• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2436-2457
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• 2023

The elderly population is rapidly increasing worldwide, but many face challenges in using digital tools like the Internet due to health and incapacity issues. Existing online search user interfaces (UIs) often overlook the specific usability needs of the elderly. This study proposes an adaptable web search UI model for the elderly, based on their perspectives, to enhance search performance and usability. The proposed UI model is evaluated through comparative usability testing with 20 participants, comparing it to the Google search UI. Effectiveness, efficiency, and satisfaction are measured using task completion time, error rate, and subjective preferences. The results show significant differences (p > 0.05) between the proposed web search UI model and the Google search UI. The proposed UI model achieves higher subjective satisfaction levels, indicating better alignment with the needs and preferences of elderly users. It also reduces task completion time, indicating improved efficiency, and decreases the error rate, suggesting enhanced effectiveness. These findings emphasize the importance of considering the unique usability needs of the elderly when designing search UIs. The proposed adaptable web search UI model offers a promising approach to enhance the digital experiences of elderly users. This study lays the groundwork for further development and refinement of adaptable web search UI models that cater to the specific needs of elderly users, enabling designers to create more inclusive and user-friendly search interfaces for the growing elderly population.

• 한국노년학
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• v.39 no.1
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• pp.109-125
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• 2019

This study examined factors that prevent older adults from using computers and/or smartphones for their health information search and health management. This study conducted face-to-face survey of a total of 240 older adults aged over 65. Based on the responses of open-ended questions, this study conducted semantic network analysis. The results showed that low level of perceived usefulness(PU) (e.g., information I want to find, detailed information, and trustworthiness) and perceived ease of use(PEOU) (e.g., how to search for information, how to install applications, and visibility) are main factors that prevent older adults from using computers and/or smartphones for their health information search and health management. Furthermore, based on the results of semantic network analysis, further hierarchical regression analysis confirmed that PU and PEOU were positively associated with intention to use mobile application. Thus, the results imply that increasing older adults' PU and PEOU can promote their intention to use mobile application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1119-1128
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• 2013

In this paper, we propose an algorithm to detect and track the human face with a GPU-based high speed. Basically the detection algorithm uses the existing Adaboost algorithm but the search area is dramatically reduced by detecting movement and skin color region. Differently from detection process, tracking algorithm uses only depth information. Basically it uses a template matching method such that it searches a matched block to the template. Also, In order to fast track the face, it was computed in parallel using GPU about the template matching. Experimental results show that the GPU speed when compared with the CPU has been increased to up to 49 times.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5C
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• pp.364-370
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• 2005

The first step of face recognition is to align an input face picture with database images. We propose a new algorithm of removing registration error in eigenspace. Our algorithm can correct for translation, rotation and scale changes. Linear matrix modeling of registration error enables us to compensate for subpixel errors in eigenspace. After calculating derivative of a weighting vector in eigenspace we can obtain the amount of translation or rotation without time consuming search. We verify that the correction enhances the recognition rate dramatically.

• Journal of Korean society of Dental Hygiene
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• v.24 no.2
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• pp.149-162
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• 2024

Objectives: This study aimed to identify the level of digital oral health literacy among Korean adults in Gangwon-do. Methods: A survey was conducted through face-to-face interviews with adults aged 30-89 residing in Gangwon-do, South Korea. The independent variables were socio-demographic characteristics, including gender, age, education level, income, and occupation. The dependent variable was digital oral health literacy. The statistical analysis included Independent t-test, one-way ANOVA, Pearson correlation analysis, and multiple linear regression analysis, all performed using the SPSS 27.0 software program. Results: The elderly and those with poor socioeconomic status (p<0.001) had lower average scores due to poor digital oral health literacy. The ease of searching for oral health information and the utilization of digital devices to search for information on oral health displayed a significant relationship (r=0.730, p<0.001). To develop the use of digital devices, simplifying the search for oral information (p<0.001) is essential. Conclusions: All socio-demographic characteristics, except gender, displayed a correlation with the level of digital oral health literacy. Both environmental and individual aspects of the respondents' living conditions must be considered to improve digital oral health literacy.

• KDI Journal of Economic Policy
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• v.32 no.1
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• pp.131-169
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• 2010

I develop a matching model in which risk-averse workers face borrowing constraints and make a labor force participation decision as well as a job search decision. A sharp distinction between unemployment and out of the labor force is made: those who look for work for a certain period but find no job are classified as the unemployed and those who do not look for work are classified as those out of the labor force. In the model, the job search decision consists of two steps. First, each individual who is not working obtains information about employment opportunities. Second, each individual who decides to search has to take costly actions to find a job. Since individuals differ with respect to asset holdings, they have different reservation job-finding probabilities at which an individual is indifferent between searching and not searching. Individuals, who have large asset holdings and thereby are less likely to participate in the labor market, have high reservation job-finding probability, and they are less likely to search if they have less quality of information. In other words, if individuals with large asset holdings search for job, they must have very high quality of information and face very high actual job-finding probability. On the other hand, individuals with small asset holdings have low reservation job-finding probability and they are likely to search for less quality of information. They face very low actual job-finding probability and seem to remain unemployed for a long time. Therefore, differences in the quality of information explain heterogeneous job search decisions among individuals as well as higher job finding probability for those who reenter the labor market than for those who remain in the labor force. The effect of the extended maximum duration of unemployment insurance benefits on the aggregate labor market and the labor market flows is investigated. The benchmark benefit duration is set to three months. As maximum benefit duration is extended up to six months, the employment-population ratio decreases while the unemployment rate increases because individuals who are eligible for benefits have strong incentives to remain unemployed and decide to search even if they obtain less quality of information, which leads to low job-finding probability and then high unemployment rate. Then, the vacancy-unemployment ratio decreases and, in turn, the job-finding probability for both the unemployed and those out of the labor force decrease. Finally, the outflow from nonparticipation decreases with benefit duration because the equilibrium job-finding probability decreases. As the job-finding probability decreases, those who are out of the labor force are less likely to search for the same quality of information. I also consider the matching model with two states of employment and unemployment. Compared to the results of the two-state model, the simulated effects of changes in benefit duration on the aggregate labor market and the labor market flows are quite large and significant.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1074-1081
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• 2007

This paper presents a method for real-time face detection and tracking which combined Adaboost and Camshift algorithm. Adaboost algorithm is a method which selects an important feature called weak classifier among many possible image features by tuning weight of each feature from learning candidates. Even though excellent performance extracting the object, computing time of the algorithm is very high with window size of multi-scale to search image region. So direct application of the method is not easy for real-time tasks such as multi-task OS, robot, and mobile environment. But CAMshift method is an improvement of Mean-shift algorithm for the video streaming environment and track the interesting object at high speed based on hue value of the target region. The detection efficiency of the method is not good for environment of dynamic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance. The method was proved for real image sequences including single and more faces.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.225-232
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• 2009

In this paper, a new face detection method based on pupil color distribution maps with the frequency under the illumination variance is proposed. Face-like regions are first extracted by applying skin color distribution maps to a color image and then, they are reduced by using the standard deviation of chrominance components. In order to search for eye candidates effectively, the proposed method extracts eye-like regions from face-like regions by using pupil color distribution maps. Furthermore, the proposed method is able to detect eyes very well by segmenting the eye-like regions, based on a lighting compensation technique and a segmentation algorithm even though face regions are changed into dark-tone due to varying illumination conditions. Eye candidates are then detected by means of template matching method. Finally, face regions are detected by using the evaluation values of two eye candidates and a mouth. Experimental results show that the proposed method can achieve a high performance.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.213-223
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• 2004

In this paper, we propose a new face detection method for real-time applications. It is based on the template-matching and appearance-based method. At first, we apply Min-max normalization with histogram equalization to the input image according to the variation of intensity. By applying the PCA transform to both the input image and template, PC components are obtained and they are applied to the LDA transform. Then, we estimate the distances between the input image and template, and we select one region which has the smallest distance. SVM is used for final decision whether the candidate face region is a real face or not. Since we detect a face region not the full region but within the $\pm$12 search window, our method shows a good speed and detection rate. Through the experiments with 6 category input videos, our algorithm shows the better performance than the existing methods that use only the PCA transform. and the PCA and LDA transform.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.17-44
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• 2022

The purpose of this study was to present a plan on the effect of non-face-to-face services on library anxiety facilities by analyzing the library anxiety factors of university library users. To this end, we look at the cases of university library user service response activities in response to the COVID-19 crisis and select 40 schools with the highest number of library visitors per student from among domestic four-year university libraries with 5,000 or more and less than 10,000 students. Methods of information service and program cases were analyzed, and K-LAS was reconstructed and surveyed for current students using the K university library, and frequency analysis, descriptive statistical analysis, exploratory factor analysis, and reliability analysis, correlation analysis, and multiple regression analysis were applied to analyze the library anxiety factors of users. Identify the relationship between 5 library anxiety factors and non-face-to-face service activation factors, such as physical/environmental factors of the library, data search selection factors, digital information system factors, librarian (staff) factors, and psychological/emotional factors, and activate non-face-to-face services. The influence of these factors on library anxiety factors was examined, and as a result, it was found that non-face-to-face service activation factors had the greatest influence on library digital information system anxiety factors. Based on the analysis results, it was attempted to derive a plan to relieve users' library anxiety by activating non-face-to-face services.