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2nd International Conference of Intelligent Methods, Systems and Applications, IMSA 2024

作者： Mahdy, Nevien A. Elnokrashy, Ahmed F. Hammad, D.A. Mohamed, Wael A. Benha University Benha Faculty of Engineering Electrical Engineering Department Benha Egypt Nile University Faculty of Information Technology and Computer Science Computer Science Department Giza Egypt Benha University Benha Faculty of Engineering Basic Engineering Sciences Department Benha Egypt

ISBN: (纸本)9798350362633

Hypoglycemia in Type 1 Diabetes (T1D) refers to a condition where blood glucose (BG) levels drop to abnormally low levels, typically below 70 mg/dL. This can occur when there is an excessive amount of insulin relative to the blood glucose level, leading to an imbalance that can be dangerous and potentially life-threatening if not promptly treated. The availability of large amounts of data from continuous glucose monitoring (CGM), insulin doses, carbohydrate intake, and additional vital signs, together with deep learning (DL) techniques, has revolutionized algorithmic approaches for BG prediction in T1D, achieving superior performance. In our study, we employed a Long Short-Term Memory (LSTM) neural network architecture to predict hypoglycemia events in patients with T1D. For the training and testing, we utilized the OhioT1DM (2018) dataset. In addition, real-time data collected from an individual patient for the evaluation. This patient utilized the CGM FreeStyle Libre (FSL) system, along with a smartwatch to monitor step count. The LSTM model exhibited performance demonstrating exceptional levels of sensitivity, specificity, and accuracy scores of 97.09%, 94.17%, and 95.63%, respectively, when assessed using the Ohio test dataset. Our research provides strong evidence supporting the system's efficacy in managing hypoglycemia events in individuals diagnosed with T1D. © 2024 IEEE.

关键词： Classification Deep learning Glucose prediction Hypoglycemia Type 1 diabetes

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Developing an MVDC Bipolar Coaxial Cable System for Lunar Power Transmission

Developing an MVDC Bipolar Coaxial Cable System for Lunar Po...

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

作者： Saha, Anoy Ghassemi, Mona The University of Texas at Dallas ZEROES lab Department of Electrical and Computer Science Engineering RichardsonTX United States

ISBN: (纸本)9798350366679

The increasing need for power on the lunar surface, expected to reach megawatt levels, aligns with NASA's goal of establishing a sustainable human presence on the Moon, able to support over 100 personnel indefinitely. As humanity explores sustained lunar habitation and aims to establish bases, efficient and reliable power transmission becomes crucial. Power lines with high power density are needed, focusing on weight and volume while ensuring safety and cost-effectiveness in the harsh lunar environment. There are three possible locations for power lines on the lunar surface: above, on, or below the surface. Due to harsh lunar conditions like temperature fluctuations, micro meteoroid impacts, and radiation exposure, the initial two methods have limited effectiveness in transferring power on the moon. Underground deployment is considered safe and convenient;however, low soil thermal conductivity could pose a challenge. However, a temperature of -23.15 °C at a depth of 30 cm proves beneficial for waste heat. This study employs COMSOL Multiphysics to propose a novel method for developing and analyzing bipolar MVDC cables for power transmission beneath the lunar surface. Designed for ±10 kV voltage and 2 MW power, these cables offer an efficient solution for lunar power transmission and are resilient to harsh conditions. © 2024 IEEE.

关键词： Waste heat

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Evolutionary Optimization with a Simplified Helper Task for High-Dimensional Expensive Multiobjective Problems

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ACM Transactions on Evolutionary Learning and Optimization 2024年第4期4卷 1-32页

作者： Wu, Xunfeng Lin, Qiuzhen Zhou, Junwei Liu, Songbai Coello Coello, Carlos A. Leung, Victor C. M. College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan430070 China Mexico City07300 Mexico Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada

In recent years, surrogate-Assisted evolutionary algorithms (SAEAs) have been sufficiently studied for tackling computationally expensive multiobjective optimization problems (EMOPs), as they can quickly estimate the qualities of solutions by using surrogate models to substitute for expensive evaluations. However, most existing SAEAs only show promising performance for solving EMOPs with no more than 10 dimensions, and become less efficient for tackling EMOPs with higher dimensionality. Thus, this article proposes a new SAEA with a simplified helper task for tackling high-dimensional EMOPs. In each generation, one simplified task will be generated artificially by using random dimension reduction on the target task (i.e., the target EMOPs). Then, two surrogate models are trained for the helper task and the target task, respectively. Based on the trained surrogate models, evolutionary multitasking optimization is run to solve these two tasks so that the experiences of solving the helper task can be transferred to speed up the convergence of tackling the target task. Moreover, an effective model management strategy is designed to select new promising samples for training the surrogate models. When compared to five competitive SAEAs on four well-known benchmark suites, the experiments validate the advantages of the proposed algorithm on most test cases. © 2024 held by the owner/author(s).

关键词： Multitasking

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Differentiation Method Based Approximation of Higher Order Islanded Microgrid System 4

Differentiation Method Based Approximation of Higher Order I...

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4th IEEE International Conference on Sustainable Energy and Future Electric Transportation, SEFET 2024

作者： Chaudhary, Richa Singh, V.P. Mathur, Akhilesh Yadav, U.K. Waghmare, A.V. Murari, Krishna Malaviya National Institute of Technology Department of Electrical Engineering Rajasthan Jaipur302017 India The University of Toledo Electrical Engineering and Computer Science Department ToledoOH43606 United States

ISBN: (纸本)9798350383997

The interconnections of different sub-systems in microgrid frequently leads to determination of complex higher order systems (HOSs). In this paper, order reduction of higher-order islanded microgrid system is performed. The eighth-order system of an islanded microgrid is reduced to comparatively lower order models (LOMs). For order reduction, differentiation method is exploited to obtain LOMs of orders up to second-order. To ensure the efficacy of LOMs, a comparative analysis is performed. For analysis purpose, error indices and time-domain specifications are considered and tabulated. For better visualization of ascertained LOMs, responses are also depicted. The compatibility of the obtained LOMs with its islanded microgrid's HOS is demonstrated using step response, impulse response, Bode response, Nichols response, and Nyquist response. © 2024 IEEE.

关键词： Impulse response

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Reliable and secure memristor-based chaotic communication against eavesdroppers and untrusted foundries

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Discover Internet of Things 2023年第1期3卷 1-17页

作者： Vishwakarma, Rahul Monani, Ravi Hedayatipour, Ava Rezaei, Amin Department of Computer Engineering & amp Computer Science California State University Long Beach Long BeachCA United States Department of Electrical Engineering California State University Long Beach Long BeachCA United States

Chaos is a deterministic phenomenon that occurs in a non-linear dynamic system under specific condition when the trajectories of the state vector become periodic and extremely sensitive to the initial conditions. While traditional resistor-based chaotic communications are primarily concerned with the safe transfer of information across networks, the transceivers themselves can be compromised due to outsource manufacturing. With the growth of wireless sensors in resource-constrained implantable and wearable devices, chaotic communication may be a good fit if the information transmitted is reliable and the transmitter devices are secure. We believe that memristor, as the fourth fundamental two-terminal circuit element, can close the gap between reliable communication and secure manufacturing since its resistance can be programmed and saved by the designer and not the foundry. Thus, in this paper, we propose a memristor-based Chua’s chaotic transceiver that is both reliable in the presence of eavesdroppers and secure against untrusted foundries. Specifically, we consider the pair of transmitter and receiver under the same memristor value to show the possibility of uninterrupted communication as well as cases where different values of memristors are used to find out the possible range in which the message can still be meaningfully decoded. Experimental results confirm that both reliable communication and secure design can be achieved via our proposed memristor-based chaos transceivers. © The Author(s) 2023.

关键词： Wearable technology

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Chebyshev polynimal dempster convolutional hearing sensitivity level detection with auditory evoked potentials

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Journal of Intelligent and Fuzzy Systems 2023年第4期45卷 5353-5366页

作者： Kirthika, K.M. Paulraj, M.P. Hema, C.R. Department of Computer Science Engineering Sri Ramakrishna Institute of Technology Tamil Nadu Coimbatore India Department of Electrical and Electronics Engineering Sri Ramakrishna Institute of Technology Tamil Nadu Coimbatore India

The EEG-based HTR utilizing AEP responses of both group of participants with normal hearing and abnormal hearing are managed with the objective of detecting hearing sensitivity level using Chebyshev Recurrence Polynomial and Dempster Convolutional Neural Network (CRP-DCNN) is designed. The CRP-DCNN method is split into three sections. They are preprocessing using Chebyshev Recurrence Polynomial Filter, feature extraction by employing Orthogonalized Singular Value and Median Skewed Wavelet. Here, both Orthogonalized Singular Value Decomposition-based parametric and Median Skewness-based non-parametric modeling techniques are employed for first obtaining the hearing threshold factors and then extracting statistical features for further processing. Finally Dempster Convolutional Neural Network-based Classification for detecting hearing sensitivity level is presented. Hence, the objective to determine the significant correlations between the brain dynamics and the auditory responses and detect the hearing sensitivity level of the group of participants with normal hearing and with the group of participants with hearing loss are designed on accordance with the features of EEG signals. Simulations are performed in MATLAB to validate the features of EEG signals. © 2023 - IOS Press. All rights reserved.

关键词： Convolution

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Ontology-Based Reinforcement Learning for Semantic Offloading in MEC-Enabled 6G IoT Networks

Ontology-Based Reinforcement Learning for Semantic Offloadin...

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Gyamfi, Eric Ansere, James Adu Golpayegani, Fatemeh School of Computer Science University College Dublin Ireland Sunyani Technical University Department of Electrical Engineering Ghana

ISBN: (纸本)9798350364910

The proliferation of ultra-low-latency and faster convergence applications in sixth-generation (6G) networks necessitates mobile edge computing (MEC) for offloading computationally intensive tasks from user devices to the network edge. However, traditional offloading approaches ignore the semantic aspects of tasks and resources. This paper proposes a novel ontology-based reinforcement learning (ORL) approach for optimal semantic offloading decisions in evolving dynamic MEC-enabled 6G networks, considering network uncertainty and time variation conditions. The proposed ORL approach integrates a dynamic learning mechanism that adjusts and captures semantics task resources, enabling adaptive real-time offloading decisions to satisfy task processing requirements and user demands. The numerical results demonstrate significant improvements in latency reduction, responsiveness, and adaptability compared to traditional offloading approaches. © 2024 IEEE.

关键词： Adversarial machine learning

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Misuse of Wi-Fi Data to Analyze User Behaviour 15

Misuse of Wi-Fi Data to Analyze User Behaviour

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15th International Conference Elektro, ELEKTRO 2024

作者： Kapicak, Lukas Stipal, Jiri Trubak, Kamil Machnik, Petr Burdiak, Patrik Rozhon, Jan VSB-Technical University of Ostrava Faculty of Electrical Engineering and Computer Science Department of Telecommunications Ostrava Czech Republic

ISBN: (纸本)9798350372359

There has been a huge increase in the number of mobile devices over the past few years. Many mobile users own more than one mobile device. Compared to conventional laptops, mobile devices are constantly active and their users use them outdoors more often than personal computers. Compared to desktop computers, mobile devices accompany their owners on their travels and therefore there is a significant risk of tracking and eavesdropping on user data without a user being aware of it. This paper describes techniques how the attacker could track users by using the Wireless Fidelity (Wi-Fi) network. Every mobile device generates traffic that can be divided into 'Automatic' and 'User'. When' Automatic' traffic is generated, the device can be found because of its pattern. The paper also describes how the attacker can get into the victim's Wi-Fi network without being in its range. When breaching the Wi-Fi network security, the attacker can connect to the victim's network during his first appearance in range of this network. Security pre-cautions and possible directions of future work are discussed at the end of this paper. © 2024 IEEE.

关键词： Personal computers

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Weak and Extremely Low Frequency Magnetic Fields Alter the Growth Rates of HT-1080 Fibrosarcoma

Weak and Extremely Low Frequency Magnetic Fields Alter the G...

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2025 United States National Committee of URSI National Radio science Meeting, USNC-URSI NRSM 2025

作者： Dang, Nhat Keller, Jason Bajtos, Marek Gurhan, Hakki Barnes, Frank Department of Electrical Computer and Energy Engineering College of Engineering and Applied Science University of Colorado Boulder BoulderCO United States Department of Electromagnetics and Biomedical Engineering Faculty of Electrical Engineering and Information Technology University of Zilina Zilina Slovakia

ISBN: (纸本)9781946815200

This study presents experimental results showing that weak, extremely low frequency electromagnetic (EM) fields influence the growth rates of HT-1080 fibrosarcoma cells in vitro and offers a theoretical explanation for these effects. The results demonstrate that weak magnetic fields both increase and decrease the growth rates of fibrosarcoma cells by altering the mitochondrial superoxide (O2-) and calcium ions (Ca2+) concentrations in living cells. Over a 4-day exposure period, fibrosarcoma growth rates were modulated in the presence of low-level alternating current (AC) magnetic fields at a 10 μT amplitude at 13.5 Hz to 30 Hz frequency, superimposed on a 45 μT static background field. Effects due to changes in amplitude from 10 to 30 μT at selected frequencies are also investigated with the same superimposed static field. © 2025 USNC-URSI.

关键词： Electromagnetic field effects

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Revisiting Stochastic Realization Theory using Functional Itô Calculus 26

Revisiting Stochastic Realization Theory using Functional It...

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26th International Symposium on Mathematical Theory of Networks and Systems, MTNS 2024

作者： Veeravalli, Tanya Raginsky, Maxim Department of Electrical and Computer Engineering The Coordinated Science Laboratory University of Illinois UrbanaIL61801 United States

This paper considers the problem of constructing finite-dimensional state space realizations for stochastic processes that can be represented as the outputs of a certain type of a causal system driven by a continuous semimartingale input process. The main assumption is that the output process is infinitely differentiable, where the notion of differentiability comes from the functional Itô calculus introduced by Dupire as a causal (nonanticipative) counterpart to Malliavin's stochastic calculus of variations. The proposed approach builds on the ideas of Hijab, who had considered the case of processes driven by a Brownian motion, and makes contact with the realization theory of deterministic systems based on formal power series and Chen-Fliess functional expansions. Copyright © 2024 The Authors.

关键词： Stochastic systems

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