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A Low Complexity ML-Based Methods for Malware Classification

Computers, Materials & Continua 2024年第9期80卷 4833-4857页

作者： Mahmoud E.Farfoura Ahmad Alkhatib Deema Mohammed Alsekait Mohammad Alshinwan Sahar A.El-rahman Didi Rosiyadi Diaa Salama abd Elminaam Cybersecurity Department Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan Computer Systems Program-Electrical Engineering Department Faculty of Engineering-ShoubraBenha UniversityCairo11629Egypt Research Center for Artificial Intelligence and Cybersecurity Electronics and Informatics OrganizationNational Research and Innovation Agency(BRIN)KST Samaun SamadikunBandung40135Republic of Indonesia Jadara Research Center Jadara UniversityIrbid21110Jordan MEU Research Unit Middle East UniversityAmman11831Jordan

The article describes a new method for malware classification,based on a Machine Learning(ML)model architecture specifically designed for malware detection,enabling real-time and accurate malware *** an innovative feature dimensionality reduction technique called the Interpolation-based Feature Dimensionality Reduction Technique(IFDRT),the authors have significantly reduced the feature space while retaining critical information necessary for malware *** technique optimizes the model’s performance and reduces computational *** proposed method is demonstrated by applying it to the BODMAS malware dataset,which contains 57,293 malware samples and 77,142 benign samples,each with a 2381-feature *** the IFDRT method,the dataset is transformed,reducing the number of features while maintaining essential data for accurate *** evaluation results show outstanding performance,with an F1 score of 0.984 and a high accuracy of 98.5%using only two reduced *** demonstrates the method’s ability to classify malware samples accurately while minimizing processing *** method allows for improving computational efficiency by reducing the feature space,which decreases the memory and time requirements for training and *** new method’s effectiveness is confirmed by the calculations,which indicate significant improvements in malware classification accuracy and *** research results enhance existing malware detection techniques and can be applied in various cybersecurity applications,including real-timemalware detection on resource-constrained *** and scientific contribution lie in the development of the IFDRT method,which provides a robust and efficient solution for feature reduction in ML-based malware classification,paving the way for more effective and scalable cybersecurity measures.

关键词： Malware detection ML-based models dimensionality reduction feature engineering

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Bayesian Optimized LightGBM model for predicting the fundamental vibrational period of masonry infilled RC frames

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Frontiers of Structural and Civil Engineering 2024年第7期18卷 1084-1102页

作者： Taimur rahman Pengfei ZHENG Shamima SULTANA Department of Civil Engineering World University of BangladeshDhaka 1230Bangladesh School of Civil Engineering Zhengzhou UniversityZhengzhou 450001China Department of Computer Science&Engineering University of Asia PacificDhaka 1205Bangladesh

The precise prediction of the fundamental vibrational period for reinforced concrete(RC)buildings with infilled walls is essential for structural design,especially earthquake-resistant *** learning models from previous studies,while boasting commendable accuracy in predicting the fundamental period,exhibit vulnerabilities due to lengthy training times and inherent dependence on pre-trained models,especially when engaging with continually evolving data *** predicament emphasizes the necessity for a model that adeptly balances predictive accuracy with robust adaptability and swift data *** latter should include consistent re-training ability as demanded by realtime,continuously updated data *** research implements an optimized Light Gradient Boosting Machine(LightGBM)model,highlighting its augmented predictive capabilities,realized through the astute use of Bayesian Optimization for hyperparameter tuning on the FP4026 research data set,and illuminating its adaptability and efficiency in predictive *** results show that the R^(2) score of LightGBM model is 0.9995 and RMSE is 0.0178,while training speed is 23.2 times faster than that offered by XGBoost and 45.5 times faster than for Gradient ***,this study introduces a practical application through a streamlit-powered,web-based dashboard,enabling engineers to effortlessly utilize and augment the model,contributing data and ensuring precise fundamental period predictions,effectively bridging scholarly research and practical applications.

关键词： masonry-infilled RC frame fundamental period LightGBM FP4026 research dataset machine learning data-driven approach Bayesian Optimization

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Ion-acoustic waves with non-planar wavefronts

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Plasma Science and Technology 2024年第1期26卷 1-7页

作者： Shujaht BUKHARI Muhammad SHAHID Ata-ur rahman Department of Physics The University of Azad Jummu and KashmirMuzaffarabad 13100Azad Kashmir Department of Physics Women University of Azad Jammu&KashmirBagh 12500Pakistan Department of Physics Islamia College PeshawerPeshawar 25120Pakistan

The ion-acoustic(IA) mode exhibiting various orbital angular momentum(OAM) states is examined in a plasma with drifting *** constituent plasma species are modeled with a non-gyrotropic Maxwellian distribution and discussion of dispersion relation and growth rate of twisted IA waves under various conditions is *** the domain of kinetic model,the twisted IA waves are characterized by Laguerre-Gaussian(LG) solutions,where plasma distribution function and electric field are decomposed into axial and azimuthal *** plasma response function is obtained under paraxial approximations and investigated for threshold condition of instability growth rate with helical electric field *** impact of an extra electron specie on the instability is demonstrated through a comparison of twisted waves for single and double electron species.

关键词： instability twist parameter wave excitation orbital angular momentum threshold limit

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Effects of multiple shapes for steady flow with transformer oil+Fe_(3)O_(4)+TiO_(2) between two stretchable rotating disks

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Applied Mathematics and Mechanics(English Edition) 2024年第2期45卷 373-388页

作者： M.rahman M.TURKYILMAZOGLU Z.MUSHTAQ Department of Mathematics Mirpur University of Science and TechnologyMirpur 10250Pakistan Department of Mathematics Hacettepe UniversityBeytepeAnkara 06532Turkiye

In this study,we examine the effects of various shapes of nanoparticles in a steady flow of hybrid nanofluids between two stretchable rotating *** steady flow of hybrid nanofluids with transformer oil as the base fluid and Fe_(3)O_(4)+TiO_(2)as the hybrid nanofluid is *** shapes of Fe_(3)O_(4)+TiO_(2)hybrid nanofluids,including sphere,brick,blade,cylinder,and platelet,are *** shape exists in the same volume of a *** leading equations(partial differential equations(PDEs))are transformed to the nonlinear ordinary differential equations(ODEs)with the help of similarity *** system of equations takes the form of ODEs depending on the boundary conditions,whose solutions are computed numerically by the bvp4c MATLAB *** outputs are compared with the previous findings,and an intriguing pattern is discovered,such that the tangential velocity is increased for the rotation parameter,while it is decreased by the stretching values because of the lower *** the reaction rate parameter,the concentration boundary layer becomes shorter,and the activation energy component increases the rate at which mass transfers come to the higher disk but have the opposite effect on the bottom *** ranges of various parameters taken into account are Pr=6.2,Re=2,M=1.0,φ_(1)=φ_(2)=0.03,K=0.5,S=-0.1,Br=0.3,Sc=2.0,α_(1)=0.2,γ=0.1,E_(n)=2.0,and q=1.0,and the rotation factor K is within the range of 0 to 1.

关键词： transformer oil Brinkman number skin friction coefficient double rotating disk Nusselt number Sherwood number

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Privacy-preserved learning from non-i.i.d data in fog-assisted IoT:A federated learning approach

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Digital Communications and Networks 2024年第2期10卷 404-415页

作者： Mohamed abdel-Basset Hossam Hawash Nour Moustafa Imran Razzak Mohamed abd Elfattah Faculty of Computers and Informatics Zagazig UniversityZagazigSharqiyah44519Egypt School of Engineering and Information Technology University of New South Wales@ADFACanberraACT2600Australia Deakin University Geelong Waurn Ponds CampusAustralia Computer Science Department Misr Higher Institute for Commerce and ComputersMansoura35511Egypt

With the prevalence of the Internet of Things(IoT)systems,smart cities comprise complex networks,including sensors,actuators,appliances,and cyber *** complexity and heterogeneity of smart cities have become vulnerable to sophisticated cyber-attacks,especially privacy-related attacks such as inference and data poisoning *** Learning(FL)has been regarded as a hopeful method to enable distributed learning with privacypreserved intelligence in IoT *** though the significance of developing privacy-preserving FL has drawn as a great research interest,the current research only concentrates on FL with independent identically distributed(i.i.d)data and few studies have addressed the non-i.i.d *** is known to be vulnerable to Generative Adversarial Network(GAN)attacks,where an adversary can presume to act as a contributor participating in the training process to acquire the private data of other *** paper proposes an innovative Privacy Protection-based Federated Deep Learning(PP-FDL)framework,which accomplishes data protection against privacy-related GAN attacks,along with high classification rates from non-i.i.d ***-FDL is designed to enable fog nodes to cooperate to train the FDL model in a way that ensures contributors have no access to the data of each other,where class probabilities are protected utilizing a private identifier generated for each *** PP-FDL framework is evaluated for image classification using simple convolutional networks which are trained using MNIST and CIFAR-10 *** empirical results have revealed that PF-DFL can achieve data protection and the framework outperforms the other three state-of-the-art models with 3%–8%as accuracy improvements.

关键词： Privacy preservation Federated learning Deep learning Fog computing Smart cities

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The link between intracellular calcium signaling and exosomal PD-L1 in cancer progression and immunotherapy

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Genes & Diseases 2024年第1期11卷 321-334页

作者： Md Rakibul Alam Md Mizanur rahman Zhiguo Li Department of Toxicology and Cancer Biology College of MedicineUniversity of KentuckyLexingtonKY 40506USA Department of Medicine(Nephrology) Faculty of Medicine and DentistryUniversity of AlbertaEdmontonAlberta T6E2H7Canada

Exosomes are small membrane vesicles containing microRNA,RNA,DNA fragments,and proteins that are transferred from donor cells to recipient *** cells release exo-somes to reprogram the factors associated with the tumor microenvironment(TME)causing tu-mor metastasis and immune *** evidence revealed that cancer cell-derived exosomes carry immune inhibitory molecule program death ligand 1(PD-L1)that binds with re-ceptor program death protein 1(PD-1)and promote tumor progression by escaping immune ***,some FDA-approved monoclonal antibodies are clinicallyused for cancer treatment by blocking PD-1/PD-L1 *** notable treatment outcomes,some pa-tients show poor drug *** PD-L1 plays a vital role in lowering the treatment response,showing resistance to PD-1/PD-L1 blockage therapy through recapitulating the ef-fect of cell surface *** enhance therapeutic response,inhibition of exosomal PD-L1 is *** signaling is the central regulator of tumorigenesis and can regulate exosome biogenesis and secretion by modulating Rab GTPase family and membrane fusion ***-mune checkpoints are also connected with calcium signaling and calcium channel blockers like amlodipine,nifedipine,lercanidipine,diltiazem,and verapamil were also reported to suppress cellular PD-L1 ***,to enhance the PD-1/PD-L1 blockage therapy response,the reduction of exosomal PD-L1 secretion from cancer cells is in our therapeutic *** this review,we proposed a therapeutic strategy by targeting calcium signaling to inhibit the expression of PD-L1-containing exosome levels that could reduce the anti-PD-1/PD-L1 therapy resistance and increase the patient's drug response rate.

关键词： Calcium signaling CD8^(+)T cells Exosomal PD-L1 Exosomes biogenesis Immunosuppression Immunotherapy

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Entrepreneurship training:its influences on innovation potentials among nursing students

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Frontiers of Nursing 2024年第1期11卷 85-98页

作者： Asmaa abdel rahman abdel rahman Dalia abdallah abdelatief Medical Surgical Nursing Department Faculty of NursingAin Shams UniversityCairoEgypt

Objective:To evaluate the influences of entrepreneurship training on the innovation potential among nursing ***:A quasi-experimental design was utilized to conduct this *** study was conducted in the classroom at the faculty of nursing,and the“i Hub”center at Ain Shams University(ASU)in Cairo,Egypt.A purposive sample of 42 nursing students who participated in the“Ain Shams University-innovate”competition from the Faculty of Nursing of ASU were included in this *** collection tools included(1)Nursing students'innovation skills assessment questionnaire and(2)Innovative projects evaluation ***:There was a statistically significant difference between the mean scores of nursing students'total innovation skills pre-and post-implementation of entrepreneurship training,where P-value<***:The results of the current study support the research hypothesis because the implementation of entrepreneurship training positively affects nursing students'innovation *** entrepreneurship education in nursing and integrating it into nursing programs will stimulate creativity,innovation,and entrepreneurship among nursing students and health care services.

关键词： entrepreneurship training innovation potentials nursing students creative skills energy/motivation

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Sexual dimorphism of G protein-coupled receptor signaling in the brain

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Neural Regeneration Research 2024年第8期19卷 1635-1636页

作者： Sara Aljoudi Hamdan Hamdan Khaled S.abd-Elrahman Department of Physiology and Immunology College of Medicine and Health SciencesKhalifa UniversityAbu DhabiUnited Arab Emirates Healthcare Engineering Innovation Center(HEIC) Khalifa UniversityAbu DhabiUnited Arab Emirates Department of Anesthesiology Pharmacology and Therapeuticsand Djavad Mowafaghian Center for Brain HealthUniversity of British ColumbiaVancouverBCCanada Department of Pharmacology and Therapeutics College of Medicine and Health ScienceKhalifa UniversityAbu DhabiUnited Arab Emirates Department of Pharmacology and Toxicology Faculty of PharmacyAlexandria UniversityAlexandriaEgypt

G protein-coupled receptors(GPCRs)represent the most substantial family of membrane receptors that are targeted by *** and Drug Administration-approved *** of the preclinical research to understand the pharmacology of... 详细信息

关键词： drugs clinical targeted

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Evolution of blockchain consensus algorithms: a review on the latest milestones of blockchain consensus algorithms

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Cybersecurity 2024年第3期7卷 80-101页

作者： Ziad Hussein May A.Salama Sahar A.El-rahman Electrical Engineering Department Faculty of Engineering-ShoubraBenha UniversityCairoEgypt

Blockchain technology has gained widespread adoption in recent years due to its ability to enable secure and trans-parent record-keeping and data transfer.A critical aspect of blockchain technology is the use of consensus algorithms,which allow distributed nodes in the network to agree on the state of the *** this review paper,we exam-ine various consensus algorithms that are used in blockchain systems,including proof-of-work,proof-of-stake,and hybrid *** go over the trade-offs and factors to think about when choosing a consensus algorithm,such as energy efficiency,decentralization,and *** also look at the strengths and weaknesses of each algorithm as well as their potential impact on the scalability and adoption of blockchain technology.

关键词： Blockchain Consensus Proof of work Proof of stake Decentralization

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Thermal noise-driven resonant sensors

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Microsystems & Nanoengineering 2024年第3期10卷 259-271页

作者： Yan Qiao Alaaeldin Elhady Mohamed Arabi Eihab abdel-rahman Wenming Zhang School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghaiChina Department of Systems Design Engineering University of WaterlooWaterlooONCanada

MEMS/NEMS resonant sensors hold promise for minute mass and force ***,one major challenge is that conventional externally driven sensors inevitably encounter undesired intrinsic noise,which imposes a fundamental limitation upon their signal-to-noise ratio(SNR)and,consequently,the ***,this restriction becomes increasingly pronounced as sensors shrink to the *** this work,we propose a counterintuitive paradigm shift that turns intrinsic thermal noise from an impediment to a constituent of the sensor by harvesting it as the driving force,obviating the need for external actuation and realizing‘noise-driven’*** sensors employ the dynamically amplified response to thermal noise at resonances for stimulus *** demonstrate that lightly damped and highly compliant nano-structures with high aspect ratios are promising candidates for this class of *** overcome the phase incoherence of the drive force,three noise-enabled quantitative sensing mechanisms are *** validated our sensor paradigm by experimental demonstrating noise-driven pressure and temperature ***-driven sensors offer a new opportunity for delivering practical NEMS sensors that can function at room temperature and under ambient pressure,and a development that suggests a path to cheaper,simpler,and low-power-consumption sensors.

关键词： noise resonant overcome

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