• Journal of English Language & Literature
• /
• v.54 no.2
• /
• pp.189-215
• /
• 2008

This study proposes using children's literature as a means of teaching and learning English as a foreign language and suggests practical strategies on the basis of transactional theory of reading suggested by Rosenblatt (1994, 1995). This study suggests three novels written for children or young adults: On My Honor (1986) by Marion Dane Bauer, The Giver (1993) by Lois Lowry and Hatchet (1987) by Gary Paulsen. These texts were selected because of their diverse topics, easy and comprehensible language, engaging stories, and authentic and rich expressions, making them effective materials for foreign language learners. This paper is organized as follows: First, it reviews research on teaching literature in English education and response-oriented language teaching to provide theoretical background of literature-based language teaching and learning. Second, it provides the background of the texts selected for the study. Third, it develops diverse, practical strategies for instructors who intend to use children's literature in EFL teaching. We expect to guide EFL instructors in adopting children's literature in their English class by connecting theory and practice and by providing diverse methods and strategies, and sample responses by EFL university students.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.78-80
• /
• 2021

Currently, research on natural language processing (NLP) is rapidly evolving. Natural language processing is a technology that allows computers to analyze the meanings of languages used in everyday life, and is used in various fields such as speech recognition, spelling tests, and text classification. Currently, the most commonly used natural language processing library is NLTK based on English, which has a disadvantage in Korean language processing. Therefore, after introducing KonLPy and Soynlp, the Korean Tokenizing libraries, we will analyze morphology analysis and processing techniques, compare and analyze modules with Soynlp that complement KonLPy's shortcomings, and use them as natural language processing models.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.19 no.2
• /
• pp.73-81
• /
• 2024

Recently, mobile manipulators have been utilized in agriculture industry for weed removal and harvest automation. This paper proposes a domain adaptive fruit detection method for harvest automation, by utilizing OWL-ViT model which is an open-vocabulary object detection model. The vision-language model can detect objects based on text prompt, and therefore, it can be extended to detect objects of undefined categories. In the development of deep learning models for real-world problems, constructing a large-scale labeled dataset is a time-consuming task and heavily relies on human effort. To reduce the labor-intensive workload, we utilized a large-scale public dataset as a source domain data and employed a domain adaptation method. Adversarial learning was conducted between a domain discriminator and feature extractor to reduce the gap between the distribution of feature vectors from the source domain and our target domain data. We collected a target domain dataset in a real-like environment and conducted experiments to demonstrate the effectiveness of the proposed method. In experiments, the domain adaptation method improved the AP50 metric from 38.88% to 78.59% for detecting objects within the range of 2m, and we achieved 81.7% of manipulation success rate.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.2
• /
• pp.87-92
• /
• 2024

In this paper, a RAG system was implemented using an existing Large Language Model (LLM) and Langchain library to develop a dental consultation chatbot. For this purpose, we collected contents from the webpage bulletin boards of domestic dental university hospitals and constructed consultation data with the advice and supervision of dental specialists. In order to divide the input consultation data into appropriate sizes, the chunk size and the size of the overlapping text in each chunk were set to 1001 and 100, respectively. As a result of the simulation, the Retrieval Augmented LLM searched for and output the consultation content that was most similar to the user input. It was confirmed that the accessibility of dental consultation and the accuracy of consultation content could be improved through the built chatbot.

• Journal of Intelligence and Information Systems
• /
• v.22 no.1
• /
• pp.63-82
• /
• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Journal of Science Education
• /
• v.45 no.3
• /
• pp.292-303
• /
• 2021

This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.

• Journal of Sinology and China Studies
• /
• v.81
• /
• pp.161-197
• /
• 2019

This paper aims to find out how rhetorical the rhetoric effect is in the speeches of the winners and runners-ups in the final round of the fifth final title. The subjects of this paper are the speeches of the winners and runner-ups who won the 5th and 10th finalist finals of "I Am a Speaker", which aired on Beijing TV on March 6, 2019. These speeches have images as well as texts, so we will look at the rhetorical expressions in the text and the speech and gesture language of the speakers. In addition, photographs presented as background data on stage when the winner and the runner-up each speak will be included in the analysis. In this paper, we will apply the "Rhetorical Sensitivity Scale", which quantifies the ability of persuasion as a methodology, and sets up the evaluation items based on the traditional theory of rhetoric and then analyzes two speeches. The traditional theory of rhetoric can be divided into five areas and three persuasive elements. The five areas include idea, disposition, expression, memory, and action delivery. The three persuasion elements are Ethos, Logos, and Pathos. In order to pursue objectivity as much as possible, this paper will proceed with both text analysis with verbal expression and video analysis with field situations at the time of speech.

• Journal of Internet Computing and Services
• /
• v.23 no.5
• /
• pp.145-154
• /
• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.26 no.4
• /
• pp.283-304
• /
• 2015

The purpose of this study was to identify Web accessibility issues of healthcare websites of the Korean government and public agencies by evaluating these websites' accessibility in accordance with the Korean Web Contents Accessibility Guideline. This study conducted both automated and expert testing to assess the accessibility of a total of 27 health-related websites. The results of the assessment which was conducted in two stages indicated that institutions such as the National Hospital and National Rehabilitation Center demonstrated almost no Web accessibility error. In addition, the Korea Health Insurance Review and Assessment Service, the Ministry of Health and Welfare, the Health Services Agency, the Ministry of Food and Drug Safety, and the Korea Medical Dispute Mediation and Arbitration Agency attained very high web accessibility. However, the results of an expert evaluation highlighted that there were considerable errors in providing appropriate alternative text, which was not found in the automated test, and the color contrast of the text content did not comply with Web accessibility standard. Therefore, these websites did not support web accessibility for the sight-impaired. Furthermore, the present study found that it was difficult to deliver accurate information to users due to errors in the default language display and markup, and also, issues of skipping repeated content, content linearization, and compliance with keyboard use were considered as challenges that might arise for people with sight, cognitive and mobility impairments with respect to Web accessibility. It is the first study that evaluated accessibility of healthcare websites of the Korean government and public agencies based on the Korean Web Contents Accessibility Guideline. The present study made a contribution to research on Web accessibility by conducting expert testing, which provided a more complete assessment that identified the degree and specific issues of accessibility errors when compared to automated testing.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.26 no.4
• /
• pp.1025-1036
• /
• 2016

The conversion of the international standard web utilization HTML5 technology is being developed for improvement of the internet environment based on nonstandard technology like ActiveX. Hyper Text Markup Language 5 (HTML5) of basic programming language for creating a web page is designed to consider the security more than HTML4. However, the range of attacks increased and a variety of security threats generated from HTML4 environment inherited by new HTML5 API. In this paper, we focus on the script-based attack such as CSRF (Cross-Site Request Forgery), Cookie Sniffing, and HTML5 API such as CORS (Cross-Origin Resource Sharing), Geolocation API related with the infringement of the personal information. We reproduced the infringement cases actually and embodied a detection module of a Plug-in type diagnosed based on client. The scanner allows it to detect and respond to the vulnerability of HTML5 previously, thereby self-diagnosing the reliability of HTML5-based web applications or web pages. In a case of a new vulnerability, it also easy to enlarge by adding another detection module.