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Fingerprint is a technology that helps one to find information similar to the reference data by some criteria (features). It is used for tracking the fact of illegal copying of multimedia or electronic documents. The basic algorithm of a «fingerprint» is the statistical evaluation of different features in document: the presence of characteristic elements, and frequently encountered character combinations...
Dynamic symbolic execution (DSE) is widely used to generate test cases for automated test. However, the practicability of DSE is greatly decreased by path explosion, which is an unavoidable challenge caused by that the number of execution paths increases exponentially with the increase in the size of program. To alleviate this problem, dynamic symbolic execution based on multiple test points (MPDSE)...
Using Clustering algorithm to improve the effectiveness of test case prioritization has been well recognized by many researchers. Software fault prediction has been one of the active parts of software engineering, but to date, there are few test cases prioritization technique using fault prediction. We conjecture that if the code has a fault-proneness, the test cases covering the code will findfault...
There is a constantly growing interest in evaluating music information retrieval (MIR) systems that can provide effective management of the music resources. The crucial characteristic of music is its emotion, which reflect the human's perception. To do the automatic classification of Chinese music emotions more effective, we use the lyrics of music to analysis and classify music based on emotion....
Using Clustering algorithm to improve the effectiveness of test case prioritization has been well recognized by many researchers. Software fault prediction has been one of the active parts of software engineering, but to date, there are few test cases prioritization technique using fault prediction. We conjecture that if the code has a fault-proneness, the test cases covering the code will find fault...
Derivation of input sequences for distinguishing states of a finite state machine (FSM) specification is well studied in the context of FSM-based functional testing. We present a parallel multithreaded implementation of the exact algorithm using Open Multi-Processing (OpenMP). Experiments are conducted to assess the performance of the parallel implementation as compared to the sequential implementation...
Conventional concolic testing has been used to provide high coverage of paths in statically typed languages. While it has also been applied in the context of JavaScript (JS) programs, we observe that applying concolic testing to dynamically-typed JS programs involves tackling unique problems to ensure scalability. In particular, a naive type-agnostic extension of concolic testing to JS programs causes...
Software defect localization is an important step in the process of fixing defects and is a necessary means to improve software quality. In the process of fixing defects, it is also the most time-consuming and laborious task to accurately locate the files where the defects should be fixed. In order to clarify the research progress in the field of defect localization, we introduce the key technologies...
Efficient and accurate spectrum sensing is a necessary part in cognitive radio networks. A simple and efficient spectrum sensing technique is proposed to solve the bad performance of spectrum sensing in non synchronous OFDM signals with low SNR regimes. Through the decomposition of the traditional OFDM signal spectrum sensing technology based on cyclostationarity, the real part and the imaginary part...
To improve the performance of the convolutional neural networks, it is normally done by increase the deepness or put more layers to the network. By doing such, the number of parameters is increased. In this paper, NU-InNet, which was developed from GoogLeNet, is modified by adding more layers to the network in order to improve the accuracy of the network while keeping the number of the parameters...
A generalized sequential probability ratio test (GSPRT) is a classical algorithm for binary sequential hypothesis testing. Though it is well-studied in the literature, there has been no optimal design of this test due to the difficulty of choosing its thresholds. In this paper we formulate the binary sequential hypothesis testing as an optimization problem. The latter is non-convex, and finding a...
Data mining algorithms are used to analyze and discover useful information from data. This paper presents an experiment that applies Combinatorial Testing (CT) to five data mining algorithms implemented in an open-source data mining software called WEKA. For each algorithm, we first run the algorithm with 51 datasets to study the impact different datasets have on the test coverage. We select one dataset...
Learning cumulative distribution functions (CDFs) is a widely studied problem in data stream summarization. While current techniques have efficient software implementations, their efficiency depends on updates to data structures that are not easily adapted to FPGA or ASIC implementation. In this work, we develop an algorithm and a compact hardware architecture for learning the CDF of a data stream...
Millions of file uploads and downloads happen every minute resulting in big data creation and manual text categorization is not possible. Hence, there is a need for automatic categorization of documents that makes storage and retrieval more efficient. This research paper proposes a hybrid text categorization model that combines both Rocchio algorithm and Random Forest algorithm to perform Multi-label...
The availability of Electronic Health Records (EHR) in health care settings provides terrific opportunities for early detection of patients' potential diseases. While many data mining tools have been adopted for EHR-based disease early detection, Linear Discriminant Analysis (LDA) is one of the most widely-used statistical prediction methods. To improve the performance of LDA for early detection of...
The paper studies the efficiency of a QPSO (Quantum-behaved Particle Swarm Optimization) algorithm enhanced with neighborhood strategies to solve a NDET (Non-Destructive Electromagnetic Testing) inverse problem, formulated as an optimization problem. Two different neighborhood strategies are analyzed and compared with the classic QPSO, one based on disjoint subswarms, and the other based on informants...
A holistic approach is needed to impart abstract thinking and Programming skills among the students to enable them to be successful developers when they get employed in an IT organization where the organizations are transforming towards digital technologies. Though computer programming curriculum comprises of essential topics of programming, there is wide gap between the industry expectations from...
In order to achieve excellence, it is important for the educational institutions to assess the outcomes of their graduate programmes. In general, the graduate programme outcomes are assessed through direct (examinations, projects, assignments etc) and indirect (co-curricular, extra-curricular, surveys etc) methods. The results through direct assessment are followed up with several actions such as...
The use of different evaluation measures for classification tasks have gained a significant amount of attention in the past decade, specially for those problems with multiple and imbalanced classes [1], [2]. However, the optimization of classifiers with respect to these measures is still heuristic, using ad-hoc rules with classical accuracy-optimized classifiers. We propose a classifier designed specifically...
This paper defines the problem and design of the appropriate similarity with distribution function of the omics data is a critical objective. Data mining integrate methodical section at the large explosion of huge amount data that can be obtained to utilize and innovative knowledge. Researchers present and future the omics technologies permit to imitate as highly dimensional of omics data. This paper...
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