• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.622-629
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• 2022

The study aim was to derive a stem taper equation for Phyllostachys pubescens, a type of bamboo in South Korea, and to develop a stem volume table. To derive the stem taper equation, three stem taper models (Max & Burkhart, Kozak, and Lee) were used. Since bamboo stalks are hollow because of its woody characteristics, the outer and inner diameters of the tree were calculated, and connecting them enabled estimating the tree curves. The results of the three equations for estimating the outer and inner diameters led to selection of the Kozak model for determining the optimal stem taper because it had the highest fitness index and lowest error and bias. We used the Kozak model to estimate the diameter of Phyllostachys pubescens by stem height, which proved optimal, and drew the stem curve. After checking the residual degree in the stem taper equation, all residuals were distributed around "0", which proved the suitability of the equation. To calculate the stem volume of Phyllostachys pubescens, a rotating cube was created by rotating the stem curve with the outer diameter at 360°, and the volume was calculated by applying Smalian's method. The volume of Phyllostachys pubescens was calculated by deducting the inner diameter calculated volume from the outer diameter calculated volume. The volume of Phyllostachys pubescens was only 20~30% of the volume of Larix kaempferi, which is a general species. However, considering the current trees/ha of Phyllostachys pubescens and the amount of bamboo shoots generated every year, the individual tree volume was predicted to be small, but the volume/ha was not very different or perhaps more. The significance of this study is the stem taper equation and stem volume table for Phyllostachys pubescens developed for the first time in South Korea. The results are expected to be used as basic data for bamboo trading that is in increasing public and industrial demand and carbon absorption estimation.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.167-194
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• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.

• Spatial Information Research
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• v.22 no.1
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• pp.55-63
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• 2014

Near surface air temperature data which are one of the essential factors in hydrology, meteorology and climatology, have drawn a substantial amount of attention from various academic domains and societies. Meteorological observations, however, have high spatio-temporal constraints with the limits in the number and distribution over the earth surface. To overcome such limits, many studies have sought to estimate the near surface air temperature from satellite image data at a regional or continental scale with simple regression methods. Alternatively, we applied various Kriging methods such as ordinary Kriging, universal Kriging, Cokriging, Regression Kriging in search of an optimal estimation method based on near surface air temperature data observed from automatic weather stations (AWS) in South Korea throughout 2010 (365 days) and MODIS land surface temperature (LST) data (MOD11A1, 365 images). Due to high spatial heterogeneity, auxiliary data have been also analyzed such as land cover, DEM (digital elevation model) to consider factors that can affect near surface air temperature. Prior to the main estimation, we calculated root mean square error (RMSE) of temperature differences from the 365-days LST and AWS data by season and landcover. The results show that the coefficient of variation (CV) of RMSE by season is 0.86, but the equivalent value of CV by landcover is 0.00746. Seasonal differences between LST and AWS data were greater than that those by landcover. Seasonal RMSE was the lowest in winter (3.72). The results from a linear regression analysis for examining the relationship among AWS, LST, and auxiliary data show that the coefficient of determination was the highest in winter (0.818) but the lowest in summer (0.078), thereby indicating a significant level of seasonal variation. Based on these results, we utilized a variety of Kriging techniques to estimate the surface temperature. The results of cross-validation in each Kriging model show that the measure of model accuracy was 1.71, 1.71, 1.848, and 1.630 for universal Kriging, ordinary Kriging, cokriging, and regression Kriging, respectively. The estimates from regression Kriging thus proved to be the most accurate among the Kriging methods compared.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.235-243
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• 2023

Due to the revision of the River Act and the enactment of the Act on the Investigation, Planning, and Management of Water Resources, a regular bed change survey has become mandatory and a system is being prepared such that local governments can manage water resources in a planned manner. Since the topography of a bed cannot be measured directly, it is indirectly measured via contact-type depth measurements such as level survey or using an echo sounder, which features a low spatial resolution and does not allow continuous surveying owing to constraints in data acquisition. Therefore, a depth measurement method using remote sensing-LiDAR or hyperspectral imaging-has recently been developed, which allows a wider area survey than the contact-type method as it acquires hyperspectral images from a lightweight hyperspectral sensor mounted on a frequently operating drone and by applying the optimal bandwidth ratio search algorithm to estimate the depth. In the existing hyperspectral remote sensing technique, specific physical quantities are analyzed after matching the hyperspectral image acquired by the drone's path to the image of a surface unit. Previous studies focus primarily on the application of this technology to measure the bathymetry of sandy rivers, whereas bed materials are rarely evaluated. In this study, the existing hyperspectral image-based water depth estimation technique is applied to rivers with vegetation, whereas spatio-temporal hyperspectral imaging and cross-sectional hyperspectral imaging are performed for two cases in the same area before and after vegetation is removed. The result shows that the water depth estimation in the absence of vegetation is more accurate, and in the presence of vegetation, the water depth is estimated by recognizing the height of vegetation as the bottom. In addition, highly accurate water depth estimation is achieved not only in conventional cross-sectional hyperspectral imaging, but also in spatio-temporal hyperspectral imaging. As such, the possibility of monitoring bed fluctuations (water depth fluctuation) using spatio-temporal hyperspectral imaging is confirmed.

• Journal of Embryo Transfer
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• v.21 no.3
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• pp.207-216
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• 2006

Vaginal cytology was examined in 12 Shih-tzu bitches to establish the accurate basic data for estimate to the optimal mating time and ovulation time. The mean duration of proestrus and estrus were $9.09{\pm}0.83\;(mean{\pm}SD)$ days and $7.36{\pm}0.47$ days in pregnant bitches. The gestational length in the 12 pregnant bitches was $65.2{\pm}0.5$ days in pregnant bitches when Day 0 was timed from the first day of male acceptance. Characteristic features of vaginal cytology during the estrous cycle were the high proportion of large intermediate cell, superficial cell, anuclear cell and erythrocyte in proestrus, superficial cell, anuclear cell and erythrocyte in estrus, and parabasal cell, small and large intermediate cell and leukocyte in diestrus, respectively. Cornification index (CI) was the high proportion in proestrus and estrus, then it decreased in diestrus and anestrus. When Day 0 was timed from the day of the first male acceptance, the CI peak was Day 2 and maintained above 80% between Day -4 and Day 6 during 11 days, and above 90% between Day -1 and Day 5 during 7 days. In relationship between CI and reproductive hormones, CI showed peak at the first day after plasma estradiol-$17{\beta}$ concentration peak and plasma progesterone concentration was first increased above 4.0 ng/ml at Day 0 which was the first day after CI peak. In conclusion, ovulation in Shih-tzu bitches occurred at the first day after CI peak. Vaginal cytology is the simple and reliable method for estimating estrous cycle, optimal breeding time and ovulation time in Shih-tzu bitches.

• Journal of the Korean Wood Science and Technology
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• v.49 no.5
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• pp.399-415
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• 2021

This study was conducted to suggest the optimal periods for planting and felling Larix kaempferi tree by monitoring its cambial activity period. In addition, the heat summation to induce the cambial activity of Larix kaempferi was investigated. The study sites were at Mt. Worak and Mt. Midong. After selecting 5 trees at Mt. Worak and Mt. Midong, the cambium samples were collected using a mini trephor with 2 mm diameter from April 7 to October 6, 2017 at Mt. Worak, and from April 7 to September 29, 2017 at Mt. Midong. After the collected cambium samples were embedded in PEG2000, transverse thin sections with a thickness of 10 to 15 ㎛ were prepared using a microtome. One Larix kaempferi sample from each site, Mt. Worak and Mt. Midong, in which the accurate monitoring of cambial activity was impossible due to the formation of traumatic resin canal, was excluded from the study. The observation of the initiation date of cambial activity under a light microscopy revealed that 2 specimens from Mt. Worak and 3 from Mt. Midong showed the initiation on April 28. The remaining 2 specimens of Mt. Worak and 1 specimen of Mt. Midong were initiated on May 4, which was a week later than the others. The heat summation that induced the initiation of cambial activity was 196.4-271.8 at Mt. Worak and 204.7-277.3 at Mt. Midong, which was similar. The termination of cambial activity occurred between August 4 and 25 at Mt. Worak, and between August 4 and September 1 at Mt. Midong. Based on the above results, it was found that the optimal planting period for Larix kaempferi in Mt. Worak and Mt. Midong was before April, about a month before the cambium activity, and the felling period was from October when the cambial activity was completely terminated.

• The Journal of Engineering Geology
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• v.23 no.1
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• pp.57-65
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• 2013

We developed a computer program (CDFlow v. 1.0) to design countermeasures against debris flows in natural terrain. The program can predict the probability of landslides occurring in natural terrain and can estimate the zone of damage caused by a debris flow. It can also be used to design the location and size of countermeasures against the debris flow. The program is run using the ArcGIS Engine, which is one of the most well-known Geographic Information System (GIS) tools for developers. The quasi-dynamic wetness index and the infinite slope stability equation were applied to predict landslide probability as a type of slope safety factor. The calculated safety factor was compared with the required safety factor, and areas of high probable potential for landslides were then selected and represented on the digital map. The volume of debris flow was estimated using these areas of high probable potential for landslides and soil depth. The accumulated volume of debris flow can be calculated along the flow channel. To assess the accuracy of the program, it was applied to a real landslide site at Deoksan-ri, Inje-gun, Kangwon-Province, where four debris barriers have been installed in the watershed of the site. The results of soil tests and a field survey indicate that the program has great potential for estimating probable landslide areas and the trajectory of debris flows. Calculation of the capacity volume of existing debris barriers revealed that they had insufficient capacity to store the calculated amount of debris flow. Therefore, this program enables a rational estimation of the optimal location and size of debris barriers.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.8
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• pp.1172-1180
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• 2013

Two experiments were conducted to determine the standardized ileal digestible (SID) lysine (Lys) requirement and the ideal SID threonine (Thr) to Lys ratio for finishing barrows. In Exp. 1, 120 barrows with an average body weight of $72.8{\pm}3.6$ kg were allotted to one of six dietary treatments in a randomized complete block design conducted for 35 d. Each diet was fed to five pens of pigs containing four barrows. A normal crude protein (CP) diet providing 15.3% CP and 0.71% SID Lys and five low CP diets providing 12% CP with SID Lys concentrations of 0.51, 0.61, 0.71, 0.81 and 0.91% were formulated. Increasing the SID Lys content of the diet resulted in an increase in weight gain (linear effect p = 0.04 and quadratic effect p = 0.08) and an improvement in feed conversion ratio (FCR) (linear effect p = 0.02 and quadratic effect p = 0.02). For weight gain and FCR, the estimated SID Lys requirement of finishing barrows were 0.71 and 0.71% (linear broken-line analysis), 0.79 and 0.78% (quadratic analysis), respectively. Exp. 2 was a 26 d dose-response study using SID Thr to Lys ratios of 0.56, 0.61, 0.67, 0.72 and 0.77. A total of 138 barrows weighing $72.5{\pm}4.4$ kg were randomly allotted to receive one of the five diets. All diets were formulated to contain 0.61% SID Lys (10.5% CP), which is slightly lower than the pig's requirement. Weight gain was quadratically (p = 0.03) affected by SID Thr to Lys ratio while FCR was linearly improved (p = 0.02). The SID Thr to Lys ratios for maximal weight gain and minimal FCR and serum urea nitrogen (SUN) were 0.67, 0.71 and 0.64 using a linear broken-line model and 0.68, 0.78 and 0.70 using a quadratic model, respectively. Based on the estimates obtained from the broken-line and quadratic analysis, we concluded that the dietary SID Lys requirement for both maximum weight gain and minimum FCR was 0.75%, and an optimum SID Thr to Lys ratio was 0.68 to maximize weight gain, 0.75 to optimize FCR and 0.67 to minimize SUN for finishing barrows.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.679-686
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• 2020

In this thesis, an enhanced method for the feature extraction of vocal source signals and score combination using an MCE-Based weight estimation of the score of multiple feature vectors are proposed for the performance improvement of speaker recognition systems. The proposed feature vector is composed of perceptual linear predictive cepstral coefficients, skewness, and kurtosis extracted with lowpass filtered glottal flow signals to eliminate the flat spectrum region, which is a meaningless information section. The proposed feature was used to improve the conventional speaker recognition system utilizing the mel-frequency cepstral coefficients and the perceptual linear predictive cepstral coefficients extracted with the speech signals and Gaussian mixture models. In addition, to increase the reliability of the estimated scores, instead of estimating the weight using the probability distribution of the convectional score, the scores evaluated by the conventional vocal tract, and the proposed feature are fused by the MCE-Based score combination method to find the optimal speaker. The experimental results showed that the proposed feature vectors contained valid information to recognize the speaker. In addition, when speaker recognition is performed by combining the MCE-based multiple feature parameter scores, the recognition system outperformed the conventional one, particularly in low Gaussian mixture cases.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.23-31
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• 2010

The increasing demands on low-power, and low-complexity video encoder have been motivating extensive research activities on distributed video coding (DVC) in which the encoder compresses frames without utilizing inter-frame statistical correlation. In DVC encoder, contrary to the conventional video encoder, an error control code compresses the video frames by representing the frames in the form of syndrome bits. In the meantime, the DVC decoder generates side information which is modeled as a noisy version of the original video frames, and a decoder of the error-control code corrects the errors in the side information with the syndrome bits. The noisy observation, i.e., the side information can be understood as the output of a virtual channel corresponding to the orignal video frames, and the conditional probability of the virtual channel model is assumed to follow a Laplacian distribution. Thus, performance improvement of DVC systems depends on performances of the error-control code and the optimal reconstruction step in the DVC decoder. In turn, the performances of two constituent blocks are directly related to a better estimation of the parameter of the correlation channel. In this paper, we propose an algorithm to estimate the parameter of the correlation channel and also a low-complexity version of the proposed algorithm. In particular, the proposed algorithm minimizes squared-error of the Laplacian probability distribution and the empirical observations. Finally, we show that the conventional algorithm can be improved by adopting a confidential window. The proposed algorithm results in PSNR gain up to 1.8 dB and 1.1 dB on Mother and Foreman video sequences, respectively.