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Suboptimal Feature Selection Techniques for Effective Malicious Traffic Detection on Lightweight Devices

Computer Modeling in Engineering & Sciences 2024年第8期140卷 1669-1687页

作者： So-Eun Jeon Ye-Sol Oh Yeon-Ji Lee Il-Gu Lee department of Future Convergence Technology Engineering Sungshin Women’s UniversitySeoul02844Korea department of Convergence Security Engineering SungshinWomen’s UniversitySeoul02844Korea

With the advancement of wireless network technology,vast amounts of traffic have been generated,and malicious traffic attacks that threaten the network environment are becoming increasingly *** signature-based detection methods,static analysis,and dynamic analysis techniques have been previously explored for malicious traffic detection,they have limitations in identifying diversified malware traffic *** research has been focused on the application of machine learning to detect these ***,applying machine learning to lightweight devices like IoT devices is challenging because of the high computational demands and complexity involved in the learning *** this study,we examined methods for effectively utilizing machine learning-based malicious traffic detection approaches for lightweight *** introduced the suboptimal feature selection model(SFSM),a feature selection technique designed to reduce complexity while maintaining the effectiveness of malicious traffic *** performance was evaluated on various malicious traffic,benign,exploits,and generic,using the UNSW-NB15 dataset and SFSM sub-optimized hyperparameters for feature selection and narrowed the search scope to encompass all *** improved learning performance while minimizing complexity by considering feature selection and exhaustive search as two steps,a problem not considered in conventional *** experimental results showed that the detection accuracy was improved by approximately 20%compared to the random model,and the reduction in accuracy compared to the greedy model,which performs an exhaustive search on all features,was kept within 6%.Additionally,latency and complexity were reduced by approximately 96%and 99.78%,respectively,compared to the greedy *** study demonstrates that malicious traffic can be effectively detected even in lightweight device *** verified the possibility of detecting various attack

关键词： Feature selection lightweight device machine learning Internet of Things malicious traffic

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Vertical plane depth-resolved surface potential and carrier separation characteristics in flexible CZTSSe solar cells with over 12% efficiency

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Carbon Energy 2024年第3期6卷 36-52页

作者： Dae-Ho Son Ha Kyung Park Dae-Hwan Kim Jin-Kyu Kang Shi-Joon Sung Dae-Kue Hwang Jaebaek Lee Dong-Hwan Jeon Yunae Cho William Jo Taeseon Lee JunHo Kim Sang-Hoon Nam Kee-Jeong Yang Division of Energy Technology DGISTDaeguRepublic of Korea Research Center for Thin Film Solar Cells DGISTDaeguRepublic of Korea department of Physics Ewha Womans UniversitySeoulRepublic of Korea department of Physics Incheon National UniversityIncheonRepublic of Korea department of Mechanical Engineering Massachusetts Institute of TechnologyCambridgeMassachusettsUSA

Cu2ZnSn(S,Se)4(CZTSSe)solar cells have resource distribution and economic *** main cause of their low efficiency is carrier loss resulting from recombination of photo-generated electron and *** overcome this,it is important to understand their electron-hole behavior *** determine the carrier separation characteristics,we measured the surface potential and the local current in terms of the absorber *** elemental variation in the intragrains(IGs)and at the grain boundaries(GBs)caused a band edge shift and bandgap(Eg)*** the absorber surface and subsurface,an upward Ec and Ev band bending structure was observed at the GBs,and the carrier separation was *** the absorber center,both upward Ec and Ev and downward Ec-upward Ev band bending structures were observed at the GBs,and the carrier separation was *** improve the carrier separation and suppress carrier recombination,an upward Ec and Ev band bending structure at the GBs is desirable.

关键词： carrier separation CZTSSe flexible solar cell local current surface potential

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Efficient Object Segmentation and Recognition Using Multi-Layer Perceptron Networks

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Computers, Materials & Continua 2024年第1期78卷 1381-1398页

作者： Aysha Naseer Nouf Abdullah Almujally Saud S.Alotaibi Abdulwahab Alazeb Jeongmin Park department of Computer Science Air UniversityIslamabad44000Pakistan department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Information System department Umm Al-Qura UniversityMakkahSaudi Arabia department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Object segmentation and recognition is an imperative area of computer vision andmachine learning that identifies and separates individual objects within an image or video and determines classes or categories based on their *** proposed system presents a distinctive approach to object segmentation and recognition using Artificial Neural Networks(ANNs).The system takes RGB images as input and uses a k-means clustering-based segmentation technique to fragment the intended parts of the images into different regions and label thembased on their ***,two distinct kinds of features are obtained from the segmented images to help identify the objects of *** Artificial Neural Network(ANN)is then used to recognize the objects based on their *** were carried out with three standard datasets,MSRC,MS COCO,and Caltech 101 which are extensively used in object recognition research,to measure the productivity of the suggested *** findings from the experiment support the suggested system’s validity,as it achieved class recognition accuracies of 89%,83%,and 90.30% on the MSRC,MS COCO,and Caltech 101 datasets,respectively.

关键词： K-region fusion segmentation recognition feature extraction artificial neural network computer vision

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Realizing High Thermoelectric Performance in n-Type Se-Free Bi2Te3 Materials by Spontaneous Incorporation of FeTe2 Nanoinclusions

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Energy & Environmental Materials 2024年第4期7卷 344-354页

作者： Jamil Ur Rahman Woo Hyun Nam Yong-Jae Jung Jong Ho Won Jong-Min Oh Nguyen Van Du Gul Rahman Víctor M.García-Suárez Ran He Kornelius Nielsch Jung Young Cho Won-Seon Seo Jong Wook Roh Sang-il Kim Soonil Lee Kyu Hyoung Lee Hyun Sik Kim Weon Ho Shin Leibniz Institute for Solid State and Materials Research Advanced Materials Convergence R&D Division Korea Institute of Ceramic Engineering & Technology department of Electronic Materials Engineering Kwangwoon University department of Energy Engineering Dankook University Faculty of Fundamental Science Phenikaa University department of Physics Quaid-i-Azam University Departamento de Física Universidad de Oviedo Nanomaterials and Nanotechnology Research Center-CINN department of Materials Science and Engineering Yonsei University School of Nano & Materials Science and Engineering Kyungpook National University department of Materials Science and Engineering University of Seoul School of Materials Science and Engineering Changwon National University

Bi2Te3-based materials have drawn much attention from the thermoelectric community due to their excellent thermoelectric performance near room ***,the stability of existing n-type Bi2（Te,Se）3materials is still low due to the evaporation energy of Se (37.70 kJ mol-1) being much lower than that of Te (52.55 kJ mol-1).The evaporated Se from the material causes problems in interconnects of the module while degrading the efficiency.

关键词： Bi2Te3 energy harvesting FeTe2 nanoinclusion n-type materials thermoelectric

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UNet Based onMulti-Object Segmentation and Convolution Neural Network for Object Recognition

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Computers, Materials & Continua 2024年第7期80卷 1563-1580页

作者： Nouf Abdullah Almujally Bisma Riaz Chughtai Naif Al Mudawi Abdulwahab Alazeb Asaad Algarni Hamdan A.Alzahrani Jeongmin Park department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of Computer Science Air UniversityIslamabad44000Pakistan department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Information Technology department College of Computing and InformaticsSaudi Electronic UniversityRiyadh13316Saudi Arabia department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Republic of Korea

The recent advancements in vision technology have had a significant impact on our ability to identify multiple objects and understand complex *** technologies,such as augmented reality-driven scene integration,robotic navigation,autonomous driving,and guided tour systems,heavily rely on this type of scene *** paper presents a novel segmentation approach based on the UNet network model,aimed at recognizing multiple objects within an *** methodology begins with the acquisition and preprocessing of the image,followed by segmentation using the fine-tuned UNet ***,we use an annotation tool to accurately label the segmented *** labeling,significant features are extracted from these segmented objects,encompassing KAZE(Accelerated Segmentation and Extraction)features,energy-based edge detection,frequency-based,and blob *** the classification stage,a convolution neural network(CNN)is *** comprehensive methodology demonstrates a robust framework for achieving accurate and efficient recognition of multiple objects in *** experimental results,which include complex object datasets like MSRC-v2 and PASCAL-VOC12,have been *** analyzing the experimental results,it was found that the PASCAL-VOC12 dataset achieved an accuracy rate of 95%,while the MSRC-v2 dataset achieved an accuracy of 89%.The evaluation performed on these diverse datasets highlights a notably impressive level of performance.

关键词： UNet segmentation blob fourier transform convolution neural network

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Prediction of Damping Capacity Demand in Seismic Base Isolators via Machine Learning

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2899-2924页

作者： Ayla Ocak Umit Isıkdag Gebrail Bekdas Sinan Melih Nigdeli Sanghun Kim ZongWoo Geem department of Civil Engineering Istanbul University-CerrahpasaIstanbul34320Turkey department of Informatics Mimar Sinan Fine Arts UniversityIstanbul34427Turkey department of Civil and Environmental Engineering Temple UniversityPhiladelphiaPA19122USA department of Smart City Gachon UniversitySeongnam13120Korea

Base isolators used in buildings provide both a good acceleration reduction and structural vibration control *** base isolators may lose their damping capacity over time due to environmental or dynamic *** deterioration of them requires the determination of the maintenance and repair needs and is important for the long-termisolator *** this study,an artificial intelligence prediction model has been developed to determine the damage and maintenance-repair requirements of isolators as a result of environmental effects and dynamic factors over *** the developed model,the required damping capacity of the isolator structure was estimated and compared with the previously placed isolator capacity,and the decrease in the damping property was tried to be *** this purpose,a data set was created by collecting the behavior of structures with single degrees of freedom(SDOF),different stiffness,damping ratio and natural period isolated from the foundation under far fault *** data is divided into 5 different damping classes varying between 10%and 50%.Machine learning model was trained in damping classes with the data on the structure’s response to random seismic *** a result of the isolator behavior under randomly selected earthquakes,the recorded motion and structural acceleration of the structure against any seismic vibration were examined,and the decrease in the damping capacity was estimated on a class *** performance loss of the isolators,which are separated according to their damping properties,has been tried to be determined,and the reductions in the amounts to be taken into account have been determined by *** the developed prediction model,using various supervised machine learning classification algorithms,the classification algorithm providing the highest precision for the model has been *** the results are examined,it has been determined that the damping of the isolator structure with the

关键词： Vibration control base isolation machine learning damping capacity

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M1-polarized macrophage-derived cellular nanovesicle-coated lipid nanoparticles for enhanced cancer treatment through hybridization of gene therapy and cancer immunotherapy

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Acta Pharmaceutica Sinica B 2024年第7期14卷 3169-3183页

作者： Ha Eun Shin Jun-Hyeok Han Seungyong Shin Ga-Hyun Bae Boram Son Tae-Hyung Kim Hee Ho Park Chun Gwon Park Wooram Park department of Integrative Biotechnology Sungkyunkwan University(SKKU)SuwonGyeonggi 16419Republic of Korea Deparment of Inteligent Precision Healthcare Convergence SKKUSuwonGyeonggi 16419Republic of Korea department of MetaBioHealth SKKU Institute for ConvergenceSKKUSuwonGyeonggi 16419Republic of Korea department of Bioengineering Hanyang UniversitySeoul 04763Republic of Korea department of Integrative Engineering Chung-Ang UniversitySeoul 06974Republic of Korea department of Biomedical Engineering SKKUSuwonGyeonggi 16419Republic of Korea Korea Institute of Science and Technology(KIST) Seoul 02792Republic of Korea

Optimum genetic delivery for modulating target genes to diseased tissue is a major obstacle for profitable gene *** nanoparticles(LNPs),considered a prospective vehicle for nucleic acid delivery,have demonstrated efficacy in human use during the COVID-19 *** study introduces a novel biomaterial-based platform,M1-polarized macrophage-derived cellular nanovesicle-coated LNPs(M1-C-LNPs),specifically engineered for a combined gene-immunotherapy approach against solid *** dual-function system of M1-C-LNPs encapsulates Bcl2-targeting siRNA within LNPs and immune-modulating cytokines within M1 macrophage-derived cellular nanovesicles(M1-NVs),effectively facilitating apoptosis in cancer cells without impacting T and NK cells,which activate the intratumoral immune response to promote granule-mediating killing for solid tumor *** retention within tumor was observed upon intratumoral administration of M1-C-LNPs,owing to the presence of adhesion molecules on M1-NVs,thereby contributing to superior tumor growth *** findings represent a promising strategy for the development of targeted and effective nanoparticle-based cancer genetic-immunotherapy,with significant implications for advancing biomaterial use in cancer therapeutics.

关键词： Genetic-immunotherapy M1 macrophage-derived cellular nanovesicles Lipid nanoparticles(LNPs) Gene therapy siRNA Cancer immunotherapy Solid tumor Tumor microenvironment(TME)

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Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

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Computers, Materials & Continua 2024年第3期78卷 3683-3701页

作者： Asifa Mehmood Qureshi Naif Al Mudawi Mohammed Alonazi Samia Allaoua Chelloug Jeongmin Park department of Creative Technologies Air UniversityIslamabad46000Pakistan department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Road traffic monitoring is an imperative topic widely discussed among *** used to monitor traffic frequently rely on cameras mounted on bridges or ***,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger *** this end,different models have shown the ability to recognize and track ***,these methods are not mature enough to produce accurate results in complex road ***,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image *** extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the *** masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring ***,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise *** preprocessing,the blob detection algorithm helped detect the *** of varying sizes have been detected by implementing a dynamic thresholding *** was done on the first image of every ***,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching *** further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple *** accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been *** the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

关键词： Unmanned Aerial Vehicles(UAV) aerial images dataset object detection object tracking data elimination template matching blob detection SIFT VAID

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Erythrocytes serve as a template to create nanozymes with uniform Fe single-atom sites for healing bacteria-infected wound

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Science China(Life Sciences) 2024年第9期67卷 2048-2050页

作者： Thinh Viet Dang Moon Il Kim department of BioNano Technology Gachon UniversitySeongnam 13120Republic of Korea

Bacterial infection is recognized as one of the biggest global health threats,causing millions of people's death every year(Wang et al.,2020).Traditional antibiotics-based therapies have been widely utilized to control this issue(Kohanski et al.,2010);however,their excessive use leads to the emergence of antibioticresistant bacteria,endangering to human health(Levy and Marshall,2004).

关键词： template healing utilized

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Intelligent reflecting surface for sum rate enhancement in MIMO systems

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Digital Communications and Networks 2024年第1期10卷 94-100页

作者： Chan-Yeob Park Ji-Sung Jung Yeong-Rong Lee Beom-Sik Shin Hyoung-Kyu Song department of Information and Communication Engineering Sejong UniversitySeoulGwangjin-guGunja-dong 98Republic of Korea department of Convergence Engineering for Intelligent Drone Sejong University SeoulGwangjin-guGunja-dong 98Republic of Korea

The research for the Intelligent Reflecting Surface(IRS)which has the advantages of cost and energy efficiency has been *** capacity can be effectively increased by appropriately setting the phase value of IRS elements according to the channel ***,the problem of obtaining an appropriate phase value of IRs is difficult to solve due to the non-convex *** paper proposes an iterative algorithm for the alternating optimal solution in the Single User Multiple-Input-Multiple-Output(SU-MIMO)*** proposed iterative algorithm finds an alternating optimal solution that is the phase value of IRS one by *** results show that the proposed method has better performance than that of the randomized IRS *** number of iterations for maximizing the performance of the proposed algorithm depends on the channel state between the IRS and the receiver.

关键词： Intelligent reflecting surface MIMO Sum rate

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