• Science of Emotion and Sensibility
• /
• v.13 no.1
• /
• pp.243-250
• /
• 2010

A study is presented that examines the effect of personality on preference and purchase intention of positive and negative novelty design products. Participants evaluated their preference and purchase intention on 18 design products including positive and negative novelty design products. A cute Scream character was created as a positive novelty design and a skeleton Mickey character was used as a negative one. We measured extroversion, neuroticism, and visual product aesthetics as individual traits. The results shows that people, of course, prefer(and want to buy) the positive novelty design product to the negative novelty design product. Only in the case of the negative novelty design product, the more neurotic people is, the more they prefer it. Also, among the people who like the negative novelty design product, introvert ones are likely to purchase it but extroverted ones are not. These findings imply that personality plays an important role in liking and purchasing negative novelty design product.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.393-395
• /
• 2009

심장의 활성 근육의 움직임에 의하여 발생되는 전기적 변화량을 나타내는 심전도는 부정맥 또는 허혈성 심장질환을 진단하는데 널리 활용되고 있다. 특히 심실빈맥(Ventricular Tachycardia) 또는 심실세동(Ventricular Fibrillation)과 같이 치명적인 심장리듬이 발생하기 이전에, 심실조기수축(Ventricular Premature Contraction)을 검출하여 생명을 위협할 수 있는 부정맥을 조기에 진단할 수 있는 연구들이 일부 진행되고 있다. 이에 따라서 본 연구에서는 심전도 신호의 R-R 간격 정보와 R-peak 정보의 진위성을 판단하여 PVC 부정맥 패턴뿐만 아니라 PVC 파형이 연속적으로 진행되는 PVC-RUNs을 효율적으로 검출할 수 있는 부정맥 진단 알고리즘을 제안하고자 하였다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.1172-1175
• /
• 2021

비대면 교육 형식이 보편화됨에 따라 온라인 학습 및 시험 형태가 교육기관에서 일반화되고 있다. 이러한 급격한 변화로 교육의 공정성 문제와 온라인 시험의 부정행위 문제가 대두되고 있다. 시험응시자의 다양한 환경을 고려하여 정확하게 부정행위자를 판별하는 방법이 중요해지고 있다. 이를 위해 본 연구에서는 온라인 시험환경에서의 응시자의 행동 데이터와 영상데이터 분석을 진행하여 부정행위자를 감별하는 연구를 진행하였다. 분석 결과 기존의 부정행위자 감별방식의 한계점을 보완할 수 있는 방식에 대해 제안하였으며 온라인 시험환경에 대한 시사점을 제공하였다.

• Journal of Digital Convergence
• /
• v.20 no.3
• /
• pp.35-40
• /
• 2022

With the advent of the internet age and the outbreak of COVID-19, many companies have embraced online trade. However, due to the way the cyber economy works, the number of companies engaged in financial fraud by falsifying their transaction amounts and customer numbers has been gradually increasing. The purpose of this study is to analyze financial fraud of companies in the Internet era and to present solutions. Therefore, this study analyzed the financial fraud behavior of Luckin Coffee in China as an example and studied the causes and countermeasures of financial fraud. As a result, it was found that the cause of financial fraud lies in the opacity of cash flows from online transactions. The recommendations proposed by this study is to improve internal control systems in companies, develop risk management system, and establish comprehensive external supervision system

• The korean journal of orthodontics
• /
• v.31 no.1 s.84
• /
• pp.39-50
• /
• 2001

In proceeding with orthodontic treatment, the prediction for the shape, growth rate and growth direction of mandible plays a major role to set up the treatment plan and determine its period and prognosis. Various approaches being made so far have shown that the linear and angular measurement using lateral cephalograms are relatively accurate to estimate them. This study was purposed to find the shape of mandible more clearly by preventing the overlap of the Condyle head area which appears in lateral cephalogram, and to estimate its growth rate by comparing the growth quantity and ratio via lateral area measurement. This experimental was performed against 40 patients total, of which Class I of 14, Class II of 9 and Class III of 17 consist. Wide open lateral cephalograms of 40 patients were taken over average period of 4 Year 3 Months, then the linear and angular measurements were carried out with 11 itemized lists. Autocad Rl4 application program was utilized to draw their appearance, measure and compare their lateral area. As a result of study, conclusions were made as follows; 1. Mandibular body length (gonion-menton) tended to increase in order of CIII, CI and CII, and Mandibular body length of CIII group had a tendency to grow twice faster than that of CII group. 2. In lateral items such as Go-Me, A-Cd, B-Cp, E-F and G-H, CIII showed a significant increase on the year-average quantity and rate of the growth, and especially apparent difference was observed in CIII group rather than CII group. 3. For the 4 Year 3 Months period, the year-average growth quantity of lateral area of the mandible was $1.0cm^2$ for Class I, $0.8cm^2$ for Class II and $1.4cm^2$ for Class III, which corresponds to $11.9\%,\;11.8\%\;and\;20.3\%$ of growth ratio respectively. Thus, growth ratio almost 2 times more than other groups was observed in group CIII while growth ratio between group CI and CII has little difference. 4. Considering the results as above, it can be proposed that the difference in size of the mandible between groups is caused by the difference in the growth rate and growth quantity of the mandible, which generated in the middle of growth, rather than the difference in size of congenital Jaw-bone.

• The Korean Journal of Applied Statistics
• /
• v.32 no.5
• /
• pp.671-681
• /
• 2019

Studies on predicting arrhythmia using machine learning have been actively conducted with increasing number of arrhythmia patients. Existing studies have predicted arrhythmia based on multivariate data of feature variables extracted from RR interval data at a specific time point. In this study, we consider that the pattern of the heart state changes with time can be important information for the arrhythmia prediction. Therefore, we investigate the usefulness of predicting the arrhythmia with multivariate time series data obtained by extracting and accumulating the multivariate vectors of the feature variables at various time points. When considering 1-nearest neighbor classification method and its ensemble for comparison, it is confirmed that the multivariate time series data based method can have better classification performance than the multivariate data based method if we select an appropriate time series distance function.

• Journal of Digital Convergence
• /
• v.18 no.10
• /
• pp.129-136
• /
• 2020

The purpose of this study is to identify the influence of external-social and cultural factors on the perception of corruption in the public society through the Structural Equation Model(SEM) and to seek ways to reduce corruption in the public society. Currently the level of corruption in public sectors that people think is still large, and it is necessary to continuously reduce corruption in public sectors in order to improve national competitiveness. Since one society is a part of a country in system theory and social network theory, public society needs quantitative research in order to find the causes of corruption and solve them. The model was built and the variables were defined in SEM based on 600 questionnaires. As a result of analysis, corruption in public offices has decreased since the implementation of the solicitation and graft law, and socio-cultural factors have had a direct impact on corruption in public offices. The further research area is to seek detailed ways for transforming the education and awareness of civil society across the country in addition to the efforts of the public officials themselves in order to reduce corruption in public offices.

• Journal of Internet Computing and Services
• /
• v.10 no.5
• /
• pp.107-116
• /
• 2009

This paper presents an approach to detect arrhythmia using heart rate variability and a fuzzy neural network. The proposed algorithm diagnoses arrhythmia using 32 RR-intervals that are 25 seconds on average. We extract six statistical values from the 32 RR-intervals, which are used to input data of the fuzzy neural network. This paper uses the neural network with weighted fuzzy membership functions(NEWFM) to diagnose arrhythmia. The NEWFM used in this algorithm classifies normal and arrhythmia. The performances by Tsipouras using the 48 records of the MIT-BIH arrhythmia database was below 80% of SE(sensitivity) and SP(specificity) in both. The detection algorithm of arrhythmia shows 88.75% of SE, 82.28% of SP, and 86.31% of accuracy.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2003.05a
• /
• pp.115-119
• /
• 2003

본 연구는 인간에 있어서 가장 간단한 의사라고 여겨지는 긍정과 부정 응답에 대해 나타나는 뇌파의 변화를 잘 반영하는 특징을 찾아내고자 하기 위한 것이다. 고차 통계적 방법(high order statical analysis)인 바이스펙트럼(bispectrum)은 뇌파의 다른 부위와 다른 주파수 사이의 비선형위상커플링(non-linear phase coupling)을 잘 반영하므로, 이를 이용하여 긍정이나 부정을 선택할 때 나타나는 뇌파를 분석하였다. 분석결과, 반응 전 1.25초∼0.5초 에 유의미한 차이를 보였다. 긍정과 부정 응답에 대한 뇌파의 주파수와 부위를 찾아 신경회로망의 입력으로 사용하여 긍정과 부정 응답에 대해 분별하였다. 2번의 뇌파실험에서 각각 실험 데이터에 대해서는 긍/부정 차이가 존재하지만 공통적인 특징이 나타나지는 않았다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.11a
• /
• pp.703-705
• /
• 2022

코로나19 대유행으로 비대면 교육이 보편화되어 온라인 학습과 시험이 교육기관에서 일반화되고 있다. 이러한 급격한 변화로 교육의 공정성 문제와 온라인 시험의 부정행위 문제가 대두되고 있다. 온라인 시험은 대면 시험과는 달리 시험 감독관이 부정행위를 적발하기 어렵기 때문에 응시자의 다양한 환경을 고려하여 정확하게 부정행위를 판별하는 방법이 필요하다. 본 연구에서는 온라인 시험환경에서 응시자의 행동 데이터와 영상데이터를 분석하여 부정행위를 감독관에게 추천하는 시스템을 제안한다. 제안 시스템의 구현을 통해 온라인 시험 환경에서 부정행위를 탐지 기능을 확인한다.