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Fault localization techniques have been applied to database and data-centric applications that use SQL or SQL-based languages. However, existing techniques can only identify the SQL statements that have faults, but not determine the precise location of the faults within SQL statements. Since SQL statements can be rather complex, programmers are still left with a difficult repair chore. We propose...
Big data applications (e.g., Extract, Transform, and Load (ETL) applications) are designed to handle great volumes of data. However, processing such great volumes of data is time-consuming. There is a need to construct small yet effective test data sets during agile development of big data applications. In this paper, we apply a combinatorial test data generation approach to two real-world ETL applications...
This paper identifies three problems when testing software that uses Hadoop-based big data techniques. First, processing big data takes a long time. Second, big data is transferred and transformed among many services. Do we need to validate the data at every transition point? Third, how should we validate the transferred and transformed data? We are developing a novel big data test framework to address...
Recently, studies have been performed on harmony features for speech emotion recognition. It is found in our study that the first- and second-order differences of harmony features also play an important role in speech emotion recognition. Therefore, we propose a new Fourier parameter model using the perceptual content of voice quality and the first- and second-order differences for speaker-independent...
This paper presents the most recent progress and state of the art result obtained from BBN's Arabic offline handwriting recognition research. Our system is based a left-to-right hidden Markov model and integrates discriminative learning methods including discriminative MPE and n-best rescoring using the scores of glyph classifiers (SVM, DNN) and the RNNLM. Arabic-related features for n-best rescoring...
In this paper we present a novel clustering analysis method based on the Most Similar Relation Diagram (MSRD). MSRD is a diagram in which each datum of a dataset is linked to its most similar data. By cutting off some links in the diagram a certain number of clusters are formed. A compare of the MSRD method with hierarchical method is implemented. Clustering experiences using MSRD were done and the...
Introduced was the development and implementation for the water pollution control technology database platform based on general management information system. The technology research and application demonstration of the system were developed, covering six fields such as lake water pollution treatment and ecological restoration, improvement of environment quality of urban water, drinking water safety,...
In many researches, one of major challenges is to archive, access, and analyze various heterogeneous databases containing useful information gathered from a large volume of data. Metadata plays a critical role in database integration, so metadata model is put forward which comprises information of data content. Discussion on information integration solves the problem with manipulating the metadata...
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