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4th International Conference on Smart City Engineering and Public Transportation, SCEPT 2024

作者： Li, Shuangpin Li, Yonghua Pei, Zhuoyan Liu, Zuqiang Chen, Yuanzhu Shi, Bo Zhang, Bin Zhen, Ming Chen, Yiming Changjiang Spatial Information Technology Engineering Co. Ltd Wuhan China Hubei Water Conservancy Information Perception and Big Data Engineering Technology Research Center Wuhan China National Dam Safety Engineering Technology Research Center Wuhan China

ISBN: (数字)9781510679825

ISBN: (纸本)9781510679818

Inspection is an important means of managing the safety of water projects and an important task for ensuring the safe operation of dams. In response to issues such as scattered inspection data, severe information islands, insufficient visualization, inadequate information management, and poor timeliness in traditional manual patrol inspections, this paper has developed an intelligent safety monitoring and inspection system based on micro inertial navigation technology. The system integrates "inertial navigation + internet of things + digital map"technology, which can accurately locate the patrol route based on indoor inertial navigation positioning or outdoor GNSS positioning. Through multimedia methods such as intelligent terminals taking photos and videos, the system records inspection data and generates inspection results based on the patrol route and inspection data. This effectively improves the intelligence level of safety monitoring and patrol inspection work. Engineering applications have shown that this system is worth promoting in other projects. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Inspection

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Recognizing Public Satisfaction Toward Kampus Mengajar Program with Naive Bayes 10

Recognizing Public Satisfaction Toward Kampus Mengajar Progr...

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10th International Conference on Computer, Control, Informatics and its Applications, IC3INA 2023

作者： Suhud, Ridwan Febriandirza, Arafat Permatasari, Intan Ramadan, Farhan Research Center for Data and Information Sciences Jakarta Indonesia Department of Data and Information Center Jakarta Indonesia University of Muhammadiyah Prof. DR. Hamka Faculty of Industrial and Informatics Technology Jakarta Indonesia

ISBN: (纸本)9798350394870

Merdeka Belajar Kampus Merdeka (MBKM) is a policy governed by the Minister of Education and Culture to improve college students' capability, creativity, and innovation. Several programs are offered to realize MBKM, one is Kampus Mengajar which gives the opportunity for the participants in problem-solving, strategic development, effective, innovative, and fun learning. The teaching campus program gets different responses from the public which is conveyed on social media, various comments in the form of comments that are positive, negative, or neutral. To recognize public opinions of Kampus Mengajar's implementation, this research conducted a sentiment analysis using A thousand and five hundred Twitter datasets containing Kampus Mengajar as a keyword. We apply pre-processing before classifying the dataset in Naive Bayes. Thus, SMOTE is carried out to overcome imbalanced data. The results showed that the level of accuracy in determining categories was 77.45% and the micro average was 77.45% in determining sentiment and had a precision level of 81.46% and a recall of 77.45%. © 2023 IEEE.

关键词： Sentiment analysis

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Development of CCSDS Remote Sensing Satellite Raw data Extraction Based on Reed Solomon Code Using SoC Development Board 8

Development of CCSDS Remote Sensing Satellite Raw data Extra...

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8th International Conference on information technology, information Systems and Electrical Engineering, ICITISEE 2024

作者： Adhitama, Bayu Satya Nasution, Ali Syahputra Safitri, Yuvita Dian Rasyidy, Fadillah Halim Dwi, Adi Aufarachman Putra Bambang Jatmiko, Nugroho Widi Suhermanto Gunawan, Hidayat Munawar, Sutan Takdir Ali Darlis, Denny Jakarta Indonesia Research Center for Satellite Technology Jakarta Indonesia Data and Information Center Jakarta Indonesia Telkom University Faculty of Applied Science Bandung Indonesia

ISBN: (纸本)9798350368970

Ingest card decoding using Reed Solomon (RS) codes in the Consultative Committee for Space data Systems (CCSDS) standard plays a critical role in ensuring the success of satellite missions by providing accurate and reliable data transmission. The RS code decoder can be applied to a System on Chip (SoC) Field Programmable Gate Array (FPGA) with a Hard Processor System (HPS), thereby providing high-speed and efficient error correction for data transmission systems. This paper aims to design an RS code decoder based on CCSDS RS (255, 223) interleave 4, which is implemented on the SoC DE-10 Nano development board device. This system was developed using the C++ programming language on the Linux platform. The implementation results show that ingest system that can extract raw data from low-resolution satellite imagery is feasible. Through the use of interleave 4, PN derandomization, and ASM removal, the tested SoC system successfully decodes raw data from the CADU CCSDS of MetOp-B/C satellites. This allows for error correction on the received raw data and the creation of an Multiplex Protocol data Unit (M-PDU) file. © 2024 IEEE.

关键词： System-on-chip

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Generative dataset Distillation Based on Large Model Pool 13

Generative Dataset Distillation Based on Large Model Pool

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13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Li, Longzhen Li, Guang Togo, Ren Maeda, Keisuke Ogawa, Takahiro Haseyama, Miki Hokkaido University Graduate School of Information Science and Technology Japan Hokkaido University Education and Research Center for Mathematical and Data Science Japan Hokkaido University Faculty of Information Science and Technology Japan Hokkaido University Data-Driven Interdisciplinary Research Emergence Department Japan

ISBN: (纸本)9798350355079

Distilling knowledge into generative models is a technique to extract knowledge from a large dataset and embed it into a generative model, which effectively reduces redeployment costs and boosts dataset distillation efficiency. In this paper, we propose a novel approach to enhance the performance of generative models by expanding the size of the model pool. Our approach strives to improve the diversity of models in the model pool so that more distinctive information can be considered when matching the prediction logits. We also verified the proposed method is effective on the CIFAR-10 dataset. © 2024 IEEE.

关键词： Generative adversarial networks

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A structural variation genotyping algorithm enhanced by CNV quantitative transfer

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Frontiers of Computer Science 2022年第6期16卷 159-165页

作者： Tian ZHENG Xinyang QIAN Jiayin WANG Department of Computer Science and Technology School of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an710049China Institute of Data Science and Information Quality Shaanxi Engineering Research Center of Medical and Health Big DataXi’an Jiaotong UniversityXi’an710049China

Genotyping of structural variations considering copy number variations(CNVs)is an infancy and challenging ***,a prevalent form of critical genetic variations that cause abnormal copy numbers of large genomic regions in cells,often affect transcription and contribute to a variety of *** characteristics of CNVs often lead to the ambiguity and confusion of existing genotyping features and algorithms,which may cause heterozygous variations to be erroneously genotyped as homozygous variations and seriously affect the accuracy of downstream *** the allelic copy number increases,the error rate of genotyping increases *** instances with different copy numbers play an auxiliary role in the genotyping classification problem,but some will seriously interfere with the accuracy of the *** by these,we propose a transfer learning-based method to genotype structural variations accurately considering *** method first divides the instances with different allelic copy numbers and trains the basic machine learning framework with different genotype *** maximizes the weights of the instances that contribute to classification and minimizes the weights of the instances that hinder correct *** adjusting the weights of the instances with different allelic copy numbers,the contribution of all the instances to genotyping can be maximized,and the genotyping errors of heterozygote variations caused by CNVs can be *** applied the proposed method to both the simulated and real datasets,and compared it to some popular algorithms including GATK,Facets and *** experimental results demonstrate that the proposed method outperforms the others in terms of accuracy,stability and *** source codes have been uploaded at github/TrinaZ/CNVtransfer for academic use only.

关键词： genotyping copy number variations transfer earning

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Entrodeduper: data Deduplication Using Entropy and Secure Hash Algorithm

Entrodeduper: Data Deduplication Using Entropy and Secure Ha...

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2023 IEEE Conference on Computer Applications, ICCA 2023

作者： Thwel, Tin Thein Maung, Hsu Mon University of Computer Studies Faculty of Information Science Yangon Myanmar Myanmar Institute of Information Technology Data Center Department Mandalay Myanmar

ISBN: (纸本)9781665435994

Being a data science era, any bulk of data concerned with specific fields need to maintain in data centers with the help of rack server. For reducing storage for data center, the need to implement the data deduplication mechanism and keeping backup of those data in data center is becoming more important. In the case of reducing redundant data from the various servers in data center, the huge amount of data become the biggest challenge. As the data deduplication mechanism not only it can reduce the size of data to be stored or to be transmit but also it can give the backup and recovery features. This paper proposed the efficient data deduplication mechanism called EntroDeduper, which is the hybrid of entropy, secure hash algorithm and indexing. The input files are divided into blocks using file separator and the redundant block is removed by applying the entropy gain theory, which is used to get not only the significant reduction rate but also the full block coverage for reconstruction. © 2023 IEEE.

关键词： Entropy

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Design and realization of marine map service platform based on microservice 6

Design and realization of marine map service platform based ...

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6th International Conference on Geoscience and Remote Sensing Mapping, GRSM 2024

作者： Guo, Xue Qu, Hui Sun, Hanrui He, Long Zhang, Can Technology Innovation Center of Marine Information MNR Tianjin300171 China National Marine Data and Information Service Tianjin300171 China Marine academy of Zhejiang Province Hangzhou310012 China

ISBN: (纸本)9781510688018

With the development of marine information in China, the application of spatial basic geographic information in the marine field is increasing. System integration and specialized applications based on marine spatial geographic information are becoming increasingly common. This article establishes a spatiotemporal database for marine geographic information applications. It produces and releases basic geographic base map data services for vector, terrain, and remote sensing images, as well as marine 3D sphere model services. Application of microservice architecture and container technology, platform portal customized integration technology, sea and land integrated data distribution integration technology to build marine map service platform and realize the base map sharing application, special data query and analysis, spatial processing analysis, online mapping and microservice API sharing, and other functions. The platform improves the utilization efficiency of marine spatial geographic information resources. © 2025 SPIE.

关键词： Marine applications

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Two efficient beamforming methods for hybrid IRS-aided AF relay wireless networks

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Science China(information Sciences) 2025年第4期68卷 363-379页

作者： Xuehui WANG Qingbo LI Wen ZHU Feng SHU Mengxing HUANG Fuhui ZHOU Riqing CHEN Cunhua PAN Yongpeng WU Jiangzhou WANG School of Mathematics and Statistics Hainan Normal University Key Laboratory of Data Science and Smart Education Ministry of Education Hainan Normal University School of Information and Communication Engineering Hainan University Collaborative Innovation Center of Information Technology Hainan University School of Electronic and Optical Engineering Nanjing University of Science and Technology College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Digital Fujian Institute of Big Data for Agriculture Fujian Agriculture and Forestry University National Mobile Communications Research Laboratory Southeast University Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Jiao Tong University School of Engineering University of Kent

Owing to its ability to mitigate the double-fading effect by amplifying the reflected signal, the active intelligent reflecting surface(IRS) has garnered significant attention. In this paper, an amplify-and-forward(AF) relay network assisted by a hybrid IRS consisting of both passive and active units is developed. A signal-to-noise ratio(SNR) maximization problem is formulated, where the AF relay beamforming matrix and the hybrid IRS reflecting coefficient matrices for two-time slots need to be optimized. To address the SNR maximization problem, this paper proposes both a high-performance(HP) method and a low-complexity(LC) method. The HP method is based on the semidefinite relaxation and fractional programming(SDR-FP)algorithm, with rank-1 solutions obtained through Gaussian randomization. For the LC method, the amplification coefficient of each active IRS element is assumed to be equal. The SNR maximization problem is then addressed using the whitening filter,generalized power iteration, and generalized Rayleigh-Ritz(WF-GPI-GRR) approach. Simulation results show that compared with the benchmarks, such as the passive IRS-aided AF relay network, the proposed HP-SDR-FP and WF-GPI-GRR methods achieve significant rate improvements. In particular, the HP-SDR-FP and WF-GPI-GRR methods yield more than a 135.0%rate gain when the transmit power Ps of the source is 10 dBm. Furthermore, the proposed HP-SDR-FP method outperforms the WF-GPI-GRR method in terms of rate performance.

关键词： double-fading intelligent reflecting surface active elements passive elements hybrid IRS AF relay

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Federated Dynamic Client Selection for Fairness Guarantee in Heterogeneous Edge Computing

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Journal of Computer Science & technology 2024年第1期39卷 139-158页

作者：毛莺池沈莉娟吴俊平萍吴杰 Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai UniversityNanjing 211100China College of Computer and Information Hohai UniversityNanjing 211100China Center of Networked Computing Temple UniversityPhiladelphiaPA 19122-6096U.S.A

Federated learning has emerged as a distributed learning paradigm by training at each client and aggregat-ing at a parameter *** heterogeneity hinders stragglers from responding to the server in time with huge com-munication *** client grouping in federated learning can solve the straggler problem,the stochastic selection strategy in client grouping neglects the impact of data distribution within each ***,current client grouping ap-proaches make clients suffer unfair participation,leading to biased performances for different *** order to guaran-tee the fairness of client participation and mitigate biased local performances,we propose a federated dynamic client selec-tion method based on data representativity(FedSDR).FedSDR clusters clients into groups correlated with their own lo-cal computational *** estimate the significance of client datasets,we design a novel data representativity evalua-tion scheme based on local data ***,the two most representative clients in each group are selected to optimize the global ***,the DYNAMIC-SELECT algorithm updates local computational efficiency and data representativity states to regroup clients after periodic average *** on real datasets show that FedS-DR improves client participation by 27.4%,37.9%,and 23.3%compared with FedAvg,TiFL,and FedSS,respectively,tak-ing fairness into account in federated *** addition,FedSDR surpasses FedAvg,FedGS,and FedMS by 21.32%,20.4%,and 6.90%,respectively,in local test accuracy variance,balancing the performance bias of the global model across clients.

关键词： federated learning fairness computational efficiency data distribution client selection client grouping

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Using analytic hierarchy process to evaluate deep learning for infrared target recognition

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Multimedia Tools and Applications 2024年第38期83卷 86229-86245页

作者： Xu, Laixiang Cao, Bingxu Wei, Xinhong Li, Bei Su, Jingfeng Ning, Shiyuan Zhao, Junmin School of Computer and Data Science Henan University of Urban Construction Pingdingshan467036 China School of Information Engineering Luohe Vocational Technology College Henan University of Technology Luohe Institute of Technology Luohe462000 China School of Computer and Data Science Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Pingdingshan467036 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Henan University of Urban Construction Pingdingshan467036 China Department of Software Information China Electronics Technology Group Corporation 36-th Research Institute Jiaxing314033 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Research Center of Intelligent Campus Application Engineering of Henan Province Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Henan University of Urban Construction Pingdingshan467036 China

In order to promote the evaluation performance of deep learning infrared automatic target recognition (ATR) algorithms in the complex environment of air-to-air missile research, we proposed an analytic hierarchy process (AHP) evaluation system consisting of the target recognition ability, the generalization recognition ability, the anti-interference ability, the background suppression ability, and the cost metrics ability. According to detailed quantitative analysis and experimental results, we establish probability evaluation models and get their probability values. Compared with traditional evaluation systems, our proposed method implementation is showing high reliability. Similar superior performances are also achieved, such as quick, comprehensive, and scientific. Through the above research, the key technology of deep learning performance evaluation in automatic target recognition has been broken through, which provides some basis and guidance for the analysis of infrared imaging-guided weapon systems. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Infrared imaging

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