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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

Towards wafer-scale growth of two-dimensional cerium dioxide single crystal with high dielectric performance

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Nano Research 2024年第9期17卷 8592-8599页

作者： Zhuofeng Shi muhammad imran Xiaohui Chen Xin Liu Yaqi Zhu Zhaoning Hu Saiyu Bu Jialin Zhang Chunhu Li Xiaodong Zhang Li Lin College of Chemistry and Chemical Engineering Qingdao UniversityQingdao 266000China School of Materials Science and Engineering Peking UniversityBeijing 100871China Center for Nanochemistry Beijing Science and Engineering Center for NanocarbonsBeijing National Laboratory for Molecular ScienceCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China Key Laboratory of Marine Chemistry Theory and Technology Ministry of EducationCollege of Chemistry and Chemical EngineeringOcean University of ChinaQingdao 266100China

Owing to the atomically thin nature,two-dimensional(2D)oxide materials have been widely reported to exhibit exciting transport and dielectric properties,such as fine gate controllability and ultrahigh carrier mobility,that outperform their bulk ***,unlike the successful synthesis of bulk oxide single crystals,reliable methods for synthesizing large-area single crystal of 2D oxide,that would suppress the negative influence from defective grain boundaries,remain unavailable,especially for nonlayered ***,we report that the lattice symmetry between the substrate and cerium dioxide(CeO_(2))would allow for the aligned nucleation and epitaxial growth of CeO_(2)on sapphire substrates,enabling the wafer-sized growth of CeO_(2)single *** careful tuning of the growth temperature and oxygen flow rate contributed to the harvesting of CeO_(2)wafer with reduced thickness and enhanced growth *** removal of grain boundaries improved the dielectric performance in terms of high dielectric strength(Ebd≈8.8 MV·cm^(-1)),suppressed leakage current,along with high dielectric constants(εr≈24).Our work demonstrates that with fine dielectric performance and ease of synthesizing wafer-sized single crystals,CeO_(2)can function as potential candidate as gate insulator for 2D-materials based nanoelectronics,and we believe the reported protocol of aligned nucleation can be extended to other 2D oxides.

关键词： dielectric materials two-dimensional materials chemical vapor deposition cerium dioxide

DeepSVDNet:A Deep Learning-Based Approach for Detecting and Classifying Vision-Threatening Diabetic Retinopathy in Retinal Fundus Images

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Computer Systems Science & Engineering 2024年第2期48卷 511-528页

作者： Anas Bilal Azhar imran Talha Imtiaz Baig Xiaowen Liu Haixia Long Abdulkareem Alzahrani muhammad Shafiq College of Information Science and Technology Hainan Normal UniversityHaikou571158China Department of Creative Technologies Air UniversityIslamabadPakistan School of Life Science and Technology University of Electronic Science and Technology of China UESTCChengduChina School of Science and Technology University of Management and Technology UMTLahorePunjabPakistan Faculty of Computer Science&Information Technology Al Baha UniversityAl BahaSaudi Arabia School of Information Engineering Qujing Normal UniversityQujingChina

Artificial Intelligence(AI)is being increasingly used for diagnosing Vision-Threatening Diabetic Retinopathy(VTDR),which is a leading cause of visual impairment and blindness ***,previous automated VTDR detection methods have mainly relied on manual feature extraction and classification,leading to *** paper proposes a novel VTDR detection and classification model that combines different models through majority *** proposed methodology involves preprocessing,data augmentation,feature extraction,and classification *** use a hybrid convolutional neural network-singular value decomposition(CNN-SVD)model for feature extraction and selection and an improved SVM-RBF with a Decision Tree(DT)and K-Nearest Neighbor(KNN)for *** tested our model on the IDRiD dataset and achieved an accuracy of 98.06%,a sensitivity of 83.67%,and a specificity of 100%for DR detection and evaluation tests,*** proposed approach outperforms baseline techniques and provides a more robust and accurate method for VTDR detection.

关键词： Diabetic retinopathy(DR) fundus images(FIs) support vector machine(SVM) medical image analysis convolutional neural networks(CNN) singular value decomposition(SVD) classification

Regulatory potential of soil available carbon,nitrogen,and functional genes on N_(2)O emissions in two upland plantation systems

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Journal of Integrative Agriculture 2024年第8期23卷 2792-2806页

作者： Peng Xu Mengdie Jiang imran Khan muhammad Shaaban Hongtao Wu Barthelemy Harerimana Ronggui Hu Key Laboratory of Mountain Surface Processes and Ecological Regulation Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China College of Resources and Environment Huazhong Agricultural UniversityWuhan 430070China Hubei Collaborative Innovation Centre for Grain Industry College of AgricultureYangtze UniversityJingzhou 434025China College of Agriculture Henan University of Science and TechnologyLuoyang 471000China College of Urban and Environmental Sciences Hubei Normal UniversityHuangshi 435002China University of Chinese Academy of Sciences Beijing 100049China

Dynamic nitrification and denitrification processes are affected by changes in soil redox conditions,and they play a vital role in regulating soil N_(2)O emissions in rice-based *** is imperative to understand the influences of different upland crop planting systems on soil N_(2)O *** this study,we focused on two representative rotation systems in Central China:rapeseed–rice(RR)and wheat–rice(WR).We examined the biotic and abiotic processes underlying the impacts of these upland plantings on soil N_(2)O *** results revealed that during the rapeseed-cultivated seasons in the RR rotation system,the average N_(2)O emissions were 1.24±0.20 and 0.81±0.11 kg N ha^(–1)for the first and second seasons,*** values were comparable to the N_(2)O emissions observed during the first and second wheat-cultivated seasons in the WR rotation system(0.98±0.25 and 0.70±0.04 kg N ha^(–1),respectively).This suggests that upland cultivation has minimal impacts on soil N_(2)O emissions in the two rotation *** positive correlations were found between N_(2)O fluxes and soil ammonium(NH_(4)^(+)),nitrate(NO_(3)^(–)),microbial biomass nitrogen(MBN),and the ratio of soil dissolved organic carbon(DOC)to NO_(3)^(–)in both RR and WR rotation ***,the presence of the AOA-amoA and nirK genes were positively associated with soil N_(2)O fluxes in the RR and WR systems,*** implies that these genes may have different potential roles in facilitating microbial N_(2)O production in various upland plantation *** using a structural equation model,we found that soil moisture,mineral N,MBN,and the AOA-amoA gene accounted for over 50%of the effects on N_(2)O emissions in the RR rotation *** the WR rotation system,soil moisture,mineral N,MBN,and the AOA-amoA and nirK genes had a combined impact of over 70%on N_(2)O *** findings demonstrate the interactive effects of functional genes and soil factors,including

关键词： upland-rice cultivation N_(2)O emission regulatory factors functional genes

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Enhancing PDF Malware Detection through Logistic Model Trees

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Computers, Materials & Continua 2024年第3期78卷 3645-3663页

作者： muhammad Binsawad Department of Information Systems King Abdulaziz UniversityP.O.Box 80217Jeddah21589Saudi Arabia

Malware is an ever-present and dynamic threat to networks and computer systems in cybersecurity,and because of its complexity and evasiveness,it is challenging to identify using traditional signature-based detection *** study article discusses the growing danger to cybersecurity that malware hidden in PDF files poses,highlighting the shortcomings of conventional detection techniques and the difficulties presented by adversarial *** article presents a new method that improves PDF virus detection by using document analysis and a Logistic Model *** a dataset from the Canadian Institute for Cybersecurity,a comparative analysis is carried out with well-known machine learning models,such as Credal Decision Tree,Naïve Bayes,Average One Dependency Estimator,Locally Weighted Learning,and Stochastic Gradient *** traditional structural and JavaScript-centric PDF analysis,the research makes a substantial contribution to the area by boosting precision and resilience in malware *** use of Logistic Model Tree,a thorough feature selection approach,and increased focus on PDF file attributes all contribute to the efficiency of PDF virus *** paper emphasizes Logistic Model Tree’s critical role in tackling increasing cybersecurity threats and proposes a viable answer to practical issues in the *** results reveal that the Logistic Model Tree is superior,with improved accuracy of 97.46%when compared to benchmark models,demonstrating its usefulness in addressing the ever-changing threat landscape.

关键词： Malware detection PDF files logistic model tree feature selection cybersecurity

Progress in electrocatalytic nitrate reduction for green energy:Catalyst engineering,mechanisms,and techno-economic feasibility

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Journal of Energy Chemistry 2024年第8期95卷 380-406,I0009页

作者： Hafiz muhammad Adeel Sharif Hafiz muhammad Farooq Khan Sadeeq Ullah Yuwei Wang muhammad Ahmad Bo Yang Changping Li muhammad Bilal Asif Research Center for Eco-Environmental Engineering Dongguan University of TechnologyDongguan 523808GuangdongChina College of Chemistry and Engineering Shenzhen UniversityShenzhen 518060GuangdongChina FMH College of Medicine and Dentistry LahorePakistan School of Environment and Civil Engineering Research Center for Eco-Environment EngineeringDongguan University of TechnologyDongguan 523106GuangdongChina Advanced Membranes and Porous Materials Center(AMPMC) Physical Sciences and Engineering(PSE)King Abdullah University of Science and Technology(KAUST)Thuwal 23955Saudi Arabia

Ammonia(NH_(3))is an irreplaceable chemical that has been widely demanded to keep the sustainable development of modern ***,its industrial production consumes a huge amount of energy and releases extraordinary greenhouse gases(GHGs),leading to various environmental *** the green production of ammonia is a great challenge,which has been extensively pursued in the last *** this review,the most promising strategy,electrochemical nitrate reduction reaction(e-NO_(3)RR),is comprehensively investigated to give a complete understanding of its development and mechanism and provide guidance for future ***,owing to the complex reactions and limited selectivity,a comprehensive understanding of the mechanisms is crucial to further development and ***,NO_(3)^(-)RR is a promising strategy for simultaneous water treatment and NH_(3)production.A detailed overview of the recent progress in NO_(3)^(-)RR for NH_(3)production with nontransition and transition metal based electrocatalysts is *** addition,critical advanced techniques,future challenges,and prospects are discussed to guide future research on transition metal-based catalysts for commercial NH_(3)synthesis by NO_(3)^(-)reduction.

关键词： Nitrate reduction Electrolysis Pollution to solution Transition metal catalysts Ammonia synthesis Green energy

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Design and Synthesis of NiO@Co_(3)O_(4)@ZSM-5 Heterogeneous Multitask Hollow Structures for Tandem Catalysis

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Chemical Research in Chinese Universities 2024年第3期40卷 529-535页

作者： muhammad Waqas Interdisciplinary Research Center for Refining and Advanced Chemicals King Fahd University of Petroleum&MineralsDhahran 31261Saudi Arabia

Precipitation and impregnation procedures unevenly distribute metals on zeolite,limiting chemical transformation in Lewis-acid,Brönsted-acid and metal-catalyzed tandem ***,heterogeneous multitask transition metals oxides@zeolites are promising catalysts for sustainable processes;nevertheless,synthesis is fascinating and ***,the construction of purposely designed multitask materials segregated in selective shells reveals the remarkable spatial organization of metals-zeolite,resulting in them being suitable for a wide range of tandem *** synthesis of multi-site catalysts begins with a universal wet chemistry approach that yields nickel oxide(NiO)***,the NiO crystals are stabilized using cationic dodecyltrimethylammonium bromide,followed by achieving cross-linking carbon growth by emulsion polymerization of glucose in hydrothermal treatment to yield uniformed NiO@carbon spheres(NiO@CSs).Next,sequential adsorption of cobalt cations and colloidal ZSM-5(1%in H_(2)O,mass fraction),followed by calcination in air,yielded NiO@cobalt oxide@zeolite denoted as NiO@Co_(3)O_(4)@ZEO hollow *** hollowing mechanism and materials segregation within shells are revealed by scanning and transmission electron microscopy,thermogravimetric analysis,and X-ray *** finding advances the rational synthesis of heterogenous core-shell hollow structures for various gas phase catalytic tandem reactions to yield valuable chemicals.

关键词： Multifunctional Core-shell hollow spheres Gas-phase reaction Valuable chemical

Al3+ doped CeO2 for proton conducting fuel cells

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International Journal of Minerals,Metallurgy and Materials 2024年第10期31卷 2253-2262页

作者： Sarfraz Shahzad Rasool muhammad Khalid M.A.K.Yousaf Shah Bin Zhu Jung-Sik Kim muhammad imran Asghar Nabeela Akbar Wenjing Dong Jiangsu Provincial Key Laboratory of Solar Energy Science and Technology/Energy Storage joint Research Center School of Energy and Environment Southeast University Sino-French Engineer School/School of General Engineering Beihang University Renewable Energy Technologies Group Faculty of Engineering and Natural Sciences Tampere University School of Microelectronics Hubei University

Developing high ionic conducting electrolytes is crucial for applying proton-conducting fuel cell （PCFCs） *** current study investigates the effect of alumina on the structural,morphological,electrical,and electrochemical properties of *** oxygen vacancies are induced in CeO2by a general doping concept that enables fast ionic conduction at low-temperature ranges（300–500°C） for *** refinement of the X-ray diffraction （XRD） patterns established the pure cubic fluorite structure of Aldoped CeO2（ADC） samples and confirmed Al ions’fruitful integration in the *** electronic structure of the alumina-doped ceria of the materials （10ADC,20ADC,and 30ADC） has been *** a result,it was found that the best composition of 30ADC-based electrolytes induced maximum lattice oxygen *** corresponding PCFC exhibited a maximum power output of 923 mW/cm2at 500°***,the investigation proves the proton-conducting ability of alumina-doped ceria-based fuel cells by using an oxide ion-blocking layer.

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Highly responsive broadband Si-based MoSphototransistor on high-k dielectric

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Science China(Information Sciences) 2024年

作者： Ali imran Xin HE Jiwei LIU Qinghai ZHU muhammad SULAMAN Fei XUE Mingsheng XU Deren YANG Beijing Key Lab of Nanophotonics and Ultrafine Optoelectronic Systems School of PhysicsBeijing Institute of Technology ZJU-Hangzhou Global Scientific and Technological Innovation Centre College of Integrated Circuits State Key Laboratory of Silicon and Advanced Semiconductor MaterialsZhejiang University School of Materials Science and Engineering State Key Laboratory of Silicon and Advanced Semiconductor MaterialsZhejiang University

The demand for photodetectors and image sensors has grown exponentially in the past decade in biomedical, security surveillance, robotics, automotive, quality control, image recognition, and military applications, due to their superior quality, broadband detection, lower noise, and economic viability. Here,we report a MoS2channel-based phototransistor over an HfO2/n-Si substrate isolated by an h BN layer. The high photoresponse is achieved through the integration of the photoconduction, photogating, and mobility enhancement process by utilizing excellent features of MoS2, HfO2/Si, and h BN. The capacitive coupling of the photogenerated carriers by high-k dielectric HfO2leads to modulation of MoS2Fermi level due to electrostatic doping. Furthermore, the MoS2also contributes to the photogeneration of carriers due to its semiconducting nature, leading to additional photocurrent. Ultimately, the combination of photogating,photoconduction, and swift carrier extraction with remarkable mobility of 11.65 cm2·V-1·s-1results in high responsivity, external quantum efficiency, and detectivity of 4.5×108A·W-1, 0.72×106, and 6.20×1016Jones at 266 nm illumination, respectively. The device also demonstrates broadband photoresponse from 266–1000 nm wavelengths. The high responsivity distinguishes the potential of our device for the future of optoelectronics and broadband image sensing applications.

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