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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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Optimal Planning Framework for Mitigating Cyber-Induced Cascading Failures in Power Grids

Optimal Planning Framework for Mitigating Cyber-Induced Casc...

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2024 IEEE Power and Energy Society General Meeting, PESGM 2024

作者： Venkatasubramanian, Balaji V. Hashemi, Sina Wells, Linton Laskey, Kathryn Blackmond van de Lindt, John W. Amir, Yair Babay, Amy Chiu, Imes Panteli, Mathaios Department of Electrical and Computer Engineering University of Cyprus Cyprus School of Technology Woxsen University Telangana India Center for Resilient and Sustainable Communities George Mason University FairfaxVA22030 United States Department of Civil and Environmental Engineering Colorado State University Fort CollinsCO80523 United States Department of Computer Science Johns Hopkins University BaltimoreMD21218 United States School of Computer and Information University of Pittsburgh PittsburghPA15213 United States Fort Belvoir22060 United States

The growing digitization of power grids has increased their vulnerability to cyberattacks, potentially leading to widespread power outages. While many studies address cyber-induced outages, resulting cascading failures are often overlooked. This paper introduces a planning framework that employs cyber-physical measures to mitigate these disruptions. It generates a range of cyberattack scenarios, including denial of service (DoS) attack and load alter attacks (LAA) on substations while accounting for uncertainties. These cyberattacks can shift the grid's stable operating point, potentially triggering protection mechanisms and causing cascading failures. The impact of these failures is quantified using a cascading failure model that quantifies the demand not served. The framework integrates cyber-physical measures, including the optimal allocation of cyber reinforcement units (which may include components like phasor measurement units and other cyber-defense mechanisms) and energy storage systems to reduce cascading propagation. The framework's effectiveness in reducing cascading impacts is evaluated using the IEEE 39-bus system. © 2024 IEEE.

关键词： Phasor measurement units

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UHF IoT Humidity and Temperature Sensor for Smart Agriculture Applications Powered from an Energy Harvesting System

UHF IoT Humidity and Temperature Sensor for Smart Agricultur...

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2022 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2022

作者： Nadeem, Adnan Chatzichristodoulou, David Quddious, Abdul Shoaib, Nosherwan Vassiliou, Loukia Vryonides, Photos Nikolaou, Symeon Frederick Research Center Nicosia Cyprus School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad Pakistan Rf and Microwave Solutions Ltd Cyprus Kios Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus Agricultural Research Institute Nicosia Cyprus Electrical Engineering Department Frederick University Nicosia Cyprus

ISBN: (数字)9798350396454

ISBN: (纸本)9798350396454

This manuscript presents a novel UHF IoT humidity and temperature sensor module that is powered from an integrated energy harvesting (EH) system. The module is intended for smart agriculture applications. The sensing module is powered from the collected RF energy that is harvested by a meander monopole antenna operating at 915 MHz (US UHF band) and therefore the use of a battery is not required. The rectifying voltage doubler converts the received RF energy into DC while the Power Management Unit (PMU) boosts-up and stores the rectified voltage providing a regulated output voltage of 1.8V to the RFID tag IC (ROCKY100) and 3.3V to the microcontroller unit (MCU) and the humidity and temperature sensor IC. The communication RFID antenna uses the European UHF frequency band centered at 868 MHz. When the RFID tag IC is supplied with 1.8 V from the PMU it operates in semi-passive mode and it effectively increases its communication range. The ROCKY100 is EPC C1G2 compliant and is compatible with power harvesting modules and SPI communication to support external low-power sensors and actuators. In addition, a capacitive digital humidity and temperature sensor (HTS221) is used as the sensing module for soil measurements. The process of measuring the relative humidity and temperature of the soil is controlled with a Texas Instrument mixed signal microcontroller that possesses two SPI interfaces that allows it to communicate with the RFID IC and the sensor in parallel. Upon receiving a SPI directed read request from the RFID reader, the ROCKY100 SPI bridge requests the value of the last measurement from the microcontroller and the humidity and temperature measurements taken by the HTS221 IC are sent to the RFID reader. The use of harvested wireless energy as a power source makes the demonstrated module a potentially batteryless and thus a 'Green' sensor. © 2022 IEEE.

关键词： Radio frequency identification (RFID)

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A Systematic Overview on Simulation of Connected Vehicles Infrastructure in Smart Cities 1

A Systematic Overview on Simulation of Connected Vehicles In...

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1st International Conference in Advanced Innovation on Smart City, ICAISC 2023

作者： Gupta, Manik Dhaou, Imed Ben Garg, Kamal Deep Sharma, Bhisham Chitkara University School of Engineering and Technology Chitkara University Himachal Pradesh India Dar Al-Hekma University Hekma School of Engineering Computing and Informatics Department of Computer Science Jeddah Saudi Arabia Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9781665472753

The development and use of connected vehicles are becoming increasingly important areas of study in the wireless networking and transportation research communities. These networks can provide various services such as collision warning. Unlike other types of devices, such as hand-held devices, the vehicles' nodes are not limited by their energy consumption and storage capacity. Therefore, the development of connected networks can be carried out with minimal resources. It is necessary to run a simulation in order to determine whether they are feasible. The availability of multiple devices and protocols has led to the creation of new utilization scenarios. Due to the complexity of the task, many simulation tools were developed during the past few years. This paper systematically reviews the current state of these tools and discusses their capabilities to evaluate the various scenarios related to the development of connected vehicles network. © 2023 IEEE.

关键词： Energy utilization

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Implicit and Explicit Formulas of the Joint RDF for a Tuple of Multivariate Gaussian Sources with Individual Square-Error Distortions

Implicit and Explicit Formulas of the Joint RDF for a Tuple ...

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IEEE International Symposium on Information Theory

作者： Evagoras Stylianou Charalambos D. Charalambous Themistoklis Charalambous Chair of Theoretical Information Technology Technical University of Munich Munich Germany Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

This paper analyzes the joint Rate Distortion Function (RDF) of correlated multivariate Gaussian sources with individual square-error distortions. Leveraging Hotelling's canonical variable form, presented is a closed-form characterization of the joint RDF, that involves a system of nonlinear equations. Furthermore, for the special case of symmetric distortions (i.e., equal distortions), the joint RDF is explicitly expressed in terms of two water-filling variables. The results greatly improve our understanding and advance the development of closed-form solutions of the joint RDF for multivariate Gaussian sources with individual square-error distortions.

关键词： Nonlinear equations Closed-form solutions Nonlinear distortion Rate-distortion Resource description framework Vectors Optimization

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Automated segmentation and classification of the atherosclerotic carotid plaque in ultrasound videos

Automated segmentation and classification of the atheroscler...

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International Conference on Digital Signal Processing (DSP)

作者： Georgia D. Liapi Michalis Gemenaris Christos P. Loizou Efthyvoulos Kyriacou Kyriacos P. Constatninou Andrew Nicolaides Dept. of Electrical Eng. Computer Eng. and Informatics Cyprus University of Technology Limassol Cyprus Dept. of Computer Science University of Cyprus Nicosia Cyprus Vascular Screening and Diagnostic Centre Nicosia Cyprus

The automated and reliable delineation of atherosclerotic carotid plaques in ultrasound (CUS) videos is of significant clinical relevance for management of the disease and the prediction of future stroke events. To facilitate stroke risk assessment, in this study, we propose an integrated software system for the automated segmentation and classification of atherosclerotic carotid plaques in longitudinal CUS videos, which was evaluated using 10 CUS videos, from 10 patients (5 Asymptomatic, AS, and 5 Symptomatic, SY). The proposed methodology involves the following steps: a) CUS video frame (VF) resolution and intensity normalization, b) speckle reduction filtering, c) Motion-mode state-based cardiac cycle (CC) identification, d) deep learning (DL)-based plaque segmentation, e) extraction and selection of plaque region of interest (ROI)-specific textural features, and f) machine learning (ML)-based plaque classification. Initially, one CC (cardiac diastole-systole-diastole) was selected per CUS video, and the CC’s consecutive VFs were identified and reduced in number to exclude redundant VFs. All standardized VFs per patient were extracted, cropped and resized to mainly accommodate the ROI and were fed into a priorly trained and evaluated 2-dimensional DL plaque segmentation model. For each VF, the DL-based segmented plaque ROI was projected onto its primary resolution-normalized VF counterpart, from which textural and amplitude modulation-frequency modulation (AM-FM) plaque ROI features were extracted. Statistical analysis on the total AS and SY VFs was used for feature selection. We identified 2 plaque-originating AM-FM features, which exhibited statistically significant differences between the AS and SY standardized VFs (p<0.05), followed by 3 textural features (p<0.05). To finalize our system, in a future study, the strong AM-FM AS/SY descriptors, identified here, will be evaluated alone or in combinations with other plaque-descriptive features, in machine learnin

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AMC Integrated Multilayer Wearable Antenna for Multiband WBAN Applications

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computers, Materials & Continua 2022年第5期71卷 3227-3241页

作者： Iqra Aitbar Nosherwan Shoaib Akram Alomainy Abdul Quddious Symeon Nikolaou Muhammad Ali Imran Qammer H.Abbasi Research Institute for Microwave and Millimeter-Wave Studies(RIMMS)National University of Sciences and Technology(NUST) H-1244000IslamabadPakistan School of Electronic Engineering and Computer Science Queen Mary University of LondonLondonE14NSUK KIOS Research and Innovation Center of Excellence University of Cyprus2109NicosiaCyprus Frederick Research Center(FRC)and Department of Electrical Engineering Frederick University1036NicosiaCyprus James Watt School of Engineering University of GlasgowGlasgowG128QQU.K

In this paper,a compact,efficient and easy to fabricate wearable antenna integrated with Artificial Magnetic Conductor(AMC)is *** of slots and bevels/cuts in the rectangular monopole patch antenna yield a wide bandwidth along with band *** proposed antenna is backed with an AMC metasurface that changes the bidirectional radiation pattern to a unidirectional,thus,considerably reducing the Specific Absorption Ratio(SAR).The demonstrated antenna has a good coverage radiating away from the body and presents reduced radiation towards the body with a front-to-back ratio of 13 dB and maximum gain of 3.54 *** proposed design operates over a wide frequency band of 2.9 to 12 GHz(exceeding the designated 3.1−10.6 GHz Ultra-Wideband(UWB)band).The band notches were created using slots on the radiating patch in the sub-bands from 5.50 to 5.67 GHz and 7.16 to 7.74 *** overall dimensions of the structure are 33×33×6.75 *** antenna’s radiation performance increased considerably with the addition of the AMC *** SAR values for the antenna are reduced by 85.3%when the AMC is used and are 0.083 W/kg which is well below the FCC SAR *** simple design,miniaturized profile,low SAR and wide operating bands with multiple band notches make the presented antenna an appealing choice for several UWB wearable body area network(WBAN)applications.

关键词： Ultra-wideband(UWB) monopole antenna wearable antenna specific absorption ratio(SAR)

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Mathematical Modeling of an Anion Exchange Membrane Electrolyzer for Integration in a Novel Solar Photovoltaic-Battery-Green Hydrogen Nanogrid

Mathematical Modeling of an Anion Exchange Membrane Electrol...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Alexandros Arsalis Panos Papanastasiou George E. Georghiou Department of Electrical and Computer Engineering PV Technology Laboratory University of Cyprus Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus Department of Civil and Environmental Engineering University of Cyprus Nicosia Cyprus

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

The Mediterranean area is an ideal location for harnessing solar energy due to the high solar irradiation availability. Utilization of innovative solutions address renewable energy instabilities and optimize the utilization of local clean energy resources. A promising technology is the utilization of green hydrogen subsystem to these solar systems. Such an integration could add significant capabilities, namely, provision of seasonal energy storage, increase of solar photovoltaic capacity, and export of the generated green hydrogen for other uses, such as fueling of hydrogen electric vehicles. A detailed model is developed in this work to assess the performance of the proposed green hydrogen subsystem configuration with a view to utilizing it as part of a future, larger, wholistic energy system. At full-load the model performs at an efficiency of 62.4%, while performance at a 10% part-load is 82.3%. These performance results suggest a very promising potential for this technology which can be harnessed in the future multi-scale energy systems, provided that the economic performance is also promising.

关键词： Photovoltaic systems Green energy Radiation effects Electric potential Solar energy Green hydrogen Electric vehicles Mathematical models Solar system Energy storage

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DeepFuzzLoc Positioning: A Unified Fusion of Fuzzy Clustering and Deep Learning for Scalable Indoor Localization Using Wi-Fi RSSI 13

DeepFuzzLoc Positioning: A Unified Fusion of Fuzzy Clusterin...

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Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024

作者： Mahali, Muhammad Izzuddin Leu, Jenq-Shiou Achmad Sulistyo Putro, Nur Widyawan Prakosa, Setya Avian, Cries National Taiwan University of Science and Technology Dept. of Electronic and Computer Engineering Taipei Taiwan Universitas Negeri Yogyakarta Dept. of Electronics and Informatics Engineering Education Yogyakarta Indonesia Universitas Gadjah Mada Dept. of Computer Science and Electronics Yogyakarta Indonesia

ISBN: (纸本)9798350373332

This research introduces a novel method for indoor positioning by integrating Fuzzy C-Means clustering with deep learning autoencoders, leveraging Wi-Fi RSSI fingerprinting for precise location prediction and building and floor level classification within a unified framework. The approach combines the comprehensibility of Fuzzy C-Means (FCM) with the robust feature extraction capabilities of deep autoencoders through a dual-phase strategy: extensive offline training utilizing RSSI fingerprint data followed by real-time online position prediction. The model's performance was rigorously tested using 5-Fold cross-validation, examining its effectiveness both with and without the integration of FCM on various cluster numbers. Evaluation metrics, including Euclidean distance error for regression and accuracy, F1-score, precision, and specificity for classification effectiveness, were used for comparative analysis. The results were visualized through regression plots, confusion matrices, and learning curves, supplemented by t-SNE visualizations that provide profound insights into the feature space. These detailed analyses highlight the considerable promise of this integrated approach in enhancing the accuracy and reliability of indoor positioning systems. © 2024 IEEE.

关键词： Fuzzy clustering

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An Attention-Based Deep Network for Plant Disease Classification

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Machine Graphics and Vision 2024年第1期33卷 47-67页

作者： Bera, Asish Bhattacharjee, Debotosh Krejcar, Ondrej Department of Computer Science and Information Systems Birla Institute of Technology and Science Rajasthan Pilani India Department of Computer Science and Engineering Jadavpur University West Bengal Kolkata India Center for Basic and Applied Science Faculty of Informatics and Management University of Hradec Králové Czech Republic Škoda Auto University Mladá Boleslav Czech Republic Universiti Teknologi Malaysia Kuala Lumpur Malaysia

Plant disease classification using machine learning in a real agricultural field environment is a difficult task. Often, an automated plant disease diagnosis method might fail to capture and interpret discriminatory information due to small variations among leaf sub-categories. Yet, modern Convolutional Neural Networks (CNNs) have achieved decent success in discriminating various plant diseases using leave images. A few existing methods have applied additional pre-processing modules or sub-networks to tackle this challenge. Sometimes, the feature maps ignore partial information for holistic description by part-mining. A deep CNN that emphasizes integration of partial descriptiveness of leaf regions is proposed in this work. The efficacious attention mechanism is integrated with high-level feature map of a base CNN for enhancing feature representation. The proposed method focuses on important diseased areas in leaves, and employs an attention weighting scheme for utilizing useful neighborhood information. The proposed Attention-based network for Plant Disease Classification (APDC) method has achieved state-of-the-art performances on four public plant datasets containing visual/thermal images. The best top-1 accuracies attained by the proposed APDC are: PlantPathology 97.74%, PaddyCrop 99.62%, PaddyDoctor 99.65%, and PlantVillage 99.97%. These results justify the suitability of proposed method. © 2024 Institute of Information technology, Warsaw university of Life Sciences - SGGW. All rights reserved.

关键词： Convolutional neural networks

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