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Cyber Resilience (ICCR), International Conference on

作者： Haider Rasheed Abdulshaheed Yaseen Saadi Abbas Jamal F. Tawfeq Karamath Ateeq Saif. E. A. Alnawayseh Taher M. Ghazal Computer Engineering Techniques Department Baghdad College of Economic Sciences University Baghdad Iraq Electronic and Communications Engineering Department College of Engineering Al-Nahrain University Baghdad Iraq Department of Medical Instrumentation Technical Engineering Medical Technical College Al-Farahidi University Baghdad Iraq School of Computing Skyline University College University City Sharjah Sharjah UAE Department of Electrical Engineering College of Engineering Mutah University Al-Karak Jordan Computer Science Department Centre for Cyber Physical Systems Khalifa University Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia (UKM) Bangi Selangor Malaysia

ISBN: (数字)9798350394962

ISBN: (纸本)9798350394979

Providing quality healthcare services and promoting collaborative clinical research are easier and more efficient with electronic medical record (EMR) systems. All aspects of care are included in electronic health records. Data characterized by volume, variety, and velocity is what IBM defines as big data. Therefore, we evidently have a significant problem managing “big EMR data” from a volume, accuracy, and velocity perspective. Data misuse and patient safety are significant risks associated with poorly implemented EMR-based systems. Storage, access, and retrieval of big data are all aspects of security to consider. Location is another important aspect of secure data use, in addition to strong access control mechanisms. Researchers are investigating secure mobile data usage based on location after recent reports of illegal trade and theft of patient data over mobile devices. To improve work flow dynamics and efficiency, healthcare facilities are increasingly using mobile devices. In spite of this, mobile devices are becoming more and more common. A new technique for preventing EMR infiltration and manipulation by hackers using the cloud is presented in this article.

关键词： Cloud computing Hospitals Watermarking Big Data Mobile handsets Robustness Safety

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Deciphering the role of nitric oxide in mitigation of systemic fungicide induced growth inhibition and oxidative damage in wheat

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Chemosphere 2024年 364卷 143046页

作者： Touzout, Nabil Mihoub, Adil Ahmad, Iftikhar Jamal, Aftab Danish, Subhan Department of Nature and Life Sciences Faculty of Sciences Pole Urban Ouzera University of Medea Medea26000 Algeria Biophysical Environment Station Center for Scientific and Technical Research on Arid Regions Touggourt Algeria Department of Environmental Sciences COMSATS University Islamabad Vehari Campus Vehari61100 Pakistan Department of Soil and Environmental Sciences Faculty of Crop Production Sciences The University of Agriculture Peshawar25130 Pakistan Department of Soil Science Faculty of Agricultural Sciences and Technology Bahauddin Zakariya University Punjab Multan60000 Pakistan Pesticide Quality Control Laboratory Agriculture Complex Old Shujabad Road Punjab Multan60000 Pakistan

Consento (CON) poses a significant environmental hazard as a systemic fungicide, adversely affecting the health of non-target organisms. Nitric oxide (NO), a signaling molecule, is known to play a crucial role in plant physiology and abiotic stress tolerance. However, whether NO plays any role to enhance fungicide CON tolerance in wheat seedlings is yet unclear. Therefore, we conducted a hydroponic experiment i) to investigate the morpho-physio-biochemical changes of wheat seedlings to fungicide CON stress, and ii) to examine the effects of NO and fungicide CON treatments on oxidative damage, antioxidant system, secondary metabolism and detoxification of systemic fungicide in wheat seedlings. The results showed that CON fungicide at the highest (4X) concentration significantly decreased wheat seedlings fresh weight (46.89%), shoot length (40.26%), root length (56.11%) and total chlorophyll contents (67.44%) in a dose response relationship. Moreover, CON significantly increased hydrogen peroxide, malondialdehyde, catalase, ascorbate peroxidase, glutathione-S-transferase, and peroxidase activities while decreased reduced glutathione (GSH) content. This ultimately impaired the redox homeostasis of cells, leading to oxidative damage in cell membrane. Under fungicide treatment, the addition of NO reduced the fungicide phytotoxicity, with an increase of over 60% in seedling growth. The NO application mitigated CON phytotoxicity as reflected by significantly increased chlorophyll pigments (69.88%) and decreased oxidative damage in wheat leaves. Indeed, the NO alleviatory effect was able to increase the tolerance of seedlings to fungicide, which resulted increments in antioxidant and detoxification enzymes activity, with the enhanced GSH level (78.54%). Interestingly, NO alleviated CON phytotoxicity through the phenylpropanoid pathway by enhancing the activity of secondary metabolism enzymes such as phenylalanine ammonia-lyase (47.28%), polyphenol oxidase (9%), and associat

关键词： Antioxidants

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A Topology for Five-Level Active Neutral Point-Clamped Inverter

SSRN

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SSRN 2023年

作者： Obe, Emeka Simon Mtengi, Bokani Amuhaya, Lilian Livutse Obe, Pauline Ijeoma Ugwuishiwu, Helen Chikodili Odeh, Charles Ikechukwu Department of Electrical Engineering University of Nigeria Nsukka Nigeria Department of Electrical Computer and Telecommunications Engineering Botswana International University of Science and Technology Palapye Botswana Department of Industrial Technical Education University of Nigeria Nsukka Nigeria Department of Computer Science University of Nigeria Nsukka Nigeria Department of Electric Drives and Energy Conversions Faculty of Electrical and Control Engineering Gdańsk University of Technology Gdańsk Poland

A combination of two shared input splitting capacitor banks and varying number of individualized inverter-leg flying-capacitors characterized topological feature of a large group of 5L ANPC inverters configurations. The inconveniences in the provision of these per phase flying-capacitors make these configurations less attractive in most applications. The 5L E-type inverter, characterized by four shared input capacitor banks, becomes a viable alternative topology. However, the high blocking-voltage rating of the constituent switches still places restrictions on the use of the 5L E-type inverter within this voltage range. In view of this, this paper presents a reconfiguration of the 5L E-type inverter. To lessen the voltage stress on the switching devices used here, the common node of the E-type inverter’s bidirectional switch is investigated. Inverter costs and losses are influenced by the decreased voltage stress. The carrier-overlapped pulse-width modulation, or COPWM, perspective serves as the foundation for the inverter control technique. Simulated results of the inverter performances are presented together with an analysis of the cost competitiveness of the proposed inverter power circuit. A 17.68% reduction in loss dissipation and a 13.61% cost savings were recorded by using the proposed power circuit. © 2023, The Authors. All rights reserved.

关键词： Pulse width modulation

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Machine Learning-Based Cascade Filtering System for fNIRS Data Analysis

Machine Learning-Based Cascade Filtering System for fNIRS Da...

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Progress in Applied Electrical Engineering (PAEE)

作者： Mariusz Pelc Dariusz Mikołajewski Tuukka Ruotsalo Luis A. Leiva Adam Sudoł Edward Jacek Gorzelańczyk Adam Łysiak Aleksandra Kawala-Sterniuk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland University of Helsinki Finland University of Copenhagen Denmark Department of Computer Science University of Luxembourg Luxembourg Luxembourg Faculty of Natural and Technical Sciences University of Opole Opole Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland

This paper presents a preliminary study on the use of machine learning-based methods to select the appropriate parameters of cascade filters in the analysis of brain signals recorded using functional infrared spectroscopy (fNIRS), which shows the level of oxygenation in the brain and, unlike EEG signals (showing electrical brain activity), are less prone to potential interference, disturbances or artifacts occurrence.

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Information Fusion in Smart Agriculture: Machine Learning Applications and Future Research Directions

arXiv

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arXiv 2024年

作者： Katharria, Aashu Rajwar, Kanchan Pant, Millie Velásquez, Juan D. Snášel, Václav Deep, Kusum Mehta Family School of Data Science and Artificial Intelligence Indian Institute of Technology Roorkee Roorkee India Statistical Quality Control and Operations Research Unit Indian Statistical Institute Hyderabad India Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Roorkee Roorkee India Department of Industrial Engineering University of Chile Santiago Chile Instituto Sistemas Complejos de Ingeniería Santiago Chile Department of Computer Science VSB-Technical University of Ostrava Ostrava Czech Republic Department of Mathematics Indian Institute of Technology Roorkee Roorkee India

Machine learning (ML) is a rapidly evolving technology with expanding applications across various fields. This paper presents a comprehensive survey of recent ML applications in agriculture for sustainability and efficiency. Existing reviews mainly focus on narrow subdomains or lack a fusion-driven perspectives. This study provides a combined analysis of ML applications in agriculture, structured around five key objectives: (i) Analyzing ML techniques across pre-harvesting, harvesting, and post-harvesting phases. (ii) Demonstrating how ML can be used with agricultural data and data fusion. (iii) Conducting a bibliometric and statistical analysis to reveal research trends and activity. (iv) Investigating real-world case studies of leading artificial intelligence (AI)-driven agricultural companies that use different types of multisensors and multisource data. (v) Compiling publicly available datasets to support ML model training. Going beyond existing previous reviews, this review focuses on how machine learning (ML) techniques, combined with multi-source data fusion (integrating remote sensing, IoT, and climate analytics), enhance precision agriculture by improving predictive accuracy and decision-making. Case studies and statistical insights illustrate the evolving landscape of AI driven smart farming, while future research directions also discusses challenges associated with data fusion for heterogeneous datasets. This review bridges the gap between AI research and agricultural applications, offering a roadmap for researchers, industry professionals, and policymakers to harness information fusion and ML for advancing precision agriculture. Copyright © 2024, The Authors. All rights reserved.

关键词： Adversarial machine learning

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A new Fermatean fuzzy Spearman-like correlation coefficient and its application in evaluating insecurity problem via multi-criteria decision-making approach

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Heliyon 2024年第22期10卷 e40403页

作者： Ejegwa, Paul Augustine Kausar, Nasreen Aydin, Nezir Feng, Yuming Olanrewaju, Oludolapo Akanni Department of Mathematics Joseph Sarwuan Tarka University Makurdi Nigeria Department of Mathematics Faculty of Arts and Science Yildiz Technical University Esenler Istanbul 34220 Turkey College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Department of Industrial Engineering Yildiz Technical University Besiktas Istanbul 34349 Turkey Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Chongqing 404100 China Department of Industrial Engineering Durban University of Technology Durban 4001 South Africa

The problem of insecurity is a global crisis with adverse effects on lives and properties. Fermatean fuzzy correlation coefficient is a dependable method for handling imprecision, which is the main bottleneck of insecurity assessment. A number of Fermatean fuzzy correlation coefficient methods have been developed. Based on Spearman's correlation coefficient, an innovative Fermatean fuzzy correlation coefficient method is built to enhance trustworthy insecurity assessment. The existing Fermatean fuzzy correlation coefficient methods are evaluated, and their shortcomings are identified in order to validate the construction of a new Fermatean fuzzy correlation coefficient method. The drawbacks of the existing methods lead us into building a new Fermatean fuzzy correlation coefficient method by using the Spearman's correlation coefficient approach, which has the potential of overcoming the drawbacks of the existing Fermatean fuzzy correlation coefficient methods. In addition, some theoretical findings are provided to support the strength of the novel Fermatean fuzzy correlation coefficient method and it is shown that the new method satisfies the Fermatean fuzzy correlation coefficient requirements. Furthermore, the novel Fermatean fuzzy correlation coefficient method is applied to assess the insecurity situation in the North-Central Region of Nigeria to furnish intended tourists with relevant travel advice. To demonstrate the inherent significance of the novel Fermatean fuzzy correlation coefficient method, we compare its effectiveness to that of the extant Fermatean fuzzy correlation coefficient methods. The results of the comparison show the superiority of the novel Fermatean fuzzy correlation coefficient method over the existing ones in terms of reliability, consistency, precision and compliance with the Fermatean fuzzy correlation coefficient axioms. Ultimately, it is discovered that the new method can effectively address hesitations related to insecurity assessment

关键词： Correlation coefficient Fermatean fuzzy sets Insecurity assessment Multi-criteria decision-making North central region of Nigeria Security crises

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On the Complexity of Problems on Tree-structured Graphs

arXiv

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arXiv 2022年

作者： Bodlaender, Hans L. Groenland, Carla Jacob, Hugo Pilipczuk, Marcin Pilipczuk, Michal Department of Information and Computing Sciences Utrecht University Netherlands Faculty of Electrical Engineering Mathematics and Computer Science Technical University Delft Netherlands LIRMM Université de Montpellier CNRS Montpellier France University of Warsaw Poland

In this paper, we introduce a new class of parameterized problems, which we call XALP: the class of all parameterized problems that can be solved in f(k)nO(1) time and f(k) log n space on a non-deterministic Turing Machine with access to an auxiliary stack (with only top element lookup allowed). Various natural problems on 'tree-structured graphs' are complete for this class: we show that List Colouring and All-or-Nothing Flow parameterized by treewidth are XALP-complete. Moreover, Independent Set and Dominating Set parameterized by treewidth divided by log n, and Max Cut parameterized by cliquewidth are also XALP-complete. Besides finding a 'natural home' for these problems, we also pave the road for future reductions. We give a number of equivalent characterisations of the class XALP, e.g., XALP is the class of problems solvable by an Alternating Turing Machine whose runs have tree size at most f(k)nO(1) and use f(k) log n space. Moreover, we introduce 'tree-shaped' variants of Weighted CNF-Satisfiability and Multicolour Clique that are XALP-complete. Copyright © 2022, The Authors. All rights reserved.

关键词： Turing machines

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A Comparative Nanotribological Investigation on Amorphous and Polycrystalline Forms of Mos2

SSRN

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SSRN 2024年

作者： Khaksar, Hesam Mittal, Prashant Daghbouj, Nabil Cios, Grzegorz Polcar, Tomas Gnecco, Enrico Marian Smoluchowski Institute of Physics Jagiellonian University Krakow30-348 Poland Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic AGH University of Science and Technology Academic Centre for Materials and Nanotechnology Al. A. Mickiewicza 30 Krakow30-059 Poland

The wear behavior of two amorphous and polycrystalline forms of MoS2 prepared by magnetron sputtering is characterized in a combined nanoindentation and atomic force microscopy study. From the morphology of wear tracks estimated after scratching the surfaces with a Berkovich indenter and a loading force up to 2 mN, we conclude that both forms follow the Archard wear equation, and the wear resistance is about four times higher on the amorphous MoS2. A comparison of lateral force maps on pristine and worn areas shows a considerable reduction of friction on both forms, which is possibly due to significant smoothing of the surfaces caused by scratching. With normal forces in the µN range, the analysis is made difficult by the fact that the linear dimensions of the wear tracks are comparable to those of the granular structures forming the surfaces. Even if the Archard equation could not be tested in this case, the wear resistance is considerably larger on amorphous MoS2 also on the nanoscale. In this way, our results disclose information on the nanotribology of MoS2 thin films in forms different from the layered structures commonly discussed in the literature. The amorphous form outperforms the polycrystalline one. © 2024, The Authors. All rights reserved.

关键词： Friction

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Nonlinear Observer Design Methods Based on High-Gain Methodology and LMIs with Application to Vehicle Tracking

Nonlinear Observer Design Methods Based on High-Gain Methodo...

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American control Conference (ACC)

作者： H. Bessafa C. Delattre Z. Belkhatir A. Zemouche R. Rajamani CRAN CNRS UMR 7039 Université de Lorraine Cosnes et Romain France Department of Electronics and Computer Science University of Southampton Southampton UK Faculty of Computing Engineering and Media De Montfort University The Gateway Leicester UK Department of Mechanical Engineering Laboratory for Innovations in Sensing Estimation and Control University of Minnesota Minneapolis USA

The main objective of this work is to propose a solution to observer design for triangular systems where additional output measurements are available, which may improve the estimation quality. In fact, such additional measurements prevent the standard high-gain observer methodology to provide solutions for the estimation problem. In this paper, motivated by this issue, we propose two novel observer design methods to handle the additional output measurements. The first one can be viewed as an extension of the standard high-gain observer by introducing a weighting matrix as a tuning parameter, while the second method, which can be viewed as an alternative method, exploits jointly the high-gain methodology and the LPV/LMI technique to overcome some limitations related to the first design method. The proposed methods are applied to a vehicle trajectory estimation problem using the well-known kinematic model. The efficiency of the estimation using both proposed methods and a comparative study between them are provided.

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An Efficient Wireless Sensor Network based Intrusion Detection System

An Efficient Wireless Sensor Network based Intrusion Detecti...

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Communication, Security and Artificial Intelligence (ICCSAI), International Conference on

作者： Dinesh Rajassekharan V Ramachandran Dilip Kumar Sharma Thirumoorthy Palanisamy Y. Varatharaj Myilsam Ramesh Chandra Poonia Faculty of Computer Science Peninsula College Malaysia Department of Computer Science and Engineering GITAM School of Computing GITAM Deemed to be University Bengaluru India Department of Mathematics Jaypee University of Engineering and Technology Guna Madhya Pradesh India Department of Computer Science and Engineering Nandha Engineering College Erode Tamil Nadu India Department of Electrical and Electronics Engineering V.S.B College of Engineering Technical Campus Coimbatore Tamil Nadu India Department of Computer Science CHRIST (Deemed to be University) Delhi-NCR Ghaziabad Uttar Pradesh India

Wireless Sensor Networks (WSNs) are widely used in diverse applications due to their cost-effectiveness and versatility. However, they face substantial difficulties because of their innate resource constraints and susceptibility to security attacks. A possible method to improve the security of WSNs is clustering-based intrusion detection and responding mechanisms. An in-depth analysis of the clustering-based intrusion detection and response method for WSNs is presented in this study. The suggested method efficiently uses data mining and machine learning techniques to identify unusual behaviour and probable intrusions. The system effectively analyses data inside clusters by grouping Sensor Nodes (SN) into clusters, allowing it to differentiate between legitimate patterns and insecure activity. The network may respond promptly to identified breaches and react to the responsive mechanism, which reduces their impact and protects network integrity. The proposed Mathematically Modified Gene Populated Spectral Clustering Based Intrusion Detection System and Responsive Mechanism (MMMMGPSC-IDS-RM) is compared with existing state-of-art techniques, and MMMMGPSC-IDS-RM outperforms with the highest detection rate of 96%.

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