• 한국소음진동공학회논문집
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• 제14권10호
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• pp.930-938
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• 2004

This paper presents the noise source identification of a car A/V system. There are two different kinds of noise sources noise generated by loading mechanism and rattle noise by externally forced vibration. A dynamometer has been made to produce stationary inertia to the loading mechanism of A/V system. Sound pressure spectra and sound intensity were measured by operating the dynamometer setup as various motor speeds, and the results were analyzed. A dominant rattle noise source about A/V system's components has been found by multi-dimensional spectral analysis. Residual spectrum method was applied for eliminating coherence between the vibration sources. In result, the dominant rattle noise source was identified by partial coherent output spectrum of individual vibration component.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.960-963
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• 2003

Sound intensity method is well known as a visualization technique of sound field and sound propagation in noise control. Sound intensity is a vector quantity that describes the magnitude and the direction of net flow of acoustic energy at a given position. The current measuring method is expensive and difficult to identify the noise source exactly. In this paper, we have studied the noise source identification and the characteristics of noise source of rotary compressor for air conditioner using complex sound intensity method. The new method for instantaneous sound intensity is also proposed and it is useful for transient state and steady state. The criteria of these state, select auto correlation coefficient. The advantage, simplicity and economic attribution of this method are verified by analyzing the characteristics of noise source with instantaneous sound intensity compared to mean sound intensity.

• 인터넷정보학회논문지
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• 제19권5호
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• pp.33-41
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• 2018

최근 인터넷 기술이 발전함에 따라 다양한 프로그램들이 만들어지고 있고 이에 따라 다양한 코드들이 많은 사람들을 통해 만들어진다. 이러한 측면을 이용하여 특정 작성자가 작성한 코드들 그대로 가져가 자신이 작성한 것처럼 보여주거나, 참고한 코드들에 대한 정확한 표기 없이 그대로 사용하여 이에 대한 보호가 점차 어려워지고 있다. 따라서 본 논문에서는 작성자 분석 이론과 합성곱 신경망 기반 자연어 처리 방법을 적용한 작성자 식별 프레임워크룰 제안한다. 작성자 분석 이론을 적용하여 소스 코드에서 작성자 식별에 적합한 특징들을 추출하고 이를 텍스트 마이닝에서 사용하고 있는 특징들과 결합하여 기계학습 기반의 작성자 식별을 수행한다. 그리고 합성곱 신경망 기반 자연어 처리 방법을 소스 코드에 적용하여 코드 작성자 분류를 수행한다. 본 논문에서는 작성자 분석이론과 합성곱 신경망을 적용한 작성자 식별 프레임워크를 통해 작성자를 식별하기 위해서는 작성자 식별만을 위한 특징들이 필요하다는 것과 합성곱 신경망 기반 자연어 처리 방법이 소스 코드등과 같은 특수한 체계를 갖추고 있는 언어에서도 적용이 가능하다. 실험 결과 작성자 분석 이론 기반 작성자 식별 정확도는 95.1%였으며 CNN을 적용한 결과 반복횟수가 90번 이상일 경우 98% 이상의 정확도를 보여줬다.

• 한국소음진동공학회논문집
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• 제21권9호
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• pp.787-797
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• 2011

The noise in a vehicle is an important factor for customers purchasing a car. Particularly, reduction of the noise that is generated from HVAC(heating, ventilation and air conditioning) is very important since it has considerable effects on interior noise. In general, identification of noise source is crucial to reduce noise level. The complex acoustic intensity method is widely used to obtain the accurate measurement and identification of noise source. Therefore, in the previous study, noise source of HVAC was identified through experimental approach using the complex acoustic intensity method. In this study, we are intended to confirm reduced level of noise by comparing the result between before and after modification of cam curve that is based on identified noise source of HVAC. It is found out that noise source of HVAC are motor and cam area using the complex acoustic intensity method in the previous study. We performed experiments to compare noise level between before and after modification of cam curve. Especially, it can be seen that complex acoustic intensity method using both active and reactive intensity is vital in devising a strategy for comparison to noise level. Also, the vector flow of acoustic intensity was investigated to identify sound intensity distributions and energy flow in the near field of HVAC.

• 전기학회논문지
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• 제64권7호
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• pp.1031-1039
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• 2015

Present guided missiles are equipped with infrared seeker to find the infrared sources radiating from target plane and then chase, which results in an improvement of the hitting success rate when in striking target objects. To interrupt the chases from the guided missile, the target plane spreads the flare, avoiding the missile attracts. Our research is to develop a 2-color infrared identification technique to discern the flare and real thermal source from target plane. Considering flare radiation properties and EM atmosphere transmission rates, two channels were selected, in which main channel (MC) was in a range of 3.7 μm∼4.8 μm and auxiliary channel (AC) in 1.7 μm∼2.3 μm. A 2500K heat source was used for an artificial flare source, while a 570K heat source was utilized for airplane infrared source in experimental testing. Two infrared sensors detectable only at each chanel were employed in order to measure the voltage ratio from two channels, identifying the flare and real target plane via comparison the voltage ratio. Several experimental conditions were imported in order to prove that our proposed 2-color infrared identification technique is very efficient way to discern heat sources from aircraft and flare, demonstrating that our proposed technique is very promising means for our force’s InfraRed Counter Counter Measure (IRCCM) in order to countermeasure opposite force’s InfraRed Counter Measures (IRCM).

• Asian Journal of Atmospheric Environment
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• 제8권3호
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• pp.115-125
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• 2014

In this study, particle composition data for $PM_{10}$ samples were collected every 3 days at Seoul, Korea from August 2006 to November 2007, and were analyzed to provide source identification and apportionment. A total of 164 samples were collected and 21 species (15 inorganic species, 4 ionic species, OC, and EC) were analyzed by particle-induced x-ray emission, ion chromatography, and thermal optical transmittance methods. Positive matrix factorization (PMF) was used to develop source profiles and to estimate their mass contributions. The PMF modeling identified nine sources and the average mass was apportioned to secondary nitrate (9.3%), motor vehicle (16.6%), road salt (5.8%), industry (4.9%), airborne soil (17.2 %), aged sea salt (6.2%), field burning (6.0%), secondary sulfate (16.2%), and road dust (17.7%), respectively. The nonparametric regression (NPR) analysis was used to help identify local source in the vicinity of the sampling area. These results suggest the possible strategy to maintain and manage the ambient air quality of Seoul.

• 한국정보처리학회논문지
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• 제6권10호
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• pp.2693-2706
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• 1999

Reengineering to object-oriented system is needed to maintain the system and satisfy requirements of structure change. Target systems which should be reengineered to object-oriented system are difficult to change because these systems have no design document or their design document is inconsistent of source code. Using design document to identifying objects for these systems is improper. There are several researches which identify objects through procedural source code analysis. In this paper, we propose automatic object identification method based on clustering of VTFG(Variable-Type-Function Graph) which represents relations among variables, types, and functions. VTFG includes relations among variables, types, and functions that may be basis of objects, and weights of these relations. By clustering related variables, types, and functions using their weights, our method overcomes limit of existing researches which identify too big objects or objects excluding many functions. The method proposed in this paper minimizes user's interaction through automatic object identification and make it easy to reenginner procedural system to object-oriented system.

• 대한기계학회논문집A
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• 제21권7호
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• pp.1127-1140
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• 1997

With the study for identifying the transmission characteristics of vibration and noise generated by operating engine system of a vehicle, recently many engineers have studied actively the reduction of vibration and noise inducing uncomfortableness to the passenger. In this study, output noise was analyzed by multi-dimensional spectral analysis and vector synthesis method. The multi-dimensional analysis method is very effective in case of identification of primary source, but this method has little effect on suggestion for interior noised reduction. For compensation of this, vector synthesis method was used to obtain effective method for interior noise reduction, after identifying primary source for output noise. In this paper, partial coherence function of each input was calculated to know which input was most coherent to output noise, then with simulation of changes for input magnitude and phase by vector synthesis diagram, the trends of synthesized output vector was obtained. As a result, the change of synthesized output vector could be estimated.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권7호
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• pp.313-318
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• 2006

An automatic sample centering system is underway at the protein crystallography beam line of the Pohang Light Source to improve the efficiency of the crystal screening process. A sample pin which contains a protein crystal is mounted on a goniometer head. Then the crystal should be moved to the center of X-ray beam by controlling the motorized goniometer to obtain diffraction data. Since the X-ray beam is located at the center of the image obtained from the CCD camera when the image of the sample pin is in focus, an auto-focusing algorithm is a very important part in the auto-sample-centering system. However the results of applying several well-known auto focusing algorithms directly to the images are not satisfactory owing to the following factors: misalignment of CCD camera, non-uniform cryo-stream in the background of the image and the supporter of the loop. The performance of an auto-focusing algorithm can be increased if the algorithm is applied to only the loop region identified. Non-uniform cryo-stream and a various illumination condition and a stain, which is shown in the image, are main obstacles to loop region identification. In this paper, a simple loop region identification algorithm, which can solve these problems, is proposed and the effective ness of the proposed scheme is shown by applying the auto-focusing algorithm to the loop region identified.

• 대한원격탐사학회지
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• 제35권1호
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• pp.93-115
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• 2019

The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. However, the presence of other mass movements, such as landslides within the same region of interest, poses additional challenges to this task. Thus, this research presents a method based on an integration of Gaussian mixture model (GMM) and ensemble artificial neural network (bagging ANN [BANN]) for automatic detection of potential rockfall sources at Kinta Valley area, Malaysia. The GMM was utilised to determine slope angle thresholds of various geomorphological units. Different algorithms(ANN, support vector machine [SVM] and k nearest neighbour [kNN]) were individually tested with various ensemble models (bagging, voting and boosting). Grid search method was adopted to optimise the hyperparameters of the investigated base models. The proposed model achieves excellent results with success and prediction accuracies at 95% and 94%, respectively. In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.