A Data-Semantic-Conflict-Based Multi-Truth Discovery Algorithm for a Programming Site
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With the extensive application of software collaborative development technology, the processing of code data generated in programming scenes has become a research hotspot. In the collaborative programming process, different users can submit code in a distributed way. The consistency of code grammar can be achieved by syntax constraints. However, when different users work on the same code in semantic development programming practices, the development factors of different users will inevitably lead to the problem of data semantic conflict. In this paper, the characteristics of code segment data in a programming scene are considered. The code sequence can be obtained by disassembling the code segment using lexical analysis technology. Combined with a traditional solution of a data conflict problem, the code sequence can be taken as the declared value object in the data conflict resolution problem. Through the similarity analysis of code sequence objects, the concept of the deviation degree between the declared value object and the truth value object is proposed. A multi-truth discovery algorithm, called the multiple truth discovery algorithm based on deviation (MTDD), is proposed. The basic methods, such as Conflict Resolution on Heterogeneous Data, Voting-K, and MTRuths_Greedy, are compared to verify the performance and precision of the proposed MTDD algorithm.No abstract available.
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The algorithm GDBSCAN only needs two parameters.It can discover clusters of any shape.But it is very sensitive to the parameter Eps.This paper puts forward a kind of method to make sure the Eps,which is based on datagrid.The method can achieve better result on the case of data distributing unevenly and shapes of clusters reaching each other.
DBSCAN
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We present a method to classify objects in video streams using a brain-inspired Hierarchical Temporal Memory (HTM) algorithm. Object classification is a challenging task where humans still significantly outperform machine learning algorithms due to their unique capabilities. We have implemented a system which achieves very promising performance in terms of recognition accuracy. Unfortunately, conducting more advanced experiments is very computationally demanding; some of the trials run on a standard CPU may take as long as several days for 960x540 video streams frames. Therefore we have decided to accelerate selected parts of the system using OpenCL. In particular, we seek to determine to what extent porting selected and computationally demanding parts of a core may speed up calculations. The classification accuracy of the system was examined through a series of experiments and the performance was given in terms of F1 score as a function of the number of columns, synapses, $min\_overlap$ and $winners\_set\_size$. The system achieves the highest F1 score of 0.95 and 0.91 for $min\_overlap=4$ and 256 synapses, respectively. We have also conduced a series of experiments with different hardware setups and measured CPU/GPU acceleration. The best kernel speed-up of 632x and 207x was reached for 256 synapses and 1024 columns. However, overall acceleration including transfer time was significantly lower and amounted to 6.5x and 3.2x for the same setup.
Porting
Kernel (algebra)
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The thesis introduce a solution of using DataGrid coned and ComboBox control to realize DataBase of querying
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article Free Access Share on Remarks on Algorithm 332: Jacobi polynomials: Algorithm 344: student's t-distribution: Algorithm 351: modified Romberg quadrature: Algorithm 359: factoral analysis of variance Author: Arthur H. J. Sale Univ. of Sydney, Sydney, Australia Univ. of Sydney, Sydney, AustraliaView Profile Authors Info & Claims Communications of the ACMVolume 13Issue 7July 1970 https://doi.org/10.1145/362686.362700Published:01 July 1970Publication History 0citation275DownloadsMetricsTotal Citations0Total Downloads275Last 12 Months10Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Quadrature (astronomy)
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This paper analyzed the DataGrid Web Server Control. DataGrid is one of the most popular control of ASP .NET which is used to render data to a Web page in tabular form. This paper provides two types of typical usage of DataGrid.
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Interface (matter)
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First, two methods to realize the bidirectional sorts including the ascendant sort order and the descendant sort order in the DataGrid through storing the sort expression and the sort direction by means of attributes and viewstate are summarized in order that the users browse and look up more conveniently; Second, the method to choose a row by click any cell in the DataGrid is given in order that the users could operate more conveniently; Third, the methods to update or delete the selected record row in the DataGrid from Web forms controls are given to ensure data validation.
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