• KOREAN JOURNAL OF CROP SCIENCE
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• v.69 no.1
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• pp.49-60
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• 2024

A region can be divided into cultivation zones based on homogeneity in weather variables that have the greatest influence on crop growth and yield. This study classified the cultivation zone of soybean using weather indices as a prior study to classify the agroclimatic zone of soybean. Meteorological factors affecting soybeans were determined through correlation analysis over a 10 year period (from 2013 to 2022) using data from the Miryang and Suwon regions collected from the soybean yield trial database of the Rural Development Administration, Korea and the meteorological database of the Korea Meteorological Administration. The correlation between growth characteristics and the minimum temperature, daily temperature range, and precipitation were high during the vegetative growth stages. Moreover, the correlation between yield components and the maximum temperature, daily temperature range, and precipitation were high during the reproductive growth stages. As a result of k-means clustering, soybean cultivation zones were divided into three zones. Zone 1 was the central inland region and southern Gyeonggi-do; Zone 2 was the southern part of the west coast, the southern part of the east coast, and the South Sea; and Zone 3 included parts of eastern Gyeonggi-do, Gangwon-do, and areas with high altitudes. Zone 1, which has a wide latitude range, was further subdivided into three cultivation zones. The results of this study may provide useful information for estimating agrometeorological characteristics and predicting the success of soybean cultivation in South Korea.

• Archives of design research
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• v.18 no.2 s.60
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• pp.211-218
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• 2005

As digital Information equipment is new arrival, new paradigm such as 'function exist but form don't' is needed in the field of design. Therefore, the activity of design is focused on the relationship of human and machine against visual form. For that reason, it is involved emotional factor in the relationship and studied on new field, the emotional interlace. The goal of this paper is to suggest the way of emotional interface on searching multimedia data. The main target of paper is effect sound and human's step and the main way of research is visualization after measuring and analyzing numerically similarity level among emotion-words. This paper suggests the theoretical bad(ground such as personal opinion, the character of auditory information and human's step and case studies on the emotion research. The experimental content about sound is fueled from my previous research and the main experimental content about human's step is made with regression-expression to substitute Quantification method 1 for value about stimulation. The realistic prototype to apply the research result will is suggested on the next research after studying the search environment.

• Journal of KIISE:Software and Applications
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• v.33 no.8
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• pp.692-702
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• 2006

In this study, a weighted fuzzy min-max (WFMM) neural network model for pattern classification is proposed. The model has a modified structure of FMM neural network in which the weight concept is added to represent the frequency factor of feature values in a learning data set. First we present in this paper a new activation function of the network which is defined as a hyperbox membership function. Then we introduce a new learning algorithm for the model that consists of three kinds of processes: hyperbox creation/expansion, hyperbox overlap test, and hyperbox contraction. A weight adaptation rule considering the frequency factors is defined for the learning process. Finally we describe a feature analysis technique using the proposed model. Four kinds of relevance factors among feature values, feature types, hyperboxes and patterns classes are proposed to analyze relative importance of each feature in a given problem. Two types of practical applications, Fisher's Iris data and Cleveland medical data, have been used for the experiments. Through the experimental results, the effectiveness of the proposed method is discussed.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.4
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• pp.87-92
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• 2019

This paper describes the pattern analysis for data of the factory energy consumption by using machine learning method. While usual statistical methods or approaches require specific equations to represent the physical characteristics of the plant, machine learning based approach uses historical data and calculate the result effectively. Although rule-based approach calculates energy usage with the physical equations, it is hard to identify the exact equations that represent the factory's characteristics and hidden variables affecting the results. Whereas the machine learning approach is relatively useful to find the relations quickly between the data. The factory has several components directly affecting to the electricity consumption which are machines, light, computers and indoor systems like HVAC (heating, ventilation and air conditioning). The energy loads from those components are generated in real-time and these data can be shown in time-series. The various sensors were installed in the factory to construct the database by collecting the energy usage data from the components. After preliminary statistical analysis for data mining, time-series clustering techniques are applied to extract the energy load pattern. This research can attributes to develop Factory Energy Management System (FEMS).

• Journal of The Korean Association For Science Education
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• v.33 no.5
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• pp.911-931
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• 2013

The purpose of this study was to analyze pre-service teachers' reflective discussion on their practical work-based teaching by focusing on the components of instruction and the connectivity of discussion. Eight after-class discussions were recorded and transcribed, and finally analyzed in terms of theoretically driven categories such as aims, teacher knowledge and learner response which also respectively reflect the actual flow of planning, implementation and evaluation of the teaching practice. The result showed that in their discussion about students, conceptual understanding and scientific skill components were most emphasized, while teaching method and strategy were most frequently addressed in the discussion about teacher knowledge. But this also revealed problems in their discussions such as the lack of discussion about inquiry and student interest, difficulties in clarifying theoretical terms and the lack of discussion about instructional models and theories. Meanwhile, pre-service teachers' discussions were limited in terms of connectivity between the components of instruction, meaning that their discussion tended to deal with each component separately rather than occurred in connection with each other. Furthermore, when connections were made during the discussion, only few components of instruction appeared. Based on this result, the paper suggests the need to develop tools to facilitate effective reflection in ways that incorporate various components of instruction and enhance connectivity between the components and between the instructions.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.8
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• pp.385-392
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• 2016

Market analysis for a business plain is required for the success in the modern world. Most important part in this analysis is pedestrian traffic counting. A traditional way for this is counting it in person. However, it causes high labor costs and mistakes. This paper proposes an automatic algorithm to measure the pedestrian traffic count using images with webcam. The proposed algorithm is composed of two parts: pedestrian area detection and movement tracking. In pedestrian area detection, moving blobs are extracted and pedestrian areas are detected using HoG features and Adaboost algorithm. In movement tracking, multi-level matching and false positive removal are applied to track pedestrian areas and count the pedestrian traffic. Multi-level matching is composed of 3 steps: (1) the similarity calculation between HoG area, (2) the similarity calculation of the estimated position with Kalman filtering, and (3) the similarity calculation of moving blobs in the pedestrian area detection. False positive removal is to remove invalid pedestrian area. To analyze the performance of the proposed algorithm, a comparison is performed with the previous human area detection and tracking algorithm. The proposed algorithm achieves 83.6% accuracy in the pedestrian traffic counting, which is better than the previous algorithm over 11%.

• Journal of The Korean Association For Science Education
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• v.28 no.6
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• pp.592-602
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• 2008

The purpose of this research is to explore types of pedagogical content knowledge (PCK, hereafter) for effective science teaching. In this research, we explored three science teachers' PCK on light, who were effective in teaching the topic with particular students. The data analysis consisted of identifying the three teachers' unique PCK and ways to improve each teaching episode through the teacher meetings. These analyses, which consisted of verbal exchanges among the participants, were identified on the basis of our understanding. Using grounded theory methods, the types of science PCK drawn from this research are: (1) teaching through curriculum reconstruction, (2) teaching to help students build their own explanation models about surrounding nature, (3) teaching for learning the social language of science, (4) teaching to motivate students' learning needs based on relevance of science to students, (5) teaching through lowering students' learning demand by providing scaffolding, (6) teaching based on the teacher's understanding of students, (7) teaching through inquiry with argumentation, (8) teaching through reification of abstract science concepts, and (9) teaching none marginalized science. Common features of science teachers with quality PCK and their professionalism in teaching are discussed.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.1
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• pp.116-122
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• 2012

Volatile flavor compounds derived from four black garlic extracts purchased in a local market were analyzed for the purpose of quality assessment. A total of 68 compounds was detected in samples using solid phase microextraction (SPME)/GC/MSD, and they were mainly sulfur-containing compounds, including three unknown compounds (21), aldehydes (10), furans (7), alcohols (6), aromatic compounds (7), ketones (4), acids (4), nitrogen-containing compounds (3), esters (2), and miscellaneous compounds (4). 2,6-Dimethyl-4-heptanone having a fruity-sweet odor was the most abundant in all of the samples. Six sulfur-containing compounds including allyl sulfide, 4-methyl-1,2,4-thiazole, 1,3,5-trithiane, unknown I (RI 1564), unknown II (RI 1565), and unknown III (RI 1613) were detected in all of the samples and appeared to contribute to the garlic-like odor. Particularly, three aldehydes (3-methylbutanal, benzaldehyde, phenylacetaldehyde), four furans (furfural, 2-acetylfuran, 5-methyl-2-furfural, furfural alcohol), and others (2,6-dimethylpyrazine, acetic acid) formed through a Maillard reaction during garlic aging were detected in all of the samples, and they contributed to the characteristic burnt, sweet, and sour flavors of black garlic extracts.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.253-257
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• 2007

최근 웹 상에 정보가 폭발적으로 증가함에 따라, 사용자의 취향에 맞는 정보를 선별하여 제공하는 추천 시스템에 대한 연구가 활발히 진행되고 있다. 추천시스템은 사용자의 관심정보를 기술한 사용자 프로파일을 기반으로 동작하기 때문에 정확한 사용자 프로파일의 생성은 매우 중요하다. 사용자의 암시적인 행동정보를 기반으로 취향을 분석하는 대표적인 연구로 사용자가 이용한 웹 문서를 분석하는 방법이 있다. 이는 사용자가 이용하는 웹 문서에 빈번하게 등장하는 단어를 기반으로 사용자의 프로파일을 생성하는 것이다. 그러나 최근 웹 문서는 사용자 취향과 관련 없는 많은 구성요소들(로고, 저작권정보 등)을 포함하고 있다. 따라서 이러한 내용들을 모두 포함하여 웹 문서를 분석한다면 생성되는 프로파일의 정확도는 낮아질 것이다. 따라서 본 논문에서는 사용자 기기에서 사용자의 웹 문서 이용내역을 분석하고, 동일한 사이트로부터 얻어진 문서들에서 반복적으로 등장하는 블록을 제거한 후, 정보블럭을 식별하여 사용자의 관심단어를 추출하는 새로운 프로파일 생성방법을 제안한다. 이를 통해 보다 정확하고 빠른 프로파일 생성이 가능해진다. 본 논문에서는 제안방법의 평가를 위해, 최근 구매활동이 있었던 사용자들이 이용한 웹 문서 데이터를 수집하였으며, TF-IDF 방법과 제안방법을 이용하여 사용자 프로파일을 각각 추출하였다. 그리고 생성된 사용자 프로파일과 구매데이터와의 연관성을 비교하였으며, 보다 정확한 프로파일이 추출되는 결과와 프로파일 분석시간이 단축되는 결과를 통해 제안방법의 유효성을 입증하였다.)으로 높은 점수를 보였으며 내장첨가량에 따른 관능특성에서는 온쌀죽은 내장 $2{\sim}5%$ 첨가, 반쌀죽은 내장 $3{\sim}5%$ 첨가구에서 유의적(p<0.05)으로 높은 점수를 보였으나 쌀가루죽은 내장 $1{\sim}2%$ 첨가구에서 유의적(p<0.05)으로 낮은 점수를 보였다. 이상의 연구 결과를 통해 온쌀은 2%, 반쌀은 3%, 쌀가루는 4%의 내장을 첨가하여 제조한 전복죽이 이화학적, 물성적 및 관능적으로 우수한 것으로 나타났다.n)방법의 결과와 비교하였다.다. 유비스크립트에서는 모바일 코드의 개념을 통해서 앞서 언급한 유비쿼터스 컴퓨팅 환경에서의 문제점을 해결하고자 하였다. 모바일 코드에서는 프로그램 코드가 네트워크를 통해서 컴퓨터를 이동하면서 수행되는 개념인데, 이는 물리적으로 떨어져있으면서 네트워크로 연결되어 있는 다양한 컴퓨팅 장치가 서로 연동하기 위한 모델에 가장 적합하다. 이는 기본적으로 배포(deploy)라는 단계가 필요 없게 되고, 새로운 버전의 프로그램이 작성될지라도 런타임에 코드가 직접 이동하게 되므로 버전 관리의 문제도 해결된다. 게다가 원격 함수를 매번 호출하지 않고 한번 이동된 코드가 원격지에서 모두 수행을 하게 되므로 성능향상에도 도움이 된다. 장소 객체(Place Object)와 원격 스코프(Remote Scope)는 앞서 설명한 특징을 직접적으로 지원하는 언어 요소이다. 장소 객체는 모바일 코드가 이동해서 수행될 계산 환경(computational environment

• Journal of Gifted/Talented Education
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• v.21 no.4
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• pp.1033-1053
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• 2011

In the process of establishing the principle of genetics, Mendel discovered problems based on various observations. Mendel's scientific thinking ability can be effective if this ability is embedded in gifted science education programs. The study aims to develop a science gifted education program utilizing Mendel's scientific thinking ability shown in the principles of genetics and examine students' changes in scientific thinking ability before and after the program implementation. For the program development, first, the characteristics of Mendel's scientific thinking ability in the process of establishing the principle of genetics were investigated and extracted the major elements of inquiry. Second, the science gifted education programs was developed by applying the inquiry elements from the Mendel's Law. The program was implemented with 19 students of $7^{th}$, $8^{th}$ graders who attend the science gifted education center affiliated with university during July 2011. The Mendel's scientific thinking ability was classified into induction, deduction, and integration. The elements of inquiry extracted from the Mendel's scientific thinking include making observation, puzzling observation, proposing causal questions, generating hypothesis, drawing inference, designing experiment, gathering and analyzing data, drawing conclusions, and making generalization. With applying these elements, the program was developed with four phases: $1^{st}$ - problem finding; $2^{nd}$ - hypothesis generating; $3^{rs}$ - hypothesis testing and $4^{th}$ - problem solving. After implementation, students' changes in scientific thinking ability were measured. The findings from the study are as follows: First, students' abilities of problem finding is significantly (p<.05) increased. Second, students' abilities of hypothesis generating is significantly (pp<.05) increased.