• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.2
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• pp.95-107
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• 2020

The purpose of this study is to provide the basic data by analyzing and analysing the Growth Conditions of old Trees in Yangdong village. This study investigated about the conducted on tree information, soil information, and tree health. The result are as follows. The trees information in Yangdong Village consists of Juniperus chinensis, Salix chaenomeloides, Salix pseudolasiogyne, Celtis sinensis, Zelkova serrata, Gleditsia japonica, and Gleditsia sinensis trees, The range of height was 4.0~17.0m, and the diameter was 0.51~1.34m, Juniperus chinensis trees of No.17 was most large. In the results of soil analysis, there showed that acidity was pH4.1~6.3, hardness of 5~48mm, organic matter content of 21.2~29.1g/kg, electrical conductivity(EC) of 0.34~1.76dS/m, available P₂O₅ of 79.8~451.6mg/kg, exchangeable K of 0.22~1.71cmol+/kg, exchangeable Ca of 4.98~7.44cmol+/kg, exchangeable Mg of 0.67~2.19cmol+/kg, exchangeable Na of 0.19~1.04cmol+/kg and cation exchange capacity(C.E.C) of 7.23~13.02cmol+/kg. As a result, the highest number of tree health levels is 8 of 11trees of Celtis sinensis, 2 of 7trees of Zelkova serrata, and 3 of Gleditsia sinensis, and 13 of 30 trees of health levels, The Older trees with high infection, spoil and hollowed part were the remaining trees except for the healthy part. Relatively, more than half of the number of targets is infected, decay, and the hollowed site, and it is necessary to perform surgery on the damaged area. In addition, preservation and protection measures should be implemented by supplying root nutrients for trees, controlling nutrients in the body to prevent secondary and tertiary damages that cause the infection site to metastasize to the health site, In order to continually monitor the trees, measures to improve the location environment and management of the trees should be sought.

• Journal of Elementary Mathematics Education in Korea
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• v.13 no.2
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• pp.163-192
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• 2009

Currently, our country operates gifted education only as a special curriculum, which results in many problems, e.g., there are few beneficiaries of gifted education, considerable time and effort are required to gifted students, and gifted students' educational needs are ignored during the operation of regular curriculum. In order to solve these problems, the present study formulates the following research questions, finding it advisable to conduct gifted education in elementary regular classrooms within the scope of the regular curriculum. A. To devise a teaching plan for the gifted students on mathematics in the elementary school regular classroom. B. To develop a learning program for the gifted students in the elementary school regular classroom. C. To apply an in-depth learning program to gifted students in mathematics and analyze the effectiveness of the program. In order to answer these questions, a teaching plan was provided for the gifted students in mathematics using a differentiating instruction type. This type was developed by researching literature reviews. Primarily, those on characteristics of gifted students in mathematics and teaching-learning models for gifted education. In order to instruct the gifted students on mathematics in the regular classrooms, an in-depth learning program was developed. The gifted students were selected through teachers' recommendation and an advanced placement test. Furthermore, the effectiveness of the gifted education in mathematics and the possibility of the differentiating teaching type in the regular classrooms were determined. The analysis was applied through an in-depth learning program of selected gifted students in mathematics. To this end, an in-depth learning program developed in the present study was applied to 6 gifted students in mathematics in one first grade class of D Elementary School located in Nowon-gu, Seoul through a 10-period instruction. Thereafter, learning outputs, math diaries, teacher's checklist, interviews, video tape recordings the instruction were collected and analyzed. Based on instruction research and data analysis stated above, the following results were obtained. First, it was possible to implement the gifted education in mathematics using a differentiating instruction type in the regular classrooms, without incurring any significant difficulty to the teachers, the gifted students, and the non-gifted students. Specifically, this instruction was effective for the gifted students in mathematics. Since the gifted students have self-directed learning capability, the teacher can teach lessons to the gifted students individually or in a group, while teaching lessons to the non-gifted students. The teacher can take time to check the learning state of the gifted students and advise them, while the non-gifted students are solving their problems. Second, an in-depth learning program connected with the regular curriculum, was developed for the gifted students, and greatly effective to their development of mathematical thinking skills and creativity. The in-depth learning program held the interest of the gifted students and stimulated their mathematical thinking. It led to the creative learning results, and positively changed their attitude toward mathematics. Third, the gifted students with the most favorable results who took both teacher's recommendation and advanced placement test were more self-directed capable and task committed. They also showed favorable results of the in-depth learning program. Based on the foregoing study results, the conclusions are as follows: First, gifted education using a differentiating instruction type can be conducted for gifted students on mathematics in the elementary regular classrooms. This type of instruction conforms to the characteristics of the gifted students in mathematics and is greatly effective. Since the gifted students in mathematics have self-directed learning capabilities and task-commitment, their mathematical thinking skills and creativity were enhanced during individual exploration and learning through an in-depth learning program in a differentiating instruction. Second, when a differentiating instruction type is implemented, beneficiaries of gifted education will be enhanced. Gifted students and their parents' satisfaction with what their children are learning at school will increase. Teachers will have a better understanding of gifted education. Third, an in-depth learning program for gifted students on mathematics in the regular classrooms, should conform with an instructing and learning model for gifted education. This program should include various and creative contents by deepening the regular curriculum. Fourth, if an in-depth learning program is applied to the gifted students on mathematics in the regular classrooms, it can enhance their gifted abilities, change their attitude toward mathematics positively, and increase their creativity.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.62 no.4
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• pp.317-324
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• 2017

The purpose of this study was to provide basic data on the genetic and environmental effects of stickiness in glutinous rice varieties. In our study, we analyzed the genotype-by-environment ($G{\times}E$) interactions of the stickiness using six glutinous rice varieties under six environmental conditions. AMMI (Additive Main Effects and Multiplicative Interaction) analysis results showed that genotype (variety, G), environment (cultivation region, E) and $G{\times}E$ interaction were highly significant (P < 0.001). Among all the variations of stickiness for glutinous rice varieties, the environmental effect was 24.5%, the genetic effect was 37.1%, and the $G{\times}E$ interaction effect was 28.9%. From the AMMI analysis, the IPCA1 scores of Aranghangchal (G6, IPCA1: 3.85) and Hwaseonchal (G4, IPCA1: -5.24) was lower than other varieties. On the other hand, the Sangjuchal (G1, IPCA1: -61.23) and Boseogchal (G2, IPCA1: 41.21) were highly affected by environmental effects. In this study, there were large differences in stickiness according to region of cultivation. In the future, it is considered that a precise study should be carried out on the environmental factors that may increase the stickiness of glutinous rice varieties.

• Journal of Animal Science and Technology
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• v.50 no.3
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• pp.391-400
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• 2008

Odor management is significantly concerned with sustainable livestock production because odor nuisance is a primary cause for complaint to neighbors. This study was conducted to measure the concentration of odorous compounds, odor intensity, and odor offensiveness at unit process in animal waste treatment facility combined composting and methane fermentation process by an instrumental analysis and direct olfactory method. Ammonia, sulfur-containing compounds, and volatile fatty acid were analyzed at each process units and boundary area in summer and winter, respectively. Higher concentration of odorants occurred in the summer than in the winter due to high ambient temperature. The maximum concentration of odorants was detected in composting pile when mixed manure was being turned followed by inlet, curing, outlet, and screen & packing process. Highest concentration of detected odorous compounds was ammonia ranging from 3.4 to 224.7 ppm. Among the sulfur-containing compounds measured, hydrogen sulfide was a maximum level of 2.3 ppm and most of them exceeded reported odor detection thresholds. Acetic acid was the largest proportion of VFA generated, reaching a maximum of 51 to 89%, followed by propionic and butyric acid at 1.9 to 35% and 1.8 to 15%, respectively. Malodor assessment by a human panel appeared a similar tendency in instrumental analysis data. Odor quotient for predicting major odor-causing compounds was calculated by dividing concentrations measured in process units by odor detection thresholds. In the composting process, hydrogen sulfide, ammonia, dimethyl sulfide, and methyl mercaptan were deeply associated with odor-causing compounds, while the major malodor compounds in the inlet process were methyl mercaptan, hydrogen sulfide, and butyric acid.

• Journal of Nutrition and Health
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• v.50 no.1
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• pp.74-84
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• 2017

Purpose: In this study, factors of metabolic syndrome and nutritional status were examined according to gender and occupations using the 2013 Korea National Health and Nutrition Examination Survey (KNHANES). Methods: This study was conducted on 1,750 workers (male : 892, female : 858) aged between 30 and 64, who participated in a health survey, health examination, and nutrition survey using the 6th 2013 KNHANES. Occupations were classified into white collar and blue collar workers, and nutrient intake was analyzed using a food frequency questionnaire. Analysis of complex sample design data through SPSS 19.0 was used for analysis. Results: The prevalence rate of metabolic syndrome among blue collar (35.1%) was higher than that among white collar workers (26.8%) in male subjects (p < 0.05) as well as in blue collar (24.8%) compared to white collar workers (8.9%) in female subjects (p < 0.001). Intake frequency per week, considering one portion by food category, showed significant differences in cooked rice (p < 0.05) and bakeries and confectioneries (p < 0.05) in make workers as well as stew and casserole (p < 0.01) and fruits (p < 0.05) in female workers. With regard to nutrient intake by occupation and gender, white collar workers consumed a greater amount of nutrients (not including total energy intake) compared to blue collar workers in both male and female workers. With regard to nutrient adequacy ratio (NAR) and mean adequacy ratio (MAR) according to gender and occupation, white collar workers showed higher numbers than blue collar workers in both male and female subjects. Conclusions: This study examined the prevalence rates of metabolic syndrome and nutrient intake according to gender and occupation. In both male and female subjects, blue collar workers showed higher prevalence rates compared to white collar workers, and their diet quality was worse than white collar workers' diet quality. Considering this result, customized nutrition education according to gender and occupation should be provided to workers to prevent diseases.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.35 no.6
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• pp.639-643
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• 2002

Water quality, bacterial phase and fish growth rate were analyzed in the process of artificial seed production of flounder (Paralichtys oliraceus) larvae to investigate the water quality in rearing tank using Ultra Filtration System (UES). Sand Filtration System (SFS) and Ultra Filtration System (Ins) were set up in the experimental group. For the analysis of water quality, pH, salinity, DO, SS, COD, $NH_{4}^{+},\;NO_{2}^{-},\;NO^-,\;DIN$ (dissolved inorganic nitrogen) and DU (dissolved inorganic phosphate) were measured. There was no data difference between SFS group and UES group in most analysis items, but the UEs group showed low salinity and low 55 values, such that salinity was $33.5\%_{\circ}$ in SES group and $30.2\%_{\circ}$ in WS group and 55 was 15.5 mL/L in SES group and 7.0 mL/L for UPS group. For changes in bacterial phase and TBC (Total Bacterial Counts), in SES group, 6$\times$10^{5}CFU/mL in seawater decreased to the ratio of about 116, and TBC, Genus Vibrio and bacteria in the Genus Acinetobacter and Genus Micrococcus sharply increased after nine days, while stable bacterial phase was maintained low in UES group during the experiment except for Genus Ajteromonas. In the growth of the larvae, fish length was 17.0 mm (SGR 14.0) in the SES group and 18.8 mm (SGR 14.3) in the UFS group. It is concluded that when water is supplied for artificial seed production with WS, stabilization of water quality condition and inhibition of bacterial multiplication are possible. When production environment becomes stable, stable growth of fish becomes possible by reduction of environmental stress.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.53-77
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• 2015

Korea has witnessed an increasing number of domestic patent applications, but a majority of them are not utilized to their maximum potential but end up becoming obsolete. According to the 2012 National Congress' Inspection of Administration, about 73% of patents possessed by universities and public-funded research institutions failed to lead to creating social values, but remain latent. One of the main problem of this issue is that patent creators such as individual researcher, university, or research institution lack abilities to commercialize their patents into viable businesses with those enterprises that are in need of them. Also, for enterprises side, it is hard to find the appropriate patents by searching keywords on all such occasions. This system proposes a patent recommendation system that can identify and recommend intellectual rights appropriate to users' interested fields among a rapidly accumulating number of patent assets in a more easy and efficient manner. The proposed system extracts core contents and technology sectors from the existing pool of patents, and combines it with secondary social knowledge, which derives from tags information created by users, in order to find the best patents recommended for users. That is to say, in an early stage where there is no accumulated tag information, the recommendation is done by utilizing content characteristics, which are identified through an analysis of key words contained in such parameters as 'Title of Invention' and 'Claim' among the various patent attributes. In order to do this, the suggested system extracts only nouns from patents and assigns a weight to each noun according to the importance of it in all patents by performing TF-IDF analysis. After that, it finds patents which have similar weights with preferred patents by a user. In this paper, this similarity is called a "Domain Similarity". Next, the suggested system extract technology sector's characteristics from patent document by analyzing the international technology classification code (International Patent Classification, IPC). Every patents have more than one IPC, and each user can attach more than one tag to the patents they like. Thus, each user has a set of IPC codes included in tagged patents. The suggested system manages this IPC set to analyze technology preference of each user and find the well-fitted patents for them. In order to do this, the suggeted system calcuates a 'Technology_Similarity' between a set of IPC codes and IPC codes contained in all other patents. After that, when the tag information of multiple users are accumulated, the system expands the recommendations in consideration of other users' social tag information relating to the patent that is tagged by a concerned user. The similarity between tag information of perferred 'patents by user and other patents are called a 'Social Simialrity' in this paper. Lastly, a 'Total Similarity' are calculated by adding these three differenent similarites and patents having the highest 'Total Similarity' are recommended to each user. The suggested system are applied to a total of 1,638 korean patents obtained from the Korea Industrial Property Rights Information Service (KIPRIS) run by the Korea Intellectual Property Office. However, since this original dataset does not include tag information, we create virtual tag information and utilized this to construct the semi-virtual dataset. The proposed recommendation algorithm was implemented with JAVA, a computer programming language, and a prototype graphic user interface was also designed for this study. As the proposed system did not have dependent variables and uses virtual data, it is impossible to verify the recommendation system with a statistical method. Therefore, the study uses a scenario test method to verify the operational feasibility and recommendation effectiveness of the system. The results of this study are expected to improve the possibility of matching promising patents with the best suitable businesses. It is assumed that users' experiential knowledge can be accumulated, managed, and utilized in the As-Is patent system, which currently only manages standardized patent information.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.121-145
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• 2010

University timetabling depending on the educational environments of universities is an NP-hard problem that the amount of computation required to find solutions increases exponentially with the problem size. For many years, there have been lots of studies on university timetabling from the necessity of automatic timetable generation for students' convenience and effective lesson, and for the effective allocation of subjects, lecturers, and classrooms. Timetables are classified into a course timetable and an examination timetable. This study focuses on the former. In general, a course timetable for liberal arts is scheduled by the office of academic affairs and a course timetable for major subjects is scheduled by each department of a university. We found several problems from the analysis of current course timetabling in departments. First, it is time-consuming and inefficient for each department to do the routine and repetitive timetabling work manually. Second, many classes are concentrated into several time slots in a timetable. This tendency decreases the effectiveness of students' classes. Third, several major subjects might overlap some required subjects in liberal arts at the same time slots in the timetable. In this case, it is required that students should choose only one from the overlapped subjects. Fourth, many subjects are lectured by same lecturers every year and most of lecturers prefer the same time slots for the subjects compared with last year. This means that it will be helpful if departments reuse the previous timetables. To solve such problems and support the effective course timetabling in each department, this study proposes a university timetabling support system based on two phases. In the first phase, each department generates a timetable template from the most similar timetable case, which is based on case-based reasoning. In the second phase, the department schedules a timetable with the help of interactive user interface under the timetabling criteria, which is based on rule-based approach. This study provides the illustrations of Hanshin University. We classified timetabling criteria into intrinsic and extrinsic criteria. In intrinsic criteria, there are three criteria related to lecturer, class, and classroom which are all hard constraints. In extrinsic criteria, there are four criteria related to 'the numbers of lesson hours' by the lecturer, 'prohibition of lecture allocation to specific day-hours' for committee members, 'the number of subjects in the same day-hour,' and 'the use of common classrooms.' In 'the numbers of lesson hours' by the lecturer, there are three kinds of criteria : 'minimum number of lesson hours per week,' 'maximum number of lesson hours per week,' 'maximum number of lesson hours per day.' Extrinsic criteria are also all hard constraints except for 'minimum number of lesson hours per week' considered as a soft constraint. In addition, we proposed two indices for measuring similarities between subjects of current semester and subjects of the previous timetables, and for evaluating distribution degrees of a scheduled timetable. Similarity is measured by comparison of two attributes-subject name and its lecturer-between current semester and a previous semester. The index of distribution degree, based on information entropy, indicates a distribution of subjects in the timetable. To show this study's viability, we implemented a prototype system and performed experiments with the real data of Hanshin University. Average similarity from the most similar cases of all departments was estimated as 41.72%. It means that a timetable template generated from the most similar case will be helpful. Through sensitivity analysis, the result shows that distribution degree will increase if we set 'the number of subjects in the same day-hour' to more than 90%.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.43-56
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• 2020

Recommender systems help users make the best choice among various options. Especially, recommender systems play important roles in internet sites as digital information is generated innumerable every second. Many studies on recommender systems have focused on an accurate recommendation. However, there are some problems to overcome in order for the recommendation system to be commercially successful. First, there is a lack of transparency in the recommender system. That is, users cannot know why products are recommended. Second, the recommender system cannot immediately reflect changes in user preferences. That is, although the preference of the user's product changes over time, the recommender system must rebuild the model to reflect the user's preference. Therefore, in this study, we proposed a recommendation methodology using topic modeling and sequential association rule mining to solve these problems from review data. Product reviews provide useful information for recommendations because product reviews include not only rating of the product but also various contents such as user experiences and emotional state. So, reviews imply user preference for the product. So, topic modeling is useful for explaining why items are recommended to users. In addition, sequential association rule mining is useful for identifying changes in user preferences. The proposed methodology is largely divided into two phases. The first phase is to create user profile based on topic modeling. After extracting topics from user reviews on products, user profile on topics is created. The second phase is to recommend products using sequential rules that appear in buying behaviors of users as time passes. The buying behaviors are derived from a change in the topic of each user. A collaborative filtering-based recommendation system was developed as a benchmark system, and we compared the performance of the proposed methodology with that of the collaborative filtering-based recommendation system using Amazon's review dataset. As evaluation metrics, accuracy, recall, precision, and F1 were used. For topic modeling, collapsed Gibbs sampling was conducted. And we extracted 15 topics. Looking at the main topics, topic 1, top 3, topic 4, topic 7, topic 9, topic 13, topic 14 are related to "comedy shows", "high-teen drama series", "crime investigation drama", "horror theme", "British drama", "medical drama", "science fiction drama", respectively. As a result of comparative analysis, the proposed methodology outperformed the collaborative filtering-based recommendation system. From the results, we found that the time just prior to the recommendation was very important for inferring changes in user preference. Therefore, the proposed methodology not only can secure the transparency of the recommender system but also can reflect the user's preferences that change over time. However, the proposed methodology has some limitations. The proposed methodology cannot recommend product elaborately if the number of products included in the topic is large. In addition, the number of sequential patterns is small because the number of topics is too small. Therefore, future research needs to consider these limitations.

• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.5
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• pp.626-635
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• 2009

The purposes of the study were to identify a comprehensive competency list related to the jobs of nutrition teachers and to compare the competency needs for nutrition teachers and dieticians' competency levels. Job functional areas and a competency list for nutrition teachers were developed based on a review of literature and revised through expert panel reviews. A total of 53 competency statements associated with 11 job functional areas were specified. Questionnaires were distributed to 457 dieticians engaged in school food service and 148 responses were returned (response rate: 32.4%). Excluding incomplete responses, 142 questionnaires were used for data analysis. Approximately half of the respondents were enrolled in an 1-year nutrition teacher certificate program, 25% in a graduate school of nutrition education, and 19% had completed an 1-year nutrition teacher certificate program. The dieticians highly rated requirements of the competencies related to sanitation and employee safety, nutrition counseling, nutrition education, and teaching practices; in contrary, their competency levels for nutrition education, nutrition counseling, and teaching practices were low. Respondents' competency levels were significantly lower than the required competency levels of effective nutrition teachers in all functional areas. A quadratic analysis based on the requirement and self-evaluation of the competencies revealed that priorities of education programs targeting school nutrition teachers or students preparing to be nutrition teachers should be placed on improving competencies related to nutrition education, nutrition counseling, teaching practices, sanitation and employee safety, menu management, and human resource management. These results can be used to develop curriculum materials for basic and continuing professional education for nutrition teachers. It is necessary to review and update competencies regularly to reflect environmental changes in school food service programs.