• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.475-480
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• 2005

인터넷상에 존재하는 수 많은 웹 페이지들에는 정형화되지 않은 각종 정보들이 이종의 형태로 산재되어 있다. 현재의 검색 기술을 통하여 필요한 정보를 찾아내는 것은 시간과 비용이 많이 소요되는 비효율적인 방법으로 이뤄지고 있다. 이러한 상황에서 사용자가 원하는 정보를 검색 및 추출해내어 정형화시키는 것은 매우 중요하다. 전자상거래의 폭발적 성장에도 불구하고 전자상거래 표준 활용 및 적용이 미비하여 e- Procurement, e-Marketplace, on-Line Shopping Mall 등에서 소비자가 원하는 상품 정보를 손쉽게 획득하지 못하고 있다. 이는 공급자에게는 보다 많은 매출의 기회를 구매자에게는 보다 좋은 자재 및 상품을 저렴한 가격에 소싱 할 수 있는 기회를 제공하지 못하는 문제점이 발생한다. 본 연구에서 제안하고자 하는 지능형 상품 에이전트는 소비자가 구매하고자 하는 특정 상품에 대한 공급자 검색 문제를 해결하기 위하여, 시스템 내부 정보의 확장 및 지식화 뿐만 아니라 웹 상의 다양한 상품 정보를 자동적으로 수집 및 가공하여 저장하는 역할을 수행한다. 이러한 연구를 위해서 사용한 기술은 우선 database 의 schema 를 읽어 들일 수 있는 DB schema reader, 인터넷 웹 페이지(웹문서)를 방문해서 다양한 정보들의 URL을 수집하는 일을 하는 Meta Search Engine 과 Focused Crawler, 그리고 다른 형태의 데이터 구조를 특정 목적에 따라 표준화된 형태로 바꾸는 Wrapper가 있다. 이러한 기술들을 연동하여 필요한 정보들을 추출 공급자 검색 문제를 해결하고자 하는 것이 연구의 목적이다. 정보추출은 사용자의 관심사에 적합한 문서들로부터 어떤 구체적인 사실이나 관계를 정확히 추출하는 작업을 가리킨다.앞으로 e-메일, 매신저, 전자결재, 지식관리시스템, 인터넷 방송 시스템의 기반 구조 역할을 할 수 있다. 현재 오픈웨어에 적용하기 위한 P2P 기반의 지능형 BPM(Business Process Management)에 관한 연구와 X인터넷 기술을 이용한 RIA (Rich Internet Application) 기반 웹인터페이스 연구를 진행하고 있다.태도와 유아의 창의성간에는 상관이 없는 것으로 나타났고, 일반 유아의 아버지 양육태도와 유아의 창의성간의 상관에서는 아버지 양육태도의 성취-비성취 요인에서와 창의성제목의 추상성요인에서 상관이 있는 것으로 나타났다. 따라서 창의성이 높은 아동의 아버지의 양육태도는 일반 유아의 아버지와 보다 더 애정적이며 자율성이 높지만 창의성이 높은 아동의 집단내에서 창의성에 특별한 영향을 더 미치는 아버지의 양육방식은 발견되지 않았다. 반면 일반 유아의 경우 아버지의 성취지향성이 낮을 때 자녀의 창의성을 향상시킬 수 있는 것으로 나타났다. 이상에서 자녀의 창의성을 향상시키는 중요한 양육차원은 애정성이나 비성취지향성으로 나타나고 있어 정서적인 측면의 지원인 것으로 밝혀졌다.징에서 나타나는 AD-SR맥락의 반성적 탐구가 자주 나타났다. 반성적 탐구 척도 두 그룹을 비교 했을 때 CON 상호작용의 특징이 낮게 나타나는 N그룹이 양적으로 그리고 내용적으로 더 의미 있는 반성적 탐구를 했다용을 지원하는 홈페이지를 만들어 자료 제공 사이트에 대한 메타 자료를 데이터베이스화했으며 이를 통해 학생들이 원하는 실시간 자료를 검색하여 찾을 수 있고 홈페이지를 방분했을 때 이해하기 어려운 그래프나 각 홈페이지가 제공하는 자료들에 대한 처리 방법을 도움말로 제공받을 수 있게 했다. 실시간 자료들을 이용한 학습은 학생들의 학습 의욕과 탐구 능력을 향상시켰으

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.55-64
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• 2013

Due to the popularization of digital high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy for anyone to make a high-quality counterfeit money. However, the probability of detecting a counterfeit money to the general public is extremely low. In this paper, we propose a counterfeit money detection algorithm using a general purpose scanner. This algorithm determines counterfeit money based on the different features in the printing process. After the non-local mean value is used to analyze the noises from each money, we extract statistical features from these noises by calculating a gray level co-occurrence matrix. Then, these features are applied to train and test the support vector machine classifier for identifying either original or counterfeit money. In the experiment, we use total 324 images of original money and counterfeit money. Also, we compare with noise features from previous researches using wiener filter and discrete wavelet transform. The accuracy of the algorithm for identifying counterfeit money was over 94%. Also, the accuracy for identifying the printing source was over 93%. The presented algorithm performs better than previous researches.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1573-1587
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• 2021

A Drone image is an ultra-high-resolution image that is several or tens of times higher in spatial resolution than a satellite or aerial image. Therefore, drone image-based remote sensing is different from traditional remote sensing in terms of the level of object to be extracted from the image and the amount of data to be processed. In addition, the optimal scale and size of data used for model training is different depending on the characteristics of the applied deep learning model. However, moststudies do not consider the size of the object to be found in the image, the spatial resolution of the image that reflects the scale, and in many cases, the data specification used in the model is applied as it is before. In this study, the effect ofspatial resolution and image size of drone image on the accuracy and training time of the semantic segmentation deep learning model of six wintering vegetables was quantitatively analyzed through experiments. As a result of the experiment, it was found that the average accuracy of dividing six wintering vegetablesincreases asthe spatial resolution increases, but the increase rate and convergence section are different for each crop, and there is a big difference in accuracy and time depending on the size of the image at the same resolution. In particular, it wasfound that the optimal resolution and image size were different from each crop. The research results can be utilized as data for getting the efficiency of drone images acquisition and production of training data when developing a winter vegetable segmentation model using drone images.

• The Journal of Bigdata
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• v.6 no.1
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• pp.37-49
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• 2021

The number of dementia patients in Korea is estimated to be over 800,000, and the severity of dementia is becoming a social problem. However, no treatment or drug has yet been developed to cure dementia worldwide. The number of dementia patients is expected to increase further due to the rapid aging of the population. Currently, early detection of dementia and delaying the course of dementia symptoms is the best alternative. This study presented a methodology for early diagnosis of dementia by measuring and analyzing amyloid plaques. This vital protein can most clearly and early diagnose dementia in the retina through AI-based image analysis. We performed binary classification and multi-classification learning based on CNN on retina data. We also developed a deep learning algorithm that can diagnose dementia early based on pre-processed retinal data. Accuracy and recall of the deep learning model were verified, and as a result of the verification, and derived results that satisfy both recall and accuracy. In the future, we plan to continue the study based on clinical data of actual dementia patients, and the results of this study are expected to solve the dementia problem.

• Journal of the Korean Chemical Society
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• v.63 no.3
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• pp.196-208
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• 2019

This study analyzed achievement standards in the 2015 revised Science Education Standards as well as activities and assessment items in grade 7 science textbooks using science core competencies and subcomponents. Scientific participation and lifelong learning capacity was not involved in the achievement standards. Logical thinking of scientific thinking capacity, planning and carrying out investigation, analyzing and interpreting data, developing and using models, and constructing explanation of scientific inquiry capacity, collecting and selecting information of scientific problem solving capacity, and using various communication methods of scientific communication capacity were involved in the achievement standards. All five scientific core competencies including all subcomponents except rational decision making of scientific problem solving capacity and understanding and coordinating diverse thoughts of scientific communication capacity were involved in activities of science textbooks. All five scientific core competencies were involved in assessment items of science textbooks. Logical thinking and creative thinking of scientific thinking capacity, planning and carrying out investigation and constructing explanation of scientific inquiry capacity, identifying problems, collecting and selecting information, suggesting solutions, and performing of scientific problem solving capacity, using various communication methods, arguing based on evidence of scientific communication capacity, and being interested in science technology and society issues of scientific participation and lifelong learning capacity.

• Journal of The Korean Association For Science Education
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• v.39 no.2
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• pp.295-305
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• 2019

In previous study, visual representation competence taxonomy (VRC-T), which is composed of two dimensions, was developed for the purpose of promoting effective visual representation use and research in science education. In this study, elementary school students' visual representation competence for shadow phenomenon was investigated using VRC-T. In terms of visual representation competence, 'interpretation' was the highest score, followed by 'construction' and 'integration'. It also showed that students' visual representation competence was not high even after learning shadow-related units in the regular curriculum. On the other hand, text-based scientific knowledge was not correlated with all categories of visual representation competence. This indicates that there is a need to emphasize visual representation more in science class. Finally, hierarchical relationship among cognitive processes of VRC-T was explored according to ordering theory. If the tolerance level is somewhat loosened, a linear hierarchical relationship was found between the six cognitive processes. This suggests that VRC-T is an analytical framework that can be useful when designing assessment tools, tasks, and science class activities to enhance visual representation competence.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.681-692
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• 2020

This study analyzed a textbook published for Korean culture education in a trend of communicative teaching methods, and suggested the ways for the integrated diversity of culture education with expression activities. This study set up the final goal of strengthening 'cultural competence' which is the next stage of 'cultural awareness' and 'cultural literacy' in the goal hierarchy for culture education, and analyzed not only the theme distribution but the patterns of expression activities in the textbook. It assumed that one of the most effective ways to achieve the goal is the convergence with expression activities in order to strengthen 'cultural competence' which aims to the creative culture production as well as the simple comparison between learners' mother culture and the target culture. This textbook is characterized by abundant visual materials, focus on the behavior culture and the information culture rather than the achieved culture. and media reading materials in diverse levels for utilization possibly in any proficiency levels. Also, it found out by analyzing the patterns of expression activities that the question forms inducing learners' speech and writing are restricted to a few patterns. Lastly, this study proposed the ways to achieve the goal "cultural competence" as follows: diversity of question forms, extension of expression activities and creative application in integrating the related activities.

• Education of Primary School Mathematics
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• v.25 no.4
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• pp.343-360
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• 2022

In mathematics classes, the verbal explanation may contain diverse mathematical concepts and principles in short sentences. It may also include mathematics symbols and terms that might not be used in everyday life. Therefore, students may need particular listening ability in order to understand and participate in mathematics communication. Unlike general listening, the listening ability for mathematics classes may require student to integrate their mathematical and linguistic knowledge. The aim of this study is to reveal the subdomains of listening ability for mathematics classes in a elementary school. I categorized listening ability for mathematics classes in a elementary school from the literature. The categories of listening ability for mathematics are Interpretive Listening, Evaluative Listening, Hermeneutic Listening, Selective Listening, Pretend Listening, and Ignored Listening. In order to develop a framework for understanding listening ability for mathematics classes, I investigated a hierarchy of 412 South Korean elementary teachers' perception. Through a web-based survey, the teachers were asked to rank order their beliefs about and students' listening ability. Findings show that teachers' perceptions about listening ability for mathematics classes are divergent from current research trends. South Korean elementary teachers perceived Interpretive Listening as the most important listening.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.923-935
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• 2022

This paper deals with detection and classification of leaf diseases for phenomics systems. As the smart farm systems of plants are increased, It is important to determine quickly the abnormal growth of plants without supervisors. This paper considers the color distribution and shape information of leaf diseases, and designs two deep leaning networks in training the leaf diseases. In the first step, color distribution of input image is analyzed for possible diseases. In the second step, the image is first partitioned into small segments using mean shift clustering, and the color information of each segment is inspected by the proposed Color Network. When a segment is determined as disease, the shape parameters of the segment are extracted and inspected by proposed Shape Network to classify the leaf disease types in the third step. According to the experiments with two types of diseases (frogeye/rust and tipburn) for apple leaves and iceberg, the leaf diseases are detected with 92.3% recall for a segment and with 99.3% recall for an input image where there are usually more than two disease segments. The proposed method is useful for detecting leaf diseases quickly in the smart farm environment, and is extendible to various types of new plants and leaf diseases without additional learning.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.2
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• pp.310-321
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• 2022

This study aimed to find out how creative education programs using AR/VR affect student's creative problem-solving skills and class satisfaction. For this purpose, a total of 179 students in 7 classes of the first grade of J High school located in the chungbuk region were the subjects of this study. The data were analyzed by performing two-dependent samples (t-test) based on the difference between the pre- and post-scores of creative problem-solving ability test, and the value of class satisfaction was analyzed and interpret using descriptive statistics and interview. The results of this study are as follows. First, except for 'execution', 'problem discovery and analysis', 'idea generation', 'execution plan', 'conviction and communication', and 'innovation tendency' showed statistically significant results. Second, in terms of class satisfaction of the creative education program, it was an average of 3.75 and it was difficult for learners to derive creative ideas, outputs, and results through groups within a given time in regular class, but generally showed a positive response. Therefore, it was confirmed that the creative education program using AR/VR increased student's learning motivation and interest in the process of generation or expanding ideas to solve problems like educational effect of STEAM.