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Computers, Materials & Continua 2024年第2期78卷 2269-2286页

作者： s.Abinaya k.Uttej kumar school of Computer science&Engineering Vellore Institute of TechnologyChennaiTamilnadu600127India

A recommender system(rs)is a crucial part of several firms,particularly those involved in *** conventional rs,a user may only offer a single rating for an item-that is insufficient to perceive consumer ***,businesses in industries like e-learning and tourism enable customers to rate a product using a variety of factors to comprehend customers’*** the other hand,the collaborative filtering(CF)algorithm utilizing AutoEncoder(AE)is seen to be effective in identifying user-interested ***,the cost of these computations increases nonlinearly as the number of items and users *** triumph over the issues,a novel expanded stacked autoencoder(EsAE)with kernel Fuzzy C-Means Clustering(kFCM)technique is proposed with two *** the first phase of offline,the sparse multicriteria rating matrix is smoothened to a complete matrix by predicting the users’intact rating by the EsAE approach and users are clustered using the kFCM *** the next phase of online,the top-N recommendation prediction is made by the EsAE approach involving only the most similar user from multiple *** the EsAE_kFCM model upgrades the prediction accuracy of 98.2%in Top-N recommendation with a minimized recommendation generation *** experimental check on the Yahoo!Movies(YM)movie dataset and TripAdvisor(TA)travel dataset confirmed that the EsAE_kFCM model constantly outperforms conventional rs algorithms on a variety of assessment measures.

关键词： recommender systems multicriteria rating collaborative filtering sparsity issue scalability issue stacked-autoencoder kernel Fuzzy C-Means Clustering

Covalent Bond Based Android Malware Detection Using Permission and system Call Pairs

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Computers, Materials & Continua 2024年第3期78卷 4283-4301页

作者： rahul Gupta kapil sharma r.k.Garg Department of Information Technology Delhi Technological UniversityNew Delhi110042India Department of Mechanical Engineering Deenbandhu Chhotu Ram University of Science and TechnologyMurthal131039India

The prevalence of smartphones is deeply embedded in modern society,impacting various aspects of our *** versatility and functionalities have fundamentally changed how we communicate,work,seek entertainment,and access *** the many smartphones available,those operating on the Android platform dominate,being the most widely used *** widespread adoption of the Android Os has significantly contributed to increased malware attacks targeting the Android ecosystem in recent ***,there is an urgent need to develop new methods for detecting Android *** literature contains numerous works related to Android malware *** far as our understanding extends,we are the first ones to identify dangerous combinations of permissions and system calls to uncover malicious behavior in Android *** introduce a novel methodology that pairs permissions and system calls to distinguish between benign and malicious *** approach combines the advantages of static and dynamic analysis,offering a more comprehensive understanding of an application’s *** establish covalent bonds between permissions and system calls to assess their combined *** introduce a novel technique to determine these pairs’Covalent Bond strength *** pair is assigned two scores,one for malicious behavior and another for benign *** scores serve as the basis for classifying applications as benign or *** correlating permissions with system calls,the study enables a detailed examination of how an app utilizes its requested permissions,aiding in differentiating legitimate and potentially harmful *** comprehensive analysis provides a robust framework for Android malware detection,marking a significant contribution to the *** results of our experiments demonstrate a remarkable overall accuracy of 97.5%,surpassing various state-of-the-art detection techniques proposed in the current literature.

关键词： Android malware android security hybrid analysis permission and system call pairs

Emission colour tuning in kLnF_(4):Yb^(3+),Er^(3+)/Ho^(3+)phosphor

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Journal of rare Earths 2024年第1期42卷 57-65,I0002页

作者： Janani k Gayathri E Vijayatha V ramasubramanian s Thiyagarajan P Department of science and Humanities Nehru Institute of TechnologyKaliapuramThirumalayampalayamCoimbatoreIndia Department of sciences Amrita School of Physical SciencesAmrita Vishwa VidyapeethamCoimbatoreIndia Department of Physics Anna UniversityChennaiIndia

kLnF_(4):Yb^(3+),Er^(3+)/Ho^(3+)(Ln=Y,Yb,Gd)phosphors were prepared by solid-state reaction *** each of the Yb^(3+)/Er^(3+)and Yb^(3+)/Ho^(3+)co-doped phosphors independently,phase confirmation and morphological examination were accomplished using the X-ray diffraction technique and scanning electron microscope analysis.X-ray photoelectron spectroscopy analysis shows the charge state and existence of lanthanides and *** luminescence emissions of green and red colour were detected for the synthesized *** changes in the upconverted emission intensities and colour output pertaining to the change of the lanthanide host matrix along with dopants were investigated for the prepared *** the upconversion luminescence,erbium-doped samples exhibit a predominance of red emission while holmium-doped samples display a prevalence of green *** rare-earth Er/Ho doped kYbF4shows strong red emission compared to other ***_(4):Yb,Er/Ho exhibits relatively significant green upconve rsion emissions,while Yb,Er-doped kGdF_(4)host displays a 10-fold increase in green/red emission ratio with an increase in the input power of 20-780 *** photoluminescence studies and decay curve analysis were carried out using UV light excitation for the developed phosphors.A higher lifetime of 2.2 ms was measured for the downshifting red emission in the Ho doped kYbF_(4)*** study suggests a potential for colour tunability in the upconversion and downshifting emissions through host modifications to the fluoride phosphor.

关键词： rare earths Energy transfer upconversion Downshifting Colour coordinates

An Efficient Modelling of Oversampling with Optimal Deep Learning Enabled Anomaly Detection in streaming Data

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China Communications 2024年第5期21卷 249-260页

作者： r.rajakumar s.sathiya Devi srinivasa ramanujan Centre SASTRA Deemed UniversityKumbakonamTamil Nadu 612001India University College of Engineering BIT CampusAnna UniversityTiruchirappalli 620024India

recently,anomaly detection(AD)in streaming data gained significant attention among research communities due to its applicability in finance,business,healthcare,education,*** recent developments of deep learning(DL)models find helpful in the detection and classification of *** article designs an oversampling with an optimal deep learning-based streaming data classification(Os-ODLsDC)*** aim of the OsODLsDC model is to recognize and classify the presence of anomalies in the streaming *** proposed Os-ODLsDC model initially undergoes preprocessing *** streaming data is unbalanced,support vector machine(sVM)-synthetic Minority Over-sampling Technique(sVM-sMOTE)is applied for oversampling ***,the Os-ODLsDC model employs bidirectional long short-term memory(Bi LsTM)for AD and ***,the root means square propagation(rMsProp)optimizer is applied for optimal hyperparameter tuning of the Bi LsTM *** ensuring the promising performance of the Os-ODLsDC model,a wide-ranging experimental analysis is performed using three benchmark datasets such as CICIDs 2018,kDD-Cup 1999,and NsL-kDD datasets.

关键词： anomaly detection deep learning hyperparameter optimization oversampling sMOTE streaming data

Effect of solidification cooling rate on microstructure and tribology characteristics of Zn-4si alloy

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International Journal of Minerals,Metallurgy and Materials 2024年第2期31卷 362-373页

作者： F.Akbari M.Golkaram s.Beyrami G.shirazi k.Mantashloo r.Taghiabadi M.saghafi Yazdi I.Ansarian Department of Metallurgy and Material science Imam Khomeini International University(IKIU)Qazvin ***Iran

The main objective of this work was to modify the microstructure and enhance the tribological properties of a new Zn-4si al-loy through a high solidification cooling rate(sCr).According to the results,by increasing the sCr from 2.0 to 59.5℃/s the average size of primary si particles and that of the grains reduced from 76.1 and 3780μm to less than about 14.6 and 460μm,***-ing the sCr also enhanced the microstructural homogeneity,decreased the porosity content(by 50%),and increased the matrix hardness(by 36%).These microstructural changes enhanced the tribological *** instance,under the applied pressure of 0.5 MPa,an in-crease in the sCr from 2.0 to 59.5℃/s decreased the wear rate and the average friction coefficient of the alloy by 57%and 23%,*** wear mechanism was also changed from the severe delamination,adhesion,and abrasion in the slowly-cooled alloy to the mild tribolayer delamination/abrasion in the high-cooling-rate-solidified sample.

关键词： zinc-silicon alloy primary silicon solidification cooling rate tribology sliding wear

Juxtapose of system Performance for Food Calorie Estimation Using IoT and Web-based Indagation

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Journal of Harbin Institute of Technology(New series) 2024年第1期31卷 54-63页

作者： Anusuya s sharmila k Department of Computer science VISTASChennai 600117India Department of Computer science Dr.MGR Janaki College for WomenChennai 600028India

A rudimentary aspect of human life is the health of an individual,and most commonly the wellbeing is impacted in a colossal manner through the consumption of food. The intake of calories therefore is a crucial aspect that must be meticulously monitored. Various health gremlins can be largely circumvented when there is a substantial balance in the number of calories ingested versus the quantity of calories *** food calorie estimation is a popular domain of research in recent times and is meticulously analyzed through various image processing and machine learning techniques. However,the need to scrutinize and evaluate the calorie estimation through various platforms and algorithmic approaches aids in providing a deeper insight on the bottlenecks involved,and in improvising the bariatric health of an individual. This paper pivots on comprehending a juxtaposed approach of food calorie estimation through the use of employing Convolution Neural Network(CNN)incorporated in Internet of Things(IoT),and using the Django framework in Python,along with query rule-based training to analyze the subsequent actions to be followed post the consumption of food calories in the constructed webpage. The comparative analysis of the food calorie estimate implemented in both platforms is analyzed for the swiftness of identification,error rate and classification accuracy to appropriately determine the optimal method of use. The simulation results for IoT are carried out using the raspberry Pi4B model,while the Anaconda prompt is used to run the server holding the web page.

关键词： food calorie estimation convolution neural network Django framework internet of things raspberry Pi

5G resource Allocation Using Feature selection and Greylag Goose Optimization Algorithm

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Computers, Materials & Continua 2024年第7期80卷 1179-1201页

作者： Amel Ali Alhussan s.k.Towfek Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer science and Intelligent systems research Center BlacksburgVA 24060USA

In the contemporary world of highly efficient technological development,fifth-generation technology(5G)is seen as a vital step forward with theoretical maximum download speeds of up to twenty gigabits per second(Gbps).As far as the current implementations are concerned,they are at the level of slightly below 1 Gbps,but this allowed a great leap forward from fourth generation technology(4G),as well as enabling significantly reduced latency,making 5G an absolute necessity for applications such as gaming,virtual conferencing,and other interactive electronic *** of this change are not limited to connectivity alone;it urges operators to refine their business strategies and offers users better and improved digital *** essential factor is optimization and the application of artificial intelligence throughout the general arrangement of intricate and detailed 5G *** Binary Greylag Goose Optimization(bGGO)to achieve a significant reduction in the feature set while maintaining or improving model performance,leading to more efficient and effective 5G network management,and Greylag Goose Optimization(GGO)increases the efficiency of the machine ***,the model performs and yields more accurate *** work proposes a new method to schedule the resources in the next generation,5G,based on a feature selection using GGO and a regression model that is an ensemble of k-Nearest Neighbors(kNN),Gradient Boosting,and Extra Trees *** ensemble model shows better prediction performance with the coefficient of determination r squared value equal *** proposed framework is supported by several statistical analyses,such as theWilcoxon signed-rank *** of the benefits of this study are the introduction of new efficient optimization algorithms,the selection of features and more reliable ensemble models which improve the efficiency of 5G technology.

关键词： Optimization ensemble learning 5G technology artificial intelligence greylag goose optimization ANOVA test

A Novel Approach to Breast Tumor Detection: Enhanced speckle reduction and Hybrid Classification in Ultrasound Imaging

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Computers, Materials & Continua 2024年第5期79卷 1875-1901页

作者： k.Umapathi s.shobana Anand Nayyar Judith Justin r.Vanithamani Miguel Villagómez Galindo Mushtaq Ahmad Ansari Hitesh Panchal Department of Biomedical Engineering KIT-Kalaignarkarunanidhi Institute of TechnologyCoimbatore641402India Graduate school Faculty of Information TechnologyDuy Tan UniversityDa Nang550000Viet Nam Department of Biomedical and Instrumentation Engineering Avinashilingam Institute for Home Science and Higher Education forWomenCoimbatore641043India UniversidadMichoacana de sanNicolás de HidalgoAvenida Francisco J.Múgica s/N Ciudad Universitaria MoreliaCP58030Mexico Department of Pharmacology and Toxicology College of PharmacyKing Saud UniversityRiyadh11451Saudi Arabia Department of Mechanical Engineering Gujarat Technological UniveristyNigam NagarChandkhedaAhmedabadGujarat382424India

Breast cancer detection heavily relies on medical imaging, particularly ultrasound, for early diagnosis and effectivetreatment. This research addresses the challenges associated with computer-aided diagnosis (CAD) of breastcancer fromultrasound images. The primary challenge is accurately distinguishing between malignant and benigntumors, complicated by factors such as speckle noise, variable image quality, and the need for precise segmentationand classification. The main objective of the research paper is to develop an advanced methodology for breastultrasound image classification, focusing on speckle noise reduction, precise segmentation, feature extraction, andmachine learning-based classification. A unique approach is introduced that combines Enhanced speckle reducedAnisotropic Diffusion (srAD) filters for speckle noise reduction, U-NET-based segmentation, Genetic Algorithm(GA)-based feature selection, and random Forest and Bagging Tree classifiers, resulting in a novel and efficientmodel. To test and validate the hybrid model, rigorous experimentations were performed and results state thatthe proposed hybrid model achieved accuracy rate of 99.9%, outperforming other existing techniques, and alsosignificantly reducing computational time. This enhanced accuracy, along with improved sensitivity and specificity,makes the proposed hybrid model a valuable addition to CAD systems in breast cancer diagnosis, ultimatelyenhancing diagnostic accuracy in clinical applications.

关键词： Ultrasound images breast cancer tumor classification segmentation deep learning lesion detection

Predictive active control of building structures using LQr and artificial intelligence

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Earthquake Engineering and Engineering Vibration 2024年第2期23卷 489-502页

作者： Nirmal s.Mehta Vishisht Bhaiya k.A.Patel Ehsan Noroozinejad Farsangi Department of Civil Engineering SVNIT SuratGujarat 395007India Urban Transformations research Centre Western Sydney UniversityNSWAustralia

This study presents a neural network-based model for predicting linear quadratic regulator(LQr)weighting matrices for achieving a target response *** on the expected weighting matrices,the LQr algorithm is used to determine the various responses of the *** responses are determined by numerically analyzing the governing equation of motion using the state-space *** training a neural network,four input parameters are considered:the time history of the ground motion,the percentage reduction in lateral displacement,lateral velocity,and lateral acceleration,Output parameters are LQr weighting *** study the effectiveness of an LQr-based neural network(LQrNN),the actual percentage reduction in the responses obtained from using LQrNN is compared with the target percentage ***,to investigate the efficacy of an active control system using LQrNN,the controlled responses of a system are compared to the corresponding uncontrolled *** trained neural network effectively predicts weighting parameters that can provide a percentage reduction in displacement,velocity,and acceleration close to the target percentage *** on the simulation study,it can be concluded that significant response reductions are observed in the active-controlled system using ***,the LQrNN algorithm can replace conventional LQr control with the use of an active control system.

关键词： active control system linear quadratic regulator artificial neural networks state-space approach response effectiveness factor resilience

Influence of erbium on structural,and charged particles,photons,and neutrons shielding properties of Ba_(1-x)Er_(x)snO_(3) perovskite ceramics

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Journal of rare Earths 2024年第4期42卷 724-732页

作者： M.k.h.Hamad Nidal Dwaikat M.H.A.Mhareb M.I.sayyed r.M.Hamad Y.s.M.Alajerami M.A.Almessiere Gameel saleh Ahmad Hussein Alomari k.A.Ziq Department of Basic sciences School of Social and Basics SciencesAl Hussein Technical UniversityKing Abdullah II St 242Amman11831Jordan Department of Physics College of Engineering and PhysicsInterdisciplinary Research Center for Advanced MaterialsKing Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia Department of Physics College of ScienceImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Basic and Applied scientific research Center Imam Abdulrahman Bin Faisal UniversityP0.Box 1982Dammam31441Saudi Arabia Department of Physics Faculty of ScienceIsra UniversityAmman11622Jordan Department of Nuclear Medicine research Institute for Research and Medical Consultations(IRMC)Imam Abdulrahman Bin Faisal UniversityPo.Box 1982Dammam31441Saudi Arabia Medical Imaging Department Applied Medical Sciences FacultyAl Azhar University-Gaza CityPo.Box 1277Palestine Department of Biophysics Institute for Research and Medical Consultations(IRMC)Imam Abdulrahman Bin Faisal UniversityPo.Box1982Dammam 31441Saudi Arabia Department of Biomedical Engineering College of EngineeringImam Abdulrahman Bin Faisal UniversityPo.Box 1982Dammam31441Saudi Energy&Minerals regulatory Commission Amman11821Jordan

Five perovskite ceramics samples of Ba_(1-x)Er_(x)snO_(3) with x=0.00,0.05,0.10,0.15,and 0.20 were synthesized using the conventional solid-state reaction *** prepared samples were characterized by X-ray diffraction(XrD),Fourier transforms infrared(FTIr),and UV-Vis *** shielding properties against ionizing radiation were also *** XrD analysis shows the perovskite cubic structure as the major phase in all *** FTIr reveals a distinctive band around 614-620 cm^(-1) ascribed to the antisymmetric O-sn-O ***-Vis spectroscopy was used to determine the bandgap according to diffuse reflectance,and the results display a fixed enhancement in the bandgap from 3.2 to 3.3 eV for all ***-ray shielding properties of the synthesized samples were experimentally measured and compared with XCOM computational *** relative differences(Δ,%)between experimental and theo retical values are low and fall within the 0.446%-7.10%*** addition of Er leads to the enhanced density,neutron,and gamma shielding *** contrast,charged particles’shielding parameters gradually reduce with rising Er *** results suggest that Ba_(1-x)Er_(x)snO_(3) samples can be used in different radiation shielding applications.

关键词： Perovskite Ceramics Gamma ray shielding Mass stopping power rare earths