• Korean Journal of Poultry Science
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• v.32 no.3
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• pp.219-224
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• 2005

This study was carried out to investigate the effect of feldspar on laying Performance and e99 qualify in hens. A total of 96 'Tetra Brown' layers were assigned to 4 treatments in a completely randomized design. Each treatment consisted 4 replicates accommodating 6 layers per replication. Experiment diets were a control diet without feldspar and supplemented 0.5, 1.0 and $1.5\%$ feldspar. The egg Production rate was significantly increased in layers 134 diets supplemented 0.5 and $1.0\%$ feldspar compared to that of control (P<0.05). Egg weight, egg mass, feed intake, feed conversion ratio, egg shell strength and egg yolk color were not significantly different among the treatments (P>0.05). The haugh unit and blood spot of the eggs were significantly increased in $1.5\%$ feldspa. diets compared to that of control (p<0.05). However, the albumen index and meat spot in the eggs were not statistically different among treatments (P>0.05). Sensory evaluation traits were not significantly differed in terms of appearance, color, texture flavor and overall acceptability of eggs (P>0.05). The juiciness of boiled eggs was significantly increased in eggs of birds fed $1.0\%$ feldspar diets(P>0.05).

• Journal of Animal Science and Technology
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• v.50 no.4
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• pp.465-474
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• 2008

The amount of telomeric DNA was quantified across different breeds(Landrace, Duroc, Yorkshire and Berksire), at different ages(90 days old and 180 days old) and among sexes(male and female) in pigs raised at the Performance Testing Station of Korea Swine Association, Jinkyo, Korea. The telomeric DNA amount was quantified by Quantitative Fluorescence In Situ Hybridization(Q-FISH) using a porcine telomeric DNA probe on interphase nuclei of lymphocytes. Analysis revealed that the amount of telomeric DNA on the pig lymphocytes was found to decrease with age. The quantity of telomeres significantly differed among breeds at 90 days of age. The colored breeds such as Berkshire and Duroc had higher amount of telomeric DNA than the Yorkshire and Landrace breed. In addition, the amount of telomeric DNA in male lymphocytes was significantly higher than that of females. In the correlation coefficients between the telomere quantity and their productive traits; average daily gain, loin percent and index value were positively correlated, whereas body length, feed efficiency and back fat thickness correlated negatively. However, the correlation coefficients were very low and not significant. Therefore, this study suggests that the amount of telomeres on lymphocytes can be considered as a physiological marker but not as a productive marker in pig.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.275-290
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• 2019

The present study aimed to develop a sports psychological skill training program and to test its applicability to improve the performance of national wheelchair curling players. A total of 4 participants completed the study. Subjects have been to 12 sessions of 6 different psychological skills training programs (routine training, attentional focus training, writing practice training in diary, relation training, self-control training, and positive self-talk training). The effectiveness of psychological skills training has been evaluated with 6 questionnaires and EEG measurement. The result was that psychological skills training had improved coping with adversity, peaking under pressure, and concentration, self-management and reduced anxiety of Korean national wheelchair curling player. The result was that the EEG inter-hemispheric asymmetry index showed negative emotional states before psychological skill training but positive emotional states after. The result implies that psychological skill training plays an important mediating role in bringing about positive effects in the psychological elements and competitiveness in national wheelchair curling players.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.643-654
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• 2018

In order to understand and manage traffic flows in urban areas in the past, a variety of traffic engineering theoretical indicators such as intersection lag and highway speed have been applied. However, these theories and indicators have been developed under the constraints of traffic engineering research before the construction of intelligent transportation system. Since the ATIS system currently exists, it is necessary to introduce a separate traffic engineering technology that utilizes the data. In this paper, it is aimed to confirm whether it is applicable to intermittent flow (approach road, intersection, control group, main road axis) by using 'congestion intensity' which is already used in traffic engineering field. The results of this study are as follows: (1) The traffic signal improvement effect of urban road access road, intersection road, control group, Two verification studies were performed to verify the derived congestion intensity index. (1) verification of congestion intensity threshold value analysis and (2) crossing improvement using the congestion intensity. Through verification, it was confirmed that it is possible to apply the congestion intensity in the inter - city intermittent flow using the 5 - minute unit speed data so as to be able to escape from the existing traffic signal operation management which is past passive and manpower limit.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.9-16
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• 2021

In the past, there have been various studies on predicting the stock market by machine learning techniques using stock price data and financial big data. As stock index ETFs that can be traded through HTS and MTS are created, research on predicting stock indices has recently attracted attention. In this paper, machine learning models for KOSPI's up and down predictions are implemented separately. These models are optimized through a grid search of their control parameters. In addition, a hybrid machine learning model that combines individual models is proposed to improve the precision and increase the ETF trading return. The performance of the predictiion models is evaluated by the accuracy and the precision that determines the ETF trading return. The accuracy and precision of the hybrid up prediction model are 72.1 % and 63.8 %, and those of the down prediction model are 79.8% and 64.3%. The precision of the hybrid down prediction model is improved by at least 14.3 % and at most 20.5 %. The hybrid up and down prediction models show an ETF trading return of 10.49%, and 25.91%, respectively. Trading inverse×2 and leverage ETF can increase the return by 1.5 to 2 times. Further research on a down prediction machine learning model is expected to increase the rate of return.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.1
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• pp.20-25
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• 2021

The cement clinker, the main raw material of cement, is manufactured using limestone as the main material. Depending on the quality of limestone, the use of subsidiary materials changes, and has a great influence on the production of cement clinkers. In this study, the effect of CaO content of limestone, a cement clinker material, on Raw Mill grinding and sintering of cement clinker was investigated. The grinding time of the union materials changed in the content of limestone CaO was measured to identify the grinding properties. The raw material combination was cleaned within a range of 1,350-1,500℃. The sintering performance of cement clinker by Burnability index calculation was identified. The lower the grade of limestone, the lower the grinding quality of the raw material combination. The lower the CaO content of limestone, the greater the variation in F-CaO for sintering temperature. The lower the class of limestone, the higher B. I. value was calculated, indicating the lower cement clinker sintering. In addition, the mineral analysis results of cement clinker showed that if the F-CaO value was low due to the increase in sintering temperature, the Belite content decreased and the Alite content increased. In the case of Alite, the ratio of R-type decreased and that of M-type increased as the content of limestone CaO increased.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1407-1422
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• 2022

This study was conducted to classify tree species and assess the classification accuracy, using SE-Inception, a classification-based deep learning model. The input images of the dataset used Worldview-3 and GeoEye-1 images, and the size of the input images was divided into 10 × 10 m, 30 × 30 m, and 50 × 50 m to compare and evaluate the accuracy of classification of tree species. The label data was divided into five tree species (Pinus densiflora, Pinus koraiensis, Larix kaempferi, Abies holophylla Maxim. and Quercus) by visually interpreting the divided image, and then labeling was performed manually. The dataset constructed a total of 2,429 images, of which about 85% was used as learning data and about 15% as verification data. As a result of classification using the deep learning model, the overall accuracy of up to 78% was achieved when using the Worldview-3 image, the accuracy of up to 84% when using the GeoEye-1 image, and the classification accuracy was high performance. In particular, Quercus showed high accuracy of more than 85% in F₁ regardless of the input image size, but trees with similar spectral characteristics such as Pinus densiflora and Pinus koraiensis had many errors. Therefore, there may be limitations in extracting feature amount only with spectral information of satellite images, and classification accuracy may be improved by using images containing various pattern information such as vegetation index and Gray-Level Co-occurrence Matrix (GLCM).

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.9-24
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• 2022

Currently, a vast amount of hydrologic data is accumulated in real-time through automatic water level measuring instruments in agricultural reservoirs. At the same time, false and missing data points are also increasing. The applicability and reliability of quality control of hydrological data must be secured for efficient agricultural water management through calculation of water supply and disaster management. Considering the characteristics of irregularities in hydrological data caused by irrigation water usage and rainfall pattern, the Korea Rural Community Corporation is currently applying the Hampel filter as a water level data quality management method. This method uses window size as a key parameter, and if window size is large, distortion of data may occur and if window size is small, many outliers are not removed which reduces the reliability of the corrected data. Thus, selection of the optimal window size for individual reservoir is required. To ensure reliability, we compared and analyzed the RMSE (Root Mean Square Error) and NSE (Nash-Sutcliffe model efficiency coefficient) of the corrected data and the daily water level of the RIMS (Rural Infrastructure Management System) data, and the automatic outlier detection standards used by the Ministry of Environment. To select the optimal window size, we used the classification performance evaluation index of the error matrix and the rainfall data of the irrigation period, showing the optimal values at 3 h. The efficient reservoir automatic calibration technique can reduce manpower and time required for manual calibration, and is expected to improve the reliability of water level data and the value of water resources.

• Korean Journal of Environmental Biology
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• v.40 no.3
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• pp.307-315
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• 2022

In terms of habitat conservation, it is essential to develop a habitat assessment system that can evaluate not only the suitability of the current habitat, but also the health and stability of the habitat. This study aimed to develop a methodology of habitat quality assessment for endangered species by analyzing various existing habitat assessment methods. The habitat quality assessment consisted of selecting targeted species, planning of assessment, selecting targeted sites, assessing performance, calculating grade, and expert verification. Target sites were selected separately from core and potential habitats using a species distribution model or habitat suitability index. Habitat assessment factors were classified into ecological characteristic, landscape characteristic, and species-habitat characteristic. Ecological characteristic consisted of thirteen factors related to health of tree, vegetation, and soil. Landscape characteristic consisted of five factors related to fragment and connectivity of habitat. Species-habitat characteristic consisted of factors for evaluating habitat suitability depending on target species. Since meanings are different depending on characteristics, habitat quality assessment of this study could be used by classifying results for each characteristic according to various assessment purposes, such as designation of alternative habitats, assessment of restoration project, and protected area valuation for endangered species. Forest habitat quality assessment is expected to play an important role in conservation acts of endangered species in the future through continuous supplementation of this system in regard to quantitative assessment criteria and weighting for each factor with an influence.

• Steel and Composite Structures
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• v.47 no.1
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• pp.91-102
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• 2023

To study the evaluation standard and control limit of mortar filling layer void length, in this paper, the train sub-model was developed by MATLAB and the track-bridge sub-model considering the mortar filling layer void was established by ANSYS. The two sub-models were assembled into a train-track-bridge coupling dynamic model through the wheel-rail contact relationship, and the validity was corroborated by the coupling dynamic model with the literature model. Considering the randomness of fastening stiffness, mortar elastic modulus, length of mortar filling layer void, and pier settlement, the test points were designed by the Box-Behnken method based on Design-Expert software. The coupled dynamic model was calculated, and the support vector regression (SVR) nonlinear mapping model of the wheel-rail system was established. The learning, prediction, and verification were carried out. Finally, the reliable probability of the amplification coefficient distribution of the response index of the train and structure in different ranges was obtained based on the SVR nonlinear mapping model and Latin hypercube sampling method. The limit of the length of the mortar filling layer void was, thus, obtained. The results show that the SVR nonlinear mapping model developed in this paper has a high fitting accuracy of 0.993, and the computational efficiency is significantly improved by 99.86%. It can be used to calculate the dynamic response of the wheel-rail system. The length of the mortar filling layer void significantly affects the wheel-rail vertical force, wheel weight load reduction ratio, rail vertical displacement, and track plate vertical displacement. The dynamic response of the track structure has a more significant effect on the limit value of the length of the mortar filling layer void than the dynamic response of the vehicle, and the rail vertical displacement is the most obvious. At 250 km/h - 350 km/h train running speed, the limit values of grade I, II, and III of the lengths of the mortar filling layer void are 3.932 m, 4.337 m, and 4.766 m, respectively. The results can provide some reference for the long-term service performance reliability of the ballastless track-bridge system of HRS.