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Breathing+: A Game-based System for Enhancing Respiratory Training and Motivation 6

Breathing+: A Game-based System for Enhancing Respiratory Tr...

引用

6th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2023

作者： Lin, Chang Yu Chu, Edward T.-H. National Yunlin University of Science and Technology Dept. of Computer Science and Information Engineering Yunlin Taiwan

ISBN: (纸本)9798350323535

Breathing difficulties, such as shortness of breath or rapid breathing, can significantly harm health and diminish the quality of life. Breathing exercises are widely recognized for their effectiveness in resolving such difficulties. They increase lung function, ease discomfort, and alleviate stress. However, current breathing-assisted methods, such as the incentive spirometer, do not accurately track the duration and frequency of training despite their advantages. Furthermore, the process of performing breathing exercises is tedious over time, making users feel bored and reducing their motivation. Thus, we presented Breathing+, a breathing video game designed to address these limitations by providing a series of game challenges. Breathing+ incorporated sensors to detect breathing signals and provided users with real-time feedback on a screen. According to the experimental results, Breathing+ achieved a breathing recognition accuracy of 95%. In addition, the response time to the user's breathing was around 0.23 s. © 2023 IEEE.

关键词： Motivation

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A Case Study of Detecting HULK-based DDoS Traffic with Random Forest Classifier

A Case Study of Detecting HULK-based DDoS Traffic with Rando...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Cai, Yi-Xian Chang, Tsu-Chen Wang, Chih-Chiang National Kaohsiung University of Science and Technology Dept. of Computer Science and Information Engineering Kaohsiung Taiwan

ISBN: (纸本)9798350324174

Modern network administration desires to have early detection of DDoS traffic before damages occur. Nevertheless, as Internet traffic grows over years, it becomes more challenging to detect DDoS traffic in an efficient and effective manner. The survey of existing literature shows that random forest classifier, when applied to DDoS detection, yields great performance at low learning costs. This work is devoted to a case study of implementing and using random forest classifier to detect DDoS traffic generated by a well-known DDoS tool named HULK. Our result indicates that when used with a good feature selection mechanism, random forest classifier can achieve a high detection accuracy with fast training time. © 2023 IEEE.

关键词： HTTP

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Ensuring Electronic Health Record (EHR) Privacy using Zero Knowledge Proofs (ZKP) and Secure Encryption Schemes on Blockchain 5

Ensuring Electronic Health Record (EHR) Privacy using Zero K...

引用

5th International Conference on Advancements in Computing, ICAC 2023

作者： Ranaweera, T.A.V.Y. Hewage, H.N.H. Hapuhinna, H.K.D.W.M.C.B. Preethilal, K.L.K.T. Senarathne, Amila Ruggahakotuwa, Laneesha Sri Lanka Institute of Information Technology Dept. Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

In the haste of EHR digitization, the protection of patient data becomes paramount, casting a spotlight on small healthcare clinics grappling with the threats of an ever more interconnected healthcare sector. That is due to the existing centralized system and traditional password-based authentications which cause a single point of failure. Besides this patient consent for EHR sharing is narrowed to a one-time consent. To overcome these problems, this study suggests a robust solution that makes data sharing utilizing blockchain while achieving privacy using web-based Zero Knowledge Proofs (ZKP) authentication and Homomorphic Encryption (HE). The research also considers securely outsourcing EHRs to research organizations to improve data exchange for research purposes. Along with patient-controlled encryption, consent control, and time-limited data access, it also explores dynamic consent management while complying with healthcare standards. Lastly, this study stream-lines secure data sharing with insurance providers while ensuring patient privacy and defending against insurance fraud. © 2023 IEEE.

关键词： Blockchain

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Deep Learning for Skin Disease Diagnosis with End-To-End Data Security 2

Deep Learning for Skin Disease Diagnosis with End-To-End Dat...

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2nd International Conference on Informatics, ICI 2023

作者： Pingulkar, Shriya Divekar, Diti Tiwary, Aryaman K. J. Somaiya College of Engineering Dept. of Information Technology Mumbai India

ISBN: (纸本)9798350343830

Skin diseases, particularly skin cancer, pose significant health risks, necessitating accurate and timely diagnosis. Traditional manual analysis methods, however, are subject to errors and can be time-consuming. To address these challenges, we propose an automated classification system for skin disease detection that leverages deep learning algorithms to accurately diagnose skin lesions. This system facilitates secure sharing of diagnostic information among healthcare professionals, promoting collaborative treatment planning. Recognizing the critical importance of data security and confidentiality in the healthcare industry, our system employs state-of-The-Art security measures to protect sensitive patient data whilst medical data transfer. By maintaining the integrity of patient information and adhering to regulatory requirements, our skin disease classification system provides healthcare professionals with fast and accurate diagnosis, and the confidence that patient privacy is upheld at all times. © 2023 IEEE.

关键词： Data transfer

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A Blockchain-Based E-Voting System for India: Addressing Security Challenges with Aadhaar Card Authentication 3

A Blockchain-Based E-Voting System for India: Addressing Sec...

引用

3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Shadab, Mohd Kumar, Prashant Kumar, Saurabh Rajkiya Engineering College Dept. of Information Technology Uttar Pradesh Ambedkar Nagar224122 India

ISBN: (纸本)9798350322842

The integration of technology in various spheres of social life has brought about positive transformations, and one significant game-changer is blockchain technology. With its decentralized architecture and immutability property, blockchain has revolutionized numerous services, offering a level playing field for both consumers and large entities like corporations and governments. The immutability feature ensures the integrity of the voting process by eliminating any possibility of tampering, while the decentralized nature of the blockchain allows for transparency, enabling independent verification of election results. Although blockchain-based e-voting systems provide advantages such as transparency, immutability, and decentralization, there are also challenges that need to be addressed. Among these challenges, scalability is a major concern. Additionally, ensuring the security of the election process is crucial, covering aspects like voter impersonation, hacking, and tampering of votes. However, by incorporating robust measures such as Aadhaar card authentication for voter identification, along with the implementation of advanced security protocols like multi-factor authentication and encryption. © 2023 IEEE.

关键词： Authentication

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Steganalysis on Dual-Layer Security of Messages Using Steganography and Cryptography 15

Steganalysis on Dual-Layer Security of Messages Using Stegan...

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15th International Conference on information technology and Electrical engineering, ICITEE 2023

作者： Shamsi, Zeba Saha, Anish Kumar Patgiri, Ripon Singh, Khoirom Motilal Singh, Laiphrakpam Dolendro National Institute of Technology Dept. of Computer Science and Engineering Assam Silchar788010 India Indian Institute of Information Technology Dept. of Computer Science and Engineering Manipur Senapati795002 India

ISBN: (纸本)9798350304466

Recently, Bansal et al. proposed a dual-layer message security technique using steganography and cryptography. An index table maps each text data to an index point and an elliptic curve point. The text data are encrypted using elliptic curve cryptography, and the corresponding index values are embedded in a cover image using the Least Significant Bit Inversion technique. The proposed paper breaks the security of the key exchange technique in the Bansal et al. method and the secret text is extracted. © 2023 IEEE.

关键词： Steganography

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Cardiovascular Disease Prediction with Machine Learning Algorithms and Interpretation using Explainable AI methods: LIME & SHAP 3

Cardiovascular Disease Prediction with Machine Learning Algo...

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3rd International Conference for Advancement in technology, ICONAT 2024

作者： Pratheek, N. Balaji Yashas, D.H. Bhanu Prakash, Y.R. Bharadwaj, Anirudh M Kodapalli, Ashwini Rao, Trupthi Global Academy of Technology Dept. of Information Science & Engineering Karnataka Bengaluru India Global Academy of Technology Dept of Artificial Intelligence & Data Science Karnataka Bengaluru India

ISBN: (纸本)9798350354171

Every year a third of the population dies due to cardiovascular disease and these numbers grow exponentially which is one of the leading cause of deaths. Cardiovascular disease is a group of disorders that affect the heart and blood vessels. These disorders often result from high cholesterol, high blood pressure, smoking, obesity, and many other medical attributes. Therefore, early intervention and diagnosis of cardiovascular diseases improves the patient's quality of life. In this era of AI and ML, the ML techniques integrated with explainable AI are a promising tool for implementing and getting improved accuracies in the detection of cardiovascular disease. With the usage of Binary classification dataset on heart disease this paper explored a comparative study with various machine learning algorithms which includes single classifiers (LR, KNN, DT, SVM), bagging(RF), and boosting(XG, ADA, CAT, GRADIENT), ensemble machine learning model using RF, GRAD, ADA, XG, CAT helped in achieving exceptional accuracy of 89.13%, ensemble model with hyperparameter tuning techniques (GridsearchCV and RandomsearchCV) and implementation XAI methods(lime and sharp). In a comparative analysis of boosting algorithms specifically CAT and ADA boost outperformed other algorithms in identifying cardiovascular disease. The hyperparameter tuning techniques help improve the accuracy of Random forest classifier method to an impressive 88.26%. Additionally, the use of XAI methods such as LIME and SHARP provides global and local insights into model behavior and feature importance and represents it graphically which helps in better *** use of these machine learning models in remote areas where diagnosis and specialized treatment of heart-related disease is limited this model plays a pivotal role by helping in early intervention and diagnosis of cardiovascular disease. © 2024 IEEE.

关键词： Diagnosis

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Optimizing Solar Energy Adoption through Technological and Economic Initiatives 3

Optimizing Solar Energy Adoption through Technological and E...

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3rd International Conference on Creative Communication and Innovative technology, ICCIT 2024

作者： Santoso, Nuke Puji Lestari Desrianti, Dewi Immaniar Darmawan, Dani Wahid, Syahrul MuArif Fitriani, Anandha Fauzi, Ahmad Yadi University of Raharja Dept. of Informatics Technology Tangerang Indonesia University of Raharja Dept. of Informatics Engineering Tangerang Indonesia Bina Bangsa University Master of Information Technology Serang Indonesia Sesindo Dept. of Economics and Business Tangerang Indonesia Cai Sejahtera Indonesia Dept. of Economics and Business Tangerang Indonesia Pandawan Sejahtera Indonesia Dept. of Informatics Engineering Tangerang Indonesia

ISBN: (纸本)9798350367492

The global energy landscape is undergoing a significant transformation, emphasizing the need for sustainable and renewable energy sources. Solar energy, with its abundant availability, stands out as a potential solution to reduce greenhouse gas emissions and meet growing energy demands. Indonesia, blessed with ample sunlight, has yet to fully capitalize on this potential due to technological and economic barriers. This study aims to analyze the role of technology and economic benefits in enhancing solar energy adoption. Using a comprehensive structural equation modeling approach, the research examines the interplay between technological advancements and economic incentives on adoption decisions. Data were collected from residential, commercial, and industrial sectors in Indonesia. The findings reveal that while both technological factors and economic benefits significantly influence solar energy adoption, economic benefits, such as cost savings and return on investment, have a more substantial impact. The study concludes with actionable recommendations for policymakers and industry stakeholders, emphasizing the need for increased awareness of economic incentives and translating technological improvements into clear economic advantages for users. By addressing these factors, Indonesia can accelerate its transition towards sustainable energy systems. © 2024 IEEE.

关键词： Energy economics

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Exploring Deep Learning Techniques for Automated Cataract Detection in Digital Camera Imagery

Exploring Deep Learning Techniques for Automated Cataract De...

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2024 International Conference on Advances in Modern Age Technologies for Health and engineering Science, AMATHE 2024

作者： Kamepalli, Sujatha Veeranjaneyulu, N. Bodapati, Jyostna Devi Vignan's Foundation For Science Technology And Research Dept. Department Of Information Technology And Computer Application Guntur India Vignan's Foundation For Science Technology And Research Dept. Department Of Advnced Computer Science And Engineering Guntur India

ISBN: (纸本)9798350371567

Cataracts, a prevalent eye condition impacting vision, demand accurate and prompt identification for effective risk reduction and blindness prevention. Traditional methods of cataract diagnosis rely heavily on manual examination by ophthalmologists, which can be time-consuming and subject to human error. With the advent of digital imaging technology, there is an opportunity to enhance the efficiency of cataract detection. The deep neural network models VGG19 and ResNet-50 are recommended in this paper for automatic cataract identification on digital camera images. To optimize network performance, adjustments to loss and activation functions were made, incorporating minimal kernels, reduced training parameters, and layers. This resulted in a ResNet-50 model with significantly decreased computational cost and average operating time compared to the cutting-edge models. The proposed ResNet 50 model achieved an average accuracy of 93.41%, outperforming the VGG 19 model, which had an accuracy of 91.13%. This research contributes to the evolution of cataract detection methodologies, emphasizing the potential of deep learning models, particularly ResNet-50, in improving diagnostic accuracy and operational efficiency for enhanced eye health outcomes. © 2024 IEEE.

关键词： Digital cameras

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A Probabilistic Topology Inference Method for Networked Dynamical System via Single Excitation 63

A Probabilistic Topology Inference Method for Networked Dyna...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Jiao, Qing Li, Yushan He, Jianping Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Dept. of Automation Shanghai China

ISBN: (纸本)9798350316339

A growing number of works have investigated inferring the topology of networked dynamical systems from observations, such as to better understand the system behaviour. Despite the tremendous advances, most of them require the observations to be abundant. This paper focuses on inferring the topology by injecting single excitation on a node and collecting several steps of noisy observations. The problem is challenging because the noises cannot be depressed in several observations and are mixed with the injected excitation, making it hard to directly reveal the topology. To practice, we develop a probabilistic method based on the hypothesis test framework. First, we infer the neighbors that are within h-hop of the excited node and derive the accuracy guarantees. Then, we extend the method to infer the exact h-hop neighbors. A computable lower bound for the accuracy probability is established to provide confidence support in the inference procedures. Furthermore, we give the conditions of excitation input to ensure a desired inference probability, which provides guidance for the input design. Numerical simulations are conducted to verify the effectiveness of the proposed method. © 2024 IEEE.

关键词： Network topology

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