• Journal of Distribution Science
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• v.13 no.4
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• pp.5-8
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• 2015

Purpose - The purpose of this paper is to review, analyze, and learn from the most recent cases of plagiarism and to identify and promote ethical practices in research and publication. Research design, data, and methodology - This is a case study, an analytical approach, which focuses on analyzing the most recent cases of plagiarism to identify ethical issues and concerns in journal publication practices. Results - Despite the availability of many software and web-based applications and programs to detect plagiarism, there is no universal or perfect plagiarism detection application available to ease the editorial responsibility. Lack of understanding the concept and ignorance of plagiarism were the main reasons for the cases of plagiarism. Conclusions - Some of the plagiarism cases reveal a lack of knowledge in proper application of in-text citations and references, including quoting, requiting, paraphrasing, and citing sources, etc. Furthermore, the need for recognizing and considering the distorted and falsified primary and secondary research data as plagiarism is essential to enhance ethical practices in journal publication.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.40-43
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• 2009

최근 모바일 영상기반 응용 분야에 관한 연구가 활발히 진행되고 있으며 모바일기기로 촬영된 영상에서 문자정보를 추출하고자 하는 많은 연구도 진행되고 있다. 자연이미지로부터 문자정보를 추출을 위한 전단계로 문자영역 검출이 필수적이다. 본 연구는 문자영역의 지역적 에지 및 연결요소 특징을 고려하여 조명 및 복잡한 배경에서도 문자영역을 검출하는 방법을 제안한다. 에지 검출은 캐니-에지 검출기로 추출하고, RGB 컬러분포 패턴을 분석하여 컬러 양자화를 함으로서 연결성분을 추출한다. 각각 추출된 에지 및 연결성분으로부터 문자후보 영역을 검출하고, 각각의 결과를 결합하여 최종적인 문자 후보 영역을 검출하고, 문자 후보 영역에 대한 검증을 수행함으로서 최종적인 문자영역을 검출한다. 제안한 방법은 다양한 환경에서 얻어진 자연이미지를 대상으로 실험한 결과, 에지 및 연결성분의 두 가지 특징을 결합함으로서 자연이미지에 존재하는 다양한 형태의 문자영역을 효과적으로 검출하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.228-231
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• 2011

최근 표절에 대한 사회적 관심이 꾸준히 높아지고 있는 가운데, 기계적으로 유사한 문서를 탐색하는 방법에 대한 많은 연구가 이루어지고 있다. 이 중 생물정보학에서 유전자 서열을 분석하기 위해 사용되는 '지역 정렬(local alignment)' 기법은 문서 간 유사 영역을 탐색하는 데에 유용하다. 한편 한글에는 조사가 존재하는데, 이 때문에 한글 문장은 각 품사의 순서에 큰 영향을 받지 않는다. 이러한 한글의 특성을 이용해 기존 문서의 어순만 바꾼 문장을 생성할 경우, 지역 정렬을 이용한 탐색 방법으로는 이를 찾아내기 힘들다. 본 논문에서는 한글의 특성을 고려하여 어순과 관계없이 해당 영역의 유사성을 찾아내는 새로운 한글 유사 문서 탐색 방법을 제시한다. 이를 위하여, 성분 정렬(composition alignment) 기법을 적용한다. 성분 정렬 기법은 생물학에서 생물의 진화 과정이나 돌연변이 DNA 등 서열의 순서가 일부 뒤바뀌는 것을 허용하면서 유사한 시퀀스를 찾는 기법으로 기존의 방법보다 더욱 유연하고 민감한 방법이라 할 수 있다. 이를 적용하여 한글 문서를 탐색한 결과, 일반적인 문장 및 거의 동일한 문장 간의 유사도 점수는 큰 변화가 없었으나, 어순을 바꾼 문장의 경우 기존의 방법보다 평균 35.34% 가량 민감하게 탐색할 수 있었다. 추후 한글에 대한 초성 추출 및 성분 정렬 방법을 응용하여 다단계 구조의 유사 문서 탐색 방법에 대해 연구할 계획이다.

• International Journal of Knowledge Content Development & Technology
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• v.3 no.1
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• pp.81-95
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• 2013

Through a series of precise text handling processes, including automatic extraction of information from documents with knowledge from various fields, recognition of entity names, detection of core topics, analysis of the relations between the extracted information and topics, and automatic inference of new knowledge, the most efficient knowledge base of the relevant field is created, and plans to apply these to the information knowledge management and service are the core requirements necessary for intellectualization of information. In this paper, the knowledge base, which is a necessary core resource and comprehensive technology for intellectualization of science and technology information, is described and the usability of academic information services using it is evaluated. The knowledge base proposed in this article is an amalgamation of information expression and knowledge storage, composed of identifying code systems from terms to documents, by integrating terminologies, word intelligent networks, topic networks, classification systems, and authority data.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.3
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• pp.257-266
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• 2020

It is very important to share tactical information such as video, images, and text messages among soldiers for situational awareness. Under the wireless environment of the battlefield, the available bandwidth varies dynamically and is insufficient to transmit high quality images, so it is necessary to minimize the distortion of the area of interests such as targets. A natural operating method for soldiers is also required considering the difficulty in handling while moving. In this paper, we propose a natural ROI(region of interest) setting and image compression method for effective image sharing among soldiers. We verify the proposed method through prototype system design and implementation of eye gaze detection and ROI-based image compression.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.377-378
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• 2018

This paper introduce the improvement of the pupil motion recognition algorithm in the previously reported "Eye-Motion Communication System using FPGA and OpenCV". It is a system for generalized paralysis and Lou Gehrig patients who can not move their body naturally, recognizing the pupil's motion and selecting the text in the FPGA in real time. In this paper, we improve the speed of motion recognition by minimizing the operation of eye detection function based on the user being general paralysis patient.

• Journal of the Korea Society of Computer and Information
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• v.22 no.1
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• pp.15-21
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• 2017

In this paper, we present a solution to the problems caused by using only text - based information as an index element when a commercialized missing person indexing system indexes missing persons registered in the database. The existing system could not be used for the missing persons inquiry because it could not formalize the image of the missing person registered together when registering the missing person. To solve these problems, we propose a method to extract the similarity of images by using OpenCV image processing and TensorFlow deep - running image processing, and to process images of missing persons to process them into meaningful information. In order to verify the indexing method used in this paper, we constructed a Web server that operates to provide the information that is most likely to be needed to users first, using the image provided in the non - regular environment of the same subject as the search element.

• ETRI Journal
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• v.38 no.1
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• pp.174-184
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• 2016

Information identification with image data by means of low-level visual features has evolved as a challenging research domain. Conventional text-based mapping of image data has been gradually replaced by content-based techniques of image identification. Feature extraction from image content plays a crucial role in facilitating content-based detection processes. In this paper, the authors have proposed four different techniques for multiview feature extraction from images. The efficiency of extracted feature vectors for content-based image classification and retrieval is evaluated by means of fusion-based and data standardization-based techniques. It is observed that the latter surpasses the former. The proposed methods outclass state-of-the-art techniques for content-based image identification and show an average increase in precision of 17.71% and 22.78% for classification and retrieval, respectively. Three public datasets - Wang; Oliva and Torralba (OT-Scene); and Corel - are used for verification purposes. The research findings are statistically validated by conducting a paired t-test.

• Food Science and Industry
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• v.54 no.3
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• pp.160-170
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• 2021

A recent advance in communication technologies accelerates the spread of food safety issues once presented by the news media. To respond to those safety issues and take steps in a timely manner, automatically detecting related information from the news data matters. This work presents an AI-based system that detects risk information within a food-related news article. Experts in food safety areas participated in labeling risk information from the food-related news articles; we acquired 43,527 articles in which food names and risk information are marked as labels. Based on the news document, our system automatically detects food names and risk information by analyzing similarities between words within a text by leveraging learned word embedding vectors. Our AI-based system shows higher detection accuracy scores over a non-AI rule-based system: achieving an absolute gain of +32.94% in F1 for the food name category and +41.53% for the risk information category.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.10
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• pp.215-225
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• 2022

This study investigates employees' online reviews, conducts in-depth text topic mining, effectively summarizes the dimensions of employer brand value, and seeks effective ways to build employer brands from a multi-dimensional perspective. This study employs samples of employer reviews, filter keywords according to word frequency-inverse document frequency, builds a review network containing the same keywords, explore the community and summarize the theme dimensions. Simultaneously, it makes a dynamic comparison and analysis of the employer brand value dimension of different industries and enterprises. The study shows that the community exploration theme can be summarized into 11 dimensions of employer brand value, and the dimensions of employer brand value are significantly different across industries and among different enterprises within the industry. The attention to the employer brand value dimension has a significant time change. Various industries pay increasing attention to the dimension of work intensity and career development, while employers pay steady attention to the dimension of welfare benefits. The findings of this study suggest that seeking the heterogeneity of employer brand resources from the multi-dimensional differences and changes is an effective way to improve the competitiveness of enterprises in the human capital market.