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Monitoring of Heart and Respiration Rate Using a 3D Knitted T-shirt with Textile-based Electrodes

IFAC-PapersOnLine 2024年第30期58卷 49-54页

作者： Nada Al-azzawi Irem Yunculer Asli Tuncay Atalay Ozgur Atalay Gökhan Ince Faculty of Computer and Informatics Engineering Computer Engineering Department Istanbul Technical University Istanbul 34469 Turkey Faculty of Textile Technologies and Design Textile Engineering Department Istanbul Technical University Istanbul 34437 Turkey

The emergence of e-textiles has facilitated impressive growth in the field of wearable technologies in recent years. Textile-based electrodes enabled long-period electrocardiogram monitoring within the health care field as they are less irritant to the skin and can be naturally embedded into the clothes. Beyond the specific health-oriented applications, physiological signals monitoring is also beneficial during other activities such as daily activities and sports. In this work, a system of a knitted t-shirt embedded with textile electrodes that targets measuring heart rate and respiration rate during various positions and activities is created. The performance of the implemented system is benchmarked against the performance of an off-the-shelf product using root mean square error. It has been shown that the proposed system can achieve good performance with heart rate respiration rate values close to that of the benchmark device.

关键词： E-textile technology smart t-shirt wearable technology heart rate monitoring ECG ECG derived respiration

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AVIG: A Real-Time Visual Inspection for Guava Grading System Using computer Vision and XGBoost 23

AVIG: A Real-Time Visual Inspection for Guava Grading System...

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8th International Conference on Sustainable Information engineering and Technology, SIET 2023

作者： Setyawan, Raden Arief Perdana, Rizal Setya Harilegawa, Made Wena Balantimuhe, Alan Stevrie Basuki, Achmad Department of Electrical Engineering Faculty of Engineering Brawijaya University Malang Indonesia Department of Informatics Engineering Faculty of Computer Science Brawijaya University Malang Indonesia Directorate of Information Technology Brawijaya University Malang Indonesia

ISBN: (纸本)9798400708503

The conventional approach to manual inspection can be described by its considerable time and labor demands and the unavoidable occurrence of human error when faced with the inspection of a large number of products. Therefore, the application of an automated visual inspection system is frequently employed. The camera(s) can easily capture visual features for automatic visual inspection. However, it is essential to note that there are limitations when using this method to estimate the size-based grading system. The volume measurement is an essential feature in the field of automatic image analysis for fruit and vegetable grading, specifically guava. In this study, we propose a novel image analysis approach that utilizes a dual-view camera system to enhance the accuracy of volume approximation, particularly in scenarios involving non-perfect spherical objects. Hence, this research presents the training process of a comprehensive model for estimating the volume of objects with irregular shapes, named AVIG (Automatic Visual Inspection for Grading). The model utilizes the ellipsoid approximation technique, a dual-view camera, and XGBoost algorithm. The results from the accuracy comparison demonstrate that XGBoost shows the highest degree of accuracy, specifically 86%, thereby outperforming the performance of other algorithms. The comprehensive experiment conducted in this study has shown that the proposed architecture, AVIG, exhibits superior performance compared to previous research in terms of automatic evaluation of moving objects. © 2023 ACM.

关键词： computer vision

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Comparison of The Accuracy of Predicting The Number Of Positive Covid-19 Between The Neural Network and LSTM Methods

Comparison of The Accuracy of Predicting The Number Of Posit...

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2023 International Conference on informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Riyanto, Eko Amalia, Rifka Dwi Stmik Himsya Informatics Engineering Semarang Indonesia Universitas Pembangunan Nasional Veteran Jakarta Information Systems Faculty of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350307306

The COVID-19 pandemic (Coronavirus) is likely to be one of the most serious global problems in the last year. Countries do not have similar experiences with the spread of the virus and its impact from various fields. Estimating the number of COVID-19 cases in the past can help in decision-making about action and plan for virus prevention. The study aims to provide accurate predictive model in predicting confirmed cases of COVID-19 in Semarang city. In predicting the number of people exposed to Covid-19 positive need to be accurate and accurate methods, in some previous studies the two methods most recommended are neural network and LSTM (Long Short Term Memory) which have high levels of accuracy. Based on research that has been carried out that the results of accurate prediction comparison between RNN and LSTM obtain the smallest MSE result is the method. © 2023 IEEE.

关键词： Forecasting

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Early Detection of Alzheimer’s Disease Based on Laplacian Re-Decomposition and XGBoosting

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computer Systems Science & engineering 2023年第9期46卷 2773-2795页

作者： Hala Ahmed Hassan Soliman Shaker El-Sappagh Tamer Abuhmed Mohammed Elmogy Information Technology Department Faculty of Computers and InformationMansoura UniversityMansoura35511Egypt Faculty of Computer Science and Engineering Galala UniversitySuez435611Egypt Faculty of Computers and Artificial Intelligence Benha UniversityBanha13518Egypt College of Computing and Informatics Sungkyunkwan UniversitySuwonKorea

The precise diagnosis of Alzheimer’s disease is critical for patient treatment,especially at the early stage,because awareness of the severity and progression risks lets patients take preventative actions before irreversible brain damage *** is possible to gain a holistic view of Alzheimer’s disease staging by combining multiple data modalities,known as image *** this paper,the study proposes the early detection of Alzheimer’s disease using different modalities of Alzheimer’s disease brain ***,the preprocessing was performed on the ***,the data augmentation techniques are used to handle ***,the skull is removed to lead to good *** the second phase,two fusion stages are used:pixel level(early fusion)and feature level(late fusion).We fused magnetic resonance imaging and positron emission tomography images using early fusion(Laplacian Re-Decomposition)and late fusion(Canonical Correlation Analysis).The proposed system used magnetic resonance imaging and positron emission tomography to take advantage of *** resonance imaging system’s primary benefits are providing images with excellent spatial resolution and structural information for specific *** emission tomography images can provide functional information and the metabolisms of particular *** characteristic helps clinicians detect diseases and tumor progression at an early ***,the feature extraction of fused images is extracted using a convolutional neural *** the case of late fusion,the features are extracted first and then ***,the proposed system performs XGB to classify Alzheimer’s *** system’s performance was evaluated using accuracy,specificity,and *** medical data were retrieved in the 2D format of 256×256 *** classifiers were optimized to achieve the final results:for the decision tree,the maximum depth of a tree was *** best number of trees for the random forest was 60;for

关键词： Alzheimer’s disease(AD) machine learning(ML) image fusion Laplacian Re-decomposition(LRD) XGBoosting

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Blockchain-based Internet of Musical Things

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Blockchain(Research and Applications) 2022年第3期3卷 60-69页

作者： Luca Turchet Chan Nam Ngo Department of Information Engineering and Computer Science University of TrentoTrento38122Italy Faculty of Mathematics Informaticsand Mechanics of the University of WarsawWarsaw00-927Poland

Blockchain technology is impacting several industries,including the creative industries and those operating in the Internet of Things(IoT).Lately,researchers'attention has been devoted to the application of blockchain in the recorded music ***,thus far,no research has investigated the use of such technology in the Internet of Musical Things(IoMusT).The IoMusT is a new area emerging in industry and academy as an extension of the IoT to the musical *** IoMusT itself,as the IoT,is a distributed network of musical things,which are objects augmented with information and communication technologies serving a musical *** IoMusT vision requires,above all,IoT features such as decentralization,seamless authentication,transparency,data integrity and privacy,and self-maintenance,as well as the musical domain features such as efficient handling of copyrights and speed of royalties *** features can be brought by *** this paper,we investigate the integration of blockchain technology with the IoMusT,and we name such synthesis“Blockchain-based IoMusT”.We present a vision for this new paradigm in terms of the novel opportunities that are enabled,and we propose a set of application scenarios enabled by technological ***,we outline the open research directions in this promising area.

关键词： Internet of Musical Things Blockchain Music industry Privacy Security Internet of Things

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Evaluation of the security of password-protected encrypted RAR3 and RAR5 archives

Evaluation of the security of password-protected encrypted R...

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2022 International Conference on Networks, Communications and Information Technology, NCIT 2022

作者： Krupalija, Ehlimana Mrdović, Saša Cogo, Emir Prazina, Irfan Bećirović, Šeila Department of Computer Science and Informatics Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9783800760190

Roshal Archive (RAR) format is one of the most widely used data archive formats, enabling users to reduce the size of data and protect it with the desired password before the data is transferred to its intended recipients over the network. This work focuses on the security of encrypted RAR archives and various different approaches for their decryption. Two different datasets composed of randomly generated and real-world user passwords were used for deploying brute force and dictionary attacks on password-protected RAR archives. Two available and widely used tools, John the Ripper and Hashcat, were used for cracking passwords of encrypted RAR3 and RAR5 archives. Experimental results indicate that both brute force and dictionary attacks were unsuccessful for RAR archives protected with randomly generated passwords, even of very small length. Real-world user passwords were successfully cracked only partially by brute force attacks, whereas dictionary attacks were very successful. The success rate for RAR5 archives was only slightly lower than for RAR3 archives and processing times were similar, indicating that this new version of the RAR format does not significantly improve data security. Instead, the security of RAR archives can be increased by using longer passwords more similar to randomly generated data, which are not present in commonly used dictionaries, as indicated by the experimental results. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Cryptography

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Modelling and Performance Analysis of Visible Light Communication System in Industrial Implementations

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computers, Materials & Continua 2023年第11期77卷 2189-2204页

作者： Mohammed S.M.Gismalla Asrul I.Azmi Mohd R.Salim Farabi Iqbal Mohammad F.L.Abdullah Mosab Hamdan Muzaffar Hamzah Abu Sahmah M.Supa’at Faculty of Electrical Engineering Faculty of EngineeringUniversiti TeknologiMalaysiaSkudai81310Malaysia Lightwave Communications Research Group(LCRG) Faculty of Electrical EngineeringUniversiti TeknologiSkudaiJohorMalaysia Department of Communication Engineering Faculty of Electrical and Electronic EngineeringUniversiti Tun Hussein Onn Malaysia(UTHM)Parit RajaBatu PahatJohor86400Malaysia Faculty of Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400Malaysia Department of Computer Science University of São PauloSão PauloBrazil

Visible light communication(VLC)has a paramount role in industrial implementations,especially for better energy efficiency,high speed-data rates,and low susceptibility to ***,since studies on VLC for industrial implementations are in scarcity,areas concerning illumination optimisation and communication performances demand further *** such,this paper presents a new modelling of light fixture distribution for a warehouse model to provide acceptable illumination and communication *** proposed model was evaluated based on various semi-angles at half power(SAAHP)and different height levels for several parameters,including received power,signal to noise ratio(SNR),and bit error rate(BER).The results revealed improvement in terms of received power and SNR with 30 Mbps data *** modulations were studied to improve the link quality,whereby better average BER values of 5.55×10^(−15) and 1.06×10^(−10) had been achieved with 4 PAM and 8 PPM,*** simulation outcomes are indeed viable for the practical warehouse model.

关键词： Visible light communication(VLC) industrial applications warehouse model light fixtures bit error rate(BER)

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Blockchain and Artificial Intelligence: Enhancing Security and Efficiency in Metaverse Payment Transactions 6th

Blockchain and Artificial Intelligence: Enhancing Security a...

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6th International Conference on Recent Innovations in Computing, ICRIC 2023

作者： Rajawat, Anand Singh Goyal, S.B. Shaari, Rosnizah Bt Verma, Chaman Singh, Pradeep Kumar School of Computer Sciences and Engineering Sandip University Nashik Nashik India City University Petaling Jaya Malaysia City University Petaling Jaya46100 Malaysia Department of Media and Educational Informatics Faculty of Informatics Eötvös Loránd University Budapest1053 Hungary Department of Computer Science and Engineering Central University of Jammu Jammu India

ISBN: (纸本)9789819778614

Blockchain and artificial intelligence (AI) are two revolutionary technologies that are significantly impacting various sectors, including the metaverse. The integration of these technologies is particularly influential in enhancing security and efficiency in metaverse payment transactions. Blockchain, with its decentralized and immutable ledger, provides a secure and transparent way to record transactions. This characteristic is crucial in the metaverse, where digital assets and virtual currencies are frequently exchanged. By leveraging blockchain, metaverse platforms can ensure the integrity and traceability of transactions, reducing the risk of fraud and unauthorized access. On the other hand, AI contributes to the efficiency and intelligence of payment systems. Through machine learning algorithms and data analytics, AI can detect and prevent fraudulent activities, provide personalized recommendations, and automate complex transaction processes. This not only improves the user experience but also enhances the overall security of the system by identifying and mitigating risks in real time. The convergence of blockchain and AI in the metaverse enables the development of more sophisticated and secure payment solutions. These technologies work together to ensure that transactions are not only fast and efficient but also robust against various security threats. This synergy is essential for building trust in the digital economy of the metaverse, encouraging more users and businesses to engage in this emerging virtual space. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blockchain

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Heart and Lung Sound Monitoring System Based Embedded System 7

Heart and Lung Sound Monitoring System Based Embedded System

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7th International Conference on Sustainable Information engineering and Technology, SIET 2022

作者： Endrawan, Nadi Rahmat Prasetio, Barlian Henryranu Maulana, Rizal Department of Informatics Engineering Brawijaya University Indonesia Faculty of Computer Science University of Brawijaya Indonesia

ISBN: (纸本)9781450397117

Every year, Indonesians still suffer from heart and lung diseases. To anticipate many lethal effects caused by these diseases, an early diagnosis solution is needed. This research discusses the implementation of a heart and lung auscultation monitoring system that aims to facilitate doctors in diagnosing patients. The system has three main components: sampler, signal conditioner, and interface. The sampler samples the signal with a period of 250 μs which is also the deadline of task completion in the system. The signal conditioner will filter the signal according to the doctor's wishes with a choice of two modes (heart and lung). Then the interface can display heart rate (HR) or respiration rate (RR) parameters according to the selected mode and other features such as sound output and signal visualization. The test results show that the system completes the task faster than the deadline with an average of each sampler, signal conditioner, and interface: 21.6 μs, 185.13 μs, and 122.62 μs. There is an increase in the signal-To-noise ratio value of both filters after filtering with a value of 35.05 for the heart and 23.64 for the lungs. Finally, the performance of the Smoothed Z score algorithm in predicting HR and RR gives an accuracy of 94% and 82%. © 2022 ACM.

关键词： FIR filters

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Neutrosophic Model for Evaluation Healthcare Security Criteria for Powerful and Lightweight Secure Storage System in Cloud-Based E-Healthcare Services

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Neutrosophic Sets and Systems 2023年 58卷 367-378页

作者： El-Douh, Ahmed A. Lu, SongFeng Abdelhafeez, Ahmed Ali, Ahmed M. Aziz, Alber S. School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Faculty of Information Systems and Computer Science October 6th University Giza12585 Egypt Faculty of Computers and Informatics Zagazig University Sharqiyah Zagazig44519 Egypt

Large data volumes make manually keeping and preserving health records for future reference problematic. Most unusual is the coronavirus epidemic's overcrowding of hospitals. The Secure Pattern Electronic Healthcare Records (SPEHR) scheme provides a powerful and lightweight secure storage system for cloud-based E-healthcare services that meets remote healthcare security criteria. So we proposed a neutrosophic model with a multi-criterion decision-making (MCDM) method for the analysis and evaluation of these criteria. The neutrosophic model is used to deal with vague and uncertain data. Then we integrated the neutrosophic model with the AHP method to rank and compute the weights of the criteria. Offering stakeholders a secure interface and avoiding unwanted access to cloud-stored data mitigates E-healthcare risks. The key derivation ensures end-to-end data. ciphering to prevent unauthorized use (KDF). This work provides robust security solutions for various environments. This work can meet security needs for people and secure-communicating organizations. We found the data privacy is the best criterion. © (2023). All Rights Reserved.

关键词： Access control

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