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2021 International Conference on Power, Energy and Innovations, ICPEI 2021

作者： Thitinaruemit, Aphirak Sitjongsatapom, Suchada Prongnuch, Sethakarn Mahanakorn University of Technology The Electrical Engineering Graduate Program Faculty of Engineering and Technology Bangkok Thailand Faculty of Engineering and Technology Dept. of Electronic Engineering Bangkok Thailand Suan Sunandha Rajabhat University Faculty of Industrial Technology Dept. of Computer Engineering Bangkok Thailand

ISBN: (纸本)9781665402163

This paper present the network design and capacity planning of access point (AP) deployment for indoor positioning system. The estimation of WiFi distance is described briefly how to measure the signal strength of AP. Co-channel interference is a key for network design of access point installation for network capacity. The objective function for network capacity planning of AP deployment is to optimize the number of access point and location for indoor positioning system concerning with the minimized co-channel interference. Simulations are tested to install AP for lecture hall in university. Capacity planning design of wireless AP deployment is proposed for indoor position systems in terms of the received signal strength indications (RSSI). We assume the situation is supported for the crowded conference. The requirement of the results of wireless AP positioning in crowded conference rooms are placing the wireless AP in forms of overlap the signal in order to get the strong signal. Experimental results have been tested their received signal of WiFi APs with the 2.4GHz frequency using the receiver installed in laptops to check the signal. The empirical results shown that the strength of RSSI will be received a signal of -44 dBm at a distance of approximately 20 meters. © 2021 IEEE.

关键词： Signal receivers

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Review ofPractical Psychometrics: A Guide for Test Users

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Structural Equation Modeling: A Multidisciplinary Journal 2024年第5期31卷 932-934页

作者： Musyaffa’ Ahmad Muhammad Faisal a Graduate Program Department of Electrical Engineering and Information Technology Faculty of Engineering Universitas Gadjah Mada Jl. Grafika No. 2 UGM Campus Yogyakarta55281 Indonesia b Master of Mathematics Education Program Faculty of Mathematics and Natural Sciences Yogyakarta State University Jl. Colombo 1 Yogyakarta55281 Indonesia

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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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The Application of Artificial Neural Network Model to Predicting the Acid Mine Drainage from Long-Term Lab Scale Kinetic Test

arXiv

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arXiv 2024年

作者： Abfertiawan, Muhammad Sonny Kautsar, Muchammad Daniyal Hasan, Faiz Palinggi, Yoseph Pranoto, Kris Water and Wastewater Research Group Faculty of Civil and Environmental Engineering Bandung Institute of Technology Indonesia Department of Electrical and Information Engineering Universitas Gadjah Mada Indonesia Environmental Engineering Master Program Faculty of Civil and Environmental Engineering Bandung Institute of Technology Indonesia Environmental Department PT Kaltim Prima Coal Indonesia

Acid mine drainage (AMD) is one of the common environmental problems in the coal mining industry that was formed by the oxidation of sulfide minerals in the overburden or waste rock. The prediction of acid generation through AMD is important to do in overburden management and planning the post-mining land use. One of the methods used to predict AMD is a lab-scale kinetic test to determine the rate of acid formation over time using representative samples in the field. However, this test requires a long-time procedure and large amount of chemical reagents lead to inefficient cost. On the other hand, there is potential for machine learning to learn the pattern behind the lab-scale kinetic test data. This study describes an approach to use artificial neural network (ANN) modeling to predict the result from lab-scale kinetic tests. Various ANN model is used based on 83 weeks experiments of lab-scale kinetic tests with 100% potential acid-forming rock. The model approaches the monitoring of pH, ORP, conductivity, TDS, sulfate, and heavy metals (Fe and Mn). The overall Nash-Sutcliffe Efficiency (NSE) obtained in this study was 0.99 on training and validation data, indicating a strong correlation and accurate prediction compared to the actual lab-scale kinetic tests data. This show the ANN ability to learn patterns, trends, and seasonality from past data for accurate forecasting, thereby highlighting its significant contribution to solving AMD problems. This research is also expected to establish the foundation for a new approach to predict AMD, with time efficient, accurate, and cost-effectiveness in future applications. © 2024, CC BY-NC-SA.

关键词： Coal industry

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Configuration blade shape for enhancement crossflow turbine performance by the CFD method

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International Journal of Thermofluids 2024年 22卷

作者： Adanta, Dendy Sari, Dewi Puspita Syofii, Imam Thamrin, Ismail Yani, Irsyadi Marwani Fudholi, Ahmad Prakoso, Aji Putro Department of Mechanical Engineering Faculty of Engineering Universitas Sriwijaya Ogan Ilir South Sumatera30862 Indonesia Study Program of Mechanical Engineering Education Faculty of Teacher Training and Education Universitas Sriwijaya Ogan Ilir South Sumatera 30862 Indonesia Serpong15314 Indonesia Solar Energy Research Institute Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Department of Mechanical Engineering Faculty of Manufacturing Technology Universitas Jenderal Ahmad Yani West Java Cimahi Indonesia

The pico scale crossflow turbine (CFT) is a prospect as an independent power plant for remote and rural areas because it has a stable efficiency range of 64 % to 79.5 % in high discharge fluctuation. An alternative to CFT performance enhancement is determining the upper blade configuration to increase lift force. Hence, this study investigates four configurations of the upper CFT blade: convex blade at the centre edge, convex at the trailing edge, convex at the leading edge and ordinary curvature. This research employs a computational fluid dynamics (CFD) method to visualise the flow field. The upper CFT blade configuration significantly affects its performance, and convex at the leading edge has higher performance than others. The performance related to each blade shape's specific speed is parabolic and expressed using empirical law. The empirical law recommends 4.88 as specific speed for designing a pico scale CFT. © 2024 The Author(s)

关键词： Turbomachine blades

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Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method

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Joule 2024年第7期8卷 1958-1981页

作者： Maradesa, Adeleke Py, Baptiste Huang, Jake Lu, Yang Iurilli, Pietro Mrozinski, Aleksander Law, Ho Mei Wang, Yuhao Wang, Zilong Li, Jingwei Xu, Shengjun Meyer, Quentin Liu, Jiapeng Brivio, Claudio Gavrilyuk, Alexander Kobayashi, Kiyoshi Bertei, Antonio Williams, Nicholas J. Zhao, Chuan Danzer, Michael Zic, Mark Wu, Phillip Yrjänä, Ville Pereverzyev, Sergei Chen, Yuhui Weber, André Kalinin, Sergei V. Schmidt, Jan Philipp Tsur, Yoed Boukamp, Bernard A. Zhang, Qiang Gaberšček, Miran O'Hayre, Ryan Ciucci, Francesco Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Hong Kong Metallurgical and Materials Engineering Colorado School of Mines Golden80401 United States Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical Engineering Tsinghua University Beijing China Green Energy Storage Trento38123 Italy Department of Manufacturing and Production Engineering Faculty of Mechanical Engineering and Ship Technology Institute of Machine and Materials Technology Gdańsk University of Technology Gdańsk Poland Electrode Design for Electrochemical Energy Systems University of Bayreuth Bayreuth Germany School of Chemistry University of New South Wales Sydney Australia School of Advanced Energy Sun Yat-Sen University Shenzhen China Sustainable Energy Center CSEM Neuchâtel2002 Switzerland Interdisciplinary Faculty of Science and Engineering Shimane University Matsue Japan Centre for Electronic and Optical Materials National Institute for Materials Science Tsukuba Japan Department of Civil and Industrial Engineering University of Pisa Pisa Italy Department of Materials Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Department of Chemical Engineering Massachusetts Institute of Technology Cambridge02139 United States Electrical Energy Systems University of Bayreuth Bayreuth Germany Ruder Boskovic Institute Zagreb Croatia Department of Materials and Minerals Resources Engineering National Taipei University Taipei Taiwan Finland Johann Radon Institute for Computational and Applied Mathematics Linz Austria School of Science and Engineering Nanjing Tech. University Nanjing China Karlsruhe Germany Department of Materials Science and Engineering University of Tennessee KnoxvilleTN37996 United States Physical Science Division Pacific Northwest National Laboratory RichlandWA99354 United States Systems Engineering for Electrical Energy Storage University of B

Electrochemical impedance spectroscopy (EIS) is widely used in electrochemistry, energy sciences, biology, and beyond. Analyzing EIS data is crucial, but it often poses challenges because of the numerous possible equivalent circuit models, the need for accurate analytical models, the difficulties of nonlinear regression, and the necessity of managing large datasets within a unified framework. To overcome these challenges, non-parametric models, such as the distribution of relaxation times (DRT, also known as the distribution function of relaxation times, DFRT), have emerged as promising tools for EIS analysis. For example, the DRT can be used to generate equivalent circuit models, initialize regression parameters, provide a time-domain representation of EIS spectra, and identify electrochemical processes. However, mastering the DRT method poses challenges as it requires mathematical and programming proficiency, which may extend beyond experimentalists’ usual expertise. Post-inversion analysis of DRT data can be difficult, especially in accurately identifying electrochemical processes, leading to results that may not always meet expectations. This article examines non-parametric EIS analysis methods, outlining their strengths and limitations from theoretical, computational, and end-user perspectives, and provides guidelines for their future development. Moreover, insights from survey data emphasize the need to develop a large impedance database, akin to an impedance genome. In turn, software development should target one-click, fully automated DRT analysis for multidimensional EIS spectra interpretation, software validation, and reliability. Particularly, creating a collaborative ecosystem hinged on free software could promote innovation and catalyze the adoption of the DRT method throughout all fields that use impedance data. © 2024 Elsevier Inc.

关键词： Electrochemical impedance spectroscopy

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Defense scheme to avoid voltage collapse in transmission lines: A case study of paiton- situbondo transmission lines 2

Defense scheme to avoid voltage collapse in transmission lin...

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2nd International Conference on Technology and Policy in Electric Power and Energy, ICT-PEP 2020

作者： Kennedy, Andrey Facta, Mochammad Hermawan Diponegoro University Magister Study Program of Electrical Engineering Semarang Indonesia Indonesia Diponegoro University Faculty of Engineering Department of Electrical Engineering Semarang Indonesia

ISBN: (数字)9781728188355

ISBN: (纸本)9781728188355

Reliability, and continuity of service to customers is the top priority in the power system defense scheme. One important criterion is avoiding instability. Most conventional stability analysis is related to power swings due to frequency variations because the frequency is directly affected by power plant performance. However, in the transmission line, voltage instability is crucial because it practically give direct impact on customers. Especially for high voltage consumers, poor voltage quality is very influential on the performance of industrial equipment such as electric motors, textile machinery, and other electronic equipment, so the voltage quality must be maintained to avoid complaints from these consumers. The merge of frequency and voltage criteria instability is becoming the main focus in recent studies. In a large power system, voltage stability problem usually happens due to excess of electrical demand and deficiency of power generation. To avoid voltage instability, under-voltage load shedding can be an option to remove buses with unstable voltage in the power system. This paper focuses on the Paiton-Situbondo 150 kV transmission lines as the backbone of the power transfer from Java to Bali to investigating the role and effectiveness of the combination of frequency and voltage threshold to maintain the system stability when the faults occur on the transmission lines. © 2020 IEEE.

关键词： Electric lines

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Optimizing the Future of Production: Addressing Challenges in Job Shop Scheduling

Optimizing the Future of Production: Addressing Challenges i...

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Electronic and electrical engineering and Intelligent System (ICE3IS), International Conference on

作者： Teddy Nurcahyadi Christian Blum Mechanical Engineering Study Program Engineering Faculty Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia Institut d'Investigació en Intel·ligència Artificial Consejo Superior de Investigaciones Científicas Barcelona Spain

ISBN: (数字)9798350378368

ISBN: (纸本)9798350378375

Job shop scheduling methods are among the earliest optimization techniques that have been well-studied since 1950s. This fact reflects the prevalence of job shop scheduling problems in our daily lives, and hence, the importance of methods and tools needed to solve them. Human civilization has been evolving rapidly in the last several decades, presenting more difficult scheduling problems and the need to solve them efficiently. This article assesses the existing problems and optimization techniques in job shop scheduling. Furthermore, current and future challenges in this area are highlighted.

关键词： electrical engineering Job shop scheduling Metaheuristics Production Human factors Market research Deep reinforcement learning Dispatching Intelligent systems

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Pentapod: A New Type of Concrete Armor for Coastal Protection

SSRN

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SSRN 2024年

作者： Natakusumah, Dantje Kardana Achiari, Hendra Nugroho, Eka Oktariyanto Hidayatulloh, Syarif Ishakputra, Jonathan Angelo Adinata, Fitra Expertise Group in Water Resources Engineering Faculty of Civil and Environmental Engineering Institut Teknologi Bandung FCEE ITB Indonesia Marine Engineering Study Program FCEE ITB United Kingdom Institut Teknologi Bandung Indonesia PT. Sapta Ahi Pratama Indonesia

This paper explores PentaPod, an invention in concrete armor units developed to protect coastal areas from damage caused by waves and currents. Until now, there hasn't been an armor unit intentionally designed to enhance its stability through connections with neighboring units. PentaPod provides a novel perspective, suggesting that the stability of armor units can be significantly improved not only by having substantial weight and effective interlocking but also by securely connecting them to each other. With this in mind, PentaPod concrete armor can be installed in a random or regular manner without the need for fasteners. Alternatively, it can also be installed regularly in layers with fasteners. Compared to conventional concrete armor installations, the overall stability of structures is significantly improved with interconnected PentaPod, either partially or entirely. In this paper, the results of testing the Stability Coefficient (Kd) for two variations of armor, namely PentaCone and PentaOcta, tested in a Wave Tank are also presented. The objective of this testing is to ascertain the stability coefficient for both variations of armor when installed randomly or regularly without any tying involved. The PentaPod arrangement allows for the implementation of both Grey Protection (using concrete armor) and Green Protection (conservation of mangrove areas) simultaneously, showcasing its versatility and integrated approach to coastal protection. © 2024, The Authors. All rights reserved.

关键词： Armor

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Aerobic-pond Palm Oil Mill Effluent (POME) utilization as growth medium of Scenedesmus obliquus for lipid production 5

Aerobic-pond Palm Oil Mill Effluent (POME) utilization as gr...

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5th International Seminar on Sustainable Urban Development, ISoSUD 2020

作者： Situmeang, C.A. Sianturi, R. Lestari, Y. Martgrita, M.M. Bioprocess Engineering Study Program Faculty of Biotechnology Institut Teknologi Del Laguboti Toba Samosir North Sumatera22381 Indonesia

The purpose of this research is to know the growth rate and biomass production of Scenedesmus obliquus in palm oil mill effluent (POME) medium taken from aerobic pond and to know the lipid concentration produced by S. obliquus. In this research, S. obliquus was cultured in various POME concentration, those were 20, 60, 80, 90, 95, and 100% v/v, while the concentration of inoculum was 30% v/v, and fatty acid content was analysed by gas chromatography. The results revealed that growth rate was decrease with the increasing concentration of POME (0.3545, 0.1792, 0.1566, 0.1268, 0.1158, and 0.1008/day), dry biomass weight was increase with the increasing concentration of POME (0.40, 1.20, 1.30, 1.77, 2.28, and 2.45 g/L), and lipid content also tended to increase with the increasing concentration of POME (13.10%, 36.59%, 36.65%, 50.37%, 60.40%, and 64.98%). Oleic acid and behenic acid were the dominant fatty acid content in S. obliquus lipid cultured in 100% concentration POME media. It is concluded that aerobic-pond POME can be utilized as growth medium for S. obliquus with a high lipid content. © Published under licence by IOP Publishing Ltd.

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