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2014 IEEE International Conference on systems, Man, and Cybernetics, SMC 2014

作者： Lotfi, Ehsan Khosravi, Abbas Akbarzadeh, M.-R. Nahavandi, Saeid Department of Computer Engineering Torbat-e-Jam Branch Islamic Azad University Torbat-e-Jam Iran Center for Intelligence Systems Research Deakin University Geelong3217 Australia Departments of Electrical and Computer Engineering Center of Excellence on Soft Computing and Intelligent Information Processing Ferdowsi University of Mashhad Iran Centre for Intelligent Systems Research Deakin University 75 Pigdons Road Waurn PondsVIC3216 Australia

ISBN: (纸本)9781479938407

Emotional neural network (ENN) is a recently developed methodology that uses simulated emotions aiding its learning process. ENN is motivated by neurophysiological knowledge of the human's emotional brain. In this paper, ENNs are developed and examined for prediction tasks. Genetic algorithm is applied for optimal tuning of crisp numerical parameters of ENN. The performance of the proposed ENN is examined using data sets for a couple of synthetic (with constant and variable noise) and real world (wind farm power generation data) case studies. A traditional artificial neural network (ANN) is also implemented for comparison purposes. Numerical results indicate the superiority of ENN over ANN in terms of accuracy and stability. © 2014 IEEE.

关键词： Wind power

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The Use of a PMU-Based State Estimator for Tracking Power System Dynamics

The Use of a PMU-Based State Estimator for Tracking Power Sy...

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IEEE Power and Energy Society General Meeting

作者： Markos Asprou Elias Kyriakides Saikat Chakrabarti Department of Electrical and Computer Engineering KIOS Research Center for Intelligent Systems and Networks University of Cyprus Department of Electrical Engineering Indian Institute of Technology Kanpur

ISBN: (纸本)9781479964161

Monitoring of the power system states in real time, especially after the occurrence of a fault, can enhance the situational awareness of the power system operators. Although the state estimator is designed for monitoring steady state conditions of the power system, the advent of Synchronized Measurement Technology (SMT) can make the state estimator a helpful tool for monitoring the power system operating condition in quasi real time. In this paper, the use of a linear state estimator using only synchronized phasor measurements will be presented. The innovation lies in the use of the linear state estimator for the estimation of the states of the system in the presence of a fault. With the proper PMU placement, all system buses can be monitored accurately and the voltage/angle behavior can be tracked with precision.

关键词： Fault monitoring Linear state estimator Real time monitoring Synchronized phasor measurements

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Opening remarks

2016 International Conference on Advances in Human Machine I...

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2016 International Conference on Advances in Human Machine Interaction, HMI 2016 2016年

作者： Nagaraja, Ch. Swamy, J. Nagendra Rajendra, J. Khan, M.S. Vishwanath Reddy, D.S. Manjunath, N. Dillmann, Ruediger Tarn, Tzyh Jong Zhao, Qianchuan Ammi, Mehdi Zuberek, Wlodek M. Sandhu, P.S. Patthira Newman, K. De Silva Liyanage, Chandratilak Hassan, Sohair Aly Aly Sun, Kien Wen Rahman, Md. Moshiur Ordoño, E. Evangelista Sharma, R.K. Mishra, Preeti Chandel, B.S. Singla, Ekta Petric, Tadej Zhong, Yu Jiglar, Janson Alemzadeh, Kazem Asokan, T. Tripathi, Animesh Tripathi, Manoj Ram, Swaminath Shrma, M.K. Panday, P.N. Kumar, Devendra Hinchey, Mike Stilman, Boris Suraj, Zbigniew Pal, Sankar K. Sasi, Sreela Rajan, Deepu Marshall, Roger G. Abraham, Ajith Peter S, David Paul, Vargheese Gopakumar, V. Dustdar, Schahram Soto, Sebastián Ventura Rausch, Andreas Angelis, Lefteris Nelson, Andrew L. Botzheim, Janos Bernardino, Heder Soares Zboril, Frantisek Ane, Bernadetta Kwintiana Maeda, Toshiyuki Sakalauskas, Virgilijus Hann, Garenth Lim King Samek, Jan Romero Salguero, José Raúl Varghese, Kuruvilla Kriksciuniene, Dalia Mathew, Jimson Reif, Wolfgang Mauri, Giancarlo Cabrerizo Lorite, Francisco Javier Özcan, Ender Cho, Sung-Bae Paily, Roy P. Rezankova, Hana Tudjarov, Boris Hong, Wei-Chiang De Oliveira, José Valente Flores Romero, Juan Jose Oskouei, Rozita Jamili Cicchetti, Antonio Roy, Chanchal Segura, Sergio Samuel, C. Mallet, Frédéric Mernik, Marjan Punnekkat, Sasikumar Waseemulla, A. Sri Devaraj Urs Educational Trust Bangalore India R. L. Jalappa Institute of Technology Doddaballapur Bangalore India Humanoids and Intelligence Systems Lab Kalsruhe Germany Electrical and Systems Engineering Washington University in St. Louis United States Deputy Director of Center for Intelligent and Networked Systems Department of Automation Tsinghua University Beijing China Department of Computer Science CNRS/LIMSI Lab AMI Group France Memorial University St. John'sNL Canada RBIT and Bio-Technology India LR University Thailand University of Colorado at Boulder Boulder United States Faculty of Science University of Brunei Brunei University of Kuala Lumpur Malaysia National Chiao Tung University Taiwan EPR Centre Bangladesh Mapua Institute of Technology Philippines ARO CWC Lucknow India Mpec Kanpur India DSC DBS Kanpu India Indian Institute of Technology Ropar India Jozaf Stefan Institute Department of Automation Biocyernetics and Robotics Ljubljana Slovenia Robotics Institute Carnegie Mellon University Pittsburgh United States Faculty of Engineering University of Bristol United Kingdom Department of Engineering Design Indian Institute of Technology Madras India Lucknow Uni Lucknow India CSJM Uni Kanpur India UPPCB Lucknow India PCB Roorkee India Awadh Uni Faijabad India Agra Uni Agra India Lero University of Limerick Ireland University of Colorado Denver United States University of Rzeszow Poland Indian Statistical Institute Kolkata India Gannon University PA United States Nanyang Technical University Singapore Singapore Plymouth State University NH United States MIR Labs United States Cochin University of Science and Technology India State Project Facilitation Unit TEQIP Kerala India Technical University of Vienna Austria University of Cordoba Spain Clausthal University of Technology Germany Aristotle University of Thessaloniki Greece Androtics LLC TucsonAZ United States Tokyo Metropolitan University Japan Federal Unive

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Flexible triangular formation keeping of marine robotic vehicles using range measurements 19

Flexible triangular formation keeping of marine robotic vehi...

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19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014

作者： Rego, Francisco Soares, Jorge M. Pascoal, António Aguiar, A. Pedro Jones, Colin Laboratory of Robotics and Systems in Engineering and Science Instituto Superior Técnico University of Lisbon Lisbon Portugal Department of Electrical and Computer Engineering Faculty of Engineering University of Porto Porto Portugal Institute of Mechanical Engineering School of Engineering École Polytechnique Fédérale de Lausanne Lausanne Switzerland Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering École Polytechnique Fédérale de Lausanne Lausanne Switzerland National Institute of Oceanography Dona Paula Goa India

ISBN: (纸本)9783902823625

This paper addresses the problem of keeping an autonomous marine vehicle in a moving triangular formation by regulating its position with respect to two leader vehicles. The follower vehicle has no prior knowledge of the path described by the leaders but has access to their heading angle and is able to measure inter-vehicle ranges. It is assumed that the distance between the leaders is constant and known. A control strategy is adopted that generates speed and heading commands so as to drive suitably defined along track and cross track errors to zero. The commands are used as input to local inner loops for yaw and speed control. The paper describes the algorithms derived for range-based control and assesses their performance in simulations using realistic models of the vehicles involved. Tests with three autonomous marine vehicles equipped with acoustic modems and ranging devices allow for the evaluation of the performance of the algorithms in a real-world situation. © IFAC.

关键词： Vehicle performance

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Adaptive frequency control application for a real autonomous islanded grid

Adaptive frequency control application for a real autonomous...

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IEEE Power and Energy Society General Meeting

作者： Yiannis Tofis Yiasoumis Yiasemi Elias Kyriakides Klaus Kansala Department of Electrical and Computer Engineering KIOS Research Center for Intelligent Systems and Networks University of Cyprus VTT Technical Research Centre of Finland

ISBN: (纸本)9781479964161

This paper presents an adaptive frequency remote control of an islanded autonomous grid equipped with a 5.5 kW wind generator, 7.2 kW solar panels, and 58 kWh energy storage. The islanded grid is located at VTT premises in Finland. The grid was controlled remotely from Cyprus using a communication protocol. The ultimate aim of the work described in this paper is to control and balance the generation and demand in the islanded grid through direct load management based on a single point measurement of the electric frequency.

关键词： Adaptive frequency control Frequency response Direct load management Islanded grid

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Prediction of Atheromatic Plaque Evolution in Carotids using Features extracted from the Arterial Geometry

Prediction of Atheromatic Plaque Evolution in Carotids using...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Paschalis A. Bizopoulos Antonis I. Sakellarios Dimitrios D. Koutsouris Jannis Kountouras Lazaros Kostretzis Stella Karagergou Lampros K. Michalis Dimitrios I. Fotiadis the Biomedical Engineering Laboratory School of Electrical and Computer Engineering National Technical University of Athens (NTUA) GR 15773 Zografou Athens Greece the Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering University of Ioannina GR 45110 Ioannina Greece the Department of Medicine Second Medical Clinic Aristotle University of Thessaloniki Ippokration Hospital Thessaloniki Greece the First Orthopaedic Department G.Papanikolaou Hospital GR 5701 Exohi Thessaloniki Greece the Obstetricts and Gynecology Department General Hospital of Serres Ag. Ioannis GR 62100 Serres Greece the Michaelideion Cardiac Center Department of Cardiology in Medical School GR 45110 University of Ioannina Ioannina Greece

ISBN: (纸本)9781424492695

Knowing the arterial geometry might be helpful in the assessment of a plaque rupture event. We present a proof of concept study implementing a novel method which can predict the evolution in time of the atheromatic plaque in carotids using only statistical features which are extracted from the arterial geometry. Four feature selection methods were compared: Quadratic Programming Feature Selection (QPFS), Minimal Redundancy Maximal Relevance (mRMR), Mutual Information Quotient (MIQ) and Spectral Conditional Mutual Information (SPECCMI). The classifier used is the Support Vector Machines (SVM) with linear and Gaussian kernels. The maximum accuracy that was achieved in predicting the variation in the mean value of the Lumen distance from the centerline and the thickness was 71.2% and 70.7% respectively.

关键词： QPFS MIQ SPECCMI

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Determining mood via emotions observed in face by induction

Determining mood via emotions observed in face by induction

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Mojgan Hashemian Hadi Moradi Maryam S Mirian Mehdi Tehrani-doost Advanced Robotics and Intelligent Systems Lab University of Tehran Iran School of Electrical and Computer Engineering University of Tehran Iran Department of Psychiatry Tehran University of Medical Science Iran

Determining the mood of a person is an important step in the Human-Robot interaction. In this paper, we propose a human-inspired approach in which the changes in emotions, done using emotion induction, can be used to determine the mood of a person. The emotion induction, which can be done through robot actions or through showing video clips, stimulates changes in the emotions of the person, reducing the observation time needed to estimate mood. Consequently, the changes in the emotions, which are biased by his/her mood can be used by a robot to determine the mood of a person. To do so, we induced happy emotions by showing a comical clip and measured the intensity of each happy and sad emotions, and also the intensity of the neutral state. Then we extracted a feature set, including both time and frequency domain features, which is used to determine the mood of the person. The approach has been implemented and compared to no-emotion-induction approach and shows better results. Based on the classification results, the approach is able to distinguish between good vs. bad moods with the accuracy of 91.5% with 0.1 mean absolute error. But the neutral state was not distinguishable well.

关键词： Mood Robots Accuracy Feature extraction Face Educational institutions Human-robot interaction

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Determining mood using emotional features

Determining mood using emotional features

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International Symposium on Telecommunications, IST

作者： Mojgan Hashemian Amin Nikoukaran Hadi Moradi Maryam S Mirian Mehdi Tehrani-doost Advanced Robotics and Intelligent Systems Lab University of Tehran Iran School of Electrical and Computer Engineering University of Tehran Iran Department of Psychiatry Tehran University of Medical Science Iran

The ability to determine mood is one of fundamental challenges in affective computing. In this paper, we present a novel approach for mood detection via emotional variations. In this approach, the mood is considered as a low magnitude and more stable, i.e. low frequency, emotion that can be detected using emotion detection approaches. A Bayes classification is applied on a feature vector composed of statistical aspects of the intensity of the emotions. The approach has been implemented in which two emotions, i.e. happiness and sadness, and also neutral state, have been targeted to determine the good, bad, and neutral, mood of subjects respectively. A Bayes classification is applied on a feature vector containing statistical aspects of the intensity of the emotions. The obtained Correct Classification Rate (CCR) is 91.1, with 0.09 mean error and variance of 4.9 discriminating good mood vs. neutral.

关键词： Mood Educational institutions Face Videos computers Mice Accuracy

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Control of a humanoid robot via N200 potentials

Control of a humanoid robot via N200 potentials

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World Congress on intelligent Control and Automation (WCICA)

作者： Mengfan Li Wei Li Jing Zhao Qinghao Meng Genshe Chen Institute of Robotics and Autonomous Systems Tianjin University Tianjin China Department of Computer & Electrical Engineering and Computer Science California State University Bakersfield California USA Intelligent Fusion Technology Inc Germantown MD

In this paper, we present a N200 model for control of a humanoid robot with mind. N200 is a major component of the motion visual evoked potential (mVEP) which can be used to detect the subject's intention. In order to acquire N200, we design a visual stimulus interface in which the activation of a stimulus is a bar scanning above the image of a humanoid robot behavior. By analyzing brain signals induced by this kind of stimulus and calculating some system indexes, the results of this study demonstrate that the designed interface can induce prominent N200 potentials, and another component P300 induced by this experiment can be considered as another characteristic of the feature vector to contribute to the classification. To our best knowledge, this paper would be the first report on an application of N200 model to control a humanoid robot with visual feedback in real time.

关键词： Visualization Accuracy Humanoid robots Feature extraction Support vector machine classification Legged locomotion

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Corneal nerve morphometry for diabetic peripheral neuropathy assessment

Corneal nerve morphometry for diabetic peripheral neuropathy...

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International Conference on Health Informatics, ICHI 2013

作者： Silva, Susana Figueiredo. Otel, Iulian Gouveia, Sofia Gomes, Leonor Negrão, Luís Quadrado, Maria João Gonçalves, Nuno Barreto, João Pedro Morgado, António Miguel IBILI - Institute for Biomedical Imaging and Life Sciences University of Coimbra Coimbra Portugal Department of Endocrinology Diabetes and Metabolism Portugal Department of Neurology Portugal Department of Ophthalmology Coimbra Hospital University Center Coimbra Portugal ISR - Institute of Systems and Robotics University of Coimbra Coimbra Portugal Department of Electrical and Computer Engineering University of Coimbra Coimbra Portugal Department of Physics University of Coimbra Coimbra Portugal

ISBN: (纸本)9783319030043

Diabetic peripheral neuropathy (DPN) is one of the more common complications of diabetes, being associated to 50-75% of non-traumatic amputations. Early diagnosis of DPN often fails or occurs only when patients became symptomatic due to the non-availability of a simple, reliable, noninvasive method. We present the results of a pilot study where we used peripheral nerves morphometric information, retrieved from images of the corneal sub-basal nerve plexus, obtained in vivo by corneal confocal microscopy, to identify and stage patients with DPN. Nerve segmentation was done manually and using an automatic algorithm. Both standard statistical techniques and classification techniques were used for DPN identification. With manual segmentation, differences were found between controls and patients with mild and moderate DPN, for the nerve fiber length and density parameters. A simple comparison between individuals with and without DPN results in significant differences for those parameters, as well as for branching pattern and density. No differences were found with automatic segmentation. Simple classification techniques based on manually extracted parameters were tested for identification of DPN patients. The best results were obtained with a binary tree classifier, using PCA transformed data, for a pruning level 9. The classifier accuracy was 87%. The results confirm that morphometric analysis of corneal nerves images may be used as a complementing technique for DPN diagnosis. A fully automatic tool for identifying and staging DPN patients requires additional work on the nerve segmentation algorithm and the use of more robust classifiers with additional reliance on image features other than the tested morphometric parameters. © 2014, Springer International Publishing Switzerland.

关键词： Confocal microscopy

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