• Genomics & Informatics
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• v.18 no.2
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• pp.21.1-21.7
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• 2020

Scientific research is mostly published in English, regardless of the researcher's nationality. However, this growing practice impairs or hinders the comprehension of professionals who depend on the results of these studies to provide adequate care for their patients. We suggest that machine translation (MT) can be used as a way of providing useful translation for biomedical articles, even though the translation itself may not be fluent. To tackle possible mistranslation that can harm a patient, we resort to crowd-sourced validation of translations. We developed a prototype of MT validation and edition, where users can vote for that translation as valid, or suggest modifications (i.e., post-editing the MT). A glossary match system is also included, aiming at terminology consistency.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.301-309
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• 2009

This study focuses on event-driven social media (EDSM), which supports the production of unique cultural items of small groups by satisfying the conflicting desires of distinctiveness and assimilation that small groups possess. EDSM is a system which promotes the production of idioculture through small group interaction by using an actual event in which people participate in small groups. By setting up an EDSM system in a university festival in which 10,000 to 15,000 people gather in small groups, idioculture production was tested for approximately eight hours and a half. Interaction records gathered from the test, as well as focus group interview data garnered soon after were used to analyze usage patterns of EDSM, types of idiocultures produced, and resulting factors of user experience. Through this, considerations upon designing future EDSM were proposed.

• Journal of Information Technology Services
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• v.11 no.3
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• pp.227-240
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• 2012

Given the prevalence of internet and web 2.0, SNS(Social Network Service) market is growing rapidly. IT providers which focused marketing point on network hub have become to disseminate SNS mainly now. Many users are using the various functions of SNS to communicate each other or share the information. At this point, identifying the influencing factors to WOM(Word-Of-Mouth) of SNS is very important. In this paper, we aim to examine the effects of perceived variables on the WOM of SNS. In order to analyze the antecedents, we selected perceived factors such as perceived usefulness, perceived easiness, perceived enjoyment and perceived crowd. For statistical analysis, we surveyed real users of SNS. As a result, all antecedents of WOM showed significant influence and among the variables the perceived enjoyment has top standardized coefficient. In addition, perceived crowd has significant on perceived easiness, perceived enjoyment but not on perceived usefulness. The result of this research can be useful guidelines to increase SNS Market.

• Journal of information and communication convergence engineering
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• v.10 no.1
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• pp.40-44
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• 2012

Data mining, which is attracting public attention, is a process of drawing out knowledge from a large mass of data. The key technique in data mining is the ability to maximize the similarity in a group and minimize the similarity between groups. Since grouping in data mining deals with a large mass of data, it lessens the amount of time spent with the source data, and grouping techniques that shrink the quantity of the data form to which the algorithm is subjected are actively used. The current grouping algorithm is highly sensitive to static and reacts to local minima. The number of groups has to be stated depending on the initialization value. In this paper we propose a gene algorithm that automatically decides on the number of grouping algorithms. We will try to find the optimal group of the fittest function, and finally apply it to a data mining problem that deals with a large mass of data.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3323-3332
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• 2000

본 논문에서는 PML-트리라는 공간색인구조를 제안한다. PML-트리는 object distribution heuristics를 사용하여 공간 데이터 객체를 여러 개의 데이터 공간에 균일하게 배치함으로써 질의처리 속도를 향상시킨다. 두 가지의 object distribution heuristics(absolute crowd index와 relative crowd index)가 제안이 된다. PML-트리는 공간 객체를 분배함으로써 R+-트리의 말단 노드 내에 존재하는 데이터의 중복을 제거하면서, R-트리의 단점인 색인 사각형들 사이에 중첩을 허용치 않는다. PML-트리의 성능은 여러 타입의 테스트 데이터를 사용하여 MXR-트리와 비교된다. PML-트리는 MXR-트리에 비해 높은 공간활용도와 빠른 질의 반응시간을 보임으로써 공간 데이터베이스를 위한 효율적인 색인구조로 사용이 될 것으로 기대된다.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.49-55
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• 2017

Recently, for safety of people, there are proposed so many technologies which detect density of people at the specific place or space. The representative technology for crowd density estimation was using image analysis method from CCTV images. However, this method had a weakness which could not be used and which's accuracy was lower at the dark or smog space. Therefore, in this paper, to solve this problem, we proposed a user density estimation system at closed space using high frequency and smart device. The system send inaudible high frequencies to smart devices and it count the smart devices which detect the high frequencies on the space. We tested real-time user density with the proposed system and ten smart devices to evaluate performance. According to the testing results, we confirmed that the proposed system's accuracy was 95% and it was very useful. Thus, because the proposed system could estimate about user density at specific space exactly, it could be useful technology for safety of people and measurement of space use state at indoor space.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.252-253
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• 2015

군중의 이상행동을 검출하는 것은 군중 모니터링, 보안 및 CRM 시스템의 관점에서 중요한 요소 중의 하나이다. 기존의 방법은 대다수가 옵티컬플로우를 기반으로한 검출방법으로 객체가 움직이지 않는 경우에는 객체로 인식할 수 없는 문제점이 생긴다. 또한, 많은 데이터량을 처리하기 때문에 실시간성이 보장되지 않는다는 단점이 있다. 이를 극복하기 위해서, 본 논문에서는 특징점 맵 보정과 분포분석을 통한 군중의 밀집과 대피하는 현상을 검출하는 방법을 제안한다. 먼저, 군중에서 옵티컬플로우 기반으로 움직이는 FAST 특징점을 추출하고 추출된 특징점의 분포에따라 특징점맵을 복원한다. 복원된 특징점 맵과 특징점의 분포에 기반하여 군중의 이상정도를 결정하게 된다. PETS2009 데이터베이스를 사용하여 결과를 측정하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.703-706
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• 2002

군중잡음(crowd noise)이 발생하는 환경에서 음성 통화 및 화자 인식을 할 때에는 음성에 파열음이나 마찰음과 같은 유색잡음(colored noise)이 부가되어 원래 음성이 왜곡된다. 이와 같이 왜곡된 음성 신호를 처리할 때에는 군중잡음을 제거하는 과정이 반드시 필요하다. 본 논문에서는 전형적인 군중잡음의 모델인 쇼핑 센터 잡음을 분석하고, 그 결과를 이용하여 음성 신호처리시에 효과적으로 군중잡음만을 제거할 수 있는 모델을 제안한다. 제안된 모델은 시간 영역에서 마찰음과 파열음을 제거하고. DSI(Digital Speech Interpolation)를 이용하여 침묵 구간을 검출한다. 이때 주파수 영역에서는 이 침묵구간을 잡음으로 간주하여 이를 이용한 스펙트럼 차감법(spectral subtraction)으로 음성 신호에 부가된 군중 잡음을 제거하는 과정을 거친다.

• The Journal of Korea Robotics Society
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• v.10 no.2
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• pp.90-95
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• 2015

The main goal of e-learning systems is just-in-time knowledge acquisition. Rule-based e-learning systems, however, suffer from the mesa effect and the cold start problem, which both result in low user acceptance. E-learning systems suffer a further drawback in rendering the implementation of a natural interface in humanoids difficult. To address these concerns, even exceptional questions of the learner must be answerable. This paper aims to propose a method that can understand the learner's verbal cues and then intelligently explore additional domains of knowledge based on crowd data sources such as Wikipedia and social media, ultimately allowing for better answers in real-time. A prototype system was implemented using the NAO platform.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.3
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• pp.156-162
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• 2013

Social manufacturing architecture is based on information delivery through social media and SNS, PLM and social platform, crowd source and knowledge base on whole phase of product life cycle. Although advanced social manufacturing issues are rising globally, its technology emerging into domestic industry is likely to be slow. We focused to review technological changes and R&D trend, patent issues, and then suggest assignments and advices to be practiced for social manufacturing modeling.