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检索条件"任意字段=9th International Conference on Computer Aided Design and Computer Graphics"

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designing a Workplace Violence Reporting Tool for Healthcare Workers in Hospital Settings 9th

Designing a Workplace Violence Reporting Tool for Healthcare...

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9th international conference on HCI in Business, Government and Organizations (HCIBGO) Held as Part of the 24th international conference on Human-computer Interaction (HCII)

作者： Foster, Meagan Adapa, Karthik Cole, Amy Khasawneh, Amro Soloway, Anna Francki, Jeffrey Havill, Nancy Mazur, Lukasz Univ N Carolina Chapel Hill NC 27514 USA UNC Hlth Chapel Hill NC 27514 USA

ISBN: (纸本)9783031055447;9783031055430

Workplace violence (WPV) is severely underreported among healthcare workers (HCWs) who are four times more likely to experience WPV compared to professionals in other industries. the frequency in which HCWs are exposed to acts of WPV prompts urgency in the development of improved reporting tools to capture HCWs' experiences more adequately and provide evidence for strategic improvement initiatives. Techniques in human-centered design and product discovery techniques can enhance the redesign process and help teams identify what HCWs value and deliver value, faster. Purpose: To explore how human-centered design and product discovery techniques can be used to inform feature recommendations for a minimum viable product (MVP) for an improved WPV reporting tool for HCWs. Methods: We used a mixed-methods approach based on human-centered design and product discovery techniques. Results: Two distinctive themes emerged, informing our design objectives: (1) To increase reporting of WPV and (2) to provide access to WPV support resources. the recommended set of product features was well-received among HCWs. Conclusion: Human-centered design and product discovery techniques can be used in a complementary fashion to design WPV reporting tools that better align with the values of HCWs.

关键词： Workplace violence Hospital Product discovery Human-centered design Cognitive ergonomics Case study

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A Survey of Advanced Learning Techniques Used for Initial Detection of vital Human organs Disorders through Iris 9

A Survey of Advanced Learning Techniques Used for Initial De...

引用

9th IEEE international conference on Smart Structures and Systems, ICSSS 2023

作者： Sandhiya, M. Aneetha, A.S. Department of Computer Science and Engineering India

An approach of early detection that makes use of an optimization technique that was brought about by learning techniques. Artificial intelligence technology breakthroughs that can scan a patient's body and diagnose the conditions they have would be expected by certain doctors. To gain a deeper understanding of the human body, iridology is an applied health practice. Images of iris can be acquired and interpreted using a variety of innovative techniques. Information on the human body and organ health is contained in Iris. Iridology is an academic discipline that examines the strengths and limitations of iris tissue to gain insight into the health of the body's various organs. Iridology has grown more well-liked and trustworthy as a result of the quick growth of picture processing. Many iridology-based methods have been created recently that use certain iris features to detect the human disorders. the information contained herein displays every iris recognition method that has been studied along with the precision of each region. Future iridology research' design and methodological decisions can be influenced by the studies outcomes. © 2023 IEEE.

关键词： Feature extraction

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Machine Learning Algorithms for Early Predicting Dropout Student Online Learning 9

Machine Learning Algorithms for Early Predicting Dropout Stu...

引用

9th IEEE international conference on Computing, Engineering and design, ICCED 2023

作者： Dewi, Meta Amalya Kurniadi, Felix Indra Murad, Dina Fitria Rabiha, Sucianna Ghadati Romli, Awanis Bina Nusantara University BINUS Online Learning Information Systems Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Universiti Malaysia Pahang Faculty of Computing Pahang Malaysia

ISBN: (纸本)9798350370126

Online learning is different from offline learning in the classroom with supervision from the lecturer. Online learning using the Learning Management System (LMS) media requires high awareness from students because their learning activities are not supervised, they are free to study wherever and whenever, so they need to manage and control their own study time without the help of lecturers or administrators. this is one of the causes of the high dropout rate among online learning students, so it is very important for lecturers and administrators to support students in a timely manner to avoid the risk of dropping out. this study uses access log data recorded in the LMS and student statistical information and calculated data and aims to present a suitable predictive algorithm for dropout early prediction systems for online learning students using machine learning. Of the 4 algorithms used, the highest recall value is in Naive Bayes (1), the highest precision is in Logistic Regression with Lasso (1), while the highest accuracy value (0.99) and F1score (0.97) are obtained from the Support Vector Machine which has value equal to Logistic Regression with Lasso. In general, the early dropout prediction model will allow lecturers and administrators to focus on students who have the potential to dropout and take quick action to improve their learning performance so as to reduce the number of student dropouts. © 2023 IEEE.

关键词： Forecasting

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Task Model design and Analysis with Alloy 9th

Task Model Design and Analysis with Alloy

引用

9th international conference on Rigorous State-Based Methods (ABZ)

作者： Cunha, Alcino Macedo, Nuno Kang, Eunsuk INESC TEC Porto Portugal Univ Minho Braga Portugal Univ Porto Fac Engn Porto Portugal Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9783031331626;9783031331633

this paper describes a methodology for task model design and analysis using the Alloy Analyzer, a formal, declarative modeling tool. Our methodology leverages (1) a formalization of the HAMSTERS task modeling notation in Alloy and (2) a method for encoding a concrete task model and compose it with a model of the interactive system. the Analyzer then automatically verifies the overall model against desired properties, revealing counter-examples (if any) in terms of interaction scenarios between the operator and the system. In addition, we demonstrate how Alloy can be used to encode various types of operator errors (e.g., inserting or omitting an action) into the base HAMSTERS model and generate erroneous interaction scenarios. Our methodology is applied to a task model describing the interaction of a traffic air controller with a semi-autonomous Arrival MANager (AMAN) planning tool.

关键词： Task models HAMSTERS Interactive system analysis Alloy Air traffic control Arrival manager

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An improved KPLS-KELM method for breast cancer detection 9

An improved KPLS-KELM method for breast cancer detection

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9th IEEE international conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

作者： Bacha, Sawssen Taouali, Okba Liouane, Noureddine National Engineering School of Monastir Research Laboratory of Automation Signal Processing and Image Monastir5019 Tunisia University of Tabuk Faculty of Computers and Information Technology Department of Computer Engineering Tabuk Saudi Arabia

ISBN: (数字)9781728184425

ISBN: (纸本)9781728184425

the conception of a computer-aided Diagnosis system (CAD) using Artificial Intelligence (AI) is a hot topic in the domain of medical diagnosis. Recently, many approaches have been developed. In the proposed work, a novel classification technique from mammograms based on Kernel Extreme Learning Machine (KELM) and Kernel Partial Least Square (KPLS) method is introduced. the suggested algorithm first used the KPLS algorithm to extract features from the images. the extracted characteristics were then sent to the KELM classifier. In order to improve the generalization of the proposed approach, the cross-validation strategy was used. the simulation results were tested on the Mammographic Image Analysis Society (MIAS) dataset and measured using accuracy, F score, sensitivity, and specificity analysis. these results were compared to existing approaches tested on the same dataset and it was observed that the proposed work is the most efficient. © 2022 IEEE.

关键词： Mammography

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Microwave Metamaterial Absorber for X, C and Ku Band Applications 9

Microwave Metamaterial Absorber for X, C and Ku Band Applica...

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9th IEEE international conference on Smart Structures and Systems, ICSSS 2023

作者： Praveena, R. Babu, T.R. Ganesh Sakthimurugan, K. Elango, S. Muthayammal Engineering College Department of Electronics and Communication Engineering Tamil Nadu Namakkal India Psn College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Tirunelveli India Madanapalle Institute of Technology & Science Department of Computer Science & Engineering Madanapalle India

ISBN: (纸本)9798350384208

this paper presents a three-band polarization insensitive microwave metamaterial absorber (MMA). the proposed MMA (Metamaterial Absorber) consists of a unit cell made up of a top metallic patch and a ground metallic plane, with these components separated by an FR4 dielectric substrate that is extremely thin, with a thickness of only 0.014 times the wavelength (λ) of the incident electromagnetic waves. this structure has been designed to achieve excellent absorption properties in different frequency bands. the outcome of this work is used to find out the explosive detection, sensing and radar applications. the fabricated microwave Metamaterial Absorber (MMA) has been tested and validated through measurements. Its design was initially analyzed using numerical simulations performed with CST Microwave Studio Software. © 2023 IEEE.

关键词： Dielectric materials

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5th international conference on Innovative Computing, IC 2022

5th International Conference on Innovative Computing, IC 202...

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5th international conference on Innovative Computing, IC 2022

ISBN: (纸本)9789811941313

the proceedings contain 177 papers. the special focus in this conference is on Innovative Computing. the topics include: Fe Cluster Structure Optimization Based on Small Habitat Differential Evolution Algorithm;evaluation Method of Posture Balance of Wushu Athletes Based on Higuchi Analysis;design of Mental Health Information Service Platform for College Students in Private Independent Colleges Based on B/S Architecture;research and Application of Improved Decision Tree Algorithm in Enterprise Training Management System;different Information Systems in Cross-Cultural Communication Between China and the West Under Cloud Computing;design of Data Concentrator in Power Grid Collecting System Based on Embedded Linux;the Teaching Curriculum System design of "Internet +" Graphic design;Curriculum design of VR conference Interpretation Virtual Simulation Teaching;remote Monitoring and Fault Diagnosis of Mine Hoist Operation System;a Study for Digital Contents Management Based on Smart Home;design of a Peristaltic Robot Trajectory Control System Based on Hydrodynamic Technology;the Application of computer graphics Image Processing Technology;design and Implementation of an Aesthetic Scoring System for Art Images;research and design of a Micro-commerce Platform for Agricultural Products Based on Intelligent Recommendation and Logistics Planning;analysis of the design of a Regional Cross-Border E-Commerce and Cross-Border Logistics Industry Integration Platform with Artificial Intelligence;a Meta-cellular Automata-Based Approach to Simulate Flooding Processes in Complex Terrain;progress in the Study of Engineering Properties of Saline Contaminated Soils;enterprise Human Resource Management System Based on computer aided;an Analytical Study Based on computer-Assisted Language Teaching;research on computer aided English Teaching;preface.

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design and Performance Analysis of Model Reference Adaptive Controller applied to a Dynamical System 9

Design and Performance Analysis of Model Reference Adaptive ...

引用

9th IEEE Uttar Pradesh Section international conference on Electrical, Electronics and computer Engineering, UPCON 2022

作者： Ghosh, Arpita Saxena, Aditi Singh, Rajarshi Guha, Dipayan Department of Electrical Engineering MNNIT Allahabad India

ISBN: (数字)9798350332506

ISBN: (纸本)9798350332506

With the dynamic variation of operating environments, it is imperative to design and integrate advanced intelligent controllers that cope with unmodelled plant dynamics, parasitic effects, and endogenous/exogenous disturbances to achieve desired outputs. this paper has attempted to design and apply an adaptive controller to unknown dynamical systems and analyse the performances in terms of good tracking and better steady-state accuracy. Model reference adaptive control (MRAC) scheme has been utilized to realize the closed-loop control system. the stability of the developed closed-loop control system has been shown by applying the Lyapunov argument. Analysis of the results affirms the ability of the proposed MRAC in achieving desired outputs for unknown plant models. © 2022 IEEE.

关键词： Model reference adaptive control

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Research on Age-Friendly Home design Based on Regularized Non-Negative Matrix Factorization Algorithm 24

Research on Age-Friendly Home Design Based on Regularized No...

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9th international conference on Cyber Security and Information Engineering, ICCSIE 2024

作者： Li, Bin Zhang, Zhiwei School of Automotive and Architectural Engineering Harbin Huade University China College of Science Heilongjiang Institute of Technology China

ISBN: (纸本)9798400718137

Population aging has become a major issue in Asian countries. Advances in computer algorithms have enabled the design and development of smart home and elderly care devices. Given the limitations of existing fall detection algorithms, this paper proposes a method for an intelligent fall prevention system for the elderly, focusing on non-negative matrix factorization visual correction. this research addresses the challenges of automatically adjusting the parameters of visual detection systems in real-world scenarios. the method combines LSTM with non-negative matrix factorization visual optimization algorithms to eliminate environmental noise’s impact on visual analysis. It iteratively estimates background noise power levels based on algorithm reference layers, achieving accurate detection of elderly fall behaviors and posture features. the proposed method compensates for inaccuracies in posture description and significant tracking errors of traditional integer-order admittance control. Experimental results show that, compared to other methods, the proposed method offers superior fall posture detection performance. therefore, it can be effectively applied to elderly care smart home systems, providing new strategies for optimizing smart furniture performance. © 2024 Copyright held by the owner/author(s).

关键词： Smart homes

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NeXtCrowd: Lightweight And Efficient Network design for Dense Crowd Counting 25

NeXtCrowd: Lightweight And Efficient Network Design for Dens...

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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： Hu, Jun Han, Hui College of Computer Science and Electronic Engineering Hunan University China Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region Ministry of Natural Resources China

ISBN: (纸本)9798350330014

Dense crowd counting remains a challenging task due to complex backgrounds, large-scale scenes, diversity of human features, and computational performance requirements. Unlike past solutions with additional designs or complex architectures, we argue that the counting task only needs to give an approximate number or density distribution of people in the scene, without exact location and classification, suggesting that a relatively lightweight architecture is sufficient for this task. Motivated by this line of thought, we explore whether a simple convolutional architecture can maintain counting performance in dense crowd counting. We propose an efficient CNN framework for crowd counting, namely NeXtCrowd. Specifically, we eliminate some unnecessary architectures to reduce the complexity and number of parameters of the backbone architecture, thus improving its computational efficiency and generalization capability. We then improve the performance and stability of the network by choosing the corresponding loss function and optimization method based on the task characteristics. Last we adopt a regression layer with Global Response Normalization to generate the density map, which can make better use of the information of each channel in the deep image features, and aggregate a more accurate density map of dense crowd. Without using additional architectures, NeXtCrowd can still achieve state-of-the-art performance on several dense crowd datasets. On the UCF-QNRF and ShanghaiTech Part A datasets, our model reduces the root mean squared error by 16.87 (131.4) and 7.9 (86.29), respectively' over the baseline methods. © 2023 IEEE.

关键词： computer vision

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