• Journal of the Korean Society for information Management
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• v.29 no.3
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• pp.61-77
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• 2012

This study investigated what web users share on a health website and how the demographic characteristics of users reflect health information sharing behavior. By using a content analysis method, this study analyzed 1,042 randomly chosen messages in the discussion board of a health website. The results revealed that the health website users emotionally supported other users, provided health information, and built relationships between them. Two third of the health website users shared his/her thoughts or feelings about ALS (Lou Gehrig's Disease) on the health website and one fourth of the health website users connected with others who had ALS. A half of the users actively provided information as a direct response to a question. No significant differences were discerned with regard to total posting frequency by age and gender effect. However, the male users in the 50s answered questions to others more actively and tried to manage their life better than the other age groups.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.392-409
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• 2016

The aim of this paper is to examine the effectiveness of combining three popular tools used in pattern recognition, which are the Active Appearance Model (AAM), the two-dimensional discrete cosine transform (2D-DCT), and Kernel Fisher Analysis (KFA), for face recognition across age variations. For this purpose, we first used AAM to generate an AAM-based face representation; then, we applied 2D-DCT to get the descriptor of the image; and finally, we used a multiclass KFA for dimension reduction. Classification was made through a K-nearest neighbor classifier, based on Euclidean distance. Our experimental results on face images, which were obtained from the publicly available FG-NET face database, showed that the proposed descriptor worked satisfactorily for both face identification and verification across age progression.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1531-1538
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• 2014

The causes of cancer are diverse, complex, and only partially understood. Many factors including health behaviors, socioeconomic environments and geographical locations can directly damage genes or combine with existing genetic faults within cells to cause cancerous mutations. Collecting the cancer data and reporting the statistics, therefore, are important to help identify health trends and establish normal health changes in geographical areas. In this article, we analyzed cancer data and demon-strated how spatial patterns of the age-standardized rate and health indicators can be examined visually and simultaneously using linked micromap plots. As a result of data analysis, the age-standardized rate has positive correlativity with thyroid and breast cancer, but the rate has negative correlativity with smoking and drinking. In addition, the regions with high age-standardized rate are located in southwest and the areas of high population density while the standardized mortality ratio is higher in southwest and northeast where there are lots of rural areas.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.568-570
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• 2023

The problem of classifying of age, gender, and race images still poses challenges. Despite deep and machine learning strides, convolutional neural networks (CNNs) remain pivotal in addressing these issues. This paper introduces a novel CNN-based approach for accurate and efficient age, gender, and race classification. Leveraging CNNs with residual blocks, our method enhances learning while minimizing computational complexity. The model effectively captures low-level and high-level features, yielding improved classification accuracy. Evaluation of the diverse 'fair face' dataset shows our model achieving 56.3%, 94.6%, and 58.4% accuracy for age, gender, and race, respectively.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.483-486
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• 2020

Age estimation and gender classification for human is a classic problem in computer vision. Almost research focus just only one task and the models are too heavy to run on low-cost system. In our research, we aim to apply multitasking learning to perform both task on a lightweight model which can achieve good precision on embedded system in the real time.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.73-81
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• 2016

With the increasing popularity of social network services (SNSs), there have been many attempts to analyze the users of SNSs. By doing so, the characteristics and preferences of the users can be understood, which can help companies provide personalized information and services that they need or are relevant for them. This study aimed to analyze the usage behavior of Korean Twitter users from various perspectives to deepen the understanding of it. For this research goal, an online survey was conducted for the users of Twitter and the data about their actual usage were collected using the open API of Twitter. Factor analysis of the data revealed five factors that explain about 69.3% of the usage variables. It was also investigated how the factors are related to gender, age, and brand preferences. The results showed that the usage behavior of Twitter is largely affected by age (p<0.001), and also by gender through an interaction effect (p<0.05). Also, the factors showed significant statistical correlations with the brand preferences of the users.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1503-1512
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• 1988

As the basic analysis to solve the within-and cross-speaker variability in phoneme based speech recognition, changes in pitch and formant frequencies of 8 Korean vowels with age and sex of speaker has been investigated by analyzing a large number fo samples. Conclusions obtained are as follows: 1) Changes in pitch frequency with age and sex of speaker for children are hard to distinguish and the difference of before and after the voice change is analyzed approximately 0.2 oct. for female an 0.9 oct. for male. 2) While most of the formants of vowel considerably change with the age of speaker, the change becomes smaller as the age becomes older. 3) While there is an indirect correlation between pitch and formant with change in age, it is hard to see a direct correlation. 4) When the objects of the recognition experiment by pitch and formants are various speakers in each age and sex, pitch also works as an efficient recognition parameter.

• Journal of the Korea Furniture Society
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• v.21 no.5
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• pp.367-379
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• 2010

Reflecting a particular place and time, from the agrarian society, through the Industrial Age, furniture has been one of the closest factors to our housing life and developed continuously. The information age representing digital, information and telecommunication generally gave a wide range of individuals and societies various phases of culture shock that had never been experienced so far, among which the change of the attitude toward work and marriage influenced on housing life style, they have required unexplored style and function of furniture additionally. People so called the singles has recently become a culture code reflecting the present time, they already have built their own territories in society, economy and culture. The ideas about a variety of furniture for the singles, which consider the housing culture of the singles, has been floated, therefore furniture for the singles are main streamed into home furniture category, required characteristics of furniture for the singles are drawn, furthermore some design examples are suggested on the basis of those characteristics in this study.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.14-16
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• 2004

Although there have been wide range of studies to characterize forest stands based upon spectral information of satellite image, it was not fully understood the texture information of forest stand using high resolution data. The objective of this study is to evaluate several texture measures for characterizing forest stand structure, such as species composition, diameter at breast height(DBH), stand density, and age. High resolution IKONOS satellite imagery data were acquired in August 200 lover the forested area near Ulsan, Korea. Primary forest types were plantation pine, mixed forest, and natural deciduous forest of stand age ranging from 10 to 50 years old. Several GLCM-based texture measures were compared with forest stand characteristics. In overall, a texture measure (contrast) calculated using red band were better to differentiate species and age group than other texture measures and near infrared bands.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.10a
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• pp.285-288
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• 1999

Creep is a major parameter to represent long-term behavior of concrete structures concerning serviceability and durability. The effect of creep is recently taking account into crack resistance analysis of early-age concrete concerning durability evaluation. Since existing creep prediction models were proposed to predict creep for hardened concrete, most of them cannot consider effectively the information on microstructure formation and hydration developed in the early-age concrete. In this study, creep tests for early-age concrete made of the type I cement and the type V cement are carried out respectively and creep prediction models are evaluated for the prediction of creep behavior in early-age concrete. A creep prediction model is modified for the prediction of creep in early-age concrete and also verified by comparing prediction results with results of creep tests on early-age concrete.