• Title/Summary/Keyword: Source identification

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Noise Source Identification of a Car A/V System (차량탑재용 A/Y 시스템의 소음원 규명)

  • 홍종호;이상호;강연준
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.14 no.10
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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.

Development and Application of Measuring Method for Instantaneous Intensity (순시 인텐시티 측정 기법의 개발 및 응용)

  • 이장우;안병하
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.05a
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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.

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The Identification Framework for source code author using Authorship Analysis and CNN (작성자 분석과 CNN을 적용한 소스 코드 작성자 식별 프레임워크)

  • Shin, Gun-Yoon;Kim, Dong-Wook;Hong, Sung-sam;Han, Myung-Mook
    • Journal of Internet Computing and Services
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    • v.19 no.5
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    • pp.33-41
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    • 2018
  • Recently, Internet technology has developed, various programs are being created and therefore various codes are being made through many authors. On this aspect, some author deceive a program or code written by other particular author as they make it themselves and use other writers' code indiscriminately, or not indicating the exact code which has been used. Due to this makes it more and more difficult to protect the code. In this paper, we propose author identification framework using Authorship Analysis theory and Natural Language Processing(NLP) based on Convolutional Neural Network(CNN). We apply Authorship Analysis theory to extract features for author identification in the source code, and combine them with the features being used text mining to perform author identification using machine learning. In addition, applying CNN based natural language processing method to source code for code author classification. Therefore, we propose a framework for the identification of authors using the Authorship Analysis theory and the CNN. In order to identify the author, we need special features for identifying the authors only, and the NLP method based on the CNN is able to apply language with a special system such as source code and identify the author. identification accuracy based on Authorship Analysis theory is 95.1% and identification accuracy applied to CNN is 98%.

Evaluation for Noise Reduction of the HVAC by Modification of CAM Curve (CAM 곡선 개선에 의한 차량용 공조기의 소음 저감 평가)

  • Jeong, J.E.;Jung, C.Y.;Seo, B.J.;Jeong, U.C.;Oh, J.E.
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.21 no.9
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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.

Heat Source Identification Technique of Aircraft and Flare using 2-color Detectable Infrared Sensors (복수 대역 감지 적외선 센서를 이용한 항공기와 플레어의 열원 식별 기술)

  • Lee, Dong-Si;Lee, Kee-Keun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.7
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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).

Source Identification and Estimation of Source Apportionment for Ambient PM10 in Seoul, Korea

  • Yi, Seung-Muk;Hwang, InJo
    • Asian Journal of Atmospheric Environment
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    • v.8 no.3
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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.

A Method of Object Identification from Procedural Programs (절차적 프로그램으로부터의 객체 추출 방법론)

  • Jin, Yun-Suk;Ma, Pyeong-Su;Sin, Gyu-Sang
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.10
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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.

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The Identification of Generation Mechanism of Noise and Vibrtaion and Transmission Characteristics for Engine System - The Source Identification and Noise Reduction of Compartment by Multidimensional Spectral Analysis and Vector Synthesis Method - (엔진의 소음.진동발생기구 및 전달특성 규명 -다차원해석법과 벡터합성법에 의한 차실소음원 규명 및 소음저감 -)

  • O, Jae-Eung
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.21 no.7
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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.

Development of an Auto Sample Centering Algorithm at the Macromolecular Crystallography Beam Line of the Pohang Light Source (단백질 결정학 빔 라인에서의 자동 샘플 정렬 알고리즘 개발)

  • Jang, Yu-Jin
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.55 no.7
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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.

Rockfall Source Identification Using a Hybrid Gaussian Mixture-Ensemble Machine Learning Model and LiDAR Data

  • Fanos, Ali Mutar;Pradhan, Biswajeet;Mansor, Shattri;Yusoff, Zainuddin Md;Abdullah, Ahmad Fikri bin;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.35 no.1
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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.