• Journal of the Korean Society of Propulsion Engineers
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• v.14 no.4
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• pp.59-64
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• 2010

Measurement uncertainty assessment was performed for altitude performance test for a turboshaft engine. Mathematical models of measurement were suggested for major performance parameters such as shaft horse power, fuel flow, specific fuel consumption, and airflow. The procedure was compared with the test of turbojet or turbofan engines. Uncertainty involved with the test condition measurement was assessed. Influence of the test condition measurement uncertainty on the corrected performance data was discussed. Uncertainty assessment result was provided for a example test case using a real altitude test facility. For major performance parameters, measurement uncertainties were assessed as 0.65~1.09% including the test condition measurement uncertainty, 0.36~0.94% not including it.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.1
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• pp.73-81
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• 2011

The performance of emission factor has been validated by comparison with on-road test data. Emission factor, which is a function of vehicle speed, has been acquired based on chassis dynamometer test with NIER driving pattern. Portable Emission Measurement System, PEMS has measured on-road emission. Test vehicle was operated on defined test routes under different driving conditions, and made ten trips along its route. Emission factors properly simulate on-road test result, although there is some drawback to consider variety of driving condition on real world. Vehicle specific power and acceleration have been used to explain the distributed on-road result within same vehicle speed range. The trend in carbon dioxide and nitrogen oxide emission with respect to specific power and acceleration is clear. It has been found that specific power is a good explanatory variable for microscopic analysis for modal test result. Acceleration is good for microscopic as well as macroscopic analysis.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.1
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• pp.119-128
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• 2017

G-induced Loss of Consciousness(G-LOC) can be predicted by measuring Electromyogram(EMG) signals. Existing studies have mainly focused on specific body parts and lacked of consideration with quantitative EMG indices. The purpose of this study is to analyze the indices of EMG signals by human body parts for monitoring G-LOC condition. The data of seven EMG features such as Root Mean Square(RMS), Integrated Absolute Value(IAV), and Mean Absolute Value(MAV) for reflecting muscle contraction and Slope Sign Changes(SSC), Waveform Length (WL), Zero Crossing(ZC), and Median Frequency(MF) for representing muscle contraction and fatigue was retrieved from high G-training on a human centrifuge simulator. A total of 19 trainees out of 47 trainees of the Korean Air Force fell into G-LOC condition during the training in attaching EMG sensor to three body parts(neck, abdomen, calf). IAV, MAV, WL, and ZC under condition after G-LOC were decreased by 17 %, 17 %, 18 %, and 4 % comparing to those under condition before G-LOC respectively. Also, RMS, IAV, MAV, and WL in neck part under condition after G-LOC were higher than those under condition before G-LOC; while, those in abdomen and calf part lower. This study suggest that measurement of IAV and WL by attaching EMG sensor to calf part may be optimal for predicting G-LOC.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.203-207
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• 2008

Prestack depth migration is used to image for complex geological structure such as faults, folds, and subsalt. In this case, it is widely used the surface reflection data as a input data. However, the surface reflection data have intrinsic problems to image the subsalt and the salt flank due to the complex wavefields and multiples which come from overburden. For overcoming the structural defect of the surface reflection data in the imaging, I used the virtual sources in terms of seismic interferometry to image the subsurface and suppress the multiples using the velocity model of the lower part of the virtual sources. The results of the prestack depth migration using virtual source gathers and velocity model below receivers are similar geological interfaces to the results from shot gathers of the conventional ocean bottom seismic survey. And especially artificial interfaces by multiples were suppressed without applying any other data processing to eliminate multiples. This study results by numerical modeling can make a valuable imaging tool when it is applied to satisfied field data for specific condition.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.2
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• pp.112-119
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• 2007

In order to predict vibration trends occurred during vehicle drive, acceleration data was processed by using data processing algorithm with moving average and Hilbert transform. Specific mode constants of acceleration were obtained under various disturbance. Vehicle velocity, road condition, property of pointing structure were considered as factors which make change of vibration trend in vehicle dynamics. Results of signal processing were compared and analysed. Advanced performance of the timing selection algorithm from this study was verified by using simple equipment comparing with the deflection measurement laser system(Muzzle Reference System).

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.6
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• pp.252-258
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• 1998

In a SI engine, it is necessary to control fuel quantity in accordance with intake air amount in order to reduce exhaust emission and improve the specific fuel consumption. Generally the map data is used for the vehicles with a SI engine. For the precise control of air-fuel ratio, the real time control method is recommended rather than the control method using map data. In this paper, we developed real time control system using microprocessor and IBM-PC, and applied it to the commercial SI engine. We got good results for air-fuel ratio under the idle condition.

• Journal of Korean society of Dental Hygiene
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• v.20 no.6
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• pp.831-841
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• 2020

Objectives: The purpose of this study was to investigate the oral health status and oral health behavior and identify the factors related to the oral health status by age-specific groups in vulnerable elderly individuals. Methods: We used data from the 7th Korea National Health and Nutrition Examination Survey. The differences in the oral health status and oral health behavior by age-specific groups were analyzed using complex sample chi-square tests and a generalized linear model. The relationship between the oral health status and oral health behavior by age-specific groups was analyzed using a complex samples general linear model. Results: The DMFT index of the young-old elderly was 10.65±0.60, and that of the old-old elderly was 12.78±0.72, which was higher. The condition of the mandibular prosthesis was more common in the old-old elderly, and there was a statistically significant difference (p<0.05). The DMFT index in the old-old elderly was found to be higher as the average number of brushings per day decreased, and no oral examination was performed. Conclusions: The vulnerable elderly themselves are interested in maintaining their own health, and the government needs to undertake efforts to reduce the medical blind spots by supporting institutional and environmental conditions so that health care services can be provided to the vulnerable elderly.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.6
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• pp.264-273
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• 2006

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) by means of consecutive optimization and also discuss its comprehensive design methodology involving mechanisms of genetic optimization. The network is based on a structurally as well as parametrically optimized fuzzy polynomial neurons (FPNs) conducted with the aid of information granulation and genetic algorithms. In structurally identification of FPN, the design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics and addresses specific aspects of parametric optimization. In addition, the fuzzy rules used in the networks exploit the notion of information granules defined over system's variables and formed through the process of information granulation. That is, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. This granulation is realized with the aid of the hard c-menas clustering method (HCM). For the parametric identification, we obtained the effective model that the axes of MFs are identified by GA to reflect characteristic of given data. Especially, the genetically dynamic search method is introduced in the identification of parameter. It helps lead to rapidly optimal convergence over a limited region or a boundary condition. To evaluate the performance of the proposed model, the model is experimented with using two time series data(gas furnace process, nonlinear system data, and NOx process data).

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.653-662
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• 2016

This paper describes a test case generation algorithm for Simulink/Stateflow models based on the Rapidly exploring Random Tree (RRT) algorithm that has been successfully applied to path finding. An important factor influencing the performance of the RRT algorithm is the metric used for calculating the distance between the nodes in the RRT space. Since a test case for a Simulink/Stateflow (SL/SF) model is an input sequence to check a specific condition (called a test target in this paper) at a specific status of the model, it is necessary to drive the model to the status before checking the condition. A status maps to a node of the RRT. It is usually necessary to check various conditions at a specific status. For example, when the specific status represents an SL/SF model state from which multiple transitions are made, we must check multiple conditions to measure the transition coverage. We propose a unique distance calculation metric, based on the observation that the test targets are gathered around some specific status such as an SL/SF state, named key nodes in this paper. The proposed metric increases the probability that an RRT is extended from key nodes by imposing penalties to non-key nodes. A test case generation algorithm utilizing the proposed metric is proposed. Three models of Electrical Control Units (ECUs) embedded in a commercial vehicle are used for the performance evaluation. The performances are evaluated in terms of penalties and compared with those of the algorithm using a typical RRT algorithm.

• Journal of Environmental Impact Assessment
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• v.20 no.6
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• pp.879-890
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• 2011

The GOSAT (Greenhouse gases Observing SATellite) data provide new opportunities the most regionally complete and up-to-date assessment of $CO_2$. However, in practice, GOSAT records often suffer from missing data values mainly due to unfavorable meteorological condition in specific time periods of data acquisition. The aim of this research was to identify optimal spatial interpolation techniques to ensure the continuity of $CO_2$ from samples taken in the North East Asia. The accuracy among ordinary kriging (OK), universal kriging (UK) and simple kriging (SK) was compared based on the combined consideration of $R^2$ values, Root Mean Square Error (RMSE), Mean Error (ME) for variogram models. Cross validation for 1312 random sampling points indicate that the (UK) kriging is the best geostatistical method for spatial predictions of $CO_2$ in the East Asia region. The results from this study can be useful for selecting optimal kriging algorithm to produce $CO_2$ map of various landscapes. Also, data users may benefit from a statistical approach that would allow them to better understand the uncertainty and limitations of the GOSAT sample data.