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International Conference on Environment and Electrical Engineering (EEEIC)

作者： David Carrasco-González Raúl Sarrias-Mena Pablo Horrillo-Quintero Ehsan Hosseini Francisco Llorens-Iborra Luis M. Fernández-Ramírez SURET Research Group Department of Electrical Engineering University of Cadiz Algeciras Spain SURET Research Group Department of Engineering in Automation Electronics and Computer Architecture and Networks University of Cadiz Algeciras Spain

ISBN: (数字)9798350355185

ISBN: (纸本)9798350355192

In response to growing energy demands and concerns about climate change, microgrid clusters (MGCs) are gaining widespread attention. Their ability to integrate technologies for energy consumption, generation, and storage in AC, DC or a compound of both offer a high degree of flexibility and resiliency. This research introduces a new control strategy for an MGC composed of two MGs interconnected to a local grid via a point of common coupling. The first one is a DC MG comprising an ultracapacitor (UC), wind turbine (WT), DC loads and hydrogen system. The second is an AC MG with a battery bank, AC loads and photovoltaic (PV) generator. The control strategy employs local controllers for each device and distributed control via two control agents, coordinating the power distribution among the energy storage systems (ESSs) of the MGC. This system is tested and validated on a real-time experimental setup, using two Raspberry Pi microcontrollers and an OPAL-RT unit, under different working conditions. The results obtained in this work show that the control strategy implemented in the MGC works correctly.

关键词： Energy consumption Microcontrollers Wind speed Decentralized control Hydrogen Microgrids Supercapacitors Real-time systems Wind turbines Solar radiation

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Predictability performance enhancement for suspended sediment in rivers: Inspection of newly developed hybrid adaptive neuro-fuzzy system model

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International Journal of Sediment Research 2022年第3期37卷 383-398页

作者： Rana Muhammad Adnan Zaher Mundher Yaseen Salim Heddam Shamsuddin Shahid Aboalghasem Sadeghi-Niaraki Ozgur Kisi State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering Hohai University Department of Urban Planning Engineering Networks and Systems Institute of Architecture and Construction South Ural State University New Era and Development in Civil Engineering Research Group Scientific Research Center Al-Ayen University Faculty of Science Agronomy Department Hydraulics Division University School of Civil Engineering Faculty of Engineering Universiti Teknologi Malaysia (UTM) Geoinformation Tech.Center of Excellence Faculty of Geomatics Engineering K.N.Toosi University of Technology Department of Computer Science and Engineering Sejong University Civil Engineering Department Ilia State University

Reliable modeling of river sediments transport is important as it is a defining factor of the economic viability of dams, the durability of hydroelectric-equipment, river susceptibility to pollution, suitability for navigation, and potential for aesthetics and fish habitat. The capability of a new machine learning model, fuzzy c-means based neuro-fuzzy system calibrated using the hybrid particle swarm optimization-gravitational search algorithm（ANFIS-FCM-PSOGSA） in improving the estimation accuracy of river suspended sediment loads（SSLs） is investigated in the current study. The outcomes of the proposed method were compared with those obtained using the fuzzy c-means based neuro-fuzzy system calibrated using particle swarm optimization（ANFIS-FCM-PSO）, ANFIS-FCM, and sediment rating curve（SRC） models. Various input combinations involving lagged river flow（Q） and suspended sediment（S） values were used for model development. The effect of Q and S on the model's accuracy also was assessed by including the difference between lagged Q and S values as inputs. The model performance was assessed using the root mean square error（RMSE）, mean absolute error（MAE）, Nash-Sutcliffe Efficiency（NSE）, and coefficient of determination（R2） and several graphical comparison methods. The results showed that the proposed model enhanced the prediction performance of the ANFIS-FCM-PSO（or ANFIS-FCM） models by 8.14%（1.72%）, 14.7%（5.71%）, 12.5%（2.27%）, and 25.6%（1.86%）,in terms of the RMSE, MAE, NSE and R2, respectively. The current study established the potential of the proposed ANFIS-FCM-PSOGSA model for simulation of the cumulative sediment load. The modeling results revealed the potential effects of the river flow lags on the sediment transport quantification.

关键词： Suspended sediment load Adaptive neuro-fuzzy system Particle swarm optimization Gravitational search algorithm

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An Interdisciplinary Approach to Designing Adaptive Lighting Environments

An Interdisciplinary Approach to Designing Adaptive Lighting...

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International Conference on Intelligent Environments (IE)

作者： Remco Magielse Philip Ross Sunder Rao Tanir Ozcelebi Paola Jaramillo Oliver Amft Designing Quality in Interaction (DQI) Group Department of Industrial Design Intelligent Lighting Institute (ILI) Eindhoven University of Technology Eindhoven Netherlands System Architecture and Networks (SAN) Group Department of Mathematics and Computer Science Intelligent Lighting Institute (ILI) Eindhoven University of Technology Eindhoven Netherlands Signal Processing Systems (SPS) Group Department of Electrical Engineering Intelligent Lighting Institute (ILI) Eindhoven University of Technology Eindhoven Netherlands

Due to advancements in lighting technologies new opportunities for application emerge. In this paper an interdisciplinary study towards the development of adaptive lighting environments is presented. An implementation of an adaptive lighting environment is made in the domain of office work. For evaluation, experts from the domains of human-system interaction, activity and context recognition, and system architecture design are interviewed. Contributions are made with regard to the implementation of the adaptive lighting in office environments and an evaluation method that is in line with the interdisciplinary approach. From the evaluation method insights in the fields of human-computer interaction, activity and context recognition and system architecture and (wireless) networking and in topics that span across these fields are gained.

关键词： Indexes

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States-Based Energy Management System for an EV Hybrid Charging Station with Z-Source Converters

States-Based Energy Management System for an EV Hybrid Charg...

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Power Tech Conference

作者： Enrique González-Rivera Pablo García-Triviño Luis M. Fernández-Ramirez Raúl Sarrias-Mena Juan P. Torreglosa Francisco Jurado Department of Electrical Engineering Research Group in Sustainable and Renewable Electrical Technologies (PAIDI-TEP-023) University of Cadiz Algeciras Spain Department of Engineering in Automation Research Group in Sustainable and Renewable Electrical Technologies (PAIDI-TEP-023) Electronics and Computer Architecture & Networks University of Cadiz Algeciras Spain Electrical Engineering Department University of Huelva Palos de la Frontera Spain Department of Electrical Engineering Research Group in Research and Electrical Technology (PAIDI- TEP-152) University of Jaen Linares Spain

ISBN: (数字)9781665435970

ISBN: (纸本)9781665411738

This work presents a new energy management system (EMS) based on states for a hybrid charging station of electric vehicles (EV). The hybrid charging station is composed of a photovoltaic (PV) system, a complete hydrogen system based on fuel cell (FC), electrolyzer (EZ) and tank as energy storage system (ESS), a battery energy storage system (BES), a grid connection, and six fast charging units, all of them connected to a common MVDC bus through Z-sources converters (ZSC). The states-based EMS is designed to control the power flow among the energy sources of the hybrid charging station. The viability of the EMS is proved under a long-term simulation of 25 years in Simulink by using an EV load profile taken from the Strategy Technology Energy Plan of the EU and real data for the sun irradiance.

关键词： Photovoltaic systems Renewable energy sources Costs Software packages Hydrogen Charging stations Hybrid power systems

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A Joint Transmit and Receive Design for Dimmable High Speed MC MU VLC Systems

A Joint Transmit and Receive Design for Dimmable High Speed ...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Yujie Yang Yang Yang Hailun Xia Caili Guo Mahdi Chehimi Walid Saad Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of. Posts and Telecommunications Beijing China Bradley Department of Electrical and Computer Engineering Wireless@VT Group Virginia Tech Blacksburg VA USA

ISBN: (纸本)9781665435413

In multi-cell multi-user multiple-input multiple-output (MC MU-MIMO) visible light communication (VLC) systems, each user is equipped with multiple closely-placed photodiodes (PDs) with similar channel gains, leading to severe inter-cell interference and intra-cell interference. To address this problem, this paper proposes a hybrid dimming (HD) scheme with MIMO VLC transceiver design, which jointly optimizes transmit and receive antenna selection (TRAS), cell clustering and precoding (TRASP-HD) for MC MU-MIMO VLC systems. In this scheme, a sum-rate maximization problem under the dimming level and illumination uniformity is formulated and solved by being divided into two sub-problems. In particular, The first sub-problem is on TRAS and cell formation based on the criterion of sum-rate maximization under the illumination uniformity constraint. With the same goal, the second sub-problem is on optimizing the precoding matrices of each cell. Finally, these two sub-problems are iteratively solved to obtain a convergent solution. Simulation results verify that in a typical indoor scenario, the mean bandwidth efficiency of TRASP-HD scheme is 2.36 bit/s/Hz higher than the conventional MC MU-MIMO system.

关键词： Spectral efficiency Precoding Simulation Lighting Receiving antennas Transceivers MIMO

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Deep learning-based instance segmentation for the precise automated quantification of digital breast cancer immunohistochemistry images

arXiv

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arXiv 2023年

作者： Priego-Torres, Blanca Maria Lobato-Delgado, Barbara Atienza-Cuevas, Lidia Sanchez-Morillo, Daniel Biomedical Engineering and Telemedicine Research Group Department of Automation Engineering Electronics and Computer Architecture and Networks School of Engineering University of Cádiz Avda. Universidad de Cádiz 10 Cádiz Puerto Real11510 Spain Hospital Universitario Puerta del Mar Avda Ana de Viya 21 Cádiz11009 Spain Department of Pathology Hospital Universitario Puerta del Mar Avda. Ana de Viya 21 Cádiz11009 Spain

The quantification of biomarkers on immunohistochemistry breast cancer images is essential for defining appropriate therapy for breast cancer patients, as well as for extracting relevant information on disease prognosis. This is an arduous and time-consuming task that may introduce a bias in the results due to intra- and inter-observer variability which could be alleviated by making use of automatic quantification tools. However, this is not a simple processing task given the heterogeneity of breast tumors that results in non-uniformly distributed tumor cells exhibiting different staining colors and intensity, size, shape, and texture, of the nucleus, cytoplasm and membrane. In this research work we demonstrate the feasibility of using a deep learning-based instance segmentation architecture for the automatic quantification of both nuclear and membrane biomarkers applied to IHC-stained slides. We have solved the cumbersome task of training set generation with the design and implementation of a web platform, which has served as a hub for communication and feedback between researchers and pathologists as well as a system for the validation of the automatic image processing models. Through this tool, we have collected annotations over samples of HE, ER and Ki-67 (nuclear biomarkers) and HER2 (membrane biomarker) IHC-stained images. Using the same deep learning network architecture, we have trained two models, so-called nuclei- and membrane-aware segmentation models, which, once successfully validated, have revealed to be a promising method to segment nuclei instances in IHC-stained images. The quantification method proposed in this work has been integrated into the developed web platform and is currently being used as a decision support tool by pathologists. © 2023, CC BY-NC-ND.

关键词： Textures

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Preface: Human-centred AmI: Cognitive approaches, reasoning and learning

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Journal of Ambient Intelligence and Smart Environments 2017年第5期9卷 537页

作者： Juan Carlos Augusto Carles Gomez Andrea Prati Hamid Aghajan Department of Computer Science and Research Group on Development of Intelligent Environments Middlesex University UK Wireless Networks Group Department of Network Engineering Universitat Politecnica de Catalunya Spain Department of Engineering and Architecture University of Parma Italy imec IPI Department of Telecommunications and Information Processing Gent University Belgium

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Self-Awareness for Autonomous Systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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EVALUATION OF THE PUPIL RESPONSE AS A PREDICTIVE TOOL OF THE FUNCTIONAL ALTERATION OF THE LOCUS COERULEUS IN PAIN. COMPARISON BETWEEN ACUTE AND CHRONIC PAIN.

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IBRO Neuroscience Reports 2023年 15卷 S601-S601页

作者： Carolina López-Martín Sonia Torres-Sanchez Alejandro Lara-Doña Daniel Sanchez-Morillo Esther Berrocoso University of Cadiz Neuropsychopharmacology And Psychobiology Research Group Department Of Psychology Cadiz Spain Instituto de Investigación e Innovación en Ciencias Biomédicas de Cádiz Inibica Cádiz Spain University of Cadiz Neuropsychopharmacology And Psychobiology Research Group Department Of Neuroscience Cádiz Spain Centro de Investigación Biomédica en Red de Salud Mental Instituto De Salud Carlos Iii Madrid Spain University of Cádiz Biomedical Engineering And Telemedicine Research Group Department Of Engineering In Automation Electronics Architecture And Computer Networks Cádiz Spain

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