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Although there has been increasing demand for more reliable web applications, JavaScript bugs abound in web applications. In response to this issue, researchers have proposed automated fault detection tools, which statically analyze the web application code to find bugs. While useful, these tools either only target a limited set of bugs based on predefined rules, or they do not detect bugs caused...
Electric network frequency (ENF), a signature in multimedia application, is been utilized as a significant tool to check the authenticity of media recordings. In this type of authentication systems the ENF signals are extracted from the tampered recording and compared with reference ENF database. This establishes a popular application of audio timestamp verification. In this paper the authentication...
In this paper, we develop a robust generalization of the Gaussian quasi score test (GQST) for composite binary hypothesis testing. The proposed test, called measure-transformed GQST (MT-GQST), is based on a transformation applied to the probability distribution of the data. The considered transform is structured by a non-negative function, called MT-function, that weights the data points. By appropriate...
This paper mainly concerns about the binary hypothesis testing problems with unknown parameters in null hypothesis and alternative hypothesis, where the prior for unknown parameters is not completely known, but is assumed to belong to an ∊-contamination class. We develop a method that decides between null hypothesis and alternative hypothesis reliably. Furthermore, when it decides in favor of null...
Automated recognition of spacecraft and space debris using imaging plays an important role in securing space safety and space exploration. Although deep learning is now the most successful solution for image-based object classification, it requires a myriad number of training data, which are not available for most real applications. In this paper, we investigate different single and hybrid data augmentation...
We prove that the solvability of systems of linear equations and related linear algebraic properties are definable in a fragment of fixed-point logic with counting that only allows polylogarithmically many iterations of the fixed-point operators. This enables us to separate the descriptive complexity of solving linear equations from full fixed-point logic with counting by logical means. As an application...
This paper proposes an efficient method for accelerating Transform Unit (TU) depth decisions based on the rough mode cost (RMC), which is the simplified rate-distortion (RD) cost during the rough mode decision (RMD), in HEVC intra coding. The TU partition of the mode with the minimal RMC is used to determine the TU partitions of remaining intra modes. The proposed TU partitioning method improves RD...
In the presence of environmental noise, speaker verification systems inevitably see a decrease in performance. This paper proposes the (1) use of two parallel classifiers, (2) feature enhancement based on blind signal-to-noise ratio (SNR) estimation and (3) fusion, to improve the performance of speaker verification systems. The two classifiers are based on Gaussian mixture models and the partial least-squares...
One of the most widely studied techniques in software testing researchis mutation testing - a technique for evaluating the quality of testsuites. Despite over four decades of academic advances in thistechnique, mutation testing has not found its way to mainstreamdevelopment. The key issue with mutation testing is its highcomputational cost: it requires running the test suite against notjust the program...
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....
Multi-Label classification aims to classify an example that can belong to many classes. Although One-versus-All (OVA) is the most common approach, our prior work has shown that the proposed One-versus-One (OVO) always gives higher prediction accuracy than OVA. However, OVO requires an extremely high computational cost when there are a large number of labels. In this paper, we apply our OVO SVMs on...
A Regionlet model explored here provides a new object representation strategy for generic object detection, which integrates local deformation handling into object classifier learning and feature extraction. Generic object detection deals with different degrees of variations in discrete object classes with tractable computations and hence faces problems. This generates a need for representational...
Tiny target detections, especially power line detection, have received great attention due to its critical role in ensuring the flight safety of low-flying unmanned aerial vehicles (UAVs). In this paper, an accurate and robust power line detection method is proposed, wherein background noise is mitigated by an embedded convolution neural network (CNN) classifier before conducting the final power line...
Cancer classification based on microarray data has gained attention in recent years from the bioinformatics community, due to a high death toll of cancer and the significance of early diagnosis. Among the many steps in cancer classification, one that is underexplored and can significantly affect the classification performance is data transformation. We develop two transformation techniques, called...
Point-of-care testing (POCT) has transformed the healthcare landscape by delivering quick and cheap diagnostic services closer to the patient. Urine test strips are one of the most commonly used POCT tools, however their manual interpretation can be challenging, particularly for the elderlies and people with eye disorders. In this study, we propose a smartphone application designed to automatically...
Distribution network in our country mostly uses the neutral point grounding way directly namely the small current grounding system, and the single-phase earth fault of distribution network fault is about 80%. When single-phase earth fault occurs, the system can still run 1 ∼ 2 h. This request in the electric power, as soon as possible accurately find out the fault line and the location, based on traditional...
In this work, we address the issue of automatic assessment for programming assignments. The objective is to provide immediate feedback to the learners and save teachers from manually managing all the students' solutions. We will present a method merging results from dynamic and static analysis to ensure a reliable and objective evaluation job. While dynamic analysis is based on unit testing framework,...
The welding inspector ensures the integrity of weld joints since the structural stability mainly depends on it. Welded joints are tested for the prediction of remaining useful life using different Non Destructive Testing (NDT) schemes such as Ultrasonic Testing (UT). In this proposed study, possible classification of UT signals acquired from weld areas in terms of different levels of thermal fatigue...
At present, the issue of intrusion detection must be a hot point to all over the computer security area. In this paper, two novel intrusion detection techniques have been proposed. First, unlike the current existent detection methods, this paper combines the theories of both intuitionistic fuzzy sets (IFS) and artificial neural networks (ANN) together, which lead to much fewer iteration numbers, higher...
Depression is an increasingly prevalent mood disorder. This is the reason why the field of computer-based depression assessment has been gaining the attention of the research community during the past couple of years. The present work proposes two algorithms for depression detection, one Frame-based and the second Video-based, both employing Curvelet transform and Local Binary Patterns. The main advantage...
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