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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Feng, Ziliang Ramesh, Rahul Raman Ebrahimi, Seyyedmilad Jatskevich, Juri University of British Columbia Department of Electrical and Computer Engineering Vancouver Canada

ISBN: (纸本)9798350328202

Brushless DC (BLDC) motors are widely used in various applications today. The two commonly used control methods include the maximum torque per ampere (MTPA) control and maximum torque per volt (MTPV) control, which can be easily implemented through different advances in firing angle. However, both of those methods also have their limitations and drawbacks. The MTPA may not produce enough torque to satisfy operation requirements, especially during high-speed operation. The MTPV method, while capable of delivering higher torque, results in higher losses. This paper proposes a novel flux-weakening (FW) control strategy to enable the BLDC motors to operate within a higher speed range, produce sufficient torque, and minimize the magnitude of stator current. The proposed method applies the MTPA at low speeds, and at higher speeds or when high torque is required, it smoothly transitions to the FW region. The proposed method is demonstrated to have improved dynamic response, a wider speed/torque operating range, and higher efficiency (compared to MTPV). © 2024 IEEE.

关键词： Brushless DC motors

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Skin Disease Detection with Deep Learning

Skin Disease Detection with Deep Learning

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Ferdous, Jannatul Akib, Md. Arifur Rahman Mahzabeen, Fariah North South University Electrical and Computer Engineering Department Dhaka Bangladesh

ISBN: (纸本)9798350350821

Nowadays, skin diseases are very common due to increasing bacterial attack, fungal infection, UVB rays due to the depleting ozone layer. So, if we can take preventive measures from early on, then we can increase the rate of recovery. For early detection, we proposed a method that uses computer vision based techniques to detect three kinds of dermatological skin diseases. We have trained our CNN model with the dataset of eight types of diseases, those are Acne, Basal Cell Carcinoma, Rosacea, Nevus, Melanoma, Eczema, Actinic Keratosis and Seborrheic keratosis. The system successfully detects these eight diseases with an accuracy rate of 95% © 2024 IEEE.

关键词： Dermatology

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Impact of Rain on Frequency Bands in 4G/5G Networks: Implications for Industrial Connectivity 8

Impact of Rain on Frequency Bands in 4G/5G Networks: Implica...

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8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024

作者： Avanzato, Roberta Beritelli, Francesco Borzì, Maria Grazia University of Catania Department of Electrical Electronic and Computer Engineering Catania Italy

ISBN: (纸本)9798350362138

In recent years, there has been a growing interest in understanding how rain affects frequency bands in 4G/5G networks, especially in outdoor industrial environments. Most studies focus on the use of frequencies above 10 GHz, while few address this issue using frequencies typical of 4G/5G systems. This study investigates the effects of rain on band variation in 4G/5G mobile radio networks. In particular, by hypothesizing a value of eNBID, the number of times a band change occurs with and without rain was calculated. From these data, an increment factor (Δ F), normalized over time, was calculated to define the occurrence of band changes with and without rain. Two CNN network trainings were conducted with two different datasets, the first characterized by the absence of band variation information and the second characterized by the presence of such information. In the first case, an accuracy of about 75% was obtained, and in the second case, the obtained result was around 71%. These findings suggest that the addition of band variation information seems to be not relevant in terms of network performance. Finally, a CTGAN network was introduced for the generation of synthetic data for smaller classes, which resulted in an increase in performance of about 10%, reaching an average accuracy of 85% © 2024 IEEE.

关键词： 4G mobile communication systems

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An Adaptive Acoustic Transceiver Testbed on System-on-Chip for Underwater Communication

An Adaptive Acoustic Transceiver Testbed on System-on-Chip f...

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OCEANS 2024 - Halifax, OCEANS 2024

作者： Nges, Boris Bam Moore, Dylan Doucet, Andrew Bhattacharya, Ananya Alloway, Hunter Bousquet, Jean-Francois Dalhousie University Department of Electrical and Computer Engineering HalifaxNS Canada

ISBN: (纸本)9798331540081

This paper describes a test setup to support the development of a bi-directional acoustic communication link relying on adaptive transceivers. The physical layer relies on the JANUS protocol for discovery of new nodes and assessment of the channel conditions. The transmitter has a bandwidth of 5 kHz at a center frequency of 27.5 kHz, while the receiver relies on broadband hydrophones. The embedded system allows to transmit in diverse underwater scenarios, and the System-on-Chip is programmed to transmit various waveforms including through coded Orthogonal Frequency Division Multiplexing (OFDM). Key elements of the program are described to maintain real-time operation on the embedded systems. At the receiver, the data is sampled at 96 kHz and a 4 Mbps cabled link to a host interface is developed to diagnose the communication link reliability. © 2024 IEEE.

关键词： System-on-chip

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Impact of High-Frequency Repetitive Bipolar Square Wave Voltages on the Lifetime of Turn-to-Turn Insulation

Impact of High-Frequency Repetitive Bipolar Square Wave Volt...

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2024 IEEE Conference on electrical Insulation and Dielectric Phenomena, CEIDP 2024

作者： Rahman, Md Asifur Arafat, Easir Islam, Farzana Ghassemi, Mona Laboratory Department of Electrical and Computer Engineering RichardsonTX United States

ISBN: (纸本)9798350366679

Emerging power electronic drives and converters are planned to operate at high voltages with high switching frequencies (up to a few hundred kHz), which will affect the reliability of insulation systems of windings of electrical machines. To evaluate the insulation quality under such high-frequency pulses, lifetime test is a prominent way. For simplification of test procedure, turn-to-turn insulation samples are approved by IEC 60034-18-42. In past studies, the impact of switching frequencies has been investigated under lower frequencies (up to 20 kHz), which cannot address the challenges of next-generation wide bandgap (WBG)-based power converters. In this study, the lifetimes of turn-to-turn insulations under high switching frequencies (50 kHz) are tested at four different rise times (50 ns, 100 ns, 150 ns, 200 ns), and the impact of switching frequency on the lifetime of the insulation is analyzed. © 2024 IEEE.

关键词： Switching frequency

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A Comprehensive Comparison of Machine Learning Classification Techniques for Early Detection of Alzheimer's Disorder

A Comprehensive Comparison of Machine Learning Classificatio...

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2025 IEEE International Conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Vairale, Prathmesh Dubey, Vandana IES-IPS Academy Department of Computer Science and Engineering-AIML Indore452012 India IES-IPS Academy Department of Computer Science and Engineering Indore452012 India

ISBN: (纸本)9798331512965

Alzheimer's disorder (AlzD) is a chronic condition in which brain cells degenerate and eventually die. People over the age of 65 are most likely to get this condition. There is no cure for this, but nowadays proper medications and treatments are available to slow down the disease progression temporarily. Detection of AlzD in its early stage may help doctors and physicians provide proper medicines as early as possible to slow its development. Artificial intelligence is a blooming field in every sector nowadays that can help in AlzD detection to save us from time-consuming and expensive conventional methods. Various machine learning algorithms are researched to prevent AlzD. This paper uses different linear, distance, and tree-based supervised classifier algorithms. The used dataset contains different psychological parameters like a person's age, number of visits, Mini-Mental State Examination (MMSE), and years of education, on which machines can be trained to predict whether the person is demented or non-demented. The main goal of this research paper is to compare these classification algorithms which give the best result in the early detection of AlzD. RFC, KNN, and MLP algorithms outperform all other algorithms with an accuracy of 96.77%, followed by NB and LR algorithms with 95.70%. © 2025 IEEE.

关键词： Random forests

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Analysis and Design of Various Types of DC-DC Converters: A Comprehensive Study 21

Analysis and Design of Various Types of DC-DC Converters: A ...

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21st International Learning and Technology Conference, L and T 2024

作者： Salem, Nema Almatrafi, Lina Shigdar, Basmah Alaidaroos, Batool Effat University Electrical and Computer Engineering Department Jeddah Saudi Arabia

ISBN: (纸本)9798350393569

DC-DC converters are essential components in power electronics systems, enabling efficient voltage conversion and regulation. This paper presents a comprehensive study on the analysis and design of different types of DC-DC converter topology including Boost, Cuk, SEPIC, and Zeta converters. The design aspect of DC-DC converters covers the component selection to assist in achieving desired converter performance and meeting specific application requirements. The analysis focuses on examining key performance parameters such as efficiency, voltage ripple, transient response, and output regulation. To validate the theoretical analysis and design principles, simulation tools such as Simulink and MATLAB are employed. © 2024 IEEE.

关键词： MATLAB

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Resource Allocation in Cooperative NOMA: Opportunities and Challenges 3

Resource Allocation in Cooperative NOMA: Opportunities and C...

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3rd International Conference on Emerging Trends in electrical, Control, and Telecommunication engineering, ETECTE 2024

作者： Mushtaq, Uzma Baig, Sobia Department of Electrical and Computer Engineering COMSATS University Islamabad Lahore Pakistan

ISBN: (纸本)9798331504861

The radio access technology keeps users connected to communication networks anywhere and anytime in Fifth Generation and beyond wireless communication systems (b5G). Future radio access technologies incorporate major wireless communication system parameters, like huge data rates, massive connectivity, high energy efficiency, very low latency, etc. Hence, there is a need to bring revolutionary changes in the present radio access technologies (RATs). The employment of 5G and beyond technologies aim to provide better throughput, lower latency, excellent user connectivity and quality of service, and reliability. Non-orthogonal multiple access (NOMA) techniques are employed to allow users to share the same time-frequency blocks. NOMA can support huge data rates, massive connectivity and promises user fairness. The user capacity of NOMA can be enhanced by integrating it with the cooperative relay networks, that provide enhanced spectral efficiency, energy efficiency and user connectivity. This article presents the detailed review of resource allocation techniques in Cooperative NOMA (CNOMA) with discussion about the challenges in implementing CNOMA in multi-user communications system. ©2024 IEEE.

关键词： Cooperative communication

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Blockchain-Based Knowledge Repository for Training Artificial Intelligence Models: Bridging AIML with Decentralized Data

Blockchain-Based Knowledge Repository for Training Artificia...

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2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Das, Amit Kumar Tonoy, Md. Thouhedul Alam Hossain, Meherab Chandigarh University Department of Computer Engineering Mohali India United International University Department of Computer Science & Engineering Dhaka Bangladesh

ISBN: (纸本)9798350364866

This paper presents a Blockchain-Based Knowledge Repository (BBKR) tailored for the secure storage and management of training data crucial for Artificial Intelligence and Machine Learning (AIML) models. Leveraging Ethereum blockchain technology and smart contracts, the BBKR ensures data integrity, enhances security measures, and promotes decentralization principles. The proposed mechanism includes a detailed explanation of data validation processes, decentralized access control, and scalable transaction mechanisms. Our empirical evaluations validate the efficacy of BBKR in upholding data integrity, enhancing scalability, and fortifying security provisions. The results show significant improvements in data management performance compared to traditional centralized repositories. This research underscores the transformative potential of BBKR in revolutionizing AIML data management paradigms and offers a robust foundation for further advancements in the field. Future work will explore real-world applications and potential enhancements using advanced cryptographic techniques. © 2024 IEEE.

关键词： Artificial Intelligence and Machine Learning (AIML) Blockchain blockhain-Based Knowledge Repository (BBKR) Data integrity Decentralization Ethereum Security Smart Contracts Training data

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Exploring Alzheimer's disease:a comprehensive brain connectome-based survey

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Psychoradiology 2024年第1期4卷 43-57页

作者： Lu Zhang Junqi Qu Haotian Ma Tong Chen Tianming Liu Dajiang Zhu Department of Computer Science and Engineering The University of Texas at ArlingtonArlingtonTX 76019USA Department of Computer Science The University of GeorgiaAthensGA 30602USA

Dementia is an escalating global health challenge,with Alzheimer's disease(AD)at its *** evidence highlights the accumulation of AD-related pathological proteins in specific brain regions and their subsequent dissemination throughout the broader area along the brain network,leading to disruptions in both individual brain regions and their *** a comprehensive understanding of the neurodegeneration-brain network link is lacking,it is undeniable that brain networks play a pivotal role in the development and progression of *** thoroughly elucidate the intricate network of elements and connections constituting the human brain,the concept of the brain connectome was *** based on the connectome holds immense potential for revealing the mechanisms underlying disease development,and it has become a prominent topic that has attracted the attention of numerous *** this review,we aim to systematically summarize studies on brain networks within the context of AD,critically analyze the strengths and weaknesses of existing methodologies,and offer novel perspectives and insights,intending to serve as inspiration for future research.

关键词： Alzheimer’s disease brain-connectome graph theory deep graph neural networks

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