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8th IEEE International Conference on engineering Technologies and Applied Sciences, ICETAS 2023

作者： Bagadi, Kalapraveen Annepu, Visalakshi Jameel Al-Tamimi, Adnan Naji Challa, Naga Raju Aljibori, H.S.S. Mohammed, M.N. Abdullah, Oday I. Abbas Helmi, Rabab Alayham Alfiras, M. School of Electronics Enineering VIT-AP University Amaravati India School of Comp. Science & Eng. VIT-AP University Amaravati India College of Technical Engineering Al-Farahidi University Baghdad Iraq Bapatla Engineering College Dept. of Elec. and Comm. Eng. Baptla India College of Engineering University of Warith Al-Anbiyaa Karbala Iraq College of Engineering Gulf University Mechanical Engineering Department Sanad26489 Bahrain University of Baghdad Dept of Energy Engineering Iraq College of Engineering Gulf University Mechanical Engineering Dept Sanad26489 Bahrain Hamburg University of Technology Institute of Laser and Systems Technologies Hamburg Germany School of Graduate Studies Management and Science University Selangor Shah Alam Malaysia College of Engineering Gulf University Electrical and Electronic Engineering Department Sanad26489 Bahrain

ISBN: (纸本)9798350327090

The fact that cardiovascular disease (CVD) is a major cause of death worldwide highlights the significance of accurate prediction for successful preventative and treatment measures. Machine learning algorithms, which use the analysis of vast patient data to reveal hidden patterns and risk variables, have recently come to light as potential techniques for CVD prediction. This study intends to analyse how machine learning (ML) techniques are used in CVD prediction and evaluate how well they perform in comparison to conventional approaches. The study makes use of a sizable patient cohort's medical history, demographic data, and clinical factors in a complete dataset. Predictive models are built using a variety of machine learning algorithms, including support vector machine (SVM), gradient boosting, K-nearest neighbours, naive Bayes classifier, and logistic regression. To find the most important factors influencing CVD risk, feature selection techniques are used. Metrics like accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve are used to assess how well the machine learning models work. The outcomes are contrasted with well-known risk prediction models and clinical guidelines in order to assess the added value of machine learning methods. This work intends to improve CVD prediction capabilities and offer useful insights for better risk assessment and management strategies by utilizing the power of machine learning. © 2023 IEEE.

关键词： Forecasting

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Computation of the (Positive) Largest Lyapunov Exponent Using Spice-Like programs

SSRN

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SSRN 2023年

作者： Nardo, Lucas G. Nazaré, Thalita E. Nepomuceno, Erivelton Butusov, Denis N. Arias-Garcia, Janier Graduate Program in Electrical Engineering Department of Electronic Engineering Federal University of Minas Gerais Brazil Centre for Ocean Energy Research Department of Electronic Engineering Maynooth University Ireland Youth Research Institute Saint Petersburg Electrotechnical University "LETI" Russia

In this paper, a novel method to calculate the positive largest Lyapunov exponent (LLE) using only SPICE-like programs is presented. The LLE is calculated directly from systems that are represented in schematic circuits. The method is inspired by interval extensions, which exploits divergent trajectories to calculate the lower bound error. The exponent is calculated from the slope of the line derived from the lower bound error. A differential amplifier is used to quantify this exponent along with a straightforward linear fit to the logarithm of the divergence of two pseudo circuits’ trajectories. The method is simple and different from the majority of other approaches, user-skills required relies only on SPICE-like programs. Results demonstrate that the suggested method has successfully estimated the LLE for six well-known systems. © 2023, The Authors. All rights reserved.

关键词： SPICE

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Detection of lactate in human sweat via surface-modified, screen-printed carbon electrodes

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Talanta 2023年 265卷 124888页

作者： Kumar, Nitish Lin, Yi-Jie Huang, Yu-Chiao Liao, Yu-Te Lin, Shu-Ping Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung40227 Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan

Real-time and continuous monitoring of lactate levels in sweat has been used as an indicator of physiological information to evaluate exercise outcomes and sports performance. We developed an optimal enzyme-based biosensor to detect the concentrations of lactate in different fluids (i.e., a buffer solution and human sweat). The surface of the screen-printed carbon electrode (SPCE) was first treated with oxygen plasma and then surface-modified by lactate dehydrogenase (LDH). The optimal sensing surface of the LDH-modified SPCE was identified by Fourier transform infrared spectroscopy and electron spectroscopy for chemical analysis. After connecting the LDH-modified SPCE to a benchtop E4980A precision LCR meter, our results showed that the measured response was dependent on the lactate concentration. The recorded data exhibited a broad dynamic range of 0.1–100 mM (R2 = 0.95) and a limit of detection of 0.1 mM, which was unachievable without the incorporation of redox species. A state-of-the-art electrochemical impedance spectroscopy (EIS) chip was developed to integrate the LDH-modified SPCE for a portable bioelectronic platform in the detection of lactate in human sweat. We believe the optimal sensing surface can improve the sensitivity of lactate sensing in a portable bioelectronic EIS platform for early diagnosis or real-time monitoring during different physical activities. © 2023

关键词： Electrochemical impedance spectroscopy

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Performance Analysis of OFDM-IM Systems over Generalized $\kappa-\mu$ and $\eta-\mu$ Fading Channels

Performance Analysis of OFDM-IM Systems over Generalized $\k...

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International Conference on Next Generation Intelligent Systems (ICNGIS)

作者： Mustafa Lafci Busra Ceniklioglu Ayse Elif Canbilen Ibrahim Develi Graduate School of Natural and Applied Sciences Erciyes University Kayseri Turkey Electrical and Electronics Engineering Department Nuh Naci Yazgan University Kayseri Turkey Electrical and Electronics Engineering Department Konya Technical University Konya Turkey Electrical and Electronics Engineering Department Erciyes University Kayseri Turkey

In this paper, average bit error rate (ABER) performance of an orthogonal frequency division multiplexing with index modulation (OFDM-IM) system, which is a strong transmission technology candidate for next-generation networks, has been analyzed over generalized fading models, namely eta-mu $(\eta-\mu)$ and kappa-mu $(\kappa-\mu)$ fading channels. These models have the advantage of simple algebraic notation, line-of-sight (LOS) and non-line-of-sight (NLOS) propagation effects. The $\kappa-\mu$ fading channel model is a LOS distribution, that includes the Nakagami-m and the Rice (Nakagami-n) distributions. Similarly, the special cases of $\eta-\mu$ fading channel model are Hoyt, Rayleigh, Nakagami-m and One-sided Gaussian distributions. The effect of $\eta-\mu$ and $\kappa-\mu$ fading channel characteristics on the ABER performance of OFDM-1M systems was shown via computer simulations.

关键词： Fading channels Productivity Measurement Analytical models Computational modeling OFDM Modulation

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Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains

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Computational and Structural Biotechnology Journal 2024年 23卷 1864-1876页

作者： Do, Duyen Thi Yang, Ming-Ren Vo, Tran Nam Son Le, Nguyen Quoc Khanh Wu, Yu-Wei Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Business Administration College of Management Lunghwa University of Science and Technology Taoyuan City Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan TMU Research Center for Digestive Medicine Taipei Medical University Taipei Taiwan

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR. © 2024 The Authors

关键词： Genes

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Important Ways in Designing Vocational Secondary School Teacher Development Education and Training 3

Important Ways in Designing Vocational Secondary School Teac...

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3rd International Conference on electrical, electronics, Informatics, and Vocational Education, ICE-ELINVO 2020

作者： Kholis, N. Supriyadi, E. Mardapi, D. Electrical Engineering Education Department Faculty of Engineering Yogyakarta State University Yogyakarta Indonesia Educational Research and Evaluation Study Program Graduate School Yogyakarta State University Yogyakarta Indonesia

A mid-level labor preparation having the qualification and competency appropriate with working world needs is a task from vocational secondary school (VSS). Now days, VSS become an attention by wide community, as a result of the existence of government policy which is trying to empowering vocational secondary education. The policy taken is by performing the revitalization of vocational school which has the aim to improve the quality of labor competitiveness. One of the programs is teacher quality improvement through various teacher training. However, relating to this case, it is suspected that the previous vocational school teacher training is less effective, so that it needs to be conducted the analysis about the teacher training implementation. Therefore, this article will be elaborated the ways needed to be conducted in improving the educational quality and vocational school teacher development training. The ways should be considered when it is planned and implemented the effective training program, such as: determining the needs, setting the goal, determining the content of learning, selecting the participants, determining the best schedule, selecting the appropriate facilities, selecting the proper instructor, selecting and preparing the audiovisual equipment, coordinating the program and evaluating the program. © 2021 Published under licence by IOP Publishing Ltd.

关键词： Personnel training

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Adaptive Antenna Selection for Two-Hop Full-Duplex UAV Relay Networks

Adaptive Antenna Selection for Two-Hop Full-Duplex UAV Relay...

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IEEE International Conference on Consumer electronics-Taiwan (ICCE-TW)

作者： Takumu Uda Takahiro Matsuda Takefumi Hiraguri Graduate School of Systems Design Tokyo Metropolitan University Tokyo Japan Department of Electrical Electronics and Communication Engineering Nippon Institute of Technology Saitama Japan

In unmanned aerial vehicle (UAV) relay networks, the throughput performance is influenced by wind perturbations. We consider a two-hop full-duplex UAV relay network using maximum ratio combining multiple-input multiple-output (MIMO) data transmission and propose an adaptive antenna selection scheme to improve the robustness against these perturbations. As the links with shorter distances are more influenced by the perturbations, we adjust beamwidths of the source-relay and relay-destination links by selecting antenna elements of the nodes according to the distances between neighboring nodes.

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Modified Turnstile Antenna Design for Multi-Band and Broadband Applications

Modified Turnstile Antenna Design for Multi-Band and Broadba...

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USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)

作者： I-Fong Chen Chia-Mei Fei-Lung Wu Jian-An Xie Dept. of Computer and Communication School of Electronics and Electrical Engineering Dongguan Polytechnic Jinwen University of Science and Technology New Taipei City Taiwan Department of Communications Engineering Feng Chia University Taichung City Taiwan Ph.D. Program of Electrical and Communications Engineering Feng Chia University Taichung City Taiwan

ISBN: (数字)9789463968119

ISBN: (纸本)9798350359497

The proposed antenna with a size of 90 mm x 90 mm, and the ground portion is 64 mm x 64 mm, which material is FR4 glass epoxy substrate with the thickness of 1.6 mm, relative permittivity of 4.3 and loss tangent of 0.023, consists of four modified dipole elements and four power dividers, as shown in Figure. 1. For the multi-band and broadband operation, three dipole antennas were shunted to be a dipole element. The electrical-length of the dipole element can be determined from the one quarter-wave length at the 2.45 GHz, 5.5 GHz and 6.525 GHz, for covering 2400 MHz-2500 MHz, 5150 MHz-5850 MHz and 5925 MHz-7125 MHz. In order to operates in various modes such as normal mode and axial mode, the modified four port triple-band microstrip series power divider was designed. In normal mode, it radiates horizontally polarized waves where as in axial mode, it radiates circularly polarized waves. The radiated patterns of the proposed antenna as shown in Figure. 2. The features of the proposed antenna are shown in the Table I. Impressive radiated gains and efficiencies are obtained.

关键词： Power dividers Dipole antennas Conferences Glass Broadband communication Broadband antennas Microstrip

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Design of an Advanced System-on-Chip Architecture for Chaotic Image Encryption

Design of an Advanced System-on-Chip Architecture for Chaoti...

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Symposium on Integrated Circuits and Systems Design (SBCCI)

作者： Arthur M. Lima Lucas G. Nardo Erivelton Nepomuceno Janier Arias-Garcia Jones Yudi Graduate Program in Mechatronic Systems University of Brasília Brasília Brazil Graduate Program in Electrical Engineering Federal University of Minas Gerais Belo Horizonte Brazil Department of Electronic Engineering Center for Ocean Energy Research Maynooth University Maynooth reland Department of Electronic Engineering Federal University of Minas Gerais Belo Horizonte Brazil Department of Mechanical Engineering University of Brasília Brasília Brazil

With the rise of interconnected systems, security has become a crucial concern. As a result, there has been a growing interest in developing low-cost embedded cryptographic algorithms that are lightweight and can be integrated into System-on-Chip (SoC) devices. Digital chaotic systems have emerged as a promising approach for building secure communication systems, where various cryptosystems utilize chaotic dynamics to encrypt images into noise-like representations. Recent studies have demonstrated that finite-precision error can be used to derive chaos, which can be systematically applied to encrypt images. However, there is a lack of research on how SoC-based design constraints affect the overall performance of image encryption systems, especially for applications that are sensitive to latency. This study aims to address this gap by presenting an efficient architecture that explores a hardware/software co-design for image encryption based on finite-precision error, specifically designed for resource-limited devices and latency-sensitive applications. Our platform performs the capture and encryption of images with a size of 320 × 240. Using a benchmark image, results show that the developed cryptosystem architecture can encrypt images efficiently while offering low hardware occupation.

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Graph Neural Networks for the Offline Nanosatellite Task Scheduling Problem

arXiv

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arXiv 2023年

作者： Pacheco, Bruno Machado Seman, Laio Oriel Rigo, Cezar Antônio Camponogara, Eduardo Bezerra, Eduardo Augusto dos Santos Coelho, Leandro Florianópolis Brazil Florianópolis Brazil Department of Electrical Engineering Federal University of Parana Curitiba Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil

This study investigates how to schedule nanosatellite tasks more efficiently using Graph Neural Networks (GNNs). In the Offline Nanosatellite Task Scheduling (ONTS) problem, the goal is to find the optimal schedule for tasks to be carried out in orbit while taking into account Quality-of-Service (QoS) considerations such as priority, minimum and maximum activation events, execution time-frames, periods, and execution windows, as well as constraints on the satellite’s power resources and the complexity of energy harvesting and management. The ONTS problem has been approached using conventional mathematical formulations and exact methods, but their applicability to challenging cases of the problem is limited. This study examines the use of GNNs in this context, which has been effectively applied to optimization problems such as the traveling salesman, scheduling, and facility placement problems. More specifically, we investigate whether GNNs can learn the complex structure of the ONTS problem with respect to feasibility and optimality of candidate solutions. Furthermore, we evaluate using GNN-based heuristic solutions to provide better solutions (w.r.t. the objective value) to the ONTS problem and reduce the optimization cost. Our experiments show that GNNs are not only able to learn feasibility and optimality for instances of the ONTS problem, but they can generalize to harder instances than those seen during training. Furthermore, the GNN-based heuristics improved the expected objective value of the best solution found under the time limit in 45%, and reduced the expected time to find a feasible solution in 35%, when compared to the SCIP (Solving Constraint Integer programs) solver in its off-the-shelf configuration. © 2023, CC BY-NC-ND.

关键词： Energy harvesting

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