• Korean Journal of Environmental Biology
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• v.41 no.2
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• pp.109-125
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• 2023

This study was conducted to select target fish species as baseline research for accumulation analysis of major hazardous chemicals entering the aquatic ecosystem in Korea and to analyze the impact on fish community. The test bed was selected from a sewage treatment plant, which could directly confirm the impact of the inflow of harmful chemicals, and the Geum River estuary where harmful chemicals introduced into the water system were concentrated. A multivariable metric model was developed to select target candidate fish species for hazardous chemical analysis. Details consisted of seven metrics: (1) commercially useful metric, (2) top-carnivorous species metric, (3) pollution fish indicator metric, (4) tolerance fish metric, (5) common abundant metric, (6) sampling availability (collectability) metric, and (7) widely distributed fish metric. Based on seven metric models for candidate fish species, eight species were selected as target candidates. The co-occurring dominant fish with target candidates was tolerant (50%), indicating that the highest abundance of tolerant species could be used as a water pollution indicator. A multi-metric fish-based model analysis for aquatic ecosystem health evaluation showed that the ecosystem health was diagnosed as "bad conditions". Physicochemical water quality variables also influenced fish feeding and tolerance guild in the testbed. Eight water quality parameters appeared high at the T1 site, indicating a large impact of discharging water from the sewage treatment plant. T2 site showed massive algal bloom, with chlorophyll concentration about 15 times higher compared to the reference site.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.1003-1008
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• 2004

In our life, we have used many digital appliances. They helped us to improve the quality of lift but sometimes gave us unsatisfactory result because they produce specific noise. Especially a vacuum cleaner produces a great deal of noise that is very annoying. So we need to study what sound metrics affect human sensibility. In this paper, we will study sound quality index for vacuum cleaner. The subjective evaluation of vacuum cleaner sound can be indicated to objective parameters by sound metrics of psychoacoustics. The artificial neural network can estimate the nonlinear characteristics of relation between subjective evaluation and sound metrics. We applied the artificial neural network to the development of sound quality index for vacuum sound.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.1
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• pp.37-43
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• 2018

There has been the migration to a performance-based approach in many areas which include transition planning at global, regional and local levels, performance-based navigation and safety management. Achieving continuous success of Air Traffic Management (ATM) systems would require a performance-based approach to raise productivity and efficiency of it through performance measurements and reviews. This paper considers establishment planning of performance measurement and evaluation system for ATM. Related to key performance areas proposed by International Civil Aviation Organization, performance indicators and metrics which could be used to measure and evaluate ATM performance are presented. Also, organizational system and operational planning for efficient operation of ATM are presented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.3
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• pp.601-614
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• 2007

Lately, as importance of biometric is recognized, domestic and foreign biometric software market is soaring and the requests of high reliability and quality of biometric software are inclosed. Evaluation items and criteria must be established for the biometric software quality certification. In this paper, we development the evaluation module for biometric software test based on ISO/IEC 12119 that is the standard about package software quality requirement and test, and ISO/IEC 9126 that is the standard about evaluation of software product, and ISO/IEC 14598-6 that is the standard for construction of the evaluation module. We think that this study can be used in establishing the software quality evaluation method of bio information processing software and constructing the basis for quality improvement.

• Proceedings of the Korea Society for Simulation Conference
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• 1997.04a
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• pp.13-17
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• 1997

생산시스템 관련 연구에서 시뮬레이션은 중요한 도구로 폭넓게 활용되어 왔다. 생 산시스템을 분석하기 위한 시뮬레이션 모델은 그 기본구조가 정형화되어 있기 때문에 생산 시스템 시뮬레이터 개발에 관련된 사례연구가 적지 않다. 최근 들어서는 객체지향 접근방법 을 이용한 시뮬레이터가 상용화되는 추세이다. 본 연구에서는 객체지향 생산시스템 시뮬레 이터를 설계 및 구현하는데 있어서 객체지향 접근 방법의 잇점인 재사용성 및 확장성을 제 고 시킬수 있는 방안으로 Pattern을 이용한 설계기법 및 S/W Metrics를 이용한 설계평가 방법에 대해서 논의한다. 또한 현재 개발중인 생산 시스템 시뮬레이터 KU-FASIM에 이런 개념들이 실제 적용된 결과에 대해서 검토해 본다.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.45-51
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• 2000

This study proposes that analysis and evaluation method of time series ultrasonic signal using the chaotic feature extrac-tion for degradation extent. Features extracted from time series data using the chaotic time series signal analyze quantitatively material degradation extent. For this purpose analysis objective in this study if fractal dimension lyapunov exponent and strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical syste, In experiment fractal(correlation) dimensions and lyapunov experiments showed values of mean 3.837-4.211 and 0.054-0.078 in case of degradation material The proposed chaotic feature extraction in this study can enhances ultrasonic pattern recognition results from degrada-tion signals.

• Journal of Welding and Joining
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• v.16 no.6
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• pp.86-96
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• 1998

This study proposes the analysis method of time series ultrasonic signal using the chaotic feature extraction for degradation extent evaluation. Features extracted from time series data using the chaotic time series signal analyze quantitatively degradation extent. For this purpose, analysis objective in this study is fractal dimension, lyapunov exponent, strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical system. In experiment, fractal correlation) dimensions, lyapunov exponents, energy variation showed values of 2.217∼2.411, 0.097∼ 0.146, 1.601∼1.476 voltage according to degardation extent. The proposed chaotic feature extraction in this study can enhances precision ate of degradation extent evaluation from degradation extent results of the degraded materials (SA508 CL.3)

• Korean Journal of Optics and Photonics
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• v.11 no.2
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• pp.85-90
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• 2000

The image quality of CRT displays is descnbed by the physical characteristics such as luminance, contrast, address ability, viewing distance, and so on. However, the final evaluation of rmage quality is deteITIlllled by not phYSICal data, but subjective perceived Image quality. Therefore the correlation is compared the score of subjective image qualIty accompli~hed by several persons with calculated SQRI (SQuate Root Integral) value uSlllg 4 kInds of CRT monitors. And the influence of tile physical chatac1eristics for subjective Image quality is analyzed on the basis of the validity of SQRI method as a metric for the evaluation of subjective image quality. ality.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.159-168
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• 2015

Aggregate Production Planning determines levels of production, human resources, inventory to maximize company's profits and fulfill customer's demands based on demand forecasts. Since performance of aggregate production planning heavily depends on accuracy of given forecasting demands, choosing an accurate forecasting method should be antecedent for achieving a good aggregate production planning. Generally, typical forecasting error metrics such as MSE (Mean Squared Error), MAD (Mean Absolute Deviation), MAPE (Mean Absolute Percentage Error), and CFE (Cumulated Forecast Error) are utilized to choose a proper forecasting method for an aggregate production planning. However, these metrics are designed only to measure a difference between real and forecast demands and they are not able to consider any results such as increasing cost or decreasing profit caused by forecasting error. Consequently, the traditional metrics fail to give enough explanation to select a good forecasting method in aggregate production planning. To overcome this limitation of typical metrics for forecasting method this study suggests a new metric, WACFE (Weighted Absolute and Cumulative Forecast Error), to evaluate forecasting methods. Basically, the WACFE is designed to consider not only forecasting errors but also costs which the errors might cause in for Aggregate Production Planning. The WACFE is a product sum of cumulative forecasting error and weight factors for backorder and inventory costs. We demonstrate the effectiveness of the proposed metric by conducting intensive experiments with demand data sets from M3-competition. Finally, we showed that the WACFE provides a higher correlation with the total cost than other metrics and, consequently, is a better performance in selection of forecasting methods for aggregate production planning.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.31-43
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• 2014

A depth map is an important component for stereoscopic image generation. Since the depth map acquired from a depth camera has a low resolution, upsamling a low-resolution depth map to a high-resolution one has been studied past decades. Upsampling methods are evaluated by objective evaluation tools such as PSNR, Sharpness Degree, Blur Metric. As well, the subjective quality is compared using virtual views generated by DIBR (depth image based rendering). However, works on the analysis of the relation between depth map upsampling and stereoscopic images are relatively few. In this paper, we investigate the relationship between subjective evaluation of stereoscopic images and objective performance of upsampling methods using cross correlation and linear regression. Experimental results demonstrate that the correlation of edge PSNR and visual fatigue is the highest and the blur metric has lowest correlation. Further, from the linear regression, we found relative weights of objective measurements. Further we introduce a formulae that can estimate 3D performance of conventional or new upsampling methods.