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International Conference on intelligent System and Knowledge Engineering, ISKE

作者： Gao-Jing Peng Ke-Jia Chen Shijun Xue Bin Liu Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing Jiangsu China

This paper studies relation prediction in heterogeneous information networks under PU learning context. One of the challenges of this problem is the imbalance of data number between the positive set P (the set of node pairs with the target relation) and the unlabeled set U (the set of node pairs without the target relation). We propose a K-means and voting mechanism based technique SemiPUclus to extract the reliable negative set RN from U under a new relation prediction framework PURP. The experimental results show that PURP achieves better performance than comparative methods in DBLP co-authorship network data.

关键词： Reliability Artificial neural networks Clustering algorithms Algorithm design and analysis Prediction methods Sun

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Discrimination-Aware Domain Adversarial Neural Network

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Journal of Computer Science & Technology 2020年第2期35卷 259-267页

作者： Yun-Yun Wang Jian-Min Gu Chao Wang Song-Can Chen Hui Xue College of Computer Science and Engineering Nanjing University of Posts and Telecommunications Nanjing 210046China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing 210046China College of Computer Science and Technology/College of Artificial Intelligence Nanjing University of Aeronautics and AstronauticsNanjing 210023China Key Laboratory of Pattern Analysis and Machine Intelligence Ministry of Industry and Information Technology Nanjing 210023China School of Computer Science and Engineering Southeast UniversityNanjing 210096China

The domain adversarial neural network(DANN)methods have been successfully proposed and attracted much attention *** DANNs,a discriminator is trained to discriminate the domain labels of features generated by a generator,whereas the generator attempts to confuse it such that the distributions between domains are *** a result,it actually encourages the whole alignment or transfer between domains,while the inter-class discriminative information across domains is not *** this paper,we present a Discrimination-Aware Domain Adversarial Neural Network(DA2NN)method to introduce the discriminative information or the discrepancy of inter-class instances across domains into deep domain ***2NN considers both the alignment within the same class and the separation among different classes across domains in knowledge transfer via multiple *** results show that DA2NN can achieve better classification performance compared with the DANN methods.

关键词： adversarial learning inter-class separation deep neural network discrimination-aware domain adaptation

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A Point Cloud Registration Method for Substations Based on an Improved SAC-IA Algorithm

A Point Cloud Registration Method for Substations Based on a...

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2023 China Automation Congress, CAC 2023

作者： Wang, Lei Chen, Yiping Zong, Haonan Wang, Lulu Yin, Jun School of Computer Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing210023 China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing210023 China

ISBN: (纸本)9798350303759

This paper proposes a point cloud registration method for substations based on an improved SAC-IA algorithm. This method optimizes the SAC-IA algorithm by filtering the randomly selected point pairs to ensure that the triangles formed by the selected points in the model and scene point clouds have certain similarities. Furthermore, the registration error judgment of the SAC-IA algorithm has been improved. In addition to using the Euclidean distance between the registered model and scene point clouds as the judgment standard, this method also considers the SHOT difference and average curvature difference. Successful registration is only considered when all three standards are satisfied. The experimental research shows that the time performance of this method is twice as high as that of the traditional SAC-IA algorithm on average, and the recognition accuracy is improved in the recognition results. © 2023 IEEE.

关键词： Electric substations

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Path Planning based on Reinforcement Learning with Improved APF model for Synergistic Multi-UAVs 26

Path Planning based on Reinforcement Learning with Improved ...

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26th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2023

作者： Ding, Qun Xu, Xiaolong Gui, Wenming Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing210023 China Nanjing University of Posts and Telecommunications School of Computer Science Nanjing210023 China Jinling Institute of Technology School of Computer Science Nanjing211169 China

ISBN: (纸本)9798350331684

As the emerging technology of Unmanned Aerial Vehicles (UAVs) becomes mature, UAVs are widely used in environmental monitoring, communication and other fields. In view of this, this paper analyzed the task of synergistic multi-UAVs exploration of unknown environments, and proposed a path planning method for them based on reinforcement learning. Firstly, the path planning task of the UAVs was divided into two parts: the path travel strategy module and the information exploration strategy module. Models of the two modules were based on the Deep Deterministic Policy Gradient algorithm (DDPG), and an improved Artificial Potential Field (APF) force traction mechanism was introduced in the path travel strategy module. Its aim was to assist in guiding the generation of UAV flight path trajectories. Also it could enhance the learning capability of the model. The path travel strategy module would generate the complete flight path of the whole cluster in a distributed manner. A series of temporary target points provided by the information exploration strategy module helped. In maps with 21.5%, 25.3% and 29.6% of obstacles, multi-UAVs could achieve 84.2%, 76.7% and 69.9% of environmental exploration by the designed method. Compared with the APF method, the A star method and the Breath First Search (BFS) method, the proposed method is not only able to plan feasible paths in a more complex map model, but also the curvature of the planned paths is smoother, thus achieving the goal of reducing the energy cost of UAVs. © 2023 IEEE.

关键词： Reinforcement learning

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A Point Cloud Completion Method for Industrial Component Based on Multiple Encoders

A Point Cloud Completion Method for Industrial Component Bas...

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2023 China Automation Congress, CAC 2023

作者： Wang, Lei Chen, Ran Huang, Wei Chen, Yiping Yin, Jun School of Computer Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing210023 China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing210023 China

ISBN: (纸本)9798350303759

In real-world scenarios, laser-scanned point clouds often suffer from missing data points due to occlusion and other factors, significantly impacting subsequent tasks. We propose a novel point cloud completion method based on self-attention mechanisms and multi-layer perceptrons to address this issue, building upon the PCN model. Our experimental evaluations on the PCN dataset demonstrate notable enhancements in the completion effectiveness and evaluation metrics compared to the baseline model. Additionally, focusing on the point cloud completion context for industrial components, we introduce an approach for constructing an industrial component point cloud dataset. This method leverages 3D mesh models to swiftly generate complete point clouds with uniform distribution and devoid of noise while simulating the incomplete point clouds obtained from real-world scanning scenarios. The final results fully exhibit the feasibility of this scheme, which is a strong candidate for future industrial component point cloud completion. © 2023 IEEE.

关键词： Signal encoding

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A Social-Aware Mode Selection Algorithm for D2D Communications

A Social-Aware Mode Selection Algorithm for D2D Communicatio...

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International Conference on Communications, Signal processing, and Systems, CSPS 2018

作者： Lu, Wei-feng Lin, Wei-jun Chen, Si-guang Yang, Li-jun School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210023 China College of IoT Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing210023 China

ISBN: (纸本)9789811362637

Aiming at mode selection in D2D communication, a mode selection strategy based on social-aware was proposed. In addition to physical connection status, users’ social relationships also served as an observation element. Through relationship between users, the closeness of user relationship can be judged, and then through users’ reference, the similarity between users can be obtained. In this way, by combining physical connection with social relationships, users’ aggregate utility was acquired. According to the physical connection quality and the social relationship strength, taking maximizing users’ aggregate utility as the goal, a random algorithm was designed to match users. Simulation results show that mode selection based on social perception can effectively improve users’ aggregate utility. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Aggregates

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Exploring the Pan-Relationship Between Disease and Symptom Related to Coronary Heart Disease from Chinese Electronic Medical Records 15th

Exploring the Pan-Relationship Between Disease and Symptom R...

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15th International Conference on intelligent Computing, ICIC 2019

作者： Yang, Ronggen Wang, Yichen Wang, Bo Gong, Lejun Faculty of Intelligent Science and Control Engineering Jinling Institute of Technology Nanjing211169 China Jiangsu Key Lab of Big Data Security and Intelligent Processing School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210046 China School of Geography and Bioinformatics Nanjing University of Posts and Telecommunication Nanjing China

ISBN: (纸本)9783030267650

Electronic Medical Records (EMRs) arises from the clinical treatment process, which reflects a patient’s physical condition, the disease, the treatment process, etc. It has an important significance for the recovery of the patient. As the amount of electronic medical records continues to increase, people are actively looking for ways to get the valid data contained in electronic medical records. More effective methods are urgently needed for processing EMRs. In this paper, 108 real EMRs of coronary heart disease were analyzed, through named entity recognition and entity relation extraction. Pan-relationship between entities was defined in the process. Experimental results showed the analysis of pan-relation between coronary heart disease and symptom is helpful for treatment of coronary heart disease. © 2019, Springer Nature Switzerland AG.

关键词： Diseases

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Complex Substation Scene Segmentation Method Based on Optimized Straight Line Detection

Complex Substation Scene Segmentation Method Based on Optimi...

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2023 China Automation Congress, CAC 2023

作者： Wang, Lei Huang, Wei Chen, Yiping Chen, Hao Liu, Chuang Yin, Jun School of Computer Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing210023 China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing210023 China

ISBN: (纸本)9798350303759

This paper proposes a scene segmentation method based on optimized line detection to address the difficulty of segmenting spatially independent equipment in complex substation scenes. The method first employs the RANSAC method to simulate the ground plane and extract the ground point cloud. Then, it projects the 3D point cloud scene onto a 2D plane to obtain a 2D image of the substation. Straight line segments of the power line are extracted from the image using the edge detection algorithm and an improved line detection algorithm. The straight line segments that do not belong to the power line are filtered out using the surrounding features of the 3D point corresponding to the 2D point on the line. The power line's straight line segment is extended using the region-growing algorithm. Finally, the power line clustering is completed using European clustering based on the three-dimensional coordinates of the two ends of the power line, thereby completing the scene segmentation. Experimental results show that the proposed method can effectively segment substation equipment. Compared to traditional segmentation methods, this method has an average power line identification accuracy of 14% higher. © 2023 IEEE.

关键词： Edge detection

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CROA: A content-based recommendation optimization algorithm for personalized knowledge services 21

CROA: A content-based recommendation optimization algorithm ...

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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Sun, Xiao Xu, Xiaolong Xia, Fei Jiangsu Key Laboratory Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Information and communication Branch State Grid Jiangsu Electric Power Company Nanjing China

ISBN: (纸本)9781728120584

Information explosion is a typical feature of the big data. Learners can easily find a wide variety of knowledge information online. However, the expansion of information also makes it difficult for learners to retrieve the information they want and fall into the problem of knowledge overload. In order to solve this problem effectively, we propose a content-based recommendation optimization algorithm for personalized knowledge services (CROA). First, the feature vector model is established, where each item information is represented by specific words and key information is highlighted by weighting. Second, a dynamic user vector model is then established to capture the latest preference information of the user. Finally, the feature vector model is combined with the multi-user comparison results thereby obtaining a list of recommendations. Experimental results indicate that CROA outstands in knowledge recommendation mechanism and can also alleviate knowledge overload. © 2019 IEEE.

关键词： Optimization

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MDPFL:A Multiple Differential Privacy Protection Method based on Federated Learning

MDPFL:A Multiple Differential Privacy Protection Method base...

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International Conference on Computer Supported Cooperative Work in Design

作者： Xinyu Liu Xiaolong Xu Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China

With the continuous development of artificial intelligence technology, machine learning in distributed network systems, such as IoVflntemet of Vehicles), will inevitably lead to privacy leakage. At present, there are lots of problems in federated learning, differential privacy and other machine learning privacy protection schemes, such as high loss of availability and the need of a fully trusted third-party server. In order to solve these problems, we propose MDPFL(Multiple Differential Privacy based on Federated Learning) algorithm. The algorithm combines with the differential privacy model in each stage of federated learning to solve the problem of curious third-party data collectors obtaining users’ original data in the process of machine learning. Meanwhile, the algorithm does not adopt a decentralized machine learning scheme directly, but uses a double noise adding mode with the existence of the third-party data collectors. We use Laplacian mechanism in the central server and GRR mechanism in local clients to ensure the goal of stability of the effect of the machine ¡earning model. The algorithm is compared with FedAvg, CDP, LDP algorithm in accuracy and loss rate which based on EMNIST data sets. In different global sensitivities, the model training effect is consistent with FedAvg algorithm while comparing with LDP algorithm, the speed of model convergence is improved.

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