• Journal of the Korean Society for Library and Information Science
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• v.27
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• pp.291-339
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• 1994

The purpose of this study is to find personal characteristics that affect users' cognitive characteristics of system, and to verify correlations between this users' cognitive characteristics and selection of system usage in using end -user searching systems (EUSS), For corroborative analysis of this study, preliminary model was constructed referring to Davis' Technology Acceptance Model. The model consists of exogenous variables (personal characteristics) , parameter variables (perceived usefulness, perceived ease of use), and effect variables (selection of system usage), When exogenous variables affect parameter variables, exogenous variables are independent variables and parameter variables are dependent variables. In addition, in correlation of parameter variables, which have been affected by exogenous variables, with effect variables, parameter variables are independent variables and effect variables are dependent variables, As for the research methodology, this study regards the Academic Information System connected with the Internet as EUSS, So questionnaires have been sent to researchers in universities who were conducting direct searching for the system. 229 valid responses to questionnaires have been analyzed according to Pearson Correlation Analysis and Stepwise Selection of Multiple Regression in the statistical software packages, 'SPSS PC+'. The findings and conclusions made in this study are summarized as follows; 1. Among the personal characteristics (age, disciplinary, computer literacy level, perceived usefulness of use education and training, perceived satisfaction of end-user searching, perceived satisfaction of system characteristics), all characteristics but age affect perceived usefulness and perceived ease of use. Specifically, perceived satisfaction of end user searching and perceived satisfaction of system characteristics most affect perceived usefulness and perceived ease of use respectively. 2. Perceived usefulness and perceived ease of use have a direct effect on selection of system usage in using EUSS. 3, Perceived usefulness more affect selection of system usage than perceived ease of use in using EUSS.

• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.147-156
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• 2023

Efforts to employ smart home sensors to monitor the indoor activities of elderly single residents have been made to assess the feasibility of a safe and healthy lifestyle. However, the bathroom remains an area of blind spot. In this study, we have developed and evaluated a new edge computer device that can automatically detect water usage activities in the bathroom and record the activity log on a cloud server. Three kinds of sound as flushing, showering, and washing using wash basin generated during water usage were recorded and cut into 1-second scenes. These sound clips were then converted into a 2-dimensional image using MEL-spectrogram. Sound data augmentation techniques were adopted to obtain better learning effect from smaller number of data sets. These techniques, some of which are applied in time domain and others in frequency domain, increased the number of training data set by 30 times. A deep learning model, called CRNN, combining Convolutional Neural Network and Recurrent Neural Network was employed. The edge device was implemented using Raspberry Pi 4 and was equipped with a condenser microphone and amplifier to run the pre-trained model in real-time. The detected activities were recorded as text-based activity logs on a Firebase server. Performance was evaluated in two bathrooms for the three water usage activities, resulting in an accuracy of 96.1% and 88.2%, and F1 Score of 96.1% and 87.8%, respectively. Most of the classification errors were observed in the water sound from washing. In conclusion, this system demonstrates the potential for use in recording the activities as a lifelog of elderly single residents to a cloud server over the long-term.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.149-156
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• 2011

This paper proposes the effective edge selection algorithm for the rapid processing time and low memory usage of efficient graph-based image segmentation on mobile device. The graph-based image segmentation algorithm is to extract objects from a single image. The objects are consisting of graph edges, which are created by information of each image's pixel. The edge of graph is created by the difference of color intensity between the pixel and neighborhood pixels. The object regions are found by connecting the edges, based on color intensity and threshold value. Therefore, the number of edges decides on the processing time and amount of memory usage of graph-based image segmentation. Comparing to personal computer, the mobile device has many limitations such as processor speed and amount of memory. Additionally, the response time of application is an issue of mobile device programming. The image processing on mobile device should offer the reasonable response time, so that, the image segmentation processing on mobile should provide with the rapid processing time and low memory usage. In this paper, we demonstrate the performance of the effective edge selection algorithm, which effectively controls the edges of graph for the rapid processing time and low memory usage of graph-based image segmentation on mobile device.

• Journal of the Korean Statistical Society
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• v.18 no.1
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• pp.4-12
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• 1989

An efficient method for computing minimum norm quadratic unbiased estimates (MINQUE) of variance components in the mixed model is developed. This computing algorithm which used W-matrix saves both storage usage and computing time.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11c
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• pp.2023-2026
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• 2002

인터넷의 급성장으로 소프트웨어 환경이 웹으로 급속하게 전환함으로써 사용성 중심 설계가 새로운 패러다임으로 등장하고 있다. 본 논문에서는 사용자 중심 설계의 문제점을 보완하여, 사용성 중심 설계를 기반으로 효율적인 사용자 인터페이스 프로토타입의 생성과정을 제안하였다. 요구분석 시나리오를 기반으로 사용성 중심의 요구분서 프로세스를 개발하여 미숙한 설계자도 수준 높은 프로토타입을 개발할 수 있고, 프로토타입의 반복 횟수를 줄일 수 있게 하였다. 그리고 웹 환경에 적합한 사용성 중심의 사용자 인터페이스 프로토타입을 생성함으로써 통합 설계를 지원하기 위한 통합 모델링 언어(UML)를 지원할 수 있도록 하였다.

• Journal of Korean Society for Quality Management
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• v.34 no.2
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• pp.122-128
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• 2006

One feature of a computer simulation experiment, different from a physical experiment, is that the output is often deterministic. Moreover the codes are computationally very expensive to run. This paper deals with the design and analysis of computer experiments(DACE) which is a relatively new statistical research area. We model the response of computer experiments as the realization of a stochastic process. This approach is basically the same as using a spatial linear model. Applications to the optimal mechanical designing and model calibration problems are illustrated. Algorithms for selecting the best spatial linear model are also proposed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.507-508
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• 2014

요즘 스마트폰을 사용하는 사람의 수가 늘어감에 따라 무분별한 스마트폰 사용으로 인한 스마트폰 중독의 사태가 일어나고 있다. 특히, 본인이 스마트 폰을 소유 하지는 않지만 부모의 스마트 폰을 가지고 사용하는 영유아들은 자제력이 부족할 뿐만 아니라 중독의 위험이 청소년이나 어른들보다 높은 실정이다. 스마트폰을 직접 소유한 10대 청소년뿐만 아니라, 어른들 역시 무분별한 스마트폰 사용으로 일상생활에 지장이 많다. 본 논문에서는 자제력이 부족한 청소년이나 어른들에게 스스로 사용시간 설정을 통하여 무분별한 스마트폰의 사용시간을 자제 시킬 수 있는 스마트폰 사용제한 어플리케이션을 설계하고 구현하였다.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.3
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• pp.265-274
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• 2022

This paper proposes a machine learning-based screening algorithm to build the retired battery pack of the energy storage system. The proposed algorithm creates the dataset of various performance parameters of the retired battery, and this dataset is preprocessed through a principal component analysis to reduce the overfitting problem. The retried batteries with a large deviation are excluded in the dataset through a density-based spatial clustering of applications with noise, and the K-means clustering method is formulated to select the group of the retired batteries to satisfy the deviation requirement conditions. The performance of the proposed algorithm is verified based on NASA and Oxford datasets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.11
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• pp.6856-6862
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• 2014

Web usage mining is a method to extract meaningful patterns based on the web users' log data. Most existing patterns of web usage mining, however, do not consider the users' diverse inclination but create general models. Web users' keywords can have a variety of meanings regarding their tendency and background knowledge. This study evaluated the extraction web-user's pattern after collecting and analyzing the web usage information on the users' keywords of interest. Web-user's pattern can supply a web page network with various inclination information based on the users' keywords of interest. In addition, the Web-user's pattern can be used to recommend the most appropriate web pages and the suggested method of this experiment was confirmed to be useful.

• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.43-53
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• 2014

In this paper, we propose an ontology-based approach to measuring degree-of-interest in country by analyzing wikipedia usage data. First, we developed the degree-of-interest ontology called DOI ontology by extracting concept hierarchies from wikipedia categories. Second, we map the title of frequently edited articles into DOI ontology, and we measure degree-of-interest based on DOI ontology by analyzing wikipedia page views. Finally, we perform chi-square test of independence to figure out if interesting fields are independent or not by country. This approach shows interesting fields are closely related to each country, and provides degree of interests by country timely and flexibly as compared with conventional questionnaire survey analysis.