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Wireless Disturbance Mapping and Path Selection for Placement of Network control System Components

Journal of Physics: Conference Series 2019年第1期1230卷 012025-012025页

作者： Joelianto, Endra Ghazali, Muhammad Zhaka Tutun Juhana Instrumentation and Control Research Group Faculty of Industrial Technology Institut Teknologi Bandung Jl. Ganesha 10 Bandung 40132 Indonesia. Engineering Physics Study Program Faculty of Industrial Technology Institut Teknologi Bandung Jl. Ganesha 10 Bandung 40132 Indonesia. Telecommunication Engineering School of Electrical and Informatics Institut Teknologi Bandung Jl. Ganesha 10 Bandung 40132 Indonesia.

Wireless transmitters in measurement instruments act for transmitting data or signals using radio frequency or currently better known as WIFI by means of 2.4 GHz. WIFI is a wireless local area network (WLAN) communication network. With the existence of telecommunications, measurement and control in industrial processes are heading to a high level of reliability compared to the conventional wired instruments in reaching hard locations or dangerous and hazardous areas. However, this cannot be done easily especially in maintaining the communication performances. Research is needed on the reliability of the wireless transmitter itself. Several factors such as communication disruptions are new challenges for the industry of wireless technology manufacturers to be able to prevent or to minimize errors that can arise in wireless network control systems. Signal strength mapping is needed in designing wireless network control systems. In this paper, the mapping is performed by measuring the signal strength parameters (Power Level) and the use of channels (Channel Usage) at planned locations. The measurement results are then used as sample points in the mapping. Data show that the signal strength measurement at each channel has a maximum of - 60 dBm and a minimum of -105 dBm. Mapping is performed by using two methods, namely Inverse Distance Weight (IDW) and Spline Interpolation (SI) methods. The paper proposes an algorithm to select the appropriate wireless communication paths from the planned locations. The mapping results indicate the appropriate area to place the transmitter and the receiver devices in a wireless data transmission network. With good placement, it is expected that measurements using wireless transmitters have minimum disruptions.

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J-Measure Based Pruning for Advancing Classification Performance of Information Entropy Based Rule Generation

J-Measure Based Pruning for Advancing Classification Perform...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Han Liu Mihaela Cocea Weili Ding School of Computer Science and Informatics Cardiff University Queen’s Buildings 5 The Parade Cardiff United Kingdom School of computing University of Portsmouth Buckingham Building Lion Terrace Portsmouth United Kingdom Laboratory of Pattern Recognition and Intelligent Systems Key Laboratory of Industrial Computer Control Engineering of Heibei Provience Yanshan University Qinghuangdao China

ISBN: (纸本)9781538652152

Learning of classification rules is a popular approach of machine learning, which can be achieved through two strategies, namely divide-and-conquer and separate-and-conquer. The former is aimed at generating rules in the form of a decision tree, whereas the latter generates if-then rules directly from training data. From this point of view, the above two strategies are referred to as decision tree learning and rule learning, respectively. Both learning strategies can lead to production of complex rule based classifiers that overfit training data, which has motivated researchers to develop pruning algorithms towards reduction of overfitting. In this paper, we propose a J-measure based pruning algorithm, which is referred to as Jmean-pruning. The proposed pruning algorithm is used to advance the performance of the information entropy based rule generation method that follows the separate and conquer strategy. An experimental study is reported to show how Jmean-pruning can effectively help the above rule learning method avoid overfitting. The results show that the use of Jmean-pruning achieves to advance the performance of the rule learning method and the improved performance is very comparable or even considerably better than the one of C4.5.

关键词： Decision trees Learning systems Training data Entropy Information entropy Machine learning Machine learning algorithms

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Classes and phyla of the kingdom Fungi

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Fungal Diversity 2024年第5期124卷 1-165页

作者： Nalin N.Wijayawardene Kevin D.Hyde Kirill V.Mikhailov Gabor Peter Andre Aptroot Carmen L.A.Pires‑Zottarelli Bruno T.Goto Yuri S.Tokarev Danny Haelewaters Samantha C.Karunarathna Paul M.Kirk Andre L.C.M.de A.Santiago Ramesh K.Saxena Nathan Schoutteten Madhara K.Wimalasena Vladimir V.Aleoshin Abdullah M.S.Al‑Hatmi Kahandawa G.S.U.Ariyawansa Amanda R.Assuncao Thushara C.Bamunuarachchige Hans‑Otto Baral D.Jayarama Bhat Janusz Błaszkowski Teun Boekhout Nattawut Boonyuen Michael Brysch‑Herzberg Bin Cao Jonathan Cazabonne Xue‑Mei Chen Claudia Coleine Dong‑Qin Dai Heide‑Marie Daniel Suzana B.G.da Silva Francisco Adriano de Souza Somayeh Dolatabadi Manish K.Dubey Arun K.Dutta Aseni Ediriweera Eleonora Egidi Mostafa S.Elshahed Xinlei Fan Juliana R.B.Felix Mahesh C.A.Galappaththi Marizeth Groenewald Li‑Su Han Bo Huang Vedprakash G.Hurdeal Anastasia N.Ignatieva Gustavo H.Jeronimo Ana L.de Jesus Serhii Kondratyuk Jaturong Kumla Martin Kukwa Qirui Li Juliana L.R.Lima Xiao‑Yong Liu Wenhua Lu H.Thorsten Lumbsch Hugo Madrid Franco Magurno Guy Marson Eric H.C.McKenzie Audrius Menkis Armin Mešić Elaine C.R.Nascimento Elena S.Nassonova Yong Nie Naasson V.L.Oliveira Emilia A.Ossowska Julia Pawłowska Ursula Peintner Igor R.Pozdnyakov Bhagya M.Premarathne A.K.Hasith Priyashantha C.Alisha Quandt Mariana B.Queiroz Kunhiraman C.Rajeshkumar Mubashar Raza Niranjan Roy Milan C.Samarakoon Alessandra A.Santos Lidiane A.Santos Felix Schumm Laura Selbmann Faruk Selcuk D.Rabern Simmons Anastasia V.Simakova Maudy Th.Smith Onden Paraparath Sruthi Nakarin Suwannarach Kazuaki Tanaka Saowaluck Tibpromma Elias O.Tomas Merve Ulukapı Nicolas Van Vooren Dhanushka N.Wanasinghe Evi Weber Qianzhen Wu Er Fu Yang Ryuichi Yoshioka Noha H.Youssef Annemarie Zandijk Gui‑Qing Zhang Jin‑Yong Zhang Heng Zhao RuiLin Zhao Oleg A.Zverkov Marco Thines Sergey A.Karpov Center for Yunnan Plateau Biological Resources Protection and Utilization College of Biological Resource and Food EngineeringQujing Normal UniversityQujing 655011YunnanPeople’s Republic of China Tropical Microbiology Research Foundation 96/N/10Meemanagoda RoadPannipitiya 10230Sri Lanka Department of Bioprocess Technology Faculty of TechnologyRajarata UniversityMihintaleSri Lanka Center of Excellence in Fungal Research Mae Fah Luang UniversityChiang Rai 57100Thailand School of Science Mae Fah Luang UniversityChiangRai 57100Thailand Innovative Institutefor Plant Health Zhongkai University of Agriculture and EngineeringGuangzhou 510225People’s Republic of China CAS Key Laboratory for Plant Biodiversity and Biogeography of East Asia(KLPB) Kunming Institute of BotanyChinese Academy of ScienceKunmingYunnanChina Belozersky Institute of Physicochemical Biology Lomonosov Moscow State UniversityLeninskye Gory1Build.40Moscow 119991Russian Federation Kharkevich Institute for Information Transmission Problems Russian Academy of SciencesMoscow 127051Russian Federation National Collection of Agricultural and Industrial Microorganisms Institute of Food Science and TechnologyHungarian University of Agriculture and Life SciencesSomlóiút 14‑161118 BudapestHungary Instituto de Biociências Universidade Federal de Mato Grosso do SulAvenida Costa e Silvas/n Bairro UniversitárioCampo GrandeMS CEP 79070‑900Brazil Instituto de Pesquisas Ambientais Secretaria do Meio AmbienteInfraestrutura e LogísticaAv.Miguel Stéfano 3687São PauloSP CEP 04301‑902Brazil Departamento de Botânica e Zoologia Universidade Federal do Rio Grande do NorteCampus UniversitárioNatalRN 59078-900Brazil All-Russian Institute of Plant Protection Sh.Podbelskogo 3PushkinSt.Petersburg 196608Russia Research Group Mycology Department of BiologyGhent University9000 GhentBelgium Faculty of Science University of South Bohemia37005ČeskéBudějoviceCzech Republic Department of Ecology and Evolutionary Biology University of Colora

Fungi are one of the most diverse groups of organisms with an estimated number of species in the range of 2–3 *** higher-level ranking of fungi has been discussed in the framework of molecular phylogenetics since Hibbett et al.,and the definition and the higher ranks(e.g.,phyla)of the‘true fungi’have been revised in several subsequent *** accumulation of novel genomic data and the advancements in phylogenetics now facilitate a robust and precise foundation for the higher-level classification within the *** study provides an updated classification of the kingdom Fungi,drawing upon a comprehensive phylogenomic analysis of Holomycota,with which we outline well-supported nodes of the fungal tree and explore more contentious *** accept 19 phyla of Fungi,***,Ascomycota,Basidiobolomycota,Basidiomycota,Blastocladiomycota,Calcarisporiellomycota,Chytridiomycota,Entomophthoromycota,Entorrhizomycota,Glomeromycota,Kickxellomycota,Monoblepharomycota,Mortierellomycota,Mucoromycota,Neocallimastigomycota,Olpidiomycota,Rozellomycota,Sanchytriomycota,and *** the phylogenies,Caulochytriomycota resides in Chytridiomycota;thus,the former is regarded as a synonym of the latter,while Caulochytriomycetes is viewed as a class in *** provide a description of each phylum followed by its classes.A new subphylum,Sanchytriomycotina Karpov is introduced as the only subphylum in *** subclass Pneumocystomycetidae Kirk et *** Pneumocystomycetes,Ascomycota is invalid and thus *** of fossil fungi in phyla and classes are also discussed,providing examples.

关键词： Caulochytriomycota Phylogenomic analyses Pneumocystomycetidae Sanchytriomycotina

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Data-driven Comfort Models for User-centric Predictive control in Smart Buildings: Poster Abstract 16

Data-driven Comfort Models for User-centric Predictive Contr...

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Proceedings of the 3rd ACM International Conference on Systems for Energy-Efficient Built Environments

作者： Grigore Stamatescu Alex Beltran Alberto Cerpa Automatic Control and Industrial Informatics University "Politehnica" of Bucharest Electrical Engineering and Computer Science University of California Merced

ISBN: (纸本)9781450342643

Occupant comfort and energy cost are the dual, explicit or implicit, objectives of advanced control strategies implemented in smart buildings. Focusing on the former, we present a novel approach for data-driven modeling of user comfort and a path for integrating the resulting models in a generic predictive framework for optimal HVAC control. This offers significant improvement potential over the static scheduling or occupancy based temperature bounds.

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Vehicle license plate image segmentation system using cellular neural network optimized by adaptive fuzzy and Neuro-Fuzzy algorithms

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous engineering 2016年第12期11卷 383-400页

作者： Rahmat, Basuki Joelianto, Endra Ketut Eddy Purnama, I. Purnomo, Mauridhi Hery Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia Department of Informatics Engineering Faculty of Industrial Technology Universitas Pembangunan Nasional Veteran Jawa Timur Surabaya60294 Indonesia Instrumentation and Control Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung40132 Indonesia

Vehicle License Plate Images Segmentation is a substantial stage for developing an Automatic License Plate Recognition (ALPR) system. In this paper, it is considered an efficient segmentation algorithm for extracting vehicle license plate images using Cellular Neural Networks (CNN). The learning CNN templates values are formulated as an optimization problem to achieve the desired performances which can be found by means of Adaptive Fuzzy (AF) algorithm and Neuro-Fuzzy (NF) algorithm techniques. The main objective of the paper is to compare the performances of standard CNN, Adaptive Fuzzy (AF), and Neuro-Fuzzy (NF) on real data of several vehicle license plate images of standard Indonesia License Plates. The results are then compared with ideal vehicle license plate images. Quantitative analysis between ideal vehicle license plate images and segmented vehicle license plate images is presented in terms of Peak signal-to-noise ratio (PSNR), Mean Squared Error (MSE) and Root Mean Squared Error (RMSE). From the performance analysis, the CNN template optimized by ANFIS algorithm is more recommended than the standard CNN edge detector or the CNN template optimized by Adaptive Fuzzy algorithm in vehicle license plate image segmentation. It is shown from the calculation that PSNR is 80% better than the standard CNN, and the resulted MSE and RMSE are 70% better than the standard CNN. Whereas the CNN template optimized by Adaptive Fuzzy algorithm achieves the PSNR 90% better than the standard CNN, but it yields the MSE and RMSE 40% worse than the standard CNN. © 2016 SERSC.

关键词： Signal to noise ratio

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Obstacle avoidance via B-spline parametrizations of flat trajectories

Obstacle avoidance via B-spline parametrizations of flat tra...

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Mediterranean Conference on control and Automation

作者： Florin Stoican Vlad-Mihai Ivanusca Ionela Prodan Dan Popescu Politehnica University of Bucharest Department of Automation Control and Systems Engineering Univ. Grenoble Alpes Laboratory of Conception and Integration of Systems (LCIS EA 3747) Politehnica University of Bucharest Department of Automatic Control and Industrial Informatics

ISBN: (纸本)9781467383479

This paper considers the collision avoidance problem in a multi-agent multi-obstacle framework. The originality in solving this intensively studied problem resides in the proposed geometrical view combined with differential flatness for trajectory generation and B-splines for the flat output parametrization. Using some important properties of these theoretical tools we show that the constraints can be validated at all times. Exact and sub-optimal constructions of the collision avoidance optimization problem are provided. The results are validated through extensive simulations over standard autonomous aerial vehicle dynamics.

关键词： Obstacle avoidance Flat trajectory B-spline basis MIP (Mixed-Integer Programming) UAV (Unmanned Aerial Vehicle)

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A Novel Educational Proposal: Devising an Electric Power System

A Novel Educational Proposal: Devising an Electric Power Sys...

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International Conference on Electrical Machines

作者： C. A. Platero R. M. de Castro J. R. Arribas L. F. Beites F. Blazquez A. H. Bayo M. Izzeddine M. Lafoz S. Martinez D. Ramirez C. Veganzones Department of Automatic Control Electrical and Electronic Engineering and Industrial Informatics ETSI Industriales Universidad Politecnica de Madrid

ISBN: (纸本)9781509025398

The study of electric power systems within the field of Electrical engineering is usually approached by computer simulation because any actual test is quite complex to be implemented, especially with renewable energies. Having the aim to improve student learning about this topic, a new subject called "Devising an Electric Power System" was organized following a CDIO (Conceive-Design-Implement-Operate) approach. The subject is programmed for one academic year and based entirely on laboratory work. The students are divided into three teams. Every team would have to work on a power system that includes a solar PV generator and a pumping controlled drive, both connected to a three-phase grid. The third and last part of the subject is focused on "electric utility" business strategy. In the final day of the course a competition between the three teams takes place.

关键词： Active Learning CDIO as Context Electric Drives control Electric Markets Electrical engineering Integrated Learning Experiences Solar PV Generation

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Robust Power Management control for Stand-Alone Hybrid Power Generation System

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Journal of Physics: Conference Series 2017年第1期783卷

作者： Elkhatib Kamal Lounis Adouane Abdel Aitouche Walaa Mohammed Industrial Electronics and Control Department Faculty of Electronic Engineering Menoufia University Menouf Egypt and Institut Pascal / IMobS3 Blaise Pascal University–UMR CNRS 6602 Clermont-Ferrand France. Institut Pascal / IMobS3 Blaise Pascal University – UMR CNRS 6602 Clermont-Ferrand France Laboratory CRISTAL (Center of Research in Informatics Signal and Automatic in Lille) University of Lille 1 France Industrial Electronics and Control Dep. Faculty of Electronic Engineering Menoufia University Menouf Egypt

This paper presents a new robust fuzzy control of energy management strategy for the stand-alone hybrid power systems. It consists of two levels named centralized fuzzy supervisory control which generates the power references for each decentralized robust fuzzy control. Hybrid power systems comprises: a photovoltaic panel and wind turbine as renewable sources, a micro turbine generator and a battery storage system. The proposed control strategy is able to satisfy the load requirements based on a fuzzy supervisor controller and manage power flows between the different energy sources and the storage unit by respecting the state of charge and the variation of wind speed and irradiance. Centralized controller is designed based on If-Then fuzzy rules to manage and optimize the hybrid power system production by generating the reference power for photovoltaic panel and wind turbine. Decentralized controller is based on the Takagi-Sugeno fuzzy model and permits us to stabilize each photovoltaic panel and wind turbine in presence of disturbances and parametric uncertainties and to optimize the tracking reference which is given by the centralized controller level. The sufficient conditions stability are formulated in the format of linear matrix inequalities using the Lyapunov stability theory. The effectiveness of the proposed Strategy is finally demonstrated through a SAHPS (stand-alone hybrid power systems) to illustrate the effectiveness of the overall proposed method.

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A backstepping control method for a nonlinear process-two coupled-tanks

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2015年第3 3期77 77卷 67-76页

作者： Calofir, Vasile Tʇnasʇ, Valentin Fʇgʇrʇşan, Ioana Stamatescu, Iulia Arghira, Nicoleta Stamatescu, Grigore Department of Automatic Control and Industrial Informatics University POLITEHNICA of Bucharest Romania Automatic Control and Systems Engineering Department University POLITEHNICA of Bucharest Romania

The aim of this work is to compute a level backstepping control strategy for a coupled tanks system. The coupled tanks plant is a component included in the water treatment system of power plants. The nonlinear-model of the process was designed and implemented in Matlab-Simulink. The advantages of the control method proposed is that it takes into consideration the nonlinearity which can be useful for stabilization and a larger operating point with specified performances. The backstepping control method is computed using the nonlinear model of the system and the performance was validated on the physical plant.

关键词： Backstepping

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Geometrical considerations for photogrammetry missions in an UAV context

Geometrical considerations for photogrammetry missions in an...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Florin Stoican Dan Popescu Emilian Vlăsceanu Cristian Mateescu Department of Automatic Control and Systems Engineering UPB Romania Department of Automatic Control and Industrial Informatics UPB Romania Teamnet International Bucharest Romania

This paper discusses a practical implementation for photogrammetry missions in an UAV setting. Further advances, which exploit geometrical properties of the problem are considered. In particular, a bi-level optimization procedure which minimizes the total path-length is discussed. Various constraints and limitations are taken into account.

关键词： Optimization Polynomials Shape Lattices Payloads Mathematical model Atmospheric modeling

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