• Proceedings of the National Institute of Ecology of the Republic of Korea
• /
• 제4권4호
• /
• pp.159-176
• /
• 2023

The conservation of the raccoon dog (Nyctereutes procyonoides) in South Korea requires the protection and preservation of natural habitats while additionally ensuring coexistence with human activities. Applying habitat map modeling techniques provides information regarding the distributional patterns of raccoon dogs and assists in the development of future conservation strategies. The purpose of this study is to generate potential habitat distribution maps for the raccoon dog in South Korea using geospatial technology-based models. These models include the frequency ratio (FR) as a bivariate statistical approach, the group method of data handling (GMDH) as a machine learning algorithm, and convolutional neural network (CNN) and long short-term memory (LSTM) as deep learning algorithms. Moreover, the imperialist competitive algorithm (ICA) is used to fine-tune the hyperparameters of the machine learning and deep learning models. Moreover, there are 14 habitat characteristics used for developing the models: elevation, slope, valley depth, topographic wetness index, terrain roughness index, slope height, surface area, slope length and steepness factor (LS factor), normalized difference vegetation index, normalized difference water index, distance to drainage, distance to roads, drainage density, and morphometric features. The accuracy of prediction is evaluated using the area under the receiver operating characteristic curve. The results indicate comparable performances of all models. However, the CNN demonstrates superior capacity for prediction, achieving accuracies of 76.3% and 75.7% for the training and validation processes, respectively. The maps of potential habitat distribution are generated for five different levels of potentiality: very low, low, moderate, high, and very high.

• 지능정보연구
• /
• 제29권4호
• /
• pp.31-49
• /
• 2023

레스토랑 산업의 성장과 함께 레스토랑 오프라인 매장 수는 점차 증가하지만, 소비자는 자신의 선호도에 적합한 레스토랑을 선택하는 데 어려움을 경험하고 있다. 따라서 소비자의 선호도에 맞는 레스토랑을 추천하는 개인화된 추천 서비스의 필요성이 대두하고 있다. 기존 연구에서는 설문조사 및 평점 정보를 활용하여 소비자 선호도를 조사했으나, 이는 소비자의 구체적인 선호도를 효과적으로 반영하는데 어려움이 존재한다. 이러한 배경하에 온라인 리뷰는 방문 동기, 음식 평가 등 레스토랑에 대한 소비자 구체적인 선호도를 효과적으로 반영하기 때문에 필수적인 정보이다. 한편, 일부 연구에서는 리뷰 텍스트에 전통적인 기계학습 기법을 적용하여 소비자의 선호도를 측정하였다. 그러나 이러한 접근 방식은 주변 단어나 맥락을 고려하지 못하는 한계점이 존재한다. 따라서 본 연구는 딥러닝을 효과적으로 활용하여 온라인 리뷰에서 소비자의 선호도를 정교하게 추출하는 리뷰 텍스트 기반 레스토랑 추천 모델을 제안한다. 본 연구에서 제안된 모델은 추출된 높은 수준의 의미론적 표현과 소비자-레스토랑 상호작용을 연결하여 소비자의 선호도를 정확하고 효과적으로 예측한다. 실험 결과에 따르면 본 연구에서 제안된 추천 모델은 기존 연구에서 제안된 여러 모델에 비해 우수한 추천 성능을 보이는 것으로 나타났다.

• East Asian mathematical journal
• /
• 제29권2호
• /
• pp.109-135
• /
• 2013

The purpose of the study was to investigate the reality of middle school mathematics teachers' subject matter knowledge for teaching mathematical conjecture and justification. Data in the study were collected through interviewing nine Chinese and ten Korean middle school mathematics teachers. The teachers responded to the question that was designed in the form of a scenario that presents a teaching task related to a geometrical topic. The teachers' oral responses were audiotaped and transcribed, and their written notes were collected. The results of the study were compared to the analysis of American and Chinese elementary and secondary teachers' responses to the same task in Ball (1988) and Ma (1999). The findings of the study suggested that teachers' approaches to explaining and demonstrating a mathematical topic were significantly influenced by their knowledge of learners and knowledge of the curriculum they teach. One of the practical implications of the study is that teachers should recognize the advantages of learning the conceptual structure of a mathematical topic. It allows the teachers to have the flexibility to come up with meaningful mathematical approaches to teaching the topic, which are comprehensible to the learners whatever the grade levels they teach, rather than rule-based algorithms.

• 한국초등과학교육학회지:초등과학교육
• /
• 제20권2호
• /
• pp.187-196
• /
• 2001

Students' journals in science class are supposed to contribute to students' science teaming and to provide plentiful information on students' learning and progress. If interaction could be reinforced in the process of writing journals, the positive effects of the journals are expected to be increased. New approaches in teaching should be supported by school and community. Otherwise, teachers are frequently frustrated and failed to introduce new ways of instruction into science classes. The purposes of the study are to develop interactive journals, and approaches to introduce interactive journals at school level. The status and situation of the school were investigated by survey. Interactive journals were developed by teachers who experienced workshops on developing journals. A model journal was provided as a guidance to teachers. To establish environments for introducing journals in the school, an invited lecture was provided to increase parents' perceptions on journals. A communication system among students, parents, and teachers was established, and educational materials, such as encyclopedia, books, computers, and so on were prepared. For efficient administration of journals, various prizes and events were established. As a result of the study, teachers participated experienced professional development in terms of journals, interactive journals for science class were developed, the environments for the introduction of interactive journals at school level were established, and most students successfully completed science journals.

• 정보과학회 논문지
• /
• 제43권12호
• /
• pp.1356-1364
• /
• 2016

본 논문에서는 딥러닝 기법 중 하나인 deep convolutional neural network (DCNN)을 이용하여 영상의 구도를 개선하는 방법을 제시한다. 기존의 구도 개선 방법들은 영상의 주요 물체의 위치를 바탕으로 한 구도 평가 점수를 정의한 뒤 최적화를 통해 평가 점수를 향상시키는 방향으로 영상을 개선한다. 이는 계산량이 많고 기존 주요 물체 검출 알고리즘의 성능에 종속적이기 때문에 영상에 따라 구도 개선이 제대로 수행되지 않는 경우가 존재한다. 본 논문에서는 영상의 특징 추출에 뛰어난 성능을 보이는 DCNN을 이용해 영상을 반복적으로 크롭하여 미학적으로 구도가 개선된 영상을 얻는 방법을 제안한다. 실험 결과 및 사용자 평가를 통해 본 논문에서 제안한 알고리즘이 주어진 영상을 특정 구도 가이드라인(삼분할법, 주요 물체의 크기 등)을 따르도록 자동으로 크롭한다는 것을 보인다.

• 유통과학연구
• /
• 제11권6호
• /
• pp.51-58
• /
• 2013

Purpose - Nowadays, more than ever before, fierce competition, deep market segmentation, short product life cycles, and intensifying customer needs are putting increasing pressure on franchise's organizations to satisfy their customers by creating market-oriented relationships with and enhancing their market knowledge of them. One way that this might be achieved is by establishing deep ties (i.e., job commitment and job satisfaction) with their employees. Therefore, the purpose of this study is to examine how two important constructs of franchises' strategic efforts, LO (learning orientation) and RMO (relationship marketing orientation), affect job satisfaction, given the mediating role of job commitment. A franchise system comprises a set of contractual arrangements by which mutual obligations are performed. An organizational learning goal motivates employees to improve their abilities and master the tasks they perform. Relationship marketing, in addition, is to identify, establish, maintain, and enhance relationships with customers and other stakeholders to ensure that the objectives of all parties are met and this is done through the mutual exchange of promises. In a relationship marketing orientation, then, a firm creates, maintains, and enhances a strong relationship with its customers by sustaining long-term ties. This study was designed to examine the evolution of various theoretical approaches to franchise systems in order to determine whether theories about firms have significantly affected the franchise system. To this end, the authors developed a structural model consisting of several constructs. Previous studies have suggested that franchises' learning and relationship marketing orientations are important occupational immersion dimensions driving job satisfaction. Research design, data, methodology - We empirically tested a process of how the learning orientation and the relationship marketing orientation influence job commitment and job satisfaction using survey data drawn from 150 responding franchisees who were interviewed about their individual tendencies. Results - The results of this study provide empirical evidence that learning orientation, relationship marketing orientation, and job commitment all influence franchisees' job satisfaction. The results of this study indicate that, first, learning orientation had a significant effect on job satisfaction; second, relationship marketing orientation was positively related to job commitment; third, job commitment had a significant effect on job satisfaction. We also found that relationship marketing orientation and job satisfaction were mediated by job commitment. Conclusions - The findings of this study confirm the importance of learning orientation and relationship marketing orientation in maintaining a positive marketing relationship between franchiser and franchisee from to the perspective of the market. This indicates that franchiser support such as educational programs provided by the franchiser will help franchisees attain higher business management achievement and satisfaction. Moreover, a positive relationship between franchisees and consumers can be maintained through tie effects. Our findings also suggest that learning orientation plays a critical role in job satisfaction within the franchise system.

• Genomics & Informatics
• /
• 제17권2호
• /
• pp.17.1-17.3
• /
• 2019

Text mining has become an important research method in biology, with its original purpose to extract biological entities, such as genes, proteins and phenotypic traits, to extend knowledge from scientific papers. However, few thorough studies on text mining and application development, for plant molecular biology data, have been performed, especially for rice, resulting in a lack of datasets available to solve named-entity recognition tasks for this species. Since there are rare benchmarks available for rice, we faced various difficulties in exploiting advanced machine learning methods for accurate analysis of the rice literature. To evaluate several approaches to automatically extract information from gene/protein entities, we built a new dataset for rice as a benchmark. This dataset is composed of a set of titles and abstracts, extracted from scientific papers focusing on the rice species, and is downloaded from PubMed. During the 5th Biomedical Linked Annotation Hackathon, a portion of the dataset was uploaded to PubAnnotation for sharing. Our ultimate goal is to offer a shared task of rice gene/protein name recognition through the BioNLP Open Shared Tasks framework using the dataset, to facilitate an open comparison and evaluation of different approaches to the task.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.1315-1318
• /
• 2003

In this paper, a neural network based approach using a self-organizing feature map is proposed for the segmentation of X ray images. A number of algorithms based on such approaches as histogram analysis, region growing, edge detection and pixel classification have been proposed for segmentation of general images. However, few approaches have been applied to X ray image segmentation because of blur of the X ray image and vagueness of its edge, which are inherent properties of X ray images. To this end, we develop a new model based on the neural network to detect objects in a given X ray image. The new model utilizes Mumford-Shah functional incorporating with a modified adaptive SOFM. Although Mumford-Shah model is an active contour model not based on the gradient of the image for finding edges in image, it has some limitation to accurately represent object images. To avoid this criticism, we utilize an adaptive self organizing feature map developed earlier by the authors.[1] It's learning rule is derived from Mumford-Shah energy function and the boundary of blurred and vague X ray image. The evolution of the neural network is shown to well segment and represent. To demonstrate the performance of the proposed method, segmentation of an industrial part is solved and the experimental results are discussed in detail.

• 한국학교수학회논문집
• /
• 제17권1호
• /
• pp.73-92
• /
• 2014

본 연구는 초 중등 학생의 수학에 대한 정서, 가치, 흥미 및 자기효능감 등의 정의적 영역의 개선을 위한 방안을 모색하는데 일환을 두고 수행되었다. 이에 따라 먼저, 수학학습에 어려움을 겪고 있는 학생들의 수학학습 클리닉을 위한 상담 과정에서 상담교사에게 필요한 발문이 무엇인지를 파악하고자 하였다. 이를 위하여 지난 2년간 정례적으로 실시해오고 있는 수학클리닉의 상담 내용을 수집하여 상담을 위해 오가던 질문들을 모두 분석함으로써 상담과정에서 학생들을 진단하기 위해 필요한 발문들을 추출하였다. 자료 분석은 Strauss & Corbin(1998)의 근거이론 분석방법을 사용하여 개방코딩, 축 코딩, 선택코딩의 분석단계를 실시하였다. 도출한 패러다임(paradigm) 모형은 인과적 조건으로는 '수학학습 정서', 맥락적 조건으로 '수학학습능력 자신감', 중심현상은 '수학학습 태도', 중재적 조건은 '수학학습 개인적 성향', 작용/상호작용으로 '수학학습 자기관리', 그리고 마지막 결과로는 '수학학습 방법'으로 상담과정에서 나타나는 발문들을 범주와 하위범주들 간의 관계로 연결하였다. 이 과정에서 총 81개의 개념이 도출되었으며, 진술된 개념들은 다시 31개의 관련영역으로 범주화하였다. 본 연구는 클리닉 상담을 위한 진단지 제작 표준화 작업을 위한 근거 이론으로 활용될 수 있으리라 기대된다.

• The Journal of Asian Finance, Economics and Business
• /
• 제7권7호
• /
• pp.453-462
• /
• 2020

The research postulates the conceptualization of talent in the Vietnamese banking sector via examining the factors pertaining to the concept of talent and talent management (TM) in the sector. This study applied qualitative research methods. A total of 20 managers and directors of ten banks (three public, four private and three foreign banks) were recruited for semi-structured interviews. The findings revealed that a combination of interconnected soft skills, learning ability, flexibility, technology adaptability, integrity and risk management skills contributes to talent identification. Managers in some private banks construed talent to be commensurate with high performance and high potential, whereas managers in public banks and foreign banks mainly relied on performance results in talent recognition. Moreover, talented employees holding sales-related jobs are given the most attention by management in the studied banks. Regarding practical implications, the banking community and practitioners' focus should be imparted to soft skills development and integrity control in order to foster employee performance and attitudes. Attention should be paid not only to sales positions, but also to other positions within the bank. This study is one of a few which explores talent concepts and TM approaches in the banking sector in general and Vietnamese banking field in particular.