• Journal of information and communication convergence engineering
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• v.16 no.4
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• pp.228-234
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• 2018

In software development, the quality of a product often depends on whether its developers can rapidly find and contribute to the proper tasks. Currently, the word data of projects to which newcomers have previously contributed are mainly utilized to find appropriate source files in an ongoing project. However, because of the vocabulary gap between software projects, the accuracy of source file identification based on information retrieval is not guaranteed. In this paper, we propose a novel source file identification method to reduce the vocabulary gap between software projects. The proposed method employs DBPedia Spotlight to identify proper source files based on semantic similarity between source files of software projects. In an experiment based on the Spring Framework project, we evaluate the accuracy of the proposed method in the identification of contributable source files. The experimental results show that the proposed approach can achieve better accuracy than the existing method based on comparison of word vocabularies.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.7
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• pp.520-526
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• 2002

Identification of noose sources, their locations and strengths, has been taken great attention. The methods that can identify noise sources normally assume that noise sources are located in a free field. However, the sound in a reverberant field consists of that coming directly from the source plus sound reflected or scattered by the walls or objects in the field. In contrast to the exterior sound field. reflections are added to sound field. Therefore, we haute to consider the reverberation effect on the source identification method. The main objective of this paper is to identify noise source in the reverberant field. At fist, we try to identify noise sources in a rigid wall emc;psire using the beamforming method. In many cases of practical interest, the wall has admittance so that random reflections occur in an enclosure. In this paper, we assumed the complex reverberant field in the enclosure to be the sum of plane caves with random Incidence and magnitude. Then we try to explain effects of reverberant field at interior source identification.

• Journal of KSNVE
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• v.6 no.6
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• pp.835-842
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• 1996

To identify the locations and strengths of acoustic sources, one may use a microphone line array. Apparent advantage of the source identification method utilizing a line array is that it requires less measurement points than intensity method and holography. This method is based on the information of magnitude and phase difference between pressure signals at each microphone. Since those differences are dependent on the source model, we have to assume them such as plane, monopole, etc. In this paper the conventional source identification methods such as beamforming method and MUSIC method are briefly reviewed by modeling a source as plane and spherical wave, then a modified method is introduced. This can be applied to sound field which may by either coherent or incoherent. Typical simulations and experiment are performed to confirm this identification method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3268-3283
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• 2018

With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.

• Journal of Ocean Engineering and Technology
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• v.17 no.5 s.54
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• pp.19-24
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• 2003

The question of wave source identification in a wave maker problem is the primary objective of the this paper. With the observed wave elevation, the existence of the wave maker velocity is discussed with the help of the mathematical theory of inverse problems. Utilizing the property of the Strum-Liouville system and compactness, the uniqueness and the ill-posedness(in the sense of stability) for the identification are proved.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.1203-1209
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• 2001

Identification of noise sources, their locations and strengths, have been taken great attention. The method that can identify noise sources normally assumes that noise sources are located at a free field. However, the sound in a reverberant field consists of that coming directly from the source plus sound reflected or scattered by the walls or objects in the field. In contrast to the exterior sound field, reflections are added to sound field. Therefore, we have to consider the reverberation effect on the source identification method. The main objective of this paper is to identify noise source in the reverberant field. At fist, we try to identify noise sources in a rigid wall enclosure using the spherical beamforming method. In many case of practical interest, the wall has an admittance so that complex reflection process occurred. In this paper, we assumed the complex reverberant field in the enclosure to be the sum of plane waves with random incidence and magnitude. Then the effects of reverberant field at interior source identification have been studied theoretically as well as experimentally

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5087-5102
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• 2015

Rapid popularization of smart cell phone equipped with camera has led to a number of new legal and criminal problems related to multimedia such as digital image, which makes cell phone source identification an important branch of digital image forensics. This paper proposes a classifier combination based source identification strategy for cell phone images. To identify the outlier cell phone models of the training sets in multi-class classifier, a one-class classifier is orderly used in the framework. Feature vectors including color filter array (CFA) interpolation coefficients estimation and multi-feature fusion is employed to verify the effectiveness of the classifier combination strategy. Experimental results demonstrate that for different feature sets, our method presents high accuracy of source identification both for the cell phone in the training sets and the outliers.

• Journal of Biosystems Engineering
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• v.26 no.6
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• pp.503-508
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• 2001

In this paper, time-fiequency analysis and multi-dimensional spectral analysis methods are applied for source identification and diagnosis of non-stationary sound/vibration signals. Sound or vibration problems of general vehicle and agricultural machinary are under 500 Hz. So We used linearly increased chirp signals under 500 Hz. By checking the coherences on concerned time, fur time-variant non-stationary signals, this simulation it very well coincident to expected results.

• Journal of Soil and Groundwater Environment
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• v.27 no.2
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• pp.87-98
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• 2022

This study aims to prepare a technical protocol for identifying the source of nitrate in water using nitrogen (δ¹⁵N) and oxygen (δ¹⁸O) stable isotope ratios. The technical processes for nitrate sources identification are composed of site investigation, sample collection and analysis, isotope analysis, source identification using isotope characteristics, and source apportionment for multiple potential sources with the Bayesian isotope mixing model. Characteristics of various nitrate potential sources are reviewed, and their typical ranges of δ¹⁵N and δ¹⁸O are comparatively analyzed and summarized. This study also summarizes the current knowledge on the dual-isotope approach and how to correlate the field-relevant information such as land use and hydrochemical data to the nitrate source identification.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1637-1649
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• 2017

This paper describes an intensive analysis of a harmonic identification algorithm in non-ideal voltages source systems. The dq-axis Fourier with a positive sequence voltage detector (DQFP) is a novel harmonic identification algorithm for active power filters. A compensating current control system based on repetitive control is presented. A design and stability analysis of the proposed current control are also given. The aim of the paper is to achieve a robustness of the harmonic identification in a distorted and unbalanced voltage source. The proposed ideas are supported by a hardware in the loop technique based on a $eZdsp^{TM}$ F28335 and the Simulink program. The obtained results are presented to demonstrate the performance of the harmonic identification and the control strategy for the active power filter in non-ideal systems.