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In an Ocean or a River:Bilinear Auto-Backlund Transformations and Similarity Reductions on an Extended Time-Dependent(3+1)-Dimensional Shallow Water Wave Equation

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China Ocean Engineering 2025年第1期39卷 160-165页

作者： GAO Xin-yi College of Science and Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream DataNorth China University of TechnologyBeijing 100144China Beijing Laboratory of New Energy Storage Technology Beijing Municipal Education CommissionBeijing 102206China

With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this *** symbolic computation,we find out,on one hand,a set of bilinear auto-Backlund transformations,which could connect certain solutions of that equation with other solutions of that equation itself,and on the other hand,a set of similarity reductions,which could go from that equation to a known ordinary differential *** results in this paper depend on all the oceanic variable coefficients in that equation.

关键词： ocean river extended time-dependent(3+1)-dimensional shallow water wave equation bilinear auto-Bäcklund transformation similarity reduction symbolic computation

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Improved NSGA-II based process dynamic multi-objective algorithm

Improved NSGA-II based process dynamic multi-objective algor...

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2023 IEEE International Conference on Control, Electronics and Computer Technology, ICCECT 2023

作者： Zhang, Yaze North China University of Technology Beijing Key Laboratory on Integration and Analysis of Large-Cale Stream Data Beijing China

ISBN: (纸本)9798350399028

The NSGA-II-T algorithm is proposed to solve the scheduling problem with dynamic changes in process data processing in the service Internet, modelling the problem as a dynamic multi-objective optimisation problem. In the event of regular changes in load, the solution in the next environment is predicted by the transformer model and added to the original population;in the event of changes caused by physical factors such as node downtime, the population is added randomly. The algorithm uses different means of adding populations to address the lack of diversity that can occur in static multi-objective algorithms when the environment changes. Experiments conducted on the WorkflowSim platform show that the NSGA-II-T algorithm outperforms other classical algorithms in all performance metrics when the environment changes significantly, demonstrating the effectiveness of the algorithm. © 2023 IEEE.

关键词： Multiobjective optimization

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Distributed log collection for business processes based on ELK architecture 2

Distributed log collection for business processes based on E...

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2nd IEEE International Conference on Electrical Engineering, Big data and Algorithms, EEBDA 2023

作者： Zong, Yize North China University of Technology Beijing Key Laboratory on Integration and Analysis of Large-cale Stream Data Beijing China

ISBN: (纸本)9781665462532

When it comes to executing service solutions in a distributed environment, the service solution is considered as a workflow split into many sub-processes that are scheduled to run independently and autonomously on each processing engine. Each organization's machines have its own set of limitations. They can't write too much code or rebuild the system, so they'll have to rely on a lightweight, low-code strategy to expand the service solution's process activities to collect valuable logs. As a result, we created a log collection system for the case, as mentioned earlier. The listener class is used to insert some functional code that sends the logs to the messaging middleware. Then, the service call records, or log data, are transmitted to the central administration platform. The ELK (Elasticsearch, Logstash, Kibana) framework, commonly used in log analysis nowadays, is then used to perform real-time data processing. Finally, the logs are visually displayed to provide intuitive feedback on log information and to make system maintenance and adjustment easier. © 2023 IEEE.

关键词： Middleware

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A Distributed Microservice Scheduling Optimization Method

A Distributed Microservice Scheduling Optimization Method

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2023 IEEE International Conference on Control, Electronics and Computer Technology, ICCECT 2023

作者： Li, Han Zhao, Yun Liu, Zhenxiong Liu, Wei North China University of Technology Beijing Key Laboratory on Integration and Analysis of Large-Cale Stream Data Beijing China

ISBN: (纸本)9798350399028

In the current Internet of Things environment, factors affecting scheduling are gradually increasing, and service performance is affected. There may be service delays, service non-response, and service feedback error messages. At the same time, service scheduling needs to be continued. Therefore, the scheduling The algorithm puts forward higher requirements. This paper proposes a scheduling algorithm based on depth-determined policy gradient (DDPG). By combining deep learning and reinforcement learning, it solves the problem of continuous action control and constructs a policy network and a value network. Double network structure to solve the problem of slow algorithm convergence. Secondly, this paper designs a microservice-based visual monitoring system to obtain the experimental data required by the algorithm and verify the effectiveness of the algorithm. Finally, 30 sets of data collected by the monitoring system are used to test and analyze the resource balance and service delay on the node in combination with the constraints of service and data dependency, and compare the delay and resource utilization with three typical algorithms. Experiments show that DDPG can show better performance under various constraints of the complex environment of the Internet of Things. © 2023 IEEE.

关键词： Scheduling algorithms

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Attack based on data: a novel perspective to attack sensitive points directly

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Cybersecurity 2024年第3期7卷 111-123页

作者： Yuyao Ge Zhongguo Yang Lizhe Chen Yiming Wang Chengyang Li School of Information Science and Technology North China University of TechnologyBeijingChina Bejing Key Laboratory on Integration and Analysis of Large-Scale Stream Data North China University of TechnologyBeijingChina School of Computer Science Peking UniversityBeijingChina

Adversarial attack for time-series classification model is widely explored and many attack methods are *** there is not a method of attack based on the data *** this paper,we innovatively proposed a black-box sparse attack method based on data *** method directly attack the sensitive points in the time-series data accord-ing to statistical features extract from the *** frst,we have validated the transferability of sensitive points among DNNs with different ***,we use the statistical features extract from the dataset and the sensi-tive rate of each point as the training set to train the predictive ***,predicting the sensitive rate of test set by predictive ***,perturbing according to the sensitive *** attack is limited by constraining the LO norm to achieve one-point *** conduct experiments on several datasets to validate the effectiveness of this method.

关键词： Black-box adversarial attack Time series classification data mining

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Efficient Range Query Method for Traffic data Using Learning-Based Spatiotemporal Index

Efficient Range Query Method for Traffic Data Using Learning...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Guo, Zhicheng Fang, Jun Zhang, Haibo Beijing Key Laboratory On Integration and Analysis of Large-Scale Stream Data Beijing University of Technology Beijing China North China University of Technology Beijing100144 China

ISBN: (纸本)9789819639601

Traffic data is characterized by complexity in structure, high collection frequency, large volume, and uneven spatiotemporal distribution. Efficient range querying on traffic data poses a significant challenge in intelligent transportation system research. Utilizing spatiotemporal indices to accelerate queries is an effective approach. However, traditional spatiotemporal indices suffer from issues where index efficiency is negatively correlated with data volume, and index storage size is positively correlated with data volume. To address these challenges, this paper proposes an efficient range query method for traffic data based on a learning-based spatiotemporal index. The Flood index is applied and enhanced with the following improvements: Firstly, a fully connected neural network constructs a time-cost model to predict query times and determine the optimal grid layout. Secondly, a recursive model index learns data distribution within each grid for query range prediction and proposes an index updating strategy. Experimental results using real data demonstrate that our method maintains comparable query efficiency to Flood index while reducing index storage space by a factor of 10. Furthermore, compared to baseline methods, our approach improves query speed for traffic spatiotemporal data by 3 to 8 times. © beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Structured Query Language

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Tour Guide Robot Based on large Language Model and User Behavior analysis 5

Tour Guide Robot Based on Large Language Model and User Beha...

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5th International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2024

作者： Lin, Haoran Wang, Jing Zhan, Yutong Zhang, Yuan School of Information Science and Technology North China University of Technology Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data Beijing China

ISBN: (纸本)9798331528911

With the continuous development of human-computer interaction technology, the applications of tour guide robots in scenarios such as museums and exhibition halls are becoming increasingly widespread. However, traditional tour guide robots primarily rely on predefined content and texts, as well as pre-planned routes, making it difficult to adjust in real-time based on the diverse needs and interests of different visitors. This limitation restricts interactivity and engagement. To address this issue, this paper proposes an intelligent tour guide robot system that integrates large language model and user behavior analysis technology, aimed at dynamically adjusting tour content by real-time perception of visitors' interests. This system leverages the natural language processing capabilities of large language model, along with user behavior analysis techniques, to provide visitors with a more personalized and interactive tour experience. Experimental validation shows that the proposed tour guide robot system can enhance the accuracy and proactivity of tour presentations, thereby increasing user engagement and the overall effectiveness of the tour. © 2024 IEEE.

关键词： Natural language processing systems

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A survey on graph neural network-based next POI recommendation for smart cities

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Journal of Reliable Intelligent Environments 2024年第3期10卷 299-318页

作者： Yu, Jian Guo, Lucas Zhang, Jiayu Wang, Guiling Department of Computer Science and Soft Engineering Auckland University of Technology Auckland New Zealand School of Information Science and Technology Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data North China University of Technology Beijing China

Amid the rise of mobile technologies and Location-Based Social Networks (LBSNs), there’s an escalating demand for personalized Point-of-Interest (POI) recommendations. Especially pivotal in smart cities, these systems aim to enhance user experiences by offering location recommendations tailored to past check-ins and visited POIs. Distinguishing itself from traditional POI recommendations, the next POI approach emphasizes predicting the immediate subsequent location, factoring in both geographical attributes and temporal patterns. This approach, while promising, faces with challenges like capturing evolving user preferences and navigating data biases. The introduction of Graph Neural Networks (GNNs) brings forth a transformative solution, particularly in their ability to capture high-order dependencies between POIs, understanding deeper relationships and patterns beyond immediate connections. This survey presents a comprehensive exploration of GNN-based next POI recommendation approaches, delving into their unique characteristics, inherent challenges, and potential avenues for future research. © The Author(s) 2024.

关键词： Location based services

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Research on Construction Method of Science and Technology Service Domain Knowledge Map 7

Research on Construction Method of Science and Technology Se...

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7th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Qian, Jiaqi North China University of Technology School of Information Science and Technology Beijing China Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data Beijing China

ISBN: (纸本)9798350339161

With the development of the science and technology service industry, there is an urgent need to effectively organize multi-source and heterogeneous science and technology resources to meet the personalized needs of science and technology services in different industrial fields, that is, to provide various services to different industrial fields according to industry perspectives. Required scientific and technological resources, including scientific and technological project resources and scientific and technological consulting resources, etc. Effective organization and management of scientific and technological resources can be completed by building a domain knowledge map for industrial industry scientific and technological services. However, these resource fields have a large number of data types, are highly professional, and have complex businesses. How to obtain useful data, information, and business knowledge from massive data and store it in a graph database to complete the construction of a knowledge graph is the subject of this article. Concerns. Therefore, this article proposes a set of methods that integrate data preprocessing and knowledge modeling based on structured data processing and ontology technology to complete the construction of domain knowledge graphs. © 2024 IEEE.

关键词： Knowledge graph

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Verification of IoT-Aware Business Processes Based on Extended Petri Nets 16th

Verification of IoT-Aware Business Processes Based on Exte...

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16th International Conference on Service Science, ICSS 2023

作者： Cao, Jiachen Wang, Jing Yang, Shiyi Gong, Huilong Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data North China University of Technology Beijing100144 China

ISBN: (纸本)9789819944019

With the rapid development of cloud computing and Internet of Things (IoT)technology, the convergence of BPM (Business Process Management) and IoT big data has attracted more and more attention. Integrating IoT services into BPM enables BPM to perceive changes in the physical world more quickly and accurately, but also brings challenges to process verification. The verification method that supports IoT-aware business processes is required. This paper proposes a method to formally represent the Business Process Modeling Notation (BPMN) model with IoT services integrated based on extended Petri nets, and a deadlock detection algorithm for this formaliza-tion method. The case study shows that the method proposed in this paper can effectively detect the deadlock structures in IoT-aware business process-es, and reduce process errors for process modelers. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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