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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Karam, Lina Zissis, Georges Yao, Jason Nelson, Jill Jo, Minho Sliz, Rafal Nogueira, Michele Watkins, Steve Wang, Huihui School of Electrical Computer and Energy Engineering Arizona State University TempeAZ United States Univestité Toulouse Iii - Paul Sabatier Science and Engineering Toulouse France East Carolina University Department of Engineering GreenvilleNC United States George Mason University Department of Electrical and Computer Engineering FairfaxVA United States Korea University Department of Computer Convergence Software Sejong City Korea Republic of University of Oulu Optoelectronics and Measurement Techniques Unit Oulu90570 Finland Federal University of Minas Gerais Department of Computer Science MG Belo Horizonte Brazil Missouri University of Science and Technology Department of Electrical and Computer Engineering RollaMO United States St. Bonaventure University Department of Computer Science and Cybersecurity St. Bonaventure United States

ISBN: (纸本)9798350336429

This faculty leadership panel will be held jointly by the IEEE Education Society (IEEE EdSoc) and IEEE Educational Activities Board (EAB) Faculty Resources Committee (FRC). The panel intends to provide participants introductory knowledge and skills. Two moderators and four panelists will focus on discussing their various academic leadership experiences and practices. The panel will be held in an interactive way so that the participants will have enough time to ask questions or communicate with the panelists. It is expected that this joint panel may potentially help to build up networks and mentorships. © 2023 IEEE.

关键词： faculty leadership leadership knowledge leadership skills mentorship

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Design and Analysis of Deep Learning based Water Potability Prediction

Design and Analysis of Deep Learning based Water Potability ...

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2023 International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023

作者： Arumugam, M. Vijayakumar, P. Kannan, A.C. Velmurugan, J. Arun, G. Rohith Bhat, C. Kongu Engineering College Department of Computer Technology - Pg Perundurai India Kongu Engineering College Department of Master of Computer Applications Tamil Nadu Perundurai638060 India Psna College of Engineering and Technology Department of Electrical and Electronics Engineering Dindigul624622 India Erode Sengunthar Engineering College Department of Artificial Intelligence and Data Science Thuduppathi638057 India Saveetha School of Engineering Simats Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350300857

According to the United Nations, having access to clean water for consumption is a fundamental human right. General Assembly in 2010. The importance of safe drinking water cannot be overstated. Unsafe drinking water access is a significant public health concern, especially in poor nations. In many regions of the world, waterborne illnesses including cholera, typhoid fever, and dysentery are important causes of illness and death. These diseases are especially dangerous for children, who are more vulnerable to their effects. In addition, a lack of access to clean drinking water can result in other health issues like stunted growth and malnutrition. Access to safe drinking-water is also a key component of effective policy for health protection at all levels, whether it is at the national, regional, or local level. Policies aimed at improving access to safe drinking-water can include measures such as water quality testing, water treatment, and the provision of clean water sources. Investments in water supply and sanitation can have a positive economic impact, especially in areas with inadequate access to clean drinking water. The costs of implementing the treatments may be outweighed by the reductions in unfavorable health impacts and medical expenses that may result from these investments. In conclusion, having access to clean drinking water is crucial for encouraging wellness, reducing waterborne illnesses, and raising standard of living in general. The input to the DNN could be the various water quality parameters, such as pH, hardness, chloride content, and total dissolved solids, while the output would be a binary classification indicating whether the water is potable or not. The DNN would need to be trained on a large and diverse dataset of water samples to accurately classify new samples. © 2023 IEEE.

关键词： Potable water

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Nanoimprint lithography-assisted block copolymer self-assembly for hyperfine fabrication of magnetic patterns based on L10-FePt nanoparticles

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science China Chemistry 2025年第5期68卷 2027-2034页

作者： Jie Zhang Yi Chen Guijun Li Zelin Sun Zhengong Meng Wai-Yeung Wong Department of Applied Biology and Chemical Technology and Research Institute for Smart Energy The Hong Kong Polytechnic University The Hong Kong Polytechnic University Shenzhen Research Institute Division of Integrative Systems and Design and Department of Electronic and Computer EngineeringThe Hong Kong University of Science and Technology School of Flexible Electronics (Future Technology) and Institute of Advanced Materials (IAM) Nanjing Tech University

L10-FePt-type bit-patterned media has provided a promising alternative for ultrahigh-density magnetic recording systems in the current digital era, but rapid fabrication of magnetic patterns with hyperfine bit islands is still challenging, especially with the target for miniaturization and scalable production simultaneously. Herein, Fe,Pt-containing block copolymers were utilized as single-source precursors for solution-processable patterning and subsequent generation of the demanding magnetic FePt dots by in situ pyrolysis. High-throughput nanoimprint lithography was initially employed to fabricate the predefined bit cells precisely,and then the intrinsic self-assembly of phase-separated block copolymers further drove the formation of accurate bit *** from the synergistic effect of top-down lithographic approach and bottom-up self-assembly, the customizable patterns could be achieved for large-scale mass production in targeted areas, but high-density isolated dots could also be accurately aligned along the patterned features after subsequent self-assembly. This reliable strategy would provide a good avenue to precisely construct ultrahigh-density magnetic data storage devices.

关键词： organometallic precursor magnetic nanoparticles block copolymer self-assembly nanoimprint lithography

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Terahertz squeezed light and self-pulsing in semiconductor lasers with nonlinear loss

Terahertz squeezed light and self-pulsing in semiconductor l...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Pontula, Sahil Sloan, Jamison Rivera, Nicholas Soljačić, Marin Department of Physics MIT CambridgeMA United States Department of Electrical Engineering and Computer Science MIT CambridgeMA United States Department of Physics Harvard CambridgeMA United States

We show how the combination of dispersive outcoupling and Kerr nonlinearity in semiconductor lasers creates regimes of self-pulsing and intensity-squeezed states of light from optical to terahertz wavelengths. © ... 详细信息

关键词： Semiconductor lasers

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Improving Resources in Internet of Vehicles Transportation Systems Using Markov Transition and TDMA Protocol

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IEEE Transactions on Intelligent Transportation Systems 2023年第11期24卷 13050-13067页

作者： Miri, Farimasadat Javadpour, Amir Ja'Fari, Forough Sangaiah, Arun Kumar Pazzi, Richard Faculty of Business and Information Technology OshawaL1H 7K4 Canada Harbin Institute of Technology Department of Computer Science and Technology Shenzhen150001 China Instituto Politécnico de Viana Do Castelo ADiT-Lab Electrical and Telecommunications Department Viana do Castelo4900-347 Portugal Sharif University of Technology Department of Computer Engineering Tehran14588-89694 Iran National Yunlin University of Science and Technology International Graduate Institute of Ai Yunlin64002 Taiwan Lebanese American University Department of Electrical and Computer Engineering Byblos1102 Lebanon

In today's world, interconnected Vehicular ad-hoc networks (VANET) and intelligent transportation systems have become more popular. Although IoV can bring many benefits for the smart cities and provide comforts for the passengers, however, the increasing needs for keeping the QoS and QoE at an acceptable level in time sensitive applications seems crucial and needs to be investigated deeply. Also, allocating the right number of resources to avoid congestions and fill the deficiencies in a distributed manner is a challenging issue. So, with the increase in users, attention must be given to Quality of Service (QoS) and resource allocation. As the vehicle network provides information to provide safety, comfort, and entertainment to drivers and passengers, they are one of the most compelling research topics in intelligent transportation systems. TDMA protocol is used in this study to increase the efficiency of the network and the quality of service it provides. To solve the synchronization problem, the Markov method predicts the size of slots and frames. The scenario field is used in the Markov application section to better predict TDMA gaps on solving the synchronization problem. Accordingly, the higher the quality of service, the lower the latency of the network, and the better the allocation of resources. Optimizing allocation and quality of service is further motivated by reducing collision between packets. In terms of its implementation, this method is divided into two components, the first being the database proposal for constructing the Markov matrix and the second being the simulation on VanetMobisim and implementation of the network in NS2. The proposed method performed better in different scenarios in terms of computational complexity, PDF, latency, and overhead, as shown in the results section. © 2000-2011 IEEE.

关键词： Quality of service

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Supervised learning applied to electrocardiogram statistical features for the detection of premature ventricular contraction

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Research on Biomedical engineering 2025年第1期41卷 1-12页

作者： Issa, Khouloud Rammal, Abbas Assaf, Rabih Ghandour, Ahmad Electrical and Communication Engineering Department College of Engineering Phoenicia University Zahrani South Lebanon Statistics and Informatics Department Faculty of Science Lebanese University Beirut Lebanon Mathematics and Computer Sciences Department Faculty of Arts and Sciences Lebanese American University Beirut Lebanon Department of Mathematics Faculty of Arts and Sciences Holy Spirit University of Kaslik Jounieh Lebanon Biomedical Engineering Department Faculty of Engineering Islamic University of Lebanon Wardenieh30014 Lebanon

Purpose: The development of an automated premature ventricular contraction (PVC) detection system has significant implications for early intervention and treatment decisions. This study aims to develop a novel approach using various supervised machine learning (ML) methods for detecting PVCs in electrocardiogram (ECG) recordings. Methodology: To achieve this, we extracted ten distinct statistical and temporal features from 33 long-term ECG recordings from the benchmark MIT-BIH arrhythmia database (MIT-BIH-AD), capturing significant characteristics from the signals. We then investigated the effectiveness of traditional ML algorithms in identifying PVCs based on these features, namely support vector machine (SVM), decision tree (DT), naïve Bayes (NB), k-nearest neighbor (KNN), linear discriminant analysis (LDA), and artificial neural network (ANN). Results: Among these classifiers, the SVM, KNN, ANN, and DT classifiers demonstrated exceptional discriminatory power and classification performance, yielding near-perfect area under the receiver operating characteristic curve (AUC-ROC) values of 97.3%, 95.4%, 95%, and 94.1%, respectively. On the other hand, the SVM classifier emerged as the most accurate, achieving an overall accuracy of 97.39%, indicative of making correct predictions. Conclusion: These findings underscore the generalization of the proposed approach, especially since we worked on an extended dataset encompassing different types of heartbeats to discriminate PVCs from other heartbeat types, not only normal ones, and providing closer alignment with real-world scenarios. Subsequently, the robustness and accuracy of these models highlight their suitability for clinical applications and their potential for efficient implementation and deployment in the diagnosis of cardiovascular diseases (CVDs), as they demand minimal computational resources and time. © The Author(s), under exclusive licence to The Brazilian Society of Biomedical engineering 2025.

关键词： Decision trees

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Efficient Deep Post-Decision State Learning for Privacy-Conscious Offloading in MEC-Enabled 6G Networks 1

Efficient Deep Post-Decision State Learning for Privacy-Cons...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Saeed, Mamoon M. Mokhtar, Rania A. Elbasheir, Mohammed S. Ali, Elmustafa Sayed Ahmed, Zeinab E. Ahmed, Mayada A. Yemen Faculty of Engineering School of Elecs Eng. Sudan University of Science and Technology Khartoum Sudan School of Electronic Engineering Sudan University of Science and Technology Khartoum Sudan Department of Electrical & Electronic Engineering Faculty of Engineering Red Sea University Sudan Department of Electrical and Computer International Islamic University Malaysia

ISBN: (纸本)9798331533557

With the growing demand for data-intensive applications, offloading tasks to multi-access edge computing (MEC) servers has become essential. However, privacy concerns arise as sensitive data is transmitted to remote servers. To address this, the proposed method uses deep learning techniques to intelligently analyze and classify data packets, ensuring that only non-sensitive information is offloaded. This paper proposes a novel approach called a deep post-decision state (PDS) learning privacy-concerned offloading in MEC-enabled 6G Environments. A Post-Decision State (PDS) approach that selectively selects data packets while maintaining privacy is used to train the deep learning model. The suggested method successfully balances the trade-off between increasing system performance and safeguarding user privacy to achieve privacy-aware offloading in MEC-enabled 6G networks, as shown by the experimental findings. Also, it performs noticeably better than the traditional DQN, according to simulation data. © 2024 IEEE.

关键词： Adversarial machine learning

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An Efficient Method for Quantifying the Aggregate Flexibility of Plug-In Electric Vehicle Populations

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IEEE Transactions on Smart Grid 2024年第4期16卷 1-1页

作者： Taha, Feras Al Vincent, Tyrone Bitar, Eilyan School of Electrical and Computer Engineering Cornell University Ithaca NY USA Department of Electrical Engineering and Computer Science Colorado School of Mines Golden CO USA

Plug-in electric vehicles (EVs) are widely recognized as being highly flexible electric loads that can be pooled and controlled via aggregators to provide low-cost energy and ancillary services to wholesale electricity markets. To participate in these markets, an aggregator must encode the aggregate flexibility of the population of EVs under their command as a single polytope that is compliant with existing market rules. To this end, we investigate the problem of characterizing the aggregate flexibility set of a heterogeneous population of EVs whose individual flexibility sets are given as convex polytopes in half-space representation. As the exact computation of the aggregate flexibility set—the Minkowski sum of the individual flexibility sets—is known to be intractable, we study the problem of computing maximum-volume inner approximations to the aggregate flexibility set by optimizing over affine transformations of a given convex polytope in half-space representation. We show how to conservatively approximate these set containment problems as linear programs that scale polynomially with the number and dimension of the individual flexibility sets. The inner approximation methods provided in this paper generalize and improve upon existing methods from the literature. We illustrate the improvement in approximation accuracy and performance achievable by our methods with numerical experiments. IEEE

关键词： Aggregates

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OSAP‐Loss:Efficient optimization of average precision via involving samples after positive ones towards remote sensing image retrieval

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1191-1212页

作者： Xin Yuan Xin Xu Xiao Wang Kai Zhang Liang Liao Zheng Wang Chia‐Wen Lin School of Computer Science and Technology Wuhan University of Science and TechnologyWuhanChina Hubei Province Key Laboratory of Intelligent Information Processing and Real‐time Industrial System Wuhan University of Science and TechnologyWuhanChina Nanyang Technological University SingaporeSingapore School of Computer Science Wuhan UniversityWuhanChina Department of Electrical Engineering Industrial Technology Research InstituteNational Tsing Hua UniversityHsinchuChina

In existing remote sensing image retrieval(RSIR)datasets,the number of images among different classes varies dramatically,which leads to a severe class imbalance *** studies propose to train the model with the ranking‐based metric(e.g.,average precision[AP]),because AP is robust to class ***,current AP‐based methods overlook an important issue:only optimising samples ranking before each positive sample,which is limited by the definition of AP and is prone to local *** achieve global optimisation of AP,a novel method,namely Optimising Samples after positive ones&AP loss(OSAP‐Loss)is proposed in this ***,a novel superior ranking function is designed to make the AP loss differentiable while providing a tighter upper ***,a novel loss called Optimising Samples after Positive ones(OSP)loss is proposed to involve all positive and negative samples ranking after each positive one and to provide a more flexible optimisation strategy for each ***,a graphics processing unit memory‐free mechanism is developed to thoroughly address the non‐decomposability of AP *** experimental results on RSIR as well as conventional image retrieval datasets show the superiority and competitive performance of OSAP‐Loss compared to the state‐of‐the‐art.

关键词： computer vision image retrieval metric learning

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Game theory-based attack and defense analysis in virtual wireless networks with jammers and eavesdroppers

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Digital Communications and Networks 2021年第3期7卷 327-334页

作者： Bassma S.Alsulami Chandra Bajracharya Danda B.Rawat Department of Electrical Engineering and Computer Science Howard UniversityWashingtonDC20059USA Department of Electrical Engineering Capitol Technology UniversityLaurelMD20708USA

Dynamic spectrum sharing and cognitive radio networks were proposed to enhance the Radio Frequency(RF)spectrum ***,there are several challenges to realize them in real systems,such as sensing uncertainty causing issues to licensed users,business models for licensed service *** virtualization is regarded as a technology that leverages service level agreements to sublease unused or underutilized RF spectrum that addresses aforementioned issues and helps to significantly enhance the utilization of the RF spectrum,offer improved coverage and capacity of networks,enhance network security and reduce energy *** wireless virtualization,wireless networks'physical substrate is shared and reconfigured dynamically between virtual wireless networks through Mobile Virtual Network Operations(MVNOs).Wireless virtualization with dynamic configurable features of Wireless Infrastructure Providers(WIPs),virtualized wireless networks are vulnerable to a multitude of attacks,including jamming attacks and eavesdropping *** paper investigates a means of defense through the employment of coalition game theory when jammers try to degrade the signal quality of legitimate users,and eavesdroppers aim to reduce secrecy ***,we consider a virtual wireless network where MVNO users'job is to improve their Signal to Interference plus Noise Ratio(SINR)while the jammers target to collectively enhance their Jammer Received Signal Strength(JRSS),and an eavesdropper's goal is to reduce the overall secrecy *** results have demonstrated that the proposed game strategies are effective(in terms of data rate,secrecy rate and latency)against such attackers compared to the traditional approaches.

关键词： Game theory based security Virtual wireless networks Jamming and eavesdropping

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