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检索条件"任意字段=23rd International Conference on Computer Systems and Technologies, CompSysTech 2022"

共 802 条记录，以下是281-290 订阅

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Three-level Compact Caching for Search Engines Based on Solid State Drives 23

Three-level Compact Caching for Search Engines Based on Soli...

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23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data Science and systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Zhang, Rui Sun, Pengyu Tong, Jiancong Zang, Ruirui Qian, Heng Pan, Yu Stones, Rebecca J. Wang, Gang Liu, Xiaoguang Li, Yusen College of Computer Science Nankai University Tianjin China Tianjin Key Laboratory of Network and Data Security Technology Tianjin China Baidu Inc Beijing China

ISBN: (纸本)9781665494571

The query processing in search engines can be classified into either disk I/O operations and CPU computation operations. Conventional search engine caching methods mostly aimed at reducing disk I/O operations. However, with the new trend of using solid state drives (SSDs) instead of hard disk drives for search engine storage, the bottleneck of query processing shifts from disk I/O to computation. In this paper, we design a three-level compact caching structure suited to SSD-based search engines, incorporating caches for (a) doculets, partial documents which contain previously encountered snippets, (b) fragments, compact data structures containing snippet metadata, and (c) ranked docID lists, which index the top-k documents relevant to a query. This three-level compact caching method aims at reducing the bottleneck of repetitive CPU computation operations. Moreover, by considering different levels of caches as a whole system, the proposed three-level compact caching eliminates the redundancy among cache items. This increases the efficiency of cache space utilization. Experimental results indicate an improvement in query response latency by a factor of around 2.6 when using static caching and 1.3 under dynamic caching. © 2021 IEEE.

关键词： Costs Solid state drives Smart cities Query processing Redundancy Search engines Metadata

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MetaProfiling: Inferring User Profiles with Few-Shot Data 23

MetaProfiling: Inferring User Profiles with Few-Shot Data

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作者： Sun, Yueqi Guo, Bin Li, Nuo Ouyang, Yi Li, Xiaona Xie, Jiayu Wang, Zhu Yu, Zhiwen Northwestern Polytechnical University School of Computer Science Xi'an710129 China

ISBN: (纸本)9781665494571

Inferring user profiles plays a pivotal role in various real-world scenarios. The rapid development of the online social media enables user profiling based on their interacted data. However, some user profiles are diverse and constantly changing. On the one hand, a number of new occupations are emerging, but only with few labeled users. This often leads to the class imbalance problem. On the other hand, there are some similar occupation classes which are difficult to distinguish. These issues bring new challenges to build the user profiles. In this paper, we propose a novel model, named MetaProfiling, to solve the few-shot user profiling problem, i.e., distinguishing occupation classes with few labeled users. Firstly, we extract multi-field features from multi-faceted user information, including user personal attributes and behavior attributes, to characterize users from different aspects. Then, we design a user embedding generator to learn an effective user embedding space by using the feature attention layer and the user embedding fusion layer. Finally, we design a margin-based user profiling classifier to effectively distinguish users from different classes, especially for the similar classes. Specifically, the classifier can enlarge the margin between the similar classes. Experiments on a real-world dataset from a question answering community validate that our approach can consistly outperform many baseline methods under both standard and generalized few-shot learning settings. © 2021 IEEE.

关键词： Social networking (online) Feature extraction Generators Data models Behavioral sciences Data mining Standards

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Lane-Level Traffic Flow Prediction Based on Dynamic Graph Generation 23

Lane-Level Traffic Flow Prediction Based on Dynamic Graph Ge...

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作者： Wang, Lingyun Shen, Guojiang Yu, Kaifeng Ji, Zhanhao Kong, Xiangjie College of Computer Science and Technology Zhejiang University of Technology Hangzhou China

ISBN: (纸本)9781665494571

The Intelligent Transportation System (ITS) plays a critical role in the development of smart cities, and the traffic control capability of ITS requires accurate traffic flow prediction as the footstone. Due to the neglect of the dissimilarities between lanes, existing traffic flow prediction methods like T-GCN are intractable to capture the dynamic changes of traffic flow direction, lane relationship, etc. Therefore, studies are shifting their concern to lane-level traffic flow prediction for tackling with more complicated scenarios. However, how to handle temporal-spatial correlation and model heterogeneous data effectively is still a challenge. In this paper, we propose a heterogeneous graph convolution model based on dynamic graph generation to address the issue. The model consists of three components. The internal graph convolution network captures the real-time spatial dependency between lanes in terms of generated dynamic graphs. The external heterogeneous data fusion network comprehensively considers other parameters such as lane speed, lane occupancy, and weather conditions. The codec neural network utilizes a temporal attention mechanism to capture the deep temporal dependency. Substantial experiments based on two real-world datasets indicate that the proposed heterogeneous graph convolution model can improve prediction accuracy. © 2021 IEEE.

关键词： Codecs Convolution Smart cities Roads Road side unit Transfer learning Data integration

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Mutual Information-Based Feature Selection for Federated Learning Environments 23

Mutual Information-Based Feature Selection for Federated Lea...

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23rd IEEE international conference on Machine Learning and Applications, ICMLA 2024

作者： Suárez-Marcote, Samuel Morán-Fernández, Laura Bolón-Canedo, Verónica Universidade da Coruña Citic Department of Computer Science and Information Technologies A Coruña Spain

ISBN: (纸本)9798350374889

Due to the growth of Internet of Things devices, the dimensionality of the data has only increased. These devices generate a large amount of data which, after being processed, is one of the main sources of information for machine learning systems. However, only a small part of this data is truly relevant. Understanding the relevance of this data allows us to process it at the edge of the network and improve the performance of Artificial Intelligence systems. On the one hand, feature selection is one of the most common approaches to reducing irrelevant features. On the other hand, federated learning allows the exploitation of such data by machine learning models without the need to exchange raw data. Therefore, in this paper we present modifications to two widely utilised feature selection algorithms based on the Mutual Information metric to enable them to work in a federated environment. The experimental process conducted on several datasets and data distributions demonstrates the capability of our modifications to operate in such an environment without a loss of information. This enhances execution time and leverages specific particularities of these environments, such as increased security. © 2024 IEEE.

关键词： Federated learning

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Optimal deployment design of repeaters and memories in quantum networks 23

Optimal deployment design of repeaters and memories in quant...

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作者： Yao, Jiangyuan Zou, Kaiwen Li, Deshun Jiang, Zheng School of Computer Science and Technology Hainan University Haikou China School of Cyberspace Security Hainan University Hainan China

ISBN: (纸本)9781665494571

In quantum communication networks, the transmission success rate of entangled photons decreases exponentially with the transmission distance in fiber channel. With quantum repeaters, quantum networks can realize arbitrary long-distance links based on quantum entanglement swapping, quantum storage, and quantum teleportation. Thanks to the development of quantum memory technology, the throughput of quantum relay networks can be improved by increasing the number of quantum memories. In this paper, we study the routing metric, the goal of which is to achieve a higher throughput in a long-distance quantum network by reasonably allocating repeater positions with a given memory count between source and destination. A routing metric E was proposed, where the number and distance range of repeater deployments can be obtained by numerical analysis to support an optimal network throughput. According to the above principle, various repeaters were deployed on a linear quantum network to test the effectiveness of the proposed allocation mechanism with the given transmission loss, Bell-State Measurement (BSM) success rate, memory quantity, and distance. The results of evaluation show that increasing the number of repeaters blindly can lead to a waste of resources and a throughput decreasing, which implies that repeaters need to be placed at an appropriate deployment distance to achieve the optimal performance. © 2021 IEEE.

关键词： Quantum entanglement Smart cities Relay networks (telecommunication) Teleportation Repeaters Throughput Routing

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Impact of Aging on Dielectric Properties of Oil-Paper Insulation System using Gas-to-Liquid Oil and Mineral Oil 23

Impact of Aging on Dielectric Properties of Oil-Paper Insula...

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23rd international Middle East Power systems conference, MEPCON 2022

作者： Emara, Manal M. Atiya, Eman G. Mansour, Diaa-Eldin A. Kafrelsheikh University Faculty of Engineering Department of Electrical Engineering Kafrelsheikh Egypt Tanta University Faculty of Engineering Department of Electrical Power and Machines Engineering Tanta Egypt School of Electronics Communications and Computer Engineering Electrical Power Engineering Department Egypt-Japan University of Science and Technology Alexandria Egypt Tanta University Faculty of Engineering Electrical Power and Machines Engineering Department Tanta Egypt

ISBN: (纸本)9781665463638

Lately, gas-to-liquid (GTL) oil usage has a great trend as cooling and dielectric medium in power transformers due to their good properties, represented by its purity, chemical uniformity, and better performance than conventional oils. By the way, the study of GTL oil effect in comparison to conventional mineral oil (MO) on the electrical properties of the insulation paper under thermal aging is presented in this paper. Thermal aging samples were obtained based on an accelerated thermal aging test in the laboratory, that simulates the thermal stress in the service. Two different aging durations (i.e., 3 and 6 days) are applied to the two different oil types. Pure oils and aged oil samples were tested for dielectric losses and dielectric constant for a range of frequencies from 20 Hz to 2 MHz. In addition, insulation papers were impregnated in the same samples to check their effect by thermal aging. The results indicated that aging has a lower impact on the properties of GTL oil and GTL oil-paper insulation under aging conditions compared to that of MO. © 2022 IEEE.

关键词： Thermal aging

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Digital Guardians: Enhancing Women’s Security with Artificial Intelligence and IoT 23th

Digital Guardians: Enhancing Women’s Security with Artifici...

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23rd international conference on Intelligent systems Design and Applications, ISDA 2023

作者： Arya, Leena Sharma, Yogesh Kumar Kumar, Ramakrishna Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP Guntur India College of Engineering National University of Science and Technology Muscat Oman

ISBN: (纸本)9783031646492

In the contemporary global context, women encounter various challenges, notably harassment. While numerous devices and methods have been proposed to improve women’s security, many still require manual operation. These devices rely on human intervention, making it crucial to ensure women’s online safety and security. This paper explores innovative approaches to enhance women’s digital security by combining Artificial Intelligence (AI) and the Internet of Things (IoT). The goal is to empower women in their online spaces and bolster their digital experiences. The paper begins by highlighting the unique cybersecurity challenges that women face, including online harassment, stalking, privacy breaches, and gender-based digital threats. These challenges have real-world consequences for women’s well-being and personal safety, extending beyond the digital realm. Concurrently, IoT devices such as wearables, intelligent surveillance systems, and environmental sensors provide valuable context-aware data. This data enhances the accuracy and depth of threat detection, providing a comprehensive understanding of the digital landscape. The paper underscores the ethical and legal aspects of deploying AI and IoT technologies to safeguard women’s security. Responsible practices encompass a range of measures, including robust data protection protocols, privacy safeguards, and a dedicated commitment to transparent technology implementations. The effectiveness of these proposed AI and IoT-powered security solutions is demonstrated through practical implementations and vivid case studies. These real-life examples illustrate how women can regain control over their online interactions and personal data, creating a safer and more empowering digital environment. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Internet of things

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GranDIHC-BR 2025-2035 - GC4: Sociocultural Aspects in Human-computer Interaction 24

GranDIHC-BR 2025-2035 - GC4: Sociocultural Aspects in Human-...

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23rd Brazilian Symposium on Human Factors in Computing systems, IHC 2024

作者： Neris, Vânia P.A. Pereira, Vinicius Carvalho Rosa, Jean Clemisson Santos Galvão, Vinícius F. Maciel, Cristiano Arruda, Isabela L. Department of Computing Federal University of São Carlos São Carlos São Paulo Brazil Letras Federal University of Mato Grosso Mato Grosso Cuiabá Brazil ITI LARSys Sergipe Aracaju Brazil Uninassau AJU Sergipe Aracajú Brazil ICMC University of São Paulo São Carlos São Paulo Brazil IC Federal University of Mato Grosso Mato Grosso Cuiabá Brazil IC University of Goias Goiás Goiânia Brazil

ISBN: (纸本)9798400712241

This paper addresses sociocultural aspects as a Grand Challenge for Research in Human-computer Interaction in Brazil for 2025-2035. The challenge considers the sociocultural diversity involved in the design, implementation, evaluation, and use of interactive computational artifacts. The current scenario reveals a gap between technological solutions and the real needs of various sociocultural groups. The challenge herein described includes the creation or adaptation of tools that respect sociocultural plurality, impacting both the creation of interactive computational artifacts and the education of conscious and critical professionals. This challenge arises from the need for technologies that do not discriminate against, exclude, or harm social groups, and that are developed in a responsible, conscious, ethical, and sustainable manner. Failing to meet this challenge could lead to the formation of technological "bubbles" that promote oppressive views, diminish human capabilities, and prioritize technocapitalist interests over human concerns. In response, we suggest short-, medium-, and long-term actions, emphasizing awareness, research, and continuous monitoring. Therefore, the challenge of considering sociocultural aspects in Human-computer Interaction aims to transform the relationship between interactive computational artifacts and society, promoting inclusion and positive impact through technological solutions that respect and represent human diversity. © 2024 Copyright held by the owner/author(s).

关键词： Ethical technology

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Intelligent Control for Wind Turbines Connected to Utility Grid using MPC 23

Intelligent Control for Wind Turbines Connected to Utility G...

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23rd international Middle East Power systems conference, MEPCON 2022

作者： Al-Gabalawy, Mostafa Salama, Mohamed M. M. Abdel-Sattar, Ibrahim A. Darwish, Mohamed M. F. El-Safwa High Institute of Engineering Department of Electronic Communication and Computer Engineering Cairo Egypt Benha University Faculty of Engineering at Shoubra Department of Electrical Engineering Cairo Egypt Aalto University Department of Electrical Engineering and Automation Espoo Finland

ISBN: (纸本)9781665463638

Traditional methods for controlling wind turbines often rely on accurate modelling techniques to ensure reliable and productive interaction between the wind farms and the primary electricity grids in both grid-connected and autonomous modes. Additionally, because of the unpredictable and irregular wind speed, its natural output power behaves significantly erratically. Furthermore, to avoid the negative effects of excessive fluctuation in wind turbine output power in the wind farm besides the power grid, it is essential to properly estimate, plan, and manage the wind farm output power. In addition, the transmission of the control signal can leave a gap between itself and the wind energy conversion systems (WECS) due to the communication channels' time delay, which makes the WECS operation unstable. Specifically, when running over the permitted wind speed, wind energy conversion devices frequently pitch, which reduces the mechanical power to the rated level at the price of the blade, and drives shaft loads. In this regard, this paper suggests an intelligent control system for the synchronous generator wind turbines using the model predictive controller (MPC). The results highlighted the suggested controller's greater performance against changes in wind speed rather than PI controller. Further, the coordination of pitch/torque sharing depend on the analysis performed, both generator power output quality, in addition load circumstances are maximized in a variable-weight MPC technique. © 2022 IEEE.

关键词： Model predictive control

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Means to Support the Ends: Forums that Escape the Official Gaze in the Educational Institutions 23

Means to Support the Ends: Forums that Escape the Official G...

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23rd international Arab conference on Information Technology, ACIT 2022

作者： Ghandour, Ahmad Woodford, Brendon J. Almutairy, Alhanof Al-Srehan, Hussein Salem College of Business Al Ain University Abu Dhabi United Arab Emirates School of Business University of Otago Dept. of Info Science Dunedin New Zealand College of Computer Science and Information Technology King Faisal University Dept. of Information Systems Al-Ahsa Saudi Arabia College of Education Humanities and Social Sciences Al Ain University Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350320244

Social networking apps like WhatsApp are very useful for the learning process as they enable the students to experience a new learning environment during and after the class. Specifically, WhatsApp has an amazing feature to create private groups for bounding the participant. The use of WhatsApp on university campuses enables students to be in touch with study updates. By using WhatsApp, students can contact their class fellows at any time and share data in text, image, video and audio formats. Students can help each other to complete course work including assignments, presentations, and group projects. WhatsApp makes communication easy between students to students and students to teachers. By using WhatsApp's, friendly and familiar interface teachers can run their lectures online and students can achieve their learning goals. Motivated by WhatsApp feature set, the main purpose of this research is to explore the learning outcomes achieved by students when using WhatsApp in a class group chats © 2022 IEEE.

关键词： Students

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