• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.217-227
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• 2021

The study aims to explore the rapidly changing university sports-related lecture environment from the perspective of professors and seek comprehensive and practical improvements in the online lecture environment for both professors and learners. In order to achieve the purpose of this study, six professors related to physical education at the university were selected as research participants, and in-depth interviews were used for about four months from September 2020 to December 2020. Examples of the problems, counterplans, and the improvement plans of professors who related to sports were shown as the results. First, the difficulties faced by professors have been divided into online and offline lecture problems, which are Internet and media possession, online lecture place amulet, professor-learner communication disorder, attendance verification and evaluation, COVID-19 infection, and face-to-face lecture place restriction since the outbreak of COVID-19. Second, professors' response to online and offline lecture problems was diversification of communication media, telecommuting, providing online learning videos, replacing and reinforcing practical classes, which were found to be somewhat lacking in government and school support systems. Finally, since the COVID-19 outbreak, Sports-related lecture's continuous problems and the professor's responses require the improvements such as government-level guidelines, university-level expansion of the venues for on- and off-line lecture, devising online lecture programs that enhance professor's convenience, and adjusting the number of participants for on- and off-line lecture.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.642-655
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• 2018

Occupancy sensors installed in buildings and households turn off the light if the space is vacant. Currently PIR(pyroelectric infra-red) motion sensors have been utilized. Recently, the researches using camera sensors have been carried out in order to overcome the demerit of PIR that cannot detect stationary people. The detection of moving and stationary people is a main functionality of the occupancy sensors. In this paper, we propose an on-line human occupancy tracking method using convolutional neural network (CNN) and self-organizing map. It is well known that a large number of training samples are needed to train the model offline. To solve this problem, we use an untrained model and update the model by collecting training samples online directly from the test sequences. Using videos capurted from an overhead camera, experiments have validated that the proposed method effectively tracks human.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1787-1793
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• 2018

Shadow is a common phenomenon observed in natural scenes, but it has a negative influence on image analysis such as object recognition, feature detection and scene analysis. Therefore, the process of detecting and removing shadows included in digital images must be considered as a pre-processing process of image analysis. In this paper, the existing methods for acquiring 1D invariant images, one of the feature elements for detecting and removing shadows contained in a single natural image, are described, and a method for obtaining 1D invariant images based on linear regression has been proposed. The proposed method calculates the log of the band-ratio between each channel of the RGB color image, and obtains the grayscale image line by linear regression. The final 1D invariant images were obtained by projecting the log image of the band-ratio onto the estimated grayscale image line. Experimental results show that the proposed method has lower computational complexity than the existing projection method using entropy minimization, and shadow detection and removal based on 1D invariant images are performed effectively.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.173-181
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• 2011

User authentication and key exchange protocols are the most important cryptographic applications. For user authentication, most protocols are based on the users' secret passwords. However, protocols based on the users' secret passwords are vulnerable to the password guessing attack. In 1992, Bellovin and Merritt proposed an EKE(Encrypted Key Exchange) protocol for user authentication and key exchage that is secure against password guessing attack. After that, many enhanced and secure EKE protocols are proposed so far. In 2006, Lo pointed out that Yeh et al.'s password-based authenticated key exchange protocol has a security weakness and proposed an improved protocol. However, Cao and Lin showed that his protocol is also vulnerable to off-line password guessing attack. In this paper, we show his protocol is vulnerable to on-line password guessing attack using new attack method, and propose an improvement of password authenticated key exchange protocol for imbalanced wireless networks secure against password guessing attack.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.2
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• pp.22-27
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• 2009

In this paper, an automatic functional inspection system EVT (Emulated Vision Tester) for LCD drive module PCB has been proposed and implemented. Typical automatic inspection system such as probing methods and vision-based systems are widely known and used, however, there exist undetectable defects due to critical timing factors which they may miss to catch from LCD equipments. Especially typical vision-based systems have inconsistency on acquisition of images so that distinction between gray scales can be difficult which results in low level of performance and reliability on the inspection results. The proposed EVT system is pure hardware solution. It directly compares pattern signals from a pattern generator to output signals from LCD drive module. It also inspects variety of analog signals such as voltage, resistance, wave forms and so forth. The EVT system not only shows high performance in terms of reliability and processing speed but reduces costs on inspection and maintenance. Also, full automation of entire production line can be realized when EVT is applied in in-line inspection processes.

• Parasites, Hosts and Diseases
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• v.42 no.1
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• pp.27-34
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• 2004

We investigated the optimal culture conditions for Cryptosporidium muris in a human stomach adenocarcinoma (AGS) cell line by determining the effects of medium pH and of selected supplements on the development of C. muris. The optimum pH of the culture medium required for the development of C. muris was determined to be 6.6. The number of parasites significantly increased during cultivation for 72 hr (p < 0.05) at this level. On the other hand, numbers decreased linearly after 24 hr of incubation at pH 7.5. When cultured in different concentrations of serum, C. muris in media containing 5% FBS induced 4-7 times more parasites than in 1% or 10% serum. Of the six medium supplements examined, only 1 mM pyruvate enhanced the number of C. muris in vitro. Transmission electron microscopic observation showed the developmental stages of C. muris in the cytoplasm of the cells, not in an extracytoplasmic location. The growth of C. muris in AGS cells provides a means of investigating its biological characteristics and of testing its response to therapeutic agents. However, a more optimized culture system is needed for the recovery of oocysts on a large scale in vitro.

• The Research Journal of the Costume Culture
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• v.18 no.5
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• pp.991-1002
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• 2010

Nowadays, personal media is a new tool for communication as digital cameras and mobile phones are developing rapidly. We are concerned over Cyworld users who could have different personal characteristics which will influence on buying patterns in on line shopping behaviors. The purpose of this research was to observe fashion attitudes and purchase behavior of Cyworld mini homepage users, for establishing marketing strategies by understanding consumers. For this study, one line survey was used for 500 male and female subjects who are 20 to 40 years old. Only reliable 441 questionnaires were used for analysis. The SPSS program was used for frequency, K-means cluster, t test, and chi-square test. A total of 441 respondents were clustered on the basis of 8 item self-disclosure scale, using the K-means procedures. The results indicated that respondents were clustered into two segments; 267 respondents(active attitude towards self-disclosure) and 164 ones(not active). We examined fashion attitudes in mini home page and buying behavior by self-disclosed variable. Those who are involved actively in self expression and self-disclosure considered more fashion style and trend. The major motivates of web surfing was finding a good design, and good price. High self-disclosure group tends to search many shopping mall for right design and low self disclosure group tends to search them for the right price. High self-disclosure group tend to shop the fashion products more, while low self disclosure group tend to purchase books more through the internet. We realized that active group in self-disclosure purchased their clothing accidently when they visit Cyworld.

• Journal of Broadcast Engineering
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• v.13 no.2
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• pp.236-244
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• 2008

We propose a new building detection and description algorithm for Lidar data and photogrammetric imagery using color segmentation, line segments matching, perceptual grouping. Our algorithm consists of two steps. In the first step, from the initial building regions extracted from Lidar data and the color segmentation results from the photogrammetric imagery, we extract coarse building boundaries based on the Lidar results with split and merge technique from aerial imagery. In the secondstep, we extract precise building boundaries based on coarse building boundaries and edges from aerial imagery using line segments matching and perceptual grouping. The contribution of this algorithm is that color information in photogrammetric imagery is used to complement collapsed building boundaries obtained by Lidar. Moreover, linearity of the edges and construction of closed roof form are used to reflect the characteristic of man-made object. Experimental results on multisensor data demonstrate that the proposed algorithm produces more accurate and reliable results than Lidar sensor.

• The Journal of Information Systems
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• v.27 no.4
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• pp.1-33
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• 2018

Purpose The purpose of this study is to review topic and survey methodological trends in 'The Journal of Information Systems' in order to present the practical guidelines for the future IS research. By attempting to conduct a meta-analysis on both topic and survey methodological trends, this study could provide researchers wishing to pursue this line of work further with what can be done to improve IS disciplines. Design/methodology/approach In this study, we have reviewed 185 papers that were published in 'The Journal of Information Systems' from 2010 to 2018 and classified them based on topics studied and survey methodologies used. The classification guidelines, which was developed by Palvia et al.(2015), has been used to capture the topic trends. We have also employed Struab et al.(2004)s' guidelines for securing rigor of validation issues. By using two guidelines, this study could also present topic and rigor trends in 'The Journal of Information Systems' and compare them to those trends in International Journals. Findings Our findings have identified dominant research topics in 'The Journal of Information Systems'; 1) social media and social computing, 2) IS usage and adoption, 3) mobile computing, 4) electronic commerce/business, 5) security and privacy, 6) supply chain management, 7) innovation, 8) knowledge management, and 9) IS management and planning. This study also could offer researchers who pursue this line of work further practical guidelines on mandatory (convergent and discriminant validity, reliability, and statistical conclusion validity), highly recommended (common method bias testing), and optional validations (measurement invariance testing for subgroup analysis, bootstrapping methods for testing mediating effects).