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4th IEEE International Conference on Quantum Computing and engineering, QCE 2023

作者： Clark, Joseph Humble, Travis S. Thapliyal, Himanshu University of Tennessee Dept. of Elec. Eng. and Computer Science Knoxville United States Oak Ridge National Laboratory Quantum Science Center Oak Ridge United States

ISBN: (纸本)9798350343236

We propose Greedy Topology-Aware Quantum Circuit Partitioning (GTQCP), a novel quantum gate circuit partitioning method which partitions circuits by applying a greedy heuristic to the qubit dependency graph of the circuit. GTQCP is compared against three other gate partitioning methods, two of which (QuickPartitioner and ScanPartitioner) are part of the Berkley Quantum Synthesis Toolkit. GTQCP is shown to have 18% run time improvement ratio over the fastest approach (QuickPartitioner), and a 96% improvement over the highest quality approach (ScanPartitioner). The algorithm also demonstrates nearly identical result quality (number of partitions) compared with ScanPartitioner, and a 38% quality improvement over QuickPartitioner. © 2023 IEEE.

关键词： Timing circuits

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Kalman filter estimation method for battery cell parameters in Reconfigurable Cascaded Multilevel Converter

Kalman filter estimation method for battery cell parameters ...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Tresca, Giulia Formentini, Andrea Granata, Samuele Magrini, Carlo Zanchetta, Pericle University of Genoa El. Elec. and Telec. Engineering and Naval Architecture Dept. Genova Italy University of Pavia Electrical Computer and Biomedical Engineering Dept. Pavia Italy University of Nottingham Electrical and Electronics Engineering Dept. Nottingham United Kingdom

ISBN: (纸本)9798350316445

This paper presents an online estimation technique Kalman filter-based able to evaluate both the open circuit voltage and the internal resistance of the battery cells installed within the Reconfigurable Cascaded Multilevel Converter. This technique fills the gap for the complex reconfigurable structures, allowing the estimation of the parameters with only the knowledge of the output current and voltage and instantaneous active battery cells. The estimation technique is combined with a sorting algorithm to address the specific topic of multilevel converter controlled with digital modulation. Specifically, the estimation algorithm here presented ensures a reduced convergence time, demonstrated by the low mean error computed. Moreover, the estimation technique is simulated during both discharging and charging processes, showing how different initial conditions may affect the convergence time depending on the power flow. © 2023 IEEE.

关键词： Battery cells Estimation Technique Internal resistance Kalman Filter Multilevel Converter Online Estimation Open circuit voltage Reconfigurable Cascaded Multilevel Converter Sorting algorithm

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An Implementation of Android Programming Self-learning Topic for Developing Online Database Application Using Firebase 6

An Implementation of Android Programming Self-learning Topic...

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6th International Conference on Vocational Education and elec.rical engineering, ICVEE 2023

作者： Syaifudin, Yan Watequlis Rozi, Imam Fahrur Kaswar, Andi Baso Funabiki, Nobuo Fatmawati, Triana Siradjuddin, Indrazno State Polytechnic of Malang Dept. of Information Technology Malang Indonesia State University of Makassar Dept. of Computer Engineering Makassar Indonesia Okayama University Dept. of Elec. and Comm. Engineering Okayama Japan State Polytechnic of Malang Dept. of Electrical Engineering Malang Indonesia

ISBN: (纸本)9798350326642

The trend in software development recently has been toward the creation of applications for Android smartphones that impacts the growth of Android application developer demand. The Android Programming Learning Assistance System (APLAS) has been developed to study Android programming independently. Students get automatic guidance and feedback in writing source code by implementing test-driven development (TDD) method using JUnit and Robolectric. This paper presents a new implementation of Online Database topic, as the second topic in third learning stage of APLAS, for developing an Android online database application using Firebase. It provides basic functions to make e-commerce transactions consisting of user registration and login, selling, and buying goods that are interpreted into 9 activities. The topic was applied to 50 students in an Indonesian IT department to test its efficacy, and all of the students correctly completed the assignments with compliments. © 2023 IEEE.

关键词： Students

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Advanced Results Demonstrating that Lévy Firefly Bio-Inspired Algorithms Can Improve Fetal elec.rocardiogram (FECG) Adaptive Signal Processing 58

Advanced Results Demonstrating that Lévy Firefly Bio-Inspir...

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58th Asilomar Conference on Signals, Systems and computers, ACSSC 2024

作者： Jenkins, W.K. Radhakrishnan, C. School of Electrical and Computer Engineering Pennsylvania State University University ParkPA United States University of Illinois Dept. of Elec. and Comp. Engr. Urbana-ChampaignIL United States

ISBN: (纸本)9798350354058

Previously published results demonstrated that a sequential combination of adaptive linear prediction configuration (LPC), adaptive noise cancellation (ANC), and adaptive comb filtering (CF) can effectively remove maternal interference from noninvasive fetal ECGs. More recent research results have verified that the bio-inspired Lévy Flight Firefly Algorithm (LFFA) can be effectively applied to many different forms of linear and non-linear adaptive filter structures, including low sensitivity IIR adaptive structures that could not be used with steepest descent adaptive algorithms due to their adaptive multimodal characteristics. This paper presents results when using the LFFA algorithm in various stages of the FECG sequential combination processing. © 2024 IEEE.

关键词： Adaptive filtering

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Enhancing the Maximum Tolerable Number of Active Users for Unsourced Random Access

Enhancing the Maximum Tolerable Number of Active Users for U...

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IEEE International Symposium on Information Theory

作者： Shan Lu Hiroshi Kamabe Graduate School of Engineering Nagoya University Nagoya Japan Dept. of Elec. Elec. and Computer Eng. Gifu University Gifu Japan

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

In the unsourced random access (U-RA), only a portion of users in a large number of users are active during the same time slot. Each user employs the same codebook, and the task of the decoder is to recover a list of transmitted messages, regardless of the user's identity. A concatenated coding approach, referred to as a coded compressed sensing scheme, decreases the computational complexity. However, there is a limitation that the inner CS decoding only decodes the support of a sparse vector, which leads to each user at the same sub-slot must send a different message, and the maximum tolerable active user number is low. In this paper, we consider an inner CS decoding scheme that initially decodes the amplitudes of a sparse vector and quantifies them to determine the number of active users choosing the same columns. This eliminates the constraint of requiring each user to send different messages in the same sub-slot, thereby increasing the maximum tolerable number of active users. We also show the maximum tolerable active user number with various codelengths. Next, we improve the survival probabilities' upper and lower bounds of the outer tree encoder.

关键词： Codes Vectors Encoding Decoding Task analysis Computational complexity Compressed sensing

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Generating Automated Assistance Mechanism in Android Programming Self-learning System Using Automatic Testing Tools

Generating Automated Assistance Mechanism in Android Program...

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2023 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2023

作者： Syaifudin, Yan Watequlis Liliana, Dewi Yanti Kaswar, Andi Baso Fatmawati, Triana Funabiki, Nobuo Siradjuddin, Indrazno State Polytechnic of Malang Dept. of Information Technology Malang Indonesia State Polytechnic of Jakarta Dept. of Informatics Engineering Jakarta Indonesia State University of Makassar Dept. of Computer Engineering Makassar Indonesia Okayama University Dept. of Elec. and Comm. Engineering Okayama Japan State Polytechnic of Malang Dept. of Electrical Engineering Malang Indonesia

ISBN: (纸本)9798350307771

Nowadays, computer-assisted learning (CAL) has experienced a significant increase in demand for self-learning purposes with the mechanism of automated assistance to facilitate assessments and provide instant feedback to learners. Using automatic testing, test cases can be executed repeatedly, providing informative feedback to assist students in correcting the written code referring to the assignment specifications. This research experiences an automated testing mechanism in an Android programming self-learning system to serve several important functions for learning experience enhancement. By adopting the TDD method and utilizing automatic software testing tools, the testing process combines unit testing with JUnit and integration testing with Robolectric. It ensures the quality and functionality of the application under test based on learning assignment's specifications. Utilizing the assertion methods realizes the code verification referring to expected behavior and potentially produces informative feedback that can be captured to provide automated assistance. Evaluation through the test code implementation in the Basic Application learning topic shows that automatic testing tools cover the automated assistance feature in the validations of project configuration and UI components. © 2023 IEEE.

关键词： Specifications

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How Green Are elec.ric Vehicles in Developing Countries? 60

How Green Are Electric Vehicles in Developing Countries?

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60th IEEE/IAS Industrial and Commercial Power Systems Technical Conference, I and CPS 2024

作者： Ayaz, Muhammad Ashar Ehsani, Mehrdad Rahman, Syed Khan, Irfan Su, Chun-Lien Texas A&m University Dept. of Elec. & Comp. Engr. College StationTX77840 United States National Kaohsiung University of Science & Technology Department of Electrical Engineering Taiwan

ISBN: (纸本)9798350345308

This paper addresses the urgent challenges of escalating global warming, rapid ozone layer depletion, and persistent greenhouse gas (GHG) emissions exacerbated by nations' reluctance to limit industrial emissions for economic growth. This has prompted a global shift towards exploring alternative strategies for pollution mitigation, including transitioning from conventional power generation to sustainable energy resources and a move from gasoline-based transportation to elec.ric vehicles (EVs). Particularly critical is the question of whether this transition genuinely yields environmental benefits, or if it potentially exacerbates existing challenges, especially in underdeveloped or developing countries heavily reliant on fossil fuel-generated elec.ricity. The paper presents a concise comparative analysis between elec.ric Vehicles (EVs) and Internal Combustion Engine Vehicles (ICEVs), examining GHG emissions throughout their lifetimes, during manufacturing, and in terms of fuel consumption. Additionally, it explores the energy mix of developing countries compared to the global scenario, presenting results for the comparison between ICEVs and EVs using elec.ricity from coal, gas, nuclear, and a balanced energy mix-dominated power system. The study identifies opportunities for improvement in EV adoption and emission mitigation strategies, offering valuable insights into sustainable practices and environmental conservation. © 2024 IEEE.

关键词： Gasoline

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Meta-LoRA: Meta-Learning LoRA Components for Domain-Aware ID Personalization

arXiv

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arXiv 2025年

作者： Topal, Barış Batuhan Özyurt, Umut Budak, Zafer Doğan Cinbis, Ramazan Gokberk Pixery Labs İstanbul Turkey METU Dept. of Computer Engineering Ankara Turkey METU Dept. of Electrical and Elec. Engineering Ankara Turkey

Recent advancements in text-to-image generative models, particularly latent diffusion models (LDMs), have demonstrated remarkable capabilities in synthesizing high-quality images from textual prompts. However, achieving identity personalization-ensuring that a model consistently generates subject-specific outputs from limited reference images-remains a fundamental challenge. To address this, we introduce Meta-Low-Rank Adaptation (Meta-LoRA), a novel framework that leverages meta-learning to encode domain-specific priors into LoRA-based identity personalization. Our method introduces a structured three-layer LoRA architecture that separates identity-agnostic knowledge from identity-specific adaptation. In the first stage, the LoRA Meta-Down layers are meta-trained across multiple subjects, learning a shared manifold that captures general identity-related features. In the second stage, only the LoRA-Mid and LoRA-Up layers are optimized to specialize on a given subject, significantly reducing adaptation time while improving identity fidelity. To evaluate our approach, we introduce Meta-PHD, a new benchmark dataset for identity personalization, and compare Meta-LoRA against state-of-the-art methods. Our results demonstrate that MetaLoRA achieves superior identity retention, computational efficiency, and adaptability across diverse identity conditions. Our code, model weights, and dataset are released on ***/Meta-LoRA. Copyright © 2025, The Authors. All rights reserved.

关键词： Learning to rank

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A Lightweight and Efficient Scheme for e-Health Care System using Blockchain Technology 6

A Lightweight and Efficient Scheme for e-Health Care System ...

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6th International Conference on Information Systems and computer Networks, ISCON 2023

作者： Saxena, Sandeep Arya, Namita Bharti, Sunil Kumar Dwivedi, Vimal Gniot Dept. of Cse Greater Noida India Galgotias University Dept. of Cse Greater Noida India Gcet Dept. of It Greater Noida India Institute of Computer Science University of Taru Estonia School of Elec. Elect. Engg. and Computer Science Queens University Northern Ireland Belfast United Kingdom

ISBN: (纸本)9798350346961

We are witnessed to the huge amount of health care information is processed via Internet and uploaded to the servers. Hence, the network content suffers from various challenges in handling this wide range of information such as privacy-preservation, message requests, and sharing of information with the entities. Protection of health care information with less communication overhead and avoid signaling congestion among entities is the biggest concern. We suggest a simple and effective blockchain-based system for e-health care in order to address these problems. We attempt to show the collective trust between receiver/ users and key generation center (KGC). Due to the characteristics such as tamper-resistant of transactions and responsiveness, the blockchain technology maintains the data access policy and privacy of each receiver/ users. In addition, we provide the public transactions apparently with the help of miners. Also, the performance analysis shows that the protocol is free from all the security attacks and avoid the signaling congestion with less overhead.. © 2023 IEEE.

关键词： Blockchain

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Optimizing Data Stream Freshness for Enhanced Communication in Autonomous Vehicle Networks

Optimizing Data Stream Freshness for Enhanced Communication ...

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2025 IEEE Wireless Communications and Networking Conference, WCNC 2025

作者： Ebrahimi, Dariush Ghosh, Pronab Alzhouri, Fadi De Oliveira, Thiago E. Alves Wilfrid Laurier University Dept. of Computer Science WaterlooON Canada Lakehead University Dept. of Computer Science Thunder BayON Canada Gust University Dept. of Elec. & Computer Eng. Mishref Kuwait

ISBN: (纸本)9798350368369

Autonomous vehicles (AVs) are anticipated to play a pivotal role in intelligent transportation systems, particularly in the context of future smart cities. Common performance measures like throughput and latency are not sufficient for capturing the timing and freshness of data in applications like autonomous driving and accident prevention. Therefore, this paper addresses the challenge of minimizing the Age of Information (AoI) in AVassisted vehicular networks. First, the problem is mathematically formulated as linear programming to derive optimal solutions. Recognizing the computational complexity, a scalable heuristic method tailored for large networks is proposed. Additionally, for comparative analysis, the problem is modeled as a Markov decision process and solved using Q-learning, an algorithm of Reinforcement Learning (RL). The numerical results highlight the efficacy of the proposed heuristic method in minimizing the average AoI, considering both computational efficiency and its potential to complement RL algorithms in a hybrid approach. © 2025 IEEE.

关键词： Heuristic methods

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