Journal of the Korea Academia-Industrial cooperation Society
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v.10
no.8
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pp.2103-2109
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2009
Balanced Scorecard(BSC) is one of the ways to estimate the achievement results of enterprises which, beyond the simple financial index traditionally used for enterprise achievement result management system, aims to estimate and manage the key perspectives for the future and goal achievement of enterprises as financial perspectives, customer perspectives, internal business perspectives, learning and growth perspectives with a fully consistent and balanced measure, and moreover manage their relationships regarding cause and effect on its basis. Introduction of BSC can be a profound implication for management strategies not only in that its introduction itself has numerous direct effects but also in the way of understanding whether or not its sequential relations exist. Thus this study focused on if the introduction of BSC is effectual, and if there exist any time-lag sequential relations between the effects. The results of the this study indicate that the introduction of BSC has positive effects on the internal business perspectives, learning and growth perspectives, financial perspectives, with the last aspect lasting longer. After dividing perspectives of BSC into leading indicator and lagging indicator, the analysis on if there was some relationships between two indicators was done. As a result, the introduction makes internal process improve first, which has positive effects on financial performance next.
We conducted this study to compare physiological response according to growing conditions between superior and inferior family of Pinus densiflora. In 1981, open-pollinated (OP) progenies of P. densiflora were planted in Chuncheon (CC) and Naju (NJ). We selected KW2 as a superior family and KW23 as a inferior family based on volume index among 30 OP progenies. We calculated general combining ability of each 30 OP progenies in each sites, and compared family growth rank. We collected needles of selected families in CC and NJ, and analyzed chlorophyll content, nitrated reductase (NR) activity, nitrogen content, and superoxide dismutase (SOD) acitivity. In CC, chlorophyll content and nitrogen content were more in needles of KW2 than those of KW23. In NJ, KW2 showed higher NR activity than KW23, and according to site, families in CC showed higher NR activity than those in NJ. SOD activities of both families were higher in NJ, and KW23 showed higher activity than KW2 in both sites. Consequently, inconsistency of the growth performance of two families was caused by different genetic and physiological responses.
Jang, Si Hyeong;Cho, Jung Gun;Han, Jeom Hwa;Jeong, Jae Hoon;Lee, Seul Ki;Lee, Dong Yong;Lee, Kwang Sik
Journal of Bio-Environment Control
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v.31
no.4
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pp.384-392
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2022
The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R2: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.
Purpose - This paper's aim is to investigate whether or not gross profitability explains the cross-sectional variation of the stock returns in the Korean stock market. Gross profitability is an alternative profitability measure proposed by Novy-Marx in 2013 to predict cross-sectional variation of stock returns in the US. He shows that the gross profitability adds explanatory power to the Fama-French 3 factor model. Interestingly, gross profitability is negatively correlated with the book-to-market ratio. By confirming the gross profitability premium in the Korean stock market, we may provide some implications regarding the well-known value premium. In addition, our empirical results may provide opportunities for the fund distribution industry to promote brand new styles of funds. Research design, data, and methodology - For our empirical analysis, we collect monthly market prices of all the companies listed on the Korea Composite Stock Price Index (KOSPI) of the Korea Exchanges (KRX). Our sample period covers July1994 to December2014. The data from the company financial statementsare provided by the financial information company WISEfn. First, using Fama-Macbeth cross-sectional regression, we investigate the relation between gross profitability and stock return performance. For robustness in analyzing the performance of the gross profitability strategy, we consider value weighted portfolio returns as well as equally weighted portfolio returns. Next, using Fama-French 3 factor models, we examine whether or not the gross profitability strategy generates excess returns when firmsize and the book-to-market ratio are controlled. Finally, we analyze the effect of firm size and the book-to-market ratio on the gross profitability strategy. Results - First, through the Fama-MacBeth cross-sectional regression, we show that gross profitability has almost the same explanatory power as the book-to-market ratio in explaining the cross-sectional variation of the Korean stock market. Second, we find evidence that gross profitability is a statistically significant variable for explaining cross-sectional stock returns when the size and the value effect are controlled. Third, we show that gross profitability, which is positively correlated with stock returns and firm size, is negatively correlated with the book-to-market ratio. From the perspective of portfolio management, our results imply that since the gross profitability strategy is a distinctive growth strategy, value strategies can be improved by hedging with the gross profitability strategy. Conclusions - Our empirical results confirm the existence of a gross profitability premium in the Korean stock market. From the perspective of the fund distribution industry, the gross profitability portfolio is worthy of attention. Since the value strategy portfolio returns are negatively correlated with the gross profitability strategy portfolio returns, by mixing both portfolios, investors could be better off without additional risk. However, the profitable firms are dissimilar from the value firms (high book-to-market ratio firms); therefore, an alternative factor model including gross profitability may help us understand the economic implications of the well-known anomalies such as value premium, momentum, and low volatility. We reserve these topics for future research.
Performance of a rice breeding line, Milyang 95 was evaluated at four cultural methods, direct seeding on dry soil covered by making ridges (DS ridged), direct seeding on dry soil covered by rotortilling (DS rotary), direct seeding on flooded soil (FS), and machine transplanting (MT). Days from seeding to emergence in both DS ridged and DS rotary was 15 days. The number of seedlings at DS ridged and DS rotary was lower than that at FS. Heading was earliest at MT, latest at DS rotary and DS ridged, and that at FS was between them. Days from seeding to heading was 115 days at MT, 94-95 days at DS ridged and DS rotary, and 87 days at FS. Lodging index was similar among the cultural methods and lodging was not occurred in the field although fresh weight of tillers and breaking strength at MT were higher than those of direct seedings. Yield and most of yield components were similar among the cultural methods although the number of spikelets per panicle at MT was higher and 1,000 grain weight at FS was lower compared to other cultural methods. Grain appearance (rusty, chalky abortive rice), protein and amylose contents and alkali digestibility were observed.
Korean Journal of Agricultural and Forest Meteorology
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v.23
no.4
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pp.329-339
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2021
Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R2=0.74, RMSE=246 g/m2, RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m2 and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m2 and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m2) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.
The present study was undertaken to find relationships of plasma insulin-like growth factor (IGF)-I and IGF-II concentrations to litter size and lactation performance. Sixty pure-bred Landrace and Yorkshire pigs having similar farrowing weeks which had been selected from a large number of pregnant gilts and sows were divided into low- (<${\mu}$-0.5SD) and high-litter size (>${\mu}$+0.5 SD) lines under a 2 (breed)${\times}$2 (line) factorial arrange of treatments. After adjusting the litter size to nine piglets per sow at farrowing, total litter weight was measured at three weeks postpartum at weaning as an index of milk yield. Blood samples were obtained from the jugular vein at day (d)-90 pregnancy (Px) and at d-15 postpartum. The litter size or the number of piglets born during the present experiment and the average litter size during the entire parities up to the present one were greater in the high-line than in the low-line by 3.7 and 2.4 piglets, respectively (P<0.01); effect of the breed on litter size was not significant. Plasma IGF-II concentration at d-90 Px was greater in the high-line than in the low-line. Litter size and d-90 Px IGF-I concentration were negatively correlated in Landrace (r=-0.46; P<0.05) and tended to be negatively correlated in Yorkshire (r=-0.31; P=0.09), which resulted in a significant negative correlation between these two variables in total animals (r=-0.35; P<0.01). Litter weight at weaning was not different between the two breeds or lines. Relationships between the litter weight and IGF concentration were not consistent across the breed ${\times}$ physiological stage combinations. Results suggest that d-90 Px IGF concentrations may be indicative of the litter size at impending farrowing.
Journal of Korea Spatial Information System Society
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v.6
no.1
s.11
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pp.73-85
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2004
Recently, as the growth of the wireless Internet, PDA and HPC, the focus of research and development related with GIS(Geographic Information System) has been changed to the Real-Time Mobile GIS to service LBS. To offer LBS efficiently, there must be the Real-Time GIS platform that can deal with dynamic status of moving objects and a location index which can deal with the characteristics of location data. Location data can use the same data type(e.g., point) of GIS, but the management of location data is very different. Therefore, in this paper, we studied the Real-Time Mobile GIS using the HBR-tree to manage mass of location data efficiently. The Real-Time Mobile GIS which is developed in this paper consists of the HBR-tree and the Real-Time GIS Platform HBR-tree. we proposed in this paper, is a combined index type of the R-tree and the spatial hash Although location data are updated frequently, update operations are done within the same hash table in the HBR-tree, so it costs less than other tree-based indexes Since the HBR-tree uses the same search mechanism of the R-tree, it is possible to search location data quickly. The Real-Time GIS platform consists of a Real-Time GIS engine that is extended from a main memory database system. a middleware which can transfer spatial, aspatial data to clients and receive location data from clients, and a mobile client which operates on the mobile devices. Especially, this paper described the performance evaluation conducted with practical tests if the HBR-tree and the Real-Time GIS engine respectively.
All diets were based on feeds of fattening period pigs(LY x D, ca. 90 kg) with six treatments, which were the control, containing 5% beef tallow(C), 3% beef tallows and 2% perilla seeds oil(T1), 250 ppm vit. E(${\alpha}$-tocopheryl acetate) in T1(T2), 3% beef tallow and 2% squid viscera oil(T3), 250 ppm vit. E in T3(T4), and 3% beef tallow and 2% CLA(T5), respectively. Produced porks and their carcass characteristics were as follows. The daily gain of pigs was higher in T2 and 73 than any other treatments(p<0.05). Its T2 and T3 was 3.71 and 3.80 respectively, however, there was no significance in feed intake. The highest back fat thickness was shown in control group on market weight, while there was no significant difference on their initial weight. Loin-eye muscle area did not show any significant difference on initial weight and on market weight, however, its T5 was about twice as large as T2's. Content of triglyceride in blood was high in control group as compared to others; especially, the values for T3, T4 and T5 were significantly low(p <0.05). There was no significant difference in total cholesterol contents, and the ratio of HDL cholesterol/total cholesterol was higher in vit. E treated samples than untreated sample. Atherogenic index was high in sample with T3 and low in sample with T2. The perilla seed oil, squid fish oil, and vit. E decreased atherogenic index. Dressing percentage, back fat thickness, and grade did not show any significant difference(p >0.05); however, T2, C and T3, T1 and T5 showed 4.67, 4.29, 4.00 respectively, in grades.
Korean Journal of Agricultural and Forest Meteorology
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v.17
no.4
/
pp.384-398
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2015
In this paper, the high-resolution Weather Research and Forecasting/Noah-MultiParameterization (WRF/Noah-MP) modeling system is configured for the Cheongmicheon Farmland site in Korea (CFK), and its performance in land and atmospheric simulation is evaluated using the observed data at CFK during the 2014 special observation period (21 August-10 September). In order to explore the usefulness of turning on Noah-MP dynamic vegetation in midterm simulations of surface and atmospheric variables, two numerical experiments are conducted without dynamic vegetation and with dynamic vegetation (referred to as CTL and DVG experiments, respectively). The main results are as following. 1) CTL showed a tendency of overestimating daytime net shortwave radiation, thereby surface heat fluxes and Bowen ratio. The CTL experiment showed reasonable magnitudes and timing of air temperature at 2 m and 10 m; especially the small error in simulating minimum air temperature showed high potential for predicting frost and leaf wetness duration. The CTL experiment overestimated 10-m wind and precipitation, but the beginning and ending time of precipitation were well captured. 2) When the dynamic vegetation was turned on, the WRF/Noah-MP system showed more realistic values of leaf area index (LAI), net shortwave radiation, surface heat fluxes, Bowen ratio, air temperature, wind and precipitation. The DVG experiment, where LAI is a prognostic variable, produced larger LAI than CTL, and the larger LAI showed better agreement with the observed. The simulated Bowen ratio got closer to the observed ratio, indicating reasonable surface energy partition. The DVG experiment showed patterns similar to CTL, with differences for maximum air temperature. Both experiments showed faster rising of 10-m air temperature during the morning growth hours, presumably due to the rapid growth of daytime mixed layers in the Yonsei University (YSU) boundary layer scheme. The DVG experiment decreased errors in simulating 10-m wind and precipitation. 3) As horizontal resolution increases, the models did not show practical improvement in simulation performance for surface fluxes, air temperature, wind and precipitation, and required three-dimensional observation for more agricultural land spots as well as consistency in model topography and land cover data.
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