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Availability factor of a PV power plant: evaluation based on generation and inverter running periods

Energy Procedia 2018年 147卷 71-77页

作者： Nallapaneni Manoj Kumar Srikar Dasari Jagathpally Bhagwan Reddy Faculty of Electrical and Electronics Engineering Universiti Malaysia Pahang Pahang Pekan 26600 Malaysia Automation and Power Engineering Faculty of Electrical Engineering Media Engineering and Computer Science THD Technische Hochschule Deggendorf Edlmairstr Deggendorf 94469 Germany Department of Electrical and Electronics Engineering Nalla Malla Reddy Engineering College Ghatkesar Telangana 500 088 India

In a solar PV power plant, the plant availability factor is one of the important factors to be evaluated. This depends on the operative functioning of various components and grid regulation. In this paper, a simple method is proposed to evaluate the availability factors of a solar PV plant by considering the real time data of 1 MWp solar power plant that was commissioned in 2011 in south India. Generation start time, end time, and actual running periods of the inverter were selected as prominent data in the study. A consecutive five financial years of data (2011–2012; 2012–2013; 2013–2014; 2014–2015; 2015–2016) was used to observe the variations in availability factors of inverters, as well as the plant availability factors. From the analysis, it is observed that tripping time greatly effects the availability factor of inverter as well as the PV plant. The variation in availability factor over the five consecutive financial years is seen to be within the range of 92.44 % to 95.69 %. This clearly states that, on average 4.31 % to 7.56 %, the installed solar PV power is technically not generated any power. Hence, estimating the availability factor could be very much essential to deal with the performance of the PV systems and possible options of reducing energy losses due to availability factors could be suggested.

关键词： solar energy PV power plant inverter availability factor plant availability factor inverter outages PV plant generation periods

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Quantifying Graph Anonymity, Utility, and De-anonymity

Quantifying Graph Anonymity, Utility, and De-anonymity

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Shouling Ji Tianyu Du Zhen Hong Ting Wang Raheem Beyah College of Computer Science and Technology Zhejiang University Hangzhou Zhejiang China Faculty of Mechanical Engineering & Automation Zhejiang Sci-Tech University Zhejiang Hangzhou China Department of Computer Science and Engineering Bethlehem PA USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

ISBN: (纸本)9781538641293

In this paper, we study the correlation of graph da-ta's anonymity, utility, and de-anonymity. Our main contributions include four perspectives. First, to the best of our knowledge, we conduct the first Anonymity-Utility-De-anonymity (AUD) correlation quantification for graph data and obtain close-forms for such correlation under both a preliminary mathematical model and a general data model. Second, we integrate our AUD quantification to SecGraph [31], a recently published Secure Graph data sharing/publishing system, and extend it to Sec-Graph+. Compared to SecGraph, SecGraph+ is an improved and enhanced uniform and open-source system for comprehensively studying graph anonymization, de-anonymization, and utility evaluation. Third, based on our AUD quantification, we evaluate the anonymity, utility, and de-anonymity of 12 real world graph datasets which are generated from various computer systems and services. The results show that the achievable anonymity/de-anonymity depends on multiple factors, e.g., the preserved data utility, the quality of the employed auxiliary data. Finally, we apply our AUD quantification to evaluate the performance of state-of-the-art anonymization and de-anonymization techniques. Interestingly, we find that there is still significant space to improve state-of-the-art de-anonymization attacks. We also explicitly and quantitatively demonstrate such possible improvement space.

关键词： Correlation Data models Erbium Measurement Electronic mail Conferences Mathematical model

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Large margin multi-modal multi-task feature extraction for image classification

arXiv

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arXiv 2019年

作者： Luo, Yong Wen, Yonggang Tao, Dacheng Gui, Jie Xu, Chao School of Electronics Engineering and Computer Science Peking University Beijing China Division of Networks and Distributed Systems School of Computer Engineering Nanyang Technological University Singapore Centre for Quantum Computation & Intelligent Systems Faculty of Engineering & Information Technology University of Technology Sydney Sydney Australia Centre for Quantum Computation & Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia Hefei Institute of Intelligent Machines Chinese Academy of Sciences Hefei230031 China Center for Research on Intelligent Perception and Computing National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We therefore propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization and each sub-problem can be efficiently solved. Experiments on two challenging real-world image datasets demonstrate the effectiveness and superiority of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Feature extraction

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Simulation of wood biomass combustion in hot water boiler

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IOP Conference Series: Materials science and engineering 2020年第1期776卷

作者： I Klačková I Zajačko R Lenhard I Gritsuk D Wiecek Department of Automation and Production systems Faculty of Mechanical Engineering University of Žilina Univerzitná 1 010 26 Žilina Slovak Republic Department of Power Engineering Faculty of Mechanical Engineering University of Žilina Univerzitná 1 010 26 Žilina Slovak Republic Center RUDN University 117198 Moscow Miklukho-Maklaya str.6 Moscow Russia Faculty of Mechanical Engineering and Computer Science University of Bielsko-Biala ul. Willowa 2 43-309 Bielsko-Biala Poland

Calculation methods based on finite volume methods (CFD method) have proven to be very useful in optimizing (efficiency, emission) heat sources for wood burning. Such heat sources also include gasification hot-water boilers for the combustion of dry wood. One of the important parts of the entire process of converting the primary energy contained in the fuel to the transfer of heat to the heat carrier is the gasification of the fuel in the feed chamber and the subsequent burning of wood gas. The paper presents CFD simulation of wood gasification process in the filling chamber and subsequent burning of wood gas on a model heat source. As a model heat source, was selected a hot-water boiler with lower fuel firing with a flue gas-water heat exchanger tubular heat exchanger. It is a gasification hot water boiler for the combustion of dry wood. The interior of the boiler consists of a filling chamber where the fuel is dried and fused. The wood gas then passes through the nozzle to the combustion chamber, where it burns with the aid of secondary air. The flue gases pass their heat in the heat exchanger through the walls of the pipes into the water.

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Correction: Gut microbiome in endometriosis: a cohort study on 1000 individuals

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BMC medicine 2024年第1期22卷 448页

作者： Inmaculada Pérez-Prieto Eva Vargas Eduardo Salas-Espejo Kreete Lüll Analuce Canha-Gouveia Laura Antequera Pérez Juan Fontes Andres Salumets Reidar Andreson Oliver Aasmets Katrine Whiteson Elin Org Signe Altmäe Department of Biochemistry and Molecular Biology I Faculty of Sciences University of Granada Granada Spain. inmapprieto@ugr.es. Instituto de Investigación Biosanitaria Ibs.GRANADA Granada Spain. inmapprieto@ugr.es. Department of Biochemistry and Molecular Biology I Faculty of Sciences University of Granada Granada Spain. Instituto de Investigación Biosanitaria Ibs.GRANADA Granada Spain. Systems Biology Unit Department of Experimental Biology Faculty of Experimental Sciences University of Jaen Jaen Spain. Institute of Genomics Estonian Genome Centre University of Tartu Tartu Estonia. Department of Physiology Faculty of Veterinary University of Murcia Campus Mare Nostrum Murcia Spain. Department of Computer Engineering Automation and Robotics University of Granada Granada Spain. U. Reproducción UGC Laboratorio Clínico y UGC Obstetricia y Ginecología. HU Virgen de Las Nieves Granada Spain. Competence Centre On Health Technologies Tartu Estonia. Division of Obstetrics and Gynaecology Department of Clinical Science Intervention and Technology Karolinska Institutet Huddinge Stockholm Sweden. Department of Gynaecology and Reproductive Medicine Karolinska University Hospital Huddinge Stockholm Sweden. Department of Obstetrics and Gynaecology Institute of Clinical Medicine University of Tartu Tartu Estonia. Institute of Molecular and Cell Biology University of Tartu Tartu Estonia. School of Biological Sciences University of California Irvine CA USA.

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Preface

Methodologies and Intelligent Systems for Technology Enhance...

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Methodologies and Intelligent Systems for Technology Enhanced Learning, 9th International Conference, 2019 2020年 1007卷 v-vi页

作者： Gennari, Rosella Vittorini, Pierpaolo De la Prieta, Fernando Di Mascio, Tania Temperini, Marco Silveira, Ricardo Azambuja Carranza, Demetrio Arturo Ovalle Computer Science Faculty Free University of Bozen-Bolzano Bolzano Italy Department of Life Health and Environmental Sciences University of L’Aquila L’Aquila Italy Department of Computer Science and Automation Control University of Salamanca SalamancaSalamanca Spain Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Dipartimento di Ingegneria Informatica Automatica e Gestionale Sapienza Università di Roma Rome Italy Department of Computer Science and Statistics Federal University of Santa Catarina Florianópolis Brazil Universidad Nacional de Colombia Medellin Colombia

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Implementation of particle filters for mobile robot localization 22

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22nd International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Chaos, Bayesian Methods, Intelligent Image Processing, Bio-Inspired Robotics, MENDEL 2016

作者： Růžička, Michal Mašek, Petr Věchet, Stanislav Faculty of Mechanical Engineering Institute of Automation and Computer Science Brno University of Technology Technická 2896/2616 69 Brno Czech Republic

ISBN: (纸本)9783319580876

This paper deals with mobile robot localization purpose. The presented solution is designed for indoor environment only. GPS navigation system cannot be used in environment inside of buildings. Alternative methods have to be used for this purpose. The mobile robot localization is essential part of autonomous mobile robotics. Mobile robot localization together with odometry is necessary for mobile robot navigation. Presented paper contains explanation of localization approach, which is based on probabilistic method. Next part of this paper is description of experimental odometry method, which is based on computer vision. © Springer International Publishing AG 2017.

关键词： Mobile robots

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Design of linear quadratic regulator (LQR) based on genetic algorithm for inverted pendulum 23

Design of linear quadratic regulator (LQR) based on genetic ...

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23rd International Conference on Soft Computing, MENDEL 2017

作者： Marada, Tomáš Matoušek, Radomil Zuth, Daniel Brno University of Technology Faculty of Mechanical Engineering Institute of Automation and Computer Science Technicka 2896/2 Brno616 69 Czech Republic

One of the crucial problems in the dynamics and automatic control theory is balancing of an inverted pendulum robot by moving a cart along a horizontal path. This task is often used as a benchmark for difierent method comparison. In the practical use of the LQR method, the key problem is how to choose weight matrices Q and R correctly. To obtain satisfying results the experiments should be repeated many times with difierent parameters of weight matrices. These LQR parameters can be tuned by a Genetic Algorithm (GA) technique for getting better results. In our paper, the LQR parameters weight matrices Q and R which were tuned using the Genetic Algorithm. The simulations of the control problem are designed using MATLAB script code and MATLAB Simulink on an inverted pendulum model. The results show that the Genetic Algorithm is suitable for tuning the parameters to give an optimal response. The control problem of the inverted pendulum was solved successfully. © 2017 Brno University of Technology. All rights reserved.

关键词： Genetic algorithms

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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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Forecasting time series for power consumption data in different buildings using the fractional brownian motion

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International Journal of Circuits, Systems and Signal Processing 2018年 12卷 646-652页

作者： Bondarenko, Valeria Filipova-Petrakieva, Simona K. Taralova, Ina Andreev, Desislav University of Beira Covilha Portugal Technical University of Sofia Department "Theory of Electrical Engineering" Faculty of Automation Sofia Bulgaria Laboratoire des Sciences du Numerique de Nantes Ecole Centrale de Nantes Nantes France Technical University of Sofia Department "Computer Science" Faculty of Computer systems and Technologies Sofia Bulgaria

In the present paper will be discussed the problem related to the individual household electric power consumption of objects in different areas – industry, farmers, banks, hospitals, theaters, hostels, supermarkets, universities. The main goal of the directed research is to estimate the active P and full S power consumptions for all studied buildings. The defined goal is achieved by solving of the following three problems. The first problem studies which buildings increase their power consumption. The second one finds which objects have the greatest increase of power consumption. And the third problem regards if it is possible to make a short-term forecast, based on the solutions of previous two problems. The present research and solving of the aforementioned problems is conducted using fractional Brownian motion theory. The applicability of this approach is illustrated on the example with 20 real objects in different areas. The paper ends with conclusion notes about possibilities to make short-term forecasts about power consumption of the considered buildings. © 2018, North Atlantic University Union. All rights reserved.

关键词： Electric power utilization

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