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检索条件"任意字段=4th International Conference on Smart Learning Ecosystems and Regional Development"

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Effect Induced by the Covid-19 Pandemic on Students' Perception About Technologies and Distance learning 5th

Effect Induced by the Covid-19 Pandemic on Students' Percept...

引用

5th international conference on smart learning ecosystems and regional development (SLERD)

作者： Giovannella, Carlo Univ Roma Tor Vergata Dip SPSF Rome Italy ASLERD Rome Italy

ISBN: (纸本)9789811573835;9789811573828

this paper represents the first investigation conducted in Italy at university level to detect the effects induced on students by the swap of the educational processes from physical to fully virtual, caused by the Coronavirus epidemic. the study involved 101 students attending a bachelor course in Educational Science. the results show that, although students seem to miss physical settings and face-to-face activities, the sudden switch from physical to fully virtual setting has been positively absorbed. the overall emerging scenario indicates that a large part of the present generation of university students is ready for novel educational processes, largely grounded on blended learning activities. the results of this study, beside representing an historical documentation, question the nowadays organization of the physical learning ecosystems, that date to few centuries ago and suggest to re-think both their organization and functionalities.

关键词： Distance education Distance learning Perception about technologies smart learning ecosystems Covid-19 pandemic

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smart Hospital Privacy Protection System Based On Cloud Computing Iot 4

Smart Hospital Privacy Protection System Based On Cloud Comp...

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4th international conference on Machine learning and Big Data Analytics for IoT Security and Privacy, SPIoT 2023

作者： Li, Sen Luo, Dan Liu, Xin Luo, Rong School of Information Network Security Xinjiang University of Political Science and Law Xinjiang Uygur Autonomous Region Tumshuk City843900 China College of Intelligence and Computing Tianjin Ren'ai University Tianjin301636 China Changji University Xinjiang Changji831100 China

the swift evolution of information technology is catalyzing a transformative fusion between cloud-integrated Internet of things (IoT) and smart healthcare, poised to usher in revolutionary transformations within the medical sector. through iot technology, various medical devices, sensors, and monitoring systems can connect and exchange data in real time, enabling remote monitoring, intelligent analysis, and personalized medicine. the confluence of the expanding Internet of things (IoT) and the blossoming smart healthcare sector is set to streamline medical resource allocation, uplift healthcare service quality, and markedly ameliorate patients' experiences in healthcare settings. At the same time, it also brings some challenges, such as data privacy protection, standardization and security issues, which need continuous scientific and technological innovation and policy support to solve. In this paper, the row index obfuscation Bloom filter is designed in the scenario of smart healthcare to protect the privacy of data. Compared with other schemes, the proposed scheme has better privacy protection and better performance, and the proposed scheme is secure. In a word, the combination of iot and smart healthcare is promoting the digital transformation and innovative development of the medical industry, and providing more intelligent and convenient medical services for people's health. © 2024 the Authors.

关键词： Access Control Internet Of things Privacy Preserving smart Hospital

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A Review of Research on Human Behavior Recognition Methods Based on Deep learning 4

A Review of Research on Human Behavior Recognition Methods B...

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4th international conference on Robotics and Computer Vision, ICRCV 2022

作者： Li, Shengwang Yu, Pengshuai Xu, Yunfeng Zhang, Jingwei Hebei University of Science and Technology School of Information Science and Engineering Shijiazhuang China

ISBN: (数字)9781665481700

ISBN: (纸本)9781665481700

As an important research hotspot in the field of computer vision, human behavior recognition has important research significance and wide application prospects in many fields such as intelligent surveillance, smart home, and virtual reality, and has attracted much attention from scholars at home and abroad. With the great success of deep learning in image classification, the use of deep learning in human behavior recognition has gradually become a development trend, but there are still some difficulties and challenges. this paper firstly introduces the human behavior recognition methods based on deep learning, secondly, organizes the human behavior dataset, compares the performance of each behavior recognition algorithm and the specific applications, and finally, analyzes the challenges faced by behavior recognition and the outlook for the future. © 2022 IEEE.

关键词： Convolutional neural networks

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Research on communication mechanism optimization based on distributed graph computing environment 4

Research on communication mechanism optimization based on di...

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4th international conference on Big Data Economy and Information Management, BDEIM 2023

作者： Lin, Jianchao Cao, Chunna Ren, Chunhui State Grid Laboratory of Grid Advanced Computing and Applications State Grid Smart Grid Research Institute Co. Ltd Beijing China

ISBN: (纸本)9798400716669

In recent years, with the rapid development of the Internet of things, the Internet, and social networks, the storage of data in the network is growing at an explosive rate and is becoming more and more closely related to the real natural world. Driven by large-scale data mining and machine learning applications, distributed graph computing models that use graph data structures to describe data and relationships between data have been increasingly widely used. therefore, this paper studies the optimization of communication mechanisms based on a distributed graph computing environment. Firstly, a BSP model based on a pure message-passing communication mechanism of a distributed graph computing system is established. Secondly, the optimization model is evaluated from two aspects: data communication and convergence condition judgment. Finally, large-scale data sets are used to test and evaluate performance optimization. the results show that this method can greatly improve the efficiency of graph parallel computing. © 2023 ACM.

关键词： BSP model Distributed Graph Computation Distributed system Graph processing Parallel computing

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4th international conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2023

4th International Conference on IoT Based Control Networks a...

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4th international conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2023

ISBN: (纸本)9789819965854

the proceedings contain 52 papers. the special focus in this conference is on IoT Based Control Networks and Intelligent Systems. the topics include: development of IoT-Based Vehicle Speed Infringement and Alcohol Consumption Detection System;phonocardiogram Identification Using Mel Frequency and Gammatone Cepstral Coefficients and an Ensemble learning Classifier;Automatic Conversion of Image Design into HTML and CSS;Customizing Arduino LMiC Library through LEAN and Scrum to Support LoRaWAN v1.1 Specification for Developing IoT Prototypes;prevention of Wormhole Attack Using Mobile Secure Neighbour Discovery Protocol in Wireless Sensor Networks;Comparison of Feature Extraction Methods Between MFCC, BFCC, and GFCC with SVM Classifier for Parkinson’s Disease Diagnosis;a Comprehensive Study on Artificial Intelligence-Based Face Recognition Technologies;design of IoT-Based smart Wearable Device for Human Safety;Detection of Artery/Vein in Retinal Images Using CNN and GCN for Diagnosis of Hypertensive Retinopathy;vehicle Information Management System Using Hyperledger Fabric;An Evolutionary Optimization Based on Clustering Algorithm to Enhance VANET Communication Services;visual Sentiment Analysis: An Analysis of Emotions in Video and Audio;design and Functional Implementation of Green Data Center;patient Pulse Rate and Oxygen Level Monitoring System Using IoT;ioT-Based Solution for Monitoring Gas Emission in Sewage Treatment Plant to Prevent Human Health Hazards;Evaluation of the Capabilities of LDPC Codes for Network Applications in the 802.11ax Standard;parallel Optimization Technique to Improve the Performance of Lightweight Intrusion Detection Systems;Enhancement in Securing Open Source SDN Controller Against DDoS Attack;proposal of a General Model for Creation of Anomaly Detection Systems in IoT Infrastructures;green IoT-Based Automated Door Hydroponics Farming System.

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4th international conference on Applied Technologies, ICAT 2022

4th International Conference on Applied Technologies, ICAT 2...

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4th international conference on Applied Technologies, ICAT 2022

ISBN: (纸本)9783031249846

the proceedings contain 113 papers. the special focus in this conference is on Applied Technologies. the topics include: Automatic Evaluation of Physiotherapy Activities Using Deep learning Techniques;multivariable Control Approach Applied to the Embryo Incubation Process of Gallus Gallus Domesticus;discovering Visual Deficiencies in Pilots Candidates Using Data Mining;an Electronic Equipment for Measuring Color Difference Between Tissues Based on Digital Image Processing and Neural Networks;artificial Intelligence-Based Banana Ripeness Detection;U-Net vs. TransUNet: Performance Comparison in Medical Image Segmentation;access Control through Mask Detection and Estimation of People Capacity in Covered Premises;customer Segmentation in Food Retail Sector: An Approach from Customer Behavior and Product Association Rules;Bibliometric Analysis of Web of Science Database STEM Fields in Engineering and Mathematics. Ecuador’s Case Study;smart Antenna Array for Optimal Electromagnetic Energy Capture;image Processing Method to Estimate Water Quality Parameter;use of the Student Engagement as a Strategy to Optimize Online Education, Applying a Supervised Machine learning Model Using Facial Recognition;crime Data Analysis Using Machine learning Models;Gene therapy as a Solution to Genetic Diseases through DNA Manipulation;Vulnerability of CAPTCHA Systems Using Bots with Computer Vision Abilities;military Leadership in the Ecuadorian Army;analysis of Key Variables for Ecuadorian Defense Industry development;the Prioritization of External Security as a Means of Guaranteeing Multidimensional Security and Economic Growth;Comparative Study of Deep learning Algorithms in the Detection of Phishing Attacks Based on HTML and Text Obtained from Web Pages;ground Robot for Search and Rescue Management;virtual Training Module for the Production of Rubber Adhesives through the Production of Cyclopentenol.

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4th international conference on Applied Technologies, ICAT 2022

4th International Conference on Applied Technologies, ICAT 2...

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4th international conference on Applied Technologies, ICAT 2022

ISBN: (纸本)9783031249709

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4th international conference on Applied Technologies, ICAT 2022

4th International Conference on Applied Technologies, ICAT 2...

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4th international conference on Applied Technologies, ICAT 2022

ISBN: (纸本)9783031249778

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Data-driven robust model predictive control technology for propylene distillation process 4

Data-driven robust model predictive control technology for p...

引用

4th international conference on Industrial Artificial Intelligence, IAI 2022

作者： Ju, Keshuai He, Renchu Zhao, Liang Ministry of Education East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Shanghai200237 China

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

the distillation column is always affected by external disturbances during its operation. Using data-driven robust model predictive controller (DDRMPC), which based on the data-driven robust optimization (DDRO) method, can better handle the process uncertainty than the traditional robust model predictive control (TRMPC) because of the introduction of the machine learning method. A DDRMPC of propylene distillation column is proposed to hedge against the uncertainty of propylene content at the top of the column. Firstly, a linear state space model of the process is established based on the compartmental method and the dynamic mechanism model, and then the uncertainty set of principal component analysis and robust kernel density estimation is constructed by using the historical data. Certainty equivalent MPC (CEMPC), TRMPC and DDRMPC algorithms are constructed respectively. Finally, the performance of DDRMPC is analyzed through the case study of composition control. © 2022 IEEE.

关键词： Distillation columns

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Method of Process Optimization for LMD-Processes using Machine learning Algorithms 4

Method of Process Optimization for LMD-Processes using Machi...

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4th international conference on Industry 4.0 and smart Manufacturing, ISM 2022

作者： Gröning, Holger Zenisek, Jan Wild, Norbert Huskic, Aziz Affenzeller, Michael Center of Excellence for Smart Production University of Applied Sciences Upper Austria Campus Wels and Hagenberg Austria Institute for Symbolic Artificial Intelligence Johannes Kepler University Linz Austria

Additive manufacturing processes such as laser metal deposition have great potential for supplementing or substituting established manufacturing processes. One of the challenges is the time-consuming development of thermally stable process conditions for the production of defect-free components. the presented approach aims for extracting all relevant machine-, process- and result parameters from different sources, using an algorithm to merge the heterogeneous data streams and to stabilize and optimize the process through machine learning algorithms. To provide qualified training data an expert system is presented to facilitate the identification of causal relationships by domain experts. Furthermore, the strategy focusses on the development and implementation of virtual sensors to avoid the hardware- and software-integration effort, to reduce the amount of data processed and enable for an in-situ closed-loop optimization. © 2022 the Authors. Published by ELSEVIER B.V.

关键词： Machine learning

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