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Securing Cloud-Encrypted Data:Detecting Ransomware-as-a-Service(RaaS)Attacks through Deep Learning Ensemble

Computers, Materials & Continua 2024年第4期79卷 857-873页

作者： Amardeep Singh Hamad Ali Abosaq Saad Arif zohaib mushtaq Muhammad Irfan Ghulam Abbas Arshad Ali Alanoud Al Mazroa School of Computer Information Sciences University of CumberlandsWilliamsburgKentucky40769USA Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Electrical Engineering The University of LahoreLahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware *** study provides a new approach for RaaS attack detection which uses an ensemble of deep learning *** this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is *** the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are ***,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested *** proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%*** empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual *** expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.

关键词： Cloud encryption RaaS ensemble threat detection deep learning cybersecurity

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Hyperspectral Images-Based Crop Classification Scheme for Agricultural Remote Sensing

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Computer Systems Science & Engineering 2023年第7期46卷 303-319页

作者： Imran Ali zohaib mushtaq Saad Arif Abeer D.Algarni Naglaa F.Soliman Walid El-Shafai Department of Mechanical Engineering National Taiwan University of Science and TechnologyTaipei City106335TaiwanChina Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Mechanical Engineering HITEC University TaxilaTaxila Cantt.47080Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia

Hyperspectral imaging is gaining a significant role in agricultural remote sensing *** data unit is the hyperspectral cube which holds spatial information in two dimensions while spectral band information of each pixel in the third *** classification accuracy of hyperspectral images(HSI)increases significantly by employing both spatial and spectral *** this work,the data was acquired using an airborne hyperspectral imager system which collected HSI in the visible and near-infrared(VNIR)range of 400 to 1000 nm wavelength within 180 spectral *** dataset is collected for nine different crops on agricultural land with a spectral resolution of 3.3 nm wavelength for each *** data was cleaned from geometric distortions and stored with the class labels and annotations of global localization using the inertial navigation *** this study,a unique pixel-based approach was designed to improve the crops'classification accuracy by using the edge-preserving features(EPF)and principal component analysis(PCA)in *** preliminary processing generated the high-dimensional EPF stack by applying the edge-preserving filters on acquired *** the second step,this high dimensional stack was treated with the PCA for dimensionality reduction without losing significant spectral *** resultant feature space(PCA-EPF)demonstrated enhanced class separability for improved crop classification with reduced dimensionality and computational *** support vector machines classifier was employed for multiclass classification of target crops using *** classification performance evaluation was measured in terms of individual class accuracy,overall accuracy,average accuracy,and Cohen kappa *** proposed scheme achieved greater than 90%results for all the performance evaluation *** PCA-EPF proved to be an effective attribute for crop classification using hyperspectral imaging in the VNIR *** proposed scheme

关键词： Hyperspectral imaging visible and near-infrared edge preserving feature dimensionality reduction crop classification

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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

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Minimal Doubly Resolving Sets of Certain Families of Toeplitz Graph

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Computer Modeling in Engineering & Sciences 2023年第6期135卷 2681-2696页

作者： Muhammad Ahmad Fahd Jarad zohaib Zahid Imran Siddique Department of Mathematics University of Management and TechnologyLahore54770Pakistan Department of Mathematics Cankaya UniversityEtimesgutAnkara06790Turkey Department of Medical Research China Medical University HospitalChina Medical UniversityTaichung40402Taiwan

The doubly resolving sets are a natural tool to identify where diffusion occurs in a complicated *** realworld phenomena,such as rumour spreading on social networks,the spread of infectious diseases,and the spread of the virus on the internet,may be modelled using information diffusion in *** is obviously impractical to monitor every node due to cost and overhead limits because there are too many nodes in the network,some of which may be unable or unwilling to send information about their *** a result,the source localization problem is to find the number of nodes in the network that best explains the observed *** problem can be successfully solved by using its relationship with the well-studied related minimal doubly resolving set problem,which minimizes the number of observers required for accurate *** paper aims to investigate the minimal doubly resolving set for certain families of Toeplitz graph Tn(1,t),for t≥2 and n≥t+*** come to the conclusion that for Tn(1,2),the metric and double metric dimensions are equal and for Tn(1,4),the double metric dimension is exactly one more than the metric ***,the double metric dimension for Tn(1,3)is equal to the metric dimension for n=5,6,7 and one greater than the metric dimension for n≥8.

关键词： Family of Toeplitz graph resolving sets metric dimension doubly resolving sets double metric dimension

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A Fuzzy Logic Based Power-Efficient Run-Time Reconfigurable Multicore System

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Chinese Journal of Electronics 2018年第3期27卷 549-555页

作者： Shaheryar Najam Muhammad Yasir Qadri zohaib Najam Jameel Ahmed Nadia N.Qadri Electrical Engineering Department Riphah International University School of Computer Science and Electronic Engineering University of Essex Electrical Engineering Department HITEC University Department of Electrical Engineering COMSATS Institute of Information Technology

Increasing demand for better throughput and performance has motivated designers to come up with more sophisticated processors with innovative designs. Such designs for multicore architectures offer large amount of parallelism which is often underutilized and thus becomes overhead and liability. Due to these advancements, there has been a exponential increase in power consumption and heat dissipation of computing devices. Under these circumstances, an ideal system would be a reconfigurable system that can switch off all underutilized resources and work with only required ones. There is a need of reconfigurable computing devices and processors that are smart enough to configure themselves dynamically on runtime to find balance between throughput and power-consumption. This paper proposes a novel fuzzy logic based Dynamic voltage and frequency scaling(DVFS)and power-gating enabled controller which is capable of reducing power-consumption without affecting throughput and overall performance of the system. The design is implemented on Intel processor using Ubuntu as an operating system. Implementation results show that proposed Fuzzy logic controller(FLC) reduces power-consumption upto 40% by reconfiguring the processor dynamically without compromising the throughput.

关键词： DVFS Fuzzy logic controller Energy Throughput

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Phytopharmacological potential of different species of Morus alba and their bioactive phytochemicals:A review

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Asian Pacific Journal of Tropical Biomedicine 2017年第10期7卷 950-956页

作者： Fahad Hussain zohaib Rana Hassan Shafique Arif Malik Zahid Hussain Institute of Molecular Biology and Biotechnology(IMBB) The University of LahoreRaiwind Road55150LahorePakistan Department of Pharmaceutics Faculty of PharmacyUniversiti Teknologi MARAPuncak Alam CampusBandar Puncak Alam42300SelangorMalaysia

Medicinal plants of Moraceae family have been well-recognized traditionally due to their versatile applications in various fields including agriculture, cosmetic and food as well as in pharmaceutical industries. Their biomedical and medicinal importance is reflected from their broad range of pharmacological activities for treatment of various inflammatory conditions, cancer, infectious diseases, and gastrointestinal disorders. The present review was aimed to summarize and critically discuss the biomedical implications of Morus species, their bioactive compounds, and phytochemicals. Bioactivity guided fractionation of these medicinal plants revealed that different types of bioactive phytochemicals and secondary metabolites such as steroids, saponins, alkaloids, glycosides and phenolic compounds including terpenoids, flavonoids, anthocyanins and tannins were present. The critical analysis of the literature revealed that the aqueous, methanolic, and ethanolic extracts of Morus species and their bioactive compounds exhibit remarkable anti-oxidative,anti-diabetic, anti-stress, nephroprotective, antimicrobial, anti-mutagenic, anticancer,anxiolytic, hepatoprotective, anthelmintic, antimicrobial, immune-modulatory and cholesterol lowering effects. Based on the literature review and bioactivity guided investigation of Morus species and their phytomedicinal effects, we anticipate that these herbal products hold excellent potential for future research.

关键词： Moraceae Phytochemicals Pharmacological activities Anti-inflammatory Immunomodulatory Anticancer

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Metal-Doped Brushite Cement for Bone Regeneration

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Journal of Bionic Engineering 2023年第6期20卷 2716-2731页

作者： Muhammad Aqib Aneela Anwar Humayun Ajaz Samina Akbar Ahsan Manzoor Maham Abid zohaib Waheed Qudsia Kanwal Department of Chemistry University of Engineering and TechnologyGT RoadLahore54890Pakistan Department of Chemistry University of LahoreLahore5400Pakistan

For the past several years,calcium phosphate cement was used in the biomedical *** biocompatibility,good bioactivity,self-setting qualities,minimum setting degree,appropriate toughness,and simple shape to accommodate any difficult geometry are among their most notable *** phosphate has some types and brushite is one of the most attractive mineral for bone repair *** is extensively employed in filling fractures and trauma treatments as a bone substituted *** kind of material can potentially be used as a medicine delivery *** replacement of metal,such as magnesium,zinc,and strontium ions,into the calcium phosphate structure is a major research topic these *** cement has low mechanical strength and quick setting *** is possible to produce biomaterials with higher mechanical *** adding metal that are great potential in controlling cellular density when included into *** a result,it is a successful method to develop quite well regenerative *** paper provides a detailed summary of the present achievements of metal-doped brushite cement for bone repair and healing *** major purpose of this work is to give a simple but thorough analysis of current successes in brushite cement doped with Zn,Mg,Sr,and other ions as well as to highlight new advancements and *** impact of metal replacement on cement physical and chemical properties,including microstructure,setting time,injectability,mechanical property,and ion release,is *** metal-doped cement has osteogenesis,angiogenesis,and antibacterial properties,as well as their prospective utility as drug carriers,also considered.

关键词： Calcium phosphate Brushite Bone cement Metal dopants Bone regeneration

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Enhanced Nature Inspired-Support Vector Machine for Glaucoma Detection

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Computers, Materials & Continua 2023年第7期76卷 1151-1172页

作者： Jahanzaib Latif Shanshan Tu Chuangbai Xiao Anas Bilal Sadaqat Ur Rehman zohaib Ahmad Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information TechnologyBeijing University of Technology100124BeijingChina College of Information Science Technology Hainan Normal UniversityHainan ProvinceHaikou571158China Department of Computer Science University of SalfordManchesterUK Faculty of Information Technology Beijing University of Technology Chaoyang District BeijingChina

Glaucoma is a progressive eye disease that can lead to blindness if left *** detection is crucial to prevent vision loss,but current manual scanning methods are expensive,time-consuming,and require specialized *** study presents a novel approach to Glaucoma detection using the Enhanced Grey Wolf Optimized Support Vector Machine(EGWO-SVM)*** proposed method involves preprocessing steps such as removing image noise using the adaptive median filter(AMF)and feature extraction using the previously processed speeded-up robust feature(SURF),histogram of oriented gradients(HOG),and Global *** enhanced Grey Wolf Optimization(GWO)technique is then employed with SVM for *** evaluate the proposed method,we used the online retinal images for glaucoma analysis(ORIGA)database,and it achieved high accuracy,sensitivity,and specificity rates of 94%,92%,and 92%,*** results demonstrate that the proposed method outperforms other current algorithms in detecting the presence or absence of *** study provides a novel and effective approach to Glaucoma detection that can potentially improve the detection process and outcomes.

关键词： Glaucoma detection grey golf optimization support vector machine feature extraction image classification

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Efficient hepatoprotective activity of cranberry extract against CCl_4-induced hepatotoxicity in Wistar albino rat model: Down-regulation of liver enzymes and strong antioxidant activity

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Asian Pacific Journal of Tropical Medicine 2017年第11期10卷 1054-1058页

作者： Fahad Hussain Arif Malik Ujala Ayyaz Hassan Shafique zohaib Rana Zahid Hussain Institute of Molecular Biology and Biotechnology (IMBB) The University of Lahore Department of Biochemistry University of AgricultureFaisalabad Department of Pharmaceutics Faculty of Pharmacy Universiti Teknologi MARA Puncak Alam Campus

ObjectiveTo investigate the hepatoprotective efficacy of cranberry extract (CBE) against carbon tetrachloride (CCl4)-induced hepatic injury using in-vivo animal *** hepatoprotective efficacy of CBE (200 and 400 mg/kg) was investigated against CCl4 (4 mL/kg)-induced hepatotoxicity, elevated liver enzymes [ALT (alanine aminotransferase), AST (aspartate aminotransferase), and alkaline phosphatase (ALP)], and total protein (TP) contents in the serum. Moreover, CBE-aided antioxidant defense against hepatotoxic insult of CCl4 was measured by evaluating a number of anti-oxidative biomarkers including reduced glutathione (GSH), superoxide dismutase (SOD), catalase (CAT), and malondialdehyde (MDA) in the serum by using spectrophotometric *** showed that the exposure of experimental animals to CCl4 did induce significant hepatotoxicity compared to the non-induced (untreated) group. The oral administration of CBE demonstrated a significant dose-dependent alleviation in the liver enzymes (AST, ALT, and ALP), increased antioxidant defense (GSH, SOD, and CAT), and reduced MDA levels in the serum of treated animals compared to the animals without treatment. The resulting data showed that the administration of CBE decreased the serum levels of ALT, AST, and ALP compared to the CCl4-induced *** resulting data evidenced that CBE exhibits promising hepatoprotective potential against the chemical induced hepatotoxicity, maintains homeostasis in liver enzymes, and can provide significant antioxidant defense against free radicals-induced oxidative stress.

关键词： Hepatotoxicity Carbon tetrachloride Oxidative stress Liver enzymes Cranberry extract Hepatoprotective

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The role of green industrial transformation in mitigating carbon emissions:Exploring the channels of technological innovation and environmental regulation

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Energy and Built Environment 2024年第3期5卷 464-479页

作者： Saima Mehmood Khalid Zaman Shiraz Khan zohaib Ali Haroon ur Rashid Khan Department of Economics The University of HaripurHaripurKhyber Pakhtunkhwa 22620Pakistan Department of Management Sciences The University of HaripurHaripurKhyber Pakhtunkhwa 22620Pakistan Department of Energy and Process Engineering(EPT) Norwegian University of Science and TechnologyHøgskoleringen 1Trondheim 7034Norway Faculty of Business The University of Wollongong in DubaiDubai 20183United Arab Emirates

The industrial sector is vital to economic progress,yet industrial pollution poses environmental and economic *** purpose of the study was to investigate the influence of green industrial transformation in re-ducing Pakistan’s carbon intensity between 1975 and *** emissions are considered an endogenous construct,while foreign direct investment(FDI)inflows,technological innovation,green industrial transforma-tion,environmental legislation,and research and development(R&D)investment are possible *** association between variables is assessed using the robust least-squares *** industrial transforma-tion is connected with lower carbon emissions,yet technical innovation,R&D investment,and inbound FDI raise a country’s carbon *** findings support the pollution haven hypothesis in a *** causality esti-mates indicate that inward FDI contributes to environmental regulations;green industrial transformation directly relates to inbound FDI and R&D expenditures;and technological innovations correspond to inbound FDI,R&D ex-penditures,industrial ecofriendly progression,and environmental *** to the impulse response function,environmental policies are anticipated to have a differential effect on carbon emissions in 2023,2024,2028-2030,while they are likely to decrease in the years 2025-2027 and 2031 ***,inward FDI and technology advancements would almost certainly result in a rise in carbon emissions over *** industrial transitions are projected to result in a ten-year reduction in carbon *** variance decomposi-tion analysis indicates that eco-friendly industrial adaptations would likely have the largest variance error shock on carbon emissions(11.747%),followed by inbound FDI,technological advancements,and regulatory changes,with R&D spending having a minimal impact over ***’s economy should foster a green industrial revolution to avoid pollution and increase environm

关键词： Carbon intensity Industrial green transformation Environmental regulations Technological innovations Robust least squares regression

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