• Journal of Korean Elementary Science Education
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• v.43 no.4
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• pp.504-518
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• 2024

In this study, the pre-service elementary teachers' characteristics of pedagogical design using science teacher's guides were analyzed. Eleven pre-service teachers at the University of Education in Korea participated in the study. They were provided with three types of teacher's guides and were asked to use them to design a science lesson. Semi-structured interviews were conducted to obtain specific information on how the guides were implemented. The analysis of the results revealed that they primarily used the guides to classify the learning content for each lesson and establish connections between the content of the particular lessons through the unit learning system. The teacher's guides mainly featured knowledge-based learning objectives, and most pre-service teachers accepted them without considering the attitudinal aspects. In the process of designing the assessments, the teaching goals written down by the pre-service teachers were used as the main source. Teaching and learning activities were supplemented by evaluating the activities presented in the teacher's guides based on the students' cognitive level and misconceptions. In terms of teaching methods, the teacher's guides were evaluated and reorganized to develop teaching-learning models and to construct introductory activities that cater to students' interests and motivations. Based on the results, we discussed the utilization of the guides to enhance their pedagogical design capacity and suggested directions to improve them.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

• Korean Journal of Community Nutrition
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• v.26 no.3
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• pp.188-199
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• 2021

Objectives: The purpose was to identify the ingredients that are usually surveyed for assessing real prices and to present the demand for such surveys by nutrition teachers and dietitians for ingredients used by school foodservice. Methods: A survey was conducted online from December 2019 to January 2020. The survey questionnaire was distributed to 1,158 nutrition teachers and dietitians from elementary, middle, and high schools nationwide, and 439 (37.9% return rate) of the 1,158 were collected and used for data analysis. Results: The ingredients which were investigated for price realities directly by schools were industrial products in 228 schools (51.8%), fruits in 169 schools (38.4%), and specialty crops in 166 schools (37.7%). Moreover, nutrition teachers and dietitians in elementary, middle, and high schools searched in different ways for the real prices of ingredients. In elementary schools, there was a high demand for price information about grains, vegetables or root and tuber crops, special crops, fruits, eggs, fishes, and organic and locally grown ingredients by the School Foodservice Support Centers. Real price information about meats, industrial products, and pickled processed products were sought from the external specialized institutions. In addition, nutrition teachers and dietitians in middle and high schools wanted to obtain prices of all of the ingredients from the Offices of Education or the District Office of Education. Conclusions: Schools want to efficiently use the time or money spent on research for the real prices of ingredients through reputable organizations or to co-work with other nutrition teachers and dietitians. The results of this study will be useful in understanding the current status of the surveys carried out to determine the real price information for ingredients used by the school foodservice.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.97-117
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• 2020

Product evaluation criteria is an indicator describing attributes or values of products, which enable users or manufacturers measure and understand the products. When companies analyze their products or compare them with competitors, appropriate criteria must be selected for objective evaluation. The criteria should show the features of products that consumers considered when they purchased, used and evaluated the products. However, current evaluation criteria do not reflect different consumers' opinion from product to product. Previous studies tried to used online reviews from e-commerce sites that reflect consumer opinions to extract the features and topics of products and use them as evaluation criteria. However, there is still a limit that they produce irrelevant criteria to products due to extracted or improper words are not refined. To overcome this limitation, this research suggests LDA-k-NN model which extracts possible criteria words from online reviews by using LDA and refines them with k-nearest neighbor. Proposed approach starts with preparation phase, which is constructed with 6 steps. At first, it collects review data from e-commerce websites. Most e-commerce websites classify their selling items by high-level, middle-level, and low-level categories. Review data for preparation phase are gathered from each middle-level category and collapsed later, which is to present single high-level category. Next, nouns, adjectives, adverbs, and verbs are extracted from reviews by getting part of speech information using morpheme analysis module. After preprocessing, words per each topic from review are shown with LDA and only nouns in topic words are chosen as potential words for criteria. Then, words are tagged based on possibility of criteria for each middle-level category. Next, every tagged word is vectorized by pre-trained word embedding model. Finally, k-nearest neighbor case-based approach is used to classify each word with tags. After setting up preparation phase, criteria extraction phase is conducted with low-level categories. This phase starts with crawling reviews in the corresponding low-level category. Same preprocessing as preparation phase is conducted using morpheme analysis module and LDA. Possible criteria words are extracted by getting nouns from the data and vectorized by pre-trained word embedding model. Finally, evaluation criteria are extracted by refining possible criteria words using k-nearest neighbor approach and reference proportion of each word in the words set. To evaluate the performance of the proposed model, an experiment was conducted with review on '11st', one of the biggest e-commerce companies in Korea. Review data were from 'Electronics/Digital' section, one of high-level categories in 11st. For performance evaluation of suggested model, three other models were used for comparing with the suggested model; actual criteria of 11st, a model that extracts nouns by morpheme analysis module and refines them according to word frequency, and a model that extracts nouns from LDA topics and refines them by word frequency. The performance evaluation was set to predict evaluation criteria of 10 low-level categories with the suggested model and 3 models above. Criteria words extracted from each model were combined into a single words set and it was used for survey questionnaires. In the survey, respondents chose every item they consider as appropriate criteria for each category. Each model got its score when chosen words were extracted from that model. The suggested model had higher scores than other models in 8 out of 10 low-level categories. By conducting paired t-tests on scores of each model, we confirmed that the suggested model shows better performance in 26 tests out of 30. In addition, the suggested model was the best model in terms of accuracy. This research proposes evaluation criteria extracting method that combines topic extraction using LDA and refinement with k-nearest neighbor approach. This method overcomes the limits of previous dictionary-based models and frequency-based refinement models. This study can contribute to improve review analysis for deriving business insights in e-commerce market.

• Journal of Korean Home Economics Education Association
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• v.18 no.1 s.39
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• pp.49-64
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• 2006

The objective of this research is to see the current status of application and development of web contents data, and to suggest the way to improve the application and development of web contents data in home economics classes in middle schools. The respondents of the research were 312 middle school home economics teachers from all over the nation, and the tool was a questionnaire which consist of 22 questions about general status of the person who was answering and their recognitions and demands on the application and development of the web contents data. The major findings were as follows : 1) 88.5% of the sample responded that they accurately grasped a meaning of a class employing web contents data, and as for effects on preparation of professional study. 2) Most of the teachers were making good use of materials from the web in their classes. They responded that it maximized the efficiency of students' learning. Some didn't use the web contents in their classes. The reasons why the web contents data usage had been low were that the classrooms were not equipped properly (43.2%) and it took long time to create web contests (37.8%). 3) Kinds of web contents data that showed the most amount of usage were the presentations (48.4%), multi-media teaching materials(23.7%), and moving pictures(19.9%). 4) Teaches wanted to improve these particular materials among the web contents: family life and home, administration and environment of resources, and clothing preparation and administration. As for the lessons, teachers wanted developments of contents of lessons, generating motives, and evaluation to be by individual teachers or curriculum researchers' societies, and 30.8% were by Korea Education & Research Information Service (KERIS).

• The Korean Journal of Pesticide Science
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• v.19 no.3
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• pp.204-209
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• 2015

This study was carried out to investigate residual characteristics of insecticide acetamiprid in asparagus under greenhouse condition from July to August and consequentially to obtain basic data for guideline on safe use of this pesticide in asparagus. Residues of acetamiprid in young stem of asparagus before and after removing foliage were analyzed from samples harvested at 0, 1, 3, 5 and 7 days after single application before harvest. As a result, residues of acetamiprid in young stem of asparagus before and after removing foliage at 0 day were 0.27 mg/kg and 0.14 mg/kg, respectively, which were higher than tentative limit (0.1 mg/kg). However, 3 days later residues of acetamiprid were lower than the tentative limit, representing 0.08 mg/kg and 0.03 mg/kg in the asparagus before and after removing foliage, respectively. Acetamiprid was undetectable in both samples at 5 days since the concentrations were less than detection limit (0.02 mg/kg) in this study. In summary, the half-life of acetamiprid in asparagus regardless of removing foliage was quite short under greenhouse condition from July to August, in the range of 1-3 days, and single application of acetamiprid water dispersible granule in/on asparagus at 7 days before harvest would have no problem on safety issues about pesticide residue. This result might be basic information to construct guideline for safe use of acetamiprid in asparagus.

• Journal of Food Hygiene and Safety
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• v.22 no.4
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• pp.338-345
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• 2007

This study surveyed on the actual conditions of using sanitizers and disinfectants for improvements of sanitization on food utensils at 105 school and 20 industry foodservice operations. The questionnaire which was administered to 125 foodservices was used as a mail or visitation method. The answers of asking "Perception on temporary authorization system of sanitizers and disinfectants on food utensils" were 75% in contract managed school foodservices, 81.8% in self operated school foodservices, and 50% in industry. Main factors to choose sanitizers were sterilizing power (38.6%, 28.6%, 38.9%) and safety (32.6%, 46.1%, 33.3%) at every foodservices. Keeping ratio of sanitizers and disinfectants guidelines in contract managed school, self operated school and industry foodservices were 64.8%, 52% and 73.7%, respectively. If easy and practical guideline is developed, most foodservices replied to use if for disinfection of foodservices. Most of the foodservices were not only knowing sanitizers and disinfectants but also possessing a guideline. However, they didn't perform disinfection according to the guideline due to its complexity. Consequently, we suggest that it is necessary to provide an easy and practical "sanitizers and disinfectants guideline" and useful information.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.12
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• pp.874-885
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• 2011

In this study, the urban $CO_2$ emission based on energy consumption (Coal, Petroleum, Electricity, and City Gas) in 16 provincial and metropolitan city governments in South Korea was evaluated. For calculation of the urban $CO_2$ emission, direct and indirect emissions were considered. Direct emissions refer to generation of greenhouse gas (GHG) on-site from the energy consumption. Indirect emissions refer to the use of resources or goods that discharge GHG emissions during energy production. The total GHG emission was 497,083 thousand ton $CO_2eq.$ in 2007. In the indirect GHG emission, about 240,388 thousand ton $CO_2eq.$ was occurred, as 48% of total GHG emission. About 256,694 thousand ton $CO_2eq.$ (52% of total GHG emissions) was produced in the direct GHG emission. This amount shows 13% difference with 439,698 thousand ton $CO_2eq.$ which is total national GHG emission data using current calculation method. Local metropolitan governments have to try to get accuracy and reliability for quantifying their GHG emission. Therefore, it is necessary to develop and use Korean emission factors than using the IPCC (Intergovernmental Panel on Climate Change) emission factors. The method considering indirect and direct GHG emission, which is suggested in this study, should be considered and compared with previous studies.

• Korean Journal of Environment and Ecology
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• v.24 no.3
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• pp.235-248
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• 2010

This study was carried out to the actual conditions and improvement of the eco-forests master plan in South Korea, and suggested its problems and improvement direction. Results from survey and analysis of limiting factors or constraints in the construction plans of eco-forests in Korea revealed that there were highly frequent problems involving site feasibility, topographic aspect, and existing vegetation. The results of survey on the status of land use indicated that the average ratio of the use of private estate was 29.7%, so then it was estimated that a great amount of investment in purchase of eco-forest site would be required. Results from survey on major introduced facilities showed that there was high frequency of introduction of infrastructure, building facility, recreational facility, convenience facility, and information facility, and that there was low frequency of introduction of plant culture system, ecological facility, structural symbol and sculpture, and the likes. There was just one eco-forest park where more than 500 species of plants grew, and the result of investigation indicated that the diversity of plant species in 11 eco-forest parks was lower than the standards for construction of eco-forest. Results from analysis of the projects costs revealed that investment cost in facilities was higher than planting costs, and that a large amount of investment was made in the initial stage of the project. There was no planned budget for the purpose of cultivating and maintaining the plants and vegetation after construction of eco-forest. The basic concepts in construction of eco-forests were established according to the guidelines presented by the Korea Forest Service; however, the detailed work of the project was planned with its user-oriented approach. Then the construction of eco-forest was being planned following the directions, which would lead to development of a plant garden similar to arboretum or botanical garden. Therefore, it is required that the architect who designs eco-forest as well as the public officer concerned firmly establish the concepts of eco-forest, and that, through close analysis of development conditions, a candidate site to fit the purpose of constructing eco-forest be selected, and also a substantive management plan be established upon completion of construction of eco-forest.