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International Symposium on Wireless Communication systems (ISWCS)

作者： Ogobuchi Daniel Okey Demostenes Zegarra Rodriguez João Henrique Kleinschmidt Center for Engineering Modeling and Applied Social Sciences Federal University of ABC São Paulo Brazil Graduate Program in Systems and Automation Engineering Federal University of Lavras Minas Gerais Brazil

ISBN: (数字)9798350362510

ISBN: (纸本)9798350362527

The Internet of Things (IoT) devices have been identified to have low security measures by default, thus making them highly vulnerable to malicious attacks. Machine learning-based intrusion detection systems (IDS) are used to mitigate these attacks, however, there is a compromise in security and privacy of data ownership between IoT devices. This paper proposes a Federated Ensemble IDS (CNN-GRU and LSTM-GRU) for monitoring IoT network activities using Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU) and Long-Short Term Memory (LSTM) networks that classifies the network as either normal or malicious. Two aggregation functions, including wFedAvg and wFedProx, are developed to create a global model from different clients’ contribution. We perform an evaluation of the proposed IDS on CICIoT2023 and FLNET2023 datasets. The results show that with wFedAvg, the CNN-GRU achieved an accuracy of 98.25% and 99.25% on the CICIoT2023 and FLNET2023 datasets respectively. Additionally, the LSTM-GRU model shows a detection accuracy of 93.36% and 95.66%, respectively on CICIoT2023 and FLNET2023 datasets. The performance shows that the proposed method is robust enough to enhancing the privacy of IoT devices.

关键词： Wireless communication Accuracy Intrusion detection Telecommunication traffic Robustness Internet of Things Convolutional neural networks

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Heuristic Methodology for Horizontal Multilayer Soil Stratification

Heuristic Methodology for Horizontal Multilayer Soil Stratif...

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IEEE International Conference on Environment and Electrical engineering

作者： Diogo N. Oliveira Carlos L.B. Silva Wesley P. Calixto Aylton J. Alves Viviane Gomes José Luís Domingos Graduate Program in Electronic and Automation Systems Engineering University of Brasilia Brasilia Brazil Experimental Technological Research and Study Group Federal Institute of Education Science and Technology Goiania Brazil

ISBN: (纸本)9781509023219

Soil Stratification methods are used to estimate soil geoelectrical parameters. Several stratification methods are available, but reducing the error estimation introduced by such methods still poses as a challenge. The purpose of this work is to present a heuristic algorithm applied to the optimization of geoelectrical prospection process. The goal is to estimate soil parameters, such as the amount of layers, thickness and resistivity of each layer in an optimal and automated manner. The algorithm consists of analyzing the sensitivity of sampling space parameters. The propose methodology shows error reduction above 75% between the experimental and theoretical curves of the analyzed soils. The results are presented and discussed.

关键词： Heuristic algorithm soil stratification parameter sensitivity

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Fuzzy-neuro predictive control, tuned by genetic algorithms, applied to a fermentation process

Fuzzy-neuro predictive control, tuned by genetic algorithms,...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： J.A. Fabro L.V.R. Arruda Automation and Advanced Control Systems Labratory-LASCA Graduate Program on Electrical Engineering and Applied Computer Science-CPGEI Federal Centre of Technological Education of Paraná Curitiba Parana Brazil

This paper proposes the development of a fuzzy predictive control. Genetic algorithms (GA's) are used to automatically tune the controller. A recurrent neural network is used to identify the process, and then provides predictions about the process behavior, based on control actions applied to the system. These predictions are used by the fuzzy controller, in order to accomplish a better control of an alcoholic fermentation process from chemical industry. This problem has been chosen due to its non-linearity and large accommodation time, that make it hard to control by standard controllers. Comparison of performance is made with non-predictive approaches(PID and Fuzzy-PD), and also with another predictive approach, GPC(Generalized Predictive Control).

关键词： Predictive control Genetic algorithms Control systems Fuzzy control Alcoholism Recurrent neural networks Nonlinear control systems Artificial intelligence Biomass Control system synthesis

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PV Microgeneration Perspective in Brazil: Approaching Interconnection Procedures and Equipment Certification

PV Microgeneration Perspective in Brazil: Approaching Interc...

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IEEE Green Technologies Conference (IEEE-Green)

作者： A.M.S. Alonso F.P. Marafão F.A.S. Gonçalves H.K.M. Paredes A.C.G. Martins D.I. Brandao Group of Automation and Integrated Systems São Paulo State University (Unesp) Sorocaba Brazil Graduate Program in Electrical Engineering Federal University of Minas Gerais Belo Horizonte Brazil

Considering that distributed microgeneration systems are one of the most prominent trends in adding flexibility to the Brazilian energy matrix, regulation and certification standards become key players on providing well established interconnection procedures to the electrical power system, without degrading power quality and offering fair services to all institutions. Thus, this paper presents relevant information regarding to how the local interconnection procedures occur, as well as it presents different considerations on certification requirements for grid-tied inverters and PV modules available on the Brazilian market. Moreover, an overview of current constraints is raised, based on the comparison with other worldwide known standards and conditions for distributed energy systems.

关键词： Inverters Certification Biological system modeling IEC Standards Power generation Power quality

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Towards Real-Time Machining Tool Failure Forecast Approach for Smart Manufacturing systems

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IFAC-PapersOnLine 2022年第2期55卷 548-553页

作者： Nicolas Nebelung Mario D.S. de Oliveira Santos Sofia T. Helena Athon F.C.S. de Moura Leite Matheus B. Canciglieri Anderson L. Szejka Control and Automation Engineering Department Pontifical Catholic University of Paraná (PUCPR) Curitiba Brazil Junior Scientific Initiation Program at the Nossa Senhora de Medianeira School and Pontifical Catholic University of Paraná Curitiba – Paraná Brazil Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná (PUCPR) Curitiba Brazil

Industry 4.0 is characterized by a dynamic market that constantly looking for new methods to optimize and integrate manufacturing processes. In this context, Artificial Intelligence has gained prominence in problem-solving, such as failure prediction and decision making, thus improving product quality, and consequently bringing competitiveness to the company. Aiming to contribute to this scenario, this research develops a data treatment system that, from an intelligent tool and an interoperable ontological model, automates the prediction and detection of failures in machining machines lines. The system was developed for the prediction of faults in machining lines includes an artificial intelligence formed from prediction algorithms and inferences, it is possible to guarantee the correct treatment and communication of data at different stages of the process. For the experimental research, was used data collected from a machining line of a public dataset. The information is collected and classified by Artificial Intelligence that supports a decision system. The prediction of tool wear would enable the system to infer the type of problem that is causing this wear, a possible root cause, and the needed maintenance based on the ontological inference tool. By this classification of data, it is possible to achieve, through inferences, a reduction in the decision scope, bringing the possible problems caused by the incoming value. The semantic interoperability ensures correct data exchange and processing, which generates a more assertive view of production failures. The system may help companies to increase their productive process by helping them identify future failures in production if applied in a real scenario.

关键词： Industry 4.0 Smart System Artificial Intelligence Machine Learning Ontology Machine Failure Forecast

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Ontology and Rules for Characterization of Sensors and Actuators Devices in AADL Models

Ontology and Rules for Characterization of Sensors and Actua...

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Brazilian Symposium on Computing System engineering (SBESC)

作者： Diego Camara Sales Cristian Koliver Leandro Buss Becker UFSC Florianopolis SC Brazil Federal Institute of Amazon - IFAM Campus Manaus Distrito Industrial AM Brazil Graduate Program on Automation Systems Engineering (PGEAS) UFSC Florianopolis SC Brazil

ISBN: (数字)9781728182865

ISBN: (纸本)9781728182872

This paper presents a set of ontologies to organize concepts, categories, properties, and relationships that are typically used by designers for characterizing sensing and actuation devices that compose a given system architecture (SA). From the characterization of such devices, modeling can be done using the Architecture Analysis and Design Language (AADL). AADL supports modeling and analysis of functional and nonfunctional properties to evaluate quality attributes from ontology models. The paper also proposes an AADL property set that can be applied to sensors and actuators (S&A), based on previous researches with ontologies applied to sensor networks. Specific characteristics are provided to describe systems' quality attributes. This aims to be used for analyzing the designed architecture, and also its probable future evolution.

关键词： Ontologies Actuators Software Sensor phenomena and characterization Computer architecture Standards ISO Standards

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Computation of grounding grids parameter on unconventional geometry

Computation of grounding grids parameter on unconventional g...

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CHILEAN Conference on Electrical, Electronics engineering, Information and Communication Technologies (CHILECON)

作者： Thyago G. Pires Carlos L. B. Silva Diogo N. Oliveira Jose W. L. Nerys Aylton J. Alves Wesley P. Calixto School of Electrical and Computer Engineering Federal University of Goias Goiania Brazil Graduate Program in Electronic and Automation Systems Engineering University of Brasilia Brasilia Brazil Experimental & Technologic Researsh and Study Group Federal Institute of Education Goiania Brazil

ISBN: (纸本)9781467387576

This paper deals with the computation of ground resistance, surface voltage, touch voltage and step voltage, to mesh with horizontal wires arranged in different angles. The computer program implemented used in the mathematical modeling is based on the method proposed by Heppe, which allows obtaining the grounding parameters for homogeneous soil and soil stratified in two layers. Furthermore, the results obtained by the Variable Currents Method (VCM) have been compared to traditional methods and the simplified method of ANSI-IEEE Std. 80/2013. They also present the results using a grounding grid with wires on various angles.

关键词： Soil Leakage currents Image segmentation Conductivity Grounding Surface resistance

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A WebLab Control Experiment using the Ball and Beam System and Multiobjective Optimization

A WebLab Control Experiment using the Ball and Beam System a...

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Experiment@ International Conference (exp.at)

作者： Ricardo Massao Kagami Guinther Kovalski da Costa Luciano Antônio Mendes Roberto Zanetti Freire Industrial and Systems Engineering Graduate Program – PPGEPS Pontifícia Universidade Católica do Paraná – PUCPR Curitiba Brazil Department of Control and Automation Engineering Pontifícia Universidade Católica do Paraná - PUCPR Curitiba Brazil

By associating active learning methodologies and digital media as a form to improve educational quality, the diversity of experimentations in engineering education has been motivating researches in many areas with possibilities of increasing both students' knowledge and skills. Control engineering is an area where educational laboratories are usually costly, thus the use of virtual laboratories for remote experimentation became an interesting approach. In this work, it is presented a remote experimentation procedure for the ball and beam system, which is a nonlinear and unstable open loop process. Considering the advanced control topic, multiobjective optimization was introduced in the experiment in order to tune Proportional-Integral-Derivative (PID) controllers. Through the description of the system model, the multiobjective optimization technique, and the experiment configuration, students can simulate and test their controllers remotely in a real plant.

关键词： Laboratories Mathematical model PD control Optimization Process control PI control

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Additive nanomanufacturing of lab-on-a-chip fluorescent peptide nanoparticle arrays for Alzheimer＇s disease diagnosis

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Bio-Design and Manufacturing 2018年第3期1卷 182-194页

作者： Leming Sun Zhen Fan Tao Yues Jun Yin Jianzhong FU Mingjun Zhang Department of Biomedical Engineering College ofEngineering Ohio State University Columbus OH 43210USA School of Life Sciences Northwestern PolytechnicalUniversity Xi'an 710072 Shaanxi China Department of Polymeric Materials School of MaterialScience and Engineering Tongji UniversityShanghai 201804 China Institute for Advanced Study TongjiUniversity Shanghai 200092 China School of Mechatronic Engineering and Automation Shanghai University Shanghai 200444 China The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering ZhejiangUniversity Hangzhou 310028 China Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province School of Mechanical EngineeringZhejiang University Hangzhou 310028 China Dorothy M. Davis Heart & Lung Research Institute The OhioState University Wexner Medical Center Columbus OH43210 USA Interdisciplinary Biophysics Graduate Program Ohio StateUniversity Columbus OH 43210 USA

This paper proposes an additive nanomanufacturing approach to fabricate a personalized lab-on-a-chip fluorescent peptide nanoparticles （f-PNPs） array for simultaneous multi-biomarker detection that can be used in Alzheimer＇s disease （AD） diagnosis. We will discuss optimization techniques for the additive nanomanufacturing process in terms of reliability, yield and manufacturing efficiency. One contribution of this paper lies in utilization of additive nanomanufacturing techniques to fabricate a patient-specific customize-designed lab-on-a-chip device for personalized AD diagnosis, which remains a major challenge for biomedical engineering. Through the integrated bio-design and bio-manufacturing process, doctor＇s check- up and computer-aided customized design are integrated into the lab-on-a-chip array for patient-specific AD diagnosis. In addition, f-PNPs with targeting moieties for personalized AD biomarkers will be self-assembled onto the customized lab-on-a- chip through the additive nanomanufacturing process, which has not been done before. Another contribution of this research is the personalized lab-on-a-chip f-PNPs array for AD diagnosis utilizing limited human blood. Blood-based AD assessment has been described as ＂the holy grail＂ of early AD detection. This research created the computer-aided design, fabrication through additive nanomanufacturing, and validation of the f-PNPs array for AD diagnosis. This is a highly interdisciplinary research contributing to nanotechnology, biomaterials, and biomedical engineering for neurodegenerative disease. The conceptual work is preliminary with intent to introduce novel techniques to the application. Large-scale manufacturing based on the proposed framework requires extensive validation and optimization.

关键词： Nanomanufacturing Lab-on-a-chip Fluorescent peptide nanoparticle Alzheimer's disease Diagnosis

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Hardware Particle Swarm Optimization with passive congregation for embedded applications

Hardware Particle Swarm Optimization with passive congregati...

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Southern Conference on programmable Logic

作者： Daniel M. Muñoz Carlos H. Llanos Leandro dos S. Coelho Mauricio Ayala-Rincón Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brazil Industrial and Systems Engineering Graduate Program LAS/PPGPES Pontifical Catholic University of Paraná Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brazil

Achieving high performance optimization algorithms for embedded applications can be very challenging, particularly when several requirements such as high accuracy computations, short elapsed time, area cost, low power consumption and portability must be accomplished. This paper proposes a hardware implementation of the Particle Swarm Optimization algorithm with passive congregation (HPPSOpc), which was developed using several floating-point arithmetic libraries. The passive congregation is a biological behavior which allows the swarm to preserve its integrity, balancing between global and local search. The HPPSOpc architecture was implemented on a Virtex5 FPGA device and validated using two multimodal benchmark problems. Synthesis, simulation and execution time results demonstrates that the passive congregation approach is a low cost solution for solving embedded optimization problems with a high performance.

关键词： Hardware Computer architecture Software Field programmable gate arrays Benchmark testing Optimization Software algorithms

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