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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Serhii Holdobin Natalia Brynza Olha Tiutiunyk Olena Serhiienko Ihor Sosnov Pavlo Samus Industrial and Biomedical Electronics Department Kharkiv polytechnic institute National Technical University Kharkiv Ukraine Department of Informatics and Computer Technology Simon Kuznets Kharkiv National University of Economics Kharkiv Ukraine Department of Applied Mathematics Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of Informatics and Computer Engineering Simon Kuznets Kharkiv National University of Economics Kharkiv Ukraine Business Trade and Logistics Department Kharkiv Polytechnic Institute National Technical University Kharkiv Ukraine

ISBN: (数字)9798331510886

ISBN: (纸本)9798331510893

The development of data processing technologies, microelectronics and sensor systems allows for high-precision multiparametric analysis of biosignals in real time. The paper considers the problem of automating medical processes to reduce the influence of the human factor and increase the accuracy of diagnostics. An improved method of multiparametric analysis of biosignals is proposed for long-term monitoring of the state of the cardiovascular system using modern sensor devices, data processing algorithms and artificial intelligence technologies. The research is aimed at improving the methods of collecting, transmitting and analyzing biosignals, which contributes to the creation of personalized medical devices and effective prediction of cardiovascular pathologies. The issues of classification of devices and biosignals, as well as their mathematical modeling to increase the accuracy of diagnostics, are considered.

关键词： Cardiovascular system Wireless sensor networks Accuracy Medical devices Heuristic algorithms Robot sensing systems Prediction algorithms Real-time systems Classification algorithms Monitoring

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Augmented Reality Display of Robot with Graphs of Property Response Using Its USD Model

Augmented Reality Display of Robot with Graphs of Property R...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Kazuki Tsukamoto Masanobu Koga Department of Creative Informatics Kyushu Institute of Technology Department of Intelligent and Control Systems Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology

This study proposes a method that can easily grasp the relationship between the actual machine and the graphs. In recent years, there has been a lot of research on augmented reality displays. The fields of research range from education to welfare. In the development of control systems, when evaluating the performance of a system by simulation or experiment, the results are often checked as graphs. Since the graphs are checked on a PC using CAD or other means, it is difficult to know which part of the actual machine each graph corresponds to. Therefore, we developed a tool that displays graphs in augmented reality around the actual machine through a camera on a mobile terminal. To display graphs in augmented reality, it is important to obtain the coordinates of the actual machine and display them in a location associated with the device. Therefore, a USD model with the same shape and size as the actual machine is used. This is achieved by displaying the USD model in augmented reality so that it is superimposed on the actual machine. The accuracy of the tool was also examined and its usefulness was evaluated.

关键词： Solid modeling Automation Shape Robot kinematics Robot vision systems Education Control systems

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A Lightweight and Robust Access Control Protocol for IoT-based e-Healthcare Network

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IEEE Transactions on Mobile Computing 2025年

作者： Ghaffar, Zahid Kuo, Wen-Chung Mahmood, Khalid Tariq, Tayyaba Shamshad, Salman Das, Ashok Kumar Alenazi, Mohammed J.F. National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Douliu64002 Taiwan National Yunlin University of Science and Technology Department of Computer Science and Information Engineering Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University Department of Computer Science and Engineering College of Informatics 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh Saudi Arabia

Internet of Things (IoT) devices are crucial components in e-healthcare networks. It enables remote patient health monitoring and facilitates seamless communication among medical sensors, wearable devices, and healthcare providers through public communication channels. Despite these advantages, the use of public communication among medical sensors in e-healthcare networks introduces critical challenges, such as vulnerability to impersonation, physical capture, and ephemeral secret leakage, particularly in resource-constrained environments. In recent years, various access control protocols have been developed to mitigate these risks. However, these protocols often fail to ensure robust security while incurring significant communication and computation overhead. To overcome these limitations, we propose a lightweight and robust access control protocol for IoT-based e-healthcare networks using chaotic maps. We propose a novel protocol that integrates a PUF-based mechanism to mitigate the challenges of physical tampering and cloning attacks in e-healthcare networks. It leverages the inherent uniqueness of PUF and enhances security through the high-entropy properties of chaotic maps. We analyze the proposed protocol informally, which confirms that it significantly bolsters efficiency and security. We also validate the security using the Random or Real (RoR) model. Moreover, we verify the security of the proposed protocol using Scyther. These analyses highlight that the proposed protocol offers robust resistance to numerous attacks, such as impersonation, physical capture, and ephemeral secret leakage. Moreover, we also compare it with existing and relevant protocols. The comparative analysis showcases its superior performance. Notably, the proposed authentication protocol significantly reduces 46.84% computational overhead and decreases 31.30% communication overhead, underscoring its enhanced performance and resource efficiency. © 2002-2012 IEEE.

关键词： Authentication

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A Logical Investigation of Stock Market Prediction and Analysis using Supervised Machine Learning Algorithm

A Logical Investigation of Stock Market Prediction and Analy...

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Networking and Communications (ICNWC), International Conference on

作者： R. Dhanalakshmi V. Vasantha Kumar Saleem Basha N. Vijayaraghavan School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of CSE KCG College of Technology Chennai India Computing and informatics department Mazoon University college Muscat oman

In the Field of computer science, artificial intelligence (AI) is a broad field, which is concerned with structuring smart products and machines able to perform tasks which require the intellectual capability of humans. Artificial Intelligence is in need for Stock trading’s future. Robotic advisers examine millions of pieces of data using artificial intelligence and carry out the analysis at the best possible price. Market forecasts are more precise and effective thanks to the analysts. For providing higher returns, the trading firms efficiently mitigate the risk using Artificial Intelligence Techniques. Our proposed Stock Market system is a Web Application which uses the Random Forest Algorithm. The Random Forest Algorithm comes under Supervised Learning. With the system, one can forecast the stock prices for the subsequent days.

关键词： computer science Machine learning algorithms Social networking (online) Supervised learning Forestry Prediction algorithms Stock markets

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Design and Implementation of an IoT-Based Smart Irrigation System for Optimized Water Management in Wheat Cultivation

Design and Implementation of an IoT-Based Smart Irrigation S...

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International Conference on System Modeling & Advancement in Research Trends (SMART)

作者： Ravi Shankar Shukla Remya P. George Sajithunisa Hussain Nazia Ahmad Prakash Babu Vishal Jain Department of Computer Science College of Computing and Informatics Saudi Electronic University Saudi Arabia Computer Science Department The Applied College Imam Abdulrahman Bin Faisal University Saudi Arabia Dept of IT Acharya Institute of Technology Bangalore India

The current study presents the planning and implementation of a custom-built, Internet of Things (IoT)-based smart irrigation system for wheat cultivation that helps to combat problems such as water scarcity and inefficiency in traditional irrigation methods. The proposed device employs a network of environmental sensor that ensures optimal crop development with minimum water waste. These sensors monitor soil temperature and moisture levels and shows significant improvements in water management efficiency. When compared to standard irrigation approaches, the system's pilot installation results reveal considerable water usage reductions and benefits in the health of the wheat crop. These findings prove that the system is efficient at optimizing resource use and show how it can change the way wheat is farmed forever.

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Password Manager with Multi-Factor Authentication

Password Manager with Multi-Factor Authentication

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Networking and Communications (ICNWC), International Conference on

作者： R. Dhanalakshmi N. Vijayaraghavan S. Narasimhan Saleem Basha School of Computer science and Engineering Vellore Institute of Technology Chennai India Department of Mathematics KCG College of Technology Chennai India Computing and informatics department Mazoon University college muscat oman

Data breach is a serious issue as it leaks the personal information of more than billions of users and their privacy is compromised. More than 77% of organizations do not have a Cyber Security Incident Response plan. So, it is necessary to be informed of network security and ways to store and generate secured passwords. Having different and random passwords for ones digital accounts can exponentially increase the security of user’s data. The goal of this project is to build a password manager which can securely store and encrypt passwords and other data. The multifactor authentication will provide increased security to validate the user into password management system. Multifactor authentication system includes physical security key and graphical password authentication.

关键词： Privacy Data privacy Multi-factor authentication computer bugs Passwords Organizations Network security

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An Early Warning System to Predict Earthquakes based on WT-ARIMA-ANN Model 3

An Early Warning System to Predict Earthquakes based on WT-A...

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3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Babu, Uppara Raghu Raha, Shrinwantu Khan, Mujtaba Ali Yamini, C. Jayadurga, R. Kalra, Gourav Srinivasa Ramanujan Institute of Technology Department of Civil Engineering Andhra Pradesh India Bhairab Ganguly College Department of Geography Belgharia Kolkata India University of North Carolina Department of Computer Science College of Computing and Informatics Charlotte United States PSNA College of Engineering and Technology Department of Mathematics Tamil Nadu Dindigul India Prince Shri Venkateshwara Padmavathy Engineering College Department of MBA Tamil Nadu Chennai India Department of Mechanical Engineering Mullana India

ISBN: (纸本)9798350343632

A devastating earthquake is one of the Earth's most destructive natural disasters. Real-time seismic monitoring facilities can evolve into Earthquake Early Warning (EEW) systems with the help of modern technology, property damage, reducing the number of casualties, and economic losses. The proposed EEW system's goal is to supply a precise damage assessment just before an earthquake hits a certain area. The proposed method involves preprocessing, feature extraction, and model training. It is recommended to preprocess the data by first filtering it and then reformatting it. Filtering is essential for getting rid of irrelevant or noisy information. In feature extraction, the Principal Component Analysis (PCA) provides a useful perspective on the data by establishing a new coordinate system, and it also offers a method for reducing the data's dimensionality. Once the features have been obtained, the models are trained with WT-ARIMA-ANN. The proposed method outperforms two widely used alternatives, ARIMA and ANN. © 2023 IEEE.

关键词： Autoregressive Integrated Moving Average (ARIMA) Earthquake Early Warning (EEW) Principal Component Analysis (PCA)

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Online Resource Allocation for User Experience Improvement in Heterogeneous MEC Systems

Online Resource Allocation for User Experience Improvement i...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Weiya Ni Jingwen Tong Liqun Fu Institute of Artificial Intelligence Xiamen University Xiamen China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong School of Informatics Xiamen University Xiamen China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Mobile edge cloud (MEC) has emerged as a critical technology for enabling low-latency and real-time mobile device applications. However, an efficient resource allocation framework for improving the user experience in MEC with heterogeneous users is still missing, especially considering the recent sparks of AI-generated content applications. This paper proposes a double-closed-loop online resource allocation (DORA) framework for user experience improvement. This framework employs inner and outer loops to construct the optimal online allocation strategy and recommend a suitable strategy for different types of users, respectively. Based on the DORA framework, we put forth OR2A-HetU, an Online Resource Recommendation and Allocation algorithm for Heterogeneous Users, to solve this resource allocation problem. The OR2A-HetU algorithm proceeds sequentially and can converge to the optimal solution when the time horizon is sufficiently large. The numerical results show that the proposed algorithm outperforms the baseline algorithms, and the user complaint rate decreases from 48.8% to 27.5% when the available resources increase.

关键词： Multi-access edge computing User experience Stability analysis Real-time systems Mobile handsets Resource management Sparks Low latency communication Optimization Numerical stability

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Correction to: On some novel bright, dark and optical solitons to the cubic-quintic nonlinear non-paraxial pulse propagation model

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Optical and Quantum Electronics 2024年第4期56卷 1-3页

作者： Tariqa, Kalim U. Khater, Mostafa M. A. Inc, Mustafa Department of Mathematics Mirpur University of Science and Technology Mirpur Pakistan School of Medical Informatics and Engineering Xuzhou Medical University Xuzhou People’s Republic of China Department of Basic Science Obour High Institute for Engineering and Technology Cairo Egypt Department of Computer Engineering Biruni University Istanbul Turkey

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ECG-Image-Database: A Dataset of ECG Images with Real-World Imaging and Scanning Artifacts;A Foundation for computerized ECG Image Digitization and Analysis

arXiv

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arXiv 2024年

作者： Reyna, Matthew A. Deepanshi Weigle, James Koscova, Zuzana Campbell, Kiersten Shivashankara, Kshama Kodthalu Saghafi, Soheil Nikookar, Sepideh Motie-Shirazi, Mohsen Kiarashi, Yashar Seyedi, Salman Clifford, Gari D. Sameni, Reza Department of Biomedical Informatics Emory University AtlantaGA30322 United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Department of Biomedical Engineering Georgia Institute of Technology AtlantaGA30332 United States

Objective: We introduce ECG-Image-Database, a large and diverse collection of electrocardiogram (ECG) images generated from ECG time-series data that exhibit real-world scanning, imaging, and physical artifacts. This dataset addresses the need for digitizing paper-based and non-digital ECGs for computerized analysis, providing a foundation for developing robust machine and deep learning models capable of ECG image digitization. Approach: We used ECG-Image-Kit, an open-source Python toolkit, to generate realistic images of 12-lead ECG printouts from raw ECG time-series data. We include images with realistic distortions, including noise, wrinkles, stains, and perspective shifts generated both digitally and physically. The toolkit was applied to 977 12-lead ECG records from the PTB-XL database and 1,000 from Emory Healthcare to create high-fidelity synthetic ECG images. These 1,977 unique images were subjected to both programmatic distortions using ECG-Image-Kit and to physical effects, such as soaking, staining, and mold growth, followed by scanning and photography under various lighting conditions to create real-world artifacts, producing a total of 35,595 images. Main results: The resulting dataset includes 35,595 software-labeled ECG images (generated from 1,977 unique records) from different sources (in Germany and the USA) with a wide range of imaging artifacts and distortions. The dataset provides ground truth time-series data alongside the corresponding images, offering a reference for training and evaluating machine and deep learning models for ECG digitization and classification. The images vary in quality, ranging from clear scans of clean papers to noisy photographs of degraded papers, enabling the development of more generalizable and robust digitization algorithms. Significance: ECG-Image-Database addresses a critical gap in cardiovascular research by supporting the development of machine learning models capable of classifying or converting ECG images int

关键词： Photography

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