktail-party" conditions.

The SP Theory of Intelligence: An Overview

Directory of Open Access Journals (Sweden)

J Gerard Wolff

2013-08-01

Full Text Available This article is an overview of the SP theory of intelligence, which aims to simplify and integrate concepts across artificial intelligence, mainstream computing and human perception and cognition, with information compression as a unifying theme. It is conceived of as a brain-like system that receives "New" information and stores some or all of it in compressed form as "Old" information; and it is realised in the form of a computer model, a first version of the SP machine. The matching and unification of patterns and the concept of multiple alignment are central ideas. Using heuristic techniques, the system builds multiple alignments that are "good" in terms of information compression. For each multiple alignment, probabilities may be calculated for associated inferences. Unsupervised learning is done by deriving new structures from partial matches between patterns and via heuristic search for sets of structures that are "good" in terms of information compression. These are normally ones that people judge to be "natural", in accordance with the "DONSVIC" principle—the discovery of natural structures via information compression. The SP theory provides an interpretation for concepts and phenomena in several other areas, including "computing", aspects of mathematics and logic, the representation of knowledge, natural language processing, pattern recognition, several kinds of reasoning, information storage and retrieval, planning and problem solving, information compression, neuroscience and human perception and cognition. Examples include the parsing and production of language with discontinuous dependencies in syntax, pattern recognition at multiple levels of abstraction and its integration with part-whole relations, nonmonotonic reasoning and reasoning with default values, reasoning in Bayesian networks, including "explaining away", causal diagnosis, and the solving of a geometric analogy problem.

Visualization of E-commerce Transaction Data : USING BUSINESS INTELLIGENCE TOOLS

OpenAIRE

Safari, Arash

2015-01-01

Customer Value(CV) is a data analytics company experiencing problems presenting the result of their analytics in a satisfiable manner. As a result, they considered the use of a data visualization and business intelligence softwares. The purpose of such softwares are to, amongst other things, virtually represent data in an interactive and perceptible manner to the viewer. There are however a large number of these types of applications on the market, making it hard for companies to find the one...

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

Hybrid cognitive engine for radio systems adaptation

KAUST Repository

Alqerm, Ismail

2017-07-20

Network efficiency and proper utilization of its resources are essential requirements to operate wireless networks in an optimal fashion. Cognitive radio aims to fulfill these requirements by exploiting artificial intelligence techniques to create an entity called cognitive engine. Cognitive engine exploits awareness about the surrounding radio environment to optimize the use of radio resources and adapt relevant transmission parameters. In this paper, we propose a hybrid cognitive engine that employs Case Based Reasoning (CBR) and Decision Trees (DTs) to perform radio adaptation in multi-carriers wireless networks. The engine complexity is reduced by employing DTs to improve the indexing methodology used in CBR cases retrieval. The performance of our hybrid engine is validated using software defined radios implementation and simulation in multi-carrier environment. The system throughput, signal to noise and interference ratio, and packet error rate are obtained and compared with other schemes in different scenarios.

Intelligent emission-sensitive routing for plugin hybrid electric vehicles.

Science.gov (United States)

Sun, Zhonghao; Zhou, Xingshe

2016-01-01

The existing transportation sector creates heavily environmental impacts and is a prime cause for the current climate change. The need to reduce emissions from this sector has stimulated efforts to speed up the application of electric vehicles (EVs). A subset of EVs, called plug-in hybrid electric vehicles (PHEVs), backup batteries with combustion engine, which makes PHEVs have a comparable driving range to conventional vehicles. However, this hybridization comes at a cost of higher emissions than all-electric vehicles. This paper studies the routing problem for PHEVs to minimize emissions. The existing shortest-path based algorithms cannot be applied to solving this problem, because of the several new challenges: (1) an optimal route may contain circles caused by detour for recharging; (2) emissions of PHEVs not only depend on the driving distance, but also depend on the terrain and the state of charge (SOC) of batteries; (3) batteries can harvest energy by regenerative braking, which makes some road segments have negative energy consumption. To address these challenges, this paper proposes a green navigation algorithm (GNA) which finds the optimal strategies: where to go and where to recharge. GNA discretizes the SOC, then makes the PHEV routing problem to satisfy the principle of optimality. Finally, GNA adopts dynamic programming to solve the problem. We evaluate GNA using synthetic maps generated by the delaunay triangulation. The results show that GNA can save more than 10 % energy and reduce 10 % emissions when compared to the shortest path algorithm. We also observe that PHEVs with the battery capacity of 10-15 KWh detour most and nearly no detour when larger than 30 KWh. This observation gives some insights when developing PHEVs.

Impact of emotional intelligence and spiritual intelligence on the caring behavior of nurses: a dimension-level exploratory study among public hospitals in Malaysia.

Science.gov (United States)

Kaur, Devinder; Sambasivan, Murali; Kumar, Naresh

2015-11-01

The purpose of this research is to study the impact of individual factors such as emotional intelligence (EI) and spiritual intelligence (SI) on the caring behavior of nurses. A cross-sectional survey using questionnaire was conducted by sampling 550 nurses working in seven major public hospitals in Malaysia. Data were analyzed using structural equation modeling (SEM). The main findings are: (1) critical existential thinking and transcendental awareness dimensions of SI have significant impacts on assurance of human presence dimension of caring behavior; (2) personal meaning production and conscious state expansion dimensions of SI have significant impacts on perception of emotion and managing own emotions dimensions of EI; and (3) managing own emotions dimension of EI has significant impacts on respectful deference to other and assurance of human presence dimensions of caring behavior of nurses. The results can be used to recruit and educate nurses. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Intelligent control system for nuclear power plant mobile robot

International Nuclear Information System (INIS)

Koenig, A.; Lecoeur-Taibi, I.; Crochon, E.; Vacherand, F.

1991-01-01

In order to fully optimize the efficiency of the perception and navigation components available on a mobile robot, the upper level of a mobile robot control requires intelligence support to unload the work of the teleoperator. This knowledge-based system has to manage a priori data such as the map of the workspace, the mission, the characteristics of sensors and robot, but also, the current environment state and the running mission. It has to issue a plan to drive the sensors to focus on relevant objects or to scan the environment and to select the best algorithms depending on the current situation. The environment workspace is a nuclear power plant building. The teleoperated robot is a mobile wheeled or legged vehicle that moves inside the different floors of the building. There are three types of mission: radio-activity survey, inspection and intervention. To perform these goals the robot must avoid obstacles, pass through doors, possibly climb stairs and recognize valves and pipes. The perception control system has to provide the operator with a synthetic view of the surroundings. It manages background tasks such as obstacle detection and free space map building, and specific tasks such as beacon recognition for odometry relocalization and valve detection for maintenance. To do this, the system solves perception resources conflicts, taking into account the current states of the sensors and the current conditions such as lightness or darkness, cluttered scenes, sensor failure. A perception plan is issued from the mission goals, planned path, relocalization requirements and available perception resources. Basically, the knowledge-based system is implemented on a blackboard architecture which includes two parts: a top-down planning part and a bottom-up perception part. The results of the perception are continuously sent to the operator who can trigger new perception actions. (author)

An Artificial Intelligence Approach for Gears Diagnostics in AUVs.

Science.gov (United States)

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

2016-04-12

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

An Artificial Intelligence Approach for Gears Diagnostics in AUVs

Directory of Open Access Journals (Sweden)

Graciliano Nicolás Marichal

2016-04-01

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

The Effects of Taekwondo Training on Brain Connectivity and Body Intelligence.

Science.gov (United States)

Kim, Young Jae; Cha, Eun Joo; Kim, Sun Mi; Kang, Kyung Doo; Han, Doug Hyun

2015-07-01

Many studies have reported that Taekwondo training could improve body perception, control and brain activity, as assessed with an electroencephalogram. This study aimed to assess body intelligence and brain connectivity in children with Taekwondo training as compared to children without Taekwondo training. Fifteen children with Taekwondo training (TKD) and 13 age- and sex-matched children who had no previous experience of Taekwondo training (controls) were recruited. Body intelligence, clinical characteristics and brain connectivity in all children were assessed with the Body Intelligence Scale (BIS), self-report, and resting state functional magnetic resonance imaging. The mean BIS score in the TKD group was higher than that in the control group. The TKD group showed increased low-frequency fluctuations in the right frontal precentral gyrus and the right parietal precuneus, compared to the control group. The TKD group showed positive cerebellum vermis (lobe VII) seed to the right frontal, left frontal, and left parietal lobe. The control group showed positive cerebellum seed to the left frontal, parietal, and occipital cortex. Relative to the control group, the TKD group showed increased functional connectivity from cerebellum seed to the right inferior frontal gyrus. To the best of our knowledge, this is the first study to assess the effect of Taekwondo training on brain connectivity in children. Taekwondo training improved body intelligence and brain connectivity from the cerebellum to the parietal and frontal cortex.

Combined Intelligent Control (CIC an Intelligent Decision Making Algorithm

Directory of Open Access Journals (Sweden)

Moteaal Asadi Shirzi

2007-03-01

Full Text Available The focus of this research is to introduce the concept of combined intelligent control (CIC as an effective architecture for decision-making and control of intelligent agents and multi-robot sets. Basically, the CIC is a combination of various architectures and methods from fields such as artificial intelligence, Distributed Artificial Intelligence (DAI, control and biological computing. Although any intelligent architecture may be very effective for some specific applications, it could be less for others. Therefore, CIC combines and arranges them in a way that the strengths of any approach cover the weaknesses of others. In this paper first, we introduce some intelligent architectures from a new aspect. Afterward, we offer the CIC by combining them. CIC has been executed in a multi-agent set. In this set, robots must cooperate to perform some various tasks in a complex and nondeterministic environment with a low sensory feedback and relationship. In order to investigate, improve, and correct the combined intelligent control method, simulation software has been designed which will be presented and considered. To show the ability of the CIC algorithm as a distributed architecture, a central algorithm is designed and compared with the CIC.

Hybrid soft computing systems for electromyographic signals analysis: a review.

Science.gov (United States)

Xie, Hong-Bo; Guo, Tianruo; Bai, Siwei; Dokos, Socrates

2014-02-03

Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis.

Intelligence and negotiating

International Nuclear Information System (INIS)

George, D.G.

1990-01-01

This paper discusses the role of US intelligence during arms control negotiations between 1982 and 1987. It also covers : the orchestration of intelligence projects; an evaluation of the performance of intelligence activities; the effect intelligence work had on actual arms negotiations; and suggestions for improvements in the future

Validation of an "Intelligent Mouthguard" Single Event Head Impact Dosimeter.

Science.gov (United States)

Bartsch, Adam; Samorezov, Sergey; Benzel, Edward; Miele, Vincent; Brett, Daniel

2014-11-01

Dating to Colonel John Paul Stapp MD in 1975, scientists have desired to measure live human head impacts with accuracy and precision. But no instrument exists to accurately and precisely quantify single head impact events. Our goal is to develop a practical single event head impact dosimeter known as "Intelligent Mouthguard" and quantify its performance on the benchtop, in vitro and in vivo. In the Intelligent Mouthguard hardware, limited gyroscope bandwidth requires an algorithm-based correction as a function of impact duration. After we apply gyroscope correction algorithm, Intelligent Mouthguard results at time of CG linear acceleration peak correlate to the Reference Hybrid III within our tested range of pulse durations and impact acceleration profiles in American football and Boxing in vitro tests: American football, IMG=1.00REF-1.1g, R2=0.99; maximum time of peak XYZ component imprecision 3.6g and 370 rad/s2; maximum time of peak azimuth and elevation imprecision 4.8° and 2.9°; maximum average XYZ component temporal imprecision 3.3g and 390 rad/s2. Boxing, IMG=1.00REF-0.9 g, R2=0.99, R2=0.98; maximum time of peak XYZ component imprecision 3.9 g and 390 rad/s2, maximum time of peak azimuth and elevation imprecision 2.9° and 2.1°; average XYZ component temporal imprecision 4.0 g and 440 rad/s2. In vivo Intelligent Mouthguard true positive head impacts from American football players and amateur boxers have temporal characteristics (first harmonic frequency from 35 Hz to 79 Hz) within our tested benchtop (first harmonic frequencyIntelligent Mouthguard qualifies as a single event dosimeter in American football and Boxing.

Perception of preference and risk-taking in laparoscopy, transgastric, and rigid-hybrid transvaginal NOTES for cholecystectomy.

Science.gov (United States)

Sulz, Michael C; Zerz, Andreas; Sagmeister, Markus; Roll, Thomas; Meyenberger, Christa

2013-12-03

Few data are available regarding patients' perceptions of new cholecystectomy (CC) techniques, in the context of the patients' risk behaviours. We investigated patients' preferences for transgastric pure natural orifice translumenal endoscopic surgery (NOTES; transgastric NCC) and rigid-hybrid transvaginal NOTES CC (tvNCC) compared with the standard laparoscopic CC (SL-CC), and patients' risk behaviours. A total of 140 inpatients scheduled for elective laparoscopic CC were enrolled in this prospective single-centre study, from January 2009 to January 2010. Patients judged the potential advantages and disadvantages of transgastric NCC and tvNCC compared with SL-CC. The individual's risk behaviour was analysed by means of the validated 40-item Domain-Specific Risk Attitude Scale (DOSPERT). Of the 140 recruited patients, 57 (65% females; mean age 51.5 years) were analysed. Twenty-five percent of males opted for transgastric NCC and 75% opted for SL-CC. Among females, 10.8%, 37.8% and 51.4% opted for transgastric NCC, tvNCC and SL-CC, respectively. Faster convalescence was graded as the primary potential advantage of transgastric NCC, whereas the potential risk of long-term stomach injuries was considered a primary disadvantage. Females graded the reduction of hospital-acquired morbidity as the primary advantage of tvNCC. The risk assessment showed significantly more risk-taking behaviour in the recreational domain of life among patients who opted for innovative surgical techniques than among those opting for conventional surgery. Transgastric NCC is rarely accepted by females but accepted by a quarter of males. Females consider rigid-hybrid tvNCC and SL-CC similarly attractive. Despite promising new techniques, three-quarters of male and one half of female patients still prefer the standard laparoscopic CC.

Intelligence and childlessness.

Science.gov (United States)

Kanazawa, Satoshi

2014-11-01

Demographers debate why people have children in advanced industrial societies where children are net economic costs. From an evolutionary perspective, however, the important question is why some individuals choose not to have children. Recent theoretical developments in evolutionary psychology suggest that more intelligent individuals may be more likely to prefer to remain childless than less intelligent individuals. Analyses of the National Child Development Study show that more intelligent men and women express preference to remain childless early in their reproductive careers, but only more intelligent women (not more intelligent men) are more likely to remain childless by the end of their reproductive careers. Controlling for education and earnings does not at all attenuate the association between childhood general intelligence and lifetime childlessness among women. One-standard-deviation increase in childhood general intelligence (15 IQ points) decreases women's odds of parenthood by 21-25%. Because women have a greater impact on the average intelligence of future generations, the dysgenic fertility among women is predicted to lead to a decline in the average intelligence of the population in advanced industrial nations. Copyright © 2014 Elsevier Inc. All rights reserved.

A Hybrid Model for Forecasting Sales in Turkish Paint Industry

OpenAIRE

Alp Ustundag

2009-01-01

Sales forecasting is important for facilitating effective and efficient allocation of scarce resources. However, how to best model and forecast sales has been a long-standing issue. There is no best forecasting method that is applicable in all circumstances. Therefore, confidence in the accuracy of sales forecasts is achieved by corroborating the results using two or more methods. This paper proposes a hybrid forecasting model that uses an artificial intelligence method (AI) w...

Hybrid Turbine Electric Vehicle

Science.gov (United States)

Viterna, Larry A.

1997-01-01

Hybrid electric power trains may revolutionize today's ground passenger vehicles by significantly improving fuel economy and decreasing emissions. The NASA Lewis Research Center is working with industry, universities, and Government to develop and demonstrate a hybrid electric vehicle. Our partners include Bowling Green State University, the Cleveland Regional Transit Authority, Lincoln Electric Motor Division, the State of Ohio's Department of Development, and Teledyne Ryan Aeronautical. The vehicle will be a heavy class urban transit bus offering double the fuel economy of today's buses and emissions that are reduced to 1/10th of the Environmental Protection Agency's standards. At the heart of the vehicle's drive train is a natural-gas-fueled engine. Initially, a small automotive engine will be tested as a baseline. This will be followed by the introduction of an advanced gas turbine developed from an aircraft jet engine. The engine turns a high-speed generator, producing electricity. Power from both the generator and an onboard energy storage system is then provided to a variable-speed electric motor attached to the rear drive axle. An intelligent power-control system determines the most efficient operation of the engine and energy storage system.

Body satisfaction, emotional intelligence, and the development of disturbed eating: a survey of Taiwanese students.

Science.gov (United States)

Wong, Yueching; Lin, Jing-Shan; Chang, Yu-Jhen

2014-01-01

This study explored the relationship between adolescents' emotional intelligence and the tendency to develop an eating disorder. Senior high school students in Taiwan were recruited for the study. A 3- part anonymous questionnaire measured demographic information, body weight satisfaction, and expectation of body weight. Students also completed the Adolescent Emotional Intelligence Scale and the Eating Disorders Attitude- 26 Test (EAT-26). Height and weight were also measured. The mean of EAT-26 score was 8.66 ± 7.36, and 8.6% students were at high risk to develop eating disorders. Gender, body weight, body dissatisfaction and the expected body shape were significantly related to disturbed eating attitudes and behaviours. Scores of EAT-26 were positively correlated with emotional perception, emotional expression, and emotional application. Disturbed eating behaviours exist among adolescents in Taiwan, and these behaviours may be related to emotional intelligence. However further studies with larger samples are needed.

Artificial Intelligence.

Science.gov (United States)

Information Technology Quarterly, 1985

1985-01-01

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

The impact of emotional intelligence on work engagement of registered nurses: the mediating role of organisational justice.

Science.gov (United States)

Zhu, Yun; Liu, Congcong; Guo, Bingmei; Zhao, Lin; Lou, Fenglan

2015-08-01

To explore the impact of emotional intelligence and organisational justice on work engagement in Chinese nurses and to examine the mediating role of organisational justice to provide implications for promoting clinical nurses' work engagement. The importance of work engagement on nurses' well-being and quality of care has been well documented. Work engagement is significantly predicted by job resources. However, little research has concentrated simultaneously on the influence of both personal and organisational resources on nurses' work engagement. A descriptive, cross-sectional design was employed. A total of 511 nurses from four public hospitals were enrolled by multistage sampling. Data collection was undertaken using the Wong and Law Emotional Intelligence Scale, the Organizational Justice questionnaire and the Utrecht Work Engagement Scale-9. We analysed the data using structural equation modelling. Emotional intelligence and organisational justice were significant predictors and they accounted for 44% of the variance in nurses' work engagement. Bootstrap estimation confirmed an indirect effect of emotional intelligence on work engagement via organisational justice. Emotional intelligence and organisational justice positively predict work engagement and organisational justice partially mediates the relationship between emotional intelligence and work engagement. Our study supports the idea that enhancing organisational justice can increase the impact of emotional intelligence. Managers should take into account the importance of emotional intelligence and perceptions of organisational justice in human resources management and apply targeted interventions to foster work engagement. © 2015 John Wiley & Sons Ltd.

Self-Assessing of the Emotional Intelligence and Organizational Intelligence in Schools

Science.gov (United States)

Dagiene, Valentina; Juškeviciene, Anita; Carneiro, Roberto; Child, Camilla; Cullen, Joe

2015-01-01

The paper presents the results of an evaluation of the Emotional Intelligence (EI) and Organisational Intelligence (OI) competences self-assessment tools developed and applied by the IGUANA project. In the paper Emotional Intelligence and Organisational Intelligence competences are discussed, their use in action research experiments to assess and…

Enhanced perceptual functioning in autism: an update, and eight principles of autistic perception.

Science.gov (United States)

Mottron, Laurent; Dawson, Michelle; Soulières, Isabelle; Hubert, Benedicte; Burack, Jake

2006-01-01

We propose an "Enhanced Perceptual Functioning" model encompassing the main differences between autistic and non-autistic social and non-social perceptual processing: locally oriented visual and auditory perception, enhanced low-level discrimination, use of a more posterior network in "complex" visual tasks, enhanced perception of first order static stimuli, diminished perception of complex movement, autonomy of low-level information processing toward higher-order operations, and differential relation between perception and general intelligence. Increased perceptual expertise may be implicated in the choice of special ability in savant autistics, and in the variability of apparent presentations within PDD (autism with and without typical speech, Asperger syndrome) in non-savant autistics. The overfunctioning of brain regions typically involved in primary perceptual functions may explain the autistic perceptual endophenotype.

Transient and sustained cortical activity elicited by connected speech of varying intelligibility

Directory of Open Access Journals (Sweden)

Tiitinen Hannu

2012-12-01

Full Text Available Abstract Background The robustness of speech perception in the face of acoustic variation is founded on the ability of the auditory system to integrate the acoustic features of speech and to segregate them from background noise. This auditory scene analysis process is facilitated by top-down mechanisms, such as recognition memory for speech content. However, the cortical processes underlying these facilitatory mechanisms remain unclear. The present magnetoencephalography (MEG study examined how the activity of auditory cortical areas is modulated by acoustic degradation and intelligibility of connected speech. The experimental design allowed for the comparison of cortical activity patterns elicited by acoustically identical stimuli which were perceived as either intelligible or unintelligible. Results In the experiment, a set of sentences was presented to the subject in distorted, undistorted, and again in distorted form. The intervening exposure to undistorted versions of sentences rendered the initially unintelligible, distorted sentences intelligible, as evidenced by an increase from 30% to 80% in the proportion of sentences reported as intelligible. These perceptual changes were reflected in the activity of the auditory cortex, with the auditory N1m response (~100 ms being more prominent for the distorted stimuli than for the intact ones. In the time range of auditory P2m response (>200 ms, auditory cortex as well as regions anterior and posterior to this area generated a stronger response to sentences which were intelligible than unintelligible. During the sustained field (>300 ms, stronger activity was elicited by degraded stimuli in auditory cortex and by intelligible sentences in areas posterior to auditory cortex. Conclusions The current findings suggest that the auditory system comprises bottom-up and top-down processes which are reflected in transient and sustained brain activity. It appears that analysis of acoustic features occurs

Nexus between Intelligence Education and Intelligence Training: A South African Perspective

Directory of Open Access Journals (Sweden)

M. A. van den Berg

2015-10-01

Full Text Available This paper examines the nexus of intelligence education and training from a South African perspective with the focus on current practices in light of the country’s transition towards democracy. A brief overview is provided on the history and development of the South African intelligence community with specific focus on the civilian intelligence services from the period prior 1994 to date (2015. The main focus, however, is on intelligence education that is currently available from training institutions and universities in South Africa as registered with the Department of Higher Education as well as private training institutions on the one hand, and the intelligence training practices within the statutory intelligence environment on the other. To this extent, the relations between academic institutions and the intelligence structures in terms of education and training within South Africa are perused against other practices within the African continent and internationally. The approaches to the study of intelligence are also addressed within this paper. Likewise, the how, what as well as to whom – pertaining to intelligence education and training availability and accessibility to students and practitioners within South Africa, is reviewed and analysed with the focus on making recommendations for the enhancement and improvement thereof to enable a focus on preparing the next generation of professional intelligence officers.

A Hybrid Three Layer Architecture for Fire Agent Management in Rescue Simulation Environment

Directory of Open Access Journals (Sweden)

Alborz Geramifard

2008-11-01

Full Text Available This paper presents a new architecture called FAIS for imple- menting intelligent agents cooperating in a special Multi Agent environ- ment, namely the RoboCup Rescue Simulation System. This is a layered architecture which is customized for solving fire extinguishing problem. Structural decision making algorithms are combined with heuristic ones in this model, so it's a hybrid architecture.

Quantifying the effect of disruptions to temporal coherence on the intelligibility of compressed American Sign Language video

Science.gov (United States)

Ciaramello, Frank M.; Hemami, Sheila S.

2009-02-01

Communication of American Sign Language (ASL) over mobile phones would be very beneficial to the Deaf community. ASL video encoded to achieve the rates provided by current cellular networks must be heavily compressed and appropriate assessment techniques are required to analyze the intelligibility of the compressed video. As an extension to a purely spatial measure of intelligibility, this paper quantifies the effect of temporal compression artifacts on sign language intelligibility. These artifacts can be the result of motion-compensation errors that distract the observer or frame rate reductions. They reduce the the perception of smooth motion and disrupt the temporal coherence of the video. Motion-compensation errors that affect temporal coherence are identified by measuring the block-level correlation between co-located macroblocks in adjacent frames. The impact of frame rate reductions was quantified through experimental testing. A subjective study was performed in which fluent ASL participants rated the intelligibility of sequences encoded at a range of 5 different frame rates and with 3 different levels of distortion. The subjective data is used to parameterize an objective intelligibility measure which is highly correlated with subjective ratings at multiple frame rates.

Deploying swarm intelligence in medical imaging identifying metastasis, micro-calcifications and brain image segmentation.

Science.gov (United States)

al-Rifaie, Mohammad Majid; Aber, Ahmed; Hemanth, Duraiswamy Jude

2015-12-01

This study proposes an umbrella deployment of swarm intelligence algorithm, such as stochastic diffusion search for medical imaging applications. After summarising the results of some previous works which shows how the algorithm assists in the identification of metastasis in bone scans and microcalcifications on mammographs, for the first time, the use of the algorithm in assessing the CT images of the aorta is demonstrated along with its performance in detecting the nasogastric tube in chest X-ray. The swarm intelligence algorithm presented in this study is adapted to address these particular tasks and its functionality is investigated by running the swarms on sample CT images and X-rays whose status have been determined by senior radiologists. In addition, a hybrid swarm intelligence-learning vector quantisation (LVQ) approach is proposed in the context of magnetic resonance (MR) brain image segmentation. The particle swarm optimisation is used to train the LVQ which eliminates the iteration-dependent nature of LVQ. The proposed methodology is used to detect the tumour regions in the abnormal MR brain images.

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

A study of relationship between emotional intelligence and innovative work behavior of managers

Directory of Open Access Journals (Sweden)

Mohammad Reza Shojaei

2014-07-01

Full Text Available This paper studies the relationship between emotional intelligence and its components, self-awareness, self-management, social-awareness and relationship-management, with managers’ innovative work behavior. The research statistical population includes 100 managers of private bank branches in the city of Tehran selected with the random sampling method. The research type is descriptive-correlation. The tool for data aggregation is comprised of two questionnaires of emotional intelligence by Bradberry and Greaves (2006 [Bradberry, T., & Greaves, J. (2006. The emotional intelligence quick book: Everything you need to know to put your EQ to work. Simon and Schuster.] and innovative work behavior based on the studies of Janssen (2000 [Janssen, O. (2000. Job demands, perceptions of effort‐reward fairness and innovative work behaviour. Journal of Occupational and organizational psychology, 73(3, 287-302.]. The Pearson correlation coefficient and multiple regression analysis have been used for data analysis. The results indicated that there was a positive and significant relationship between emotional intelligence and its components with innovative work behavior of managers. In addition, regression analysis showed that the self-management variable had the highest effect in estimating the managers’ innovative work behavior followed by relationship-management, self-awareness and social-awareness.

Visual perception and frontal lobe in intellectual disabilities: a study with evoked potentials and neuropsychology.

Science.gov (United States)

Muñoz-Ruata, J; Caro-Martínez, E; Martínez Pérez, L; Borja, M

2010-12-01

Perception disorders are frequently observed in persons with intellectual disability (ID) and their influence on cognition has been discussed. The objective of this study is to clarify the mechanisms behind these alterations by analysing the visual event related potentials early component, the N1 wave, which is related to perception alterations in several pathologies. Additionally, the relationship between N1 and neuropsychological visual tests was studied with the aim to understand its functional significance in ID persons. A group of 69 subjects, with etiologically heterogeneous mild ID, performed an odd-ball task of active discrimination of geometric figures. N1a (frontal) and N1b (post-occipital) waves were obtained from the evoked potentials. They also performed several neuropsychological tests. Only component N1a, produced by the target stimulus, showed significant correlations with the visual integration, visual semantic association, visual analogical reasoning tests, Perceptual Reasoning Index (Wechsler Intelligence Scale for Children Fourth Edition) and intelligence quotient. The systematic correlations, produced by the target stimulus in perceptual abilities tasks, with the N1a (frontal) and not with N1b (posterior), suggest that the visual perception process involves frontal participation. These correlations support the idea that the N1a and N1b are not equivalent. The relationship between frontal functions and early stages of visual perception is revised and discussed, as well as the frontal contribution with the neuropsychological tests used. A possible relationship between the frontal activity dysfunction in ID and perceptive problems is suggested. Perceptive alteration observed in persons with ID could indeed be because of altered sensory areas, but also to a failure in the frontal participation of perceptive processes conceived as elaborations inside reverberant circuits of perception-action. © 2010 The Authors. Journal of Intellectual Disability

Hybrid Modeling Improves Health and Performance Monitoring

Science.gov (United States)

2007-01-01

Scientific Monitoring Inc. was awarded a Phase I Small Business Innovation Research (SBIR) project by NASA's Dryden Flight Research Center to create a new, simplified health-monitoring approach for flight vehicles and flight equipment. The project developed a hybrid physical model concept that provided a structured approach to simplifying complex design models for use in health monitoring, allowing the output or performance of the equipment to be compared to what the design models predicted, so that deterioration or impending failure could be detected before there would be an impact on the equipment's operational capability. Based on the original modeling technology, Scientific Monitoring released I-Trend, a commercial health- and performance-monitoring software product named for its intelligent trending, diagnostics, and prognostics capabilities, as part of the company's complete ICEMS (Intelligent Condition-based Equipment Management System) suite of monitoring and advanced alerting software. I-Trend uses the hybrid physical model to better characterize the nature of health or performance alarms that result in "no fault found" false alarms. Additionally, the use of physical principles helps I-Trend identify problems sooner. I-Trend technology is currently in use in several commercial aviation programs, and the U.S. Air Force recently tapped Scientific Monitoring to develop next-generation engine health-management software for monitoring its fleet of jet engines. Scientific Monitoring has continued the original NASA work, this time under a Phase III SBIR contract with a joint NASA-Pratt & Whitney aviation security program on propulsion-controlled aircraft under missile-damaged aircraft conditions.

Business Intelligence & Knowledge Management - Technological Support for Strategic Management in the Knowledge Based Economy

Directory of Open Access Journals (Sweden)

Dorel PARASCHIV

2008-01-01

Full Text Available The viability and success of modern enterprises are subject to the increasing dynamic of the economic environment, so they need to adjust rapidly their policies and strategies in order to respond to sophistication of competitors, customers and suppliers, globalization of business, international competition. Perhaps the most critical component for success of the modern enterprise is its ability to take advantage of all available information - both internal and external. Making sense of all this information, gaining value and competitive advantage through represents real challenges for the enterprise. The IT solutions designed to address these challenges have been developed in two different approaches: structured data management (Business Intelligence and unstructured content management (Knowledge Management. Integrating Business Intelligence and Knowledge Management in new software applications designated not only to store highly structured data and exploit it in real time but also to interpret the results and communicate them to decision factors provides real technological support for Strategic Management. Integrating Business Intelligence and Knowledge Management in order to respond to the challenges the modern enterprise has to deal with represents not only a "new trend" in IT, but a necessity in the emerging knowledge based economy. These hybrid technologies are already widely known in both scientific and practice communities as Competitive Intelligence. In the end of paper,a competitive datawarehouse design is proposed, in an attempt to apply business intelligence technologies to economic environment analysis making use of romanian public data sources.

The relationship of Emotional Intelligence with Academic Intelligence and the Big Five

NARCIS (Netherlands)

Van der Zee, K.I.; Thijs, Melanie; Schakel, Lolle

The present study examines the relationship of self- and other ratings of emotional intelligence with academic intelligence and personality, as well as the incremental validity of emotional intelligence beyond academic intelligence and personality in predicting academic and social success. A sample

The relationship of emotional intelligence with academic intelligence and the Big Five

NARCIS (Netherlands)

van der Zee, K; Thijs, M; Schakel, L

2002-01-01

The present study examines the relationship of self- and other ratings of emotional intelligence with academic intelligence and personality, as well as the incremental validity of emotional intelligence beyond academic intelligence and personality in predicting academic and social success. A sample

Hybrid Arrays for Chemical Sensing

Science.gov (United States)

Kramer, Kirsten E.; Rose-Pehrsson, Susan L.; Johnson, Kevin J.; Minor, Christian P.

intelligence and robotics, all share the same essential data fusion challenges. The design of a hybrid sensor array should draw on this extended body of knowledge. In this chapter, various techniques for data preprocessing, feature extraction, feature selection, and modeling of sensor data will be introduced and illustrated with data fusion approaches that have been implemented in applications involving data from hybrid arrays. The example systems discussed in this chapter involve the development of prototype sensor networks for damage control event detection aboard US Navy vessels and the development of analysis algorithms to combine multiple sensing techniques for enhanced remote detection of unexploded ordnance (UXO) in both ground surveys and wide area assessments.

Influence of the Risk-Contributing Factors on the Financing of the Investment Project for Building of Intelligent Buildings

Directory of Open Access Journals (Sweden)

Voytolovskiy Nikolay

2017-01-01

Full Text Available This article provides the generic classification of risks of the investment projects for the construction of intelligent buildings which differ by the detachment of the subjective perception of risk by the investor. Risk and uncertainty were justified as system characteristics of the investment projects for the construction of intelligent buildings. Characteristics of the development was given in the context of project management. Methodical schemes of the development of the investment project risks were specified on the basis of interconnection of risk and project effectiveness. Risk management procedure at realization of the developer project was developed.

Effects of Hearing Loss and Fast-Acting Compression on Amplitude Modulation Perception and Speech Intelligibility

DEFF Research Database (Denmark)

Wiinberg, Alan; Jepsen, Morten Løve; Epp, Bastian

2018-01-01

Objective: The purpose was to investigate the effects of hearing-loss and fast-acting compression on speech intelligibility and two measures of temporal modulation sensitivity. Design: Twelve adults with normal hearing (NH) and 16 adults with mild to moderately severe sensorineural hearing loss......, the MDD thresholds were higher for the group with hearing loss than for the group with NH. Fast-acting compression increased the modulation detection thresholds, while no effect of compression on the MDD thresholds was observed. The speech reception thresholds obtained in stationary noise were slightly...... of the modulation detection thresholds, compression does not seem to provide a benefit for speech intelligibility. Furthermore, fast-acting compression may not be able to restore MDD thresholds to the values observed for listeners with NH, suggesting that the two measures of amplitude modulation sensitivity...

Workplace Culture Emotional Intelligence and Trust in the Prediction of Workplace Outcomes

Directory of Open Access Journals (Sweden)

Stough, C.

2011-01-01

Full Text Available There were two aims of this study. The first was to assess the reliability of a new measure of emotional intelligence (EI, the Workplace Culture version of the Swinburne University Emotional Intelligence Test (SUEIT which was designed to measure EI at a group level. The second aim of the study was to investigate the pre-conditions required for the formation of an emotionally intelligent group culture. Specifically, the study proposed that team leader trustworthiness at the leader/member dyad level was required for the formation of an emotionally intelligent culture at the group level. The sample comprised of 142 participants, of which 54 were male and 88 were female. Participants completed a questionnaire assessing perceptions of group EI, leader trustworthiness, job satisfaction and organizational commitment. Results of the study showed that the Workplace Culture SUEIT was reliable and predicted job satisfaction and organizational commitment. Furthermore, trustworthiness of the team leader was found to be significantly correlated to dimensions of group level EI, job satisfaction and organizational commitment. It was concluded that the Workplace Culture SUEIT is a valid and useful tool for measuring group level EI. Furthermore, it was concluded that there is a significant relationship between group level EI and leader/member trust. Implications of the results and future research concerning group and leader EI are discussed.

Hybrid soft computing systems for electromyographic signals analysis: a review

Science.gov (United States)

2014-01-01

Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis. PMID:24490979

THE ARCHITECTURE OF MULTI-COMPONENT DISTRIBUTED HYBRID EXPERT TRAINING SYSTEM

Directory of Open Access Journals (Sweden)

Оleh Shevchuk

2016-09-01

Full Text Available The paper reports on the design of a multi-component architecture of distributed hybrid expert training system that can be used for the study of knowledge base of both internal and external expert systems and artificial intelligence systems that are distributed on Internet servers and other computer networks. Expert training system is based on three groups of basic principles: cybernetic, reflecting experience of previous research of systems of artificial intelligence, expert training systems; pedagogical, determining the principles, on which pedagogical design and use of expert training systems are based; psychological, determining preconditious and understanding of pupils psychics, on which the processes of design and use of expert training systems in professional training of future specialists are based.It accounts for the efficient training through the distributed knowledge via the Internet, which greatly increases the didactic capabilities of the system.

Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization

Science.gov (United States)

Liu, Zexi

2018-01-01

Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.

Novel Damage Detection Techniques for Structural Health Monitoring Using a Hybrid Sensor

Directory of Open Access Journals (Sweden)

Dengjiang Wang

2016-01-01

Full Text Available This study presents a technique for detecting fatigue cracks based on a hybrid sensor monitoring system consisting of a combination of intelligent coating monitoring (ICM and piezoelectric transducer (PZT sensors. An experimental procedure using this hybrid sensor system was designed to monitor the cracks generated by fatigue testing in plate structures. A probability of detection (POD model that quantifies the reliability of damage detection for a specific sensor or the nondestructive testing (NDT method was used to evaluate the weight factor for the ICM and PZT sensors. To estimate the uncertainty of model parameters in this study, the Bayesian method was employed. Realistic data from fatigue testing was used to validate the overall method, and the results show that the novel damage detection technique using a hybrid sensor can quantify fatigue cracks more accurately than results obtained by conventional sensor methods.

Artificial Intelligence Project

Science.gov (United States)

1990-01-01

Symposium on Aritificial Intelligence and Software Engineering Working Notes, March 1989. Blumenthal, Brad, "An Architecture for Automating...Artificial Intelligence Project Final Technical Report ARO Contract: DAAG29-84-K-OGO Artificial Intelligence LaboratO"ry The University of Texas at...Austin N>.. ~ ~ JA 1/I 1991 n~~~ Austin, Texas 78712 ________k A,.tificial Intelligence Project i Final Technical Report ARO Contract: DAAG29-84-K-0060

Modular supervisory controller for hybrid power systems

Energy Technology Data Exchange (ETDEWEB)

Lemos Pereira, A. de

2000-06-01

The power supply of remote places has been commonly provided by thermal power plants, usually diesel generators. Although hybrid power systems may constitute the most economical solution in many applications their widespread application to the electrification schemes of remote areas still depends on improvements in the issues of design and operation control. The main limitations of the present hybrid power systems technology, which are identified in this work, are related to the control and supervision of the power system. Therefore this thesis focuses on the modularity of supervisory controllers in order to design cost-competitive and reliable hybrid power systems. The modular supervisory controller created in this project is considered an important part of a system design approach that aims to overcome the technical difficulties of the current engineering practice and contribute to open the market of hybrid power systems. The term modular refers to a set of design characteristics that allows the use of basically the same supervisory controller in different projects. The modularization and standardisation of the controller include several issues such as interfacing components, communication protocols, modelling, programming and control strategies. The modularity can reduce the highly specialised system engineering related to the integration of components, operation and control. It can also avoid the high costs for installation, service and maintenance. A modular algorithm for supervisory controllers has been developed (a Matlab program called SuperCon) using an object-oriented design and it has been tested through several simulations using different hybrid system configurations and different control strategies. This thesis presents a complete control system design process which can be used as the basis for the development and implementation of intelligent and autonomous supervisory controllers for hybrid power systems with modular characteristics. (au)

Fluid Intelligence and Automatic Neural Processes in Facial Expression Perception

DEFF Research Database (Denmark)

Liu, Tongran; Xiao, Tong; Li, Xiaoyan

2015-01-01

The relationship between human fluid intelligence and social-emotional abilities has been a topic of considerable interest. The current study investigated whether adolescents with different intellectual levels had different automatic neural processing of facial expressions. Two groups of adolescent...... males were enrolled: a high IQ group and an average IQ group. Age and parental socioeconomic status were matched between the two groups. Participants counted the numbers of the central cross changes while paired facial expressions were presented bilaterally in an oddball paradigm. There were two.......2). Participants were required to concentrate on the primary task of counting the central cross changes and to ignore the expressions to ensure that facial expression processing was automatic. Event-related potentials (ERPs) were obtained during the tasks. The visual mismatch negativity (vMMN) components were...

HYBRID HUMAN-ARTIFICIAL INTELLIGENCE APPROACH FOR PAVEMENT DISTRESS ASSESSMENT (PICUCHA

Directory of Open Access Journals (Sweden)

Reus Salini

2017-07-01

Full Text Available The pavement surface condition assessment is a critical component for a proper pavement management system as well as for pavement rehabilitation design. A number of devices were developed to automatically record surface distresses in a continuous survey mode, but the software required for automatic distress identification remains a big challenge. In this study, a new method named PICture Unsupervised Classification with Human Analysis (PICUCHA is proposed to circumvent many of the limitations of existing approaches, based on a combination of human and artificial intelligence. It was designed from scratch to be capable to identify sealed and unsealed cracks, potholes, patches, different types of pavements and others. The self-learning algorithms do not use any distresses predefinition and can process images taken by cameras with different brands, technologies and resolution. This study describes some key aspects of the new method and provides examples in which PICUCHA was tested in real conditions showing accuracy up to 96.9% in image pattern detection and classification.

Routledge companion to intelligence studies

CERN Document Server

Dover, Robert; Hillebrand, Claudia

2013-01-01

The Routledge Companion to Intelligence Studies provides a broad overview of the growing field of intelligence studies. The recent growth of interest in intelligence and security studies has led to an increased demand for popular depictions of intelligence and reference works to explain the architecture and underpinnings of intelligence activity. Divided into five comprehensive sections, this Companion provides a strong survey of the cutting-edge research in the field of intelligence studies: Part I: The evolution of intelligence studies; Part II: Abstract approaches to intelligence; Part III: Historical approaches to intelligence; Part IV: Systems of intelligence; Part V: Contemporary challenges. With a broad focus on the origins, practices and nature of intelligence, the book not only addresses classical issues, but also examines topics of recent interest in security studies. The overarching aim is to reveal the rich tapestry of intelligence studies in both a sophisticated and accessible way. This Companion...

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining.

Science.gov (United States)

Salehi, Mojtaba; Bahreininejad, Ardeshir

2011-08-01

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

Solution of Fractional Order System of Bagley-Torvik Equation Using Evolutionary Computational Intelligence

Directory of Open Access Journals (Sweden)

Muhammad Asif Zahoor Raja

2011-01-01

Full Text Available A stochastic technique has been developed for the solution of fractional order system represented by Bagley-Torvik equation. The mathematical model of the equation was developed with the help of feed-forward artificial neural networks. The training of the networks was made with evolutionary computational intelligence based on genetic algorithm hybrid with pattern search technique. Designed scheme was successfully applied to different forms of the equation. Results are compared with standard approximate analytic, stochastic numerical solvers and exact solutions.

78 FR 90 - Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting

Science.gov (United States)

2013-01-02

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting AGENCY: National Intelligence University, Defense Intelligence... hereby given that a closed meeting of the National Intelligence University Board of Visitors has been...

Improving societal acceptance of rad waste management policy decisions: an approach based on complex intelligence

International Nuclear Information System (INIS)

Rao, Suman

2008-01-01

In today's context elaborate public participation exercises are conducted around the world to elicit and incorporate societal risk perceptions into nuclear policy Decision-Making. However, on many occasions, such as in the case of rad waste management, the society remains unconvinced about these decisions. This naturally leads to the questions: are techniques for incorporating societal risk perceptions into the rad waste policy decision making processes sufficiently mature? How could societal risk perceptions and legal normative principles be better integrated in order to render the decisions more equitable and convincing to society? Based on guidance from socio-psychological research this paper postulates that a critical factor for gaining/improving societal acceptance is the quality and adequacy of criteria for option evaluation that are used in the policy decision making. After surveying three rad waste public participation cases, the paper identifies key lacunae in criteria abstraction processes as currently practiced. A new policy decision support model CIRDA: Complex Intelligent Risk Discourse Abstraction model that is based on the heuristic of Risk-Risk Analysis is proposed to overcome these lacunae. CIRDA's functionality of rad waste policy decision making is modelled as a policy decision-making Abstract Intelligent Agent and the agent program/abstraction mappings are presented. CIRDA is then applied to a live (U.K.) rad waste management case and the advantages of this method as compared to the Value Tree Method as practiced in the GB case are demonstrated. (author)

Enhanced intelligent water drops algorithm for multi-depot vehicle routing problem.

Science.gov (United States)

Ezugwu, Absalom E; Akutsah, Francis; Olusanya, Micheal O; Adewumi, Aderemi O

2018-01-01

The intelligent water drop algorithm is a swarm-based metaheuristic algorithm, inspired by the characteristics of water drops in the river and the environmental changes resulting from the action of the flowing river. Since its appearance as an alternative stochastic optimization method, the algorithm has found applications in solving a wide range of combinatorial and functional optimization problems. This paper presents an improved intelligent water drop algorithm for solving multi-depot vehicle routing problems. A simulated annealing algorithm was introduced into the proposed algorithm as a local search metaheuristic to prevent the intelligent water drop algorithm from getting trapped into local minima and also improve its solution quality. In addition, some of the potential problematic issues associated with using simulated annealing that include high computational runtime and exponential calculation of the probability of acceptance criteria, are investigated. The exponential calculation of the probability of acceptance criteria for the simulated annealing based techniques is computationally expensive. Therefore, in order to maximize the performance of the intelligent water drop algorithm using simulated annealing, a better way of calculating the probability of acceptance criteria is considered. The performance of the proposed hybrid algorithm is evaluated by using 33 standard test problems, with the results obtained compared with the solutions offered by four well-known techniques from the subject literature. Experimental results and statistical tests show that the new method possesses outstanding performance in terms of solution quality and runtime consumed. In addition, the proposed algorithm is suitable for solving large-scale problems.

A music perception disorder (congenital amusia) influences speech comprehension.

Science.gov (United States)

Liu, Fang; Jiang, Cunmei; Wang, Bei; Xu, Yi; Patel, Aniruddh D

2015-01-01

This study investigated the underlying link between speech and music by examining whether and to what extent congenital amusia, a musical disorder characterized by degraded pitch processing, would impact spoken sentence comprehension for speakers of Mandarin, a tone language. Sixteen Mandarin-speaking amusics and 16 matched controls were tested on the intelligibility of news-like Mandarin sentences with natural and flat fundamental frequency (F0) contours (created via speech resynthesis) under four signal-to-noise (SNR) conditions (no noise, +5, 0, and -5dB SNR). While speech intelligibility in quiet and extremely noisy conditions (SNR=-5dB) was not significantly compromised by flattened F0, both amusic and control groups achieved better performance with natural-F0 sentences than flat-F0 sentences under moderately noisy conditions (SNR=+5 and 0dB). Relative to normal listeners, amusics demonstrated reduced speech intelligibility in both quiet and noise, regardless of whether the F0 contours of the sentences were natural or flattened. This deficit in speech intelligibility was not associated with impaired pitch perception in amusia. These findings provide evidence for impaired speech comprehension in congenital amusia, suggesting that the deficit of amusics extends beyond pitch processing and includes segmental processing. Copyright © 2014 Elsevier Ltd. All rights reserved.

Intelligent products : A survey

NARCIS (Netherlands)

Meyer, G.G.; Främling, K.; Holmström, J.

This paper presents an overview of the field of Intelligent Products. As Intelligent Products have many facets, this paper is mainly focused on the concept behind Intelligent Products, the technical foundations, and the achievable practical goals of Intelligent Products. A novel classification of

Benefits of collective intelligence: Swarm intelligent foraging, an ethnographic research

Directory of Open Access Journals (Sweden)

Sivave Mashingaidze

2014-12-01

Full Text Available Wisdom of crowds; bees, colonies of ants, schools of fish, flocks of birds, and fireflies flashing synchronously are all examples of highly coordinated behaviors that emerge from collective, decentralized intelligence. This article is an ethnographic study of swarm intelligence foraging of swarms and the benefits derived from collective decision making. The author used using secondary data analysis to look at the benefits of swarm intelligence in decision making to achieve intended goals. Concepts like combined decision making and consensus were discussed and four principles of swarm intelligence were also discussed viz; coordination, cooperation, deliberation and collaboration. The research found out that collective decision making in swarms is the touchstone of achieving their goals. The research further recommended corporate to adopt collective intelligence for business sustainability.

Artificial intelligence methods applied in the controlled synthesis of polydimethilsiloxane - poly (methacrylic acid) copolymer networks with imposed properties

Science.gov (United States)

Rusu, Teodora; Gogan, Oana Marilena

2016-05-01

This paper describes the use of artificial intelligence method in copolymer networks design. In the present study, we pursue a hybrid algorithm composed from two research themes in the genetic design framework: a Kohonen neural network (KNN), path (forward problem) combined with a genetic algorithm path (backward problem). The Tabu Search Method is used to improve the performance of the genetic algorithm path.

Intelligence: Real or artificial?

OpenAIRE

Schlinger, Henry D.

1992-01-01

Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally r...

Hybrid model for forecasting time series with trend, seasonal and salendar variation patterns

Science.gov (United States)

Suhartono; Rahayu, S. P.; Prastyo, D. D.; Wijayanti, D. G. P.; Juliyanto

2017-09-01

Most of the monthly time series data in economics and business in Indonesia and other Moslem countries not only contain trend and seasonal, but also affected by two types of calendar variation effects, i.e. the effect of the number of working days or trading and holiday effects. The purpose of this research is to develop a hybrid model or a combination of several forecasting models to predict time series that contain trend, seasonal and calendar variation patterns. This hybrid model is a combination of classical models (namely time series regression and ARIMA model) and/or modern methods (artificial intelligence method, i.e. Artificial Neural Networks). A simulation study was used to show that the proposed procedure for building the hybrid model could work well for forecasting time series with trend, seasonal and calendar variation patterns. Furthermore, the proposed hybrid model is applied for forecasting real data, i.e. monthly data about inflow and outflow of currency at Bank Indonesia. The results show that the hybrid model tend to provide more accurate forecasts than individual forecasting models. Moreover, this result is also in line with the third results of the M3 competition, i.e. the hybrid model on average provides a more accurate forecast than the individual model.

Designing a holistic end-to-end intelligent network analysis and security platform

Science.gov (United States)

Alzahrani, M.

2018-03-01

Firewall protects a network from outside attacks, however, once an attack entering a network, it is difficult to detect. Recent significance accidents happened. i.e.: millions of Yahoo email account were stolen and crucial data from institutions are held for ransom. Within two year Yahoo’s system administrators were not aware that there are intruder inside the network. This happened due to the lack of intelligent tools to monitor user behaviour in internal network. This paper discusses a design of an intelligent anomaly/malware detection system with proper proactive actions. The aim is to equip the system administrator with a proper tool to battle the insider attackers. The proposed system adopts machine learning to analyse user’s behaviour through the runtime behaviour of each node in the network. The machine learning techniques include: deep learning, evolving machine learning perceptron, hybrid of Neural Network and Fuzzy, as well as predictive memory techniques. The proposed system is expanded to deal with larger network using agent techniques.

A survey of mindset theories of intelligence and medical error self-reporting among pediatric housestaff and faculty.

Science.gov (United States)

Jegathesan, Mithila; Vitberg, Yaffa M; Pusic, Martin V

2016-02-11

Intelligence theory research has illustrated that people hold either "fixed" (intelligence is immutable) or "growth" (intelligence can be improved) mindsets and that these views may affect how people learn throughout their lifetime. Little is known about the mindsets of physicians, and how mindset may affect their lifetime learning and integration of feedback. Our objective was to determine if pediatric physicians are of the "fixed" or "growth" mindset and whether individual mindset affects perception of medical error reporting.  We sent an anonymous electronic survey to pediatric residents and attending pediatricians at a tertiary care pediatric hospital. Respondents completed the "Theories of Intelligence Inventory" which classifies individuals on a 6-point scale ranging from 1 (Fixed Mindset) to 6 (Growth Mindset). Subsequent questions collected data on respondents' recall of medical errors by self or others. We received 176/349 responses (50 %). Participants were equally distributed between mindsets with 84 (49 %) classified as "fixed" and 86 (51 %) as "growth". Residents, fellows and attendings did not differ in terms of mindset. Mindset did not correlate with the small number of reported medical errors. There is no dominant theory of intelligence (mindset) amongst pediatric physicians. The distribution is similar to that seen in the general population. Mindset did not correlate with error reports.

Quality control of intelligence research

International Nuclear Information System (INIS)

Lu Yan; Xin Pingping; Wu Jian

2014-01-01

Quality control of intelligence research is the core issue of intelligence management, is a problem in study of information science This paper focuses on the performance of intelligence to explain the significance of intelligence research quality control. In summing up the results of the study on the basis of the analysis, discusses quality control methods in intelligence research, introduces the experience of foreign intelligence research quality control, proposes some recommendations to improve quality control in intelligence research. (authors)

Intelligence Issues for Congress

Science.gov (United States)

2013-04-23

open source information— osint (newspapers...by user agencies. Section 1052 of the Intelligence Reform Act expressed the sense of Congress that there should be an open source intelligence ...center to coordinate the collection, analysis, production, and dissemination of open source intelligence to other intelligence agencies. An Open Source

Orchestrating Multiple Intelligences

Science.gov (United States)

Moran, Seana; Kornhaber, Mindy; Gardner, Howard

2006-01-01

Education policymakers often go astray when they attempt to integrate multiple intelligences theory into schools, according to the originator of the theory, Howard Gardner, and his colleagues. The greatest potential of a multiple intelligences approach to education grows from the concept of a profile of intelligences. Each learner's intelligence…

Improving the speech intelligibility in classrooms

Science.gov (United States)

Lam, Choi Ling Coriolanus

of the reverberation time, the indoor ambient noise (or background noise level), the signal-to-noise ratio, and the speech transmission index, it aims to establish a guideline for improving the speech intelligibility in classrooms for any countries and any environmental conditions. The study showed that the acoustical conditions of most of the measured classrooms in Hong Kong are unsatisfactory. The selection of materials inside a classroom is important for improving speech intelligibility at design stage, especially the acoustics ceiling, to shorten the reverberation time inside the classroom. The signal-to-noise should be higher than 11dB(A) for over 70% of speech perception, either tonal or non-tonal languages, without the usage of address system. The unexpected results bring out a call to revise the standard design and to devise acceptable standards for classrooms in Hong Kong. It is also demonstrated a method for assessment on the classroom in other cities with similar environmental conditions.

Longevity-conscious dimensioning and power management of the hybrid energy storage system in a fuel cell hybrid electric bus

International Nuclear Information System (INIS)

Hu, Xiaosong; Johannesson, Lars; Murgovski, Nikolce; Egardt, Bo

2015-01-01

Highlights: • Hybrid energy storage system is optimally sized and controlled for a hybrid bus. • Dynamic battery health model is incorporated in the optimization. • Convex programming is efficient for optimizing hybrid propulsion systems. • Optimal battery replacement strategy is explored. • Comparison to the battery-only option is made in the health-aware optimization. - Abstract: Energy storage systems (ESSs) play an important role in the performance and economy of electrified vehicles. Hybrid energy storage system (HESS) combining both lithium-ion cells and supercapacitors is one of the most promising solutions. This paper discusses the optimal HESS dimensioning and energy management of a fuel cell hybrid electric bus. Three novel contributions are added to the relevant literature. First, efficient convex programming is used to simultaneously optimize the HESS dimension (including sizes of both the lithium-ion battery pack and the supercapacitor stack) and the power allocation between the HESS and the fuel cell system (FCS) of the hybrid bus. In the combined plant/controller optimization problem, a dynamic battery State-of-Health (SOH) model is integrated to quantitatively examine the impact of the battery replacement strategy on both the HESS size and the bus economy. Second, the HESS and the battery-only ESS options are systematically compared in the proposed optimization framework. Finally, the battery-health-perceptive HESS optimization outcome is contrasted to the ideal one neglecting the battery degradation (assuming that the battery is durable over the bus service period without deliberate power regulation)

Suppressive mechanisms in visual motion processing: From perception to intelligence.

Science.gov (United States)

Tadin, Duje

2015-10-01

Perception operates on an immense amount of incoming information that greatly exceeds the brain's processing capacity. Because of this fundamental limitation, the ability to suppress irrelevant information is a key determinant of perceptual efficiency. Here, I will review a series of studies investigating suppressive mechanisms in visual motion processing, namely perceptual suppression of large, background-like motions. These spatial suppression mechanisms are adaptive, operating only when sensory inputs are sufficiently robust to guarantee visibility. Converging correlational and causal evidence links these behavioral results with inhibitory center-surround mechanisms, namely those in cortical area MT. Spatial suppression is abnormally weak in several special populations, including the elderly and individuals with schizophrenia-a deficit that is evidenced by better-than-normal direction discriminations of large moving stimuli. Theoretical work shows that this abnormal weakening of spatial suppression should result in motion segregation deficits, but direct behavioral support of this hypothesis is lacking. Finally, I will argue that the ability to suppress information is a fundamental neural process that applies not only to perception but also to cognition in general. Supporting this argument, I will discuss recent research that shows individual differences in spatial suppression of motion signals strongly predict individual variations in IQ scores. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Semantic Business Intelligence - a New Generation of Business Intelligence

Directory of Open Access Journals (Sweden)

Dinu AIRINEI

2012-01-01

Full Text Available Business Intelligence Solutions represents applications used by companies to manage process and analyze data to provide substantiated decision. In the context of Semantic Web develop-ment trend is to integrate semantic unstructured data, making business intelligence solutions to be redesigned in such a manner that can analyze, process and synthesize, in addition to traditional data and data integrated with semantic another form and structure. This invariably leads appearance of new BI solution, called Semantic Business Intelligence.

A false-positive detection bias as a function of state and trait schizotypy in interaction with intelligence

Directory of Open Access Journals (Sweden)

Phillip eGrant

2014-09-01

Full Text Available Hallucinatory experiences are by far not limited to patients with clinical psychosis. A number of internal and external factors may bring about such experiences in healthy individuals, whereby the personality trait of (positive schizotypy is a major mediator of individual differences. Psychotic experiences are defined as associating abnormal meaning to real but objectively irrelevant perceptions. Especially the ambiguity of a stimulus correlates positively with the likelihood of abnormal interpretation, and intelligence is believed to have an important influence and act as protective against clinical psychosis in highly schizotypic individuals.In this study we presented 131 healthy participants with 216 15-letter strings containing either a word, a non-word or only random letters and asked them to report, whether or not they believed to have seen a word. The aim was to replicate findings that participants with high values in positive schizotypy on the trait-level make more false-positive errors and assess the role of stimulus-ambiguity and verbal intelligence. Additionally, we wanted to examine whether the same effect could be shown for indices of state schizotypy.Our results support findings that both state and trait positive schizotypy explain significant variance in seeing things that are not there and that the properties of individual stimuli have additional strong effects on the false-positive hit rates. Finally, we found that verbal intelligence and positive schizotypy interact with stimulus-ambiguity in the production of false-positive perceptions.

A false-positive detection bias as a function of state and trait schizotypy in interaction with intelligence.

Science.gov (United States)

Grant, Phillip; Balser, Mona; Munk, Aisha Judith Leila; Linder, Jens; Hennig, Juergen

2014-01-01

Hallucinatory experiences are by far not limited to patients with clinical psychosis. A number of internal and external factors may bring about such experiences in healthy individuals, whereby the personality trait of (positive) schizotypy is a major mediator of individual differences. Psychotic experiences are defined as associating abnormal meaning to real but objectively irrelevant perceptions. Especially, the ambiguity of a stimulus correlates positively with the likelihood of abnormal interpretation, and intelligence is believed to have an important influence and act as protective against clinical psychosis in highly schizotypic individuals. In this study, we presented 131 healthy participants with 216 15-letter strings containing either a word, a non-word, or only random letters and asked them to report, whether or not they believed to have seen a word. The aim was to replicate findings that participants with high values in positive schizotypy on the trait-level make more false-positive errors and assess the role of stimulus-ambiguity and verbal intelligence. Additionally, we wanted to examine whether the same effect could be shown for indices of state schizotypy. Our results support findings that both state and trait positive schizotypy explain significant variance in "seeing things that are not there" and that the properties of individual stimuli have additional strong effects on the false-positive hit rates. Finally, we found that verbal intelligence and positive schizotypy interact with stimulus-ambiguity in the production of false-positive perceptions.

Research of Classical and Intelligent Information System Solutions for Criminal Intelligence Analysis

OpenAIRE

Šimović, Vladimir

2001-01-01

The objective of this study is to present research on classical and intelligent information system solutions used in criminal intelligence analysis in Croatian security system theory. The study analyses objective and classical methods of information science, including artificial intelligence and other scientific methods. The intelligence and classical software solutions researched, proposed, and presented in this study were used in developing the integrated information system for the Croatian...

Embodiment and Estrangement: Results from a First-in-Human "Intelligent BCI" Trial.

Science.gov (United States)

Gilbert, F; Cook, M; O'Brien, T; Illes, J

2017-11-11

While new generations of implantable brain computer interface (BCI) devices are being developed, evidence in the literature about their impact on the patient experience is lagging. In this article, we address this knowledge gap by analysing data from the first-in-human clinical trial to study patients with implanted BCI advisory devices. We explored perceptions of self-change across six patients who volunteered to be implanted with artificially intelligent BCI devices. We used qualitative methodological tools grounded in phenomenology to conduct in-depth, semi-structured interviews. Results show that, on the one hand, BCIs can positively increase a sense of the self and control; on the other hand, they can induce radical distress, feelings of loss of control, and a rupture of patient identity. We conclude by offering suggestions for the proactive creation of preparedness protocols specific to intelligent-predictive and advisory-BCI technologies essential to prevent potential iatrogenic harms.

Selected examples of intelligent (micro) sensor systems: state-of-the-art and tendencies

Science.gov (United States)

Hauptmann, Peter R.

2006-03-01

The capability of intelligent sensors to have more intelligence built into them continues to drive their application in areas including automotive, aerospace and defense, industrial, intelligent house and wear, medical and homeland security. In principle it is difficult to overestimate the importance of intelligent (micro) sensors or sensor systems within advanced societies but one characteristic feature is the global market for sensors, which is now about 20 billion annually. Therefore sensors or sensor systems play a dominant role in many fields from the macro sensor in manufacturing industry down to the miniaturized sensor for medical applications. The diversity of sensors precludes a complete description of the state-of-the-art; selected examples will illustrate the current situation. MEMS (microelectromechanical systems) devices are of special interest in the context of micro sensor systems. In past the main requirements of a sensor were in terms of metrological performance. The electrical (or optical) signal produced by the sensor needed to match the measure relatively accurately. Such basic functionality is no longer sufficient. Data processing near the sensor, the extraction of more information than just the direct sensor information by signal analysis, system aspects and multi-sensor information are the new demands. A shifting can be observed away from aiming to design perfect single-function transducers and towards the utilization of system-based sensors as system components. In the ideal case such systems contain sensors, actuators and electronics. They can be realized in monolithic, hybrid or discrete form—which kind is used depends on the application. In this article the state-of-the-art of intelligent sensors or sensor systems is reviewed using selected examples. Future trends are deduced.

Hybrid Modeling and Optimization of Manufacturing Combining Artificial Intelligence and Finite Element Method

CERN Document Server

Quiza, Ramón; Davim, J Paulo

2012-01-01

Artificial intelligence (AI) techniques and the finite element method (FEM) are both powerful computing tools, which are extensively used for modeling and optimizing manufacturing processes. The combination of these tools has resulted in a new flexible and robust approach as several recent studies have shown. This book aims to review the work already done in this field as well as to expose the new possibilities and foreseen trends. The book is expected to be useful for postgraduate students and researchers, working in the area of modeling and optimization of manufacturing processes.

Artificial Consciousness or Artificial Intelligence

OpenAIRE

Spanache Florin

2017-01-01

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

Next gen perception and cognition: augmenting perception and enhancing cognition through mobile technologies

Science.gov (United States)

Goma, Sergio R.

2015-03-01

In current times, mobile technologies are ubiquitous and the complexity of problems is continuously increasing. In the context of advancement of engineering, we explore in this paper possible reasons that could cause a saturation in technology evolution - namely the ability of problem solving based on previous results and the ability of expressing solutions in a more efficient way, concluding that `thinking outside of brain' - as in solving engineering problems that are expressed in a virtual media due to their complexity - would benefit from mobile technology augmentation. This could be the necessary evolutionary step that would provide the efficiency required to solve new complex problems (addressing the `running out of time' issue) and remove the communication of results barrier (addressing the human `perception/expression imbalance' issue). Some consequences are discussed, as in this context the artificial intelligence becomes an automation tool aid instead of a necessary next evolutionary step. The paper concludes that research in modeling as problem solving aid and data visualization as perception aid augmented with mobile technologies could be the path to an evolutionary step in advancing engineering.

Intelligent mechatronics; Intelligent mechatronics

Energy Technology Data Exchange (ETDEWEB)

Hashimoto, H. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science

1995-10-01

Intelligent mechatronics (IM) was explained as follows: a study of IM essentially targets realization of a robot namely, but in the present stage the target is a creation of new values by intellectualization of machine, that is, a combination of the information infrastructure and the intelligent machine system. IM is also thought to be constituted of computers positively used and micromechatronics. The paper next introduces examples of IM study, mainly those the author is concerned with as shown below: sensor gloves, robot hands, robot eyes, tele operation, three-dimensional object recognition, mobile robot, magnetic bearing, construction of remote controlled unmanned dam, robot network, sensitivity communication using neuro baby, etc. 27 figs.

A Hybrid Model for Forecasting Sales in Turkish Paint Industry

Directory of Open Access Journals (Sweden)

Alp Ustundag

2009-12-01

Full Text Available Sales forecasting is important for facilitating effective and efficient allocation of scarce resources. However, how to best model and forecast sales has been a long-standing issue. There is no best forecasting method that is applicable in all circumstances. Therefore, confidence in the accuracy of sales forecasts is achieved by corroborating the results using two or more methods. This paper proposes a hybrid forecasting model that uses an artificial intelligence method (AI with multiple linear regression (MLR to predict product sales for the largest Turkish paint producer. In the hybrid model, three different AI methods, fuzzy rule-based system (FRBS, artificial neural network (ANN and adaptive neuro fuzzy network (ANFIS, are used and compared to each other. The results indicate that FRBS yields better forecasting accuracy in terms of root mean squared error (RMSE and mean absolute percentage error (MAPE.

Brain Intelligence: Go Beyond Artificial Intelligence

OpenAIRE

Lu, Huimin; Li, Yujie; Chen, Min; Kim, Hyoungseop; Serikawa, Seiichi

2017-01-01

Artificial intelligence (AI) is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan's economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India. The attention has been focused mainly on developing new artificial intelligence information communication ...

Business Intelligence Systems

Directory of Open Access Journals (Sweden)

Bogdan NEDELCU

2014-02-01

Full Text Available The aim of this article is to show the importance of business intelligence and its growing influence. It also shows when the concept of business intelligence was used for the first time and how it evolved over time. The paper discusses the utility of a business intelligence system in any organization and its contribution to daily activities. Furthermore, we highlight the role and the objectives of business intelligence systems inside an organization and the needs to grow the incomes and reduce the costs, to manage the complexity of the business environment and to cut IT costs so that the organization survives in the current competitive climate. The article contains information about architectural principles of a business intelligence system and how such a system can be achieved.

A Novel Supercapacitor/Lithium-Ion Hybrid Energy System with a Fuzzy Logic-Controlled Fast Charging and Intelligent Energy Management System

Directory of Open Access Journals (Sweden)

Muhammad Adil Khan

2018-05-01

Full Text Available The electric powered wheelchair (EPW is an essential assistive tool for people with serious injuries or disability. This manuscript describes the validation of applied research for reducing the charging time of an electric wheelchair using a hybrid electric system (HES composed of a supercapacitor (SC bank and a lithium-ion battery with a fuzzy logic controller (FLC-based fast charging system for Li-ion batteries and a fuzzy logic-based intelligent energy management system (FLIEMS for controlling the power flow within the HES. The fast charging FLC was designed to drive the voltage difference (Vd among the different cells of a multi-cell battery and the cell voltage (Vc of an individual cell. These parameters (voltage difference and cell voltage were used as input voltages to reduce the charge time and activate a bypass equalization (BPE scheme. BPE was introduced in this paper so that the battery operates within the safe voltage range. For SC/Li-ion HES, the FLIEMS presented in this paper controls the bi-directional power flow to smooth the power extracted from Li-ion batteries. Moreover, a dual active bridge isolated bidirectional DC converter (DAB-IBDC was used for power conversion. The DAB-IBDC presented in this paper has the characteristics of galvanic isolation, and high power conversion efficiency compared to the conventional converter circuits due to the reduced reverse power flow and current stresses.

Intelligent decision support algorithm for distribution system restoration.

Science.gov (United States)

Singh, Reetu; Mehfuz, Shabana; Kumar, Parmod

2016-01-01

Distribution system is the means of revenue for electric utility. It needs to be restored at the earliest if any feeder or complete system is tripped out due to fault or any other cause. Further, uncertainty of the loads, result in variations in the distribution network's parameters. Thus, an intelligent algorithm incorporating hybrid fuzzy-grey relation, which can take into account the uncertainties and compare the sequences is discussed to analyse and restore the distribution system. The simulation studies are carried out to show the utility of the method by ranking the restoration plans for a typical distribution system. This algorithm also meets the smart grid requirements in terms of an automated restoration plan for the partial/full blackout of network.

Analysis and Study of Muhammad Husayn Tabataba'i's Theory about the origin of secondary philosophical intelligibles using Morteza Motahhari's Commenting

Directory of Open Access Journals (Sweden)

Alireza Dorri Nogoorani

2018-02-01

Full Text Available Secondary philosophical intelligibles are general philosophical concepts such as existence, non-existence, cause, effect and accident on which the life of Islamic philosophy depends. Muhammad Husayn Tabataba'I has tried to propose a comprehensive theory about the way through which secondary philosophical intelligibles are originated. He believes that these intelligibles are first understood through relational concepts and then non-relational concepts are abstracted from those relational ones and generalized. This article tries to give a clear formulation of the theory with four phases (in addition to its foundations using Tabataba'i's works and Motahhari's comments. The resuts of this research study shows that these concepts are not delusion. It also depicts that these concepts are not extracted from internal or external experiences or primordial human nature (fitrah but are created from perceptive faculty. In addition, some other key issues to which Allameh has not paid enough attention, such as how to generalize the concept of secondary intelligible which has been abstracted from a special mental state to the whole world and the relationship between secondary intelligible obtained in the mind and the object to which the secondary intelligible refers, have been stated and the researcher has tried to find answers for these questions.

Professionalizing Intelligence Analysis

Directory of Open Access Journals (Sweden)

James B. Bruce

2015-09-01

Full Text Available This article examines the current state of professionalism in national security intelligence analysis in the U.S. Government. Since the introduction of major intelligence reforms directed by the Intelligence Reform and Terrorism Prevention Act (IRTPA in December, 2004, we have seen notable strides in many aspects of intelligence professionalization, including in analysis. But progress is halting, uneven, and by no means permanent. To consolidate its gains, and if it is to continue improving, the U.S. intelligence community (IC should commit itself to accomplishing a new program of further professionalization of analysis to ensure that it will develop an analytic cadre that is fully prepared to deal with the complexities of an emerging multipolar and highly dynamic world that the IC itself is forecasting. Some recent reforms in intelligence analysis can be assessed against established standards of more fully developed professions; these may well fall short of moving the IC closer to the more fully professionalized analytical capability required for producing the kind of analysis needed now by the United States.

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

International Nuclear Information System (INIS)

Lhuillier, C.; Malvache, P.

1987-01-01

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

Exploring the Effects of Working Memory on Time Perception in Attention Deficit Hyperactivity Disorder.

Science.gov (United States)

Lee, Hom-Yi; Yang, En-Lin

2018-01-01

Children with attention deficit hyperactivity disorder (ADHD) are often reported to have deficits of time perception. However, there is a strong relation between performance on tasks of working memory and time perception. Thus, it is possible that the poor performance of children with ADHD on time perception results from their deficit of working memory. In this study, the working memory of participants was separately assessed; therefore, we could explore the relationship between working memory and time perception of children with ADHD. Fifty-six children with ADHD and those of healthy controls completed tasks measuring working memory and time perception. The results showed that the time discrimination ability of children with ADHD was poorer than that of controls. However, there was a strong association between time perception and working memory. After controlling working memory and intelligence, the time discrimination ability of children with ADHD was not significantly poorer than that of controls. We suggest that there is an interdependent relationship between time perception and working memory for children with ADHD.

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.

Lexical effects on speech production and intelligibility in Parkinson's disease

Science.gov (United States)

Chiu, Yi-Fang

Individuals with Parkinson's disease (PD) often have speech deficits that lead to reduced speech intelligibility. Previous research provides a rich database regarding the articulatory deficits associated with PD including restricted vowel space (Skodda, Visser, & Schlegel, 2011) and flatter formant transitions (Tjaden & Wilding, 2004; Walsh & Smith, 2012). However, few studies consider the effect of higher level structural variables of word usage frequency and the number of similar sounding words (i.e. neighborhood density) on lower level articulation or on listeners' perception of dysarthric speech. The purpose of the study is to examine the interaction of lexical properties and speech articulation as measured acoustically in speakers with PD and healthy controls (HC) and the effect of lexical properties on the perception of their speech. Individuals diagnosed with PD and age-matched healthy controls read sentences with words that varied in word frequency and neighborhood density. Acoustic analysis was performed to compare second formant transitions in diphthongs, an indicator of the dynamics of tongue movement during speech production, across different lexical characteristics. Young listeners transcribed the spoken sentences and the transcription accuracy was compared across lexical conditions. The acoustic results indicate that both PD and HC speakers adjusted their articulation based on lexical properties but the PD group had significant reductions in second formant transitions compared to HC. Both groups of speakers increased second formant transitions for words with low frequency and low density, but the lexical effect is diphthong dependent. The change in second formant slope was limited in the PD group when the required formant movement for the diphthong is small. The data from listeners' perception of the speech by PD and HC show that listeners identified high frequency words with greater accuracy suggesting the use of lexical knowledge during the

[Social intelligence deficits in autistic children and adolescents--subjective theories of psychosocial health care professionals].

Science.gov (United States)

Krech, M; Probst, P

1998-10-01

The paper is concerned with personal theories of health care professionals about deficiencies in social intelligence of autistic persons. In the component-model of social intelligence means the ability of individuals or groups, to interact with each other in social situations. This contains social perception, social behavior as well as social conceptions and refers to emotional, cognitive and normative aspects. 33 interviewees, working as psychologists or teachers in kindergartens, schools or therapy institutions, are questioned by a half-standardized single interview concerning their beliefs about nonverbal social abilities, social perspective taking, and construction of a theory of mind in autistic persons. The major finding is: The impairments can be found in all aspects of social intelligence. Especially emotional handicaps, which are quoted by more than 80% of the interviewees, and low cognitive preconditions of mastering social stimuli, which are quoted by nearly all interviewees, are relevant. The subjective theories of the interviewees are in accordance to the models of parents as well as the models of the leading experts. The professional relationship to autistic persons and the practical experiences of the health care professionals lead to their specific personal theories of deficiencies in social intelligence of autistic people with wide consequences in respect to the professional contact with the autistic children and young adults.

Continuing debates on direct social perception: Some notes on Gallagher's analysis of "the new hybrids".

Science.gov (United States)

Bohl, Vivian

2015-11-01

This commentary argues that Gallagher's account of direct social perception has remained underdeveloped in several respects. Gallagher has not provided convincing evidence to support his claim that mindreading is rare in social situations. He and other direct perception theorists have not offered a substantive critique of standard theories of mindreading because they have attacked a much stronger claim about the putative unobservability of mental states than most theories of mindreading imply. To provide a genuine alternative to standard theories of mindreading, the direct perception theorist needs to provide more detailed answers to the following questions: What are the criteria for distinguishing perceptual processes from non-perceptual processes? How exactly does direct social perception function on the subpersonal level? What is the content of direct social perception? How does direct perception theory relate to more recent developments in the mindreading literature? Copyright © 2015 Elsevier Inc. All rights reserved.

77 FR 32952 - Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting

Science.gov (United States)

2012-06-04

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting AGENCY: Department of Defense, Defense Intelligence Agency, National Intelligence University. ACTION: Notice of closed meeting. SUMMARY: Pursuant to the provisions of...

Pitch perception and production in congenital amusia: Evidence from Cantonese speakers.

Science.gov (United States)

Liu, Fang; Chan, Alice H D; Ciocca, Valter; Roquet, Catherine; Peretz, Isabelle; Wong, Patrick C M

2016-07-01

This study investigated pitch perception and production in speech and music in individuals with congenital amusia (a disorder of musical pitch processing) who are native speakers of Cantonese, a tone language with a highly complex tonal system. Sixteen Cantonese-speaking congenital amusics and 16 controls performed a set of lexical tone perception, production, singing, and psychophysical pitch threshold tasks. Their tone production accuracy and singing proficiency were subsequently judged by independent listeners, and subjected to acoustic analyses. Relative to controls, amusics showed impaired discrimination of lexical tones in both speech and non-speech conditions. They also received lower ratings for singing proficiency, producing larger pitch interval deviations and making more pitch interval errors compared to controls. Demonstrating higher pitch direction identification thresholds than controls for both speech syllables and piano tones, amusics nevertheless produced native lexical tones with comparable pitch trajectories and intelligibility as controls. Significant correlations were found between pitch threshold and lexical tone perception, music perception and production, but not between lexical tone perception and production for amusics. These findings provide further evidence that congenital amusia is a domain-general language-independent pitch-processing deficit that is associated with severely impaired music perception and production, mildly impaired speech perception, and largely intact speech production.

Intelligent playgrounds

DEFF Research Database (Denmark)

Larsen, Lasse Juel

2009-01-01

This paper examines play, gaming and learning in regard to intelligent playware developed for outdoor use. The key questions are how does these novel artefacts influence the concept of play, gaming and learning. Up until now play and game have been understood as different activities. This paper...... examines if the sharp differentiation between the two can be uphold in regard to intelligent playware for outdoor use. Play and game activities will be analysed and viewed in conjunction with learning contexts. This paper will stipulate that intelligent playware facilitates rapid shifts in contexts...

Artificial intelligence

CERN Document Server

Ennals, J R

1987-01-01

Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

Advanced intelligence and mechanism approach

Institute of Scientific and Technical Information of China (English)

ZHONG Yixin

2007-01-01

Advanced intelligence will feature the intelligence research in next 50 years.An understanding of the concept of advanced intelligence as well as its importance will be provided first,and detailed analysis on an approach,the mechanism approach.suitable to the advanced intelligence research will then be flolowed.And the mutual relationship among mechanism approach,traditional approaches existed in artificial intelligence research,and the cognitive informatics will be discussed.It is interesting to discover that mechanism approach is a good one to the Advanced Intelligence research and a tmified form of the existed approaches to artificial intelligence.

Microcontroller based implementation of fuel cell and battery integrated hybrid power source

International Nuclear Information System (INIS)

Fahad, A.; Ali, S.M.; Bhatti, A.A.; Nasir, M

2013-01-01

This paper presents the implementation of a digitally controlled hybrid power source system, composed of fuel cell and battery. Use of individual fuel cell stacks as a power source, encounters many problems in achieving the desired load characteristics. A battery integrated, digitally controlled hybrid system is proposed for high pulse requirements. The proposed hybrid power source fulfils these peak demands with efficient flow of energy as compared to individual operations of fuel cell or battery system. A dc/dc converter is applied which provides an optimal control of power flow among fuel cell, battery and load. The proposed system efficiently overcomes the electrochemical constraints like over current, battery leakage current, and over and under voltage dips. By formulation of an intelligent algorithm and incorporating a digital technology (AVR Microcontroller), an efficient control is achieved over fuel cell current limit, battery charge, voltage and current. The hybrid power source is tested and analyzed by carrying out simulations using MATLAB simulink. Along with the attainment of desired complex load profiles, the proposed design can also be used for power enhancement and optimization for different capacities. (author)

Computational Intelligence in Intelligent Data Analysis

CERN Document Server

Nürnberger, Andreas

2013-01-01

Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intell...

micROS: a morphable, intelligent and collective robot operating system.

Science.gov (United States)

Yang, Xuejun; Dai, Huadong; Yi, Xiaodong; Wang, Yanzhen; Yang, Shaowu; Zhang, Bo; Wang, Zhiyuan; Zhou, Yun; Peng, Xuefeng

2016-01-01

Robots are developing in much the same way that personal computers did 40 years ago, and robot operating system is the critical basis. Current robot software is mainly designed for individual robots. We present in this paper the design of micROS, a morphable, intelligent and collective robot operating system for future collective and collaborative robots. We first present the architecture of micROS, including the distributed architecture for collective robot system as a whole and the layered architecture for every single node. We then present the design of autonomous behavior management based on the observe-orient-decide-act cognitive behavior model and the design of collective intelligence including collective perception, collective cognition, collective game and collective dynamics. We also give the design of morphable resource management, which first categorizes robot resources into physical, information, cognitive and social domains, and then achieve morphability based on self-adaptive software technology. We finally deploy micROS on NuBot football robots and achieve significant improvement in real-time performance.

Before and Beyond Anticipatory Intelligence: Assessing the Potential for Crowdsourcing and Intelligence Studies

Directory of Open Access Journals (Sweden)

Alexander Halman

2015-10-01

Full Text Available Crowdsourcing is a new tool for businesses, academics, and now intelligence analysts. Enabled by recent technology, crowdsourcing allows researchers to harness the wisdom of crowds and provide recommendations and insight into complex problems. This paper examines the potential benefits and limitations of crowdsourcing for intelligence analysis and the intelligence community beyond its primary use: anticipatory intelligence. The author constructs a model and compares it to existing crowdsourcing theories in business, information science, and public policy. Finally, he offers advice for intelligence analysis and public policy.

The effect of varying talker identity and listening conditions on gaze behavior during audiovisual speech perception.

Science.gov (United States)

Buchan, Julie N; Paré, Martin; Munhall, Kevin G

2008-11-25

During face-to-face conversation the face provides auditory and visual linguistic information, and also conveys information about the identity of the speaker. This study investigated behavioral strategies involved in gathering visual information while watching talking faces. The effects of varying talker identity and varying the intelligibility of speech (by adding acoustic noise) on gaze behavior were measured with an eyetracker. Varying the intelligibility of the speech by adding noise had a noticeable effect on the location and duration of fixations. When noise was present subjects adopted a vantage point that was more centralized on the face by reducing the frequency of the fixations on the eyes and mouth and lengthening the duration of their gaze fixations on the nose and mouth. Varying talker identity resulted in a more modest change in gaze behavior that was modulated by the intelligibility of the speech. Although subjects generally used similar strategies to extract visual information in both talker variability conditions, when noise was absent there were more fixations on the mouth when viewing a different talker every trial as opposed to the same talker every trial. These findings provide a useful baseline for studies examining gaze behavior during audiovisual speech perception and perception of dynamic faces.

2015 Chinese Intelligent Systems Conference

CERN Document Server

Du, Junping; Li, Hongbo; Zhang, Weicun; CISC’15

2016-01-01

This book presents selected research papers from the 2015 Chinese Intelligent Systems Conference (CISC’15), held in Yangzhou, China. The topics covered include multi-agent systems, evolutionary computation, artificial intelligence, complex systems, computation intelligence and soft computing, intelligent control, advanced control technology, robotics and applications, intelligent information processing, iterative learning control, and machine learning. Engineers and researchers from academia, industry and the government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.

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

Science.gov (United States)

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

2017-05-01

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

Can Artificial Intelligence and Online Dispute Resolution enhance efficiency and effectiveness in Courts

Directory of Open Access Journals (Sweden)

John Zeleznikow

2017-05-01

Full Text Available The growing rise in the number of self-represented litigants has negative implications for both the court system and access to justice. The expanding use of Artificial Intelligence and the World Wide Web has led to the development and use of Online Dispute Resolution. In this article we investigate a number of systems in Australian Family Law that enhance Alternative Dispute Resolution and Access to Justice. We discuss how a hybrid system that incorporates advice about BATNAs and potential trade-offs as well as allowing online communication can enhance access to justice.

Intelligence and the machinery of government: conceptualizing the intelligence community

OpenAIRE

Davies, PHJ

2010-01-01

This article argues that the failure to address intelligence agencies as public organizations part and parcel with the overt machinery of government constitutes a significant lacuna both in the specialist study of intelligence and the broader discipline of public administration studies. The role and status of intelligence institutions as aspects of the machinery of central government is examined, along with the prospects of certain key paradigms in the field for understanding those institutio...

An Exploratory Study of the Ways in Which Elementary School Principals Use Their Emotional Intelligence to Address Conflict in Their Educational Organizations

Science.gov (United States)

Espinoza, Lorissa

2016-01-01

Purpose. This study described the knowledge, skills, behaviors, and strategies associated with emotional intelligence (EI) that elementary school principals used to address conflict in their organizations. This study also determined the impact EI had on elementary school principals' perceptions of their ability to lead their organizations. This…

Secular gains in fluid intelligence: evidence from the Culture-Fair intelligence test.

Science.gov (United States)

Colom, Roberto; García-López, Oscar

2003-01-01

There is no doubt about the reality of the secular increase in cognitive test scores. However, there is disagreement about a key issue: does the observed increase reflect a genuine upward trend in intelligence? Evidence from the Raven test is clear, although there are some doubts about its adequacy as a fine-grained measure of fluid intelligence. Evidence from the so-called 'method of correlated vectors' is much less clear. When a crystallized battery is considered, the results leave little doubt: the increase does not reflect gains in general intelligence. However, when a fluid battery is analysed, the increase does reflect gains in general intelligence. The present study uses one of the best available measures of fluid intelligence (the Culture-Fair intelligence test) to provide new evidence for the secular increase in fluid intelligence, beyond the findings from the Raven test and the method of correlated vectors. A total of 4498 Spanish high school students and high school graduates were tested within a time interval of 20 and 23 years, respectively. The results show that there is a clear upward trend in intelligence. Moreover, students show an average increase equivalent to 6 IQ points, while graduates show an average increase of 4 IQ points. Therefore, more selected people (graduates) show a smaller increase than less selected people (students). Some implications are discussed.

Scholastic Success: Fluid Intelligence, Personality, and Emotional Intelligence

Science.gov (United States)

Downey, Luke A.; Lomas, Justine; Billings, Clare; Hansen, Karen; Stough, Con

2014-01-01

The aim of the current study was to examine the role of fluid intelligence, personality traits, and emotional intelligence (EI) in predicting female Year 9 students' grade point average (GPA) and to determine whether any differences in scholastic performance were related to differences in EI or Personality. Two-hundred and forty-three female…

Perceived emotional intelligence, general intelligence and early professional success: predictive and incremental validity

Directory of Open Access Journals (Sweden)

José-Manuel de Haro

2014-05-01

Full Text Available Although the study of factors affecting career success has shown connections between biographical and other aspects related to ability, knowledge and personality, few studies have examined the relationship between emotional intelligence and professional success at the initial career stage. When these studies were carried out, the results showed significant relationships between the dimensions of emotional intelligence (emotional self-awareness, self-regulation, social awareness or social skills and the level of professional competence. In this paper, we analyze the relationship between perceived emotional intelligence, measured by the Trait Meta-Mood Scale (TMMS-24 questionnaire, general intelligence assessed by the Cattell factor "g" test, scale 3, and extrinsic indicators of career success, in a sample of 130 graduates at the beginning of their careers. Results from hierarchical regression analysis indicate that emotional intelligence makes a specific contribution to the prediction of salary, after controlling the general intelligence effect. The perceived emotional intelligence dimensions of TMMS repair, TMMS attention and sex show a higher correlation and make a greater contribution to professional success than general intelligence. The implications of these results for the development of socio-emotional skills among University graduates are discussed.

Multiple intelligences in school

Directory of Open Access Journals (Sweden)

Alejandro Castro Solano

2016-02-01

Full Text Available During many years has prevailed the idea of intelligence as a single problem solving ability (factor g considered the best predictor of student’s academic achievement. Recently, researches have begun to take an alternative view of the problem, understanding it is a multidimensional construct. Multiple intelligences (MI theory proposed by Gardner (1983 takes into account seven talents or skills individuals appear to have in certain amount. These latent bio-psychological potentials are stable and they are mantained through life. Theory of MI proposes that every person learns in relation to them. MI theory has many educational applications, however, very few efforts have been made to verify such statements. The main goal of this study is to analyze the IM differential individual profile of high school and university students studying the relation between IM, academic achievement and self efficacy competence on course performance. Two studies were carried out , the first was done with high school students (N=500 and the second with military students (N=362. Based on Armstrong’s proposals to assess IM, an inventory was designed. Main results point out that there is a correspondence between academic attainment, self interest and self perception of competence in different courses students take. MI are good predictors of academic achievement considering specific areas but they don’t provide a better estimation compared to traditional assessment instruments. Students who have failed in school were those with more spatial and corporal abilities, usually relegated by traditional instruction. High achievers were those with more logical and intrapersonal skills. Different relations were found for military students. For these latter students IM theory was not a valuable predictor of successful academic attainment. 

Complementary Machine Intelligence and Human Intelligence in Virtual Teaching Assistant for Tutoring Program Tracing

Science.gov (United States)

Chou, Chih-Yueh; Huang, Bau-Hung; Lin, Chi-Jen

2011-01-01

This study proposes a virtual teaching assistant (VTA) to share teacher tutoring tasks in helping students practice program tracing and proposes two mechanisms of complementing machine intelligence and human intelligence to develop the VTA. The first mechanism applies machine intelligence to extend human intelligence (teacher answers) to evaluate…

A Belief-Space Approach to Integrated Intelligence - Research Area 10.3: Intelligent Networks

Science.gov (United States)

2017-12-05

A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks The views, opinions and/or findings contained in this...Technology (MIT) Title: A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks Report Term: 0-Other Email: tlp...students presented progress and received feedback from the research group . o wrote papers on their research and submitted them to leading conferences

Artificial Intelligence

CERN Document Server

Warwick, Kevin

2011-01-01

if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

Intelligence of programs

Energy Technology Data Exchange (ETDEWEB)

Novak, D

1982-01-01

A general discussion about the level of artificial intelligence in computer programs is presented. The suitability of various languages for the development of complex, intelligent programs is discussed, considering fourth-generation language as well as the well established structured COBOL language. It is concluded that the success of automation in many administrative fields depends to a large extent on the development of intelligent programs.

Relationships between the Kaufman Brief Intelligence Test and the Wechsler Adult Intelligence Scale-Third Edition.

Science.gov (United States)

Walters, Steven O; Weaver, Kenneth A

2003-06-01

The Kaufman Brief Intelligence Test detects learning problems of young students and is a screen for whether a more comprehensive test of intelligence is needed. A study to assess whether this test was valid as an adult intelligence test was conducted with 20 undergraduate psychology majors. The correlations between the Kaufman Brief Intelligence Test's Composite, Vocabulary, and Matrices test scores and their corresponding Wechsler Adult Intelligence Scale-Third Edition test scores, the Full Scale (r=.88), Verbal (r=.77), and Performance scores (r=.87), indicated very strong relationships. In addition, no significant differences were obtained between the Composite, Vocabulary, and Matrices means of the Kaufman Brief Intelligence Test and the Full Scale, Verbal, and Performance means of the WAIS-III. The Kaufman Brief Intelligence Test appears to be a valid test of intelligence for adults.

Phenotypic and genetic relations between the HEXACO dimensions and trait emotional intelligence.

Science.gov (United States)

Veselka, Livia; Petrides, K V; Schermer, Julie Aitken; Cherkas, Lynn F; Spector, Tim D; Vernon, Philip A

2010-02-01

The present study investigated the location of trait emotional intelligence (trait EI or trait emotional self-efficacy) within the context of the HEXACO model - a more comprehensive personality framework than the conventional Big Five structure. A total of 666 MZ and 526 DZ adult twin pairs from the United Kingdom completed the short form of the Trait Emotional Intelligence Questionnaire (TEIQue-SF) and the short form of the HEXACO Personality Inventory (HEXACO-60). Many significant phenotypic correlations between the TEIQue-SF and the HEXACO-60 were obtained, which were strongest for HEXACO Extraversion, and weakest for HEXACO Honesty-Humility. As was expected, Emotionality was the only HEXACO dimension to correlate negatively with TEIQue-SF scores. Bivariate behavioral genetic analyses revealed that all phenotypic correlations were attributable to common genetic and common nonshared environmental factors. The study confirms the validity of trait EI as a constellation of emotional self-perceptions located at the lower levels of personality.

Fluid intelligence: A brief history.

Science.gov (United States)

Kent, Phillip

2017-01-01

The concept of fluid and crystallized intelligence was introduced to the psychological community approximately 75 years ago by Raymond B. Cattell, and it continues to be an area of active research and controversy. The purpose of this paper is to provide a brief overview of the origin of the concept, early efforts to define intelligence and uses of intelligence tests to address pressing social issues, and the ongoing controversies associated with fluid intelligence and the structure of intelligence. The putative neuropsychological underpinnings and neurological substrates of fluid intelligence are discussed.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

Science.gov (United States)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

A hybrid simulated annealing approach to handle energy resource management considering an intensive use of electric vehicles

DEFF Research Database (Denmark)

Sousa, Tiago; Vale, Zita; Carvalho, Joao Paulo

2014-01-01

The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed...... to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated...... annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA...

Educational Programs for Intelligence Professionals.

Science.gov (United States)

Miller, Jerry P.

1994-01-01

Discusses the need for education programs for competitive intelligence professionals. Highlights include definitions of intelligence functions, focusing on business intelligence; information utilization by decision makers; information sources; competencies for intelligence professionals; and the development of formal education programs. (38…

Exploring the relationships among attachment, emotional intelligence and communication.

Science.gov (United States)

Cherry, M Gemma; Fletcher, Ian; O'Sullivan, Helen

2013-03-01

Attachment style has been shown to influence both emotional intelligence (EI) and the clinical communication of medical students and doctors. No research has assessed the relationships among attachment, EI and clinical communication in medical students. This study was conducted to evaluate the effect of EI on the relationship between medical students' attachment style and clinical communication. Medical students were invited to complete measures of attachment (using the Experiences in Close Relationships-Short Form [ECR-SF], a 12-item measure that provides attachment avoidance and attachment anxiety dimensional scores) and EI (using the Mayer-Salovey-Caruso Emotional Intelligence Test [MSCEIT], a 141-item measure of the perception, use, understanding and management of emotions) at the end of Year 1, prior to a summative objective structured clinical examination (OSCE). Clinical communication was assessed using OSCE scores. Structural equation modelling (SEM) was used to analyse a hypothetical model of the relationships among attachment style, EI and clinical communication. A total of 200 of 358 (55.9%) students participated. Attachment avoidance was significantly negatively correlated with total EI scores (r=-0.28, pcommunication. © Blackwell Publishing Ltd 2013.

Groundwater vulnerability indices conditioned by Supervised Intelligence Committee Machine (SICM).

Science.gov (United States)

Nadiri, Ata Allah; Gharekhani, Maryam; Khatibi, Rahman; Sadeghfam, Sina; Moghaddam, Asghar Asghari

2017-01-01

This research presents a Supervised Intelligent Committee Machine (SICM) model to assess groundwater vulnerability indices of an aquifer. SICM uses Artificial Neural Networks (ANN) to overarch three Artificial Intelligence (AI) models: Support Vector Machine (SVM), Neuro-Fuzzy (NF) and Gene Expression Programming (GEP). Each model uses the DRASTIC index, the acronym of 7 geological, hydrological and hydrogeological parameters, which collectively represents intrinsic (or natural) vulnerability and gives a sense of contaminants, such as nitrate-N, penetrating aquifers from the surface. These models are trained to modify or condition their DRASTIC index values by measured nitrate-N concentration. The three AI-techniques often perform similarly but have differences as well and therefore SICM exploits the situation to improve the modeled values by producing a hybrid modeling results through selecting better performing SVM, NF and GEP components. The models of the study area at Ardabil aquifer show that the vulnerability indices by the DRASTIC framework produces sharp fronts but AI models smoothen the fronts and reflect a better correlation with observed nitrate values; SICM improves on the performances of three AI models and cope well with heterogeneity and uncertain parameters. Copyright © 2016 Elsevier B.V. All rights reserved.

Spiritual intelligence of nurses in two Chinese social systems: a cross-sectional comparison study.

Science.gov (United States)

Yang, Ke-Ping; Wu, Xin-Juan

2009-09-01

The spirituality of healthcare providers and their clients is becoming a crucial issue in a world increasingly preoccupied with material issues. In light of such, how do nurses enhance their spiritual intelligence against such materialist pressures? After a 60-year separation of Chinese on both sides of the Taiwan Strait and the rancor between their two governments, what are the similarities and the differences in nurse spirituality profiles between these two different societies? With increasing contact between the two, this issue should be examined and explored, as it has the potential to become an essential unspoken element underpinning holistic care quality. The purpose of this study was to compare spiritual intelligence between nurses in two different Chinese societies. A cross-sectional descriptive and inferential study was conducted at five medical centers in China and Taiwan. A total of 524 registered hospital nurses were recruited as participants. We used R. N. Wolman's (2001) self-reported PsychoMatrix Spirituality Inventory to measure participant levels of spiritual intelligence. The PsychoMatrix Spirituality Inventory incorporated seven factors, including divinity, mindfulness, extrasensory perception, community, intellectuality, trauma, and childhood spirituality. Results showed that social systems did have an impact on nurses' spiritual intelligence. Childhood spirituality and religious beliefs and activities greatly affected and effectively predicted nurses' spiritual intelligence. Nurses on either side of the Taiwan Strait all reported a need to deal with their daily lives pragmatically, objectively, and rationally and relied on empirical evidence in work settings. As social and economic contacts increase across the Taiwan Strait, it is imperative that nurses adopt cultural awareness and sensitivity as they provide holistic care to clients. This study opens doors to dialogue about and a better understanding of nurses' spiritual intelligence in Taiwan

Harmonizing intelligence terminologies in business: Literature review

Directory of Open Access Journals (Sweden)

Sivave Mashingaidze

2014-11-01

Full Text Available The principal objective of this article is to do a literature review of different intelligence terminology with the aim of establishing the common attributes and differences, and to propose a universal and comprehensive definition of intelligence for common understanding amongst users. The findings showed that Competitive Intelligence has the broadest scope of intelligence activities covering the whole external operating environment of the company and targeting all levels of decision-making for instance; strategic intelligence, tactical intelligence and operative intelligence. Another terminology was found called Cyber IntelligenceTM which encompasses competitor intelligence, strategic intelligence, market intelligence and counterintelligence. In conclusion although CI has the broadest scope of intelligence and umbrella to many intelligence concepts, still Business Intelligence, and Corporate Intelligence are often used interchangeably as CI

Dealing with distributed intelligence in monitoring and control systems

International Nuclear Information System (INIS)

McLaren, R.A.

1981-01-01

The Euorpean Hybrid Spectrometer is built up of many individual detectors, each having widely varying monitoring and control requirements. With the advent of cheap microprocessor systems a shift from the concept of a single monitoring and control computer of that of distributed intelligent controllers has been economically feasible. A detector designer can now thoroughly test and debug a complete monitoring and control system on a local, dedicated micro-computer, while during operation, the central computer can be relieved of many simple repetitive tasks. Rapidly, however, it has become obvious that the designers of these systems have to take into account the final operational environment and build into both the hardware and software, features allowing easy integration into a central monitoring and control chain. In addition, the problems of maintenance and enventual modification have to be taken into consideration early in the development. Examples of currently operational systems will be briefly described to demonstrate how a set of basic guidelines plus standardisation of hardware/software can minimise the problems of integration and maintenance. Based on practical experience gained in the European Hybrid Spectrometer, investigations are proceeding on various possible alternatives for future micro-computer based monitoring and control systems. (orig.)

A Study of Spiritual Intelligence of the Pre-Service Teachers at the Secondary Stage in Relation to Self Esteem and Emotional Maturity

Science.gov (United States)

Vibha, Keerti

2011-01-01

The study was conducted on a sample of 500 B.Ed. teacher trainees from School of Education, Lovely Professional University, Phagwara. Spiritual Intelligence and its dimensions of Transcendence, Interconnectedness, Expansion of Self, Extrasensory Perception and Existential Enquiry were taken up as dependent variables and whereas Self Esteem and…

Business Intelligence using Software Agents

OpenAIRE

Ana-Ramona BOLOGA; Razvan BOLOGA

2011-01-01

This paper presents some ideas about business intelligence today and the importance of developing real time business solutions. The authors make an exploration of links between business intelligence and artificial intelligence and focuses specifically on the implementation of software agents-based systems in business intelligence. There are briefly presented some of the few solutions proposed so far that use software agents properties for the benefit of business intelligence. The authors then...

78 FR 32241 - Defense Intelligence Agency National Intelligence University Board of Visitors; Notice of Closed...

Science.gov (United States)