• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.29 no.1
• /
• pp.36-41
• /
• 2018

This paper presents an implementation of a millimeter-wave(W band) multiflare-angle horn antenna. The proposed antenna is a multimode dual-polarized square horn having equal E- and H-plane beamwidths and consists of a multimode generating section, a four-square-waveguide exciter, orthomode transducers, and power combiners for the sum pattern formation. The antenna structure has been designed to allow for easy fabrication and the designed antenna has been fabricated to a precision of ${\pm}0.02mm$ by layer-by-layer machining and diffusion bonding. The input reflection coefficient and the radiation pattern of the fabricated antenna have been measured using a network analyzer and a far-field test facility. Measurements show that the proposed antenna has 17.7~18.3 dBi gain, $25.2{\sim}28.5^{\circ}$ beamwidth, and an input VSWR between 1.02~1.75, within ${\pm}0.5GHz$ from the center frequency.

• Journal of Korea Multimedia Society
• /
• v.15 no.4
• /
• pp.540-551
• /
• 2012

Recently, the W3C has developed the HTML5 standard which gives the basis for providing various web applications on the web environments. Because of the advent of the smart devices and the broadband wireless network, users can accesse the web applications on the smart devices at anytime and anywhere. In addition, the demand on the multiscreen services, which enables users to use the appropriate device to their situation, has increased, since users have various smart devices. In this paper, we propose the grouping mechanism of web objects on the HTML5 based web platform, the extraction mechanism of the web object information which is used to create the web object on other devices, and the web object creation mechanism based on the received web object information. In addition, we propose the web service migration architecture between devices on the open web platform and implement the grouping, extraction and creation mechanism of the web objects on the test web document and generic web document with Chrome extension. Finally, we implement the delivery mechanism of the web object information between devices using the node.js and the WebSocket technologies.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.1
• /
• pp.418-428
• /
• 2015

This study conducted influencing and mediated effect on stroke to lead correct health behavior of stroke patients and tried to provide preliminary data of stroke prevention. It used stage 4 and 5 data of a national health and nutrition examination survey, analysis method was frequency analysis, Chi-square test, multiple logistic regression and structural equation modeling. In case of male, factors affecting to stroke were age, job, self-related health, alcohol, hypertention and diabetes. In case of female, age, job, self-related health, stress level and hypertention affected to stroke. In tested results on whether or not mediated effect of preceding disease exists, 5.80 difference in ${\chi}^2$ between partial mediated modeling and full mediated modeling was statistically significant(p<0.01). Therefore, partial mediated modeling was adequate to this study. We need preventive health education for changing wrong health behaviors and policy that strengthens health care network. If someone has preceding disease, they need long-term diagnosis for health condition and continuous improvement in life style.

• Journal of Korean Society of Transportation
• /
• v.17 no.5
• /
• pp.99-110
• /
• 1999

This study deals with the adaptability questions of O-D table estimation models. Its objectives are two-fold; (1) to estimate the characteristics of various O-D table estimation models(i.e. linear regression models. entropy models and statistic models) and (2) to find the model which estimates the O-D table with the best accuracy under the various data conditions. In Pursuing the above, this study gives the particular attentions to the test of the models, using the Sioux Falls network and equilibrium assignment method of MINUTP. The major findings are the followings. Firstly. it finds that the statistic models have the most goodness of fat among all models, if the required data are all Prepared. But it Presents that statistic models are the most sensitive against the underspecification and inconsistency problems of link data. Secondly, It shows that the linear regression models have the worst goodness of fat among all models. But the linear regression models are the most insensitive to the underspecification and inconsistency problems. Thirdly, THE/1 model of entropy model is sensitive against the underspecification and incon-sistency problems, but THE/2 model is insensitive. Finally, other informations like total volume, zonal Production and attraction volumes in 0-D table, help models to gain the better goodness of fit. Especially, in the statistic models. both the zonal production and attraction volume data are helpful to estimate the link volumes. It can be expected that the results dive some implications not only to the selection of optimal model under the various given data, but also to the development or modification of model.

• Journal of Korean Society of Transportation
• /
• v.30 no.4
• /
• pp.43-59
• /
• 2012

Assuming a completed Smart Highway road & communication environment that allows real-time information collection and transmission of road traffic condition ahead, the purpose of this study is to develop a plan for inducing a network-level safe driving pattern by providing road traffic condition and safety information to multiple drivers through a road information provision device. In this study, the device with a function that displays different colors according to the hazard level to the existing delineator has been named 'Smart Delineator'. Smart Delineator is a device that provides not only alignment information but also safety information for drivers to receive real-time warning information and intuitively recognize road traffic condition ahead so that drivers can respond. To examine the effects of safety driving inducement level on drivers, a simulation test was conducted using driving simulator as well as a satisfaction survey. The result showed that the Smart Delineator was able to identify the location of occurrence and affecting driving according pattern, either adhering to recommended speed or reducing speed according to the pre-defined hazard level.

• Journal of Korean Society of Transportation
• /
• v.36 no.3
• /
• pp.203-215
• /
• 2018

This study suggests a method to construct large scale dynamic O/D reflecting the characteristic that the passengers' travel patterns change according to the land use patterns of the destination. There are limitations in the existing research about dynamic O/D estimation method, such as the difficulty of collecting data, which can be applied only to a small area, or limiting to a specific transportation network such as highway networks or public transportation networks. In this paper, we propose a method to estimate dynamic O/D without limitation of analysis area based on transportation resources that can be easily collected and used according to the big data era. Clustering analysis was used to calculate the departure time trip distribution ratio based on arrival time and departure time trip distribution function was estimated by each cluster. As a result of the comparison test with the survey data, the estimated distribution function was statistically significant.

• Information Systems Review
• /
• v.10 no.2
• /
• pp.137-158
• /
• 2008

Rapid development of various information technologies creates new opportunities in online and offline markets. In this changing market environment, customers have various demands on new products and services. Therefore, their power and influence on the markets grow stronger each year. Companies have paid great attention to customer relationship management. Especially, personalized product recommendation systems, which recommend products and services based on customer's private information or purchasing behaviors in stores, is an important asset to most companies. CRM is one of the important business processes where reliable information is mined from customer database. Data mining techniques such as artificial intelligence are popular tools used to extract useful information and knowledge from these customer databases. In this research, we propose a recommendation system that predicts customer's purchase intention. Then, customer's purchasing intention of specific product is predicted by using data mining techniques using receipt data set. The performance of this suggested method is compared with that of other data mining technologies.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.4 no.4
• /
• pp.277-286
• /
• 2002

Most of the problems in dealing with the tunnel construction are the uncertainties and complexities of the stress conditions and rock strengths in ahead of the tunnel excavation. The limitations on the investigation technology, inaccessibility of borehole test in mountain area and public hatred also restrict our knowledge on the geologic conditions on the mountainous tunneling area. Nevertheless an extensive and superior geophysical exploration data is possibly acquired deep within the mountain area, with up to the tunnel locations in the case of alternative design or turn-key base projects. An appealing claim in the use of artificial neural networks (ANN) is that they give a more trustworthy results on our data based on identifying relevant input variables such as a little geotechnical information and biological learning principles. In this study, error back-propagation algorithm that is one of the teaching techniques of ANN is applied to presupposition on Rock Mass Ratings (RMR) for unknown tunnel area. In order to verify the applicability of this model, a 4km railway tunnel's field data are verified and used as input parameters for the prediction of RMR, with the learned pattern by error back propagation logics. ANN is one of basic methods in solving the geotechnical uncertainties and helpful in solving the problems with data consistency, but needs some modification on the technical problems and we hope our study to be developed in the future design work.

• The Journal of Industrial Distribution & Business
• /
• v.10 no.1
• /
• pp.59-67
• /
• 2019

Purpose - The Millennial Generation, which grew in the wake of the spread of the Internet and rapid changes in the media environment, is rapidly moving from the traditional broadcasting environment to the Internet-broadcasting environment in terms of content acceptance. With the emergence of UGC (User-generated content), the change in the status of single-person content creators enables the growth of multi-channel networks (MCN), a new content-distribution platform and an agency concept for single creators. Youtube-based MCN produces multiple single star producers and casts and provides its own video series through Youtube. It is also emerging as a major M&A target for global media providers in terms of providing content to a wide range of consumers with the same interests and consumption characteristics. In addition, for the Millennials generation, which are part of their lives, MCN is becoming the most suitable media for TGIF (Twitter, Google, i-phone, Facebook). Accordingly, this study defines newly emerging MCNs and analyzes the factors for accepting MCN-produced content based on the push-pull-mooring (PPM) model. Research design, data, and methodology - An empirical analysis is performed through a questionnaire survey. For this purpose, 204 people who have experience of watching MCN were studied. Collected data is processed through analysis of a structural equation model using R to test the hypothesis. Results - For the MCN service to become an alternative to existing media, it is necessary to continuously promote cultural diversity and diversity of attempts that conventional media cannot provide. It is the attractiveness of the alternative that has the greatest influence on the intention to switch to a MCN service. When we look at MCN content so far, certain patterns such as game progress, introduction, food, and chat rooms have already appeared. We need to overcome this and develop a completely new conceptual content that we have never seen before. This requires a more generous viewer perception of the topics covered. For diversity, linguistic and verbal violence should be tolerant in common sense to provide a foundation for securing cultural diversity. Conclusions - In this study, we tried to develop a comprehensive approach to the substitution effect of MCN. In terms of academic achievement, the PPM model is used to enhance the utilization of media and broadcasting. Practical implications are to provide an analytical framework for verifying alternative or complementary effects when viewers switch to MCN.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.5
• /
• pp.150-166
• /
• 2020

Based on the theory of cognitive reserve, we undertook this study to develop a cognitive function training program for woman in menopausal transition with complaints of declining in cognitive function. The program was established by applying the analysis, design, and development stages of the network-based instructional system designed by Jung. The cognitive function training program developed by us is an was an 8-week program composed of cognitive and video training using a mobile application. The program consists of 24 sessions, each with 20-30 minutes of duration, to be completed 3 sessions per week. The contents of the cognitive function training comprise of memory, attention, language function, and scenario-based problem-solving for executive functions, all of which are cognitive areas found to be the most vulnerable for menopausal women. The educational contents were developed for eight subject areas, one subject area per week, including the definition of menopause, its causes and symptoms, menopause and brain function, etc. During the pilot test, the cognitive function training program was applied to 10 menopausal women who complained of cognitive function decline. The results indicated that, after eight weeks of training, the overall cognitive function of participants increased, revealing statistically significant differences (t=-3.04, p=.014) after the program was completed. The mobile app-based cognitive function training program might not only improve patients' memory functions but also potentially reduce the incidence of dementia.