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31st Symposium of Advanced Database systems, SEBD 2023

作者： Mahmood, Tariq Hashemi, Seyedeh Khadijeh Mirtaheri, Seyedeh Leili Greco, Sergio Department of Computer Science Modeling Electronics and Systems Engineering University of Calabria Italy Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran

Credit cards became one of the most popular payment methods as technology advanced and e-commerce services expanded, resulting in an increase in the volume of banking transactions. Furthermore, the significant increase in the number of frauds necessitates high banking transaction costs. As a result, detecting fraudulent activities has become an intriguing topic, attracting a large number of researchers. We consider the use of class weight-tuning hyperparameters to control the weight of fraudulent and legitimate transactions in this study. We use Bayesian optimization, in particular, to optimize the hyperparameters while taking into account practical issues such as unbalanced data. We propose weight-tuning as a pre-process for unbalanced data, as well as using CatBoost and XGBoost to improve the performance of the LightGBM method by taking the voting mechanism into account. Finally, we use deep learning to fine-tune the hyperparameters, particularly our proposed weight-tuning one, in order to improve performance even further. We conducted some experiments to evaluate the proposed methods on real-world data. We use recall-precision metrics in addition to the common ROC-AUC to better cover unbalanced datasets. We use a 5-fold cross-validation method to test CatBoost, LightGBM, and XGBoost separately. Furthermore, the performance of the combined algorithms is evaluated using the majority voting ensemble learning method. According to the results, LightGBM and XGBoost achieve the best level criteria of ROC-AUC = 0.95, precision 0.79, recall 0.80, F1 score 0.79, and MCC 0.79. Also, by using deep learning and the Bayesian optimization method to tune the hyperparameters, we meet the following criteria: ROC-AUC = 0.94, precision = 0.80, recall = 0.82, F1 score = 0.81, and MCC = 0.81. This is a big improvement over the state-of-the-art methods we compared it to. © 2023 CEUR-WS. All rights reserved.

关键词： Learning systems

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Sampling and Quantization-Aware Control Barrier Functions for Safety-Critical Control of Cyber-Physical systems 63

Sampling and Quantization-Aware Control Barrier Functions fo...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Niu, Luyao Ramasubramanian, Bhaskar Clark, Andrew Poovendran, Radha University of Washington Department of Electrical and Computer Engineering SeattleWA United States Western Washington University Electrical and Computer Engineering BellinghamWA United States Washington University in St. Louis Department of Electrical and Systems Engineering St. LouisMO United States

ISBN: (纸本)9798350316339

Safety is critical to a wide range of cyber-physical systems (CPS). Safety violations may damage CPS and cause harm to humans that co-exist in the operating environment. However, it is nontrivial to guarantee safety of complex CPS whose computation and control workload are shifted to the cloud. The reason is that the system states which evolve continuously are sampled periodically and quantized before being sent to the controller to compute control inputs. Moreover, the controller may operate with finite precision, making the coefficients involved in computation different from those of the actual system. Consequently, the synthesized control inputs to the system may lead to safety violations. In this paper, we study the co-design of quantizer and control inputs for such CPS. We construct a control barrier function (CBF) constraint for the digital controller and analyze how it differs from the CBF constraint formulated using the actual system states and dynamics. We observe that this difference is dependent on the sampling error, quantization error, and error induced by finite precision of the controller. We derive upper bounds of these errors and use the bounds to design a state quantizer. We show that the problem of designing a quantizer can be converted to a facility location problem. We prove the submodularity of the quantizer design problem, and leverage the submodularity property to develop an efficient greedy algorithm to construct the quantizer. Given the quantized states calculated by the quantizer, we modify the CBF constraint used by the controller to synthesize control inputs for the system at each sampling interval. We show that the synthesized inputs guarantee the system safety. We demonstrate the proposed approach using a numerical case study on a batch reactor system. © 2024 IEEE.

关键词： Control system synthesis

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A High-Efficiency, Indirectly-Fed, Dual Moon-Shaped Printed Antenna for Measuring Sand Gradation 7

A High-Efficiency, Indirectly-Fed, Dual Moon-Shaped Printed ...

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7th IEEE International Symposium on Telecommunication Technologies, ISTT 2024

作者： Abbas, Mohammed K. Hammed, Raaed T. Salim, Ali J. Sali, Aduwati University of Technology Department of Electrical Engineering Baghdad Iraq University of Technology Department of Communication Engineering Baghdad Iraq Department of Computer and Communication Systems Engineering Selangor Serdang43400 Malaysia

ISBN: (纸本)9798350392074

In this paper, an enhanced bandwidth antenna featuring a dual moon-shaped patch design is presented. The antenna occupies an area of 153 mm by 130 mm and operates within the frequency band of 0.69 to 1.19 GHz. The structure is printed on an FR4 substrate with a dielectric constant of 4.3 and a substrate thickness of 1.5 mm. It achieves a bandwidth of 0.5 GHz (50%) and a minimum return loss of-47 dB at the resonant frequency of 1.00 GHz, with a gain of 4.02 dB. The proposed antenna consists of a dual moon-shaped patch positioned on the top of the dielectric substrate. It utilizes an indirect feeding method via a transmission line with two arms to enhance bandwidth. The ground plane is partially reduced, which allows the antenna to resonate at a lower frequency. Additionally, a triangular slot on the backside improves impedance matching from-15dB to-47dB, thus optimizing the electric size. Experimental results confirm the antenna's performance, showing excellent agreement with the predicted parameters. The antenna demonstrates robust performance with effective gain and high bandwidth, making it suitable for practical applications in infrastructure monitoring. An innovative method for measuring sand gradation on-site is being developed by voltage network analyzer Device, eliminating the need for traditional sieve analysis in the laboratory. © 2024 IEEE.

关键词： Microstrip antennas

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Guest Editorial Special Issue on Self-Powered Sensors and Wearable Electronic systems

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2024年第4期3卷 118-119页

作者： Nag, Anindya Ozioko, Oliver Kim, Woo Soo Andrews, Joseph Technische Universität Dresden Faculty of Electrical and Computer Engineering Dresden01062 Germany Dresden01069 Germany University of Derby Department of Electrical and Electronic Engineering DerbyDE22 1GB United Kingdom Simon Fraser University School of Mechatronic Systems Engineering BurnabyBCV5A 1S6 Canada University of Wisconsin-Madison Department of Mechanical Engineering and Department of Electrical and Computer Engineering MadisonWI53706 United States

Wearable sensing has recently been highly preferred due to its quick and accurate measurement of physiological parameters. These sensors have been devised using various polymers [1], [2] and nanomaterials [3], [4] suited for the chosen application. With the exponential growth of wearable electronics [5], [6], [7], there is a need to broaden their capabilities in terms of functionality and availability. Commercializing these wearable electronics needs further encouragement to use these sensors as point-of-care devices. Self-powered sensors [8], [9] are one of the growing aspects in the sector of wearable sensing. With the growing requirement for energy usage, self-powered sensing systems need to be developed to generate and harvest energy ubiquitously [10], [11]. This Special Issue highlights some of the published papers that work on using smart textiles and self-powered devices for efficient and sustainable sensing applications. © 2022 IEEE.

关键词： Wearable sensors

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Control of Grid-Connected Inverters Using PLL for Synchronization and Harmonic Mitigation

Control of Grid-Connected Inverters Using PLL for Synchroniz...

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2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Yousefpour, Kamran Yousefpour, Mohammad Molla, Seyyed Javad Hosseini Andani, Mansour Taheri Varnousdaderani, Sepideh Alaei Andani, Hamid Taheri Mississippi State University Department of Electrical and Computer Engineering United States Azad University Iran Babol Noshirvani University of Technology Department of Electrical and Computer Engineering Iran School of Manufacturing Systems and Networks Arizona State University United States Azad University Department of Computer Engineeering Iran Isfahan University of Technology Department of Electronic Engineering Iran

ISBN: (纸本)9798331541125

This paper presents the design and simulation of a single-phase grid-connected inverter control system, focusing on enhancing power quality and dynamic performance. The control system comprises a resonant controller for real and reactive power regulation, ensuring sinusoidal current injection into the grid. Additionally, a Phase-Locked Loop (PLL) is incorporated to improve synchronization with the grid voltage, generating accurate reference signals for current control and mitigating harmonic disturbances. The PLL design leverages specific gain parameters, μ1,μ2, and μ3, optimized for a critically damped response. A comprehensive simulation study evaluates the system's performance under different conditions, including soft-start operation, transient power commands, and grid voltage distortion with low-order harmonics (Sth, 7th, LIth, and 13th). Results highlight the system's robust dynamic response, low total harmonic distortion (THD), and effective harmonic attenuation, demonstrating its suitability for grid-connected distributed energy resource (DER) applications. This work provides a scalable and reliable control framework for next-generation inverter systems operating in modern, complex grid environments. © 2025 IEEE.

关键词： Harmonic distortion

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Incentive Designs for Learning Agents to Stabilize Coupled Exogenous systems 63

Incentive Designs for Learning Agents to Stabilize Coupled E...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Certorio, Jair Martins, Nuno C. La, Richard J. Arcak, Murat Institute for Systems Research University of Maryland College Park Department of Electrical and Computer Engineering College ParkMD20740 United States University of California Department of Electrical Engineering and Computer Science BerkeleyCA94720 United States

ISBN: (纸本)9798350316339

We consider a large population of learning agents noncooperatively selecting strategies from a common set, influencing the dynamics of an exogenous system (ES) we seek to stabilize at a desired equilibrium. Our approach is to design a dynamic payoff mechanism capable of shaping the population's strategy profile, thus affecting the ES's state, by offering incentives for specific strategies within budget limits. Employing system-theoretic passivity concepts, we establish conditions under which a payoff mechanism can be systematically constructed to ensure the global asymptotic stability of the ES's equilibrium. In comparison to previous approaches originally studied in the context of the so-called epidemic population games, the method proposed here allows for more realistic epidemic models and other types of ESs, such as predator-prey dynamics. The stability of the equilibrium is established with the support of a Lyapunov function, which provides useful bounds on the transient states. © 2024 IEEE.

关键词： Lyapunov functions

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Liver Ailment Prediction Using Random Forest Model

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computers, Materials & Continua 2023年第1期74卷 1049-1067页

作者： Fazal Muhammad Bilal Khan Rashid Naseem Abdullah A Asiri Hassan A Alshamrani Khalaf A Alshamrani Samar M Alqhtani Muhammad Irfan Khlood M Mehdar Hanan Talal Halawani Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan City University of Science and Information Technology PeshawarPakistan Department of IT and Computer Science Pak-Austria Fachhochschule Institute of Applied Sciences and TechnologyHaripurPakistan Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia

Today,liver disease,or any deterioration in one’s ability to survive,is extremely common all around the *** research has indicated that liver disease is more frequent in younger people than in older *** the liver’s capability begins to deteriorate,life can be shortened to one or two days,and early prediction of such diseases is *** several machine learning(ML)approaches,researchers analyzed a variety of models for predicting liver disorders in their early *** a result,this research looks at using the Random Forest(RF)classifier to diagnose the liver disease early *** dataset was picked from the University of California,Irvine ***’s accomplishments are contrasted to those of Multi-Layer Perceptron(MLP),Average One Dependency Estimator(A1DE),Support Vector Machine(SVM),Credal Decision Tree(CDT),Composite Hypercube on Iterated Random Projection(CHIRP),K-nearest neighbor(KNN),Naïve Bayes(NB),J48-Decision Tree(J48),and Forest by Penalizing Attributes(Forest-PA).Some of the assessment measures used to evaluate each classifier include Root Relative Squared Error(RRSE),Root Mean Squared Error(RMSE),accuracy,recall,precision,specificity,Matthew’s Correlation Coefficient(MCC),F-measure,and *** has an RRSE performance of 87.6766 and an RMSE performance of 0.4328,however,its percentage accuracy is *** widely acknowledged result of this work can be used as a starting point for subsequent *** a result,every claim that a new model,framework,or method enhances forecastingmay be benchmarked and demonstrated.

关键词： Liver ailment random forest machine learning

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A hybrid machine-learning model for solar irradiance forecasting

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Clean Energy 2024年第1期8卷 100-110页

作者： Ameera M.Almarzooqi Maher Maalouf Tarek H.M.El-Fouly Vasileios E.Katzourakis Mohamed S.El Moursi Constantinos V.Chrysikopoulos Department of Industrial and Systems Engineering Khalifa UniversityAbu DhabiPO Box 127788UAE Electrical Engineering and Computer Science Department Khalifa University Abu DhabiUAE Department of Civil Infrastructure and Environmental Engineering Khalifa UniversityAbu DhabiPO Box 127788UAE School of Chemical and Environmental Engineering Technical University of CreteChaniaGreece

Nowcasting and forecasting solar irradiance are vital for the optimal prediction of grid-connected solar photovoltaic(PV)power *** plants face operational challenges and scheduling dispatch difficulties due to the fluctuating nature of their power *** the generation capacity within the electric grid increases,accurately predicting this output becomes increasingly essential,especially given the random and non-linear characteristics of solar irradiance under variable weather *** study presents a novel prediction method for solar irradiance,which is directly in correlation with PV power output,targeting both short-term and medium-term forecast *** proposed hybrid framework employs a fast trainable statistical learning technique based on the truncated-regularized kernel ridge regression *** proposed method excels in forecasting solar irradiance,especially during highly intermittent weather periods.A key strength of our model is the incorporation of multiple historical weather parameters as inputs to generate accurate predictions of future solar irradiance values in its scalable *** evaluated the performance of our model using data sets from both cloudy and sunny days in Seattle and Medford,USA and compared it against three forecasting models:persistence,modified 24-hour persistence and least *** on three widely accepted statistical performance metrics(root mean squared error,mean absolute error and coefficient of determination),our hybrid model demonstrated superior predictive accuracy in varying weather conditions and forecast horizons.

关键词： solar power generation kernel ridge regression hybrid model forecasting

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Explainability and Interpretability in Decision Trees and Agent Based Modelling When Approximating Financial Time Series. A Matter of Balance with Performance 8

Explainability and Interpretability in Decision Trees and Ag...

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8th International Conference on Computational Intelligence and Applications, ICCIA 2023

作者： Layfield, Colin Neri, Filippo University of Malta Department of Computer Information Systems Msida Malta University of Naples Department of Electrical and Computer Engineering Naples Italy

ISBN: (纸本)9798350339741

The paper discusses the notions of explainability and interpretability when using decision tree learning and agent based modeling to approximate financial time series. And how they related to the selected learning algorithm. As experimental context, the LFABS system for agent based modeling is used together with C4.5 for decision tree learning. The paper proposes the following definitions for interpretability: being able to make sense of a learning system output. And explainability: understanding how that output was generated. The study's goal is achieved by comparing the different knowledge representations used by the two systems. © 2023 IEEE.

关键词： Autonomous agents

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Assessing the Performance of AI-Generated Code: A Case Study on GitHub Copilot 35

Assessing the Performance of AI-Generated Code: A Case Study...

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35th IEEE International Symposium on Software Reliability engineering, ISSRE 2024

作者： Li, Shuang Cheng, Yuntao Chen, Jinfu Xuan, Jifeng He, Sen Shang, Weiyi Wuhan University School of Computer Science Wuhan China University of Arizona Department of Systems and Industrial Engineering Tucson United States University of Waterloo Department of Electrical and Computer Engineering Waterloo Canada

ISBN: (纸本)9798350353884

The integration of Large Language Models (LLMs) into software development tools like GitHub Copilot holds the promise of transforming code generation processes. While AI-driven code generation presents numerous advantages for software development, code generated by large language models may introduce challenges related to security, privacy, and copyright issues. However, the performance implications of AI-generated code remain insufficiently explored. This study conducts an empirical analysis focusing on the performance regressions of code generated by GitHub Copilot across three distinct datasets: HumanEval, AixBench, and MBPP. We adopt a comprehensive methodology encompassing static and dynamic performance analyses to assess the effectiveness of the generated code. Our findings reveal that although the generated code is functionally correct, it frequently exhibits performance regressions compared to code solutions crafted by humans. We further investigate the code-level root causes responsible for these performance regressions. We identify four major root causes, i.e., inefficient function calls, inefficient looping, inefficient algorithm, and inefficient use of language features. We further identify a total of ten sub-categories of root causes attributed to the performance regressions of generated code. Additionally, we explore prompt engineering as a potential strategy for optimizing performance. The outcomes suggest that meticulous prompt designs can enhance the performance of AI-generated code. This research offers valuable insights contributing to a more comprehensive understanding of AI-assisted code generation. © 2024 IEEE.

关键词： Software design

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