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检索条件"任意字段=21st International Conference on Intelligent Data Engineering and Automated Learning"

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Open Tools for data Literacy Development at School. A Case of Systemic and Experience Design Approach to Civic Tech Education 13th

Open Tools for Data Literacy Development at School. A Case o...

引用

13th international conference on Methodologies and intelligent Systems for Technology Enhanced learning, mis4TEL 2023

作者： Cangiano, Serena SUPSI University of Applied Sciences and Arts of Southern Switzerland Mendrisio6850 Switzerland

ISBN: (纸本)9783031421334

As technology literacy is recognized as a crucial 21st-century skill to confront the challenges of the rapidly approaching digital transformation, a significant concern within formal educational settings revolves around how to effectively train young students. The objective is to move beyond the confines of traditional computer science teaching methods that solely rely on keyboards and mice. Instead, the focus should be on fostering explorative and creative activities that emphasize the collection and utilization of data. This paper presents the methodological framework of a one-year pilot project. Through a co-design process, the project aimed to address the pressing need for a more comprehensive and innovative approach to developing data literacy in schools. The project achieved this by designing open connected tools, educational resources, and facilitating a collaborative process based on active citizenship. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： students

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Gossip Swap SGD: Lightweight Decentralized Machine learning for Non-Homogeneous data Distribution 21

Gossip Swap SGD: Lightweight Decentralized Machine Learning ...

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21st international conference on New Trends in intelligent Software Methodologies, Tools and Techniques, SoMeT 2022

作者： Yokota, Naoya Hara-Azumi, Yuko School of Engineering Tokyo Institute of Technology Japan

ISBN: (纸本)9781643683164

Developing lightweight training approaches for distributed machine learning is of key importance to deploy machine learning on Internet-of-Things (IoT) devices. Gossip SGD is attractive among distributed machine learning methods thanks to its applicability to various network topologies (irrespective of having a central entity) and simple parameters update strategy. However, it is known to be inefficient in non-homogeneous data distribution environments. Our work addresses this issue by introducing 'parameters swapping' in the Gossip SGD during parameters update to let devices simply exchange their parameters. Our method, named Gossip Swap SGD, efficiently resolves a cause of insufficient accuracy or delayed convergence in parameters update for non-homogeneous data distribution. Our quantitative evaluation demonstrated that our method not only outperforms exiting methods in non-homogeneous data distribution but also has no degradation even in homogeneous data distribution. © 2022 The authors and IOS Press. All rights reserved.

关键词： Machine learning

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A V-NDN Based Adaptive data Forwarding Approach for Connected Autonomous Vehicles 21

A V-NDN Based Adaptive Data Forwarding Approach for Connecte...

引用

21st IEEE India Council international conference, INDICON 2024

作者： Kaushik, Anu Bali, Rasmeet S. Chandigarh University Science & Engineering Department India

ISBN: (纸本)9798350391282

With the increasing amount of content distribution in the intelligent transportation systems, one of the major concern is to provide in a timely and authenticated data to the requesting vehicle. This paper presents a Content Centric Multimodal Deep learning approach termed as CCM D in a vehicular named data environment. In this, several sources such as connected autonomous vehicles, on road sensors, handheld devices etc are used for data collection and distribution. This data is further used to derive a federated output for improving the road safety by suggesting some preventive measures. By using adaptive data forwarding scheme based on the data received from multimodal sources including pictures, global positioning systems coordinates, depth maps, text information and employing advanced algorithms of deep learning, the proposed methodology addresses the hurdle free movement of vehicles. The scenario has been implemented using ndnSim simulator where extensive simulations have been performed to measure the efficiency of the proposed scheme. Numerous parameters have been used to analyze CCM D which shows that it has provided satisfactory results in terms of delay and overhead. © 2024 IEEE.

关键词： Autonomous vehicles

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The Visual Management of Subway Tunnel Construction Safety Based On the Infinite Perception Network and FME-DS Evidence Multi-Source data Fusion Model Framework 11th

The Visual Management of Subway Tunnel Construction Safety B...

引用

11th international conference on Applications and Techniques in Cyber Intelligence, ATCI 2023

作者： Wang, Hao Yang, Yang Shen, Han Fujian CIECC Planning & Design Research Group Co. Ltd. Fujian Zhangzhou363000 China School of Construction Management Chongqing Metropolitan College of Science and Technology Chongqing Yubei401120 China

Entering the 21st century, with the acceleration of economic globalization, urban development is facing many challenges such as population growth, resource scarcity, and environmental pressure. Therefore, underground engineering construction has received widespread attention. The application of Wireless Sensing Network (WSN) technology in civil engineering structural monitoring meets the intelligent monitoring needs of tunnel construction and solves the problem of construction safety monitoring. This study combines statistical analysis, theoretical research, numerical simulation, BIM technology, and on-site verification methods to systematically explore the perception and visualization management of safety risks in subway construction. The application of wireless monitoring technology has verified the monitoring effect of wireless laser ranging and wireless inclination sensors during the construction period. The results show that under timely support conditions, the tunnel structure remains basically safe. For weak stratum tunnels, numerical simulation and backward advanced deep hole grouting pre reinforcement technology are studied to ensure the stability of the soil layer around the tunnel. At the same time, BIM technology is used to construct a tunnel model, visualize the construction process, and develop an intelligent sensing control system for real-time monitoring and risk warning. © 2024 The Authors. Published by Elsevier B.V.

关键词： Urban growth

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ISE 2022 - Proceedings of the 1st international Workshop on intelligent Software engineering, co-located with 29th Asia-Pacific Software engineering conference, APSEC 2022

ISE 2022 - Proceedings of the 1st International Workshop on ...

引用

1st international Workshop on intelligent Software engineering, ISE 2022

The proceedings contain 14 papers. The topics discussed include: MediaPipe-based LstM-autoencoder sarcopenia anomaly detection and requirements for improving detection accuracy;the application of machine learning on the injury prediction of soccer players;real-time twist rebar detection system exploiting GAN-based data augmentation technique;performance evaluation of fire and smoke detection with object based DNN algorithm;business process model annotation techniques: identification, classification and analysis;automatic testing of OCE, a human-centered reinforcement learning system for automated software composition;towards automated open source assessment - an empirical study;load balancing in cloud computing using nature-inspired algorithms: a systematic literature review;and quality assurance in MLOps setting: an industrial perspective.

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Neuro-Fuzzy Systems for learning Analytics 21st

Neuro-Fuzzy Systems for Learning Analytics

引用

21st international conference on intelligent Systems Design and Applications (ISDA)

作者： Casalino, Gabriella Castellano, Giovanna Zaza, Gianluca Univ Bari Dept Comp Sci Bari Italy

ISBN: (纸本)9783030963088;9783030963071

learning Analytics techniques are widely used to improve students' performance. data collected from Virtual learning Environments (VLEs) are helpful to predict students' outcomes through the analysis of their interactions with the platform. In this work, we propose the use of hybrid models which are able to return accurate predictions together with explanations on the processes leading to the results. Particularly, students' outcomes have been predicted through Neuro-Fuzzy Systems (NFSs), and explanations are given in form of "IF-THEN" rules. The balancing between model interpretability and accuracy has been studied by reducing the number of relevant features. Results on the Open University learning Analytics dataset (OULAD) have shown the effectiveness of NFSs in predicting students' outcomes while explaining the reasoning behind the process.

关键词： learning analytics Neuro-fuzzy systems Interpretability

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THE USE OF MOBILE learning IN THE PROFESSIONAL MAstER'S DEGREE IN CYBERSECURITY 21

THE USE OF MOBILE LEARNING IN THE PROFESSIONAL MASTER'S DEGR...

引用

21st international conference on e-Society, ES 2023 and 19th international conference on Mobile learning, ML 2023

作者： Albuquerque, Tayná Gabriela Araújo da Silva, Daniel Alves Alves, Valéria Cristina Soares de Oliveira Tabosa, Danielle Alves de Mendonça, Fábio Lúcio Lopes de Sousa Júnior, Rafael Timóteo Universidade de Brasília Brazil

ISBN: (纸本)9789898704474

Cybersecurity in Brazil and around the world has expanded due to the majority use of the world wide web through Information and Communications Technology (ICTs). In the educational field, the use of mobile devices during the COVID-19 pandemic was the common tool both students and teachers found to facilitate studies once the lockdown and the social distancing came into force, and remote teaching was adopted and implemented by universities. Notably, the Professional Graduate Program in Electrical engineering (PPEE), at the University of Brasília (UnB), has a professional postgraduate program that aims to train its students in that cybersecurity—using mobile learning as one of its learning tools—which is relevant to public and private institutions. © 2023 Proceedings of the international conferences on e-Society 2023, ES 2023 and Mobile learning 2023, ML 2023. All rights reserved.

关键词： students

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Deep learning in Colorectal Cancer Classification: A Scoping Review

Deep Learning in Colorectal Cancer Classification: A Scoping...

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21st international conference on Informatics, Management, and Technology in Healthcare, ICIMTH 2023

作者： Alalwani, Rafaa Lucas, Augusto Alzubaidi, Mahmoud Shah, Hurmat Ali Alam, Tanvir Shah, Zubair Househ, Mowafa College of Science and Engineering Hamad Bin Khalifa University Doha34110 Qatar

ISBN: (纸本)9781643684000

Colorectal cancer (CRC) is one of the most common cancers worldwide, and its diagnosis and classification remain challenging for pathologists and imaging specialists. The use of artificial intelligence (AI) technology, specifically deep learning, has emerged as a potential solution to improve the accuracy and speed of classification while maintaining the quality of care. In this scoping review, we aimed to explore the utilization of deep learning for the classification of different types of colorectal cancer. We searched five databases and selected 45 studies that met our inclusion criteria. Our results show that deep learning models have been used to classify colorectal cancer using various types of data, with histopathology and endoscopy images being the most common. The majority of studies used CNN as their classification model. Our findings provide an overview of the current state of research on deep learning in the classification of colorectal cancer. © 2023 The authors and IOS Press.

关键词： Deep learning

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A Comprehensive Analysis of a Hybrid Deep learning Model for Midterm Electric Load Forecasting 25

A Comprehensive Analysis of a Hybrid Deep Learning Model for...

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25th IEEE international conferences on High Performance Computing and Communications, 9th international conference on data Science and Systems, 21st IEEE international conference on Smart City and 9th IEEE international conference on Dependability in Sensor, Cloud and Big data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Barkous, Hamdi Amayri, Manar Bouguila, Nizar Ecole Poly Technique de Tunisie Tunis Tunisia Concordia University Ciise Montreal Canada

ISBN: (纸本)9798350330014

In the realm of time series forecasting, particularly for midterm electric load predictions, hybrid deep learning models have shown promising results. This paper introduces a thorough implementation and validation of the established ETS+RD-LstM model. Leveraging the synergy of Exponential Smoothing (ETS) and Residual Dilated Long Short-Term Memory (RD-LstM), the model was applied to monthly electricity demand datasets from 10 different countries. The validation process employed was the walk-forward validation method. When juxtaposed with traditional models like ARIMA, MLP, XGBoost, ETS, kNN, and LstM, the ETS+RD-LstM model demonstrated superior forecasting accuracy and robustness. An in-depth performance analysis offers insights into the strengths and nuances of the model's prediction capabilities. Through this research, we aim to contribute to the growing body of knowledge on advanced hybrid forecasting models and their practical applications in the energy sector. © 2023 IEEE.

关键词： Long short-term memory

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Development of a Visualization for Developers of a Distributed System Including Idle Computers 25

Development of a Visualization for Developers of a Distribut...

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作者： Tsutsumi, Shosuke Higashinc, Masayuki Takahashi, Kenichi Kawamura, Takao Tottori University Department of Engineering Tottori Japan

ISBN: (纸本)9798350330014

This paper proposes a visualization function for developers in volunteer computing. In recent years, information systems such as e-learning systems and groupware have been introduced in companies and educational institutions to promote DX, but the introduction and operation of these systems incur a large cost burden. Therefore, we are developing a distributed information system that can be introduced and operated at low cost by utilizing surplus computers (idle computers) in an organization. Idle computers are unstable depending on the operations of their original users and have different performances. In order to use idle computers efficiently, it is necessary to improve the performance of the system and modify it to add new functions, taking into account the differences in behavior and performance of each machine. In this paper, visualization for developers to easily check the behavior and performance of a computer in an idle state is developed, and its usefulness is evaluated through experiments using a real system. © 2023 IEEE.

关键词： Visualization

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