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The Imperialist Competitive Algorithm for Optimal Multi-Objective Location and Sizing of DSTATCOM in Distribution Systems Considering Loads Uncertainty

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INAE Letters 2017年第3期2卷 83-95页

作者： Sedighizadeh, Mostafa Eisapour-Moarref, Amir Faculty of Electrical and Computer Engineering Shahid Beheshti University Tehran Iran Centre of Excellence for Power System Automation and Operation Iran University of Science and Technology Tehran Iran

The optimal location and sizing of distribution static compensator (DSTATCOM) in distribution systems is a complex nonlinear problem. This problem is constrained by various technical limits and can offer different objectives that would provide many benefits to the network. These include minimization of power losses, index of voltage profile, load balancing index, and annual cost saving index which have been considered in this paper. In the present work, the Imperialist Competitive Algorithm (ICA) is employed for optimizing the distribution systems where an optimal location and sizing of DSTATCOM is investigated. In this study, an aggregating operator named Max-geometric mean is used for combination of objectives and providing overall objective function. The scaling of objectives is performed in the fuzzy framework. The proposed algorithm is implemented in 33 and 69 buses IEEE test systems. Furthermore, the uncertainty of the loads of the balanced system is modeled by using a fuzzy technique. Based on the numerical results of this work, one can extract that the performance of the ICA is slightly higher than other meta-heuristic algorithms; hence the introduced approach can be used by utility services for optimal DSTATCOM allocation and sizing in the distribution systems.

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Access neuro-fuzzy controller for W-CDMA networks

Access neuro-fuzzy controller for W-CDMA networks

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International Scientific-Practical Conference Problems of Infocommunications Science and Technology

作者： Olena Semenova Andriy Semenov Pavel Kulakov Faculty for Radio Engineering Telecommunication and Electronic Instrument Engineering Vinnytsia National Technical University Vinnytsia Ukraine Faculty for Computer Systems and Automation Vinnytsia National Technical University Vinnytsia Ukraine

ISBN: (纸本)9781538609842

The paper proposes to apply a neuro-fuzzy controller in telecommunication networks for call admission control enabling congestion avoidance in W-CDMA networks. A structure of the neuro-fuzzy controller has been proposed. Input and output linguistic variables, their terms as well as membership functions have been developed. Also, a rule base of the controller has been suggested. Functioning of the neuro-fuzzy controller has been simulated and trained.

关键词： Erbium Neural networks Communications technology computer science Artificial intelligence computer applications Cybernetics

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Reward Processing in Novelty Seekers: A Transdiagnostic Psychiatric Imaging Biomarker

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BIOLOGICAL PSYCHIATRY 2021年第8期90卷 529-539页

作者： Qi, Shile Schumann, Gunter Bustillo, Juan Turner, Jessica A. Jiang, Rongtao Zhi, Dongmei Fu, Zening Mayer, Andrew R. Vergara, Victor M. Silva, Rogers F. Iraji, Armin Chen, Jiayu Damaraju, Eswar Ma, Xiaohong Yang, Xiao Stevens, Michael Mathalon, Daniel H. Ford, Judith M. Voyvodic, James Mueller, Bryon A. Belger, Aysenil Potkin, Steven G. Preda, Adrian Zhuo, Chuanjun Xu, Yong Chu, Congying Banaschewski, Tobias Barker, Gareth J. Bokde, Arun L. W. Quinlan, Erin Burke Desrivieres, Sylvane Flor, Herta Grigis, Antoine Garavan, Hugh Gowland, Penny Heinz, Andreas Martinot, Jean-Luc Martinot, Marie-Laure Paillere Artiges, Eric Nees, Frauke Orfanos, Dimitri Papadopoulos Paus, Tomas Poustka, Luise Hohmann, Sarah Frohner, Juliane H. Smolka, Michael N. Walter, Henrik Whelan, Robert Calhoun, Vince D. Sui, Jing [a]Tri-institutional Center for Translational Research in Neuroimaging and Data Science Georgia State University Georgia Institute Technology and Emory University Atlanta Georgia [b]Department of Psychiatry University of New Mexico Albuquerque New Mexico [c]Department of Psychology Georgia State University Atlanta Georgia [d]Olin Neuropsychiatry Research Center Hartford Connecticut [e]Department of Psychiatry University of California San Francisco San Francisco California [f]Department of Radiology Duke University Durham North Carolina [g]Department of Psychiatry University of North Carolina at Chapel Hill Chapel Hill North Carolina [h]Department of Psychiatry University of Minnesota Minneapolis Minnesota [i]Department of Psychiatry University of California Irvine Irvine California [j]Departments of Psychiatry and Psychology University of Vermont Burlington Vermont [k]Centre for Population Neuroscience and Stratified Medicine Institute for Science and Technology of Brain-Inspired Intelligence Fudan University Shanghai China [l]University of Chinese Academy of Sciences Beijing China [dd]Department of Computer Science and Engineering Nanjing University of Aeronautics and Astronautics Nanjing China [m]Brainnetome Center and National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China [ee]State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University Beijing China [n]Psychiatric Laboratory and Mental Health Center the State Key Laboratory of Biotherapy West China Hospital of Sichuan University Chengdu China [o]Department of Psychiatric-Neuroimaging-Genetics and Morbidity Laboratory Nankai University Affiliated Anding Hospital Tianjin China [p]Department of Humanities and Social Science Shanxi Medical University Taiyuan China [q]Department of Psychiatry and Psychotherapy Charité – Universitätsmedizin Berlin Campus Charité Mitte corporate member of Freie Universität Berlin Humboldt-Univers

BACKGROUND: Dysfunctional reward processing is implicated in multiple mental disorders. Novelty seeking (NS) assesses preference for seeking novel experiences, which is linked to sensitivity to reward environmental cues. METHODS: A subset of 14-year-old adolescents (IMAGEN) with the top 20% ranked high-NS scores was used to identify high-NS-associated multimodal components by supervised fusion. These features were then used to longitudinally predict five different risk scales for the same and unseen subjects (an independent dataset of subjects at 19 years of age that was not used in predictive modeling training at 14 years of age) (within IMAGEN, n z 1100) and even for the corresponding symptom scores of five types of patient cohorts (non-IMAGEN), including drinking (n = 313), smoking (n = 104), attention-deficit/hyperactivity disorder (n = 320), major depressive disorder (n = 81), and schizophrenia (n = 147), as well as to classify different patient groups with diagnostic labels. RESULTS: Multimodal biomarkers, including the prefrontal cortex, striatum, amygdala, and hippocampus, associated with high NS in 14-year-old adolescents were identified. The prediction models built on these features are able to longitudinally predict five different risk scales, including alcohol drinking, smoking, hyperactivity, depression, and psychosis for the same and unseen 19-year-old adolescents and even predict the corresponding symptom scores of five types of patient cohorts. Furthermore, the identified reward-related multimodal features can classify among attention-deficit/hyperactivity disorder, major depressive disorder, and schizophrenia with an accuracy of 87.2%. CONCLUSIONS: Adolescents with higher NS scores can be used to reveal brain alterations in the reward-related system, implicating potential higher risk for subsequent development of multiple disorders. The identified high-NS- associated multimodal reward-related signatures may serve as a transdiagnostic neuroimaging bi

关键词： ADHD Attention-deficit/hyperactivity disorder Major depressive disorders MDD Novelty seeking Reward processing Schizophrenia Substance use

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M-health predictive data analysis of daily activities and physiological conditions

M-health predictive data analysis of daily activities and ph...

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2017 International Conference on E-Health, EH 2017

作者： Bocaj, Enkeleda Queiroz, Jonas Leitão, Paulo Patrikakis, Charalampos Z Polytechnic Institute of Bragança Bragança5300-253 Portugal Faculty of Automation Engineering Piraeus University of Applied Sciences Thivon 250 Egaleo122 41 Greece Faculty of Engineering University of Porto Rua Dr. Roberto Frias Porto4200-465 Portugal LIACC - Artificial Intelligence and Computer Science Laboratory Rua Campo Alegre 1021 Porto4169-007 Portugal Faculty of Electronics Engineering Piraeus University of Applied Sciences Thivon 250 Egaleo122 41 Greece

ISBN: (纸本)9789898533654

The wearable devices technology has evolved dramatically in many respects over the last decade, e.g., in the accuracy and quality of the data provided, as well as the number of parameters measured. This created new opportunities not only in the fitness domain, but also in the well-being and general health. Indeed, each day, an ever-increasing number of people are interested in monitoring their daily habits and activities, as well as their physiological and psychological condition, aiming to improve their overall quality of life. Such tasks can be realized by the use of predictive tools that can guide and support individuals during their daily living activities. In this regard, wearable devices produce large volume of data, which should be properly analyzed in a fast and personalized manner. Furthermore, in order to provide the individuals with more effective and actionable information, other individuals and health professionals should be involved in the process. Having this in mind, this paper presents a smart health collaborative approach that considers the extensive analysis of the individual's wearable data, as well as a health social network to provide an infrastructure for the individuals to manage their data and easily interact with others individuals and physicians. The experiments focused on the data analysis module and considered data from four elderly individuals, wearing a Fitbit Charge HR. A clustering analysis was performed to identify and characterize patterns in their physiological behaviors and daily activities that were used for the prediction of the individuals' daily conditions and activities.

关键词： Physiology

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Gaussian pedestrian proxemics model with social force for service robot navigation in dynamic environment 17th

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17th International Conference on Asia Simulation, AsiaSim 2017

作者： Chik, Sheng Fei Yeong, Che Fai Su, Eileen Lee Ming Lim, Thol Yong Duan, Feng Tan, Jeffrey Too Chuan Tan, Ping Hua Chin, Patrick Jun Hua Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Bahru Malaysia Centre for Artificial Intelligence and Robotics Universiti Teknologi Malaysia Johor Bahru Malaysia Malaysia Japan Institute of Technolgy Universiti Teknologi Malaysia Johor Bahru Malaysia Department of Automation College of Computer and Control Engineering Nankai University Tianjin China Institute of Industrial Science The University of Tokyo Tokyo Japan DF Automation and Robotics Sdn. Bhd Skudai Malaysia

ISBN: (纸本)9789811064623

Pedestrian motion behaves stochastically, causing difficulties in modelling the appropriate proxemics for effective and efficient service robot navigation. Intruding the pedestrian social space can affect the social acceptance of a service robot. In this paper, a new proxemics model, Social-Force Gaussian Pedestrian Proxemics Model is presented to model the pedestrian social space and to improve the service robot navigation in dynamic human environment. This model was simulated and validated in a pedestrian simulator with both low and high pedestrian density environments. Results showed that the proposed model (i) improved proxemics representation of pedestrians, (ii) enhanced the robot performance in respecting the social norm and (iii) increased the efficiency in achieving a given task. This paper also presents the methods for parameter selections for the model without the requirement of complex tuning. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Mobile robots

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A modified DTC with capability of regenerative braking energy in BLDC driven electric vehicles using adaptive control theory

arXiv

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arXiv 2017年

作者： Geraee, Shiva Mohammadbagherpoor, Hamed Shafiei, Mehdi Valizadeh, Majid Montazeri, Farshad Feyzi, Mohammad Reza Faculty of Electrical and Computer Engineering University of Tabriz Faculty of Electrical and Computer Engineering North Carolina State University United States Department of Electrical and Electronic Engineering and Computer Science Queensland University of Technology Department of Electrical and Electronic Engineering University of Ilam Center of Excellence for Power System Automation and Operation Electronic Engineering Iran University of Science and Technology

This paper represents a novel regenerative braking approach for the Electric Vehicles. The proposed method solves the short-range problem which is corresponding to the charge of the battery pack. The DTC switching algorithm has been modified to recover the electrical energy from Electrical Vehicle (EV), driven by Brushless DC motor, without using the additional power converter or the other electrical energy storage devices. During regenerative braking process, different switching pattern is applied to the inverter to convert the mechanical energy to the electrical energy through the reverse diodes. This switching pattern is different from the normal operation due to the special arrangement of voltage vectors which is considered to convert the mechanical energy to electrical energy. The state of charge of the battery is used as a performance indicator of the method. Simultaneously, a model reference adaptive system has been designed to tune the system's parameters. Several simulations are carried out to validate the performance and effectiveness of the proposed methods. The results show the high capability and performance of the designed method. Copyright © 2017, The Authors. All rights reserved.

关键词： Brushless DC motors

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Synthesis of La0.5Ca0.5-xxMnO3 nanocrystalline manganites by sucrose assisted auto combustion route and study of their structural, magnetic and magnetocaloric properties

arXiv

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arXiv 2019年

作者： Moumen, S. Ben Gagou, Y. Chettab, M. Mezzane, D. Amjoud, M. Fourcade, S. Hajji, L. Kutnjak, Z. Marssi, M.E. Amraoui, Y.E. Kopelevich, Y. Lukýanchuk, Igor A. LMCN F.S.T.G. Université Cadi Ayyad BP 549 Marrakech Morocco LPMC Université de Picardie Jules Verne 33 rue Saint-Leu Amiens Cédex80039 France LCMCB Université de Bordeaux Pessac33600 France Jozef Stefan Institute Jamova cesta 39 Ljubljana1000 Slovenia LaMCScI Faculté des Sciences Université Mohammed V Rabat Morocco Instituto de Fisica Gleb Wataghin Universidade Estadual de Campinas Unicamp 13083-859 Campinas Sao Paulo Brazil Department of Cybersecurity and Computer Engineering Faculty of Automation and Information Technologies Kyiv National University of Construction and Architecture Kyiv Ukraine

Perovskite manganite La0.5Ca0.5-xxMnO3 (LCMO) nanomaterials were elaborated using the sucrose modified auto combustion method. Rietveld refinements of the X-ray diffraction patterns of the crystalline structure confirm a single-phase orthorhombic state with Pbnm space group (No. 62). The Ca-vacancies were voluntarily created in the LCMO structure in order to study their influence on the magnetic behaviour in the system. The magnetic susceptibility was found to be highly enhanced in the sample with Ca-vacancies. Paramagnetic-to-ferromagnetic phase transition was evidenced in both samples around 254 K. This transition is, characterized by a drastic jump of the susceptibility in the sample with Ca-vacancies. The maximum of entropy change, observed for both compounds at magnetic field of 6T was 2.30 J kg-1K-1 and 2.70 J kg-1K-1 for the parent compound and the lacunar one respectively. The magnetocaloric adiabatic temperature change value calculated by indirect method was 5.6 K and 5.2 K for the non-lacunar and Ca-vacancy compound, respectively. The Ca-lacunar La0.5Ca0.5-xxMnO3 (x=0.05) reported in this work demonstrated overall enhancement of the magnetocaloric effect over the LCMO. The technique used to elaborate LCMO materials was beneficial to enhance the magnetocaloric effect and magnetic behaviour. Therefore, we conclude that this less costly environmentally friendly system can be considered as more advantageous candidate for magnetic refrigeration applications then the commonly Gd-based compounds. Copyright © 2019, The Authors. All rights reserved.

关键词： Sugar (sucrose)

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Visual Navigation Method for Indoor Mobile Robot Based on Extended BoW Model

Visual Navigation Method for Indoor Mobile Robot Based on Ex...

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第十二届中国智能机器人大会

作者： Xianghui Li Xinde Li Mohammad Omar Khyam Chaomin Luo Yingzi Tan Key Laboratory of Measurement and Control of CSE (Ministry of Education) School of Automation Sout Department of Electrical and Computer Engineering Faculty of Engineering National University of Si Department of Electrical and Computer Engineering University of Detroit Mercy Michigan USA

This paper proposes a new navigation method for mobile robots based on an extended BoW (Bag of Words) model for general object recognition in indoor *** SIFT (Scale-invariant Feature Transform) detection algorithm with the GPU (Graphic Processing Unit) acceleration technology is used to describe feature vectors in this ***,in order to add some redundant image information,statistical information of the spatial relationships of all the feature points in an image,i.e.,relative distances and angles,is used to extend the feature vectors in the original BoW ***,the unsupervised SVM (Support Vector Machine) classifier is used to classify ***,in order to navigate conveniently in unknown and dynamic indoor environments,a type of human-robot interaction method based on a hand-drawn semantic map is *** experimental results show that this new navigation technology for indoor mobile robots is very robust and highly effective.

关键词： general object recognition Bag of Words model mobile robot visual navigation

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state estimation for discrete-time stochastic memristive BAM neural networks with mixed time-delays

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International Journal of Machine Learning and Cybernetics 2017年第4期10卷 771-785页

作者： Wang, Zidong Liu, Hongjian Shen, Bo Alsaadi, Fuad E. Dobaie, Abdullah M. College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China Department of Computer Science Brunel University London Uxbridge UK School of Information Science and Technology Donghua University Shanghai China Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah Saudi Arabia

In this paper, the $$H_\infty$$ state estimation problem is investigated for a class of discrete-time stochastic memristive bidirectional associative memory (DSMBAM) neural networks with mixed time delays. The mixed time delays comprise both discrete and distributed time-delays. A series of novel switching functions are proposed to reflect the state-dependent characteristics of the memristive connection weights in the discrete-time setting, which facilitates the dynamics analysis of the addressed memristive neural networks (MNNs). By means of the introduced series of switching functions, an $$H_\infty$$ state estimator is designed such that the estimation error is exponentially mean-square stable and the prescribed $$H_\infty$$ performance requirement is achieved. The gain matrices of the desired estimator are parameterized by utilizing the semi-definite programming method. Finally, a simulation example is employed to demonstrate the usefulness and effectiveness of the proposed theoretical results.

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A method for correcting illumination unevenness of solar image 8

A method for correcting illumination unevenness of solar ima...

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8th IEEE International Conference on Software engineering and Service Science, ICSESS 2017

作者： Yang, Hongjuan Ji, Kaifan Yang, Yunfei Duan, Wenliang Deng, Hui Liang, Bo Yunnan Key Lab. of Computer Technology Application/Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Yunnan Observatory Chinese Academy of Sciences Kunming Yunnan China Key Laboratory of Solar Activity National Astronomical Observatories Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781538645703

Traditional correction methods can not be used to correct effectively the solar images with uneven illumination, such as the bilinear interpolation method. We adopt an improved algorithm that combine the background fitting method and the mask method. The algorithm consists of the following main steps: segmenting the image, selecting the sampling points, interpolating the sampling points, calculating the mask, correcting the image. By comparing four evaluation indicators of the corrected image, including the information entropy of the image, the mean brightness, the mean variance and the peak signal-to-noise ratio (PSNR), this improved algorithm is proved to be effectively in the solar images with uneven illumination. © 2017 IEEE.

关键词： Interpolation

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