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2023 IEEE International Conference on Dependable, Autonomic and Secure Computing, 2023 International Conference on Pervasive Intelligence and Computing, 2023 International Conference on Cloud and big data Computing, 2023 International Conference on Cyber science and technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Yuan, Linlin Yang, Yuxiang Tan, Chaoyue Dou, Hui Luo, Yun Chen, Yuling College of Information Engineering Guizhou Open University Guiyang China College of Computer Science and Technology Guizhou University State Key Laboratory of Public Big Data Guiyang China

ISBN: (纸本)9798350304602

Blockchain's immutability, while a core feature, can pose challenges in cases involving sensitive information or compliance with legal regulations, hindering its development. Many subsequent works designed editable blockchains based on the chameleon hash function proposed by H. Krawczyk et al. to solve the above problems. However, existing editable blockchain solutions lack security and are inefficient. To address the security and efficiency issues, we introduce the novel concept of Chameleon hashing based on Schnorr threshold signatures (CHSTS). The CHSTS scheme has double trapdoors, the publisher of the message owns the long-term trapdoor, and the editorial committee owns the ephemeral trapdoor. Message publishers can collaborate with the editorial committee to modify their published information, preventing the exposure of private data, facilitating oversight during the editing process, and enabling the tracking of malicious users. We have designed an updatable ephemeral trapdoor based on Schnorr signatures, effectively avoiding the inefficiencies associated with bilinear pairing. Experimental results show that our CHSTS scheme has a significant advantage in computational cost. © 2023 IEEE.

关键词： Blockchain

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A Fast and Effective Panorama Stitching Algorithm on UAV Aerial Images 14

A Fast and Effective Panorama Stitching Algorithm on UAV Aer...

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14th IEEE International Conference on Computer Research and Development, ICCRD 2022

作者： Yang, Haoran Fu, Yan Chen, Duanbing Peng, Yu University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China Chengdu Union Big Data Technology Incorporated Chengdu China

ISBN: (纸本)9781728177212

Nowadays, UAV(Unmanned Aerial Vehicle) has been widely used in many areas, such as agriculture, rescue and disaster relief, video shooting. In some applications, the whole environment needs to be perceived, so image stitching comes in handy. It is time-consuming for present methods to stitch aerial images, whose bottleneck is to generate dense point clouds. Besides, traditional image stitching algorithm may encounter accumulative error which makes the result distortion. In this paper, a fast UAV image stitching algorithm is proposed by re-placing generation of dense point clouds with image composition algorithm and taking full advantages of GPS information to initialize cameras' rotation to weaken the impact of accumulative error. The proposed model is much simpler than classical models in UAV image stitching, it can handle large scene very quickly. Furthermore, the effect of stitching is better than the current commercial software(Pix4D). When overlap ratio between two images is low, the proposed algorithm can generate a good stitching result, while commercial software may generate some black areas. © 2022 IEEE.

关键词： Antennas

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A Polynomial-Time Algorithm for MCS Partial Search Order on Chordal Graphs 48

A Polynomial-Time Algorithm for MCS Partial Search Order on ...

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48th International Symposium on Mathematical Foundations of Computer science, MFCS 2023

作者： Rong, Guozhen Yang, Yongjie Li, Wenjun Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology China Chair of Economic Theory Saarland University Saarbrücken Germany

ISBN: (纸本)9783959772921

We study the partial search order problem (PSOP) proposed recently by Scheffler [WG 2022]. Given a graph G together with a partial order on the set of vertices of G, this problem determines if there is an S-ordering that is consistent with the given partial order, where S is a graph search paradigm like BFS, DFS, etc. This problem naturally generalizes the end-vertex problem which has received much attention over the past few years. It also generalizes the so-called F-tree recognition problem which has just been studied in the literature recently. Our main contribution is a polynomial-time dynamic programming algorithm for the PSOP of the maximum cardinality search (MCS) restricted to chordal graphs. This resolves one of the most intriguing open questions left in the work of Scheffler [WG 2022]. To obtain our result, we propose the notion of layer structure and study numerous related structural properties which might be of independent interest. © Guozhen Rong, Yongjie Yang, and Wenjun Li

关键词： Dynamic programming

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Design of the Smart Bedside Table Based on Single-Chip Microcomputer 12

Design of the Smart Bedside Table Based on Single-Chip Micro...

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12th International Conference on Information technology in Medicine and Education, ITME 2022

作者： Shijia, Yang Weiqiang, Yang Xiehua, Yu Key Laboratory of Big Data and Artificial Intelligence University of Fujian Province MinNan Science and Technology University Quanzhou China

ISBN: (纸本)9798350310153

With the popularization of smart home, nightstand plays an increasingly important role in people's daily life. By means of questionnaire survey and data collection, it is found that most household nightstands only play the role of storage, the bedroom space is always not enough for all kinds of furniture, the nightstand cannot be interconnected with other smart devices. The existing smart nightstands on the market have common problems: uneven functions and low practicability. In view of the above problems, combined with the smart home system, this paper studies and designs a smart nightstand with HT66F2390 microcontroller as the core. To save the bedroom space, other furniture functions are integrated, such as adaptive adjustment of night light and brightness, refrigeration and fresh-keeping, heating and insulation, drawer fingerprint unlock, LED light group changing in different occasions. LCD displays the user interface for easy operation. The smart nightstand is set up to test the environment and optimize the functions of each module. The results show that the designed intelligent bedside table can integrate the functions of other furniture. It effectively saves bedroom space and optimizes living experience. The expected design goal has been achieved. © 2022 IEEE.

关键词： User interfaces

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Efficient Deep learning-based Real-time Migration Strategies for Containers in SDN 6

Efficient Deep learning-based Real-time Migration Strategies...

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6th International Conference on Next Generation data-Driven Networks, NGDN 2024

作者： Huang, Shan Liu, Yanan Li, Yanuo He, Feili Duan, Xiaodong School of Computer Science and Engineering Dalian Minzu University Dalian China Key Laboratory of Big Data Application Technology of the State Ethnic Affairs Commission Dalian China Dalian Ethnic Culture Digital Technology Key Laboratory Dalian China

ISBN: (纸本)9798350388374

Container technology is widely used and improve the efficiency of container real-time migration has become an important research topic. Existing studies mainly focus on optimizing iterative dumping of containers without fully considering the impact of migration node selection on migration efficiency. Software-defined networking (SDN), achieves centralized control of the network by separating the control plane and the forwarding plane. Applying deep learning to SDN makes tasks such as traffic prediction and network optimization more intelligent. This paper proposes Prediction Model based on CLCB (CNN-LSTM-CBAM) uses real-time collected load data as input, extracts feature components of load data using one-dimensional convolutional neural networks, and then predicts using LSTM. To improve prediction accuracy, a lightweight CBAM attention module is introduced, and the prediction results are output through fully connected layers. The Network Traffic Prediction Model based on GCGRU-Conv (GCN-GRU-CNN) considers both spatial and temporal features of network traffic. GCN and GRU are used to extract spatial and temporal features of network traffic, respectively, and then these features are fused together using convolutional neural networks. To address the gradient problem caused by increasing network depth, a residual network structure is introduced. Experimental results show that the method proposed can effectively reduce the container migration time and has better prediction results. © 2024 IEEE.

关键词： Convolutional neural networks

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Graph classification based fault detection in nuclear power plants with graph formulation 10

Graph classification based fault detection in nuclear power ...

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10th International Conference on Information technology and Quantitative Management, ITQM 2023

作者： Qu, Yi Xue, Xiaodong Shi, Yong Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China College of Information Science and Technology University of Nebraska OmahaNE68182 United States

In the routine production and operation of nuclear power plants (NPPs), safety management is extremely important, and consequently, a fault detection system yielding high accuracy could provide effective decision support and prevent the accidents to the maximum extent. Most of existing studies are based on the analysis of time-series data, while researches oriented to the implementation of graph data mining are barely seen. In this paper, we propose an improved fault detection method to address this task from the perspective of graph representation learning. By calculating the similarity between indicators, the multivariate temporal sequences of the running characteristics of NPPs have been formulated as a group of graphs with corresponding labels, on which the graph convolutional network (GCN) has been introduced to detect fault samples in the way of graph classification. Compared to conventional supervised learning classifiers, our proposed methodology performs more superior identification of major faults, and the sensitivity regarding significant parameter or settings in the model design has been analyzed to investigate their optimal arrangements. The findings in this article not only present the promising prospects of introducing graph learning techniques into safety management, also indicate that various kinds of digital signals could be reformulated into graph dataset based on which the original task could be executed more effectively in the way of graph representation learning. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Tenth International Conference on Information technology and Quantitative Management.

关键词： Nuclear power plants

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Unsupervised statistical text simplification using pre-trained language modeling for initialization

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Frontiers of Computer science 2023年第1期17卷 1-10页

作者： QIANG Jipeng ZHANG Feng LI Yun YUAN Yunhao ZHU Yi WU Xindong Department of Computer Science Yangzhou University Yangzhou 225127 China Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education Hefei 23009 China Mininglamp Academy of Sciences Mininglamp Beijing 100089 China

Unsupervised text simplification has attracted much attention due to the scarcity of high-quality parallel text simplification corpora. Recent an unsupervised statistical text simplification based on phrase-based machine translation system (UnsupPBMT) achieved good performance, which initializes the phrase tables using the similar words obtained by word embedding modeling. Since word embedding modeling only considers the relevance between words, the phrase table in UnsupPBMT contains a lot of dissimilar words. In this paper, we propose an unsupervised statistical text simplification using pre-trained language modeling BERT for initialization. Specifically, we use BERT as a general linguistic knowledge base for predicting similar words. Experimental results show that our method outperforms the state-of-the-art unsupervised text simplification methods on three benchmarks, even outperforms some supervised baselines.

关键词： text simplification pre-trained language modeling BERT word embeddings

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A detection method of power equipment in substation based on intelligent equipment 10

A detection method of power equipment in substation based on...

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10th International Conference on Energy Materials and Electrical Engineering, ICEMEE 2024

作者： Yan, Nannan Feng, Jianfeng Xue, Xiangyang Lei, Xing Yao, Zhoufei Chen, Yan Zhou, Yunjie He, Bangle Yuan, Jialiang State Grid Shanghai Electric Power Company Shanghai200122 China School of Big Data Institute of Brain-Like Intelligence Science and Technology Fudan University Shanghai200433 China Institute of Brain and Intelligence Science and Technology School of Computer Science Fudan University Shanghai200433 China

ISBN: (纸本)9781510686243

In view of the current problems of substation operation and maintenance, such as excessive workload, diversified tasks, low inspection efficiency, inadequate inspection, and defects in inspection data statistics, this work researches and designs substation intelligent perception and operation and maintenance methods based on intelligent technology to realize distributed recording of the operation status of each equipment by inspection system, intelligent data acquisition, and intelligent inspection of substation. At the same time, the on-site operation of personnel is more efficient and accurate supervision and guidance, and the substation management provides multi-scene decision support, and finally realizes the multi-directional intelligent management of the substation. © 2024 SPIE.

关键词： Inspection equipment

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Analysis of the Impact of Aging on Factors Affecting Economic Dynamism

Analysis of the Impact of Aging on Factors Affecting Economi...

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作者： Yujia Chen Chang Liu Data Science and Big Data Technology Wuhan Institute of Technology Department of Business Administration Hong Kong Baptist University

Population aging is one of the biggest demographic challenges facing China in the 21st century. Its impact on the economy cannot be ignored. This study employs empirical research to illustrate how population aging affects China's economic development. It is mainly explained from the perspectives of the labor force, savings rate, GDP, and pension insurance *** to the relevant data and the definition standard of the United Nations on aging society,the relevant data from 2002 to 2020 are selected for empirical analysis. The conclusion is obtained through the ADF test, determination of optimal lag order, the AR characteristic root test, and impulse response analysis. The results display that from the perspective of GDP and savings rate, population aging has an inhibitory effect on the economy, and has a lasting negative impact on the labor *** results suggest that some measures should be taken to deal with the effects of aging in order to counteract its negative impacts on the economy and society.

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Last-X-Generation Archiving Strategy for Multi-Objective Evolutionary Algorithms 13

Last-X-Generation Archiving Strategy for Multi-Objective Evo...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Shu, Tianye Nan, Yang Shang, Ke Ishibuchi, Hisao Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China Southern University of Science and Technology Shenzhen518055 China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China

ISBN: (纸本)9798350308365

For evolutionary multi-objective optimization algorithms (EMOAs), an external archive can be utilized for saving good solutions found throughout the evolutionary process. Recent studies showed that a solution set selected from an external archive is usually superior to the final population. That is, the incorporation of an external archive improves the performance of EMOAs. However, the computation time for maintaining an external archive is long, especially when the archive size is large. To solve this issue, a simple archiving strategy is to save all solutions generated in the last several generations. In this paper, we examine this archiving strategy for three representative EMOAs on artificial test problems (Minus-DTLZ and WFG) and real-world problems (RE). Our results show that archiving the last several generations clearly improves the performance of EMOAs without severely increasing the computation time. © 2024 IEEE.

关键词： Optimization algorithms

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