• Journal of Korean Society of Forest Science
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• v.110 no.1
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• pp.64-71
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• 2021

Recently, climate change has gradually accelerated the occurrence of landslides. Among the various effects caused by landslides,debris flow is recognized as particularly threatening because of its high speed and propagating distance. In this study, the impacts of various factors were analyzed using quantification theory(I) for the prediction of debris flow hazard soil volume in Seoraksan National Park, Korea. According to the range using the stepwise regression analysis, the order of impact factors was as follows: vertical slope (0.9676), cross slope (0.6876), altitude (0.2356), slope gradient (0.1590), and aspect (0.1364). The extent of the normalized score using the five-factor categories was 0 to 2.1864, with the median score being 1.0932. The prediction criteria for debris flow occurrence based on the normalized score were divided into four grades: class I, >1.6399; class II, 1.0932-1.6398; class III, 0.5466-1.0931; and class IV, <0.5465. Predictions of debris flow occurrence appeared to be relatively accurate (86.3%) for classes I and II. Therefore, the prediction criteria for debris flow will be useful for judging the dangerousness of slopes.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.59-69
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• 2021

The Moon Jae-in administration insisted on reforming the prosecution for the reform of power institutions, and also tried to control the power of the prosecution through the establishment of a high-ranking public officials criminal investigation office. Then, what is the direction of the legal prosecution reform? Above all, it is a logic to drastically reduce the power of the prosecution. How to shrink it? First, it is necessary to control or check the power of prosecution and investigation that the prosecution has. Second, the key to the reform of the prosecution is perhaps to separate personnel rights from power. In order to exclude external pressure from the prosecution's personnel rights, there must be no instruction or intervention from the attorney general. To do this, the prosecutor general must go through various personnel evaluations, such as multi-faceted evaluation. Third, the essence of the High-ranking Officials Criminal Investigations Act is to deal with crimes of prosecutors, judges, police, and members of the National Assembly. It is also the core of the institutional mechanism to cover the corruption of one's family members while holding all the right to investigate, prosecution, and warrant claims, and to check the omnipresent prosecutors who have abused their right to investigate for political purposes. Then, what is necessary for the success of the high-ranking officials criminal investigation office? Above all, We think political neutrality is very necessary. The Ministry of Airborne has a very high authority of the Director. This paper intends to examine the functions and roles of the prosecution and high-ranking officials criminal investigation offices to prevent corruption. We analyzed the contents of the prosecution and the public officials criminal investigation office, and examined the limitations and problems, and the measures to control corruption in public offices.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.391-404
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• 2021

This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.27 no.3
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• pp.283-288
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• 1982

This experiment was carried out to improve the cultural practices of seedlings and to investigate the proper planting density in aromatic tobacco, Sohang. Two different cultural practices of seedling were employed; Temporary transplanting (TT; Conventional practices) and non temporary transplanting (N.T.). Vinyl pot sizes were $3.5cm{\times}3.5cm, \;4cm{\times}4cm$ and $5cm{\times}5cm$ Plants per hole were 1, 3, 5, 7 and 9. There were little difference among the vinyl pot sizes in all characters except the survival ratio. But it may be little problem on cultural practices by 7 plants per hole in $5cm\times$5cm vinyl pot. There were not significant in price per kg, yield per 10a and value per 10a between two cultural practices of seedlings and among three pot sizes. Mildness and filling power were increased by increasing the plants per hole. Combustibility of 5-9 plants were better than those of 1-3 plants per hole. The growing of 6 seedlings per hole in $5cm\times$5cm vinyl pot by non temporary transplanting resulted the best cultural practices for an aromatic tobacco, Sohyang.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.32 no.1
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• pp.40-47
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• 1987

Under the different conditions of planting density and compound fertilizer level, some agronomic and chemical characteristics of burley tobacco were investigated from 1982 to 1984. Leaf area and dry leaf weight per plant, crop growth rate, relative growth rate and net assimilation rate for 40-60 days after transplanting were higher with increasing plant spacing and fertilizer, but leaf area index was lower with increasing plant spacing. At topping stage, the leaf size was increased with increasing plant spacing and amount of fertilizer applied and the stem diameter was increased by increasing plant spacing. Leaf area, leaf weight per plant and weight per unit leaf area of harvested leaf were higher when plant spacing and fertilizer increased. It was estimated that the optimum plant spacing was 105cm x 34cm and level of com-pound fertilizer (N-P$_2$ O$\sub$5/ -K$_2$O =10-10-20) was 263kg/l0a for high yield. There were trends toward increase the contents of total alkaloid and total nitrogen with increasing plant spacing and fertilizer application. There was significant positive correlation between plant spacing and total nitrogen, and between fertilizer application and total nitrogen. The plant spacing of 105cm x 35 to 40cm and 227.5kg/l0a of fertilizer level may be profitable for farm economy and the low nitrogenous leaf.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.8
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• pp.63-72
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• 2016

The main purpose of this study was to empirically validate whether a factor in reducing youth externalizing problem behaviors impact analysis and affection between father and youth self-esteem externalizing problem behavior through effective regulation. The survey was conducted by the researcher who visits the school to collect the sample data by random sampling method on 336 male students at D area. After delating the 38 insincere questionnaires, final 298 data were analyzed. Using SPSS 21.0, the simple correlational analysis was conducted to decide the relationship among the variables and in order to know the reciprocal model, hierarchical multiple regression analysis was implemented. The results showed the esteem and the affection his father on a statistically significant effect on youth externalizing problem behavior, father attachment had the effect of regulating the relationship between self-esteem and externalizing problem behavior. Through these results through the self-esteem Improvement Plan of the Father and the love of young people and to promote a proposal for reducing externalizing problem behavior.

• Industry Promotion Research
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• v.8 no.1
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• pp.119-134
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• 2023

An Analysis of the Choice of Wedding Time Based on the Gimundungap Theory. The purpose of this study is to research the utility and validity of wedding time selection based on the principles of Ungokgimun, a recent development of Gimundungap theory. Unlike the conventional way of choosing from common auspicious hours and days deemed available for important ceremonial occasions, Ungokgimun determines the propitious heavenly wedding time catered for a particular couple based on the birth table consisting of the four pillars of the bride- and groom-to-be. Using the Hong Guk-soo numbers which are drawn from the basic principles of oriental philosophy, it utilizes a deductive approach to wedding time choice, which is considered decisive and logical. Wedding time selection for a bride and a bridegroom is determined by auspicious combinations of matching and supporting HongGuk-soo numbers. Some relevant determining factors for the time choice are three number combination of samhap, two number combination of half-hap, latitudinal combination of yuk-hap, support and control relationships between related elements, two number punishment of hyung-sal, and three number punishment of samhyung-sal, etc. The specific auspicious palace of the spouse-to-be's luck is selected on the basis of supporting or brotherly combination of numbers which are manifested on the baseline earthly plate of the bride- and groom-to-be. This is followed by the selection of the ten-year luck, and year and month luck, and finally by the selection of auspicious day and hours. The validity of this study was verified through theoretical consideration of the Ungokgimun and practical analysis of a variety of marriage cases. It was found that the way of wedding time selection using Ungok Gimundungap was relatively more effective than other conventional methods.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• Korean Journal of Social Welfare
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• v.57 no.3
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• pp.305-335
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• 2005

This paper is a result from validation study for SPDA(A Screening Scale For Potential Drug-use Adolescents) created in 2003 and newly developed during 2004. SPDA aims to screen adolescents in their early stage of drug-use and to help practitioners make a preventive approach for the adolescents. 4307 junior and senior high school students were selected as primary research subjects by stratified and quota sampling methods. 305 adolescents on probation were also selected as a comparison group and asked to answer the same questionnaire. Reliability for SPDA recorded 0.914, which proved to be better than previous year's (0.898). Exploratory and confirmatory factor analyses to test construct validity proved that SPDA could be divided into 7 factors and that each factor structure of SPDA could be a proper measurement model with high level of fitness and factor loadings. Discriminant analysis to test predictive validity confirmed that SPDA could classify the adolescents excellently by the frequency of drug-use, with hit ratio of 86.6 percent(78.8% and 87.4% for junior and senior high school students respectively). For concurrent validity test, Hare Home Self-Esteem Scale, Hare School Self-Esteem, Zuckerman-Kuhlman Sensation-seeking Scale were employed to find correlation with SPDA and all the three scales had significant Pearson correlation coefficients with SPDA. Known-groups validity test indicated that SPDA had an adequate power to classify out adolescents on probation from those in schooling, with a hit ratio of 71.8 percent. Cut-off point to detect adolescents with high risk of substance use was 77, which indicated approximately T score, 55 (0.5 SD), satisfying sensitivity, specificity, and efficiency criteria.