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"title": "Using Ptolemy II as a Framework for Virtual Entity Integration and Orchestration in Digital Twins",
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"abstract": "The concept of Digital Twin (DT) is increasingly getting attention due to its support for digital transformation as part of Industry 4.0. A core component of a DT is the virtual entity (VE) that is meant to ‘mirror’ the physical entity (PE). A particular challenge for developing this VE is the integration between the different models that typically make up such a VE. These models, covering different disciplines or aspects of a system, commonly are developed by different engineers and expressed in different formalisms given their strengths and weaknesses. This makes integration between these models and formalisms a challenge. Such integration has two aspects: the communication among the models, and their orchestration, which concerns the order of model step execution and data exchange. In this paper, we consider the suitability of Ptolemy II, an open source framework based on an actor-oriented structure, to implement such integration. We use the Ptolemy II framework to reproduce the implementation of a DT of an autonomous scaled-down truck, which originally required a more manual configuration and execution and was developed in a monolithic way. The results show that Ptolemy II can be used to implement different communication technologies as actors, and show the expressiveness of the orchestrators by reproducing the existing DT’s behavior. This shows Ptolemy II in principle to be suitable as an integration and orchestration tool for models in the context of DTs. As future work, we plan to apply the framework to more complex DTs using different communication technologies, so as to validate its broader suitability for VE orchestration in DTs.",
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"abstract": "Considering the importance of getting the most out of virtual reality (VR) training, we evaluated the use of breaks to reduce virtual reality aftereffects in head-mounted displays. In a crossover design, we compared a 50-minute no-break exposure with an interrupted 50-minute exposure with four 10-minute breaks. Cybersickness, re-action times, workload and spatial learning were measured. Despite device manufacturers recommending breaks to reduce sickness, we found no evidence that breaks can mitigate aftereffects. Introducing breaks may also impact performance and logistical costs for training.",
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"proceeding": {
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"title": "2021 Tenth International Conference of Educational Innovation through Technology (EITT)",
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"doi": "10.1109/EITT53287.2021.00028",
"title": "Promoting Junior School Students' Spatial Ability through 3D Printing",
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"abstract": "Spatial ability is an important part of human intelligence, which plays an important role in promoting STEM learning and career choice. In order to explore the promotion mechanism of 3D printing technology on spatial ability, this study designs and develops a “STEM Teaching Implementation Model Integrating 3D Printing” based on the CDIO. To examine the effect of the new model, a quasi-experimental method is conducted. 45 junior middle school students were divided into an experimental group and a control group and received traditional 3D printing teaching and 3D printing teaching based on the CDIO model respectively. The spatial ability of students and artifacts were evaluated, accompanied by semi-structured interviews. The results show that the 3D printing teaching based on CDIO significantly enhances the spatial ability of junior middle school students, especially the more complex spatial visualization ability; And the promotion effect on girls is more significant. The study suggests that teachers can adopt individualized teaching methods in face-to-face and in the online environment to improve the effective and all-around development of students' spatial ability.",
"abstracts": [
{
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"content": "Spatial ability is an important part of human intelligence, which plays an important role in promoting STEM learning and career choice. In order to explore the promotion mechanism of 3D printing technology on spatial ability, this study designs and develops a “STEM Teaching Implementation Model Integrating 3D Printing” based on the CDIO. To examine the effect of the new model, a quasi-experimental method is conducted. 45 junior middle school students were divided into an experimental group and a control group and received traditional 3D printing teaching and 3D printing teaching based on the CDIO model respectively. The spatial ability of students and artifacts were evaluated, accompanied by semi-structured interviews. The results show that the 3D printing teaching based on CDIO significantly enhances the spatial ability of junior middle school students, especially the more complex spatial visualization ability; And the promotion effect on girls is more significant. The study suggests that teachers can adopt individualized teaching methods in face-to-face and in the online environment to improve the effective and all-around development of students' spatial ability.",
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"Data Visualisation",
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"affiliation": "(of Southwest University),Center for Studies of Education and Psychology of Ethnic Minorities In Southwest China,Chongqing,China",
"fullName": "Lin Wang",
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"affiliation": "(of Southwest University),Center for Studies of Education and Psychology of Ethnic Minorities In Southwest China,Chongqing,China",
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"affiliation": "(of Southwest University),Center for Studies of Education and Psychology of Ethnic Minorities In Southwest China,Chongqing,China",
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"affiliation": "(of Southwest University),Center for Studies of Education and Psychology of Ethnic Minorities In Southwest China,Chongqing,China",
"fullName": "XinShan Zhou",
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"affiliation": "(of Southwest University),Center for Studies of Education and Psychology of Ethnic Minorities In Southwest China,Chongqing,China",
"fullName": "ChunJie Yin",
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{
"affiliation": "Shaanxi Normal University,(of Department of education) Department of Educational Technology,Xi'an,China",
"fullName": "HongLiang Ma",
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"proceeding": {
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"title": "2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC)",
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"title": "Application and Research of Image-Based Modeling and 3D Printing Technology in Intangible Cultural Heritage Quanzhou Marionette Protection",
"normalizedTitle": "Application and Research of Image-Based Modeling and 3D Printing Technology in Intangible Cultural Heritage Quanzhou Marionette Protection",
"abstract": "We present a practical solution to the modeling improvements for Quanzhou Marionette in 3D printing. We use 3D printing technology to improve the marionette production process. We have completed rapid image-based modeling to aid in design. According to the actual situation, the special parts such as marionette heads and joints are modeled and improved. The experiment proves the advantages of 3D printing in marionette production. 3D printing can be used as a production tool method for the protection and inheritance of intangible cultural heritage.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present a practical solution to the modeling improvements for Quanzhou Marionette in 3D printing. We use 3D printing technology to improve the marionette production process. We have completed rapid image-based modeling to aid in design. According to the actual situation, the special parts such as marionette heads and joints are modeled and improved. The experiment proves the advantages of 3D printing in marionette production. 3D printing can be used as a production tool method for the protection and inheritance of intangible cultural heritage.",
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"normalizedAbstract": "We present a practical solution to the modeling improvements for Quanzhou Marionette in 3D printing. We use 3D printing technology to improve the marionette production process. We have completed rapid image-based modeling to aid in design. According to the actual situation, the special parts such as marionette heads and joints are modeled and improved. The experiment proves the advantages of 3D printing in marionette production. 3D printing can be used as a production tool method for the protection and inheritance of intangible cultural heritage.",
"fno": "260701a914",
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"Computer Graphics",
"History",
"Image Processing",
"Three Dimensional Printing",
"Image Based Modeling",
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"Computational Modeling",
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"Marionette",
"3 D Printing",
"Image Based Modeling"
],
"authors": [
{
"affiliation": "Xiamen University, China",
"fullName": "Chao Gao",
"givenName": "Chao",
"surname": "Gao",
"__typename": "ArticleAuthorType"
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{
"affiliation": "Xiamen University, China",
"fullName": "Junfeng Yao",
"givenName": "Junfeng",
"surname": "Yao",
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{
"affiliation": "Xiamen University, China",
"fullName": "Kaini Huang",
"givenName": "Kaini",
"surname": "Huang",
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{
"affiliation": "Kennesaw State University, USA",
"fullName": "Kai Qian",
"givenName": "Kai",
"surname": "Qian",
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"proceeding": {
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"title": "2020 3rd International Conference on Electron Device and Mechanical Engineering (ICEDME)",
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"doi": "10.1109/ICEDME50972.2020.00099",
"title": "Study on modification process of fly ash used to fill ABS 3D printing prototype",
"normalizedTitle": "Study on modification process of fly ash used to fill ABS 3D printing prototype",
"abstract": "Modified fly ash was prepared by being mixed with silane coupling agent under different conditions. And modified fly ash filled Acrylonitrile Butadiene Styrene (ABS) wires were prepared. Then impact and tensile specimens were three dimensional (3D) printed from modified fly ash filled ABS wires. Results show that, modification process parameters do affect properties of modified fly ash filled ABS. And there seems to be a contradiction between tensile strength and impact strength. Fly ash should be modified at 60°Cof temperature, 30min of stirring time and 160r/min of stirring speed. And at this process condition, modified fly ash filled ABS 3D printing prototype exhibits a better property.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Modified fly ash was prepared by being mixed with silane coupling agent under different conditions. And modified fly ash filled Acrylonitrile Butadiene Styrene (ABS) wires were prepared. Then impact and tensile specimens were three dimensional (3D) printed from modified fly ash filled ABS wires. Results show that, modification process parameters do affect properties of modified fly ash filled ABS. And there seems to be a contradiction between tensile strength and impact strength. Fly ash should be modified at 60°Cof temperature, 30min of stirring time and 160r/min of stirring speed. And at this process condition, modified fly ash filled ABS 3D printing prototype exhibits a better property.",
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"normalizedAbstract": "Modified fly ash was prepared by being mixed with silane coupling agent under different conditions. And modified fly ash filled Acrylonitrile Butadiene Styrene (ABS) wires were prepared. Then impact and tensile specimens were three dimensional (3D) printed from modified fly ash filled ABS wires. Results show that, modification process parameters do affect properties of modified fly ash filled ABS. And there seems to be a contradiction between tensile strength and impact strength. Fly ash should be modified at 60°Cof temperature, 30min of stirring time and 160r/min of stirring speed. And at this process condition, modified fly ash filled ABS 3D printing prototype exhibits a better property.",
"fno": "09122177",
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"Fly Ash",
"Impact Strength",
"Recycling",
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"Stirring Speed",
"Stirring Time",
"Fly Ash Filled ABS Wires",
"Modification Process Parameter",
"Three Dimensional Printing",
"Impact Strength",
"Tensile Strength",
"Silane Coupling Agent",
"Acrylonitrile Butadiene Styrene Wires",
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"Temperature 60 0 Deg C",
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"authors": [
{
"affiliation": "Heyuan Polytechnic,Mechanical and Electrical Engineering College,Heyuan,China,517000",
"fullName": "YE Xuan",
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"affiliation": "Heyuan Polytechnic,Mechanical and Electrical Engineering College,Heyuan,China,517000",
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"affiliation": "Heyuan Polytechnic,Mechanical and Electrical Engineering College,Heyuan,China,517000",
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"content": "In recent years, personal genomic data can be quickly generated in an affordable price. Abundant research results on genetic diseases have also been published in the past two decade. Therefore, it is desired to utilize updated genetic disease research results into personal genomic data analysis and apply them into genomics-based personalized healthcare. However, this is a challenging task for current healthcare professionals because the desired clinically relevant information is hidden in highly complex genomics data sets and in various types of databases, which were typically created for genomics researchers in the past. In this project, an integrated patient genomic information analysis and management system is created for healthcare professionals, especially physicians, so that they can conveniently access the desired patient genetic information and current research results related to the genetic makeup, and utilize the information in personalized healthcare practice. The accuracy of the data integrated in the system and analysis results from the system were evaluated and a usability study was conducted to determine the usability of the system by physicians. These evaluations indicated that the results obtained in this system were the same as the ones obtained from a manual but more tedious approach, and physicians could easily finish all the designed tasks and obtain desired data using the system.",
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"abstract": "The human genome uniquely identifies, and contains highly sensitive information about, individuals. This creates a high potential for misuse of genomic data (e.g., Genetic discrimination). This paper investigates how genomic privacy can be measured in scenarios where an adversary aims to infer a person's genome by constructing probability distributions on the values of genetic variations. Specifically, we investigate 22 privacy metrics using adversaries of different strengths, and uncover problems with several metrics that have previously been used for genomic privacy. We then give suggestions on metric selection, and illustrate the process with a case study on Alzheimer's disease.",
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"abstract": "Recently, various works that attempted to introduce rotation invariance to point cloud analysis have devised point-pair features, such as angles and distances. In these methods, however, the point-pair is only comprised of the center point and its adjacent points in a vicinity, which may bring information loss to the local feature representation. In this paper, we instead connect each point densely with all other points in a local neighborhood to compose the point-pairs. Specifically, we present a simple but effective local feature representation, called sorted Gram matrix(SGM), which is not only invariant to arbitrary rotations, but also models the pair-wise relationship of all the points in a neighbor-hood. In more detail, we utilize vector inner product to model distance- and angle-information between two points, and in a local patch it naturally forms a Gram matrix. In order to guarantee permutation invariance, we sort the correlation value in Gram matrix for each point, therefore this geometric feature names sorted Gram matrix. Furthermore, we mathematically prove that the Gram matrix is rotation-invariant and sufficient to model the inherent structure of a point cloud patch. We then use SGM as features in convolution, which can be readily integrated as a drop-in module into any point-based networks. Finally, we evaluated the proposed method on two widely used datasets, and it outperforms previous state-of-the-arts on both shape classification and part segmentation tasks by a large margin.",
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"abstract": "Simple presentation graphics are intuitive and easy-to-use, but show only highly aggregated data and present only a very limited number of data values (as in the case of bar charts). In addition, these graphics may have a high degree of overlap which may occlude a significant portion of the data values (as in the case of the x-y plots). In this paper, we therefore propose a generalization of traditional bar charts and x-y-plots which allows the visualization of large amounts of data. The basic idea is to use the pixels within the bars to present the detailed information of the data records. Our so-called pixel bar charts retain the intuitiveness of traditional bar charts while allowing very large data sets to be visualized in an effective way. We show that, for an effective pixel placement, we have to solve complex optimization problems, and present an algorithm which efficiently solves the problem. Our application using real-world e-commerce data shows the wide applicability and usefulness of our new idea.",
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"affiliation": "University of Constance",
"fullName": "Daniel Keim",
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"abstract": "Pie charts were first published in 1801 by William Playfair and have caused some controversy since. Despite the suggestions of many experts against their use, several empirical studies have shown that pie charts are at least as good as alternatives. From Brinton to Few on one side and Eells to Kosara on the other, there appears to have been a hundred-year war waged on the humble pie. In this paper a set of experiments are reported that compare the performance of pie charts and horizontal bar charts with various visual cues. Amazon's Mechanical Turk service was employed to perform the tasks of estimating segments in various part-to-whole charts. The results lead to recommendations for data visualization professionals in developing dashboards.",
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"abstract": "Anomaly detection is a common analytical task that aims to identify rare cases that differ from the typical cases that make up the majority of a dataset. When applied to the analysis of event sequence data, the task of anomaly detection can be complex because the sequential and temporal nature of such data results in diverse definitions and flexible forms of anomalies. This, in turn, increases the difficulty in interpreting detected anomalies. In this paper, we propose an unsupervised anomaly detection algorithm based on Variational AutoEncoders (VAE) to estimate underlying normal progressions for each given sequence represented as occurrence probabilities of events along the sequence progression. Events in violation of their occurrence probability are identified as abnormal. We also introduce a visualization system, EventThread3 (ET<sup>3</sup>, to support interactive exploration and interpretations of anomalies within the context of normal sequence progressions in the dataset through comprehensive one-to-many sequence comparison. Finally, we quantitatively evaluate the performance of our anomaly detection algorithm and demonstrate the effectiveness of our system through a case study.",
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"content": "Anomaly detection is a common analytical task that aims to identify rare cases that differ from the typical cases that make up the majority of a dataset. When applied to the analysis of event sequence data, the task of anomaly detection can be complex because the sequential and temporal nature of such data results in diverse definitions and flexible forms of anomalies. This, in turn, increases the difficulty in interpreting detected anomalies. In this paper, we propose an unsupervised anomaly detection algorithm based on Variational AutoEncoders (VAE) to estimate underlying normal progressions for each given sequence represented as occurrence probabilities of events along the sequence progression. Events in violation of their occurrence probability are identified as abnormal. We also introduce a visualization system, EventThread3 (ET<sup>3</sup>, to support interactive exploration and interpretations of anomalies within the context of normal sequence progressions in the dataset through comprehensive one-to-many sequence comparison. Finally, we quantitatively evaluate the performance of our anomaly detection algorithm and demonstrate the effectiveness of our system through a case study.",
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"authors": [
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"affiliation": "East China Normal University,Department of Software Engineering",
"fullName": "Shunan Guo",
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"affiliation": "Tongji University,College of Design and Innovation",
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"affiliation": "Tongji University,College of Design and Innovation",
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"affiliation": "University of North Carolina at Chapel Hill,School of Information and Library Science",
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"affiliation": "Tongji University,College of Design and Innovation",
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"abstract": "Timely automatic detection of anomalies like road accidents forms the key to any intelligent traffic monitoring system. In this paper, we propose a novel Fractional Data Distillation model for segregating traffic anomaly videos from a test dataset, with a precise estimation of the start time of the anomalous event. The model follows a similar approach to that of the typical fractional distillation procedure, where the compounds are separated by varying the temperature. Our model fractionally extracts the anomalous events depending on their nature as the detection process progresses. Here, we employ two anomaly extractors namely Normal and Zoom, of which former works on the normal scale of video and the latter works on the magnified scale on the videos missed by the former, to separate the anomalies. The backbone of this segregation is scanning the background frames using the YOLOv3 detector for spotting possible anomalies. These anomaly candidates are further filtered and compared with detection on the foreground for matching detections to estimate the start time of the anomalous event. Experimental validation on track 4 of 2020 AI City Challenge shows an s4 score of 0.5438, with an F<sub>1</sub> score of 0.7018.",
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"content": "Multi-body collision detection is a key and impor-tant technology in societies of computer graphics, system simu-lation, virtual reality, etc, and has been widely used in various applications. To deal with the collision problems in large scale multi-body simulations robustly and efficiently, we in this paper proposed a robust and efficient algorithm of continuous multi-body collision detection based on the kinetic \"Sweep and Prune\" (SaP) technique and the event-driven mechanism. Our algorithm first culls redundant detection calculations among very large numbers of moving bodies, and then automatically generates events to predict these collisions, probably taken place in coming time, of the object pairs. All these events are been pushed into a priority queue, which is used to drive our algorithm to run. By introducing a new hybrid bounding box hierarchy in the event processing process, our algorithm can detect positions where the object pairs collide. We discovered the event blocking problem potentially occurred during event processing, and further proposed several methods to alarm or relieve the system from the event blocking state. Experimental results show that our algorithm has good stability and strong robustness, and it can improve the speed and accuracy of the multi-body collision detection effectively.",
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"abstract": "To better capture the shapes as well as the rich dynamics of hair, image based modelling techniques have been developed for reconstructing their 3D geometry and important visual features. Most hair images contain inevitable noises which impair reconstructed hair models. Therefore we propose to pre-process hair images and provide an orientation map of hair strands to enhance the follow-on modelling. To demonstrate the usage of pre-processing techniques, we apply our pre-processing results for bas-relief stylisation and modelling of hair from image inputs. We compare different techniques to estimate hair orientations, adopting four types of filter mechanisms. Our analysis of their performance sheds insight on designing a suitable pre-processing technique for hair reconstruction from images. Several examples of bas-relief creation validate the effectiveness of the proposed approach.",
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"content": "To better capture the shapes as well as the rich dynamics of hair, image based modelling techniques have been developed for reconstructing their 3D geometry and important visual features. Most hair images contain inevitable noises which impair reconstructed hair models. Therefore we propose to pre-process hair images and provide an orientation map of hair strands to enhance the follow-on modelling. To demonstrate the usage of pre-processing techniques, we apply our pre-processing results for bas-relief stylisation and modelling of hair from image inputs. We compare different techniques to estimate hair orientations, adopting four types of filter mechanisms. Our analysis of their performance sheds insight on designing a suitable pre-processing technique for hair reconstruction from images. Several examples of bas-relief creation validate the effectiveness of the proposed approach.",
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"fullName": "Wenshu Zhang",
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"fullName": "Jian Chang",
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{
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"abstract": "Virtual tourism is a novel trend that enhances the experience the users perceive from touristic places, such as archaeological sites. Drones are equipped with 360° video cameras and used for video capturing of the heritage sites. The video material is streamed to the users in real time, enriched with additional 3D, Augmented Reality (AR) or Mixed Reality (MR) material. Furthermore, the selection of the appropriate flying route for each drone should be performed, in order to provide a satisfactory tour experience to the user, considering his preferences about specific monuments. To address this issue, this paper describes a heritage route selection scheme for supporting real-time virtual tours in sites with cultural interest using drones. The proposed scheme applies a Fuzzy Multiple Attribute Decision Making (FMADM) algorithm, the Trapezoidal Fuzzy Topsis for Heritage Route Selection (TFT-HRS), to accomplish the ranking of the candidate heritage routes. The algorithm uses Interval-Valued Trapezoidal Fuzzy Numbers (IVTFN) for the representation of heritage routes evaluation values. Performance evaluation shows that the suggested method produces better results compared to the Fuzzy Topsis (FTOPSIS) by selecting the most appropriate flying route for the drone.",
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"title": "2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)",
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"title": "A Novel FCA-Based Method for Mining the Attribute Dependence of Different Granularities from Real Estate Data",
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"abstract": "Association rules among properties are common knowledge patterns, which can often provide potential and useful information. Formal concept analysis(FCA) is an approach to identify conceptual structures among relational data sets, which is a very useful clustering technique providing a formal framework to explore the relationship among the objects and attributes. This paper provides a FCA-based method for mining the intrinsic relationships among real estate data such as the price and sales rate, which can help users discover hidden patterns and meet different degrees of users requirements. There are two contributions as follows: 1) in order to describe the attribute-values in different granularities, a method is proposed, which is an important basis for attribute dependence; 2) a visualization method is provided, which can help buyers analyze the real estate data. The experimental results show that the proposed methods improved quality and relevance of association rules.",
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"content": "Association rules among properties are common knowledge patterns, which can often provide potential and useful information. Formal concept analysis(FCA) is an approach to identify conceptual structures among relational data sets, which is a very useful clustering technique providing a formal framework to explore the relationship among the objects and attributes. This paper provides a FCA-based method for mining the intrinsic relationships among real estate data such as the price and sales rate, which can help users discover hidden patterns and meet different degrees of users requirements. There are two contributions as follows: 1) in order to describe the attribute-values in different granularities, a method is proposed, which is an important basis for attribute dependence; 2) a visualization method is provided, which can help buyers analyze the real estate data. The experimental results show that the proposed methods improved quality and relevance of association rules.",
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"Data Mining",
"Formal Concept Analysis",
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"Association Rules",
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"Intrinsic Relationships",
"Sales Rate",
"Hidden Patterns",
"Users Requirements",
"Attribute Values",
"Visualization Method",
"Lattices",
"Data Mining",
"Data Visualization",
"Education",
"Cultural Differences",
"Image Color Analysis",
"Knowledge Discovery",
"Formal Concept Analysis",
"Association Rules",
"Knowledge Granularity",
"Real Estate Data"
],
"authors": [
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"affiliation": "Rizhao Polytechnic",
"fullName": "Jingying Tian",
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"title": "2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)",
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"title": "Research on the Development of Virtual Pavilion Based on Virtual Reality",
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"abstract": "Virtual Reality (VR) is today's cutting-edge technology and an emerging force driving economic, social and cultural development. VR technology builds virtual pavilions through computer-based collaboration, multi-channel user interface, 3D human-computer interaction, simulation system and other technical means to provide immersive, interactive, multi-perceive and all-round, multi-angle The viewing experience allows the audience to experience the most authentic feelings in the virtual pavilion environment. Compared with the traditional pavilion, the virtual pavilion has a huge technical advantage from static to dynamic, from single to multiple, from passive to interactive, and from offline to online. This paper analyzes the basic characteristics of VR technology such as immersion, interactivity and conception, and expounds the development status of virtual pavilion based on VR technology, pointing out that hardware technology needs to be improved, and the technology is still immature in the protection and development of non-legacy culture. In the commercial product display design and production, the cost is higher, the content is more single and so on. To comprehensively analyze the above problems, propose the path of virtual pavilion construction, such as: \"people-oriented\" design concept, technology and art integration, establish dynamic environment, real-time three-dimensional image generation and display, research and development of new interactive equipment, intelligent voice development, use Large-scale distributed network virtual reality, etc., and pointed out the future development trend of virtual pavilion immersed, interactive, information, and convenient, the theme and content of its exhibition will have a profound impact on people's thoughts and behaviors and lifestyle.",
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"content": "Virtual Reality (VR) is today's cutting-edge technology and an emerging force driving economic, social and cultural development. VR technology builds virtual pavilions through computer-based collaboration, multi-channel user interface, 3D human-computer interaction, simulation system and other technical means to provide immersive, interactive, multi-perceive and all-round, multi-angle The viewing experience allows the audience to experience the most authentic feelings in the virtual pavilion environment. Compared with the traditional pavilion, the virtual pavilion has a huge technical advantage from static to dynamic, from single to multiple, from passive to interactive, and from offline to online. This paper analyzes the basic characteristics of VR technology such as immersion, interactivity and conception, and expounds the development status of virtual pavilion based on VR technology, pointing out that hardware technology needs to be improved, and the technology is still immature in the protection and development of non-legacy culture. In the commercial product display design and production, the cost is higher, the content is more single and so on. To comprehensively analyze the above problems, propose the path of virtual pavilion construction, such as: \"people-oriented\" design concept, technology and art integration, establish dynamic environment, real-time three-dimensional image generation and display, research and development of new interactive equipment, intelligent voice development, use Large-scale distributed network virtual reality, etc., and pointed out the future development trend of virtual pavilion immersed, interactive, information, and convenient, the theme and content of its exhibition will have a profound impact on people's thoughts and behaviors and lifestyle.",
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"affiliation": "Changsha University of Science & Technology",
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"doi": "10.1109/ICCST53801.2021.00023",
"title": "Research on virtual competitive form based on E-sports games",
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"abstract": "E-sports is a new kind of virtual competition between people playing electronic games. In recent years, E-sports players and audiences have continued to grow, and the scale of E-sports competitions has evolved from simple single or double player confrontations to an official event in the Asian Games. The influence of E-sports is increasing daily on a global scale, and the huge economic value it brings is also favored by investors. E-sports has gradually formed a large-scale industrial chain and it is becoming an important sector in the field of science and technology that is also culturally oriented. This article aims to study the characteristics and elements of E-sports, and put forward some suggestions and conclusions for the E-sports industry based on in-depth analysis.",
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"authors": [
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"affiliation": "E-sports college Communication University of China,Nanjing,Nanjing,China",
"fullName": "Xiao Gong",
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"affiliation": "University of South China,Solex School of Design and Art,Hengyang,China",
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"affiliation": "E-sports college Communication University of China,Nanjing,Nanjing,China",
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{
"affiliation": "E-sports college Communication University of China,Nanjing,Nanjing,China",
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"abstract": "Currently, the most common way to control an electric wheelchair is to use joystick. However, there are some individuals unable to operate joystick-driven electric wheelchairs due to sever physical disabilities, like quadriplegia patients. This paper proposes a novel head pose estimation method to assist such patients. Head motion parameters are employed to control and drive an electric wheelchair. We introduce a direct method for estimating user head motion, based on a sequence of range images captured by Kinect. In this work, we derive new version of the optical flow constraint equation for range images. We show how the new equation can be used to estimate head motion directly. Experimental results reveal that the proposed system works with high accuracy in real-time. We also show simulation results for navigating the electric wheelchair by recovering user head motion.",
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"content": "Currently, the most common way to control an electric wheelchair is to use joystick. However, there are some individuals unable to operate joystick-driven electric wheelchairs due to sever physical disabilities, like quadriplegia patients. This paper proposes a novel head pose estimation method to assist such patients. Head motion parameters are employed to control and drive an electric wheelchair. We introduce a direct method for estimating user head motion, based on a sequence of range images captured by Kinect. In this work, we derive new version of the optical flow constraint equation for range images. We show how the new equation can be used to estimate head motion directly. Experimental results reveal that the proposed system works with high accuracy in real-time. We also show simulation results for navigating the electric wheelchair by recovering user head motion.",
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"affiliation": "KTH Royal Institute of Technology, Stockholm, Sweden",
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"proceeding": {
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"title": "2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA)",
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"title": "An extended Eye Movement Tracker system for an electric wheelchair movement control",
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"abstract": "To compensate the incapability of severely disabled person, intelligent wheelchairs are commonly adopted using several non manual command techniques. Eye tracking is one of such techniques. Although it has been the subject of intense research for many years, Eye tracking has not yet reached the level of perfection to be commercially used in an intelligent wheelchair to control electrical powered wheelchairs (EPW). This paper presents an eye tracking system based on fuzzy logic controller to control an EPW with a simple web cam placed in front of the user. Simulation results indicate that the fuzzy logic controller gives better results compared to other techniques.",
"abstracts": [
{
"abstractType": "Regular",
"content": "To compensate the incapability of severely disabled person, intelligent wheelchairs are commonly adopted using several non manual command techniques. Eye tracking is one of such techniques. Although it has been the subject of intense research for many years, Eye tracking has not yet reached the level of perfection to be commercially used in an intelligent wheelchair to control electrical powered wheelchairs (EPW). This paper presents an eye tracking system based on fuzzy logic controller to control an EPW with a simple web cam placed in front of the user. Simulation results indicate that the fuzzy logic controller gives better results compared to other techniques.",
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"normalizedAbstract": "To compensate the incapability of severely disabled person, intelligent wheelchairs are commonly adopted using several non manual command techniques. Eye tracking is one of such techniques. Although it has been the subject of intense research for many years, Eye tracking has not yet reached the level of perfection to be commercially used in an intelligent wheelchair to control electrical powered wheelchairs (EPW). This paper presents an eye tracking system based on fuzzy logic controller to control an EPW with a simple web cam placed in front of the user. Simulation results indicate that the fuzzy logic controller gives better results compared to other techniques.",
"fno": "07507101",
"keywords": [
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"Control Engineering Computing",
"Digital Simulation",
"Fuzzy Control",
"Gaze Tracking",
"Handicapped Aids",
"Intelligent Control",
"Medical Control Systems",
"Motion Control",
"Wheelchairs",
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"Electric Wheelchair Movement Control",
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"authors": [
{
"affiliation": "Ecole Nationale d'Ingénieurs de Sfax, Université de Sfax, Tunisia",
"fullName": "Fatma Ben Taher",
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{
"affiliation": "Ecole Nationale d'Ingénieurs de Sfax, Université de Sfax, Tunisia",
"fullName": "Nader Ben Amor",
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{
"affiliation": "Ecole Nationale d'Ingénieurs de Sfax, Université de Sfax, Tunisia",
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"proceeding": {
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"title": "2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
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"doi": "10.1109/VR.2018.8446345",
"title": "Investigating a Sparse Peripheral Display in a Head-Mounted Display for VR Locomotion",
"normalizedTitle": "Investigating a Sparse Peripheral Display in a Head-Mounted Display for VR Locomotion",
"abstract": "Head-Mounted Displays (HMDs) provide immersive experiences for virtual reality. However, their field of view (FOV) is still relatively small compared to the human eye, which adding sparse peripheral displays (SPDs) could address. We designed a new SPD, SparseLightVR2, which increases the HMD's FOV to 180° horizontally. We evaluated SparseLightVR2 with a study (N=29) by comparing three conditions: 1) no SPD, where the peripheral display (PD) was inactive; 2) extended SPD, where the PD provided visual cues consistent with and extending the HMD's main screen; and 3) counter-vection SPD, where the PD's visuals were flipped horizontally during VR travel to provide optic flow in the opposite direction of the travel. The participants experienced passive motion on a linear path and reported introspective measures such as sensation of self-motion. Results showed, compared to no SPD, both extended and counter-vection SPDs provided a more natural experience of motion, while extended SPD also enhanced vection intensity and believability of movement. Yet, visually induced motion sickness (VIMS) was not affected by display condition. To investigate the reason behind these non-significant results, we conducted a follow-up study and had users increase peripheral counter-vection visuals on the central HMD screen until they nulled out vection. Our results suggest extending HMDs through SPDs enhanced vection, naturalness, and believability of movement without enhancing VIMS, but reversed SPD motion cues might not be strong enough to reduce vection and VIMS.",
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"content": "Head-Mounted Displays (HMDs) provide immersive experiences for virtual reality. However, their field of view (FOV) is still relatively small compared to the human eye, which adding sparse peripheral displays (SPDs) could address. We designed a new SPD, SparseLightVR2, which increases the HMD's FOV to 180° horizontally. We evaluated SparseLightVR2 with a study (N=29) by comparing three conditions: 1) no SPD, where the peripheral display (PD) was inactive; 2) extended SPD, where the PD provided visual cues consistent with and extending the HMD's main screen; and 3) counter-vection SPD, where the PD's visuals were flipped horizontally during VR travel to provide optic flow in the opposite direction of the travel. The participants experienced passive motion on a linear path and reported introspective measures such as sensation of self-motion. Results showed, compared to no SPD, both extended and counter-vection SPDs provided a more natural experience of motion, while extended SPD also enhanced vection intensity and believability of movement. Yet, visually induced motion sickness (VIMS) was not affected by display condition. To investigate the reason behind these non-significant results, we conducted a follow-up study and had users increase peripheral counter-vection visuals on the central HMD screen until they nulled out vection. Our results suggest extending HMDs through SPDs enhanced vection, naturalness, and believability of movement without enhancing VIMS, but reversed SPD motion cues might not be strong enough to reduce vection and VIMS.",
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"Virtual Reality",
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],
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"affiliation": "Simon Fraser University, School of Interactive Arts + Technology, Vancouver, CANADA",
"fullName": "Abraham M. Hashemian",
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"affiliation": "Simon Fraser University, School of Interactive Arts + Technology, Vancouver, CANADA",
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"surname": "Kitson",
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"affiliation": "Simon Fraser University, School of Interactive Arts + Technology, Vancouver, CANADA",
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"affiliation": "Microsoft Research",
"fullName": "Hrvoje Benko",
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"affiliation": "Simon Fraser University, School of Interactive Arts + Technology, Vancouver, CANADA",
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"affiliation": "Simon Fraser University, School of Interactive Arts + Technology, Vancouver, CANADA",
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"abstract": "Shooter bias has been extensively studied in desktop environments, however research in more immersive environments is lacking. We evaluated the effects of target race and perceived socioeconomic status using a 2(target race: Black or White) x2(target SES: low or high) x2(target object: gun or cellphone) within-subjects design. Participants (N=50) completed 160 trials. We found evidence that shooter bias exists in virtual reality. More data is needed to strengthen conclusions. Virtual reality fills an important gap in shooter bias research, as it increases the realism of the task and provides a potential avenue for police training.",
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"abstract": "As one of the Minimally Invasive Surgery (MIS), laparoscopy is widely applied in gastrointestinal surgery. Benefits from its minimally invasive procedure and fast postoperative rehabilitation for patients. However, it is a huge challenge for surgeons to operate slender surgical instruments under a limited field of view taken by laparoscopy which requires the surgeon to have rich surgical experience. In laparoscopic surgeries, an accurate 3D reconstruction mode with internal anatomy structure and laparoscopic positions in the abdominal cavity can effectively help the surgeon to reduce the dependence on surgical experience. In addition, reconstructing the structure of the surgical scene is also a key step for data registration in surgical navigation and augmented reality surgery. In this paper, a novel Simultaneous Localization and Mapping (SLAM) method based on feature patch tracking by Kernel Correlation Filter (KCF) is proposed for 3D dense point clouds reconstruction, which is called KCF-SLAM. It reconstructs the laparoscopic surgery scene accurately and densely under stereo laparoscopic conditions. The proposed method is validated on a public in-vivo data set captured by a stereo laparoscope. Compared with the feature-based SLAM, the proposed method can work efficiently when the image texture is missing or insignificant. The results suggest that the proposed method can reconstruct the dense point cloud of laparoscopic scene stably and accurately.",
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"content": "As one of the Minimally Invasive Surgery (MIS), laparoscopy is widely applied in gastrointestinal surgery. Benefits from its minimally invasive procedure and fast postoperative rehabilitation for patients. However, it is a huge challenge for surgeons to operate slender surgical instruments under a limited field of view taken by laparoscopy which requires the surgeon to have rich surgical experience. In laparoscopic surgeries, an accurate 3D reconstruction mode with internal anatomy structure and laparoscopic positions in the abdominal cavity can effectively help the surgeon to reduce the dependence on surgical experience. In addition, reconstructing the structure of the surgical scene is also a key step for data registration in surgical navigation and augmented reality surgery. In this paper, a novel Simultaneous Localization and Mapping (SLAM) method based on feature patch tracking by Kernel Correlation Filter (KCF) is proposed for 3D dense point clouds reconstruction, which is called KCF-SLAM. It reconstructs the laparoscopic surgery scene accurately and densely under stereo laparoscopic conditions. The proposed method is validated on a public in-vivo data set captured by a stereo laparoscope. Compared with the feature-based SLAM, the proposed method can work efficiently when the image texture is missing or insignificant. The results suggest that the proposed method can reconstruct the dense point cloud of laparoscopic scene stably and accurately.",
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"normalizedAbstract": "As one of the Minimally Invasive Surgery (MIS), laparoscopy is widely applied in gastrointestinal surgery. Benefits from its minimally invasive procedure and fast postoperative rehabilitation for patients. However, it is a huge challenge for surgeons to operate slender surgical instruments under a limited field of view taken by laparoscopy which requires the surgeon to have rich surgical experience. In laparoscopic surgeries, an accurate 3D reconstruction mode with internal anatomy structure and laparoscopic positions in the abdominal cavity can effectively help the surgeon to reduce the dependence on surgical experience. In addition, reconstructing the structure of the surgical scene is also a key step for data registration in surgical navigation and augmented reality surgery. In this paper, a novel Simultaneous Localization and Mapping (SLAM) method based on feature patch tracking by Kernel Correlation Filter (KCF) is proposed for 3D dense point clouds reconstruction, which is called KCF-SLAM. It reconstructs the laparoscopic surgery scene accurately and densely under stereo laparoscopic conditions. The proposed method is validated on a public in-vivo data set captured by a stereo laparoscope. Compared with the feature-based SLAM, the proposed method can work efficiently when the image texture is missing or insignificant. The results suggest that the proposed method can reconstruct the dense point cloud of laparoscopic scene stably and accurately.",
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"abstract": "Recently, people are increasingly pursuing more accurate machine learning systems. At the same time, the problem is that it is difficult for people to understand the internal logical structure of the system, and the machine learning model has become a black box. Lack of explanation is not only a practical problem, but also an ethical problem. At this point, understanding why a model makes a prediction is as important as the accuracy of the prediction. In order to balance the interpretability and accuracy of the model, many experts and scholars have done a lot of research on improving the interpretability of machine learning model, improved the interpretability of the model from different dimensions, and created a series of interpretable methods to help users understand the internal logic of the system and make the black box transparent. However, the current interpretability research is still in the stage of development, and there is no completely unified interpretable method at present. In this paper, firstly, the development status of machine learning and the importance of interpretable learning are discussed. Then, according to the current research status, interpretable methods are introduced from interpretable models and model independent categories, the research and application in the field of interpretability are discussed, and the current challenges and future development of interpretability are analyzed, To further promote the research and development of interpretability.",
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"content": "Recently, people are increasingly pursuing more accurate machine learning systems. At the same time, the problem is that it is difficult for people to understand the internal logical structure of the system, and the machine learning model has become a black box. Lack of explanation is not only a practical problem, but also an ethical problem. At this point, understanding why a model makes a prediction is as important as the accuracy of the prediction. In order to balance the interpretability and accuracy of the model, many experts and scholars have done a lot of research on improving the interpretability of machine learning model, improved the interpretability of the model from different dimensions, and created a series of interpretable methods to help users understand the internal logic of the system and make the black box transparent. However, the current interpretability research is still in the stage of development, and there is no completely unified interpretable method at present. In this paper, firstly, the development status of machine learning and the importance of interpretable learning are discussed. Then, according to the current research status, interpretable methods are introduced from interpretable models and model independent categories, the research and application in the field of interpretability are discussed, and the current challenges and future development of interpretability are analyzed, To further promote the research and development of interpretability.",
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"abstract": "The loosely-coupled microservices architecture has become increasingly popular due to the advantage of its modularity and elasticity in cloud applications. However, it also seriously complicates cloud management and degrades the performance of IT operations. Today, AI has been the locus of commerce and transactions, and transforming traditional IT operations for speed and growth. Inferring the dependencies among an application's microservices can greatly help SREs diagnose possible root causes of performance issues, which is a hard task due to the complex topology of microservices is often unknown in practice. Prior literature on detecting causal structure for cloud services requires significant application instrumentation, which rarely holds in reality. In this work, we leverage Granger causality models on just monitored log data of a microservice-based application to infer the impact of dependencies between microservices. We first describe the approach of modeling discrete log data as time series, and then formally define the Granger causality problem using both linear and nonlinear autoregressive models. Finally, we conduct an extensive comparative study to show the performance of the state-of-the-art linear and nonlinear (i.e., neural) Granger causality methods on both synthetic data and real-world log data from a publicly available benchmark microservice system. Our preliminary results indicate that neural Granger causality models outperform traditional Granger causality methods on both linear and nonlinear time series data, while for large linear time series, linear Granger causal models are more efficient with high accuracy. Using the real-world log data, we also demonstrate our interesting findings on inferred dependency graph of microservices by linear and neural Granger causality models.",
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"content": "The loosely-coupled microservices architecture has become increasingly popular due to the advantage of its modularity and elasticity in cloud applications. However, it also seriously complicates cloud management and degrades the performance of IT operations. Today, AI has been the locus of commerce and transactions, and transforming traditional IT operations for speed and growth. Inferring the dependencies among an application's microservices can greatly help SREs diagnose possible root causes of performance issues, which is a hard task due to the complex topology of microservices is often unknown in practice. Prior literature on detecting causal structure for cloud services requires significant application instrumentation, which rarely holds in reality. In this work, we leverage Granger causality models on just monitored log data of a microservice-based application to infer the impact of dependencies between microservices. We first describe the approach of modeling discrete log data as time series, and then formally define the Granger causality problem using both linear and nonlinear autoregressive models. Finally, we conduct an extensive comparative study to show the performance of the state-of-the-art linear and nonlinear (i.e., neural) Granger causality methods on both synthetic data and real-world log data from a publicly available benchmark microservice system. Our preliminary results indicate that neural Granger causality models outperform traditional Granger causality methods on both linear and nonlinear time series data, while for large linear time series, linear Granger causal models are more efficient with high accuracy. Using the real-world log data, we also demonstrate our interesting findings on inferred dependency graph of microservices by linear and neural Granger causality models.",
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"affiliation": "University of Western Ontario, London, ON, Canada",
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"abstract": "The long period error and short period error of the inductosyn have been studied. And the study result is that the long period error mainly includes the first order error and secondary error in the period of 360°and the short period error mainly includes first order, secondary, third, fifth harmonic error, and so on. A novel model of error separation and compensation is firstly presented according to the error characteristic of inductosyn. And the fourier transform are compared with least-squares in many aspects, The implement method of the error separation based on least-squares is also discussed in detail. One new measuring method is proposed, which can use less than test position to attain the long period error and the short period error. The experiments show that the error compensation method can improve the precision of the inductosyn.",
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"abstract": "In this paper, we propose minimizing the Fisher information of the error in supervised training of linear and nonlinear adaptive filters. Fisher information considers the local structure of the error probability distribution and therefore it is a criterion that deserves to be investigated as an alternative to more common statistics such as minimum mean-square-error or minimum-error-entropy. A gradient-based training algorithm, based on a nonparametric estimator of Fisher information is presented and the performances of the three mentioned optimization criteria are compared using Monte Carlo simulations.",
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"abstract": "In the CNC machining process, a main factor affecting the machining accuracy is thermal error. The optimization of spindle thermal error temperature measurement point is of great significance to establish the thermal error model of the machine tool spindle and improve the accuracy of the model. The temperature field of a vertical machining center and the thermal deformation of the machine tool spindle is obtained through experiments. According to the measured data, the temperature measurement points are grouped and optimized based on the method of fuzzy clustering and grey theory. The thermal error compensation model is established by using multiple linear regression. The verification shows that this method can effectively reduce the number of temperature measurement points. The thermal error compensation model with high precision is established, and the compensation rate is 91.3%, which is of great practical significance to improve the accuracy of the machine tool.",
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