检索结果-内蒙古大学图书馆

Advancements in Computing (ICAC), International Conference on

作者： Thiwanka Cholitha Hettiarachchi Lakisuru Sathyajith Semasinghe Shashika Lokuliyana Narmada Gamage Rajitha De Silva Dept. Computer Systems Engineering Sri Lanka Institute of Information Technology Lincoln Institute for Agri-Food Technology University of Lincoln

ISBN: (纸本)9798350398106

Exploration and manipulation of physical objects are essential for early childhood learning. Previous investigations found several TUI uses in other fields. Less research has been done on tangible learning for youngsters; thus, it is unclear if they are more collaborative, playful, or functional. TangiGuru consists of 12 tangible, manipulative objects known as TangiCubes, which are used as a tangible user interface between children and the e-Learning application. It can carry out cognitive learning activities related to colors, languages, shapes and basic math by dynamically varying assigned values by changing the external appearance of TangiCubes. This dynamic nature of the TangiCubes makes it possible to use the same tangibles with endless possibilities compared to traditional tangible learning solutions with static value for each tangible. After the prototyping phase, children were evaluated with the traditional tangible learning solutions compared to TangiGuru. They concluded that the more interactive tangible interfaces could make the children perform activities more engagingly.

关键词： Performance evaluation Human computer interaction Electronic learning Shape Toy manufacturing industry Collaboration Games

来源：评论

学校读者我要写书评

暂无评论

Deep Ear Biometrics for Gender Classification

arXiv

引用

arXiv 2023年

作者： Singh, Ritwiz Kashyap, Keshav Mukherjee, Rajesh Bera, Asish Chakraborty, Mamata Dalui Department of Computer Science and Engineering Haldia Institute of Technology WB India Department of Computer Science and Information Systems Birla Institute of Technology and Science Pilani Pilani Campus Rajasthan333 031 India Dept. of Computer Science and Engineering National Institute of Technology West Bengal Durgapur India

Human gender classification based on biometric features is a major concern for computer vision due to its vast variety of applications. The human ear is popular among researchers as a soft biometric trait, because it is less affected by age or changing circumstances, and is non-intrusive. In this study, we have developed a deep convolutional neural network (CNN) model for automatic gender classification using the samples of ear images. The performance is evaluated using four cutting-edge pre-trained CNN models. In terms of trainable parameters, the proposed technique requires significantly less computational complexity. The proposed model has achieved 93% accuracy on the EarVN1.0 ear dataset. © 2023, CC BY.

关键词： Biometrics

来源：评论

学校读者我要写书评

暂无评论

An Implementation of Answer Code Validation Program for Code Writing Problem in Java Programming Learning Assistant System

An Implementation of Answer Code Validation Program for Code...

引用

Information and Education technology (ICIET), International Conference on

作者： Khaing Hsu Wai Nobuo Funabiki Soe Thandar Aung Khin Thet Mon Htoo Htoo Sandi Kyaw Wen-Chung Kao Dept. of Information and Communication Systems Okayama University Okayama Japan Dept. of Computer and Information Science Tokyo University of Agriculture and Technology Tokyo Japan Department of Electrical Engineering National Taiwan Normal University Taipei Taiwan

To assist Java programming learning of novice students, we have developed the web-based Java Programming Learning Assistant System (JPLAS). It provides various exercise problems to cultivate code reading and code writing skills to support studies at various levels. The code writing problem (CWP) asks a student to write a source code to pass the given test code where the correctness is verified by running them on JUnit. Previously, we implemented the answer platform for students to solve CWP assignments with the automatic runs. However, the teacher needs to manually run them one by one to verify a lot of source codes from students. In this paper, we implement the answer code validation program that automatically verifies all the source codes for one test code and reports the number of tests that each code passed with the CSV file. For evaluations, we applied the program to a total of 999 source codes from 12-43 students for a total of 45 test codes that were assigned in the Java programming course in Okayama university, including for final examinations. The application results confirm the validity and effectiveness of the proposal.

关键词： Java Codes Source coding Education Writing Proposals Programming profession

来源：评论

学校读者我要写书评

暂无评论

Privacy-Preserving Machine Learning for E-Health Applications: A Survey

Privacy-Preserving Machine Learning for E-Health Application...

引用

Computing and Machine Intelligence (ICMI), International Conference on

作者： Jared Romeo Mahmoud Abbass Ahmed Sherif Mohammad M. R. Khan Mamun Mohamed Elsersy Kasem Khalil School of Computing Sciences and Computer Engineering University of Southern Mississippi MS USA Electrical and Computer Engineering Department Tennessee Technological University TN USA Computer and Information Systems Dept. Higher Colleges of Technology AlAin Abu Dhabi UAE Electrical and Computer Engineering Department University of Mississippi MS USA

ISBN: (数字)9798350372977

ISBN: (纸本)9798350372984

As more information about people's health is gath-ered and analyzed, privacy concerns have become increasingly essential. This paper summarizes how machine learning (ML) methods are presently used to safeguard privacy in e-health apps. Furthermore, we discuss how privacy-preserving approaches such as differential privacy, secure multi-party computing, and homomorphic cryptography may be utilized to protect privacy in ML. The study also conducts an overview of the literature on how these methods can be used in various e- health scenarios, such as predictive modeling, disease detection, and clinical decision support. Based on the privacy-preserving technique, we classified current privacy-preserving ML work into four categories (i.e., data encryption, data anonymization, model encryption, and model obfuscation). Finally, the article discusses the challenges of applying privacy-preserving machine learning (PPML) in the e-health domain and what types of research could be conducted as open future problems in this field.

关键词： Surveys Privacy Computational modeling Machine learning Medical services Predictive models Data models

来源：评论

学校读者我要写书评

暂无评论

2D LiDAR-Based Eucalyptus Tree Measurement and Monitoring System using Mobile Application

2D LiDAR-Based Eucalyptus Tree Measurement and Monitoring Sy...

引用

International Electrical Engineering Congress (iEECON)

作者： Pruek Vanna-Iampikul Visutr Boonnateephisit Somphop Limsoontharakul Jednipat Moonrinta Matthew Dailey Mongkol Ekpanyapong Department of Electrical Engineering Burapha University Chonburi Thailand School of Engineering and Technology Asian Institute of Technology Pathumthani Thailand Dept. Computational Science Prince of Songkla University Songkhla Thailand Computer Science Field of Study School of Engineering and Technology Asian Institute of Technology Pathumthani Thailand Information & Communication Tech. School of Engineering and Technology Asian Institute of Technology Pathumthani Thailand Dept. of Industrial Systems Engineering School of Engineering and Technology Asian Institute of Technology Pathumthani Thailand

ISBN: (数字)9798331543952

ISBN: (纸本)9798331543969

LiDAR technology has rapidly advanced, offering highly accurate solutions for tree geometry estimation, which is particularly valuable in agriculture and forestry. Its ability to capture precise 2D and 3D data has revolutionized tree detection and measurement. In Eucalyptus plantations, continuous monitoring is critical to maximizing growth, enhancing paper production, and mitigating environmental damage. However, existing solutions face challenges in real-time monitoring due to factors such as parasitic interference, low-light conditions, and uneven terrain. In this work, we present a novel, end-to-end framework that enhances Eucalyptus tree measurement and monitoring. Our framework significantly improves data collection efficiency by allowing measurements at walking speed, reducing measurement distance by 50% compared to traditional manual approaches. This system integrates 2D-LiDAR with additional environmental sensors to extract key tree parameters, including circumference, position, and tree count. The collected data is stored in real-time and uploaded to a centralized server for further analysis. Experimental evaluations across 160 trees, under five distinct farm conditions, demonstrate that our system achieves 89% accuracy in tree diameter estimation and 98.5% accuracy in tree counting, significantly outperforming traditional methods. These results establish our framework as a highly effective solution for improving the accuracy and efficiency of tree monitoring in challenging environments.

关键词： Geometry Accuracy Laser radar Plantations Estimation Vegetation Production Real-time systems Time measurement Monitoring

来源：评论

学校读者我要写书评

暂无评论

Using the recurrence plots as indicators for the recognition of Parkinson’s disease through phonemes assessment

Using the recurrence plots as indicators for the recognition...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Vasileios Skaramagkas Anastasia Pentari Dimitrios I. Fotiadis Manolis Tsiknakis Dept. of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Crete Greece Institute of Computer Science Foundation for Research and Technology Hellas (FORTH) Heraklion Crete Greece Dept. of Biomedical Research Institute of Molecular Biology and Biotechnology (FORTH) Ioannina Greece Dept. of Materials Science and Engineering Unit of Medical Technology and Intelligent Information Systems University of Ioannina Ioannina Greece

Parkinson’s disease (PD) is considered to be the second most common neurodegenerative disease which affects the patients’ life throughout the years. As a consequence, its early diagnosis is of major importance for the improvement of life quality, implying that the severe symptoms can be delayed through appropriate clinical intervention and treatment. Among the most important premature symptoms of PD are the voice impairments of articulation, phonation and prosody. The objective of this study is to investigate whether the voice’s dynamic behavior can be used as possible indicator for PD. Thus in this work, we employ the recurrence plots (RPs) which derive from the analysis of the three modulated vowels /a/, /e/ and /o/, which belong to the PC-GITA dataset, and are fed as input images to a 3-channel Convolutional Neural Network-based (CNN) architecture, which, finally, differentiates the 50 PD patients from 50 healthy subjects. The experimental results obtained provide evidence that the RP-based approach is a promising tool for the recognition of PD patients through the analysis of voice recordings, with a classification accuracy achieved equal to 87%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Advanced Visual Interfaces and Interactions in Cultural Heritage (AVICH 2024) 24

Advanced Visual Interfaces and Interactions in Cultural Heri...

引用

Proceedings of the 2024 International Conference on Advanced Visual Interfaces

作者： Tsvi Kuflik Berardina Nadja De Carolis Cristina Gena Antonio Origlia Julia Sheidin Information Systems The University of Haifa Israel Department of Computer Science dipartimento di informatica universita' di bari Italy Computer Science Department of Computer Science University of Torino Italy Dept. of Electrical Engineering and Information Technology URBAN/ECO Research Center ?Federico II? University Naples Italy Italy Information Systems Braude College Israel

ISBN: (纸本)9798400717642

Cultural Heritage (CH) is a challenging domain of application for novel Information and Communication Technologies (ICT), where visualization plays a major role in enhancing the visitors’ experience, whether onsite or online. technology-supported natural human-computer interaction is a key factor in enabling access, both on-site and online, to CH assets. Recent advances in ICT enhance visitors’ access to online collections as well as their CH experience onsite, bringing even wider audiences than those who visit the physical museums. The range of visualization devices – from tiny smartwatch screens, through large situated public displays, to the latest generation of immersive Head-Mounted Displays – together with the increasing availability of real-time 3D rendering technologies for online and mobile devices and, recently, Internet of Things (IoT) approaches, Social Robotics, requires exploring how they can be applied successfully in CH. Following the successful workshops at AVI 2016, AVI 2018, AVI 2020, AVI 2022 and AVI 2024 and a large number of recent events and projects focusing on CH, the goal of the workshop is to bring together researchers and practitioners interested in presenting and discussing the potential of state of the art advanced visual interfaces in enhancing our daily cultural heritage experience. This year the workshop theme will be: AVI for accessibility in CH.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Real-Time Safety Helmet Detection Using Enhanced YOLOv5 Object Detection 9

Real-Time Safety Helmet Detection Using Enhanced YOLOv5 Obje...

引用

9th IEEE International Conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2023

作者： Zamri, Fatin Najihah Muhamad Kartiwi, Mira Zulkurnain, Nurul Fariza Yusoff, Nelidya Md. Gunawan, Teddy Surya Nur, Levy Olivia International Islamic University Malaysia Electrical and Computer Engineering Dept. Kuala Lumpur53100 Malaysia International Islamic University Malaysia Information Systems Department Kuala Lumpur53100 Malaysia Utm Kuala Lumpur Razak Faculty of Technology and Informatics Kuala Lumpur54100 Malaysia Telkom University School of Electrical Engineering Bandung Indonesia

ISBN: (纸本)9798350343380

Personal Protective Equipment (PPE) regulations require construction workers to wear safety helmets to ensure site safety. However, monitoring PPE compliance consistently in fast-paced, dynamic construction environments poses a significant challenge. In response, we developed a sophisticated object detection system that automates the real-time verification of helmet use, thereby improving safety standards and reducing the likelihood of accidents. Extensive research was conducted to analyze all feasible algorithms that can be implemented in the safety helmet detection system and compare the proposed model with an existing one to ensure the proposed system can give high accuracy and high inference speed. Therefore, YOLOv5 was identified as the ideal choice in terms of accuracy and speed, and it was then enhanced with optimized transfer learning. We began our methodology by pre-training a comprehensive Kaggle dataset before refining the model using Roboflow on a specialized dataset. Using PyTorch and YOLOv5, we conducted exhaustive model training, testing, and evaluation. Our system achieved a lightning-fast inference speed of 39.8 milliseconds and a remarkable 91.4 percent accuracy in identifying helmet compliance. The implementation of such object detection technologies has the potential to significantly increase safety helmet compliance, thereby creating a safer environment for construction workers. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Establishing Wireless Intranet Network Using UAVs and Web Application for Emergency Communications

Establishing Wireless Intranet Network Using UAVs and Web Ap...

引用

IEEE Sensors Applications Symposium, SAS

作者： Jihoon Yang Juhyun Kim Sion Kang Haeeun Ok Yijun Yoo Hyewon Koh Pilkyo Kim Alexander L. Head Anthony Smith Dept. of Computer Education Jeju National University Jeju Republic of Korea Dept. of Management Information Systems Jeju National University Jeju Republic of Korea Dept. of Computer Science and Engineering Chungnam National University Daejeon Republic of Korea Dept. of Computer Engineering Jeju National University Jeju Republic of Korea Major of Housing & Family Welfare(Faculty of Human Ecology & Welfare) Jeju National University Jeju Republic of Korea Dept. of Computer Science & Statistics Jeju National University Jeju Republic of Korea Dept. of Computer and Information Technology Purdue University West Lafayette Indiana USA

Every year, natural disasters such as earthquakes, hurricanes, volcanic eruptions, and tsunamis occur around the world. Natural disasters not only cause economic damage and casualties, but also destroy entire infrastructures. When communication infrastructure is damaged, information exchange between rescuers and victims or among rescuers themselves is not smooth, which inevitably reduces the effectiveness of relief activities. The purpose of this study is to establish a communication network using unmanned aerial vehicles (UAVs) known as drones, and to provide smooth communication services to areas where communication facilities have been destroyed through web application development. A low-altitude aerial base station (ABS) is built using a drone and provides a wireless intranet communication network. The intranet-only web application is developed to provide a service that allows people to send and receive messages and location information. In future research, separating the communication network between rescuers and non-rescuers and using multiple ABSs to build the network could serve more people in a wider disaster area.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Framework for Digital Twin Collaboration

A Framework for Digital Twin Collaboration

引用

Simulation Winter Conference

作者： Zhengchang Hua Karim Djemame Nikos Tziritas Georgios Theodoropoulos Dept. of Computer Science and Eng. Southern University of Science and Technology (SUSTech) Shenzhen China School of Computing University of Leeds Leeds UK Dept. of Informatics and Telecommunications University of Thessaly Lamia GREECE Research Institute of Trustworthy Autonomous Systems (RITAS) SUSTech Shenzhen China

ISBN: (数字)9798331534202

ISBN: (纸本)9798331534219

Digital Twins (DTs) have emerged as a powerful tool for modeling Large Complex systems (LCSs). Their strength lies in the detailed virtual models that enable accurate predictions, presenting challenges in traditionally centralized approaches due to the immense scale and decentralized ownership of LCSs. This paper proposes a framework that leverages the prevalence of individual DTs within LCSs. By facilitating the exchange of decisions and predictions, this framework fosters collaboration among autonomous DTs, enhancing performance. Additionally, a trust-based mechanism is introduced to improve system robustness against poor decision-making within the collaborative network. The framework's effectiveness is demonstrated in a virtual power plant (VPP) scenario. The evaluation results confirm the system's objectives across various test cases and show scalability for large deployments.

关键词： Accuracy Federated learning Scalability Decision making Collaboration Virtual power plants Predictive models Robustness Digital twins Complex systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：