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30th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2023

作者： Da Costa, Patrícia Da Rosa, Morgana Soares, Rafael Da Costa, Eduardo Bampi, Sergio Federal University of Rio Grande Do Sul Graduate Program on Microelectronics Porto Alegre Brazil Graduate Program on Computing Pelotas Brazil Graduate Program on Electronic Engineering and Computing Pelotas Brazil Porto Alegre Brazil

ISBN: (纸本)9798350326499

This work presents an optimized exponential function VLSI hardware design by Taylor series expansion. The proposed architecture implements the exponential by approximating the logic design of a 4th-order Taylor series and explores efficient CMOS arithmetic operation strategies. It implements a shift-based divider and explores an efficient 4-2 adder compressor in the adder tree. The proposal with a -7 to 11 input values range shows an output error of around 2% of MRED with a reduced energy consumption of 3.63 pJ/operation for 32-bit output. For a 64-bit output, the energy per operation of the VLSI exponential unit is 14.97pJ/op, being able to process a more comprehensive input range (i.e., -14 to 22) for a negligible mean output error of around 1.7% of MRED. © 2023 IEEE.

关键词： Adders

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Accuracy-, Delay- and Area-Driven Evaluation of Lower-Part Approximate Parallel Prefix Adder 30

Accuracy-, Delay- and Area-Driven Evaluation of Lower-Part A...

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30th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2023

作者： Rosa, Morgana M. A. Costa, Eduardo Soares, Rafael Bampi, Sergio Pelotas Brazil Graduate Program on Electronic Engineering and Computing Pelotas Brazil Porto Alegre Brazil

ISBN: (纸本)9798350326499

This work proposes an accuracy-driven evaluation model of an approximate adder (AxA) called an approximate parallel prefix adder (AxPPA). It explores the significance of approximate computing (AxC) in optimizing performance and energy efficiency in computer systems by accepting minor accuracy trade-offs. We examine the AxPPA through a meticulous error analysis model and an automated analysis framework that comprehensively evaluates area and delay based on the fundamental equations of parallel prefix adders (PPAs). Additionally, it emphasizes the importance of lower-part approximation in adders, effectively addressing the elongation of carry chains and enhancing overall efficiency. The choice of approximation method directly impacts computational accuracy, resulting in variations in the number of approximated bits and carry chain length for a given tolerance level. Conducting a thorough comparison of accuracy trade-offs requires a unique design and simulation for each unit and approximation level, which can be time-consuming, particularly in larger circuits. Therefore, the proposed approach facilitates the exploration of larger circuit design space encompassing multiple AxAs, significantly minimizing time investment. In our experiments, the accuracy-driven evaluation of the lower part approximation method in AxA took 71.268 milliseconds for 1 million random inputs, with a K -bits approximation ranging from 1 to 16. The results indicate that AxPPA exhibits a minor error magnitude among the explored literature AxAs, being approximately 50.97% more accurate on average. © 2023 IEEE.

关键词： Adders

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Dynamic Sampling-Based Meta-Learning Using Multilingual Acoustic Data for Under-Resourced Speech Recognition

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IEEE Access 2024年 12卷 106070-106083页

作者： Hsieh, I-Ting Wu, Chung-Hsien Zhao, Zhe-Hong National Cheng Kung University Graduate Program of Multimedia Systems and Intelligent Computing Tainan70101 Taiwan National Cheng Kung University Department of Computer Science and Information Engineering Tainan70101 Taiwan

Under-resourced automatic speech recognition (ASR) has become an active field of research and has experienced significant progress during the past decade. However, the performance of under-resourced ASR trained by existing methods is still far inferior to high-resourced ASR for practical applications. In this paper, speech data from languages that share the most phonemes with the under-resourced language are selected as supplementary resources for meta-training based on the Model-Agnostic Meta-Learning (MAML) strategy. Besides supplementary language selection, this paper proposes a dynamic sampling method instead of the original random sampling method to select support and query sets for each task in MAML to improve meta-training performance. In this study, Taiwanese is selected as the under-resourced language, and the speech corpus of five languages, including Mandarin, English, Japanese, Cantonese, and Thai, are chosen as supplementary training data for acoustic model training. The proposed dynamic sampling approach uses phonemes, pronunciation, and speech recognition models as the basis to determine the proportion of each supplementary language to select helpful utterances for MAML. For evaluation, with the selected utterances from each supplementary language for meta-training, we obtained a Word Error Rate of 20.24% and a Syllable Error Rate of 8.35% for Taiwanese ASR, which were better than the baseline model (26.18% and 13.99%) using only the Taiwanese corpus and other methods. © 2013 IEEE.

关键词： Speech recognition

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Mobility-Aware Federated Learning-Based Proactive UAVs Placement in Emerging Cellular Networks

IEEE Transactions on Machine Learning in Communications and ...

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IEEE Transactions on Machine Learning in Communications and Networking 2024年 2卷 1305-1318页

作者： Manzoor, Sanaullah Shakir, Muhammad Zeeshan Hasna, Mazen O. Qaraqe, Khalid A. University of the West of Scotland School of Computing Engineering and Physical Sciences PaisleyG72 0LH United Kingdom Qatar University College of Engineering Doha Qatar Texas A and M University Electrical and Computer Engineering Program Doha Qatar

With the vast proliferation of smart mobile devices, there is an ever-increasing demand for higher data rates and seamless connectivity throughout. Current 5th generation and beyond (B5G) cellular networks struggle to eradicate outage zones and ensure seamless connectivity. One promising solution to this problem is the use of unmanned aerial vehicles (UAVs) to assist the traditional ground network and provide connectivity in places where there are no small base stations or faulty ones as a result of some natural disasters such as flooding. In this paper, we propose a novel users' mobility-aware & users' demand-aware federated learning-based proactive UAV placement (MFPUP) framework to assist the existing ground communication network and minimise overall network outages. Our MFPUP framework utilises the federated learning-based mobility prediction model that recommends the potential outage areas to deploy UAVs using user-UAV association techniques such as the optimum association approach (OAP) and the greedy association approach (GAP). In order to validate the performance of the proposed MFPUP scheme we carried out extensive simulations. The proposed LSTM-based mobility model outperforms the DNN model with 92.88% prediction accuracy. Further, our results show that the proposed MFPUP framework associates the optimal number of users to UAVs while also improving 1.25 times users' downlink rates as compared other UAVs placement schemes. © 2023 CCBY.

关键词： Aircraft accidents

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Hybrelastic: a hybrid elasticity strategy with dynamic thresholds for microservice-based cloud applications

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International Journal of Cloud computing 2024年第2期13卷 99-123页

作者： Accorsi, José Augusto da Rosa Righi, Rodrigo Rodrigues, Vinicius Facco da Costa, Cristiano André Singh, Dhananjay Applied Computing Graduate Program Universidade do Vale do Rio dos Sinos RS São Leopoldo Brazil Department of Electronics Engineering Hankuk University of Foreign Studies Yongin17035 Korea Republic of

Microservices-based architectures aim to divide the application’s functionality into small services so that each one of them can be scaled, managed, implemented, and updated individually. Currently, more and more microservices are used in application modelling, making them compatible with resource elasticity. In the literature, solutions employ elasticity to improve application performance;however, most of them are based on CPU utilisation metrics and only on reactive elasticity. In this context, this article proposes the hybrelastic model, which combines reactive and proactive elasticity with dynamically calculated thresholds for CPU and network metrics. The article presents three contributions in the context of microservices: 1) combination of two elasticity policies;2) use of more than one elasticity evaluation metric;3) use of dynamic thresholds to trigger elasticity. Experiments with hybrelastic demonstrate 10.31% higher performance and 20.28% lower cost compared to other executions without hybrelastic. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Elasticity

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On proposing a non-intrusive device and methodology to monitor motor degradation

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Journal of King Saud University - engineering Sciences 2023年第3期35卷 215-223页

作者： Kuhn, Henrique Cafruni da Rosa Righi, Rodrigo Crovato, Cesar David Paredes Electrical Engineering Graduate Program Universidade do Vale do Rio dos Sinos São Leopoldo Brazil Applied Computing Graduate Program Universidade do Vale do Rio dos Sinos São Leopoldo Brazil

Monitoring the degradation of induction motors is an essential concern for industries, especially when there are high costs related to maintenance and their stops. Nowadays, there are many non-invasive ways to monitor the health status of induction motors, including sensors to measure temperature, magnetic field, vibration, current, and power. However, installing these sensors may not be a simple task since intrusive procedures such as engine disassembling, wire separation, and engine interruption are commonly observed. Thus, we propose MUCLA (Multiphase Clamp and Tracking - patent pending) as a new device and methodology for monitoring motor degradation by analyzing its stator current. MUCLA introduces a non-invasive current sensors array on a proposed clamp in the hardware perspective, while a spectral tracking methodology refers to our novelty in the software viewpoint. For end-users, the main MUCLA contribution relies on the combination of the simplicity of installation and the possibility of using the proposed device even when considering Variable-Frequency Drive powered engines. The results obtained with both simulation and practical tests show encouraging results over different input workloads and emulated degradation. Compared to the current initiatives, we can classify MUCLA as a better solution for industrial plants in terms of installation time, installation complexity, and cost. © 2021 The Authors

关键词： Induction motors

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Human-in-the-Loop Evolution of Database Views for Data Exploration

Human-in-the-Loop Evolution of Database Views for Data Explo...

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2023 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2023

作者： de Carvalho, Thiego Buenos Aires Martins, Denis Mayr Lima de Lima Neto, Fernando Buarque Computing Engineering Program University of Pernambuco Recife Brazil Machine Learning and Data Engineering University of Münster ERCIS Münster Germany

ISBN: (纸本)9798350348071

Under the increasingly complex and interconnected world we live in, data has become extremely valuable. Nevertheless, exploring even a simple database is not a trivial task, as it requires technical knowledge which many new and non-technical data users do not have. This task includes writing database queries to retrieve data, uncover insights, and exploit patterns. Furthermore, in large volumes of data, finding valuable data that matches a certain user’s purpose requirement is challenging, especially under restrictive time constraints. Typically, this task is manual, ad-hoc, and time-consuming. To address these challenges, researches have proposed tools to support data exploration tasks, especially by means of View Recommendation. However, current recommendation approaches require enumerating all candidate views that can be defined over an input database. In this work, we introduce a novel view recommendation method that leverages a human-in-the-loop approach to create, evaluate, and tailor views to match user intent. Our experimental evaluation on real-world data demonstrates that our approach suitably recommends views that capture multiple perspectives on the data at hand. © 2023 IEEE.

关键词： Data visualization

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Statistical Device Simulation and Machine Learning of Process Variation Effects of Vertically Stacked Gate-All-Around Si Nanosheet CFETs

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IEEE Transactions on Nanotechnology 2024年 23卷 386-392页

作者： Kola, Sekhar Reddy Li, Yiming Butola, Rajat National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Department of Electronics and Electrical Engineering Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Biomedical Engineering Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation Hsinchu300093 Taiwan

In this study, we report the process variation effect (PVE) including the work function fluctuation (WKF) on the DC/AC characteristic fluctuation of stacked gate-all-around silicon complementary field-effect transistors (CFETs). The PVE affects characteristic fluctuation significantly;in particular, for the variability of off-state current. Owing to the bottom channel of a fin-type, the P-FET suffers from the worst off-state current fluctuation (more than 200% variation) compared to the N-FET. The device variability induced by the WKF is marginal because of amorphous-type metal grains. As input features to an artificial neural network (ANN) model, low and high work function values, as well as parameters of PVE that have prevalent effects on CEFT transfer characteristics are further considered and modeled. The estimated values of R2-score prove that the ANN model properly grasps information from the dataset successfully;thus, it can be used to model emerging CFETs for circuit simulation. © 2002-2012 IEEE.

关键词： Neural networks

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Vision-Based Landing Guidance Through Tracking and Orientation Estimation

Vision-Based Landing Guidance Through Tracking and Orientati...

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2025 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2025

作者： Ferreira, João P. K. Pinto, João P. Moura, Júlia Li, Yi Castro, Cristiano L. Angelov, Plamen Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Brazil School of Computing and Communications Lancaster University United Kingdom

ISBN: (纸本)9798331510831

Fixed-wing aerial vehicles are equipped with functional-ities such as ILS (instrument landing system), PAR (precision approach radar) and, DGPS (differential global positioning system), enabling fully automated landings. How-ever, these systems impose significant costs on airport op-erations due to high installation and maintenance requirements. Moreover, since these navigation parameters come from ground or satellite signals, they are vulnerable to in-terference. A more cost-effective and independent alternative for guiding landing is a vision-based system that de-tects the runway and aligns the aircraft, reducing the pi-lot's cognitive load. This paper proposes a novel frame-work that addresses three key challenges in developing au-tonomous vision-based landing systems. Firstly, to over-come the lack of aerial front-view video data, we created high-quality videos simulating landing approaches through the generator code available in the LARD (landing approach runway detection dataset) repository. Secondly, in contrast to former studies focusing on object detection for finding the runway, we chose the state-of-the-art model Lo-RAT to track runways within bounding boxes in each video frame. Thirdly, to align the aircraft with the designated landing runway, we extract runway keypoints from the re-sulting LoRAT frames and estimate the camera relative pose via the Perspective-n-Point algorithm. Our experimental re-sults over a dataset of generated videos and original images from the LARD dataset consistently demonstrate the proposed framework's highly accurate tracking and alignment capabilities. Our approach source code and the Lo-RAT model pre-trained with LARD videos are available at https://***/jpklock2/vision-based-landing-guidance © 2025 IEEE.

关键词： Global positioning system

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DMSS:An Attention-Based Deep Learning Model for High-Quality Mass Spectrometry Prediction

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Big Data Mining and Analytics 2024年第3期7卷 577-589页

作者： Yihui Ren Yu Wang Wenkai Han Yikang Huang Xiaoyang Hou Chunming Zhang Dongbo Bu Xin Gao Shiwei Sun Key Lab of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190Chinaand with University of Chinese Academy of SciencesBeijing 100049China Syneron Technology Guangzhou 510000China College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China Computer Science Program ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Insitute of Computing Technology Chinese Academy of SciencesBeijing 100190China with Western Institute of Computing Technology Chongqing 400000China

Accurate prediction of peptide spectra is crucial for improving the efficiency and reliability of proteomic analysis,as well as for gaining insight into various biological *** this study,we introduce Deep MS Simulator(DMSS),a novel attention-based model tailored for forecasting theoretical spectra in mass *** has undergone rigorous validation through a series of experiments,consistently demonstrating superior performance compared to current methods in forecasting theoretical *** superior ability of DMSS to distinguish extremely similar peptides highlights the potential application of incorporating our predicted intensity information into mass spectrometry search engines to enhance the accuracy of protein *** findings contribute to the advancement of proteomics analysis and highlight the potential of the DMSS as a valuable tool in the field.

关键词： mass spectrometry proteomics machine learning deep learning

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