• Korean Journal of Acupuncture
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• 제35권3호
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• pp.149-158
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• 2018

Objectives : In this study, we quantitatively evaluated the needle forces using needle insertion-measurement system and compared the needle sensation of each acupuncture practical model. Methods : After inserting acupuncture with a sensor to six models, a lifting-thrusting motion was implemented using the needle insertion-measurement system. The needle force was measured repeatedly, and the measurement was analyzed based on the modified Karnopp friction model for a comparison of friction coefficients. After the insertion, practitioners did lifting-thrusting manipulations. They quantified the similarity of needle sensation with VAS (Visual Analogue Scale). Results : When friction force and coefficients of friction in five different models were compared with a porcine shank model, all five models were significantly different from a porcine shank model, cotton and apple showing the closest frictional values to that of a porcine shank model. In the Cp and Cn values of cotton and in the Cp values of IM injection pad, there was no statistically significant difference. The similarity of the needle sensation between the porcine shank and five models was the highest in the apple, and overlapping papers was the lowest. Conclusions : This study quantitatively compared the physical forces in the practical model when implementing lifting-thrusting manipulations, using a needle insertion-measurement system. We suggest that a reproducible exercise model that reflects the characteristics of various human tissues, such as viscoelasticity or strength, needs to be further developed. This will contribute to establishing standardized acupuncture practice training.

• 한국도로학회논문집
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• 제18권1호
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• pp.91-97
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• 2016

PURPOSES : The objective of this paper is to develop a pavement performance model based on the Bayesian algorithm, and compare the measured and predicted performance data. METHODS : In this paper, several pavement types such as SMA (stone mastic asphalt), PSMA (polymer-modified stone mastic asphalt), PMA (polymer-modified asphalt), SBS (styrene-butadiene-styrene) modified asphalt, and DGA (dense-graded asphalt) are modeled in terms of the performance evaluation of pavement structures, using the Bayesian algorithm. RESULTS : From case studies related to the performance model development, the statistical parameters of the mean value and standard deviation can be obtained through the Bayesian algorithm, using the initial performance data of two different pavement cases. Furthermore, an accurate performance model can be developed, based on the comparison between the measured and predicted performance data. CONCLUSIONS : Based on the results of the case studies, it is concluded that the determined coefficients of the nonlinear performance models can be used to accurately predict the long-term performance behaviors of DGA and modified asphalt concrete pavements. In addition, the developed models were evaluated through comparison studies between the initial measurement and prediction data, as well as between the final measurement and prediction data. In the model development, the initial measured data were used.

• ETRI Journal
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• 제34권6호
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• pp.858-868
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• 2012

In this paper, stochastic models for the cross-correlation of multiple channels are established based on measurement data collected using a wideband multiple-input multiple-output relay Band Exploration and Channel Sounder system at 3.7 GHz. We propose models for the cross-correlation characteristics of large-scale parameters (LSPs) between two links, that is, the base station and mobile station (MS) link and the relay station and MS link. The LSPs include shadow fading, Rician K-factor, delay spread, angle spread of arrival, and angle spread of departure. Furthermore, models are established for the cross-correlation of the small-scale fading in the impulse responses of two links. The statistics of these model parameters are investigated as functions of geometrical features of the multilink. They are extracted from a large amount of cross-correlation observations, which are obtained in three measurement sites along more than one hundred measurement routes. These models can be used together with the standard single-link channel models for the generation of correlated components, for example, path clusters, in two separate channels.

• Wind and Structures
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• 제32권2호
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• pp.143-159
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• 2021

The 246.8-m-tall Beijing Olympic Tower (BOT) is a new landmark in Beijing City, China. Its unique architectural style with five sub-towers and a large tower crown gives rise to complex dynamic characteristics. Thus, it is wind-sensitive, and a double-stage pendulum tuned mass damper (DPTMD) has been installed for vibration mitigation. In this study, a finite-element analysis of the wind-induced responses of the tower based on full-scale measurement results was performed. First, the structure of the BOT and the full-scale measurement are introduced. According to the measured dynamic characteristics of the BOT, such as the natural frequencies, modal shapes, and damping ratios, an accurate finite-element model (FEM) was established and updated. On the basis of wind measurements, as well as wind-tunnel test results, the wind load on the model was calculated. Then, the wind-induced responses of the BOT with the DPTMD were obtained and compared with the measured responses to assess the numerical wind-induced response analysis method. Finally, the wind-induced serviceability of the BOT was evaluated according to the field measurement results for the wind-induced response and was found to be satisfactory for human comfort.

• 동의생리병리학회지
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• 제36권5호
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• pp.193-208
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• 2022

In this study, we proposed a mathematical model that can explain the source of the observed variability of repeated measurement data collected in Korean medicine clinical practice, and conducted a pilot analysis to infer the source of these variability based on our model. Mathematical model was constructed by dividing the observed variations into three components: common time-dependent variations, signal shift, and measurement error. To show the applicability of our model in real data, we analyzed 20 repeated measurement data of Korean clinical indicators in graduate students of Pusan National University Graduate School of Korean Medicine. We showed how to infer each source of variations based on our model and also showed the limitation of inference given the acquired the dataset. On the basis of objective recognition of these source of the variability, we hope that quantitative investigations on these sources for each Korean medicine clinical indicator are made in the future, so that they can be used in the clinical and educational areas of Korean medicine.

• 한국CDE학회논문집
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• 제11권5호
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• pp.335-343
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• 2006

Design changes for an original surface model are frequently required in a manufacturing area: for example, when the physical parts are modified or when the parts are partially manufactured from analogous shapes. In this case, an efficient 3D model updating method by locally adding scan data for the modified area is highly desirable. For this purpose, this paper presents a new procedure to update an initial model that is composed of combinatorial triangular facets based on a set of locally added point data. The initial surface model is first created from the initial point set by Tight Cocone, which is a water-tight surface reconstructor; and then the point cloud data for the updates is locally added onto the initial model maintaining the same coordinate system. In order to update the initial model, the special region on the initial surface that needs to be updated is recognized through the detection of the overlapping area between the initial model and the boundary of the newly added point cloud. After that, the initial surface model is eventually updated to the final output by replacing the recognized region with the newly added point cloud. The proposed method has been implemented and tested with several examples. This algorithm will be practically useful to modify the surface model with physical part changes and free-form surface design.

• 정보처리학회논문지D
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• 제12D권1호
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• pp.91-102
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• 2005

과거 소프트웨어 품질은 곧 제품품질이란 인식이 지배적이었다. 하지만 현대에 소프트웨어가 거대화되고 복잡해짐에 따라 제품품질만을 가지고서는 고객의 요구조건에 맞는 양질의 소프트웨어를 제작하는데 있어 한계가 있었다. 이러한 이유로 현재 국내외 많은 기업들은 프로세스 개선을 통한 제품품질 향상을 위하여 노력을 기울이고 있다. 프로세스 개선활동 중 측정 활동은 프로세스 개선에 대한 효과를 향상시키며, 프로세스 개선 활동을 파악하고, 이를 효과적으로 구현하는데 있어 많은 도움을 줄 수 있다. 본 논문은 현재 국내외 많은 기업들이 프로세스 개선 모델로 채택하고 있는 CMMI를 기반으로 측정 프로그램에 관한 연구를 수행하였다. CMMI의 프로세스 영역 중 측정 프로세스 수립에 대해서 다루고 있는 MA 프로세스 영역을 기반으로 측정 프로그램을 수립하였으며, 이렇게 개발한 측정 프로그램을 통해 CMMI 각 레벨 별로 측정 프로그램이 어떠한 차이를 두고 있으며, 어떻게 측정 프로그램을 작용할 지에 대해 연구하였다. 본 연구를 통해 CMMI 기반의 프로세스 개선을 수행하고 있거나 시작하려는 기업들에게 측정 프로그램 수립 지원할 수 있으며, 더 나아가 레벨 별로 진화하는 측정 프로그램의 로드맵을 제시하고자 한다.

• 지능정보연구
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• 제4권1호
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• pp.133-147
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• 1998

Recently, many researchers have been involved in finding deterministic equations which can accurately predict future event, based on chaotic theory, or fractal theory. The theory says that some events which seem very random but internally deterministic can be accurately predicted by fractal equations. In contrast to the conventional methods, such as AR model, MA, model, or ARIMA model, the fractal equation attempts to discover a deterministic order inherent in time series data set. In discovering deterministic order, researchers have found that neural networks are much more effective than the conventional statistical models. Even though prediction accuracy of the network can be different depending on the topological structure and modification of the algorithms, many researchers asserted that the neural network systems outperforms other systems, because of non-linear behaviour of the network models, mechanisms of massive parallel processing, generalization capability based on adaptive learning. However, recent survey shows that prediction accuracy of the forecasting models can be determined by the model structure and data structures. In the experiments based on actual economic data sets, it was found that the prediction accuracy of the neural network model is similar to the performance level of the conventional forecasting model. Especially, for the data set which is deterministically chaotic, the AR model, a conventional statistical model, was not significantly different from the MLP model, a neural network model. This result shows that the forecasting model. This result shows that the forecasting model a, pp.opriate to a prediction task should be selected based on characteristics of the time series data set. Analysis of the characteristics of the data set was performed by fractal analysis, measurement of Hurst index, and measurement of Lyapunov exponents. As a conclusion, a significant difference was not found in forecasting future events for the time series data which is deterministically chaotic, between a conventional forecasting model and a typical neural network model.

• 한국수자원학회논문집
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• 제55권spc1호
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• pp.1295-1303
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• 2022

안정적인 수도 공급을 위한 상수도관망의 역할이 더욱 주목받음에 따라 비정상 상황에 대한 신속한 탐지와 적절한 대처 역시 중요시되고 있다. 장치에 의존한 탐지기법 등 기존의 방법론에는 한계가 존재하므로 데이터를 이용한 모델 기반의 방법이 개발되었다. 하지만 상수도관망 내 측정 데이터는 불확실성을 가져 실제 사용량과 다르다. 따라서 본 연구에서는 기계학습 방법의 하나인 인공신경망 모델을 이용하여 상수도관망 압력값을 예측함에 있어 데이터 불확실성의 영향을 조사한다. 정규분포를 따르는 임의의 값을 고려하여 데이터에 측정치 오류를 형성하고 측정치 오류 여부 및 종류에 따라 총 9가지 데이터를 인공신경망 모델을 통해 예측해 경향성을 비교한다. 분석을 통해 데이터 불확실성이 증가할수록 모델 성능이 감소하며, 출력데이터의 측정치 오류가 모델 성능에 미치는 정도가 더 큼을 확인하였다. 특히 입력데이터와 출력데이터의 측정 오차 크기가 동일한 경우 예측 정확도는 각각 72.25%, 38.61%로 큰 차이를 보였다. 따라서 ANN 모델 예측 성능 향상을 위해서는 입력 데이터보다 출력데이터인 주절점의 측정 오류 크기를 줄이는 것이 중요하다.

• Journal of Positioning, Navigation, and Timing
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• 제5권1호
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• pp.1-9
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• 2016

Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.