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17th IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC)

作者： Yin, Xiaoyin He, Jiangnan Gao, Ying Li, Jingxian Yunnan Minzu Univ Lanmei Sch Kunming Yunnan Peoples R China Yunnan Univ Finance & Econ Business Sch Kunming Yunnan Peoples R China Yunnan Minzu Univ Peoples Armed Forces Coll Kunming Yunnan Peoples R China

ISBN: (纸本)9781728186160

With the continuous improvement of information and communication technology, the popularity of mobile terminals and endless new technologies, the application of mobile Internet is increasingly extensive. This paper mainly studies the multi-source data analysis method based on mobile Internet. Through the connection of multi-source database, the data is associated and the foundation of data fusion is constructed. It is stored in the specified storage database or data medium according to certain rules. On this basis, first of all, preprocess the data, sort out and correct those disordered storage formats, disordered data records and redundant fields to form standard data. Secondly, these data are cleaned to remove data redundancy and noise. Through the combination of multi-source data, new data records are obtained, and these data are sorted and improved. According to the actual situation and problems of the project, the multi-source data is fused to build an effective data set. data show that the accuracy of the model can reach more than 85%. The results show that mobile Internet technology can provide security and risk information for the participants of the exhibition.

关键词： Mobile Internet Exhibition Site multi-source data analysis Passenger Flow Evacuation

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Research on the Application of multi-source data analysis for Bridge Safety Monitoring in the Reconstruction and Demolition Process

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BUILDINGS 2022年第8期12卷 1195页

作者： Fu, Meizhen Liang, Yuxiong Feng, Qingsong Wu, Bitao Tang, Guoxi East China Jiaotong Univ Sch Civil Engn & Architecture Nanchang 330013 Jiangxi Peoples R China East China Jiaotong Univ State Key Lab Performance Monitoring Protecting R Nanchang 330013 Jiangxi Peoples R China Anhui Transport Consulting & Design Inst Co Ltd Hefei 530021 Peoples R China

With the increase of bridge-required demolition/dismantling for reconstruction or modification, the early warning of construction emergencies is greatly needed for monitoring the structural safety of bridges under construction. In this paper, based on the multi-source data of nearby construction and demolition construction of a large-span RC arch bridge in China, the Analytic Hierarchy Process (AHP) method is adopted to analyze the multi-source data and set the early warning threshold for bridge safety in construction. According to the analytical results, a reasonable evaluation of AHP factors can improve the accuracy and timeliness of safety early warning in the structural safety monitoring of bridges during the construction process. The weight of the monitoring data in AHP should be assigned according to its reliability, stability, and importance. Bridge safety assessment of nearby construction having harmful vibration should prioritize dynamic bridge monitoring by cooperating with multi-source data, including stress, and deformation monitoring of the bridge is necessary. The assessment results proved that multi-source data, including but not limited to structural stress and deformation monitoring data, vibration data, theoretical prediction data, environment data such as temperature data, and construction/maintenance history data, are necessary for safety monitoring and early warning of construction with specifications related to bridge construction. The early warnings triggered by the evaluation results successfully ensure the safety status of the bridge during nearby construction and demolition construction, which shows the proposed method can provide a guideline for comprehensively evaluating and early warning of the status of bridge construction.

关键词： bridge reconstruction and demolition safety monitoring multi-source data analysis analytic hierarchy process early warning threshold

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Providing personalized learning guidance in MOOCs by multi-source data analysis

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WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS 2019年第3期22卷 1189-1219页

作者： Zhang, Ming Zhu, Jile Wang, Zhuo Chen, Yunfan Peking Univ Sch Elect Engn & Comp Sci Beijing 100871 Peoples R China

Although millions of students have access to varieties of learning materials in Massive Open Online Courses (MOOCs), many of them feel lost or isolated in their learning experience. One of the potential reasons is the lack of interactions and guidance for individuals. Since MOOC students have diverse learning objectives, we propose to design different strategies for those students with different engagement styles. In this paper, we provide personalized learning guidance for MOOC students based on multi-source data analysis. We first conduct content analysis to identify key concepts in the courses. We then propose two structured model to evaluate student knowledge states by their quiz submissions. We also study on student learning behaviors and design a dropout prediction system. The experiments show the effectiveness of our algorithms and we discuss on the result both quantitatively and qualitatively. Last but not least, we employ a Web application of online student assessment service for both students and instructors, in order to display student learning states and provide suggestion for individuals.

关键词： Massive open online courses Personalized guidance multi-source data analysis Web application Student assessment

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Evaluation and maintenance method for general speed railway turnouts based on multi-source data

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CONSTRUCTION AND BUILDING MATERIALS 2024年 451卷

作者： Wang, Pu Yang, Liang Wang, Shuguo Zhang, Huixin Han, Lei Jing, Guoqing China Acad Railway Sci CO Ltd Railway Engn Res Inst Beijing Peoples R China China Acad Railway Sci Grad Dept Beijing Peoples R China Beijing Jiaotong Univ Sch Civil Engn Beijing Peoples R China

In recent years, with the increasing passengers' requirements for safety and comfort, as well as the measures of increasing revenue and reducing the expenditure of railway company, more efficient, more scientific and more comprehensive requirements have been put forward for the maintenance of railway turnouts. This paper develops a maintenance strategy based on the Turnout Service State Indicator (TSSI), derived from an analysis of multi-source data concerning turnout conditions. The weights of critical indicators affecting turnout conditions are determined using Analytical Target Cascading (ATC) and Analytic Hierarchy Process (AHP). Subsequently, turnouts are classified into four categories-great, good, general, and poor-based on their TSSI values, guiding specific maintenance strategies. The proposed assessment method was validated using data from four sets of turnouts collected on actual tracks, showing consistency between the assessment results and field technicians' evaluations. A comparative analysis of the ATC and AHP suggests that the latter provides a more scientific and objective assessment of turnout conditions. The established methods for evaluating the service state and deciding on turnout maintenance actions have been proven feasible and practical through field validation. These methods can be broadly applied to maintain general speed railway turnouts to enhance repair efficiency and reduce maintenance costs.

关键词： Railway turnout maintenance Turnout service state indicator (TSSI) Analytical target cascading (ATC) Analytic hierarchy process (AHP) multi-source data analysis

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Evaluating resilience and risk mitigation strategies in Chinese petrochemical port cities

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INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION 2025年 116卷

作者： Tian, Chuang Liang, Yahui Jin, Xiaoming You, Dongni Lin, Qiaoqiao Dalian Maritime Univ Coll Transportat Engn Dalian Peoples R China Natl Marine Environm Monitoring Ctr Dalian Peoples R China Dalian Maritime Univ Sch Maritime Econ & Management Dalian Peoples R China

This study employed a multi-source data fusion-driven resilience assessment system and a multiscenario simulation framework to analyze the evolution and key determinants of resilience in Chinese petrochemical port cities (PPCs) from 2006 to 2019. The analysis revealed that, aside from Shanghai and Guangzhou, most cities faced significant petrochemical industry risks, high social vulnerability, poor economic resilience, and weak infrastructure recoverability. Effective strategies for enhancing urban resilience included economic diversification and optimizing ecological conditions. multi-scenario simulations indicated that PPCs required 2-7 years to achieve high resilience, with green development models being the fastest. The results suggested that pathway selection was crucial, with environmental and economic costs varying significantly across different development modes. These insights provided valuable guidance for policymakers in managing risks and promoting sustainable development in PPCs.

关键词： Urban resilience Risk mitigation Petrochemical industry Sustainable pathways multi-scenario simulation multi-source data analysis

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Priority Intervention Evaluation of Community Regeneration in Megacities Based on the Business Improvement District (BID) Model: A Case Study of Tianjin, China

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BUILDINGS 2024年第8期14卷 2263页

作者： Bai, Wenjia Chen, Mingyu Bai, Fazhong Huang, Jingtao Tianjin Univ Sch Architecture Tianjin 300072 Peoples R China Delft Univ Technol Fac Architecture & Built Environm NL-2628BL Delft Netherlands

This study aims to start from the macroscale of the megacity, explore a top-down operational technical path from the identification of community regeneration units as the evaluation objects to the BID priority intervention evaluation, and then propose differentiated community regeneration strategies based on the BID model. In the post-epidemic era, it is necessary for global megacities to take new measures in urban regeneration to respond to worldwide changes and challenges. As an innovative tool to promote central city revitalization, the BID model has played an important role in community transformation. In the context of the continuous decentralization of population and industry in China's megacities, it is urgent to explore the technical path to apply the BID model to local community regeneration. Given the shortcomings of existing studies in the method to identify the scope of BID implementation and evaluate intervention priorities, this study takes Tianjin, a megacity in China, as an example and uses DBSCAN (density-based spatial clustering of applications with noise) and service area analysis to define the community regeneration units with commercial agglomeration characteristics as the objects. Then, the BID priority intervention evaluation system is constructed from the two measurement aspects of the intervention potential and the necessity of community regeneration to classify the BID intervention priorities of community regeneration units. The main conclusions are as follows: 1. When the DBSCAN analysis parameters take the minimum number of elements as 30 and the search distance as 120 m, the result is most suitable for identifying community units with commercial agglomeration of the study area;2. Population vitality, especially working and residential population density, is the key factor affecting BID intervention potential, while road network density is an important indicator for determining the necessity of community regeneration;3. Community regenera

关键词： business improvement district urban regeneration older communities multi-source data analysis

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Exploring an Approach on Learning Feedback Strategy in the Metaverse: A Perspective of the Fusion of multi-source data 23

Exploring an Approach on Learning Feedback Strategy in the M...

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Proceedings of the 2023 6th International Conference on E-Business, Information Management and Computer Science

作者： Tinghui Wu Xuesong Zhai Zhejiang University China

ISBN: (纸本)9798400709333

Feedback is widely recognized as a crucial element in promoting the overall quality of education. However, the approach of feedback within the emerging Metaverse remains unclear. This study aims to address this gap by conducting an exploratory investigation into the feedback approach in the Metaverse. By utilizing supplementary log data and eye-tracking data, a feedback framework driven by multiple data sources is proposed. The findings of this study have significant implications for both theoretical and practical research in virtual learning, shedding light on the intricate feedback processes within the Metaverse and its potential to enhance educational practices.

关键词： Eye-tracking technology Feedback Metaverse multi-source data analysis

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Completion of multiview missing data based on multi-manifold regularised non-negative matrix factorisation

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ARTIFICIAL INTELLIGENCE REVIEW 2020年第7期53卷 5411-5428页

作者： Sun Jing-Tao Zhang Qiu-Yu Xian Univ Posts & Telecommun Sch Comp Sci & Technol Xian 710121 Shaanxi Peoples R China Xian Univ Posts & Telecommun Shaanxi Key Lab Network Data Anal & Intelligent P Xian 710121 Shaanxi Peoples R China Lanzhou Univ Technol Sch Comp & Commun Lanzhou 730050 Gansu Peoples R China

In multi-source data analysis, the absence of data values or attributes is inevitably brought about by various influencing factors including environment, which results in the loss of knowledge to be conveyed by data. To solve the problem of missing data in multi-source data analysis, completion method for multiview missing data based on multi-manifold regularized non-negative matrix factorization was proposed in this paper. This method was based on the assumption of consistency of the multiview data and an algorithm of multi-manifold regularized non-negative matrix factorization is adopted to obtain homogeneous manifold and global clustering. On this basis, a multiview synergistic discrimination model is built of the non-missing view that referred to the Gaussian mixture model to pre-mark the clustering that the incremental missing data belonged to. Using the consistency of each view in the low-dimensional space, a prediction model of missing data at the specified view is established using the multiple linear regression technique to achieve accurate data completion under conditions of missing multi-attributes. Through the establishment of data filling model with three handling methods for missing values, namely CMMD-MNMF, FIMUS and Hot deck, the completion performance, clustering performance and classification performance of data sets including UCI, Flower17 and Flower102 are analyzed by simulation experiments. As shown in the results, the method of multi-view data missing completion is verified to be effective.

关键词： multi-source data analysis multiview clustering Missing data completion multi-manifold regularised Non-negative matrix factorisation

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Comparison of Time Metrics in Programming 17

Comparison of Time Metrics in Programming

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13th ACM Conference on International Computing Education Research (ICER)

作者： Leinonen, Juho Leppanen, Leo Ihantola, Petri Hellas, Arto Univ Helsinki Helsinki Finland Tampere Univ Technol Tampere Finland

ISBN: (纸本)9781450349680

Research on the indicators of student performance in introductory programming courses has traditionally focused on individual metrics and specific behaviors. These metrics include the amount of time and the quantity of steps such as code compilations, the number of completed assignments, and metrics that one cannot acquire from a programming environment. However, the differences in the predictive powers of different metrics and the cross-metric correlations are unclear, and thus there is no generally preferred metric of choice for examining time on task or effort in programming. In this work, we contribute to the stream of research on student time on task indicators through the analysis of a multi-source dataset that contains information about students' use of a programming environment, their use of the learning material as well as self-reported data on the amount of time that the students invested in the course and per-assignment perceptions on workload, educational value and difficulty. We compare and contrast metrics from the dataset with course performance. Our results indicate that traditionally used metrics from the same data source tend to form clusters that are highly correlated with each other, but correlate poorly with metrics from other data sources. Thus, researchers should utilize multiple data sources to gain a more accurate picture of students' learning.

关键词： educational data mining academic success prediction time on task time metrics multi-source data analysis

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A GEOGRAPHIC data GATHERING SYSTEM FOR IMAGE GEOLOCALIZATION REFINING 2

A GEOGRAPHIC DATA GATHERING SYSTEM FOR IMAGE GEOLOCALIZATION...

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2nd International Conference on Smart data and Smart Cities

作者： Semaan, B. Servieres, M. Moreau, G. Chebaro, B. UMR 1563 AAU CRENAU Nantes France Lebanese Univ Beirut Lebanon

Image geolocalization has become an important research field during the last decade. This field is divided into two main sections. The first is image geolocalization that is used to find out which country, region or city the image belongs to. The second one is refining image localization for uses that require more accuracy such as augmented reality and three dimensional environment reconstruction using images. In this paper we present a processing chain that gathers geographic data from several sources in order to deliver a better geolocalization than the GPS one of an image and precise camera pose parameters. In order to do so, we use multiple types of data. Among this information some are visible in the image and are extracted using image processing, other types of data can be extracted from image file headers or online image sharing platforms related information. Extracted information elements will not be expressive enough if they remain disconnected. We show that grouping these information elements helps finding the best geolocalization of the image.

关键词： Image Geolocalization Refining Building Detection Semantic data Extraction Geographic data Collection multi-source data analysis

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