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New generalized fuzzy transform computations for solving fractional partial differential equations arising in oceanography

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Journal of Ocean Engineering and Science 2023年第1期8卷 55-78页

作者： Saima Rashid Rehana ashraf Zakia Hammouch Department of Mathematics Government College UniversityFaisalabadPakistan Department of Mathematis Lahore College for Women UniversityLahorePakistan Division of Applied Mathematics Thu Dau Mot University Binh Duong ProvinceVietnam Department of Medical Research China Medical University HospitalTaichungTaiwan Department of Sciences Ecole Normal SuperieureMoulay Ismail University of Meknes50000 Morocco

This paper presents a study of nonlinear waves in shallow *** Korteweg-de Vries(KdV)equa-tion has a canonical version based on oceanography theory,the shallow water waves in the oceans,and the internal ion-acoustic waves in ***,the main goal of this investigation is to employ a semi-analytical method based on the homotopy perturbation transform method(HPTM)to obtain the numerical findings of nonlinear dispersive and fifth order KdV models for investigating the behaviour of magneto-acoustic waves in plasma via *** approach is connected with the fuzzy generalized integral transform and *** that,two novel results for fuzzy generalized integral transforma-tion concerning fuzzy partial gH-derivatives are *** illustrative examples are illustrated to show the effectiveness and supremacy of the proposed ***,2D and 3D simulations de-pict the comparison analysis between two fractional derivative operators(Caputo and Atangana-Baleanu fractional derivative operators in the Caputo sense)under generalized *** projected method(GHPTM)demonstrates a diverse spectrum of applications for dealing with nonlinear wave equa-tions in scientific *** current work,as a novel use of GHPTM,demonstrates some key differ-ences from existing similar methods.

关键词： Fuzzy set theory Hukuhara differentiability KdV Equation Generalized integral transform Caputo fractional derivative AB-Fractional operator Homotopy perturbation method

Fruits and Vegetables Freshness Categorization Using Deep Learning

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Computers, Materials & Continua 2022年第6期71卷 5083-5098页

作者： Labiba Gillani Fahad Syed Fahad Tahir usama Rasheed Hafsa Saqib Mehdi Hassan Hani Alquhayz Department of Computer Science National University of Computer and Emerging SciencesIslamabad44000Pakistan Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science and Information College of Science in ZulfiMajmaah UniversityAl-Majmaah11952Kingdom of Saudi Arabia

The nutritional value of perishable food items,such as fruits and vegetables,depends on their freshness *** existing approaches solve a binary class problem by classifying a known fruit\vegetable class into fresh or rotten *** propose an automated fruits and vegetables categorization approach that first recognizes the class of object in an image and then categorizes that fruit or vegetable into one of the three categories:purefresh,medium-fresh,and *** gathered a dataset comprising of 60K images of 11 fruits and vegetables,each is further divided into three categories of freshness,using hand-held *** recognition and categorization of fruits and vegetables are performed through two deep learning models:Visual Geometry Group(VGG-16)and You Only Look Once(YOLO),and their results are ***-16 classifies fruits and vegetables and categorizes their freshness,while YOLO also localizes them within the ***,we have developed an android based application that takes the image of the fruit or vegetable as input and returns its class label and its freshness degree.A comprehensive experimental evaluation of proposed approach demonstrates that the proposed approach can achieve a high accuracy and F1score on gathered FruitVeg Freshness *** dataset is publicly available for further evaluation by the research community.

关键词： Fruits and vegetables classification degree of freshness deep learning object detection model VGG-16 YOLO-v5

Automotive Visible-Light Communication: Alternative Devices and Systems

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清华大学学报:自然科学版(英文版) 2023年第4期28卷 719-728页

作者： Lin Cheng Yue Wu Chenren Xu Khadija ashraf Ashwin Ashok Department of Engineering Trinity CollegeHartfordCT 06106USA Department of Computer Science Yale UniversityNew HavenCT 06520USA Department of Computer Science and Technology Peking UniversityBeijing 100084China Department of Computer Science Georgia State UniversityAtlantaGA 30302USA

Continuous advancements in visible-light communication(VLC)technology have paved the way for future high-capacity communication links that can simultaneously provide data transmission and *** is being accepted as a potential complementary technology in 5G networks,and standardization efforts through IEEE 802.15.7 are on their ***,vehicular networking applications have become increasingly complex with tight power and performance ***,devices and systems that can meet diverse vehicular networking applications are in great *** this article,we discuss three alternatives for vehicular networking applications in(1)LED–photodiode-based active VLC,(2)VLC with a multicamera array receiver,and(3)passive VLC based on decoding information from optical *** also present our recent experimental and modeling work using our camera-based and passive VLC prototype implementations.

关键词： visible-light communications automobile camera communications

BotSward: Centrality Measures for Graph-Based Bot Detection Using Machine Learning

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Computers, Materials & Continua 2023年第1期74卷 693-714页

作者： Khlood Shinan Khalid Alsubhi M.Usman ashraf Department of Computer Science College Computer Science in Al-LeithUmm Al-Qura UniversityMecca 21421Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Computer Science GC Women University SialkotPakistan

The number of botnet malware attacks on Internet devices has grown at an equivalent rate to the number of Internet devices that are connected to the *** detection using machine learning(ML)with flow-based features has been extensively studied in the *** flow-based detection methods involve significant computational overhead that does not completely capture network communication patterns that might reveal other features ofmalicious ***,Graph-Based Bot Detection methods using ML have gained attention to overcome these limitations,as graphs provide a real representation of network *** purpose of this study is to build a botnet malware detection system utilizing centrality measures for graph-based botnet detection and *** propose BotSward,a graph-based bot detection system that is based on *** apply the efficient centrality measures,which are Closeness Centrality(CC),Degree Centrality(CC),and PageRank(PR),and compare them with others used in the *** efficiency of the proposed method is verified on the available Czech Technical University 13 dataset(CTU-13).The CTU-13 dataset contains 13 real botnet traffic scenarios that are connected to a command-and-control(C&C)channel and that cause malicious actions such as phishing,distributed denial-of-service(DDoS)attacks,spam attacks,*** is robust to zero-day attacks,suitable for large-scale datasets,and is intended to produce better accuracy than state-of-the-art *** proposed BotSward solution achieved 99%accuracy in botnet attack detection with a false positive rate as low as 0.0001%.

关键词： Network security botnet detection graph-based features machine learning measure centrality

Energy-Efficient UAVs Coverage Path Planning Approach

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Computer Modeling in Engineering & Sciences 2023年第9期136卷 3239-3263页

作者： Gamil Ahmed Tarek Sheltami ashraf Mahmoud Ansar Yasar Computer Engineering Department Interdisciplinary Research Center of Smart Mobility and LogisticsKing Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Transportation Research Institute(IMOB) Hasselt UniversityHasselt3500Belgium

Unmanned aerial vehicles(UAVs),commonly known as drones,have drawn significant consideration thanks to their agility,mobility,and flexibility *** play a crucial role in modern reconnaissance,inspection,intelligence,and surveillance *** path planning(CPP)which is one of the crucial aspects that determines an intelligent system’s quality seeks an optimal trajectory to fully cover the region of interest(ROI).However,the flight time of the UAV is limited due to a battery limitation and may not cover the whole region,especially in large ***,energy consumption is one of the most challenging issues that need to be *** this paper,we propose an energy-efficient coverage path planning algorithm to solve the CPP *** objective is to generate a collision-free coverage path that minimizes the overall energy consumption and guarantees covering the whole *** do so,the flight path is optimized and the number of turns is reduced to minimize the energy *** proposed approach first decomposes the ROI into a set of cells depending on a UAV camera ***,the coverage path planning problem is formulated,where the exact solution is determined using the CPLEX *** small-scale problems,the CPLEX shows a better solution in a reasonable ***,the CPLEX solver fails to generate the solution within a reasonable time for large-scale ***,to solve the model for large-scale problems,simulated annealing forCPP is *** results show that heuristic approaches yield a better solution for large-scale problems within amuch shorter execution time than the CPLEX ***,we compare the simulated annealing against the greedy *** results show that simulated annealing outperforms the greedy algorithm in generating better solution quality.

关键词： Coverage path planning MILP CPLEX solver energy model optimization region of interest area of interest

An evolutionarily conserved nitrate sensor inplants

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Molecular Plant 2022年第11期15卷 1652-1653页

作者： M.Arif ashraf Stavroula Fili Department of Biology University of Massachusetts AmherstAmherstMA 01003USA Plant Biology Program University of Massachusetts AmherstAmherstMA 01003USA

Nitrogen availability in plant tissues triggers transcriptomic responses that affect not only nitrate homeostasis but also metabolic,hormonal,and developmental processes(Wang et al.,2018).The ability to sense extracellular nitrate has been attributed to the characterized nitrate transceptor NRT1.1(CHL1/NPF6.3);however,null chl1-5 mutants are not entirely impaired in the primary nitrogen response,suggesting that there might be other sensors that act independently(Wang et al.,2018).Furthermore,the calcium-sensor protein kinases(CPKs)responsible for transducing nitrate signaling downstream,even when constitutively activated,still require the presence of nitrate(Liu et al.,2017),indicating an additional nitrate-sensing mechanism.

关键词： mechanism nitrate entirely

Blockchain-Based Decentralized Authentication Model for IoT-Based E-Learning and Educational Environments

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Computers, Materials & Continua 2023年第5期75卷 3133-3158页

作者： Osama A.Khashan Sultan Alamri Waleed Alomoush Mutasem K.Alsmadi Samer Atawneh usama Mir Research and Innovation Centers Rabdan AcademyP.O.Box 114646Abu DhabiUnited Arab Emirates College of Computing and Informatics Saudi Electronic UniversityRiyadh13316Saudi Arabia School of Information Technology Skyline University CollegeP.O.Box 1797SharjahUnited Arab Emirates Department of MIS College of Applied Studies and Community ServicesImam Abdulrahman Bin Faisal UniversityP.O.Box 1982DammamSaudi Arabia Department of Computer Science University of WindsorWindsorN9J3Y1Canada

In recent times,technology has advanced significantly and is currently being integrated into educational environments to facilitate distance learning and interaction between *** the Internet of Things(IoT)into education can facilitate the teaching and learning process and expand the context in which students ***,learning data is very sensitive and must be protected when transmitted over the network or stored in data ***,the identity and the authenticity of interacting students,instructors,and staff need to be verified to mitigate the impact of ***,most of the current security and authentication schemes are centralized,relying on trusted third-party cloud servers,to facilitate continuous secure *** addition,most of these schemes are resourceintensive;thus,security and efficiency issues arise when heterogeneous and resource-limited IoT devices are being *** this paper,we propose a blockchain-based architecture that accurately identifies and authenticates learners and their IoT devices in a decentralized manner and prevents the unauthorized modification of stored learning records in a distributed university *** allows students and instructors to easily migrate to and join multiple universities within the network using their identity without the need for user *** proposed architecture was tested using a simulation tool,and measured to evaluate its *** simulation results demonstrate the ability of the proposed architecture to significantly increase the throughput of learning transactions(40%),reduce the communication overhead and response time(26%),improve authentication efficiency(27%),and reduce the IoT power consumption(35%)compared to the centralized authentication *** addition,the security analysis proves the effectiveness of the proposed architecture in resisting various attacks and ensuring the security requirements of learning data in the unive

关键词： Blockchain decentralized authentication Internet of Things(IoT) E-learning IoT security

Wi-Fi Positioning Dataset with Multiusers and Multidevices Considering Spatio-Temporal Variations

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Computers, Materials & Continua 2022年第3期70卷 5213-5232页

作者： Imran ashraf Sadia Din Soojung Hur Yongwan Park Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-si38541Korea

Precise information on indoor positioning provides a foundation for position-related customer *** the emergence of several indoor positioning technologies such as ultrawideband,infrared,radio frequency identification,Bluetooth beacons,pedestrian dead reckoning,and magnetic field,Wi-Fi is one of the most widely used ***,Wi-Fi fingerprinting is the most popular method and has been researched over the past two ***-Fi positioning faces three core problems:device heterogeneity,robustness to signal changes caused by human mobility,and device attitude,i.e.,varying *** existing methods do not cover these aspects owing to the unavailability of publicly available *** study introduces a dataset that includes the Wi-Fi received signal strength(RSS)gathered using four different devices,namely Samsung Galaxy S8,S9,A8,LG G6,and LG G7,operated by three surveyors,including a female and two *** addition,three orientations of the smartphones are used for the data collection and include multiple buildings with a multifloor *** levels of human mobility have been considered in dynamic *** analyze the time-related impact on Wi-Fi RSS,data over 3 years have been considered.

关键词： Wi-fi positioning dataset smartphone sensors benchmark analysis indoor positioning and localization spatio-temporal data

Synergy of remotely sensed data in spatiotemporal dynamic modeling of the crop and cover management factor

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Pedosphere 2022年第3期32卷 381-392页

作者： Pooja P.PREETHA ashraf Z.AL-HAMDAN Department of Civil Engineering Alabama A&M University4900 Meridian Street NHuntsvilleAL 35811-7500(USA) Department of Civil and Environmental Engineering University of Alabama in Huntsville301 Sparkman DriveHuntsvilleAL 35899-7500(USA)

Soil erosion is a threat to the water quality constituents of sediments and nutrients and can cause long-term environmental *** important parameter to quantify the risk of soil loss from erosion is the crop and cover management factor(C-factor),which represents how cropping and management practices affect the rates and potential risk of soil *** developed remotely sensed data-driven models for dynamic predictions of C-factor by implementing dynamic land cover modeling using the SWAT(Soil and Water Assessment Tool)model on a watershed *** remotely sensed processed variables included the enhanced vegetation index(EVI),the fraction of photosynthetically active radiation absorbed by green vegetation(FPAR),leaf area index(LAI),soil available water content(AWC),slope gradient(SG),and ratio of area(AR)of every hydrologic response unit(HRU)to that of the total watershed,comprising unique land cover,soil type,and slope gradient characteristics within the Fish River catchment in Alabama,USA between 2001 and *** regressions,spatial trend analysis,correlation matrices,forward stepwise multivariable regression(FSMR),and 2-fold cross-validation were conducted to evaluate whether there were possible associations between the C-factor and EVI with the successive addition of remotely sensed environmental *** on the data analysis and modeling,we found a significant association between the C-factor and EVI with the synergy of the environmental factors FPAR,LAI,AWC,AR,and SG(predicted R^(2)(R^(2)_(pred))=0.51;R^(2)=0.68,n=3220,P<0.15).The results showed that the developed FSMR model constituting the non-conventional factors AWC(R^(2)_(pred)=0.32;R^(2)=0.48,n=3220,P<0.05)and FPAR(R^(2)_(pred)=0.13;R^(2)=0.28,n=3220,P=0.31)was an improved fit for the watershed *** conclusion,the union of dynamic variables related to vegetation(EVI,FPAR,and LAI),soil(AWC),and topography(AR and SG)can be utilized for spatiotemporal C-factor estimation and to mo

关键词： C-factor enhanced vegetation index land cover modeling remote sensing soil erosion soil moisture solar radiation