• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.563-565
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• 2021

The most important feature of the recently increasing content providing service is that the amount of content increase over time is very large. Accordingly, the importance of user curation is increasing, and various techniques are used to implement it. In this paper, among the techniques for video recommendation, the analysis technique using voice data and subtitles and the video comparison technique based on keyframe extraction are compared with the results of implementing and applying the video content of real big data. In addition, through the comparison result, a video content environment to which each analysis technique can be applied is proposed.

• Korean Institute of Interior Design Journal
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• v.17 no.5
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• pp.157-165
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• 2008

This study confirm the value and the importance of the human sensibility study to add up the new meaning, and to suggest a new value of Korean sensibility study through the understanding of current statusand trend of the sensibility study in the space. The method of the study was to collect date related to the sensibility study and to analyze it focusing on its details. The date was collected from researches published on the website since the establishment of Korean Institute of Interior Design and Architectural Institute of Korea and selected at the keyword search comer. The data was extracted under keywords of research object, research purpose, research method, and analysis method. And then it was quantified with HAYASH lll program and used for analyses according to its pattern and feature. The study shows that nowadays categories representing the current status and trend of the sensibility studies in space consist of the environment, the human, and the space. The contemporary study for sensibility puts the importance on a object and a subject of the study like the environment harmonized with human and space, the humans the subject that essentially uses the spate, and the space for the architecture and the interior that puts human in. Accordingly, the study for human sensibility should develop into the study for the design focused on the intangible relationship such as 'information', 'elements for space design', 'sensibility' beyond the existing tangible categories of environment, human, and space. In addition, in the method ways of study and analysis, those studies for the sensible relationship are required to develop into new types of study applying research methods of various studies beyond the traditional border between human studies, social science, and natural science.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.8
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• pp.335-342
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• 2013

Nowadays, the traffic type and behavior are extremely diverse due to the growth of network speed and the appearance of various services on Internet. For efficient network operation and management, the importance of application-level traffic identification is more and more increasing in the area of traffic analysis. In recent years traffic identification methodology using statistical features of traffic flow has been broadly studied. However, there are several problems to be considered in the identification methodology base on statistical features of flow to improve the analysis accuracy. In this paper, we recognize these problems by analyzing the ground-truth traffic and propose the solution of these problems. The four problems considered in this paper are the distance measurement of features, the selection of the representative value of features, the abnormal behavior of TCP sessions, and the weight assignment to the feature. The proposed solutions were verified by showing the performance improvement through experiments in campus network.

• Journal of Korean Medicine for Obesity Research
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• v.21 no.2
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• pp.80-94
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• 2021

Objectives: The purpose of this study is to re-evaluate the importance of questions of obesity syndrome differentiation (OSD) questionnaire based on real-world survey and to explore the possibility of simplifying OSD types. Methods: The OSD frequency was identified, and variance threshold feature selection was performed to filter the questions. Filtered questions were clustered by K-means clustering and hierarchical clustering. After principal component analysis (PCA), the distribution patterns of the subjects were identified and the differences in the syndrome distribution were compared. Results: The frequency of OSD in spleen deficiency, phlegm (PH), and blood stasis (BS) was lower than in food retention (FR), liver qi stagnation (LS), and yang deficiency. We excluded 13 questions with low variance, 7 of which were related to BS. Filtered questions were clustered into 3 groups by K-means clustering; Cluster 1 (17 questions) mainly related to PH, BS syndromes; Cluster 2 (11 questions) related to swelling, and indigestion; Cluster 3 (11 questions) related to overeating or emotional symptoms. After PCA, significant different patterns of subjects were observed in the FR, LS, and other obesity syndromes. The questions that mainly affect the FR distribution were digestive symptoms. And emotional symptoms mainly affect the distribution of LS subjects. And other obesity syndrome was partially affected by both digestive and emotional symptoms, and also affected by symptoms related to poor circulation. Conclusions: In-depth data mining analysis identified relatively low importance questions and the potential to simplify OSD types.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.372-378
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• 2003

Limitations on the linear discriminant analysis (LDA) for face rerognition, such as the loss of generalization and the computational infeasibility, are addressed and illustrated for a small number of samples. The principal component analysis (PCA) followed by the LDA mapping may be an alternative that ran overcome these limitations. We also show that any schemes based on either mappings or template matching are vulnerable to image variations due to rotation, translation, facial expressions, or local illumination conditions. This entails the importance of a proper preprocessing that can compensate for such variations. A simple template matching, when combined with the geometrically correlated feature-based detection as a preprocessing, is shown to outperform mapping techniques in terms of both the accuracy and the robustness to image variations.

• Smart Media Journal
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• v.13 no.6
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• pp.35-43
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• 2024

During the post-pandemic period, the interest in foreign language learning surged, leading to increased usage of language-learning apps. With the rising demand for these apps, analyzing app reviews becomes essential, as they provide valuable insights into user experiences and suggestions for improvement. This research focuses on extracting insights into users' opinions, sentiments, and overall satisfaction from reviews of HelloTalk, one of the most renowned language-learning apps. We employed topic modeling and emotion analysis approaches to analyze reviews collected from the Google Play Store. Several experiments were conducted to evaluate the performance of sentiment classification models with different settings. In addition, we identified dominant emotions and topics within the app reviews using feature importance analysis. The experimental results show that the Random Forest model with topics and emotions outperforms other approaches in accuracy, recall, and F1 score. The findings reveal that topics emphasizing language learning and community interactions, as well as the use of language learning tools and the learning experience, are prominent. Moreover, the emotions of 'admiration' and 'annoyance' emerge as significant factors across all models. This research highlights that incorporating emotion scores into the model and utilizing a broader range of emotion labels enhances model performance.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.160-172
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• 2023

The metaverse, derived from the fusion of "meta" and "universe," encompasses a three-dimensional virtual realm where avatars actively participate in a range of political, economic, social, and cultural activities. With the recent development of the metaverse, the traditional way of experiencing services is changing. While existing studies have mainly focused on the technological advancements of metaverse services (e.g., scope of technological enablers, application areas of technologies), recent studies are focusing on evaluating the quality of experience (QoE) of metaverse services from a customer perspective. This is because understanding and analyzing service characteristics that determine QoE from a customer perspective is essential for designing successful metaverse services. However, relatively few studies have explored the customer-oriented approach for QoE evaluation thus far. This study conducted an online review analysis using text mining to overcome this limitation. In particular, this study analyzed 227,332 online reviews of the Roblox service, known as a representative metaverse service, and identified points for improving the Roblox service based on the analysis results. As a result of the study, nine service features that can be used for QoE evaluation of metaverse services were derived, and the importance of each feature was estimated through relationship analysis with service satisfaction. The importance estimation results identified the "co-experience" feature as the most important. These findings provide valuable insights and implications for service companies to identify their strengths and weaknesses, and provide useful insights to gain an advantage in the changing metaverse service environment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.102-108
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• 2007

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signal; onto frequency domain. The raw signals can not show the significant feature, therefore difference values are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the four fault types. This study describes the results of detecting fault using wavelet analysis.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.1
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• pp.95-102
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• 2007

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signals onto frequency domain. The raw signals can not show the significant feature, therefore difference values between the signal of the health conditions and that of the fault conditions are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the fault type. This study describes the results of detecting fault using wavelet analysis.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.880-883
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• 2021

비만은 다양한 합병증을 일으키는 위험요소로 현대인의 건강을 위협한다. 비만에 영향을 주는 요소들은 유전적 영향, 식습관, 신체활동 등이 연관된다. 비만 인구의 증가로 대사증후군의 발병률이 높아졌다. 대사증후군은 비만, 고지혈증과 고혈압 등의 여러 가지 성인병을 동반한다. 비만과 대사증후군 판별 요소 검출을 위한 개인의 신체 정보와 생활 정보 분석이 필요하다. 본 논문에서는 의사결정나무를 이용하여 비만과 대사증후군을 분류하고 분류 시 사용된 특징의 중요도 분석을 수행한다. 비만 분석 결과는 체중과 신장이 높은 특징 중요도를 나타냈으며 대사증후군은 HDL, 허리둘레, 혈압과 나이 등이 높은 특징 중요도를 보였다.