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Embedded Coded Relay System for Molecular Communications

computers, Materials & Continua 2022年第8期72卷 2729-2748页

作者： Eman S.Attia Ashraf A.M.Khalaf Fathi E.Abd El-Samie Saied M.Abd El-atty Konstantinos A.Lizos Osama Alfarraj Farid Shawki Imran Khan Ki-Il Kim Department of Electrical Engineering Faculty of EngineeringMinia UniversityMiniaEgypt Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt Department of Informatics Faculty of Mathematics and Natural SciencesUniversity of Oslo(UiO)Norway Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Electrical Engineering University of Engineering&TechnologyPeshawar814Pakistan Department of Computer Science and Engineering Chungnam National UniversityDaejeon34134Korea

With the emergence of the COVID-19 pandemic,the World Health Organization(WHO)has urged scientists and industrialists to exploremodern information and communication technology(ICT)as a means to reduce or even eliminate *** World Health Organization recently reported that the virus may infect the organism through any organ in the living body,such as the respiratory,the immunity,the nervous,the digestive,or the cardiovascular *** the abovementioned goal,we envision an implanted nanosystem embedded in the intra living-body *** main function of the nanosystem is either to perform diagnosis and mitigation of infectious diseases or to implement a targeted drug delivery system(i.e.,delivery of the therapeutic drug to the diseased tissue or targeted cell).The communication among the nanomachines is accomplished via communication-based molecular *** control/interconnection of the nanosystem is accomplished through the utilization of Internet of bio-nano things(IoBNT).The proposed nanosystem is designed to employ a coded relay nanomachine disciplined by the decode and forward(DF)principle to ensure reliable drug delivery to the targeted ***,both the sensitivity of the drug dose and the phenomenon of drug molecules loss before delivery to the target cell site in long-distance due to the molecules diffusion process are taken into *** this paper,a coded relay NM with conventional coding techniques such as RS and Turbo codes is selected to achieve minimum bit error rate(BER)performance and high signal-to-noise ratio(SNR),while the detection process is based on maximum likelihood(ML)probability and minimum error probability(MEP).The performance analysis of the proposed scheme is evaluated in terms of channel capacity and bit error rate by varying system parameters such as relay position,number of released molecules,relay and receiver *** results are validated through simulation and demonstrate that the proposed scheme can

关键词： Molecular communication nanonetwork internet of bio-nano things coded relay scheme coding

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Application of Blockchain Technologies to Improve the Quality of Microgrid Network Management 5

Application of Blockchain Technologies to Improve the Qualit...

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5th International Conference on Blockchain Computing and Applications, BCCA 2023

作者： Khilenko, Volodymyr Bielokha, Halina Denysiuk, Sergii Kotuliak, Ivan Ries, Michal Institute of Computer Engineering and Applied Informatics Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Bratislava Slovakia National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine

ISBN: (纸本)9798350339239

The use of blockchain technologies and Smart contracts to improve the quality of Microgrid network management is considered. The necessity of using a special mathematical apparatus for system analysis is noted, taking into account the nonlinear nature of dynamic processes in the network and, in particular, the presence of sharply changes in the load. The advantages and disadvantages of the approach known in the literature are analyzed, when the search for the optimal power distribution among generators to ensure the minimum costs of the Microgrid is carried out on the basis of nonlinear programming methods. Graphs of transient processes in the network are given and their corresponding analysis is carried out. © 2023 IEEE.

关键词： Smart contract

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Stress Detection Using EEG Signals: A SVM-Based Classification and Feature Selection Approach

Stress Detection Using EEG Signals: A SVM-Based Classificati...

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Electrical Power, Electronics, Communications, Controls and informatics Seminar (EECCIS)

作者： Fi Imanur Sifaunnufus Fitra Abdurrachman Bachtiar Barlian Henryranu Prasetio Department of Computer Engineering Faculty of Computer Science Brawijaya University Malang Indonesia Department of Informatics Engineering Faculty of Computer Science Brawijaya University Malang Indonesia

ISBN: (数字)9798350379914

ISBN: (纸本)9798350379921

Stress is a problem with various adverse effects, such as mental disorders and suicide. With these problems arising, a stress detection system is needed as an initial examination of the level of stress experienced. Generally, stress detection is done with a stress test at a hospital. However, medical examinations done in the hospital require high costs. Another alternative to examine stress levels is by using a biosignal electroencephalogram (EEG), which provides more objective and accurate results. In addition, there is a need to develop a portable device that can be used to detect stress. This study tries to detect stress levels using EEG Signals. The data used in this study is primary data that simulates several stress-level activities. In total, 55 subjects participated in this stress detection research. The received signal goes through preprocessing to clean it from noise and artifacts. The data will be extracted using Power Spectral Density (PSD) into power value for each signal frequency. The preprocessed input signals are then classified into indications of stress levels. This study uses Random Forest, SVM, and Decision Tree. The model is stored on a portable system with Raspberry Pi as the main component. EEG signals are taken using electrodes on Muse 2 and sent to the system. The classification model generates predicted stress levels and is displayed on a 16×2 LCD. SVM as the best model test result achieved a testing accuracy of 1, and an average computation time of 0.92.

关键词： Support vector machines Seminars Accuracy Hospitals Computational modeling Human factors Brain modeling Electroencephalography Random forests Testing

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Detection System for Lung Tumours Based on CT Scan Images Using Cellular Automata

Detection System for Lung Tumours Based on CT Scan Images Us...

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2024 International Conference on Electrical and Information Technology, IEIT 2024

作者： Latif Hayati, Fierly Harsono, Tri Yuniarti, Heny Ferriastuti, Widiana Politeknik Elektronika Negeri Surabaya Department of Informatics and Computer Engineering Surabaya Indonesia Universitas Airlangga Faculty of Medicine Dr. Soetomo General Academic Hospital Department of Radiology Surabaya Indonesia

ISBN: (纸本)9798331516888

Lung tumours are masses of tissue that arise abnormally in the lung organ. In the field of medicine, One means of detecting and analyzing lung tumours is to use Computed Tomography (CT) scan images, where doctors see with the naked eye on the image and make a diagnosis. The existence of a lung tumour area detection system using a computer program is needed as a companion system in diagnosing. This research develops a lung tumour detection system using Cellular Automata (CA) with the system input is CT scan image. The quality of CT Scan image is improved through pre-processing, then segmentation is performed to separate the lung object from the background. Binaryization is applied to the segmented image to clarify the presence of lung tumour area. The detection process by CA is conducted on the binaryized image. The experiment was implemented on 20 CT scan images for normal lung and 20 other images for abnormal lung obtained from The Lung Image Database Concortium (LIDC) and Image Database Resource Initiative (IDRI). Analyzing the experimental data using performance score, it was found that the accuracy of detection was 95%, 100% precision, 90% sensitivity, and 100% specificity. These conditions indicate that the detection system has good reliability. © 2024 IEEE.

关键词： Lung cancer

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Developing Engagement in the Learning Management System Supported by Learning Analytics

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computer Systems Science & engineering 2022年第7期42卷 335-350页

作者： Suraya Hamid Shahrul Nizam Ismail Muzaffar Hamzah Asad W.Malik Department of Information System Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala LumpurMalaysia Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Department of Computing School of Electrical Engineering and Computer Science(SEECS)National University of Sciences and Technology(NUST)IslamabadPakistan

Learning analytics is an emerging technique of analysing student par-ticipation and *** recent COVID-19 pandemic has signiﬁcantly increased the role of learning management systems(LMSs).LMSs previously only complemented face-to-face teaching,something which has not been possible between 2019 to *** date,the existing body of literature on LMSs has not analysed learning in the context of the pandemic,where an LMS serves as the only interface between students and ***,productive results will remain elusive if the key factors that contribute towards engaging students in learning are notﬁrst identiﬁ***,this study aimed to perform an exten-sive literature review with which to design and develop a student engagement model for holistic involvement in an *** required data was collected from an LMS that is currently utilised by a local Malaysian *** model was validated by a panel of experts as well as discussions with *** is our hope that the result of this study will help other institutions of higher learning determine factors of low engagement in their respective LMSs.

关键词： Engagement analysis learning analytics learning management system student engagement

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Application of Parallel Signal Processing Using Reverse Blockchain Technology in Conditions of Network Instability 4

Application of Parallel Signal Processing Using Reverse Bloc...

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4th International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2024

作者： Khilenko, Volodymyr Zinchenko, Andrii Stepanov, Oleksii Kotuliak, Ivan Ries, Michal Institute of Computer Engineering and Applied Informatics Slovak University of Technology in Bratislava Faculty of Informatics and Information Technologies Bratislava Slovakia Institute of Transport Systems and Technologies National Academy of Sciences of Ukraine Dnipro Ukraine National University of Life and Environmental Sciences of Ukraine Kyiv Department of Information Technologies Ukraine Slovak University of Technology in Bratislava Faculty of Informatics and Information Technologies Bratislava Slovakia

ISBN: (纸本)9798350391183

The theses is in line with works aimed at studying the possibility of using mathematical algorithms for parallel processing of information in reverse blockchain technology. The paper examines the use of parallel signal processing algorithms to improve the speed and quality of control systems for autonomous dynamic objects using reverse blockchain technology. The use of reverse blockchain technology is due to the possibility of loss of control signals and, at the same time, the inadmissibility of loss of control in the event of changes in the conditions and parameters of the operation of the obj ect. The purpose of the work is to analyze the implementation of solutions for parallel information processing for various models of industrially produced equipment and to develop solutions to increase the efficiency of reverse blockchain technology when using parallel data processing. © 2024 IEEE.

关键词： blockchain dynamic objects and technological processes improving the quality of control systems instability of communication channels loss of information and control signals reverse blockchain technology

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Brain Tumour Segmentation in MRI Data Using Gray Level Co-Occurrence Matrix

Brain Tumour Segmentation in MRI Data Using Gray Level Co-Oc...

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2024 International Conference on Electrical and Information Technology, IEIT 2024

作者： Al Ghifari, Muhammad Zidni Ferriastuti, Widiana Harsono, Tri Sigit, Riyanto Hayati, Fierly Politeknik Elektronika Negeri Surabaya Department of Informatics and Computer Engineering Surabaya Indonesia Dr. Soetomo General Academic Hospital Airlangga University Faculty of Medicine Department of Radiology Surabaya Indonesia

ISBN: (纸本)9798331516888

In the medical field, the image segmentation process is very important as the first step to diagnose a disease. Currently, brain tumors are one of the most life-threatening diseases. To detect brain tumors more accurately in less time, many techniques have been proposed using image segmentation. This research will present a brain tumour segmentation method on brain MRI data using GLCM (Grey Level Co-Occurrence Matrix). The input data in this system is the planned MRI data obtained from a hospital and Open Source MRI data in the form of grey level which is calculated using GLCM. Calculation using GLCM which is to find the maximum probability among the grey values of surrounding cells. The result of the GLCM calculation produces texture values (Texture Features). The combination of the intensity value in the MRI data and its texture value as an input parameter in the segmentation process. The method used to segment the tumour is thresholding by identifying contours on the MRI image. Both intensity-based and texture-based images are subjected to the same segmentation method. The segmentation result in this study is the categorization of cell areas affected by tumours and normal cells. To see the performance of the system built in this study using DSC (Dice Similarity Coefficient) and JC (Jaccard Coefficient) presented in the form of a percentage. Tests were conducted with 25 MRI data with two types of tumours namely glioblastoma and meningioma. Evaluation using Dice Similarity and Jaccard methods showed a small difference in accuracy between texture and intensity images. The texture image has an average Dice Similarity of 82.81% and Jaccard of 88.40%. While the intensity image has an average Dice Similarity of 80.35% and Jaccard 87.22%. In conclusion, the GLCMCA method provides slightly higher and more precise segmentation accuracy. © 2024 IEEE.

关键词： Magnetic resonance imaging

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The Use of Smart Devices for Assessing the User’s Physiological Status 1

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8th Future Technologies Conference, FTC 2023

作者： Fodor, Kristián Balogh, Zoltán Molnár, György Department of Computer Science Faculty of Natural Sciences and Informatics Constantine the Philosopher University in Nitra Nitra Slovakia Kandó Kálmán Faculty of Electrical Engineering Óbuda University Budapest Hungary

ISBN: (数字)9783031474576

ISBN: (纸本)9783031474569

Currently, there are various technical solutions as well as methods by which the user’s physiological functions can be obtained. From the point of view of the technical solutions, approaches based on the application of sensors (galvanic skin response, heart rate, temperature, etc.) or the use of a camera for capturing the face and its parts are most often used. The article is devoted to the creation of a system for identifying and classifying the emotional state of the user while maintaining non-invasiveness, which includes an IoT-based (Internet of Things) user interface. It deals with the capture of data about the user and the subsequent evaluation of this data with the help of a web application for visualizing and evaluating the obtained data. The research uses a pulse sensor and a galvanic skin response sensor, which are connected to an Arduino and a computer, for data evaluation. The results of the paper include the design of a portable and affordable device that can be non-invasively attached to the human body and monitor the measured values for a long time. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Internet of things

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Designing Quantum-Resilient Blockchain Frameworks: Enhancing Transactional Security with Quantum Algorithms in Decentralized Ledgers

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International Journal of Advanced computer Science and Applications 2025年第4期16卷 618-628页

作者： Kale, Meenal R. Baker El-Ebiary, Yousef A. Sathiya, L. Burugari, Vijay Kumar Yulduz, Erkiniy Muniyandy, Elangovan Alanazi, Rakan Department of Humanities Yeshwantrao Chavan College of Engineering Hingna Nagpur India Faculty of Informatics and Computing UniSZA University Malaysia Department of CSE Panimalar Engineering College Chennai India Dept of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India Automatic Control and Computer Engineering Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan Department of Biosciences-Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Applied Science Research Center Applied Science Private University Amman Jordan Department of Information Technology Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia

Quantum computing is progressing at a fast rate and there is a real threat that classical cryptographic methods can be compromised and therefore impact the security of blockchain networks. All of the ways used to secure blockchain like Rivest–Shamir–Adleman (RSA), Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm 256-bit (SHA256) are the characteristic of the traditional cryptographic techniques vulnerable to attack by quantum algorithms: Shor’s and Grover’s algorithms: can efficiently break asymmetric encryption and speed up brute force attacks. Because of this vulnerability, there exists a need to develop an advance quantum resilient blockchain framework to protect the decentralized ledgers from the future threats of the quantum. This research proposes Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD) and Quantum Random Number Generation (QRNG) as a formidable architectural integration, to fortify security of blockchain. Classical encryption is replaced with PQC, QKD with secure key exchange by detecting eavesdropping, and QRNG with improving cryptographic randomness to remove the predictable key vulnerability. Only with a small loss of transaction efficiency, we increase transaction encryption accuracy, key exchange security, and resistance to quantum attacks. In this quantum enhanced blockchain design, the idea is to preserve the decentralization, transparency and security and at the same time overcome the future quantum threat. By going through rigorous analysis and comparative evaluation, we demonstrate that the approach saves blockchain networks from the emerging quantum risks to make sure that the decentralized finance, smart contracts and cross chain transactions. © (2025), (Science and Information Organization). All rights reserved.

关键词： Quantum cryptography

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A Two-Tier Anomaly-based Intrusion Detection Approach for IoT-Enabled Smart Cities

A Two-Tier Anomaly-based Intrusion Detection Approach for Io...

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2023 IEEE INFOCOM Conference on computer Communications Workshops, INFOCOM WKSHPS 2023

作者： Hamdan, Mosab Eldhai, Arwa M. Abdelsalam, Samah Ullah, Kifayat Bashir, Ali Kashif Marsono, M.N. Kon, Fabio Batista, Daniel Macêdo Department of Computer Science Brazil University of Science and Technology Faculty of Engineering Sudan Khartoum University Faculty of Mathematical Sciences and Informatics Sudan Manchester Metropolitan University Department of Computing and Mathematics United Kingdom Universiti Teknologi Malaysia Faculty of Electrical Engineering Malaysia

ISBN: (纸本)9781665494274

The Internet of Things (IoT), like other network infrastructures, requires Intrusion Detection Systems (IDSs) to be protected against attacks. When deploying an IDS in IoT-based smart city environments, the balance between latency and node capacity must be considered, which justifies a distributed IDS with specific classifiers based on the location of the system processing nodes. This paper proposes a two-level classification technique for collaborative anomaly-based IDSs deployed on fog and edge nodes. A Gradient Boosting Classifier (GBC) is used in the lower layer classifier at the edge, while a Convolutional Neural Network (CNN) is used in the upper layer classifier at the fog. Experimentation has demonstrated that the suggested IDS architecture outperforms previous solutions. For instance, in some scenarios, when comparing our proposal with Random Forest, the former obtained an accuracy equal to 99.1%, while the latter obtained 95.3%. Furthermore, our proposal can better select the most important network traffic features, reducing 76% of the data to be analyzed and improving privacy. © 2023 IEEE.

关键词： Internet of things

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