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37th International Conference on Advanced Information Networking and Applications, AINA 2023

作者： da Silva de Oliveira, Filipe Pillon, Maurício Aronne Miers, Charles Christian Koslovski, Guilherme Piêgas Graduate Program in Applied Computing Santa Catarina State University Santa Catarina Joinville Brazil

ISBN: (纸本)9783031284502

Data centers have networks that provide, for a large number of users, various services such as video streaming, financial services, file storage, among others. Like any network-based system, a Data Center (DC) is subject to congestion, a fact that can cause slowness and instability, affecting the performance of applications for end users. Among the technologies for data center management, Software Defined Networking (SDN) separate the control from the data plane, allowing applications to access statistical information and other details about current state of the network through a controller. In this sense, SDN brings a new opportunity to detect congestion on DC networks in a centralized manner. However, identifying the occurrence of congestion in networks is an arduous task due to the high number of related data. With these data, this work seeks to apply supervised classification to identify congestion events. The experimental campaign demonstrated that the SDN-based supervised classification mechanisms find more congestion events then the native congestion control algorithms from Transmission Control Protocol (TCP). Moreover, among diverse supervised algorithms, we demonstrate which one has better accuracy and efficient performance when analyzing Cubic and DCTCP variants. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Transmission control protocol

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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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GOTE: An Edge computing Architecture for Mobile Gaming 25

GOTE: An Edge Computing Architecture for Mobile Gaming

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25th International Conference on Enterprise Information Systems, ICEIS 2023

作者： Robaina, Gabriel Fiorese, Adriano Graduate Program in Applied Computing - PPGCAP Santa Catarina State University - UDESC Joinville Brazil

ISBN: (纸本)9789897586484

The mobile games market has grown in relevancy compared to traditional gaming platforms. The standard architecture for these games requires the processing of game logic and graphics using the device's own hardware. Alternatively, cloud based architectures for remote gaming on smartphones present high game input delay at a high cost for the service provider. This poses a limitation to the variety and complexity of games that target these platforms as well as constraining user QoE. To address that limitation, this work proposes the Gaming On The Edge (GOTE) architecture, that aims to enable complex games to be played on smartphone devices while leveraging edge computing infrastructure into graphics processing and content distribution systems. A GOTE architecture's proof of concept is developed and tested using WebRTC with an RTP streaming pipeline that exploits NVENC for achieving low latency video encoding. Experimental results show that GOTE architecture is a viable alternative to cloud based remote gaming on smartphones at the advantage of lowering latency of video and game input. An open source implementation of the architecture is provided in order to assist further research in this area. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Edge computing

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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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Adding Argumentation into Human Evaluation of Long Document Abstractive Summarization: A Case Study on Legal Opinions 4

Adding Argumentation into Human Evaluation of Long Document ...

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4th Workshop on Human Evaluation of NLP Systems, HumEval 2024

作者： Elaraby, Mohamed Xu, Huihui Gray, Morgan Ashley, Kevin Litman, Diane Department of Computer Science School of Computing and Information United States Learning Research and Development Center United States Intelligent Systems Program School of Computing Information University of Pittsburgh PittsburghPA United States

ISBN: (纸本)9782493814418

Human evaluation remains the gold standard for assessing abstractive summarization. However, current practices often prioritize constructing evaluation guidelines for fluency, coherence, and factual accuracy, overlooking other critical dimensions. In this paper, we investigate argument coverage in abstractive summarization by focusing on long legal opinions, where summaries must effectively encapsulate the document’s argumentative nature. We introduce a set of human-evaluation guidelines to evaluate generated summaries based on argumentative coverage. These guidelines enable us to assess three distinct summarization models, studying the influence of including argument roles in summarization. Furthermore, we utilize these evaluation scores to benchmark automatic summarization metrics against argument coverage, providing insights into the effectiveness of automated evaluation methods. © 2024 European Language Resources Association (ELRA).

关键词： Human Evaluation Legal Summarization Summarization

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Analysis of Factors Influencing the Buyer Preferences on Goods and Services: Comparing E-Commerce and Retail Stores 6

Analysis of Factors Influencing the Buyer Preferences on Goo...

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Siek, Michael Tadjoedin, Pasha Business Information Systems Program Information Systems Department Faculty of Computing and Media Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798331539603

E-commerce is a type of businesses or individuals doing transactions through the internet, which continues to be improved to perform its tasks with more features and facilities compared to physical and brick and mortar stores. Customers is getting used to shop their wanted products in e-commerce due to convenient, practical, and useful. Specifically, during the Covid-19 pandemic, purchasing goods via e-commerce without physical contact and during lockdowns is most preferable. The research aimed at finding the crucial factors influencing the buyer preferences on goods and services by comparing ecommerce and retail stores using quantitative methods. A modified research framework was developed by considering the existing technology acceptance model and other factors related to purchasing cloths and foods. The collected response data was analyzed and modelled using structural equation model with partial least square algorithm. The modelling results showed that most assessed responses indicate a positive perception of ecommerce. The factors of buyer preference on e-commerce are mainly due to faster product searching with competitive pricing. The research results provide important information and strategies for businesses on how to sell particular products to the customers. © 2024 IEEE.

关键词： Marketplaces

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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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Compact Model Build Upon Dynamic Weighting Artificial Neural Network Approach for Complementary Field Effect Transistors

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IEEE Transactions on Electron Devices 2024年第1期71卷 246-253页

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

In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SPICE simulations for cost-effectiveness. This methodology is developed for gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field effect transistor (CFET), a potential candidate for future CMOS technology due to its innate properties. The critical process variation (PV) sources that severely degrade the CFET performance are estimated using DW-ANN. It reduces the computation cost and predicts the effects of PV sources with less than 1% error. Furthermore, a compact DW-ANN-based Verilog-A model has been developed that captures the dc as well as transient behavior accurately for circuit-level analysis. CFET-based circuits such as inverter, 6T-static random access memory (SRAM), and ring oscillator (RO) are characterized and implemented using DW-ANN-based CM. The overall average error of the model is reported as less than 2%. Therefore, the proposed device and circuit modeling approach provides a feasible solution for the rapid compact modeling of new emerging devices with good convergence and high accuracy. © 1963-2012 IEEE.

关键词： Neural networks

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Determining environmental indicators related to the propagation of contagious diseases and health issues: A Systematic Literature Review 18

Determining environmental indicators related to the propagat...

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18th Iberian Conference on Information Systems and Technologies, CISTI 2023

作者： Portillo, Janeth Dominguez Peralta, Laura M. Rodriguez Sampaio, Paulo N. M. Nunes, Eldman De Oliveira Faculty of Information Technologies and Data Science Mexico Graduate Program in Computing and Systems Bahia Salvador Brazil

ISBN: (纸本)9789893347928

The environmental indicators provide significant information in order to describe the state of a phenomenon, environment or area [1]. This paper addresses the indicators present in the air and their relationship in the accommodation and transmission of viruses, as well as how these environmental indicators can lead to health problems. Therefore, the main goal of this work is to review the scientific contributions in the literature in order to determine and select the potential environmental indicators present in indoor environments which have an impact on the health of people who work and live within these spaces. For this purpose, we carried out a Systematic Literature Review (SLR) related to environmental monitoring, COVID-19, Internet of things, air pollution and environmental indicators within indoor spaces. This SLR allowed us to identify indicators that according to their level of presence can represent a high risk for people's health. Therefore, the process of planning, conducting and reporting the Systematic Literature Review enabled us not only to identify some environmental indicators, but also their corresponding monitoring advantages and disadvantages, and multiple perspectives and approaches of each contribution in the literature. Further on, this study will be the basis for the proposal of an automatic and intelligent platform based on Internet of Things for monitoring indoor environments in order to detect high risk levels for the contamination of contagious diseases. © 2023 ITMA.

关键词： COVID-19

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Developing Accurate Prediction Model Using Machine Learning and Business Intelligence on University Students GPA 6

Developing Accurate Prediction Model Using Machine Learning ...

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Siek, Michael Lim, Kenrick Business Information Systems Program Information Systems Department School of Computing and Creative Arts Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798331539603

It has been challenging to determine students' grades and performances throughout college. The purpose of this study is to raise students' performance during each semester and guarantee satisfactory course completion with the use of accurate models for predicting student GPA. The process is using the dataset of student GPA in the first year of university as an input for the machine learning model. Then, using the dataset to develop prediction models such as Linear regression, Decision Tree, Fully Dense Neural Network and MLP. Lastly, results are evaluated using proper evaluation measures. This research provides an accurate prediction model with the usage of machine learning algorithms for predicting Students GPA. As it happens, the linear Regression Model has the best result with 0.1396 on the MSE and 0.3736 on the RMSE. By doing so, Students can then view their GPA to determine and strategize on how they might raise it in the upcoming semester as well as for academic advisor to give more accurate strategy and actions to the students to obtain a good study performance. Because graduates who have high GPAs can start their professions off well and have big opportunities in the foreseeable future. © 2024 IEEE.

关键词： Prediction models

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