• Korean Journal of Ecology and Environment
• /
• v.43 no.2
• /
• pp.319-337
• /
• 2010

Major objective of this study was to determine interannual and seasonal water quality along with characteristics of longitudinal gradients along the reservoir axis of the riverine zone (Rz)-to-lacustrine zone (Lz). Water quality dataset of five years during 2003~2007 used here were obtained from Ministry of Environment, Korea and ten physical, chemical and biological parameters were analyzed in the study. Similarity analysis, based on moropho-hydrological variables of reservoir surface area, watershed area, total inflow, and outflow, showed that the reservoirs were categorized as three groups of large-dam reservoirs (Chungju Reservoir, Daecheong Reservoir and Soyang Reservoir), mid-size reservoirs (Andong Reservoir, Yongdam Reservoir, Juam Reservoir and Hapcheon Reservoir), and small-size reservoirs (Hoengseong Reservoir and Buan Reservoir). According to the data comparison of high-flow year (2003) vs. lowflow year (2005), dissolved oxygen (DO), pH, biological oxygen demand (BOD), suspended solids (SS), total nitrogen (TN), total phosphorus (TP), chlorophyll-a (CHL) and electrical conductivity (EC) declined along the longitudinal axis of Rz to Lz and water transparency, based on Secchi depth (SD), increased along the axis. These results indicate that transparency was a function of Values of pH, DO, SS, SD, and EC at each site were greater in the low-flow year (2005) than the high-flow year (2003), whereas values of BOD, COD, TN, TP and CHL were greater in the high-flow year (2003). When values of TN, TP, CHL and SD in nine reservoirs were compared in the three zones of Rz, Tz, and Lz, values of TN, TP and CHL declined along longitudinal gradients and SD showed the opposite due to the sedimentation processes from the water column. Values of TN were not statistically correlated with TP values. The empirical linear models of TP-CHL and CHL-SD showed significant (p<0.05, $R^2$>0.04). In the mid-size reservoirs, the variation of CHL was explained ($R^2$=0.2401, p<0.0001, n=239) by the variation of TP. The affinities in the correlation analysis of mid-size reservoirs were greater in the CHL-SD model than any other empirical models, and the CHL-SD model had an inverse relations. In the meantime, water quality variations was evidently greater in Daecheong Reservoir than two reservoirs of Andong Reservoir and Hoengseong Reservoir as a result of large differences of water quality by long distance among Rz, Tz and Lz.

• Journal of the Society of Cosmetic Scientists of Korea
• /
• v.33 no.2
• /
• pp.111-115
• /
• 2007

It is inevitable to use germicidal agents like parabens, imidazolidinyl urea, phenoxyethanol and chlorphenesin to preserve the cosmetics. Although effective in reducing microblological contamination, chemical preservatives are irritative, allergenic and even toxic to human skin. So it is needed to decrease or eliminate usage of preservatives in cosmetic products Glycerin, butylene glycol (BG), prorylene glycol (PG), and dipropylene glycol (DPG) are widely used in cosmetics as skin conditioning agent or solvents. At high concentrations, they have antimicrobial activities, but deteriorate product quality like sensory feeling or safety. The purpose of study is to evaluate the effects of polyols on antimicrobial and preservative efficacy and confirm whether using adjusted polyols can decrease the contents of preservatives without deterioration of the quality of cosmetics. Effects of common polyols on antimicrobial activities of general preservatives were measured. BG and PG significantly (p < 0.05) increased activities of preservatives, but glycerin influenced little. It was inferred from the regression analysis of the results with S. aureus that adding 1% of PG increased activities of preservatives up to $2.1{\sim}8.4 %$ and BG improved activities of preservatives up to $1.8{\sim}8.4 %$. The challenge test results for oil in water lotions and creams showed that BG and PG improved the efficacy of preservative systems up to 40 % at a range of $5.5{\sim}9.9 %$, but glycerin had little effect on it. The measured rates of improvement were analogous to the inferences from regression analysis. It can be concluded that is possible to reduce total chemical preservatives up to 40 %, consequently improve the safety and sensory quality of cosmetics with the precision control of polyols. Added to that, using this paradigm, low preservative contents, praraben-free system, and even preservative-free systems can be expected in the near future.

• Journal of Intelligence and Information Systems
• /
• v.16 no.4
• /
• pp.1-19
• /
• 2010

In offline environment, unlike traditional advertising model through TV, newspaper, and radio, online advertising model draws instantaneous responses from potential consumers and it is convenient to assess. This kind of characteristics of Internet advertising model has driven the growth of advertising model among various Internet business models. There are, conventionally classified, CPM (Cost Per Mile), CPC (Cost Per Click), and CPS (Cost Per Sales) models as Internet advertising expenditure model. These can be examined in manners regarding risks that stakeholders should stand and degree of responsibility. CPM model that is based on number of advertisement exposure is mechanically exposed to users but not actually recognized by users resulting in risk of wasted expenditure by advertisers without any advertising effect. While on aspect of media, CPS model that is based on conversion action is the most risky model because of the conversion action such as product purchase is determined by capability of advertisers not that of media. In this regard, while there are issue of CPM and CPS models disadvantageously affecting only one side of Internet advertising business model value network, CPC model has been evaluated as reasonable both to advertisers and media, and occupied the largest segment of Internet advertising market. However, CPC model also can cause fraudulent behavior such as click fraud because of the competition or dishonest amount of advertising expenditure. On the user aspect, unintentionally accessed advertisements can lead to more inappropriate expenditure from advertisers. In this paper, we suggest "CPCD"(Cost Per Coupon Download) model. This goes beyond simple clicking of advertisements and advertising expenditure is exerted when users download a coupon from advertisers, which is a concept in between CPC and CPS models. To achieve the purpose, we describe the scenario of advertiser perspective, processes, participants and their benefits of CPCD model. Especially, we suggest the new value in online coupon; "possibility of storage" and "complement for delivery to the target group". We also analyze the working condition for advertiser by a comparison of CPC and CPCD models through advertising expenditure simulation. The result of simulation implies that the CPCD model suits more properly to advertisers with medium-low price products rather than that of high priced goods. This denotes that since most of advertisers in CPC model are dealing with medium-low priced products, the result is very interesting. At last, we contemplate applicability of CPCD model in ubiquitous environment.

• Progress in Medical Physics
• /
• v.24 no.4
• /
• pp.237-242
• /
• 2013

In the intracranial regions, an accurate delineation of the target volume has been difficult with only the CT data due to poor soft tissue contrast of CT images. Therefore, the magnetic resonance images (MRI) for the delineation of the target volumes were widely used. To calculate dose distributions with MRI-based RTP, the electron density (ED) mapping concept from the diagnostic CT images and the pseudo CT concept from the MRI were introduced. In this study, the look up table (LUT) from the fifteen patients' diagnostic brain MRI images was created to verify the feasibility of MRI-based RTP. The dose distributions from the MRI-based calculations were compared to the original CT-based calculation. One MRI set has ED information from LUT (lMRI). Another set was generated with voxel values assigned with a homogeneous density of water (wMRI). A simple plan with a single anterior 6MV one portal was applied to the CT, lMRI, and wMRI. Depending on the patient's target geometry for the 3D conformal plan, 6MV photon beams and from two to five gantry portals were used. The differences of the dose distribution and DVH between the lMRI based and CT-based plan were smaller than the wMRI-based plan. The dose difference of wMRI vs. lMRI was measured as 91 cGy vs. 57 cGy at maximum dose, 74 cGt vs. 42 cGy at mean dose, and 94 cGy vs. 53 at minimum dose. The differences of maximum dose, minimum dose, and mean dose of the wMRI-based plan were lower than the lMRI-based plan, because the air cavity was not calculated in the wMRI-based plan. These results prove the feasibility of the lMRI-based planning for brain tumor radiation therapy.

• The Korean Journal of Air & Space Law and Policy
• /
• v.29 no.1
• /
• pp.33-66
• /
• 2014

While the numbers of overseas travelers has been increased rapidly each year, the numbers of passengers in the aircraft also has continued to be increased gradually. In the mist of these increasing numbers, such accidents as threatening an aircraft safety like riot, aircraft hijacking and terrorism have happened constantly. In these circumstances, South Korean government has prescribed "Aviation on Security Act" in accordance with the Convention on International Civil Aviation and other international agreements. This act aims to prevent illegal activities and illegal items on the aircraft to ensure the safety and security of civil aviation. However, this act is not sufficiently regulating all the illegal crimes and illegal items on the flight. For the worse, there is a lack of effective supervisory capacity. Likewise, the inherent problems of the current laws relating to the prevention of the illegal items on the aircraft are appearing on the surface continually. Above all, illegal items on the aircraft are directly connected to the issue of aviation safety and security as well as a safe utilization of the flight service. Thus, when there occurs a serious accident on board, it surely would be led to a huge economic loss not mentioning the loss of lives following the accident. Therefore safety of the flight passengers cannot be guaranteed without ensuring the safety of aircraft facilities and good supervisory mechanism of illegal items on the aircraft. Accordingly, establishing a safe operation order tends to influence economy and tourism of a country in no small measure. Therefore, it is an urgent issue to settle down a reasonable and adequate supervisory regulations regarding the prevention of the illegal items on the aircraft. Consequently, in this article, I studied on a reasonal and effective mechanism to control the prevention of the illegal items and illegal acts on the aircraft in order to ensure a safety and security of civil aircraft.

• Journal of radiological science and technology
• /
• v.39 no.1
• /
• pp.1-11
• /
• 2016

The purpose of this study was to provide resources for medical exposure reduction through evaluation of organ dose and image resolution for lumbar spine around according to the size of the collimator in DR system. The size of the collimator were varied from $8^{\prime\prime}{\times}17^{\prime\prime}$ to $14^{\prime\prime}{\times}17^{\prime\prime}$ by 1" in AP and lateral projection for the lumbar spine radiography with RANDO phantom. The organ dose measured for liver, stomach, pancreas, kidney and gonad by the glass dosimeter. The image resolution was analyzed using the Image J program. The organ dose of around lumbar spine were reduced as the size of the collimator is decreased in AP projection. There were no significant changes decreasing rate whenever the size of the collimator were reduced 1" in the gonad. The organ dose showed higher on liver and kidney near the surface in lateral projection. There were decreasing rate of less than 5% in liver and kidney, but decreasing rate was 24.34% in the gonad whenever the size of the collimator were reduced 1". Organ dose difference for internal and external of collimator measured $549.8{\mu}Gy$ in the liver and $264.6{\mu}Gy$ in the stomach. There were no significant changes organ dose difference that measured $1,135.1{\mu}Gy$ in the gonad. Image Quality made no difference because SNR and PSNR were over than 30 dB when the collimator size is less than $9^{\prime\prime}{\times}17^{\prime\prime}$ on AP projection and $10^{\prime\prime}{\times}17^{\prime\prime}$ on lateral projection. Therefore, we are considered that the recommendations criterion for control of collimator were suggested in order to reduce unnecessary X-ray exposure and to obtain good image quality because lumbar spine radiography contains a lot of peripheral organs rather than other area radiography.

• Current Research on Agriculture and Life Sciences
• /
• v.32 no.4
• /
• pp.225-230
• /
• 2014

This study investigates the effect of organic certification of apples on consumer preference in China as a way to support the expanded export of Korean apples to China. A choice experiment was designed to analyze the apple consumption in China. A total of 298 Chinese consumers answered the survey, and multinomial logit models were used to analyze the results. Organic certification was identified as an important determinant of consumer preference for apples in China, affecting both the evaluation and choice of country of origin. The results also indicated that Korean organic certification significantly increased the probability of Chinese consumers choosing Korean apples. Thus, organic certification by the Korean government should be strengthened to promote apple exports to China, plus the results of this study may provide useful information to promote agricultural product exports and improve the organic certification system.

• Journal of IKEEE
• /
• v.25 no.3
• /
• pp.493-500
• /
• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.14 no.1
• /
• pp.139-149
• /
• 2019

The purpose of this study is to contribute to the minimization of the social cost due to the insolvency by improving the success rate of the startups by providing useful information to the founders and the start-up support institutions through analysis of non-financial information affecting the failure of the startups. This study is aimed at entrepreneurs. The entrepreneurs that are defined by the credit guarantee institutions generally refer to entrepreneurs within 5 years of establishment. The data used in the study are sampled from the companies that were supported by the start-up guarantee from January 2014 to December 2013 as the end of December 2017. The total number of sampled firms is 2,826, 2,267 companies (80.2%), and 559 non-performing companies (19.8%). The non-financial information of the entrepreneur was divided into the entrepreneur characteristics information, the entrepreneur characteristics information, the entrepreneur asset information and the entrepreneur 's credit information, and cross-tabulations and logistic regression analysis were conducted. As a result of cross-tabulations, univariate analysis showed that personal credit rating, presence in the industry, presence of residential housing, presence of employees, and presence of financial statements were selected as significant variables. As a result of the logistic regression analysis, three variables such as personal credit rating, occupation in the industry, and presence of residential house were found to be important factors affecting the failure of founding companies. This result shows the importance of entrepreneur 's personal credibility and experience and entrepreneur' s assets in business management. The start-up support institutions should reflect these results in the entrepreneur 's credit evaluation system, and the entrepreneurs need training on the importance of the personal credit and the management plan in the entrepreneurial education. The results of this analysis will contribute to the minimization of the incapacity of startups by providing useful non-financial information to founders and start-up support organizations.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.127-137
• /
• 2019

Recidivism prediction has been a subject of constant research by experts since the early 1970s. But it has become more important as committed crimes by recidivist steadily increase. Especially, in the 1990s, after the US and Canada adopted the 'Recidivism Risk Assessment Report' as a decisive criterion during trial and parole screening, research on recidivism prediction became more active. And in the same period, empirical studies on 'Recidivism Factors' were started even at Korea. Even though most recidivism prediction studies have so far focused on factors of recidivism or the accuracy of recidivism prediction, it is important to minimize the prediction misclassification cost, because recidivism prediction has an asymmetric error cost structure. In general, the cost of misrecognizing people who do not cause recidivism to cause recidivism is lower than the cost of incorrectly classifying people who would cause recidivism. Because the former increases only the additional monitoring costs, while the latter increases the amount of social, and economic costs. Therefore, in this paper, we propose an XGBoost(eXtream Gradient Boosting; XGB) based recidivism prediction model considering asymmetric error cost. In the first step of the model, XGB, being recognized as high performance ensemble method in the field of data mining, was applied. And the results of XGB were compared with various prediction models such as LOGIT(logistic regression analysis), DT(decision trees), ANN(artificial neural networks), and SVM(support vector machines). In the next step, the threshold is optimized to minimize the total misclassification cost, which is the weighted average of FNE(False Negative Error) and FPE(False Positive Error). To verify the usefulness of the model, the model was applied to a real recidivism prediction dataset. As a result, it was confirmed that the XGB model not only showed better prediction accuracy than other prediction models but also reduced the cost of misclassification most effectively.