• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1013-1021
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• 2014

For efficient investments of government budgets, It is important to analyze the similarities of R&D projects. So, existing studies have proposed a techniques for analyzing similarities using keywords or segments. However, the techniques have low accuracy. We propose a technique for similarities of projects using patent information. To achieve our goal, we suggest three metrics that are based some mathematic theories; set theory and probability theory. In order to validate our technique, we perform case studies that have 156 R&D projects and 160,218 patent informations.

• Journal of Digital Contents Society
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• v.12 no.4
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• pp.457-465
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• 2011

The annual R&D investment in Korea increased by an average of 12.2percent during the last 5 years. Therefore, prevention of duplicate projects being performed became an important factor in promoting the efficiency of R&D investment and the originality of R&D projects. On measuring the similarity of projects, the measurement model used to estimate the accuracy of the similarity is crucial. In this paper, we propose an advanced measurement model on checking the similarity of R&D projects for promoting the efficiency of R&D investment. The proposed model is made up of the following steps for the model measurement, sampling and analyzing. During the sampling step, we append the abstract of R&D reports on the search engine based on document vector. We then measure the similarity on projects to use research title network which is consists of the compound keyword and the weight of items on during the analysis. The proposed method improved the accuracy for measuring the similarity of projects by an average of 0.19 over the existing search engine and by 9.25 over the simple keyword search on R&D projects. On searching the similarity with the appending conditions and high sampling, it improved the accuracy of measuring the similarity of R&D projects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.329-331
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• 2014

The analysis of the similarities and redundancies among R&D projects is important for the efficient investment of government budgets. When government R&D projects are planned, the redundancies of research tasks are examined by institutions specializing in research management, relevant offices and departments, and the government to prevent redundant funding. However, as existing similarity analyses depend on methods wherein new task proposals and existing R&D project proposals are compared and looked up based on keywords. This results in vulnerability wherein similarity cannot be accurately measured in the event of partial modifications of the task name or technical substitutions. This study aims to use patent information as characteristics by which R&D project documents can be identified. The patent data used is based on materials officially published by the government's R&D patent trend survey project (http://ipas.rndip.re.kr). The study aims to propose a method by which patent information can be used to analyze the similarity and redundancy among R&D projects when new projects are entered. For this purpose, a similarity measurement model based on set theory and probability theory is presented. The presented measurement model is implemented into an actual system to identify redundant documents, and calculate and show their similarity.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.54-62
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• 2009

To avoid the redundant investment on the project selection process, it is necessary to check whether the submitted research topics have been proposed or carried out at other institutions before. This is possible through the search engines adopted by the keyword matching algorithm which is based on boolean techniques in national-sized research results database. Even though the accuracy and speed of information retrieval have been improved, they still have fundamental limits caused by keyword matching. This paper examines implemented TFIDF-based algorithm, and shows an experiment in search engine to retrieve and give the order of priority for similar and redundant documents compared with research proposals, In addition to generic TFIDF algorithm, feature weighting and K-Nearest Neighbors classification methods are implemented in this algorithm. The documents are extracted from NDSL(National Digital Science Library) web directory service to test the algorithm.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.82-88
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• 2004

Comparing many programs like programming assignments one by one requires many costs. Moreover, if the checker would evaluate or grade assignments, much more time will be required. Even through the checker invest much time, fairness is not always guaranteed. These problems can be solved easily by grouping similar programs. So, programs after grouping can be easily evaluated and graded. In this paper, we propose and implement algerian performing grouping by similarity on many programs. The grouping algorithm evaluates similarity using algorithm proposed in (9), and performs a grouping following high similarity order. By using this grouping algorithm, the number of comparison among N programs can be reduced from N-1 times to N(N-1)/2 times. In the part of experiment and evaluation of this paper, we actually showed evaluation result by similarity using randomly 10 programming assignments at the university.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.05a
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• pp.559-570
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• 2017

우리나라는 과거부터 현재까지 미래 성장동력 육성을 목표로 정부주도하에 국가 R&D 투자를 점진적으로 늘려왔다. 그 결과, 최근에는 GDP 대비 연구개발비 비중이 세계 최고 수준에 이르렀다. 이렇게 연구개발 예산의 양적인 확대와 함께 연구개발 예산의 효율적 활용은 더욱 중요한 과학기술 분야의 정책적 이슈로 부각되고 있다. 연구개발 예산의 효율적인 집행을 위해서는 R&D 사업의 유사 중복성의 검토가 필수적이지만, 대부분의 유사 중복성 검토는 전문가의 직관적인 판단에 근거하여 이루어져왔다. 하지만, 전문가의 직관에만 의지한 판단은 때로는 불명확하거나 잘못된 결과를 가져올 수도 있다. 따라서, 본 연구에서는 네트워크 분석을 통해 정부 R&D 사업의 유사 중복성을 체계적으로 검토하기 위한 데이터기반의 방법론을 제안하여 전문가의 직관에 의한 유사 중복성 검토를 보완할 수 있는 가능성을 모색하고자 한다. 먼저, 본 연구에서는 정부 R&D사업 유사영역의 전체적인 구조 및 형태와 국가과학기술연구회 소속 25개 정부출연연구기관 R&D사업의 유사영역의 전반적인 형태를 시각화하여 유사영역을 파악하고 직관적인 판단과 선택을 할 수 있는 의사결정 정보를 제공하는데 초점을 두었다. 이를 위해, NTIS의 2015년 데이터를 사용하여 과제 키워드 기반으로 동시단어출현 분석을 수행하였다. 본 분석을 통해 25개 기관의 세부적인 유사연구영역 형태를 제시하였으며, 국내의 과학기술정책적 또는 과학기술학적인 현상들을 시각화하였다. 그 결과, 국내 출연연 R&D사업이 기관별 고유영역이 확고히 보이는 Mode 1적인 형태와 사회경제적인 맥락과 필요 및 유망성을 따르고, 다학제적, 적용중심적이며 과제별로 다양한 과제수행기관들이 과제들을 동시에 수행하는 Mode 2적인 형태가 출연연의 R&D사업 내에 공존하고 있음을 확인하였다.

• Science of Emotion and Sensibility
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• v.14 no.1
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• pp.137-146
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• 2011

The purpose of the present study was to investigate personality type with evoked potentials. Teenage students(121 males, 69 females) tested Myers Briggs Type Indicator and raven like discrimination task by evoked potential. Raven like discrimination tasks were made of low, medium and high levels. Conclusively extraversion and introversion while accomplishing the raven like discrimination tasks, showed the significant difference between two groups in the power of concentration. M-Beta(middle beta), Gamma and H-Beta(high beta) were also appeared significant differences between two groups. The sensing and intuition type partially appeared the different tendency of two groups while accomplishing easy and medium of difficulty tasks. Thinking and Feeling type while accomplishing raven like discrimination tasks, showed difference of the concentration power and H-Beta at Fp1. But judgment and perception type did not appear the difference between two groups while accomplishing raven like discrimination tasks of low, medium, and high. These results implied that the personality type can be affected brain wave by evoked potentials.

• Korean Journal of Cognitive Science
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• v.23 no.2
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• pp.225-248
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• 2012

The summed-similarity model of visual short-term recognition proposes that the estimated amount of summed similarity between remembered items and a recognition probe determines recognition judgement decision (Kahan & Sekuler, 2002). This study examined the effect of a task-irrelevant location change on the recognition decision against two remembered Gabor gratings differing in their spatial frequencies. On each trial in Experiment, participants reported if two gratings displayed across the visual fields are the same or not as the probe grating displayed after about a second of memory delay. The probe grating would be the same as or different from the memory items (lure) by 1 or 4 JND units. The location of the probe would also vary randomly across the left and right visual field with respect to the location of the corresponding memory item. The participants were instructed to perform their recognition task exclusively to the spatial frequencies of the memory items and the probe while ignoring the potential location change of the probe. The results showed that false-recognition rates of the lure probe increased as the summed similarity between the memory items and the probe increased. The rates also further increased in the condition where the probe location was different from the location of the corresponding memory item compared to the condition where the probe location was the same. The increased false-recognition rates indicate that information stored into visual short-term memory is represented as a form of well-bound visual features rather than independent features.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.317-324
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• 2012

Recently, coordination task of similarity between national R&D programs is emphasized on view from the R&D investment efficiency. But the previous similarity search method like text-based similarity search which using keyword of R&D projects has reached the limit due to deviation of document's quality. For the solve the limitations of text-based similarity search using the keyword extraction, in this study, utilization of R&D project's technical classification will be discussed as a new similarity search method when analyzed of similarity between national R&D programs. To this end, extracts the Science and Technology Standard Classification of R & D projects which are collected when national R&D Survey & analysis, and creates peculiar vector model of each R&D programs. Verify a reliability of this study by calculate the cosine-based and Euclidean distance-based similarity and compare with calculated the text-based similarity.

• Phonetics and Speech Sciences
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• v.12 no.1
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• pp.11-17
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• 2020

Non-tonal language speakers may have difficulty learning second language lexical tones. In the present study, we explored this issue with Korean-speaking learners of Mandarin Chinese (i.e., non-tonal first language speakers) by examining their perception and production of Mandarin lexical tones. In the perception experiment, the Korean learners were asked to listen to the tone of each stimulus and assign it to one of four Mandarin lexical tones using the response keys; in the production experiment, the learners provided speech production data for the lexical tones and then their productions were identified by native listeners of Mandarin Chinese. Our results showed that the Korean learners of Mandarin Chinese had difficulty in perceptually distinguishing Tone 2 and Tone 3, with the most frequent production error being the mispronunciation of Tone 3 as Tone 2. We also investigated whether unfamiliar non-native phonemes (i.e., Chinese phonemes) that do not exist in the native language phonemic inventory (i.e., Korean) may hinder the processing of the non-native lexical tones. We found no evidence for such effects, neither for the perception nor for the production of the tones.