• Review of KIISC
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• v.26 no.4
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• pp.41-46
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• 2016

전통적으로 바이오인식기술은 출입국심사(전자여권, 승무원 승객 신원확인), 출입통제(도어락, 출입통제 근태관리), 행정(무인민원발급, 전자조달), 사회복지(미아찾기, 복지기금관리), 의료(원격의료, 의료진 환자 신원확인), 정보통신(휴대폰 PC 인터넷 인증), 금융(온라인 뱅킹, ATM 현금인출) 등 다방면에서 폭넓게 보급되어 실생활에서 널리 활용되고 있다. [그림1]은 신체적 특징(Physiological biometrics)과 행동적 특징(Behavioral biometrics)을 이용한 사용자 인증기술인 바이오인식기술의 유형과 함께 각 기술별 보안취약점(괄호 안 빨강색글자)을 나타내고 있다. 최근 들어, 모바일 지급결제서비스 ATM 인출기 인터넷전문은행 등과 같은 핀테크 분야에서 비대면 인증기술로 바이오인식기술이 각광을 받기 시작했다. 한편, 가짜지문 등 기존의 신체적 특징을 이용한 바이오인식기술의 위변조 위협에 대한 우려 존재함에 따라 뇌파 심전도 근전도 맥박 등 살아있는 사람의 행동적(신체의 기능적) 특징을 이용한 생체신호를 이용하여 비대면 인증기술로서 활용하기 위하여 주요 선진국에서 차세대 바이오인식 기술개발이 가속화되고 있는 추세이다.[1] 또한, 이러한 생체신호는 최근에 삼성전자, LG전자, 애플 등에서 스마트워치를 통해 심장박동수를 측정하고 스마트폰을 통하여 모바일 지급결제, 헬스케어 등과 같은 IoT 모바일 융복합 응용서비스에 활용될 전망이다. 본고에서는 뇌파 심전도(심박수)와 같은 생체신호를 측정하는 스마트워치 밴드형 의복형 또는 패치형태의 웨어러블 디바이스와 같은 생체신호센서, 생체신호 인증기술 및 관련표준화 동향을 고찰해 보기로 한다. 국내외 관련기술과 표준화 동향을 면밀히 분석하여 지난 2015년 5월29일에 발족한 국내외 전문가그룹인 KISA"모바일 생체신호 인증기술 표준연구회"(이하 KISA 표준연구회)가 구심점이 되어 한국형 생체신호를 이용한 차세대 텔레바이오인식기술에 대한 연구개발과 국내외 표준화 추진에 박차를 가할 계획이다.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.278-291
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• 2016

This study examined research trends via network analyses of keywords appeared in academic research articles about news reports in South Korea during the last 10 years from 2006 to 2015. Keyword network analyses of 4410 keywords from 1108 articles suggested that framing, agenda setting, third-person effect, selective exposure, and uses and gratification were main theories but most studies used framing theory. Research areas included news reports on politics, economics, science, world issues, or tour. However, research on news reports covering culture, sports or daily life were not identified. In terms of media, research on both traditional and emerging media were ample. Research on broadcasting new, online news, and social media were frequently observed.

• The Optical Journal
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• s.120
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• pp.39-44
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• 2009

한국광학기기협회가 격월간으로 발행하는 광학세계가 창간 20주년을 맞아 독자 대상의 설문조사를 실시했다. 1989년 4월 창간되어 2009년 3월로 통권 120호가 되는 광학세계는 그간 광학분야 전문잡지로 자리매김을 해왔다. 20년 동안 내용적인 변화는 물론 외형적인 변화도 있었다. 초기 $4{\times}6$배판에서 $5{\times}7$국배판으로 변화됐으며 협회 홈페이지를 통해 온라인상에서도 과월호를 볼 수 있게 되었다. 설문분석 결과 응답자들은 대체로 현재의 편집스타일과 기획에 만족하고 있다고 답했다. 대부분 광학세계를 통해 산업 및 업계 동향 파악의 활용이 가장 많은 것으로 나타났고 더욱 다양한 산업분야의 기술 및 시장 동향 소개를 바라는 요구가 있었다. 광학세계는 이와 같은 독자들의 생생한 평가와 제안을 수렴하여 앞으로 더욱 독자들의 요구를 만족시켜주는 광학전문잡지로 거듭나기 위해 노력할 것이다.

• Journal of Korea Game Society
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• v.5 no.2
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• pp.29-36
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• 2005

Determining the price of a newly developed game product is a substantial matter affecting many aspects of corporate management. An appropriate pricing based on the proper data encourages consumers to purchase products repeatedly Yet presently most game companies prefer to set a price according to the cost including developing expense, advertising expense and law materials. As a result that price does not reveal the rue value of the product, many corporations face the demerits in the corporate management including the low sales, the loss of client and the poor promotion. This study has emphasis on the evaluating the price according to the consumer view rather than either corporate or industrial view. The price preference research analysis shows that Korean gamers prefer the price ranging around 30 thousand won in the simulation game, RPG game, and arcade game. In the online game, around 20 thousand won is the preferred price. This difference explains well the features of each game categories.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.207-216
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• 2018

In Korea, there has been no national research on the use of antipsychotics for people with intellectual disabilities(I.D); therefore, it is difficult to identify the problems or to find solutions for problems in using antipsychotics. So, the purpose of this study analyze research findings on the use of antipsychotics for people with I.D in Japan. This research method compared and analyzed the results of research published in the journal J-STAGE and Medical Online and studied a cohort results using data. The results of the analysis are as follows. First, many antipsychotic drugs are prescribed to people with I.D, but it is difficult to accurately assess the effectiveness of the treatments. Second, it is not easy to detect side effects. Third, the potential side effects of drug interactions have been raised. The results was emphasized the need of research that accurately evaluate the drugs in survey of actual situation to ensure more safe use of antipsychotics to peoples with I.D in Korea.

• Journal of Platform Technology
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• v.10 no.3
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• pp.51-59
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• 2022

Machine learning, which has recently innovatively developed, has become an important technology that can solve various optimization problems. In this paper, we introduce the latest research papers that solve the problem of channel sharing in heterogeneous networks using machine learning, analyze the characteristics of mainstream approaches, and present a guide to future research directions. Existing studies have generally adopted Q-learning since it supports fast learning both on online and offline environment. On the contrary, conventional studies have either not considered various coexistence scenarios or lacked consideration for the location of machine learning controllers that can have a significant impact on network performance. One of the powerful ways to overcome these disadvantages is to selectively use a machine learning algorithm according to changes in network environment based on the logical network architecture for machine learning proposed by ITU.

• Convergence Security Journal
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• v.21 no.2
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• pp.19-28
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• 2021

Korea is promoting a digital new deal policy for the digital transformation and innovation accelerating of the industry. However, because of the strict existing data-related laws, there are still restrictions on the industry's use of data for the digital new deal policy. In order to solve this issue, a revised bill of the Data 3 Act has been proposed, but there is still insufficient discussion on how it will actually affect the activation of data use in the industry. Therefore, this study aims to analyze the perception of public opinion on the Data 3 Act and the implications of the revision of the Data 3 Act. To this end, the revision of the Data 3 Act and related research trends were analyzed, and the perception of the Data 3 Act was analyzed using a big data analysis technique. According to the analysis results, while promoting the vitalization of the data industry in line with the purpose of the revision, the Data 3 Act has a concern that it focuses on specific industries. The results of this study are meaningful in providing implications for future improvement plans by analyzing online perceptions of the industrial impact of the Data 3 Act in the early stages of implementation through big data analysis.

• Journal of KIISE
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• v.44 no.12
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• pp.1258-1268
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• 2017

Capturing real-time daily information on food prices is invaluable to help policymakers and development organizations address food security problems and improve public welfare. This study analyses the possible use of large-scale online data, available due to growing Internet connectivity in developing countries, to provide updates on food security landscape. We conduct a case study of Indonesia to develop a time-series prediction model that nowcasts daily food prices for four types of food commodities that are essential in the region: beef, chicken, onion and chilli. By using Twitter price quotes, we demonstrate the capability of social data to function as an affordable and efficient proxy for traditional offline price statistics.

• Electronics and Telecommunications Trends
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• v.20 no.1 s.91
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• pp.139-146
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• 2005

폭발적인 정보의 흐름 속에 놓여 있는 지식정보화 시대에서는 필요한 정보를 선택하고 가공하여 새로운지식의 창조, 전달 및 확대 재생산 할 수 있는 능력이 요구되고 있다. 지식정보화 시대가 필요로 하는 창의적 인재 육성을 위한 새로운 교육 형태와 패러다임으로 e-러닝이 유력한 솔루션으로 부각되고 있다.e-러닝은 교수자 중심의 일방향 교육이 아닌 학습자가 시간과 장소에 구애받지 않고 필요한 학습을 하는 양방향 교육 방식이나, 현재까지는 학습 콘텐츠의 단순 반복 학습에 그치고 있어 기존 교실 수업 방식에 비해 학습효율이 떨어지는 점이 이 분야 발전의 장애요소가 되고 있다. 이에 대한 해결책으로 온라인상에서 학습 과제를 여러 명의 학생들이 상호 의존하여 공동으로 해결함으로써 학습 목표를 달성하는 형태의 협력 학습에 대한 연구가 활발히 진행되고 있다. e-러닝 협력학습에는 단순히 학생들을 그룹화하여 함께 학습하도록 하는 것은 교육 효과면 에서 비효율적일 수 있으며, 학생들의 자발적인 참여와 협력을 유도할 수 있는 교수모형을 적용하여야 하며, 개인의 책임감을 근간으로 한 상호 의존적 과제 해결 활동이 이루어져야 한다. 본 고에서는 협력 e-러닝 학습을 위한 연구사례와 기술 동향들에 대해 살펴본다.