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Predicting potential invasion risks of Leucaena leucocephala(Lam.)de Wit in the arid area of saudi Arabia

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Journal of Arid Land 2024年第7期16卷 983-999页

作者： Haq s MARIFATUL Darwish mohammed Waheed muhammad Kumar MANOJ siddiqui H MANZER Bussmann W RAINER Department of Ethnobotany Institute of BotanyIlia State UniversityTbilisi 0162Georgia The Centre of Excellence on sustainable Land Management(CoE-sLM) Indian Council of Forestry Research and EducationDehradun 248006India Department of Botany and Microbiology College of ScienceKing Saud UniversityRiyadh 11451Saudi Arabia Department of Botany State Museum for Natural HistoryKarlsruhe 76133Germany

The presence of invasive plant species poses a substantial ecological impact,thus comprehensive evaluation of their potential range and risk under the influence of climate change is *** study uses maximum entropy(MaxEnt)modeling to forecast the likelihood of Leucaena leucocephala(Lam.)de Wit invasion in saudi Arabia under present and future climate change *** the MaxEnt modeling,we integrated climatic and soil data to predict habitat suitability for the invasive *** conducted a detailed analysis of the distribution patterns of the species,using climate variables and ecological *** focused on the important influence of temperature seasonality,temperature annual range,and precipitation *** distribution modeling used robust measures of area under the curve(AUC)and receiver-operator characteristic(ROC)curves,to map the invasion extent,which has a high level of accuracy in identifying appropriate *** complex interaction that influenced the invasion of *** was highlighted by the environmental parameters using Jackknife ***,the actual geographic area where *** was found in saudi Arabia was considerably smaller than the theoretical maximum range,suggesting that it had the capacity to expand *** MaxEnt model exhibited excellent prediction accuracy and produced reliable results based on the data from the ROC *** and temperature were the primary factors influencing the potential distribution of ***,an estimated area of 216,342 km^(2)in saudi Arabia was at a high probability of invasion by *** investigated the potential for increased invasion hazards in the future due to climate change scenarios(shared socioeconomic Pathways(ssPs)245 and 585).The analysis of key climatic variables,including temperature seasonality and annual range,along with soil properties such as clay composition and nitrogen content,unveiled their substanti

关键词： area under the curve invasive species invasion risks climate change MaxEnt model

Complex Decision Modeling Framework with Fairly Operators and Quaternion Numbers under Intuitionistic Fuzzy Rough Context

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Computer Modeling in Engineering & sciences 2024年第5期139卷 1893-1932页

作者： Nadeem salamat muhammad Kamran shahzaib Ashraf Manal Elzain mohammed Abdulla rashad Ismail mohammed M.Al-shamiri Institute of Mathematics Khwaja Fareed University of Engineering&Information TechnologyRahim Yar Khan64200Pakistan Department of Mathematics Thal University BhakkarPunjab30000Pakistan Department of Mathematics Faculty of Science and ArtsKing Khalid UniversityMuhayl Assir61913Saudi Arabia

The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy,accessibility,and *** paper investigates the potential applications of intuitionistic fuzzy sets(IFs)with rough sets in the context of sparse *** it comes to capture uncertain information emanating fromboth upper and lower approximations,these intuitionistic fuzzy rough numbers(IFRNs)are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets,*** use rough sets in conjunction with IFss to develop several fairly aggregation operators and analyze their underlying *** present numerous impartial laws that incorporate the idea of proportionate dispersion in order to ensure that the membership and non-membership activities of IFRNs are treated equally within these *** operations lead to the development of the intuitionistic fuzzy rough weighted fairly aggregation operator(IFRWFA)and intuitionistic fuzzy rough ordered weighted fairly aggregation operator(IFRFOWA).These operators successfully adjust to membership and non-membership categories with fairness and *** highlight the unique qualities of these suggested aggregation operators and investigate their use in the multiattribute decision-making *** use the intuitionistic fuzzy rough environment’s architecture to create a novel strategy in situation involving several decision-makers and non-weighted ***,we developed a novel technique by combining the IFss with quaternion *** establish a unique connection between alternatives and qualities by using intuitionistic fuzzy quaternion numbers(IFQNs).With the help of this framework,we can simulate uncertainty in real-world situations and address a number of decision-making *** the examples we have released,we offer a sophisticated and systematically constructed illustrative scenario that is intricately wo

关键词： Intuitionistic fuzzy set quaternion numbers fuzzy logic decision-making rough set

social Media-Based surveillance systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & sciences 2024年第5期139卷 1167-1202页

作者： samina Amin muhammad Ali Zeb Hani alshahrani mohammed Hamdi Mohammad alsulami Asadullah shaikh Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Computer science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Information system College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

social media(sM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic *** review discusses the current state of sM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their ***,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by *** paper outlines the theme of sM analysis for tracking health-related issues and detecting epidemic outbreaks in sM,along with the ML and DL techniques that have been configured for the detection of epidemic *** has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation *** recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in sM *** paper aims to provide an overview of epidemic outbreaks in sM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in sM ***,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： social media epidemic machine learning deep learning health informatics pandemic

Improving Thyroid Disorder Diagnosis via Ensemble stacking and Bidirectional Feature selection

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Computers, Materials & Continua 2024年第3期78卷 4225-4241页

作者： muhammad Armghan Latif Zohaib Mushtaq saad Arif sara Rehman muhammad Farrukh Qureshi Nagwan Abdel samee Maali Alabdulhafith Yeong Hyeon Gu mohammed A.Al-masni Department of Computer and Information system Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Biomedical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Artificial Intelligence College of Software and Convergence TechnologySejong UniversitySeoul05006Korea

Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid *** and timely diagnosis of these disorders is crucial for effective treatment and patient *** research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection *** forward feature selection,sequential backward feature elimination,and bidirectional feature elimination are investigated in this *** ensemble learning,random forest,adaptive boosting,and bagging classifiers are *** effectiveness of these techniques is evaluated using two different datasets obtained from the University of California Irvine-Machine Learning Repository,both of which undergo preprocessing steps,including outlier removal,addressing missing data,data cleansing,and feature *** experimentation demonstrates the remarkable success of proposed ensemble stacking and bidirectional feature elimination achieving 100%and 99.86%accuracy in identifying hyperthyroidism and hypothyroidism,*** enhancing detection accuracy,the ensemble stacking model also demonstrated a streamlined computational complexity which is pivotal for practical medical *** significantly outperformed existing studies with similar objectives underscoring the viability and effectiveness of the proposed *** research offers an innovative perspective and sets the platform for improved thyroid disorder diagnosis with broader implications for healthcare and patient well-being.

关键词： Ensemble learning random forests boosting dimensionality reduction machine learning smart healthcare computer aided diagnosis

Mechanical performance of cold mix asphalt containing cup lump rubber as a sustainable bio-modifier

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Journal of Traffic and Transportation Engineering(English Edition) 2024年第3期11卷 424-440页

作者： syed Abdul Ghafar muhammad Naqiuddin Mohd Warid Norhidayah Abdul Hassan Zulfiqar Ali Jattak Ashraf Abdalla mohammed Radwan Faculty of Civil Engineering Universiti Teknologi MalaysiaSkudai 81310Malaysia Department of Civil Engineering Balochistan University of Information TechnologyEngineering&Management SciencesQuettaPakistan Department of Civil Engineering Balochistan University of Engineering and TechnologyKhuzdarPakistan Department of Civil Engineering Faculty of EngineeringUniversity of TripoliTripoliLibya

The road construction industry aims to contribute to the protection of already compromised *** mix asphalt(CMA)is a measure initiated by the road industry to protect the environment and preserve *** having additional benefits,CMA has attracted little attention due to its inferior ***'s performance is enhanced using a sustainable binder bio-modifier,natural cup lump rubber(CLR)is one of *** study evaluated the tensile properties,rutting,moisture susceptibility,and adhesion properties of CLR-modified CMA(CMA-CR).The tensile property was enhanced by 26%due to CLR ***-CR had excellent rutting resistance of less than 2 mm rut depth at 10,000 load cycles,showing 70%improvement compared with conventional *** susceptibility evaluation indicated that CMA-CR had tensile strength ratio(TsR)value of 104%,satisfying the minimum 80%requirement of AAsHTO *** also retained more than 96%bitumen *** moisture damage resistance was improved by 12%and 10%in terms of TsR and stripping,*** durability results revealed that the CMA-CR mixture prevented higher mass loss,representing 14%improvement compared with conventional CMA.

关键词： Cup lump rubber Cup lump modified cold mix asphalt Moisture damage Tensile property Rutting Digital imaging

Fine-Tuning Cyber security Defenses: Evaluating supervised Machine Learning Classifiers for Windows Malware Detection

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Computers, Materials & Continua 2024年第8期80卷 2917-2939页

作者： Islam Zada mohammed Naif Alatawi syed muhammad saqlain Abdullah alshahrani Adel alshamran Kanwal Imran Hessa Alfraihi Department of software Engineering International Islamic UniversityIslamabad25000Pakistan Information Technology Department Faculty of Computers and Information TechnologyUniversity of TabukTabuk71491Saudi Arabia Department of Computer science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Computer science University of PeshawarPeshawar25121Pakistan Department of Information systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Malware attacks on Windows machines pose significant cybersecurity threats,necessitating effective detection and prevention *** machine learning classifiers have emerged as promising tools for malware ***,there remains a need for comprehensive studies that compare the performance of different classifiers specifically for Windows malware *** this gap can provide valuable insights for enhancing cybersecurity *** numerous studies have explored malware detection using machine learning techniques,there is a lack of systematic comparison of supervised classifiers for Windows malware *** the relative effectiveness of these classifiers can inform the selection of optimal detection methods and improve overall security *** study aims to bridge the research gap by conducting a comparative analysis of supervised machine learning classifiers for detecting malware on Windows *** objectives include Investigating the performance of various classifiers,such as Gaussian Naïve Bayes,K Nearest Neighbors(KNN),stochastic Gradient Descent Classifier(sGDC),and Decision Tree,in detecting Windows *** the accuracy,efficiency,and suitability of each classifier for real-world malware detection *** the strengths and limitations of different classifiers to provide insights for cybersecurity practitioners and *** recommendations for selecting the most effective classifier for Windows malware detection based on empirical *** study employs a structured methodology consisting of several phases:exploratory data analysis,data preprocessing,model training,and *** data analysis involves understanding the dataset’s characteristics and identifying preprocessing *** preprocessing includes cleaning,feature encoding,dimensionality reduction,and optimization to prepare the data for *** training utilizes various

关键词： security and privacy challenges in the context of requirements engineering supervisedmachine learning malware detection windows systems comparative analysis Gaussian Naive Bayes K Nearest Neighbors stochastic Gradient Descent Classifier Decision Tree

Recent progress in two-dimensional metallenes and their potential application as electrocatalyst

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Journal of Energy Chemistry 2024年第7期94卷 577-598页

作者： Umer shahzad Mohsin saeed muhammad Fazle Rabbee Hadi M.Marwani Jehan Y.Al-Humaidi muhammad Altaf Raed H.Althomali Kwang-Hyun Baek Md.Rabiul Awual mohammed M.Rahman Department of Chemistry Faculty of ScienceKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Biotechnology Yeungnam UniversityGyeongsanSouth Korea Center of Excellence for Advanced Materials Research(CEAMR) King Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Chemistry College of SciencePrincess Nourah Bint Abdulrahman UniversityP.O.BOX 84428Riyadh 11671Saudi Arabia Department of Chemistry Center of Excellence for Innovation in Chemistry(PERCH-CIC)Center of Excellence in Materials Science and TechnologyFaculty of ScienceChiang Mai UniversityChiang Mai 50200Thailand Department of Chemistry College of Art and SciencePrince Sattam Bin Abdulaziz UniversityWadi Al-Dawasir 11991Saudi Arabia Western Australian school of Mines:Minerals Energy and Chemical EngineeringCurtin UniversityGPO Box U 1987PerthWA 6845Australia

In this article,we looked at metallenes,a novel class of two-dimensional(2D)metals that are attracting interest in the energy and catalysis *** is one area where their exceptional physicochemical and electrical characteristics might be *** are unique because they include several metal atoms that are not in a coordinated *** makes them more active and improves their atomic uti-lization,which in turn increases their catalytic *** article delves into the potential of two-dimensional metals as electrocatalysts for carbon dioxide reduction,fuel oxidation,oxygen evolution,and oxygen reduction reactions in the context of sustainable energy *** to the exception-ally high surface-to-volume ratio,large surface area as well as their optimized atomic use efficiency,2D materials defined by atomic layers are crucial for surface-related sustainable energy *** to its exceptional properties,such as high conductivity and the ability to enhance the exposure of active metal sites,2D metallenes have recently attracted a lot of interest for use in catalysis,electronics,and energy-related *** their highly mobility,adjustable surface states,and electrical struc-tures that can be fine-tuned,2D metallenes are promising nanostructure materials for use in energy con-version with the sustainable applications.

关键词： Metallenes Electrocatalysts Electrochemical processes Atomically thin structure

smartphone-Based Wi-Fi Analysis for Bus Passenger Counting

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Computers, Materials & Continua 2024年第4期79卷 875-907页

作者： mohammed Alatiyyah Department of Computer science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

In the contemporary era of technological advancement,smartphones have become an indispensable part of individuals’daily lives,exerting a pervasive *** paper presents an innovative approach to passenger countingonbuses throughthe analysis ofWi-Fi signals emanating frompassengers’mobile *** study seeks to scrutinize the reliability of digital Wi-Fi environments in predicting bus occupancy levels,thereby addressing a crucial aspect of public *** proposed system comprises three crucial elements:signal capture,data filtration,and the calculation and estimation of passenger *** pivotal findings reveal that the system demonstrates commendable accuracy in estimating passenger counts undermoderate-crowding conditions,with an average deviation of 20%from the ground truth and an accuracy rate ranging from 90%to 100%.This underscores its efficacy in scenarios characterized by moderate levels of ***,in densely crowded conditions,the system exhibits a tendency to overestimate passenger numbers,occasionally doubling the actual *** acknowledging the need for further research to enhance accuracy in crowded conditions,this study presents a pioneering avenue to address a significant concern in public *** implications of the findings are poised to contribute substantially to the enhancement of bus operations and service quality.

关键词： Public transportation digital environment passenger estimation signal capturing Wi-Fi

EECLP: AWireless sensor Networks Energy Efficient Cross-Layer Protocol

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Computers, Materials & Continua 2024年第8期80卷 2611-2631页

作者： mohammed Kaddi mohammed Omari Moamen Alnatoor LDDI Laboratory University of AdrarAdrar01000Algeria Computer science and Engineering Department School of EngineeringAmerican University of Ras Al KhaimahRas Al Khaimah72603United Arab Emirates

Recent advancements in wireless communications have allowed the birth of novel wireless sensor networks(WsN).A sensor network comprises several micro-sensors deployed randomly in an area of interest.A micro-sensor is provided with an energy resource to supply electricity to all of its ***,the disposed energy resource is limited and battery replacement is generally *** this restriction,the sensors must conserve energy to prolong their *** energy conservation strategies for WsNs have been presented in the literature,from the application to the physical *** of these solutions focus only on optimizing a single layer in terms of energy *** this research,a novel cross-layer technique for WsNs’effective energy usage is *** most energy consumption factors exist in the Medium Access Control(MAC)layer and network layer,our EECLP protocol(Energy Efficient Cross-Layer Protocol for Wireless sensor Networks)integrates these two layers to satisfy energy efficiency *** gain access to the transmission channel,we implement a communication regime at the MAC layer based on CsMA/CA(Carrier sense Multiple Access/Collision Avoidance)***,depending on the activity and a standby period,we employ the RTs/CTs(Request to send/Clear to send)method to prevent collisions and resolve hidden node concerns by utilizing the network allocation vector(NAV)to calculate the transmission *** a greedy strategy,we establish chains amongst cluster members to mitigate the issue of high energy consumption in routing *** objective function was utilized to determine the optimal cross-chain path based on the distances to the base station(Bs)and residual energy(RE).The simulation,testing,and comparison of the proposed protocol to peer protocols have shown superior outcomes and a prolonged network *** the suggested protocol,the network lifetime increases by 10%compared to FAMACO(Fuzzy and Ant Col

关键词： WsN energy consumption MAC layer network layer EECLP energy-efficient lifespan