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A Human-Computer Interaction Optimization Method for Command and Control System Based on Gesture complexity

A Human-Computer Interaction Optimization Method for Command...

引用

Advanced algorithms and Control Engineering (ICAACE), international conference on

作者： Jiaying Li Jiadao Huo Quanmao Yao Jiangsu Automation Research Institute Lianyungang China School of Marine Science and Technology Northwestern Polytechnical University Xi'an China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

Aiming at the low efficiency of gesture interaction in the command and control system, this paper proposes a gesture interaction optimization method based on gesture complexity. Ten joint points are selected to model gestures, and gesture pairs and complexity are defined. complexity is used as the basis for gesture optimization. Finally, the commonly used GOMS model in human factors engineering is used to evaluate interaction efficiency. the results show that this method can reduce task completion time and effectively improve interaction efficiency.

关键词： Command and control systems Human computer interaction Analytical models Control engineering Ergonomics Optimization methods Human factors

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the Intersection of AI and Blockchain in Education: A Bibliometric and thematic Analysis 7

The Intersection of AI and Blockchain in Education: A Biblio...

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2023 7th international conference On Computing, Communication, Control And Automation, ICCUBEA 2023

作者： Kaul, Natashaa Deshpande, Amruta Mittal, Amit Raut, Rajesh Symbiosis International University Symbiosis Center for Management and Human Resource Development Pune India Indira School of Business Studies Pgdm Pune India Chitkara Business School Chitkara University Punjab India

ISBN: (纸本)9798350304268

Two cutting-edge technologies that are revolutionizing the education industry are artificial intelligence (AI) and blockchain. the study on AI and blockchain in education is bibliometrically analyzed in this paper, emphasizing topics, frameworks, and potential future research areas. the analysis uses the Scopus database to pinpoint essential works and sketch out the conceptual framework of this field of study. the findings show an increasing interest in applying AI and blockchain technology in various educational settings, from K-12 to higher education, as well as the various research paradigms and methodologies used in this field. Studies emphasize creating knowledge management tools, learning algorithms, and decision support systems to strengthen the educational process and enhance learning results. the study also emphasizes the growing demand for cutting-edge technologies like deep learning and the Internet of things. this paper provides a comprehensive evaluation of research on AI and blockchain in education by highlighting key ideas and frameworks that have been applied in this area. the results offer relevant information on the current level of research in this field and suggest potential directions for advancement. © 2023 IEEE.

关键词： Artificial Intelligence Bibliometrics Blockchain Education thematic Analysis

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Improved YOLOv7 UAV image small target detection algorithm 7

Improved YOLOv7 UAV image small target detection algorithm

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7th international conference on Computer Science and Artificial Intelligence, CSAI 2023

作者： Yingbo, Wang Zhi, Liu School of Software Liaoning Technical University Huludao125105 China School of Innovation Practice Liaoning Technical University Fuxin123000 China

ISBN: (纸本)9798400708688

In order to improve the detection efficiency of small targets in UAV images in traffic systems, a small target detection algorithm for UAV images in traffic systems based on improved YOLOv7 is proposed. In the feature fusion network, the small target detection layer is added to extract feature information of different scales to improve the perception ability and positioning accuracy of small targets. Deep separable convolution ( DSConv ) is introduced into the feature extraction and feature fusion network of the model, and feature extraction is performed on each channel without introducing additional parameters, which reduces the computational complexity and memory occupation of the network and enhances the ability of the network to extract target features. the nearest upsampling module of the original model is replaced by the lightweight operator Carafe, which expands the receptive field of the model and improves the quality and accuracy of the feature map. In the feature extraction and feature fusion connection part of the model, the CBAM hybrid attention mechanism is introduced to dynamically adjust the channel and spatial information in the feature map, and improve the model 's ability to capture the important features of small targets in the traffic system under complex background. the experimental results show that compared with the original algorithm, the improved YOLOv7 algorithm improves the mAP by 4.5 percentage points and the recall rate by 5 %. Compared with the current mainstream algorithms, the improved algorithm can effectively improve the detection accuracy of small targets in UAV images in traffic systems, and significantly improve the false detection and missed detection of small target images in complex backgrounds. © 2023 ACM.

关键词： Drones

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DSS-YOLOv7: An Enhanced YOLOv7-Based Algorithm for Classroom Behavior Detection 24

DSS-YOLOv7: An Enhanced YOLOv7-Based Algorithm for Classroom...

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7th international conference on Machine Learning and Machine Intelligence, MLMI 2024

作者： Yao, Fulong Chen, Xi Jiang, Yufan Jia, Wenlong Department of Software Shenyang University of Technology Shenyang China

ISBN: (纸本)9798400717833

this paper addresses the challenges of detecting students' hand-raising behavior in classrooms, which include small target sizes, complex student features, and distracting classroom background information. We propose an improved YOLOv7-based algorithm, Deformable Simulated-SE Enhanced YOLOv7 (DSS-YOLOv7), specifically designed for classroom behavior detection. the proposed algorithm introduces several enhancements: it optimizes the Feature Pyramid Networks (FPN) structure by incorporating Deformable Convolutions (DCNv2), which effectively capture variations in students' behaviors, thereby improving detection accuracy and robustness. Additionally, the Squeeze-and-Excitation (SE) attention mechanism is introduced to enhance the model's focus on important features and improve recognition accuracy. the integration of the Simple Attention Module (SimAM) helps to reduce model complexity and minimize confusion caused by background information. Furthermore, data augmentation techniques are applied to the dataset, significantly enhancing the model's feature learning capabilities. Experimental results demonstrate that the DSS-YOLOv7 model achieves a 2.6% improvement in mean Average Precision (mAP@0.5), reaching 85%, compared to YOLOv7 on the SCB-Dataset. the DSS-YOLOv7 model exhibits superior performance in detecting classroom behaviors under complex conditions. © 2024 Copyright held by the owner/author(s).

关键词： Students

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Evaluation of Target Detectability Performance Under Specific Image complexity 7th

Evaluation of Target Detectability Performance Under Specifi...

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7th international Symposium of Space Optical Instruments and Applications, ISSOIA 2022

作者： Bian, Boyuan Zhou, Feng Beijing Institute of Space Mechanics and Electricity Beijing100094 China

ISBN: (纸本)9789819940974

Infrared image complexity measurement is an important component of target detection performance evaluation. By analyzing the current studies on image complexity and measurement methods at home and abroad, it is found that most of them only calculate the complexity of a single frame image, and there are few studies on the complexity measurement methods of image sequences. Based on the generated image sequences, the target detectability under specific image complexity is evaluated. Two generally recognized indexes are used for evaluation of target feature and local background feature, which are the confusion degree of target and the occultation degree of target. the complexity of infrared image sequence is measured. the calculation result show that the occultation degree has a higher impact on the complexity of image sequence than the confusion degree. the target detectability in different image sequences is analyzed when the false alarm probability is 10% and the gray threshold is 10. It is found that the target detectability decreases with the increase of image sequence complexity. therefore, the threshold of target detectability should be set to match the image complexity. the method proposed in this paper can provide reference for the study of relationship between the complexity of image sequence and the target detection algorithms. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image analysis

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7th EAI international conference on Innovations and Interdisciplinary Solutions for Underserved Areas, InterSol 2024

7th EAI International Conference on Innovations and Interdis...

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7th EAI international conference on Innovations and Interdisciplinary Solutions for Underserved Areas, InterSol 2024

ISBN: (纸本)9783031864926

the proceedings contain 28 papers. the special focus in this conference is on Innovations and Interdisciplinary Solutions for Underserved Areas. the topics include: A Risk-Based Pedestrian Crossing Decision Model for Traffic Simulation in African Urban Traffic;modelling and Optimization of the Electrical Parameters of an InxGa1-xN Solar Cell Under Dynamic Frequency Illumination;assessment of Pavement Damage Caused by Speed Bumps Along Nyanya – Jikwoyi Road Abuja;analyzing Water’s Characteristics Health Impact with Classification algorithms;optimizing Coverage in a Wireless Sensors Network by Selecting the Best Sensors;Towards a Single-Sign-On Authentication Architecture Based on OpenID Connect Protocol and Blockchain Technology;an Experimental 5G Standalone Testbed for Rural Connectivity;an Application of the Hough Transform and Convolutional Neural Networks to Detect Straight Lines;a Slotted Random Access Algorithm for Efficient Transmission in White Area: Case of Artisanal Fishing in West Africa;a New Delay History Predictor for Multi-skill Call Center;retrieving Data from Social Network Platforms: A State-of-Art Review;strabismus Diagnosis and Angular Deviation Calculation Based on Artificial Intelligence Approaches: A Review;Towards the Implementation of a Dynamic IDS for IoT: Anomaly Detection in MQTT Traffic;straight-Line Recognition in a Virtual Hexagonal Grid Using Hough Transform;predicting the Rate of Aflatoxin Contamination in the White Corn Value Chain;the Impact of Agents Heterogeneous in Call Center Performance Measures;towards a Mobile, Intelligent, Personalized and Adaptive E-learning System Considering Learners’ Context in Semi-nomadic and Conflict Zones;comparative Study of Machine Learning Models for the Detection of Abusive Messages: Case of Wolof-French Codes Mixing Data;towards an Ontology-Based Platform for Integrating Infectious Disease Simulation Models;AI-Based Control Approach of .SN Reserved Domain Names (***);efficient Combination of

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Secure Skyline Groups Queries on Encrypted Data on Cloud Platform 23

Secure Skyline Groups Queries on Encrypted Data on Cloud Pla...

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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： Teng, Yiping Sun, Yue Shi, Zhan Jiang, Dongyue Zhao, Liang Fan, Chunlong School of Computer Shenyang Aerospace University Liaoning Large-scale Distributed System Laboratory Shenyang China

ISBN: (纸本)9781665494571

As an important category of skyline queries, the skyline groups query has drawn growing interest from the academic communities. For taking the benefit of cost savings, data owners are motivated to outsource the data storage and query processing to the public cloud to offload the massive data management. However, direct outsourcing may raise severe privacy issues. In this paper, we define and study the secure skyline groups query problem, and propose the secure skyline groups query methods. To address this problem, we first propose the Basic Secure Skyline Groups Query (BSSGQ) method to find the skyline groups on encrypted data. In BSSGQ method, candidate groups and their aggregate tuples are generated under encryption. To calculate group dominance relations, we propose a secure group dominance protocol to facilitate the dominance computation between groups. With the dominance relations, the skyline groups w.r.t the query group can be obtained, and finally the query results of the skyline groups can be securely returned without being learnt by the cloud servers. To address the efficiency problem in BSSGQ method, we further propose a Dynamic-programming-based Secure Skyline Groups Query (DSSGQ) method to effectively avoid generating the candidate groups. In DSSGQ method, the encrypted data are equivalently mapped based on the query group as the preprocessing to achieve a dynamic skyline groups query. then, DSSGQ method dynamically constructs and calculates the skyline sub-groups in ciphertext, and the final skyline groups can be combined with the obtained skyline sub-groups. thorough analysis shows the security and complexity of the proposed methods, and extensive experimental results on real datasets and synthetic datasets illustrate the performance of our proposed methods. © 2021 IEEE.

关键词： Cloud computing Privacy Protocols Smart cities Query processing Memory complexity theory

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Analysis of Monitoring Strategies for Photovoltaic Water Pumping Systems in Low-Income Remote Areas 7

Analysis of Monitoring Strategies for Photovoltaic Water Pum...

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7th IEEE international Humanitarian Technologies conference, IHTC 2024

作者： Sahuquet, Ange Meunier, Simon Cherni, Judith A. Darga, Arouna Darga, Severin Heinrich, Matthias Vezin, thomas Queval, Loic Univ. Paris-Saclay CentraleSupélec Sorbonne Univ. CNRS GeePs Gif-Sur-Yvette France Imperial College London Centre for Environmental Policy LondonSW7 2AZ United Kingdom DargaTech SARL Ouagadougou Burkina Faso Laboratoire HERUS Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland UMR-IPVF 9006 CNRS Ecole Polytechnique IPP ENSCP PSL Institut Photovoltaïque d'Ile de France Palaiseau France

ISBN: (纸本)9798350354645

Photovoltaic water pumping systems (PVWPS) can greatly enhance access to clean water in rural and low-income regions of sub-Saharan Africa, thereby contributing to improved health and well-being. PVWPS monitoring can significantly help for effective operation and performance, with continuous monitoring providing comprehensive data. However, there is a lack of detailed feedback on the long-term effects of continuous monitoring. this article addresses this gap by presenting a five-year case study of continuous monitoring on a PVWPS in Gogma, Burkina Faso, and by analyzing the benefits and challenges associated with such extended monitoring. We also detail the technical decisions involved in designing a robust data acquisition system (DAS) and highlight the academic contributions enabled by the five-year dataset obtained, including the development of machine learning algorithms for detecting module cleaning. Despite the clear benefits in terms of scientific research, significant challenges associated with continuous long-term monitoring have been identified, including logistical difficulties, financial constraints, and maintenance issues of DAS in remote areas. To mitigate these challenges, we suggest implementing a periodic monitoring approach, with annual or bi-annual site visits by trained technicians. this method is aimed at local practitioners, retaining the benefits of data collection while reducing costs and logistical burdens, making it suitable for practical (non-research) applications in resource-constrained environments. © 2024 IEEE.

关键词： Decision making

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7th international conference on Innovative Computing, IC 2024

7th International Conference on Innovative Computing, IC 202...

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7th international conference on Innovative Computing, IC 2024

ISBN: (纸本)9789819741243

the proceedings contain 157 papers. the special focus in this conference is on Innovative Computing. the topics include: Proactive Auto Scaling Based on Marginal Request Change Analysis for Reducing Tail Latency in Kubernetes Cluster;Integration of Generative Adversarial Networks (GAN) and AI Drawing in Criminal Sketches—Applied in Crime Scene Investigation by Law Enforcement;implementation of a High Quality Cardiopulmonary Resuscitation Teaching Intelligence Training and Assessment System;Predicting Twitter Posts from Fake Accounts Using XGBoost Model;the Interplay Between Self-regulated Learning and Programming Learning Achievement;a Study on the Continued Viewing Intention of YouTuber Videos: Experiential Marketing, Social Capital, and Habit Perspectives;an Exploratory Study on the Design of Human-Computer Interaction Interfaces for Augmented Reality Integrated Museum Exhibitions;communication-Aware Optimization of Microservice Scheduling on Edge Computing;Design of Computer Model for Raw Material Supplier Selection Based on Entropy Weight TOPSIS Method;exploring How Cybersecurity Competitions Can Help Improve Students’ Practical Abilities in Cybersecurity;Adversarially Residual U2Net for COVID-19 Lung Infection Segmentation from CT Images;partnerships Analysis Based on Measurements of Common Research Interest;System Design of Operating Costs of Intelligent Healthcare Services for the AHP Algorithm;a Multi-party Private Set Union Protocol Against Malicious Adversary;analysis of the Current Status of Research on Unmanned Collaborative Equipment Above and Below Water;data Mining Analysis of New Energy Vehicles Based on Cluster Analysis Technology;Two-Layer Minimum Variance FIR Filter-Based DPLL Design;fuzzy Proximity Two-Dimension Inductance Gesture Recognition System Analysis and Implement;proximity Capacitive Gesture Recognition for Recursive Neighbor Memory Neural Network;application of Genetic algorithms in Automated Mechanical Design.

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Adaptive Distributed CRC-aided SCL Decoder with Flip Operations for Polar Codes 7

Adaptive Distributed CRC-aided SCL Decoder with Flip Operati...

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7th international conference on Image, Vision and Computing, ICIVC 2022

作者： Huan, Jing Yin, Hang Lv, Yansong Communication University of China Engineering Center of Digital Audio and Video Beijing China Communication University of China State Key Laboratory of Media Convergence and Communication Beijing China

ISBN: (数字)9781665467346

ISBN: (纸本)9781665467346

Polar codes are used for image transmission due to unequal error protection. Meanwhile, a low-complexity polar code decoder helps to reduce the energy loss during polar code decoding. therefore, this paper proposes a new decoder with low complexity, called adaptive distributed cyclic-redundancy-checkaided successive cancellation list decoder with flip operations (ADD-SCLF). By combining the adaptive scheme and the distributed cyclic redundancy check (CRC) bit scheme, the decoder can find the correct path with lower average computational complexity and end the failed decoding process earlier simultaneously. Simulation results show that our ADD-SCLF decoder can reduce the computational complexity by up to 17.16% compared to the current adaptive ordered shifted-pruning list (ADOSPL) decoder. © 2022 IEEE.

关键词： Computational complexity

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