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2024 Systems and Information engineering Design Symposium, SIEDS 2024

作者： Tablada, Tulio Davis, Cleon Palumbo, Neil Johns Hopkins University Electrical and Computer Engineering Program Johns Hopkins University Applied and Computational Mathematics Program United States

ISBN: (纸本)9798350385144

In the basic vehicle routing problem (VRP), a vehicle must deliver goods from one centralized warehouse to multiple customers efficiently. Several VRP variants and constraints exist, including different product types, specific delivery times, multiple warehouses, vehicle fuel constraints, and pick-up from one location and delivery to another. This work proposes and demonstrates a flexible algorithm for solving the VRP via ant colony optimization (ACO) that can address many of the variants discussed above. ACO algorithms mimic the behavior of ants, learning optimal paths to a food source and back to the nest based on stigmergic behavior. This work compares a proposed, more flexible ACO algorithm to a traditional optimization algorithm that is implemented in the Google VRP solver. Readily available data were used to test and demonstrate results. Several VRP variants were implemented in both the (proposed) flexible ACO algorithm and the Google VRP solver. The flexible ACO algorithm performed better in terms of distance traveled versus the Google VRP solver for two variants and worse for three other cases. However, the Google VRP solver was not able to solve some of the VRP variant combinations considered here and failed when solving some backhaul datasets. Because the flexible ACO algorithm was able to better handle many case variations, it may be an attractive alternative optimization tool. © 2024 IEEE.

关键词： Ant colony optimization

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Surface phase diagram of CsSnI3 from first-principles calculations

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Physical Review Materials 2024年第9期8卷 093401页

作者： Kejia Li Chadawan Khamdang Mengen Wang Department of Electrical and Computer Engineering Materials Science and Engineering Program

CsSnI3 is widely studied as an environmentally friendly Pb-free perovskite material for optoelectronic device applications. To further improve material and device performance, it is important to understand the surface structures of CsSnI3. We generate surface structures with various stoichiometries, perform density functional theory calculations to create phase diagrams of the CsSnI3 (001), (110), and (100) surfaces, and determine the most stable surfaces under a wide range of Cs, Sn, and I chemical potentials. Under I-rich conditions, surfaces with Cs vacancies are stable, which lead to partially occupied surface states above the valence band maximum. Under I-poor conditions, we find the stoichiometric (100) surface to be stable under a wide region of the phase diagram, which does not have any surface states and can contribute to long charge-carrier lifetimes. Consequently, the I-poor (Sn-rich) conditions will be more beneficial to improve the device performance.

关键词： Electronic structure Surface reconstruction Surface states Perovskites Semiconductors Density functional theory

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Trade Ease with Machine Learning and AWS

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IEEE Access 2023年 11卷 25893-25905页

作者： Teja, Kamurthi Ravi Liu, Chuan-Ming National Taipei University of Technology International Program of Electrical Engineering and Computer Science Taipei10608 Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei10608 Taiwan

Global trading is undergoing significant changes, necessitating modifications to the trading strategies. This study presents a newly developed cloud-based trading strategy that uses Amazon Web Services (AWS), machine learning (ML), and data science to automate trading tasks. The study begins by creating a machine learning trading strategy using a customized deep neural network (DNN). The strategy was then tested using a trading station before deployment on a cloud machine. The execution of the strategy resulted in a total profit of 42.74526 USD, with a test accuracy score of 87.45% and a training accuracy score of 89.15% over 6047 epochs. The roadmap provides a step-by-step overview of the entire process from strategy development to execution. In addition, this study offers insights into related issues and solutions that can enhance the effectiveness of trading strategies. Overall, this study contributes significantly to the field of cloud-based trading strategies and opens avenues for future research. © 2013 IEEE.

关键词： Deep neural networks

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A Feasibility Study: Magnetic Field Monitoring in Cycled Lead Acid Cells for Stationary Applications

A Feasibility Study: Magnetic Field Monitoring in Cycled Lea...

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2025 IEEE electrical Energy Storage Applications and Technologies Conference, EESAT 2025

作者： Vasconcelos, Scarleth Singh, Pritpal Lee, Ross Villanova University Sustainable Engineering Program Villanova United States Villanova University Dept of Electrical and Computer Engineering Villanova United States

ISBN: (纸本)9798331524852

This research introduces a novel, real-time, non-invasive, non-destructive, and accurate method for battery mon-itoring using magnetic field mapping. This technique detects stratification in flooded Lead Acid Batteries at different states of charge, providing early notification by monitoring variations in hydrogen ion concentration during cycling. The study tracked pH and magnetic field variations across H2SO4 electrolyte specific gravities ranging from 1.07 to 1.33, showing a 17%-20% pH reduction over 12 hours, indicating acid stratification. A proof-of-concept using air-core solenoid coils demonstrated a direct correlation between secondary coil output voltage and H2SO4 concentrations, influenced by the induced magnetic field at the primary coil and electrolyte concentration changes. The optimal AC input frequency for maximizing the induced magnetic field mapping response was identified as 30-33 kHz, depending on the physical properties of the magnetic field inductors. An inverse correlation was also observed between the induced magnetic field and the distance between the coils. This approach offers a promising alternative for lead acid battery monitoring, potentially improving battery management and lifespan. The experimental tests also included monitored variations in secondary coil output voltage in a single flooded lead acid cell during cycling. The preliminary results demonstrated a decrease in the magnetic field during charge and an increase during discharge. © 2025 IEEE.

关键词： Lead acid batteries

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A Pulse Width Modulation-Based Spike Generator to Eliminate Timing Errors in Spiking Neural Networks

A Pulse Width Modulation-Based Spike Generator to Eliminate ...

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2025 International Conference on Electronics, Information, and Communication, ICEIC 2025

作者： Jo, Jungkook Sim, Keonhee Sim, Sangwoong Jun, Jaehoon Inha University Dept. of electrical and computer engineering and program in semiconductor convergence Incheon Korea Republic of Inha University Dept. of electrical engineering Incheon Korea Republic of

ISBN: (纸本)9798331510756

This paper proposes a novel spike generator for processing in memory (PIM) technology. Most of the electronics today utilize a von Neumann architecture. The von Neumann architecture suffers from the separation of memory and processor. This architecture delays data transfer between memory and processor. To overcome the issues, we utilize the spiking neural network (SNN) that combines memory and processor. SNN can be classified into voltage-based, current-based, and time-based architectures, each with its own pros and cons. Time-based SNN suffers from timing issues. To address the timing sensitivity of time-based neuron SNN, this paper proposes a PWM-based SNN. The PWM-based SNN utilizes pulse width-based logic to overcome timing sensitivity. © 2025 IEEE.

关键词： Pulse width modulation

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A ShuffleNet Architecture-Based Multi-Layer Feature Scaling and Fusion Approach for Underwater Net Cage Damage Detection in Aquaculture

A ShuffleNet Architecture-Based Multi-Layer Feature Scaling ...

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2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Huang, Xiang-Rui Chen, Yi-Cheng Chen, Liang-Bi Hu, Wu-Chih National Penghu University of Science and Technology Master Program in Electrical Engineering and Computer Science Department of Electrical Engineering Penghu Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

ISBN: (纸本)9798331530839

In offshore aquaculture operations, personnel equipped with diving gear are often necessary to inspect the underwater net cages for damage, particularly on the sea floor. This manual inspection process is time-consuming and complex. To overcome this problem, this paper proposes a computer vision solution for identifying damage in underwater net cages to address the inefficiencies and challenges of traditional manual inspections. The proposed scheme utilizes a high-performance multi-branch computational architecture designed based on ShuffleNet architecture to detect net cage damage more efficiently. Experimental results demonstrate that this work performs well on the ImageNet ILSVRC-2010 dataset and achieves an accuracy of 88.54% in underwater net damage detection. © 2024 IEEE.

关键词： Aquaculture

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Early Detection of Heart Rate Conditions in Autistic Children Using IoT-Based Systems 4

Early Detection of Heart Rate Conditions in Autistic Childre...

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4th International Conference on electrical engineering and computer Science, ICECOS 2024

作者： Albar, Nizam Melinda, Melinda Away, Yuwaldi Universitas Syiah Kuala Dept. Electrical Engineering Master of Electrical Engineering Study Program Banda Aceh Indonesia Universitas Syiah Kuala Engineering Faculty Dept. Electrical Engineering and Computer Banda Aceh Indonesia

ISBN: (纸本)9798350368253

Early detection of heart rate conditions in autistic children is crucial for anticipating tantrum reactions and providing prompt medical intervention. Previous research designed a prototype for acquiring Electrocardiogram (ECG) signals using the AD8232 sensor, but it required a long time to identify heart rate conditions. This study aims to develop the previous prototype using Internet of Things (IoT) implementation to acquire and identify the heart rate conditions of autistic children in real time. The ECG signal data is analyzed using Butterworth Filter and Artificial Neural Network (ANN) integrated into Raspberry Pi and results are transmitted to the Blynk App. Testing over 20 minutes showed that in the first 10 minutes, the system identified a normal heart rate at 105.19 BPM with 67% accuracy, while in the second 10 minutes, the heart rate rose to 117.19 BPM with tantrum symptoms and 75% accuracy. This system helps medical personnel provide immediate intervention during tantrums. © 2024 IEEE.

关键词： Butterworth filters

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A generalized adder for cell size homeostasis: Effects on stochastic clonal proliferation

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Biophysical Journal 2025年第9期124卷 1376-1386页

作者： Nieto, César Vargas-García, César Augusto Singh, Abhyudai Department of Electrical and Computer Engineering University of Delaware Newark DE United States AGROSAVIA - Corporacion Colombiana de Investigacion Agropecuaria Cundinamarca Mosquera Colombia Department of Electrical and Computer Engineering Biomedical Engineering Mathematical Sciences Interdisciplinary Neuroscience Program University of Delaware Newark DE United States

Measurements of cell size dynamics have revealed phenomenological principles by which individual cells control their size across diverse organisms. One of the emerging paradigms of cell size homeostasis is the adder, where the cell cycle duration is established such that the cell size increase from birth to division is independent of the newborn cell size. We provide a mechanistic formulation of the adder, considering that cell size follows any arbitrary nonexponential growth law. Our results show that the main requirement to obtain an adder regardless of the growth law (the time derivative of cell size) is that cell cycle regulators are produced at a rate proportional to the growth law, and cell division is triggered when these molecules reach a prescribed threshold level. Among the implications of this generalized adder, we investigate fluctuations in the proliferation of single-cell-derived colonies. Considering exponential cell size growth, random fluctuations in clonal size show a transient increase and then eventually decay to zero over time (i.e., clonal populations become asymptotically more similar). In contrast, several forms of nonexponential cell size dynamics (with adder-based cell size control) yield qualitatively different results: clonal size fluctuations monotonically increase over time, reaching a nonzero value. These results characterize the interplay between cell size homeostasis at the single-cell level and clonal proliferation at the population level, explaining the broad fluctuations in clonal sizes seen in barcoded human cell lines. © 2025 Biophysical Society

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An Expanded Latent Space Autoencoder for Land Cover Classification of Remote Sensing Images from EuroSAT 16

An Expanded Latent Space Autoencoder for Land Cover Classifi...

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16th Brazilian Symposium on Robotics and 15th Workshop on Robotics in Education, SBR-WRE 2024

作者： Vilar Oliveira, Emerson Garcia Gonçalves, Luiz Marcos Graduate Program in Electrical and Computer Engineering Universidade Federal do Rio Grande do Norte Natal Brazil

ISBN: (纸本)9798350391084

Image classification has been instrumental in the interpretation and labeling of images in the field of remote sensing, computer vision, and in robotics applications. Machine learning and artificial intelligence algorithms, particularly artificial neural networks, are extensively utilized for this purpose. In this work we propose the Expanded Latent Space Autoencoder (ELSA) with a case use application to classify land cover data. The main idea on the ELSA network structure is to utilize the latent spaces of multiple internal autoencoders in order to create an expanded latent space. This expanded latent space extracts more information from the input data, and serves as input features for a more simpler classifier network. In order to evaluate the proposed network’s ability to extract features and classify complex and multispectral images we employed it to the EuroSAT dataset. The results demonstrate a remarkable capacity for feature extraction using the ELSA network, with lower complexity, trained with a reduced number of images. The classifier network achieved a final accuracy of 98.7%, matching or exceeding the performance of more complex state-of-the-art models. ©2024 IEEE.

关键词： Neural networks

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Quality Analytics for Latin American and Brazilian Robotics Symposiums 16

Quality Analytics for Latin American and Brazilian Robotics ...

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16th Brazilian Symposium on Robotics and 15th Workshop on Robotics in Education, SBR-WRE 2024

作者： Garcia Gonçalves, Luiz Marcos Electrical and Computer Engineering Graduate Program Universidade Federal do Rio Grande do Norte Natal Brazil

ISBN: (纸本)9798350391084

We bring historical findings related to the most important Latin American and Brazilian Robotics Symposiums including their quality analytics regarding all papers published since their creation. For this quality analysis, we first provide a little of history and then we apply a methodology based on a systematic mapping of the literature using Scopus (from Elsevier) and Web of Science. The quality analysis includes variables as citations metrics, and also other historical variables as participation per countries, per states, per universities, and contributed areas among others. We use metadata and tools available in the most commonly used digital libraries, for a fair comparison. To the end, with basis on the results of our methodological approach, we point out that the community has followed the right path for establishing a high quality event, mainly regarding the decision of publication of the proceedings at IEEE Xplore, and recently in the Brazilian computer Society Library (Sol-SBC), all together. Also, our analysis corroborate to verify the modi operandi that have been used in the events execution, including joining in the Workshop of Robotics in Education (WRE) and the competitions (RCB, OBR, MNR, CBR, LARC). Besides happening jointly, each event keeps their original event structure and characteristics. ©2024 IEEE.

关键词： Taxonomies

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