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检索条件"任意字段=Proceedings of the 9th Knowledge-Based Software Engineering Conference"

共 20366 条记录，以下是4711-4720 订阅

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pFedES: Generalized Proxy Feature Extractor Sharing for Model Heterogeneous Personalized Federated Learning 39

pFedES: Generalized Proxy Feature Extractor Sharing for Mode...

引用

39th Annual AAAI conference on Artificial Intelligence, AAAI 2025

作者： Yi, Liping Yu, Han Ren, Chao Wang, Gang Liu, Xiaoguang Li, Xiaoxiao College of Computer Science TMCC SysNet DISSec GTIISC Nankai University China College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Computer Engineering The University of British Columbia Canada Vector Institute Canada

ISBN: (纸本)157735897X

Federated learning (FL), as a privacy-preserving collaborative machine learning paradigm, has attracted significant interest from industry and academia. To allow each data owner (FL client) to train a heterogeneous and personalized local model based on its local data distribution, system resources and requirements on model structure, the field of model-heterogeneous personalized federated learning (MHPFL) has emerged. Existing MHPFL approaches either rely on the availability of a public dataset with special characteristics to facilitate knowledge transfer, incur high computational and communication costs, or face potential model leakage risks. To address these limitations, we propose a model-heterogeneous personalized Federated learning approach based on generalized proxy feature Extractor Sharing (pFedES) for supervised image classification tasks. (1) We devise a shared small proxy homogeneous feature extractor before each client’s heterogeneous local model. (2) Clients train them via the proposed iterative learning to enable the exchange of global generalized knowledge and local personalized knowledge. (3) the small proxy local homogeneous extractors produced after local training are uploaded to the server for aggregation to facilitate knowledge fusion across clients. We theoretically prove pFedES converges with a non-convex convergence rate O(1/T). Experiments on 3 benchmark datasets against 9 baselines demonstrate that pFedES performs state-of-the-art model accuracy while maintaining efficient communication and computation. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Federated learning

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Performance evaluation of listed logistics enterprises based on DEA 9

Performance evaluation of listed logistics enterprises based...

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9th International Symposium on Project Management, ISPM 2021

作者： Zhang, Xuemei Hu, Jiawei Ma, Chenhao Chen, Haoran Shi, Wei Business School Fuyang Normal University Fuyang Anhui236037 China Anhui Provincial Key Laboratory of Regional Logistics Planning and Modern Logistics Engineering Fuyang Normal University Fuyang Anhui236037 China

ISBN: (纸本)9781921712777

through the establishment of a DEA cross-evaluation model, the performance of 10 listed logistics enterprises in China from 2010 to 2020 is evaluated. the study found that the number of DMU1, DMU3, DMU4 and DMU9 with a larger average cross-evaluation value accounted for a larger proportion in 2010-2020, and these four decision-making units were better. DMU2, DMU3 and DMU4 these three enterprises on the overall performance showed a fluctuating upward trend, and DMU3 increased the fastest. Except for DMU6, DMU7, DMU8, and DMU10, the average performance of the six enterprises was higher than the overall performance average, and the enterprise had the highest operational efficiency, and DMU3 had the highest average performance, ranking number and the enterprise is the best. Except for the enterprise DMU10, the overall efficiency of the 9 enterprises is not very different, and there is more room for improvement. © ISPM *** right reserved.

关键词： Decision making

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An improved approach: Adaptive learning for high-speed data encryption of low-earth orbit (LEO) satellites 9

An improved approach: Adaptive learning for high-speed data ...

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9th International conference on Digital Technologies in Education, Science and Industry, DTESI 2024

作者： Bakyt, Makhabbat Spada, Luigi La Atanov, Sabyrzhan Moldamurat, Khuralay Moldakhanov, Mansur L.N. Gumilyov Eurasian National University Astana010000 Kazakhstan School of Computing Engineering and the Built Environment Edinburgh Napier University 10 Colinton Road EdinburghEH10 5DT United Kingdom LLP Samira Pavlodar140000 Kazakhstan

this paper examines the critical problem of ensuring data security in low-Earth orbit (LEO) satellite communication systems, where resources are limited, and the risk of cyberattacks is heightened. An innovative approach to continuous user authentication is proposed, based on adaptive machine learning using logistic regression and support vector machines, combined with robust cryptographic protocols. the study's primary goal is to develop a lightweight and efficient encryption method that guarantees a high level of data security without significantly increasing the computational load on LEO satellite onboard systems. the article analyzes existing continuous authentication methods and identifies their vulnerabilities, such as dependence on specific features, scalability issues, and susceptibility to targeted attack scenarios. the proposed approach is based on the adaptive sliding window method, which allows dynamic adaptation to changes in user behavior and effectively detects anomalies indicating potential unauthorized access attempts. To safeguard data, the study proposes using functional encryption and decentralized key generation, enhancing the system's resilience to various types of attacks. Preliminary simulation results using mouse movement data demonstrate that the proposed approach achieves high anomaly detection accuracy (over 80%) with minimal computation time (less than 9 ms). this method can be applied to protect data in various communication systems with LEO satellites, including flight control, telemetry, and data transmission systems. © 2023 Copyright for this paper by its authors.

关键词： Authentication

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Extraction of key information from Chinese text of gas station safety accident cases 22

Extraction of key information from Chinese text of gas stati...

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proceedings of the 2022 5th International conference on Machine Learning and Natural Language Processing

作者： Heng Li School of Software and Artificial Intelligence Chongqing Institute of Engineering China

ISBN: (纸本)9781450399067

Keyword matching-based text structuring of gas station safety accident cases can automatically perform keyword extraction and store them in the database, and then the structured data can be subjected to multi-dimensional statistics, visual analysis, knowledge graph management and law mining. 516 cases of gas station safety accidents since 1981, which belong to unstructured electronic text data, were collected in four ways. through the establishment of a keyword dictionary, 516 case texts were extracted and stored in a structured way using a progressive model of exact matching, phrase matching and intelligent matching+manual verification. the actual evaluation results show that the success rate of exact matching is 30% - 87%, the cumulative success rate of phrase matching is 70% - 100%, the cumulative matching rate of intelligent matching+manual verification is 91% - 100%, the overall matching effect is good, and the method is practical and useful.

关键词： Chinese text of safety accident cases Phrase matching Intelligent matching Exact matching Keyword extraction

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VitaApp: Augmentative and Alternative Communication System Aimed at Older Adults 9th

VitaApp: Augmentative and Alternative Communication System A...

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9th Information and Communication Technologies conference of Ecuador (TICEC)

作者： Cedillo, Priscila Collaguazo-Malla, Christian Sanchez, William Cardenas-Delgado, Paul Prado-Cabrera, Daniela Univ Cuenca Cuenca Azuay Av 12 Abril S-N Cuenca Ecuador

ISBN: (纸本)9783030899417;9783030899400

Augmentative and Alternative Communication Systems (AACs) is an important study area for people who need alternative ways to communicate their ideas. An AAC web system based on pictograms for the elderly VitaApp is presented in this paper. the system results from the implementation of the last phase of theUIAAC method, which guides the design and implementation ofAAC systems aimed at older adults. VitaApp is based on a client-server architecture, divided into three roles: a) administrator, carer: these oversee customizing the interface and have dedicated web applications;b) elderly: they use the AAC application that their caregiver personalizes for them. the graphical interface of the AAC application is evaluated through a case study that was applied to an older adult, his caregiver, and a clinical psychologist;in this, the ease of use, usefulness, and future use of the web application were evaluated. the results show that its users perceive VitaApp as an alternative communication support tool, useful, easy to use, and considered to be used in the future.

关键词： AAC Web application Elderlies software engineering User interfaces

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ARIMA vs LSTM on NASDAQ stock exchange data 26

ARIMA vs LSTM on NASDAQ stock exchange data

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26th International conference on knowledge-based and Intelligent Information and engineering Systems, KES 2022

作者： Kobiela, Dariusz Krefta, Dawid Król, Weronika Weichbroth, Pawel Gdansk University of Technology Gabriela Narutowicza 11/12 Gdansk80-233 Poland Gdansk University of Technology Faculty of Electronics Telecommunications and Informatics Department of Software Engineering Gabriela Narutowicza 11/12 Gdansk80-233 Poland

this study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange. Research shows which model performs better in terms of the chosen input data, parameters and number of features. the chosen models were compared using the relative metric mean square error (MSE) and mean absolute percentage error (MAPE). Selected metrics are typically used in regression problems. the performed analysis shows which model achieves better results by comparing the chosen metrics in different models. It is concluded that the ARIMA model performs better than the LSTM model in terms of using just one feature - historical price values - and predicting more than one time period, using the p, q parameters in the range from 0 to 2, Adam optimizer, tanh activation function, and 2xLSTM layer architecture. the longer the data window period, the better ARIMA performs, and the worse LSTM performs. the comparison of the models was made by comparing the values of the MAPE error. When predicting 30 days, ARIMA is about 3.4 times better than LSTM. When predicting an averaged 3 months, ARIMA is about 1.8 times better than LSTM. When predicting an averaged 9 months, ARIMA is about 2.1 times better than LSTM. © 2022 the Authors. Published by Elsevier B.V.

关键词： Forecasting

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CompanyName2Vec: Company Entity Matching based on Job Ads

CompanyName2Vec: Company Entity Matching based on Job Ads

引用

International conference on Data Science and Advanced Analytics (DSAA)

作者： Ran Ziv Ilan Gronau Michael Fire Efi Arazi School of Computer Science Reichman University Department of Software and Information Systems Engineering Ben-Gurion University

ISBN: (纸本)9781665473316

Entity Matching is an essential part of all real-world systems that take in structured and unstructured data coming from different sources. Typically no common key is available for connecting records. Massive data cleaning and integration processes require completion before any data analytics, or further processing can be performed. Although record linkage is frequently regarded as a somewhat tedious but necessary step, it reveals valuable insights, supports data visualization, and guides further analytic approaches to the data. Here, we focus on organization entity matching. We introduce CompanyName2Vec, a novel algorithm to solve company entity matching (CEM) using a neural network model to learn company name semantics from a job ad corpus, without relying on any information on the matched company besides its name. based on a real-world data, we show that CompanyName2Vec outperforms other evaluated methods and solves the CEM challenge with an average success rate of 89.3%.

关键词： Couplings Semantics Neural networks Data visualization Companies Data science Cleaning

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Proposal for a software development framework based on the ISO/IEC 29110 standard: Public organizations 9

Proposal for a software development framework based on the I...

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9th International conference on software Process Improvement (CIMPS)

作者： Faustino, Israel Mejia, Jezreel Ctr Invest Matemat AC Unidad Zacatecas Calle Lasec & Andador Galileo GalileiManzana 3 Zacatecas 98160 Zacatecas Mexico

ISBN: (纸本)9781665403764

In software engineering there are several methods, methodologies, standards or frameworks, which allow the development of better quality software or with less expenditure of resources. However, the context of each organization must be taken into account in order to make the correct choice of any of them. In the case of very small entities (less than 25 people), they also face other problems, such as the limited amount of resources available. In public sector organizations that are in charge of software development or operation and services the same problems are identified. In addition, there are a number of laws or regulations that they must comply with, such as MAAGTICSI. therefore, this article shows the proposal of a framework for software development based on the ISO/IEC 29110 standard for public sector organizations that aims to help improve their processes for software management and development. In order to establish this proposal, the main standards and methodologies that are applied in public organizations in Mexico were identified, as well as, some related works that show how some standards and methodologies are implemented in small organizations.

关键词： software development ISO/IEC 29110 SCRUM Government sector MAAGTICSI

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the Human Mind and engineering Models 9th

The Human Mind and Engineering Models

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9th International conference on Culture and Computing (C&C) part of the 23rd International conference on Human-Computer Interaction (HCI)

作者： Canas, Jose J. Univ Granada Mind Brain & Behav Res Ctr Granada 18071 Spain

ISBN: (纸本)9783030774301;9783030774318

the design of systems where people and machines interact is an area where engineers work together with psychologists, sociologists, anthropologists, and other social scientists who are experts in the structure and functioning of the cognitive system and the laws of human behaviour. Both groups of experts collaborate in designing the machines and the interaction between machines and human beings. In this collaborative work, several assumptions are made, among which one of the more important is that it is possible to model the human cognitive system and its behaviour independently of the context of the interaction because these are assumed to be relatively fixed and only modifiable by evolution and learning processes. based on this assumption, a methodology is followed in which social scientists model the human cognitive system independently of the context and, based on this modelling, they bring human knowledge into the design process. However, there is evidence that the characteristics and functioning of the human cognitive system are not independent of conditions of interaction. Revisiting this assumption may have important consequences for how we design machines and how humans interact with them. Above all, if the assumption is reviewed, it would mean that it is not possible to expect that the human sciences can model the human cognitive system independently of the context of the interaction. As a consequence of this, cultural aspects of interaction must also be taken into account when modelling the functioning and characteristics of the human cognitive system.

关键词： Human mind engineering models Designing process

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Request-based forwarding strategy in vehicular named data networking 21

Request-based forwarding strategy in vehicular named data ne...

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9th International conference on Computer and Communications Management, ICCCM 2021

作者： Al-Qutwani, Majed Wang, Xingwei Yi, Bo College of Software Northeastern University Shenyang110819 China College of Computer Science and Engineering Northeastern University Shenyang110819 China

ISBN: (纸本)9781450390071

Named Data Networking (NDN) is a suitable solution for addressing the scalability and efficiency of vehicular ad hoc network (VANET). Despite applying VANET in NDN (VNDN) brings several advantages, yet few challenges, such as vehicle mobility and packet broadcasting, remain in VNDN. In this study, we propose a request-based content forwarding (RBFS) design to alleviate packet broadcast and enhance VNDN performance. Each consumer broadcasts a lighter request message instead of an interest packet to ask for a specific data packet, which will enable the provider to find the corresponding interest packet with less delay and minimal network overhead. We use a dynamic strategy, in which providers can deliver the data packet to the consumer by building unicast forwarding paths. Simulation results show that RBFS improves network performance by reducing network overhead, interest satisfaction rate, and interest packet delay. © 2021 Association for Computing Machinery.

关键词： NDN VNDN Content forwarding Vehicular named data network

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