• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.375-378
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• 2021

인간의 보행에는 다양한 분야에서 유용하게 사용할 수 있는 정보를 가지고 있어 의료분야와 수사기관에서 사용되고 있다. 보행 데이터로부터 유용한 정보를 얻어내기 위해 선행되어야 하는 작업은 보행주기를 판별하는 것이다. 본 연구에서는 보행주기 판별을 위하여 발 뒷굽 닿기와 발가락 떼기 행동을 가속도 값과 각속도 값을 사용하여 알아내고, 정확도를 분석하는 알고리즘에 대해 논한다.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.251-256
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• 2007

성형외과에서는 웹 방문자를 늘리기 위하여 다양한 노력을 하고 있지만, 웹 사이트의 어떠한 속성이 웹 방문자 수를 증대시키는지에 대한 체계적인 연구는 찾아보기 어렵다. 본 논문에서는 방문자 수가 많은 성형외과 웹 사이트와 방문자 수가 적은 웹 사이트를 구분하는 속성을 규명하였다. 다중 판별 분석과 의사결정 나무 기법, 신경망 분석 기법을 이용하여 방문자의 다소 (多少)를 구분하는 속성들을 도출하였다. 웹 사이트의 속성 중 '가상성형프로그램', '정보추천' 등 소수의 속성이 방문자 수의 다소(多少)를 설명하는 것으로 드러났다.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.415-425
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• 2000

We proposed a new classification algorithm based on bootstrap sampling and pairwise coupling method. Also, for comparing the accuracy of a proposed algorithm with those of old methods, we conducted classification with waveform data and others.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.683-686
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• 2005

주어진 악곡의 성격을 파악하거나 악곡속의 주요정보를 추출하기 위해서는 해당 악곡의 양식파악이 선행되어야 한다. 이에 본 논문에서는 선율간 유사도 분석을 통하여 악곡의 양식을 판별하는 방안을 모색하였다. 선율간의 유사도를 분석하기 위한 방법으로 Hofmann-Engl 의 Conceptual Framework을 사용하였다.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.113-117
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• 2006

우리는 다양한 자료에서 유의미한 정보를 파악하기 위한 방법으로 다변량 분석 방법 중에서 정준판별분석, 로지스틱, 다층퍼셉트론 그리고 의사결정나무를 사용자 편의를 극대화하고 사용이 간단한 비주얼 베이직 6.0을 이용하여 개발하였다.

• Korean Journal of Food Science and Technology
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• v.38 no.6
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• pp.835-837
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• 2006

The geographical origin of Tricholoma matsutake mushrooms was studied using near-infrared spectroscopy. Modified partial least-square regression analyses were used to discriminate geographical origin. Two-hundred fifty-six of 259 actual domestic Tricholoma matsutake were classified as domestic produce, Sixty of 81 actual imported mushrooms were correctly classified as imported, while the other 21 imported from North Korea were not clearly classified. The accuracy of geographical origin discrimination was 92.94% The correlation coefficient, standard error of calibration, and standard error of prediction from modified partial least-square regression analysis were 0.84, 15.10% and 18.30% respectively.

• Korean Journal of Food Science and Technology
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• v.34 no.6
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• pp.1062-1066
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• 2002

Low field NMR was employed to discriminate the geographical origin of sesame seeds from Sudan, China, and Korea. Sudan sesame seeds had the lowest contents of moisture and crude fat. Chemical components of Korean and Chinese sesame seeds were similar, whereas relaxation times $(T_1-IR,\;T_1-SR)$ measeured through spin-lattice relaxation pluse techniques using 20 MHz NMR showed significant difference (p0.05). Canonical discriminant analysis could be used to identify the habitat of sesame seeds with over 90% accuracy of NMR results. Non-destructive and fast NMR techniques can be applied to classify Korean sesame seeds from those of other origins.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.439-448
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• 2019

The purpose of this study was to investigate factors affecting the pros and cons of 'Jol-hon' among workers. For this purpose, 288 workers were surveyed in Chungnam area. The main result are as follows. First, there were positively significant correlation among a hope, growth mindset, and organizational communication. Second, according to the discrimination analysis, the lower the age, the unmarried, the lower the hope, and the lower the organizational communication, the more favorable the 'Jol-hon'. In the case of married persons, there was no difference between the groups favoring and rejecting 'Jol-hon'. In the case of unmarried people, the lower the organizational communication, the more favorable the 'Jol-hon'. Finally, this study will present the theoretical basis for studying 'Jol-hon' in the future and suggest the policy implications to solve middle and senior couple problems.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.185-194
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• 2014

One in every 10 persons suffer from chronic gastritis in Korea. Endoscopy is most commonly used to diagnose the chronic gastritis. Endoscopic diagnosis is precise but it is accompanied with pain and high cost. According to pulse diagnosis in Traditional East Asian Medicine, health problems in stomach can be diagnosed with radial pulse signals in 'Guan' location in the right wrist, which are non-invasive and cost-effective. In this study, we developed a classification model of chronic gastritis using pulse signals in right 'Guan' location. We used both linear discrimination method and logistic regression model with respect to pulse features obtained with a peak-valley detection algorithm and a Gaussian model. As a result, we obtained sensitivity ranged between 77%~89% and specificity ranged between 72%~83% depending on classification models and feature extraction methods, and the average classification rates were approximately 80%, irrespective of the models. Specifically, the Gaussian model were featured by superior sensitivities (89.1% and 87.5%) while the peak-valley detection method showed superior specificities (82.8% and 81.3%), and the average classification rate (sensitivity + specificity) of the Gaussian model was 80.9% which was 1.2% ahead of the peak-valley method. In conclusion, we obtained a reliable classification model for the chronic gastritis based on the radial pulse feature extraction algorithms, where the Gaussian model was featured by outperformed sensitivity and the peak-valley method was featured by outperformed specificity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.993-998
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• 2020

The technology of interiors is currently developing around the world. According to various studies, the use of plants to create an environment in the home interior is increasing. However, households using furniture are designed as environment-friendly environment interiors, and in Korea and abroad, plants are used for home interiors. Unexpected accidents are occurring. As a result, there were books and broadcasts about the dangers of specific plants, but until now, accidents continue to occur because they do not properly recognize the dangers of specific plants. Therefore, in this paper, we propose a toxic plant identification system based on a multiplicative neural network model that identifies common toxic plants commonly found in Korea. We propose a high efficiency model. Through this, toxic plants can be identified with higher accuracy and safety accidents caused by toxic plants.