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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Lőrinc Márton Wijaya Kurniawan Department of Electrical Engineering and Information Systems University of Pannonia Veszprem Hungary Department of Electrical Engineering Sapientia Hungarian University of Transylvania Corunca Romania Faculty of Computer Science University of Brawijaya Malang Indonesia

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This paper addresses the problem of fault isolation in networks containing loops where the dynamic behavior of the nodes can be modeled by finite gain linear systems. If the underlying graph of the network contains loops, isolating a faulty subsystem can be challenging. This is because the propagation of fault effects through the network interconnections is difficult to trace. In this study, it is shown that, if the gains of the subsystems satisfy certain assumptions, the fault can be isolated in the loops of the considered network. For each subsystem in the loop, a residual signal is generated. The isolation method examines the differences between the norms of these residual signals. Based on this information, the location of the faulty subsystem can be determined. Simulation measurements are provided to show the efficiency of the proposed fault isolation method.

关键词： Linear systems Computational modeling Simulation Directed graphs Information technology Gain

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Smart Dome 4.0: Low-Cost, Independent, Automated Energy System for Agricultural Purposes enabled by Machine Learning 2

Smart Dome 4.0: Low-Cost, Independent, Automated Energy Syst...

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2021 2nd International Symposium on Automation, Information and Computing, ISAIC 2021

作者： Budiman, Arief S Gunawan, Fergyanto Djuana, Endang Pardamean, Bens Romeli, Sugiarto Putri, Dianing Nn Aji, Daisman Pb Rahardjo, Kuat Stevanus Ilham Wibowo, M. Daffa, Nadiev Owen, Raymond Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia Department of Manufacturing and Mechanical Engineering and Technology Oregon Institute of Technology Klamath FallsOR97601 United States Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia PT. Impack Pratama Industri Tbk Jakarta Indonesia Mechanical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta Indonesia Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia

Many economically essential crops in Indonesia (such as coffee, tea, chocolate, or copra) require storage or drying under certain environmental conditions, especially temperature and humidity. The solar dryer dome, typically used for agricultural purposes in Indonesia, produces a sufficient amount of heat to increase the evaporation rate inside the dome and reduce the moisture content of the commodity. A hybrid solar dryer accompanied by a photovoltaic panel, fan, and ventilation system is generally suitable. The system can provide an optimum environment with minimum control. However, as the outdoor temperature and humidity change dramatically, such as at night time, more control is required. Based on Industry 4.0 technologies, we have developed a new kind of hybrid solar dryer that provides an optimum environment 24/7. The system, called Smart Dome 4.0, is an intelligent, low-cost, self-sufficient drying and storage system to support Indonesia Agriculture 4.0. The system has a local power generation unit to self-sustain the required energy and operate without connecting to the electricity grid. The system utilizes a machine-learning algorithm to predict the environmental condition and optimally uses self-generated electric power. The developed Smart Dome 4.0 technology is critical to producing a sustainable solar dome under drastic environmental dynamics. © Published under licence by IOP Publishing Ltd.

关键词： Learning algorithms

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Development of Antimicrobial Envelope for RFID Card

Development of Antimicrobial Envelope for RFID Card

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International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON

作者： Sukritta Paripurana Navapadol Kittiamornkul Orrathai Watcharakitchakorn Rapeepan Keawon Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangkok Thailand Department of Biomedical Engineering Faculty of Health Sciences Christian University of Thailand Thailand Department of Electrical Engineering Faculty of Engineering and Industrial Technology Silpakorn University Thailand

This paper proposes the development of an RFID envelope coated with an antimicrobial material that can stop microorganisms’ growth while the card is still regularly used. Copper is chosen as the antimicrobial material for coating on an envelope made of polyethylene terephthalate (PET) by using DC sputtering. The antimicrobial ability of the proposed envelope is investigated against Escherichia coli (E. coli). The result shows that the survival time of E. coli on the proposed envelope is decreased compared with the PET envelope without the copper thin film coated on. Besides its antimicrobial quality, copper can let radio frequency pass through. Thus, the effectiveness of electromagnetic wave transmission through the proposed envelope coated with different thickness of a copper thin film is tested. To evaluate the performance of the proposed envelope, three experiments which cover the test of the antimicrobial ability of copper thin film, the resistance of copper thin film, and performance of RF transmission of RFID reader and tag are conducted. The results of the three experiments show that a copper thin film can prevent the microorganisms’ growth, the resistance of the copper thin film is decreasing while the thickness of the copper thin film is increasing, and the radio frequency can pass though the proposed envelope.

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Water for Green Hydrogen Production

Water for Green Hydrogen Production

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International Scientific Conference on Electric Power engineering (EPE)

作者： Iwona Klosok-Bazan Miroslava Gono Hana Svehlakova Department of Thermal Engineering and Industrial Facilities Faculty of Mechanical Engineering Opole University of Technology Opole Poland Department of Electrical Power Engineering Faculty of Electrical Engineering and Computer Science VSB - Technical University of Ostrava Ostrava-Poruba Czech Republic Faculty of Mining and Geology Institute of Environmental Engineering VSB - Technical University of Ostrava Ostrava-Poruba Czech Republic

ISBN: (数字)9798350348774

ISBN: (纸本)9798350348781

Hydrogen is considered a powerful fuel for the future. Hydrogen production technologies vary widely. Green hydrogen is generated by electrolyzing water with electricity produced from renewable energy sources. According to the stoichiometry reaction, 9 kg of water is consumed to produce 1 kg of hydrogen. The water to be electrolysed has to meet stringent requirements and its preparation generates large quantities of wastewater, which should be managed appropriately. The objective of this research is to examine the methods by which water is prepared depending on its source and to determine the level of wastewater generated by its treatment. The results of the analyses carried out indicate that the water abstraction associated with green hydrogen production is significantly higher than the 9 kg per 1 kg of hydrogen value reported in numerous studies.

关键词： Cooling Electricity Green products Production Green hydrogen Power systems Wastewater

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Twin-Array Quasi FSS Reflector with Dual Band Cross-Dipole for 5G Base Station Antenna Application

Twin-Array Quasi FSS Reflector with Dual Band Cross-Dipole f...

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2023 International Conference on Power, Energy and Innovations, ICPEI 2023

作者： Santos, Ian Jerome Q. Tangjitjetsada, Maleeya Rakluea, Paitoon Wongsin, Norakamon Rakluea, Chawalit Mahatthanajatuphat, Chatree Chudpooti, Nonchanutt Thianthong, Tawan Rajamangala University of Technology Thanyaburi Faculty of Engineering Department of Electronics and Telecommunication Engineering Thanyaburi Pathum Thani 12110 Thailand Rajamangala University of Technology Suvarnabhumi Faculty of Engineering and Architecture Department of Electronics and Telecommunication Engineering Nonthaburi Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Wongsawang Bangsue Bangkok10800 Thailand King Mongkut's University of Technology North Bnagkok Faculty of Applied Science Department of Industrial Physics and Medical Instrumentation Wongsawang Bangsue Bangkok10800 Thailand Siam Airport Ground Service Co. Ltd. Don Mueang Bangkok10210 Thailand

ISBN: (纸本)9798350344585

This article provides an explanation of the use of a Twin-Array Quasi Frequency Selective Surface (FSS) Reflector with Dual Band Cross-Dipole for antenna applications in 5G base stations. The base material employed in this study is FR4 sheet, which has a dielectric constant (ϵr) of 4.3. The antenna obtained has dimensions of 100x100 mm2 and functions throughout the frequency spectrum spanning from 730 to 860 MHz, 1700 to 2130 MHz. The primary benefits of this antenna design are its lightweight structural composition, compatibility with the frequency range of 730-860 MHz, and discernible performance attributes. The CST Studio Suite software was used to conduct a simulation of the antenna's performance. The antenna has an operating frequency range of 730-860 MHz and 1700-2130 MHz, enabling it to support a unidirectional wave propagation pattern that is suitable for the implementation of a 5G mobile communication base station. © 2023 IEEE.

关键词： Dipole antennas

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Applications, Insights and Implications of Digital Twins in Smart City Management

Applications, Insights and Implications of Digital Twins in ...

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International Smart Grid Workshop and Certificate Program (ISGWCP)

作者： Mustafa Ersan Erdal Irmak Alperen Mustafa Colak Department of Electrical and Electronics Engineering Graduate School of Natural and Applied Sciences Gazi University Ankara Türkiye Department of Electrical and Electronics Engineering Faculty of Technology Gazi University Ankara Türkiye Industrial and Energy Systems Division Toshiba Mitsubishi-Electric Industrial Systems Corporation Tokyo Japan

ISBN: (数字)9798350361612

ISBN: (纸本)9798350361629

Digital twins (DTs) represent a transformative paradigm in urban management, leveraging computer modelling and real-time data integration to create virtual replicas of physical entities and systems. This paper explores their multifaceted applications, emphasizing efficiency, sustainability, and resilience. Synthesizing insights from diverse disciplines, it delineates the process of building digital twins and underscores their role in predictive maintenance, optimized performance, and data-driven decision-making. Using a smart city example, the paper illustrates how digital twins facilitate proactive interventions, resource optimization, and informed decision-making in domains such as traffic management, energy optimization, and public safety. It highlights the significance of digital twins in fostering collaboration, innovation, and resilience, empowering cities to address complex challenges and create inclusive, sustainable environments. In conclusion, digital twins emerge as indispensable tools in realizing the vision of smart, connected, and adaptive cities, poised to navigate the complexities of the contemporary urban landscape and pave the way for a sustainable future.

关键词： Technological innovation Smart cities Decision making Real-time systems Public security Digital twins Sustainable development

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Time Series Forecasting of XRP Using Machine Learning Algorithms

Time Series Forecasting of XRP Using Machine Learning Algori...

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Integration of Computational Intelligent System (ICICIS), International Conference on

作者： Nayeem Ahmed Md. Mahbubur Rahman Faculty of Electrical and Computer Engineering Technische Universität Dresden Dresden Germany Dept. of Industrial and Production Engineering BUET Dhaka Bangladesh

With the advancement of technology, cryptocurrencies are getting prominence as valuable investment assets. Unlike fiat currencies regulated by governments, cryptocurrencies allow for secure anonymous transactions and have a limited quantity in the market due to the mathematical algorithms established by the inventors. Therefore, investors across the globe find cryptocurrencies as a hedge against inflation for their investments. XRP has recently become one of the most popular cryptocurrencies, attracting huge interest from crypto investors and developers all around the world. But, because of its highly volatile nature, it can harm the market investors and users of the currency. In this study, prediction techniques based on machine learning have been proposed to forecast the price of XRP. Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Autoregressive Integrated Moving Average (ARIMA) algorithms are used in this work for the prediction. Nowadays, many financial sectors use machine learning algorithms to forecast their future trends. The closing price data of XRP is taken into a time series format and fitted into the aforementioned models. In the end, a comparative analysis is shown among the algorithms. Evaluation parameters such as MAPE (Mean Absolute Percentage Error), R2 and RMSE (Root Mean Absolute Error) are presented to determine the better one for prediction with better accuracy.

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A Low Complexity ML-Based Methods for Malware Classification

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computers, Materials & Continua 2024年第9期80卷 4833-4857页

作者： Mahmoud E.Farfoura Ahmad Alkhatib Deema Mohammed Alsekait Mohammad Alshinwan Sahar A.El-Rahman Didi Rosiyadi Diaa Salama Abd Elminaam Cybersecurity Department Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan Computer Systems Program-Electrical Engineering Department Faculty of Engineering-ShoubraBenha UniversityCairo11629Egypt Research Center for Artificial Intelligence and Cybersecurity Electronics and Informatics OrganizationNational Research and Innovation Agency(BRIN)KST Samaun SamadikunBandung40135Republic of Indonesia Jadara Research Center Jadara UniversityIrbid21110Jordan MEU Research Unit Middle East UniversityAmman11831Jordan

The article describes a new method for malware classification,based on a Machine Learning(ML)model architecture specifically designed for malware detection,enabling real-time and accurate malware *** an innovative feature dimensionality reduction technique called the Interpolation-based Feature Dimensionality Reduction Technique(IFDRT),the authors have significantly reduced the feature space while retaining critical information necessary for malware *** technique optimizes the model’s performance and reduces computational *** proposed method is demonstrated by applying it to the BODMAS malware dataset,which contains 57,293 malware samples and 77,142 benign samples,each with a 2381-feature *** the IFDRT method,the dataset is transformed,reducing the number of features while maintaining essential data for accurate *** evaluation results show outstanding performance,with an F1 score of 0.984 and a high accuracy of 98.5%using only two reduced *** demonstrates the method’s ability to classify malware samples accurately while minimizing processing *** method allows for improving computational efficiency by reducing the feature space,which decreases the memory and time requirements for training and *** new method’s effectiveness is confirmed by the calculations,which indicate significant improvements in malware classification accuracy and *** research results enhance existing malware detection techniques and can be applied in various cybersecurity applications,including real-timemalware detection on resource-constrained *** and scientific contribution lie in the development of the IFDRT method,which provides a robust and efficient solution for feature reduction in ML-based malware classification,paving the way for more effective and scalable cybersecurity measures.

关键词： Malware detection ML-based models dimensionality reduction feature engineering

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Implications of Solution Patterns on Adversarial Robustness

Implications of Solution Patterns on Adversarial Robustness

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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Hengyue Liang Buyun Liang Ju Sun Ying Cui Tim Mitchell Department of Electrical & Computer Engineering University of Minnesota Department of Computer Science & Engineering University of Minnesota Department of Industrial & Systems Engineering University of Minnesota Department of Computer Science Queens College City University of New York

Empirical robustness evaluation (RE) of deep learning models against adversarial perturbations involves solving non-trivial constrained optimization problems. Recent work has shown that these RE problems can be reliably solved by a general-purpose constrained-optimization solver, PyGRANSO with Constraint-Folding (PWCF). In this paper, we take advantage of PWCF and other existing numerical RE algorithms to explore distinct solution patterns in solving RE problems with various combinations of losses, perturbation models, and optimization algorithms. We then provide extensive discussions on the implications of these patterns on current robustness evaluation and adversarial training. A comprehensive version of this work can be found in [19].

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A discussion regarding the application of the hertz contact theory on biological samples in afm nanoindentation experiments

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Micro and Nanosystems 2021年第1期13卷 42-48页

作者： Kontomaris, Stylianos Vasileios Stylianou, A. Nikita, K.S. Malamou, A. Mobile Radio Communications Laboratory School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Faculty of Architecture Engineering & Built Environment Athens Metropolitan College Athens Greece Cancer Biophysics Laboratory Department of Mechanical and Manufacturing Engineering Faculty of Engineering University of Cyprus Nicosia Cyprus Radar Systems and Remote Sensing Lab of School Electrical & Computer Engineering National Technical University of Athens Athens Greece

Atomic Force Microscopy (AFM) Nanoindentation procedure regarding biological samples poses significant challenges with respect to the accuracy of the provided results. These challenges are related to the inhomogeneity of biological samples, various uncertainties in experimental methods and certain approximations regarding the theoretical analysis. The most commonly used theoretical model for data processing at the linear elastic regime regarding biological samples is the Hertz model. This paper focuses on the investigation of the resulting errors of the basic equation of the Hertz theory that depends on the ratio, indentation depth/indenter’s radius regarding the Young’s modulus calculation. Several examples in the literature that do not take into account the value of the ratio indentation depth/indenter’s radius are reported and the related errors are presented and discussed. In addition, an extended new equation is derived which takes into account the influence of the aforementioned ratio on the calculation of the Young’s modulus and can be easily used for calculations. Moreover, a rational explanation, regarding the extended differences of the Young’s modulus calculations using the same experimental results when these are processed using the Hertz model and the Oliver & Pharr analysis (which is the general model that applies for any axisymmetric indenter) is provided. In conclusion, the derived equation is further combined with equations which take into account the shape of the sample in order to provide a complete and reliable theoretical tool which can be generally applied in order to reduce the errors produced by the current methodology. © 2021 Bentham Science Publishers.

关键词： Nanoindentation

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