• Journal of Digital Convergence
• /
• v.19 no.10
• /
• pp.221-227
• /
• 2021

In this paper, we conducted word-to-word similarity analysis of standardized datasets collected through web crawling for 10,000 Vertical Noise Mouses using Word2Vec, and made 92 students of computer engineering use the products presented for 5 days, and conducted self-report questionnaire analysis. The questionnaire analysis was conducted by collecting the words in the form of a narrative form and presenting and selecting the top 50 words extracted from the word frequency analysis and the word similarity analysis. As a result of analyzing the similarity of e-commerce user's product review, pain (.985) and design (.963) were analyzed as the advantages of click keywords, and the disadvantages were vertical (.985) and adaptation (.948). In the descriptive frequency analysis, the most frequently selected items were Vertical (123) and Pain (118). Vertical (83) and Pain (75) were selected for the advantages of selecting the long/demerit similar words, and adaptation (89) and buttons (72) were selected for the disadvantages. Therefore, it is expected that decision makers and product planners of medium and small enterprises can be used as important data for decision making when the method applied in this study is reflected as a new product development process and a review strategy of existing products.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2024.01a
• /
• pp.55-58
• /
• 2024

최근 각 기업의 AI 면접시스템 도입이 증가하고 있으며, AI 면접에 대한 실효성 논란 또한 많은 상황이다. 본 논문에서는 AI 면접 과정에서 지원자를 평가하는 방식을 시각, 음성, 자연어처리 3영역에서 구현함으로써, 면접 지원자를 다방면으로 분석 방법론의 적절성에 대해 평가하고자 한다. 첫째, 시각적 측면에서, 면접 지원자의 감정을 인식하기 위해, 합성곱 신경망(CNN) 기법을 활용해, 지원자 얼굴에서 6가지 감정을 인식했으며, 지원자가 카메라를 응시하고 있는지를 시계열로 도출하였다. 이를 통해 지원자가 면접에 임하는 태도와 특히 얼굴에서 드러나는 감정을 분석하는 데 주력했다. 둘째, 시각적 효과만으로 면접자의 태도를 파악하는 데 한계가 있기 때문에, 지원자 음성을 주파수로 환산해 특성을 추출하고, Bidirectional LSTM을 활용해 훈련해 지원자 음성에 따른 6가지 감정을 추출했다. 셋째, 지원자의 발언 내용과 관련해 맥락적 의미를 파악해 지원자의 상태를 파악하기 위해, 음성을 STT(Speech-to-Text) 기법을 이용하여 텍스트로 변환하고, 사용 단어의 빈도를 분석하여 지원자의 언어 습관을 파악했다. 이와 함께, 지원자의 발언 내용에 대한 감정 분석을 위해 KoBERT 모델을 적용했으며, 지원자의 성격, 태도, 직무에 대한 이해도를 파악하기 위해 객관적인 평가지표를 제작하여 적용했다. 논문의 분석 결과 AI 면접의 다면적 평가시스템의 적절성과 관련해, 시각화 부분에서는 상당 부분 정확도가 객관적으로 입증되었다고 판단된다. 음성에서 감정분석 분야는 면접자가 제한된 시간에 모든 유형의 감정을 드러내지 않고, 또 유사한 톤의 말이 진행되다 보니 특정 감정을 나타내는 주파수가 다소 집중되는 현상이 나타났다. 마지막으로 자연어처리 영역은 면접자의 발언에서 나오는 말투, 특정 단어의 빈도수를 넘어, 전체적인 맥락과 느낌을 이해할 수 있는 자연어처리 분석모델의 필요성이 더욱 커졌음을 판단했다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2011.11a
• /
• pp.154-157
• /
• 2011

인간의 동작 인식은 가상 현실 시스템 및 게임 등에 적용할 수 있는 컴퓨터 비전 분야의 요소 기술 중 하나로써, 최근까지 그 연구과 활발히 진행되고 있다. 본 논문에서는 빠르고 정확한 동작 인식을 위해, 실루엣과 모션 특징이 결합된 방법을 제안한다. 제안하는 방법은 전역 특징을 이용한 후보 동작 선정 및 지역 특징을 이용한 검증 2 단계로 구성된다. 전역 특징은 Motion History Image의 Hu 모멘트를 이용해 계산되며, 후보 동작의 선정은 이들의 통계치를 이용해 결정한다. 한정된 후보 동작들 중 입력 동작을 정확히 인식하기 위해, 공간 및 방향성 비닝 기법으로 추출된 광류와 실루엣 특징을 지역 특징으로 이용한다. 최종 인식 결과는 Hu 모멘트 통계치와의 유사도 및 지역 특징의 학습을 통해 생성된 Support Vector Machine의 결과를 고려하여 결정된다. 제안하는 방법의 성능을 평가하기 위해, 실세계에서 사용 빈도가 높으며 동작의 변화가 큰 13 개의 제스처를 선정하여 데이터 셋을 구성하였다. 실험 결과 제안하는 방법의 연산 시간은 50 ms, 인식 정확도는 95%임을 확인하였다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.64-64
• /
• 2022

이상기후로 인해 돌발적이고 국지적인 호우 발생의 빈도가 증가하게 되면서 짧은 선행시간(~3 시간) 범위에서 수치예보보다 높은 정확도를 갖는 초단시간 강우예측자료가 돌발홍수 및 도시홍수의 조기경보를 위해 유용하게 사용되고 있다. 일반적으로 초단시간 강우예측 정보는 레이더를 활용하여 외삽 및 이동벡터 기반의 예측기법으로 산정한다. 최근에는 장기간 레이더 관측자료의 확보와 충분한 컴퓨터 연산자원으로 인해 레이더 자료를 활용한 인공지능 심층학습 기반(RNN(Recurrent Neural Network), CNN(Convolutional Neural Network), Conv-LSTM 등)의 강우예측이 국외에서 확대되고 있고, 국내에서도 ConvLSTM 등을 활용한 연구들이 진행되었다. CNN 심층신경망 기반의 초단기 예측 모델의 경우 대체적으로 외삽기반의 예측성능보다 우수한 경향이 있었으나, 예측시간이 길어질수록 공간 평활화되는 경향이 크게 나타나므로 고강도의 뚜렷한 강수 특징을 예측하기 힘들어 예측정확도를 향상시키는데 중요한 소규모 기상현상을 왜곡하게 된다. 본 연구에서는 이러한 한계를 보완하기 위해 적대적 생성 신경망(Generative Adversarial Network, GAN)을 적용한 초단시간 예측기법을 활용하고자 한다. GAN은 생성모형과 판별모형이라는 두 신경망이 서로간의 적대적인 경쟁을 통해 학습하는 신경망으로, 데이터의 확률분포를 학습하고 학습된 분포에서 샘플을 쉽게 생성할 수 있는 기법이다. 본 연구에서는 2017년부터 2021년까지의 환경부 대형 강우레이더 합성장을 수집하고, 강우발생 사례를 대상으로 학습을 수행하여 신경망을 최적화하고자 한다. 학습된 신경망으로 강우예측을 수행하여, 국내 기상청과 환경부에서 생산한 레이더 초단시간 예측강우와 정량적인 정확도를 비교평가 하고자 한다.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.10
• /
• pp.135-142
• /
• 2020

In this paper, we propose to analyze the impact of perceived over qualification on boundary spanning behavior and job performance. A total of 373 questionnaires were collected from corporate researchers developing VR technology in China to achieve the purpose of this study. The data collected through the survey were analyzed with frequency analysis, reliability analysis, positive factor analysis, structural equation model, etc. using statistical programs SPSS V.22 and AMOS V. 22. The empirical analysis of this study confirms the following findings. First, perceived over qualification is a positive influence on job performance. Second, perceived over qualification to have a positive influence on boundary spanning behavior. Third, boundary spanning behavior is to have a positive effect on job performance. Through the concluding and discussion sections, in-depth discussions on the theoretical implications, practical implications and limitations of the research and its future direction were presented.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.3
• /
• pp.199-206
• /
• 2020

The purpose of this study is to examine the relationship between intention to participation in sharing economy, digital cultural capital, and social connectedness and then analyze the variables affecting the intention to participate in sharing economy. This subjects were university students. Collected data were statistically processed by PASW 18.0 program using reliability, frequency analysis, T-test, one-way ANOVA, correlation and multiple regression analysis. The results were as follows. First, redistribution participation and cooperative lifestyle participation were relatively high. Second, intention to participate in sharing economy activities differs according to gender, age, monthly allowance, and SNS usage time. Third, intention to redistribution participation increases as the recognition of objectified digital culture capital, embodied digital culture capital, and social connectedness increases. And the intention to cooperative lifestyles participation and information sharing participation increased as digital culture capital increased. Forth, the most significant variable affecting the intention to participate in sharing economic activities was digital cultural capital.

• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.701-706
• /
• 2009

We proposed the device to control a computer with only a head and eye blinks so that disabilities by car accidents can use a computer. Because they have paralysis of their upper extremities such as C4~C5 paraplegics and cerebral palsy, they cannot efficiently access a general keyboard/mouse not using hands and foots. The cursor position was estimated from a gyro-sensor which can measure head movements, and the mouse event such as click/double click from opto-sensors which can detect eye blinks. The sensor was put on the proper goggle in order not to disturb the visual field. The performance of the proposed device was compared to a general optical mouse, and was used both relative and absolute coordinate in cursor positioning control. The recognition rate of click and double-click was 86% of the optical mouse, the speed of cursor movement by the proposed device was not much different from the mouse. The overall accuracy was 80%. Especially, the relative coordinate is more convenience and accuracy than the absolute coordinate, and can reduce the frequency of reset to prevent the accumulative error.

• Journal of Korean Library and Information Science Society
• /
• v.43 no.4
• /
• pp.69-88
• /
• 2012

This research is to find a direction of development through operating status survey of public library in Busan metropolitan city. First, Normally library users visit the library to check out books or to have a private study session. Also users normally obtained information about upcoming events done in the library through using offline search methods. Second, although the usage of the website was low, however the users demanded the increase in computer numbers in the library and online database for home access. Third, the users acknowledged the importance of the public library to their local community. Library policy indicator rated high in importance to the local community(m=3.86). However the reference desk(m=2.87), checkout desk(m=2.41), computer availability(m=2.47), as well as up-to-date artifact availability(m=2.64) did not reach the average point of 3.0. Thus, revealing that the public library's management policies were not sufficient enough to satisfy the needs of the library users.

• The KIPS Transactions:PartD
• /
• v.18D no.1
• /
• pp.1-8
• /
• 2011

The cache structure, which is designed for assuring fast accesses to frequently accessed data, resides on the various levels of computer system hierarchies. Many studies on this cache structure have been conducted and thus many page-replacement algorithms have been proposed. Most of page-replacement algorithms are designed on the basis of heuristic methods by using their own criteria such as how recently pages are accessed and how often they are accessed. This data-retrieval process in computer systems is analogous to human memory retrieval process since the retrieval process of human memory depends on frequency and recency of the retrieval events as well. A recent study regarding human memory cognition revealed that the possibility of the retrieval success and the retrieval latency have a strong correlation with the frequency and recency of the previous retrieval events. In this paper, we propose a novel page-replacement algorithm by utilizing the knowledge from the recent research regarding human memory cognition. Through a set of experiments, we demonstrated that our new method presents better hit-ratio than the LRFU algorithm which has been known as the best performing page-replacement algorithm for DBMS caches.

• The Journal of Korean Association of Computer Education
• /
• v.16 no.4
• /
• pp.55-62
• /
• 2013

Most of the APP market today, it is biased in the field of games and entertainment. In contrast, market-share of the educational APP is very low. This phenomenon is due to two major problems. The first is a decrease in the reuse because of the test of simple pattern. The second is difficult to consider user-level range that was learned previously. In this case it is necessary for students to do additional effort. This paper, propose an educational intelligent educational APP to solve the problems described above and shows implementation results. This system analyzes the stored results that have been saved to determine the area of vulnerability. Time-based Re-validation module helps long-term memory of student. The proposed system in this way directly supports self-directed learning. Therefore, the students can be able to relearn weak area autonomously. It results in improved academic achievement.