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Cross-Domain Bilateral Access Control on Blockchain-Cloud Based Data Trading System

Computer Modeling in Engineering & Sciences 2024年第10期141卷 671-688页

作者： Youngho Park Su Jin Shin Sang Uk Shin Electronics and information Communications research Center Pukyong National UniversityBusan48513Republic of Korea Department of information Security Graduate SchoolPukyong National UniversityBusan48513Republic of Korea Division of Computer Engineering Pukyong National UniversityBusan48513Republic of Korea

Data trading enables data owners and data requesters to sell and purchase *** the emergence of blockchain technology,research on blockchain-based data trading systems is receiving a lot of ***,to reduce the on-chain storage cost,a novel paradigm of blockchain and cloud fusion has been widely considered as a promising data trading ***,the fact that data can be used for commercial purposes will encourage users and organizations from various fields to participate in the data *** the data marketplace,it is a challenge how to trade the data securely outsourced to the external cloud in a way that restricts access to the data only to authorized users across multiple *** this paper,we propose a cross-domain bilateral access control protocol for blockchain-cloud based data trading *** consider a system model that consists of domain authorities,data senders,data receivers,a blockchain layer,and a cloud *** proposed protocol enables access control and source identification of the outsourced data by leveraging identity-based cryptographic *** the proposed protocol,the outsourced data of the sender is encrypted under the target receiver’s identity,and the cloud provider performs policy-match verification on the authorization tags of the sender and receiver generated by the identity-based signature ***,data trading can be achieved only if the identities of the data sender and receiver simultaneously meet the policies specified by each *** demonstrate efficiency,we evaluate the performance of the proposed protocol and compare it with existing studies.

关键词： Bilateral access control blockchain data sharing policy-match

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Novel Rifle Number Recognition Based on Improved YOLO in Military Environment

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Computers, Materials & Continua 2024年第1期78卷 249-263页

作者： Hyun Kwon Sanghyun Lee Department of Artificial Intelligence and Data Science Korea Military AcademySeoulKorea Graduate School of information Security Korea Advanced Institute of Science and TechnologyDaejeonKorea

Deep neural networks perform well in image recognition,object recognition,pattern analysis,and speech *** military applications,deep neural networks can detect equipment and recognize *** military equipment,it is necessary to detect and recognize rifle management,which is an important piece of equipment,using deep neural *** have been no previous studies on the detection of real rifle numbers using real rifle image *** this study,we propose a method for detecting and recognizing rifle numbers when rifle image data are *** proposed method was designed to improve the recognition rate of a specific dataset using data fusion and transfer *** the proposed method,real rifle images and existing digit images are fusedas trainingdata,andthe final layer is transferredto theYolov5 *** detectionand recognition performance of rifle numbers was improved and analyzed using rifle image and numerical *** used actual rifle image data(K-2 rifle)and numeric image datasets,as an experimental *** was used as the machine learning *** results show that the proposed method maintains 84.42% accuracy,73.54% precision,81.81% recall,and 77.46% F1-score in detecting and recognizing rifle *** proposed method is effective in detecting rifle numbers.

关键词： Machine learning deep neural network rifle number recognition detection

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Systematic Security Guideline Framework through Intelligently Automated Vulnerability Analysis

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Computers, Materials & Continua 2024年第3期78卷 3867-3889页

作者： Dahyeon Kim Namgi Kim Junho Ahn Computer information Technology Korea National University of TransportationChungju27469Korea Department of AI Computer Science and Engineering Kyonggi UniversitySuwon16227Korea

This research aims to propose a practical framework designed for the automatic analysis of a product’s comprehensive functionality and security vulnerabilities,generating applicable guidelines based on real-world *** existing analysis of software security vulnerabilities often focuses on specific features or *** partial and arbitrary analysis of the security vulnerabilities makes it challenging to comprehend the overall security vulnerabilities of the *** key novelty lies in overcoming the constraints of partial *** proposed framework utilizes data from various sources to create a comprehensive functionality profile,facilitating the derivation of real-world security *** guidelines are dynamically generated by associating functional security vulnerabilities with the latest Common Vulnerabilities and Exposure(CVE)and Common Vulnerability Scoring System(CVSS)scores,resulting in automated guidelines tailored to each *** guidelines are not only practical but also applicable in real-world software,allowing for prioritized security *** proposed framework is applied to virtual private network(VPN)software,wherein a validated Level 2 data flow diagram is generated using the Spoofing,Tampering,Repudiation,information Disclosure,Denial of service,and Elevation of privilege(STRIDE)technique with references to various papers and examples from related *** analysis resulted in the identification of a total of 121 *** successful implementation and validation demonstrate the framework’s efficacy in generating customized guidelines for entire systems,subsystems,and selected modules.

关键词： Framework automation vulnerability analysis security guidelines

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YOLO-Based Damage Detection with StyleGAN3 Data Augmentation for Parcel information-Recognition System

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Computers, Materials & Continua 2024年第7期80卷 195-215页

作者： Seolhee Kim Sang-Duck Lee Department of Electrical and Computer Engineering Sungkyunkwan UniversitySuwon16419Republic of Korea Logistics System research Division Korea Railroad Research InstituteUiwang16105Republic of Korea

Damage to parcels reduces customer satisfactionwith delivery services and increases return-logistics *** can be prevented by detecting and addressing the damage before the parcels reach the ***,various studies have been conducted on deep learning techniques related to the detection of parcel *** study proposes a deep learning-based damage detectionmethod for various types of *** is intended to be part of a parcel information-recognition systemthat identifies the volume and shipping information of parcels,and determines whether they are damaged;this method is intended for use in the actual parcel-transportation *** this purpose,1)the study acquired image data in an environment simulating the actual parcel-transportation process,and 2)the training dataset was expanded based on StyleGAN3 with adaptive discriminator ***,3)a preliminary distinction was made between the appearance of parcels and their damage status to enhance the performance of the parcel damage detection model and analyze the causes of parcel ***,using the dataset constructed based on the proposed method,a damage type detection model was trained,and its mean average precision was *** model can improve customer satisfaction and reduce return costs for parcel delivery companies.

关键词： Parcel delivery service damage detection damage classification data augmentation generative adversarial network

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A Hybrid Deep Learning and Machine Learning-Based Approach to Classify Defects in Hot Rolled Steel Strips for Smart Manufacturing

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Computers, Materials & Continua 2024年第8期80卷 2099-2119页

作者： Tajmal Hussain Jungpyo Hong Jongwon Seok Department of information and Communication Engineering Changwon National UniversityChangwon51140Republic of Korea

Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things(IoT)and artificial intelligence(AI).Quality control is an important part of today’s smart manufacturing process,effectively reducing costs and enhancing operational *** technology in the industry becomes more advanced,identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing *** this study,we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques,incorporating a global average pooling(GAP)layer and a machine learning-based SVM classifier,with the aim of enhancing ***,features are extracted by the VGG19 convolutional ***,after processing through the GAP layer,the extracted features are fed to the SVM classifier for *** this purpose,we collected images from publicly available datasets,including the Xsteel surface defect dataset(XSDD)and the NEU surface defect(NEU-CLS)datasets,and we employed offline data augmentation techniques to balance and increase the size of the *** outcome of experiments shows that the proposed methodology achieves the highest metrics score,with 99.79%accuracy,99.80%precision,99.79%recall,and a 99.79%F1-score for the NEU-CLS ***,it achieves 99.64%accuracy,99.65%precision,99.63%recall,and a 99.64%F1-score for the XSDD dataset.A comparison of the proposed methodology to the most recent study showed that it achieved superior results as compared to the other studies.

关键词： Smart manufacturing steel defect detection deep learning CNN

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Construction of daily precipitation series and the observational characteristics of extreme precipitation in Tianjin,China during 1888-2022

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Advances in Climate Change research 2024年第1期15卷 52-61页

作者： Peng SI Qing-Xiang LI Xiao-Yang CHEN Min WANG Chuan-Jun LUO Tianjin Meteorological information Center Tianjin Meteorological BureauTianjin 300074China research Centerfor Ecology and Environment of Central Asia Chinese Academy of SciencesWulumuqi 830011China School of Atmospheric Sciences Sun Yat-sen UniversityZhuhai 528478China Key Laboratory of Tropical Amosphere-Ocean System Ministry of EducationZhuhai 528478China Shaoguan Meteorological service Shaoguan 512028China

Given the difficulties in rescuing and ensuring the quality of long-term climate data,current studies on century-scale climate change are usually limited to annual and monthly data,resulting in the poor detection of extreme climate events and their changes before *** this study,we reconstructed a daily precipitation series for Tianjin from 15 September 1887 to 31 December 2022 on the basis of the most comprehensive daily precipitation records collected from the Tianjin Meteorological Archive,China,and in reference to the precipitation analysis results based on the datasets developed by the Climatic research Unit Time-Series version 4.06,Global Precipitation Climatology Centre and University of Delaware along with the application of various homogenisation methods for climate *** approach provides a complete and reliable century-long daily precipitation series for the study of regional or local extreme weather and climate *** reconstructed daily dataset reveals that the annual precipitation amount and R95 intensity in Tianjin during 1888-2022 lack significant trends and have values of 0.74±6.99 and-1.84±3.22 mm per decade,*** the annual and seasonal scales,the precipitation amount and R95 intensity,particularly those in autumn,have increased since the latter half of the 20th century relative to those in ***,the increase in precipitation amount and R95 intensity is relatively limited compared with that in atmospheric water vapour content due to surface warming,indicating the highly sensitive response of extreme precipitation events to *** addition,the estimates for the return periods of 5,10,20,50 and 100 years covering 1888-2022,1888-1950 and 1951-2022 depict that the intensity of heavy rain and above magnitude was highest in 1888-1950 and decreased in 1951-2022.

关键词： Over a century-long timescale Daily precipitation series Extreme precipitation Return period

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Lightweight Super-Resolution Model for Complete Model Copyright Protection

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Tsinghua Science and Technology 2024年第4期29卷 1194-1205页

作者： Bingyi Xie Honghui Xu YongJoon Joe Daehee Seo Zhipeng Cai Department of Computer Science Georgia State UniversityAtlantaGA 30303USA LSWare Inc. Seoul 08504Republic of Korea College of Intelligence information Engineering Sangmyung UniversityRepublic of KoreaSeoul 03016

Deep learning based techniques are broadly used in various applications, which exhibit superior performance compared to traditional methods. One of the mainstream topics in computer vision is the image super-resolution task. In recent deep learning neural networks, the number of parameters in each convolution layer has increased along with more layers and feature maps, resulting in better image super-resolution performance. In today’s era, numerous service providers offer super-resolution services to users, providing them with remarkable convenience. However, the availability of open-source super-resolution services exposes service providers to the risk of copyright infringement, as the complete model could be vulnerable to leakage. Therefore, safeguarding the copyright of the complete model is a non-trivial concern. To tackle this issue, this paper presents a lightweight model as a substitute for the original complete model in image super-resolution. This research has identified smaller networks that can deliver impressive performance, while protecting the original model’s copyright. Finally, comprehensive experiments are conducted on multiple datasets to demonstrate the superiority of the proposed approach in generating super-resolution images even using lightweight neural networks.

关键词： lightweight adversarial learning image super-resolution copyright protection

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Tailoring MXene Thickness and Functionalization for Enhanced Room‑Temperature Trace NO_(2) Sensing

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Nano-Micro Letters 2024年第5期16卷 71-86页

作者： Muhammad Hilal Woochul Yang Yongha Hwang Wanfeng Xie Department of Physics Dongguk UniversitySeoul 04620Republic of Korea Department of Control and Instrumentation Engineering Korea UniversitySejong 30019Republic of Korea School of Electronics&information University‑Industry Joint Center for Ocean Observation and Broadband CommunicationQingdao UniversityQingdao 266071China

In this study,precise control over the thickness and termination of Ti3C2TX MXene flakes is achieved to enhance their electrical properties,environmental stability,and gas-sensing *** a hybrid method involving high-pressure processing,stirring,and immiscible solutions,sub-100 nm MXene flake thickness is achieved within the MXene film on the *** control is achieved by defunctionalizing MXene at 650℃ under vacuum and H2 gas in a CVD furnace,followed by refunctionalization with iodine and bromine vaporization from a bubbler attached to the ***,the introduction of iodine,which has a larger atomic size,lower electronegativity,reduce shielding effect,and lower hydrophilicity(contact angle:99°),profoundly affecting *** improves the surface area(36.2 cm^(2) g^(-1)),oxidation stability in aqueous/ambient environments(21 days/80 days),and film conductivity(749 S m^(-1)).Additionally,it significantly enhances the gas-sensing performance,including the sensitivity(0.1119Ωppm^(-1)),response(0.2% and 23%to 50 ppb and 200 ppm NO_(2)),and response/recovery times(90/100 s).The reduced shielding effect of the–I-terminals and the metallic characteristics of MXene enhance the selectivity of I-MXene toward *** approach paves the way for the development of stable and high-performance gas-sensing two-dimensional materials with promising prospects for future studies.

关键词： Controlled MXene thickness Gaseous functionalization approach Lower electronegativity functional groups Enhanced MXene stability Trace NO_(2)sensing

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Analysis of the effect of the 2021 Semeru eruption on water vapor content and atmospheric particles using GNSS and remote sensing

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Geodesy and Geodynamics 2024年第1期15卷 33-41页

作者： Mokhamad Nur Cahyadi Arizal Bawasir Syachrul Arief Amien Widodo Meifal Rusli Deni Kusumawardani Yessi Rahmawati Ana Martina Putra Maulida Hilda Lestiana Department of Geomatics Engineering Institut Teknologi Sepuluh NopemberSurabaya 60111Indonesia research Center of Marine and Earth Science-Technology Directorate of Research and Community ServiceInstitut Teknologi Sepuluh NopemberSurabaya 60111Indonesia Geospatial education and Training Division Geospatial Information Agency(BIG)Cibinong 16911Indonesia Department of Geophysics Engineering Institut Teknologi Sepuluh NopemberSurabaya 60111Indonesia Department of Mechanical Engineering Andalas UniversityPadang City 25175Indonesia Department of Economics Airlangga UniversitySurabaya 60286Indonesia research Center for Geological Resources National Research and Innovation AgencyJakarta 10340Indonesia

Mount Semeru,an active volcano in East Java,Indonesia,erupted on December 4,2021,following extreme rainfall that caused an avalanche of hot pyroclastic flows and *** tropospheric conditions and dominant particle components in the atmosphere can be monitored using Global Navigation Satellite System(GNSS)technology and remote sensing *** signal propagation delay in Precise Point Positioning(PPP)processing can be used to determine Zenith Tropospheric Delay(ZTD)and Precipitable Water Vapor(PWV)variables so that atmospheric conditions can be *** addition,by using remote sensing satellite data,it is possible to obtain rainfall data with high temporal resolution as well as the dominant particle and gas content values during *** the eruption period,the high value of PWV was dominated by the high intensity of precipitation during the rainy *** rainfall before the eruption caused activity inside the mountain to increase,which occurred in avalanche type *** from that,the atmosphere around Semeru was also dominated by SO_(2)content,which spreaded for tens of ***_(2)content began to be detected significantly by remote sensing sensors on December 7,*** this study,deformation and atmospheric monitoring were also carried out using low-cost GNSS at the Semeru Monitoring Station on September 9-15,*** results of the ZTD and ZWD values show the dominance of the wet component,which is directly proportional to rainfall activity in this period.

关键词： Semeru GNSS Water vapor Rainfall SO_(2)

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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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