• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.752-760
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• 1993

We research ed on the noise control of a head feeding type combine harvester. It is a kind of combine harvester developed in Japan. And at present, it is used by most Japanese farmer. For a head-feeding type combine harvester it is very difficult to determine the sources of noise because it is a combination of reapers and automatic , threshers and several running parts. However we succeeded in finding out the sound sources of combine harvesters and analyzing their sound by the using sound intensity method. The sound intensity Method is a very up-to-date method to measure and analyze Sound Intensity Levels and sound directions at several measuring point sin a specified area. In this research, first a conventional sound level measurement method is used and secondly the sound intensity method. The first method shows a rather great limitation in allowed exposure duration. The second method shows pin-points the engine itself as being the main source of noise, causing sound flows a ross the operator's seat.

• Journal of Navigation and Port Research
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• v.29 no.8 s.104
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• pp.755-761
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• 2005

In this paper, we propose a high-speed adaptive PTS method which eliminates high PAR (Peak-to-Average Power Ratio) and we compare the proposed method with other conventional methods. In addition, we have designed a combined type SLM-PTS scheme to reduce PAR and evaluate the performance. The system used for evaluating PAR performance can be constructed as COFDM (Coded Orthogonal Frequency Division Multiplexing) applying ETD(Enhabced Time Diversity)-Turbo coding scheme. All the analyses in this paper are focused on the system characteristics according to IFFT's point and modulation method and the performance evaluation are based on the PAR reduction rates. As a result, the SLM-PTS combination method reveals good PAR reduction rate and remarkable reduction in the amount of calculations. Especially, in the case of combine-3 scheme, we can achieve approximately $3.7\~3.9$ dB PAR reduction on a basis of 10-5 BER level. Moreover, we can eliminate the side information in COFDM system because of its adaptive characteristics in evaluating PAR reduction rate, so that the additional errors can be omitted.

• Journal of Korea Water Resources Association
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• v.40 no.1 s.174
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• pp.73-88
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• 2007

The goal of this research is to develop and apply the generalized regression neural networks model(GRNNM) embedding genetic algorithm(GA) for the estimation and calculation of the pan evaporation(PE), which is missed or ungaged and of the alfalfa reference evapotranspiration ($ET_r$), which is not measured in South Korea. Since the observed data of the alfalfa 37. using Iysimeter have not been measured for a long time in South Korea, the Penman-Monteith(PM) method is used to estimate the observed alfalfa $ET_r$. In this research, we develop the COMBINE-GRNNM-GA(Type-1) model for the calculation of the optimal PE and the alfalfa $ET_r$. The suggested COMBINE-GRNNM-GA(Type-1) model is evaluated through training, testing, and reproduction processes. The COMBINE-GRNNM-GA(Type-1) model can evaluate the suggested climatic variables and also construct the reliable data for the PE and the alfalfa $ET_r$. We think that the constructive data could be used as the reference data for irrigation and drainage networks system in South Korea.

• The Journal of the Society of Stroke on Korean Medicine
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• v.18 no.1
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• pp.1-11
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• 2017

It is difficult to combine oriental and western medicine. Each medicine has a different academic background, perspective on the world, and studying methodology. The claim that two paradigms can not be combined is not obtained from an actual verification, but this means it is so hard to combine two medicines having different backgrounds. The amalgamation of oriental and western medicine should be phased in on the basis of the continuous reciprocal understanding and commitment. First, the strength and weakness of each medicine over the treatment and research are required to be identified. Then, a few complementary areas can be chosen enabling a trial of fusion on a small scale. A cycle of problem solving and a new research can be set by analyzing research results obtained through the implementation over a period of time. In other words, the researchers of oriental and western medicine should repeat a continuous and gradual complementary research process by identifying issues to be improved and complemented through a consensus. Once the methodology obtained through the process of problem solving and proficient implementation is established in a stable condition, a method to widen the fusion area by expanding the operating area and implementation method can be chosen. However, the integral system of oriental medicine shouldn't be substituted by mechanical idea or reductionism. What should be done primarily for oriental medicine is to objectify things through quantification. In particular, the oriental treatment should accept the microscopic diagnosis to determine the structure and observe the biochemical change.

• ETRI Journal
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• v.45 no.5
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• pp.822-835
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• 2023

Recent semantic segmentation frameworks usually combine low-level and high-level context information to achieve improved performance. In addition, postlevel context information is also considered. In this study, we present a Context ReFinement Network (CRFNet) and its training method to improve the semantic predictions of segmentation models of the encoder-decoder structure. Our study is based on postprocessing, which directly considers the relationship between spatially neighboring pixels of a label map, such as Markov and conditional random fields. CRFNet comprises two modules: a refiner and a combiner that, respectively, refine the context information from the output features of the conventional semantic segmentation network model and combine the refined features with the intermediate features from the decoding process of the segmentation model to produce the final output. To train CRFNet to refine the semantic predictions more accurately, we proposed a sequential training scheme. Using various backbone networks (ENet, ERFNet, and HyperSeg), we extensively evaluated our model on three large-scale, real-world datasets to demonstrate the effectiveness of our approach.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.1
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• pp.1-24
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• 1997

In this paper, we have proposed new solution methods to solve TSLP (two-stage stochastic linear programming) problems. One solution method is to combine the analytic center concept with Benders' decomposition strategy to solve TSLP problems. Another method is to apply an idea proposed by Geoffrion and Graves to modify the L-shaped algorithm and the analytic center algorithm. We have compared the numerical performance of the proposed algorithms to that of the existing algorithm, the L-shaped algorithm. To effectively compare those algorithms, we have had computational experiments for seven test problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.117-120
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• 1996

The objective of this study is to suggest modified Covariance Structure Analysis that combine with existing Multivariate Statistical Method which is used Casual Analysis Method in Management Information. For this purpose, we'll consider special feature and limitation about Correlation Analysis, Regression Analysis, Path Analysis and connect Covariance Structure Analysis with Statistical Factor Analysis so that theoretical casual model compare with variables structure in collecting data. A example is also presented to show the practical applicability of this approach.

• Communications for Statistical Applications and Methods
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• v.23 no.1
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• pp.85-91
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• 2016

Aggregate claim amounts with a large claim frequency represent a major concern to automobile insurance companies. In this paper, we show that a new hybrid method to combine the analytical saddlepoint approximation and Monte Carlo simulation can be an efficient computational method. We provide numerical comparisons between the hybrid method and the usual Monte Carlo simulation.

• Nuclear Engineering and Technology
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• v.30 no.6
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• pp.617-627
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• 1998

A technically more direct Statistical Combination of Uncertainties (SCU) method, extended SCU (XSCU), was developed to statistically combine the uncertainties associated with the DNBR alarm setpoint and the DNBR trip setpoint of digital nuclear power plants. The Modified SCU (MSCU) method is currently used as the USNRC approved design method to perform the same function. In this study, the MSCU and XSCU methods were compared in terms of the total uncertainties, and the thermal margins to the DNBR alarm and trip setpoints. The MSCU method resulted in small total uncertainties due to large negative biases which are unphysical. The XSCU method gives virtually unbiased total uncertainties which are physically meaningful in order to represent the actual magnitude of the total uncertainties associated with the DNBR alarm and trip setpoints. But the thermal margins to the DNBR alarm and trip setpoints by the MSCU method agree with those by the XSCU method within allowable statistical Variations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.65-71
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• 2008

Recently, the research is progressing on the SWE(Sensor Web Enablement) platform of OGC(Open Geospatial Consortium) to provide the sensing data and moving pictures collected in a sensor network through the Internet Web. However, existed research does not deal with moving objects like cars, trains, ships, and person. Therefore, we present a method to deal with integrated sensing data collected by GPS device, sensor network, and image devices. Also, this paper proposes an integrated processing method for image and sensing data based on location in mobile sensor networks. Additionally, according to proposed methods, we design and implement the combine adapter. This combine adapter receives a contexts data, and provides the common interface included parsing, queueing, creating unified message function. We verity the proposed method which deal with the integrated sensing data based on combine adapter efficiently. Therefore, the research is expected to help the development of a various context information service based on location in future.