• Proceedings of the Korean Society of Crop Science Conference
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• 1999.11a
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• pp.102-144
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• 1999

The major problems of food crop cultivation in Korea are low yield of most crops except rice. inefficient cultivation techniques for aged farmers. and low international competibility. Therefore, development of cultivation techniques of food crops should aim the yield. quality improvement, labor reduction and production cost. The primary issue for increasing the yield of soybean, barely and wheat is to reduce the yield gap between the farmer's yield and recommended ones of experiment station. More advanced cultivation techniques needs to be developed. and/or the conventional breeding methods to be reconsidered. The newly developed labor-saving mechanized technique needs to reduce labor hours , and the cost of agricultural implements and machineries. In other words the labor-saving mechanized technique should be developed based on the improvement of total farming system as well as systemic fundamental innovation of cultural methods. The efficiency of solar energy use in food production of Korea in 1997 is as low as $0.52{\%}$ so there is much room to increase yield. It is recommendable that the concept of food Production should be changed to energy Producing efficiency Per unit area basis from volume and weight of food materials. Moreover, introduction of resonable cropping system is needed to increase yield of main crops, farmer's income, solar energy use efficiency, and decrease of land service expenditure. Current cropping system emphasized on economic crops. especially in vegetables , is not desirable for resonable use of arable land. stability of agricultural management and staple food crop self-sufficiency ratio. It is desirable to increase food crops . that are energy of carbohydrate and protein rich and land dependent crops. in cropping system. And the agronomist should develop the cultural methods to replace food crops for food self-sufficiency and stable farming management instead of economic crops in current cropping system. Low-input and environmentally-sound crop cultivation techniques, especially nitrogen-reducing culture technique which is directly related to food crop quality, also needs to be developed urgently. The extended cultivation of corn in upland and barely and wheat in lowland as a feed stuffs is recommended to prevent further decrease of food self-sufficiency ratio, which is mainly caused by the high reliance on imported feed grain. It is also considered that the calculation and presentation methods of standard agricultural income needs to be improved. The current calculation method uses unit land area of 10a regardless of crop kinds , characteristics of agricultural management and cultivation scale. So, it is apt to lead misunderstanding of farm income value. Therefore. it should show an income of average farmers for certain number of years. Research and developing system for food producing is not desirable because they are conducted currently individual crop and mono-culture basis. But actual agricultural income is usually earned by cropping system including upland and lowland. For example. the barley and wheat is usually cultivated in double cropping system. The cooperation among research institutes such as university agribusiness. government and farmers is indispensible. The public information and education on importance and consumption habit of food crops is necessary in Korean society to increase food self-sufficiency through nationwide cooperation.

• The Journal of Engineering Geology
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• v.9 no.3
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• pp.187-206
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• 1999

A computer program to numerically predict the permeability tensor of fractured rocks is developed using information on discontinuities which Borehole Televiewer and Borehole Image Processing System (BIPS) provide. It uses orientation and thickness of a large number of discontinuities as input data, and calculates relative values of the 9 elements consisting of the permeability tensor by the formulation based on the EPM model, which regards a fractured rock as a homogeneous, anisotropic porous medium. In order to assess feasibility of the program on field sites, the numerically calculated tensor was obtained using BIPS logs and compared to the results of pumping test conducted in the boreholes of the study area. The degree of horizontal anisotropy and the direction of maximum horizontal permeability are 2.8 and $N77^{\circ}CE$, respectively, determined from the pumping test data, while 3.0 and $N63^{\circ}CE$ from the numerical analysis by the developed program. Disagreement between two analyses, especially for the principal direction of anisotropy, seems to be caused by problems in analyzing the pumping test data, in applicability of the EPM model and the cubic law, and in simplified relationship between the crack size and aperture. Aside from these problems, consideration of hydraulic parameters characterizing roughness of cracks and infilling materials seems to be required to improve feasibility of the proposed program. Three-dimensional assessment of its feasibility on field sites can be accomplished by conducting a series of cross-hole packer tests consisting of an injecting well and a monitoring well at close distance.

• Smart Media Journal
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• v.1 no.2
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• pp.40-46
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• 2012

In this paper, we describe interactive contents which is used the result of the inputted interface recognizing vision-based body gesture. Because the content uses the imp which is the common culture as the subject in Asia, we can enjoy it with culture familiarity. And also since the player can use their own gesture to fight with the imp in the game, they are naturally absorbed in the game. And the users can choose the multiple endings of the contents in the end of the scenario. In the part of the gesture recognition, KINECT is used to obtain the three-dimensional coordinates of each joint of the limb to capture the static pose of the actions. The vision-based 3D human pose recognition technology is used to method for convey human gesture in HCI(Human-Computer Interaction). 2D pose model based recognition method recognizes simple 2D human pose in particular environment On the other hand, 3D pose model which describes 3D human body skeletal structure can recognize more complex 3D pose than 2D pose model in because it can use joint angle and shape information of body part Because gestures can be presented through sequential static poses, we recognize the gestures which are configured poses by using HMM In this paper, we describe the interactive content which is used as input interface by using gesture recognition result. So, we can control the contents using only user's gestures naturally. And we intended to improve the immersion and the interest by using the imp who is used real-time interaction with user.

• Korean Journal of Health Education and Promotion
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• v.23 no.4
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• pp.173-192
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• 2006

Objectives: This job analysis of a staff in charge of quit-smoking policy at public health centers aims at providing fundamental information to establish strategies supporting various quit-smoking. Methods: The job analysis of a staff in charge of quit-smoking policy at public health centers was carried out through DACUM(Development of Curriculum) method from April through May 2006. Three experts had developed job description with staffs in charge of quit-smoking policy at public health centers through two workshops. The survey was practiced for staff in charge of quit-smoking policy at the other public health centers. The characteristics of the staffs such as age, years for working at public health center, years for charging with quit-smoking work, the proportion of responsibility for quit-smoking work, were surveyed. Results: The research has reached the conclusions below. 1. The job description have been developed considering input-process-outcome axis and plan-do-evaluation axis for quit-smoking policy at public health centers. The final job description is composed of 3 missions, 7 accountabilities, 20 sub-work items. 2. The quit-smoking activity mostly focused at direct education and counselling. But planing and evaluation activity for quit-smoking have been under-achieved. 3. The staffs for quit-smoking policy were feel it is easy to educate and counsel to comer to public health centers for quit-smoking. But having the high proportion of responsibility for quit-smoking policy have usually difficult to do that. So they want to education about counselling for smoker. 4. The staffs who worked over the 2 years for quit-smoking policy the public health center have responded that investigate the smoking rate of the jurisdiction community and the problem of the culture about smoking and smoking policy is important. Conclusions: The study helps reinforcing the initiatives of central government for quit-smoking policy at public health centers. Especially staffs want education in technology area for counselling smoker. And they want nationwide supporting for investigating smoking rate and related factors at the local level.

• Culinary science and hospitality research
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• v.22 no.5
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• pp.52-63
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• 2016

This research was conducted about four weeks from April 1, 2016 until April 30. Data collection for customers who visit the restaurant franchise in Seoul. Results shown that choose a restaurant franchise result sync conducted a regression analysis to analyze the impact on consumers' purchase intention. Kindness was the influence of B=0.597 (p<.001), is a unique B=0.210 (p<.001), cleanliness is B=0.230 (p<.001) significant information on the degree of consumer purchases (+). Second, choose a restaurant franchise motivation verify the moderating effect of consumer attitudes between the purchase intention of consumers eating out analysis. In the first stage determining factor model to 0.630, F=128.612 (p<0.01) emerged as significant. In the second stage of the explanatory models increased by the addition of an additional 6.1% of consumer attitudes consumer attitudes to F=58.656 (p<0.01) for it came out significantly. In Step 3 of Select synchronization options* and the increase in explanatory power due to the additional input of consumer attitudes 0.6%, so for F=1.585 (p<0.01) emerged as a significant moderating effect.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.3 s.118
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• pp.334-340
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• 2007

The prediction for vegetation attenuation using the RET model recommended in the ITU-R requires six RET input parameters. Among these, 4 parameters are related to the scattering characteristics of vegetation. To extract these parameters, two methods can be used. One is to extract the parameters by curve fitting of the measured vegetation-attenuation curve with the RET prediction model, and the other is to use the additional phase function measurement data. In the former method, fitting is quite complex and it does not result in the unique results in some cases. In addition, the extracted parameters lack the physical meaning as well. Thus, in this paper, the measurement method of phase function, and the method of extracting the RET model parameters which lead to more accurate and physically more meaningful results are presented. The extracted RET model parameters are also presented. The RET modeling method, measurement data, and the extracted RET model parameters presented in this paper were submitted to the ITU-R meeting in 2006, and adapted for ITU-R report and recommendation P.833.

• Journal of Bio-Environment Control
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• v.29 no.3
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• pp.277-284
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• 2020

To increase the utilization of the intelligent methodology of smart farm management, estimation modeling techniques are required to assess prior examination of crops and environment changes in realtime. A mandatory environmental factor such as CO₂ is challenging to establish a reliable estimation model in time domain accounted for indoor agricultural facilities where various correlated variables are highly coupled. Thus, this study was conducted to develop an artificial neural network for reducing time complexity by using environmental information distributed in adjacent areas from a time perspective as input and output variables as CO₂. The environmental factors in the smart farm were continuously measured using measuring devices that integrated sensors through experiments. Modeling 1 predicted by the mean data of the experiment period and modeling 2 predicted by the day-to-day data were constructed to predict the correlation of CO₂. Modeling 2 predicted by the previous day's data learning performed better than Modeling 1 predicted by the 60-day average value. Until 30 days, most of them showed a coefficient of determination between 0.70 and 0.88, and Model 2 was about 0.05 higher. However, after 30 days, the modeling coefficients of both models showed low values below 0.50. According to the modeling approach, comparing and analyzing the values of the determinants showed that data from adjacent time zones were relatively high performance at points requiring prediction rather than a fixed neural network model.

• Clean Technology
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• v.24 no.3
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• pp.166-174
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• 2018

Since particulate matter has high impacts on human health and everyday life, the dual fuel systems utilizing diesel and compressed natural gas have been developed to improve the environmental performance of diesel vehicles. The objective of this study is to estimate the economic feasibility of the dual fuel system based on real operating data of dual fuel buses and diesel buses. The system is economically feasible if the annual mileage of the dual bus is higher than 30,000 km, or if the unit fuel price of diesel is higher than that of CNG by 408 won. The uncertainty analysis results show that the economic feasibility of the system is probabilistically high, regardless of the variability of input data such as mileage and unit prices for the fuels. The sensitivity analysis results show that diesel and CNG prices are the highest contributor to the net present value of the system. Based on these results, economic incentives are suggested to disseminate the systems. This study would provide valuable economic information for bus business industry and policy maker to help make decisions for applying and disseminating the dual fuel systems to mitigate particulate matter problems.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.497-504
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• 2020

Constructing speaker embeddings in speaker verification is an important issue. In general, a self-attention mechanism has been applied for speaker embedding encoding. Previous studies focused on training the self-attention in a high-level layer, such as the last pooling layer. In this case, the effect of low-level layers is not well represented in the speaker embedding encoding. In this study, we propose Masked Cross Self-Attentive Encoding (MCSAE) using ResNet. It focuses on training the features of both high-level and low-level layers. Based on multi-layer aggregation, the output features of each residual layer are used for the MCSAE. In the MCSAE, the interdependence of each input features is trained by cross self-attention module. A random masking regularization module is also applied to prevent overfitting problem. The MCSAE enhances the weight of frames representing the speaker information. Then, the output features are concatenated and encoded in the speaker embedding. Therefore, a more informative speaker embedding is encoded by using the MCSAE. The experimental results showed an equal error rate of 2.63 % using the VoxCeleb1 evaluation dataset. It improved performance compared with the previous self-attentive encoding and state-of-the-art methods.

• Journal of KIISE
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• v.42 no.12
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• pp.1535-1543
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• 2015

The brain-computer interface obtains a user's electroencephalogram as a replacement communication unit for the disabled such that the user is able to control machines by simply thinking instead of using hands or feet. In this paper, we propose a feature extraction method based on a non-selected filter by SBCSP to classify motor imagery EEG. First, we divide frequencies (4~40 Hz) into 4-Hz units and apply CSP to each Unit. Second, we obtain the FLD score vector by combining FLD results. Finally, the FLD score vector is projected onto the optimal plane for classification using PCA. We use BCI Competition III dataset IVa, and Extracted features are used as input for LS-SVM. The classification accuracy of the proposed method was evaluated using $10{\times}10$ fold cross-validation. For subjects 'aa', 'al', 'av', 'aw', and 'ay', results were $85.29{\pm}0.93%$, $95.43{\pm}0.57%$, $72.57{\pm}2.37%$, $91.82{\pm}1.38%$, and $93.50{\pm}0.69%$, respectively.