• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.21-29
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• 2014

Due to enormous number of user and limited memory space, the memory saving is become an important issue for big data service these days. In the large scaled multiple-input multiple-output (MIMO) system, the Teoplitz channel can play the significance rule to improve the performance as well as power efficiency. In this paper, we propose a Toeplitz channel decomposition based on matrix vectorization. Here we use Toeplitz matrix to the channel for large scaled MIMO system. And we show that the Toeplitz Jacket matrices are decomposed to Cooley-Tukey sparse matrices like fast Fourier transform (FFT).

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.209-222
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• 2020

The purpose of this paper is to predict the future changes of housing through the Delphi technique. The targets to predict were set by housing type, housing space, housing demand, and architectural technology. The results were as follows: ① The influences of social and value perspectives on the change of housing type, space, and demand would be high, on the other hands, the influence of political perspective would be low. ② In terms of housing type, the increase in demand for downsizing housing for high-rise buildings and the possibility of realizing remote medical support services and homecare using big data are highly predicted. That is, ③ it is anticipated that IoTs will have a significant influences on future housing changes, and ④ enactment of co-housing and related laws by the sharing economy, services for maintenance through the supply of high-rise and high-density homes, housing support for residents, and advanced lease markets by developed architectural technology are expected as anticipated forms of future housing.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.31-37
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• 2021

Recently, in the market of home appliances, the technical differentiation of products using convergence technology has been receiving a lot of response to satisfy consumer demand. However, air-conditioner products are an area that requires research and development in the early stages of convergence technology. In this paper, it is developed that a non-contact bio-signal(respiration, movement) collection technology using IR-UWB(Impulse-Radio Ultra Wideband) technology, which controls the air-conditioner direction according to the user's location and also monitors sleep to provide an optimal sleep environment. In addition, emotional lighting and ASMR are developed to provide a comfortable and emotional place of life. Finally, based on the developed convergence technology, we develop intelligent smart air-conditioning services for the convenience of daily life and a comfortable resting space.

• Journal of Cadastre & Land InformatiX
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• v.53 no.1
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• pp.21-36
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• 2023

Activity-based modeling systems have increasingly been developed to address the limitations of widely used traditional four-step transportation demand forecasting models. Accordingly, this paper introduces the Activity-BAsed Traveler Analyzer (ABATA) system. This system consists of multiple components, including an hourly total population estimator, activity profile constructor, hourly activity population estimator, spatial activity population estimator, and origin/destination estimator. To demonstrate the proposed system, the emission impact of land use changes in the 5-1 block Sejong smart city is evaluated as a case study. The results indicate that the land use with the scenario of work facility dispersed plan produced more emissions than the scenario of work facility centralized plan due to the longer travel distance. The proposed ABATA system is expected to provide a valuable tool for simulating the impacts of future changes in population, activity schedules, and land use on activity populations and travel demands.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.93-103
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• 2021

The special means of transportation introduced to improve the mobility of the transportation vulnerable met the number of legal standards in 2016, but lack of development in terms of quality, such as the existence of long waiting times. In order to streamline the operation of special means of transportation, long-term standby traffic, which is the top 25% of the wait time, was extracted from the Daegu Metropolitan Government's special transportation history data, and spatial autocorrelation analysis and social network analysis were conducted. As a result of the analysis, the correlation between the average waiting time of special transportation users and the space was high. As a result of the analysis of internal degree centrality, the peak time zone is mainly visited by general hospitals, while the off-peak time zone shows high long-term waiting demand for visits by lawmakers. The analysis of external degree centrality showed that residential-based traffic demand was high in both peak and off-peak hours. The results of this study are considered to contribute to the improvement of the quality of the operation of special transportation means, and the academic implications and limitations of the study are also presented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.86-93
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• 2016

Information technology, such as IoT, Big Data, Drone, Cloud etc., is evolving every year. Information Society is changing Intelligence Society and Creative Society. A new Construction Projects Management System Roadmap is required because it is difficult to reflect the current IT environments based on the CALS(Continuous Acquisition & Life-cycle Support) master plan, which is performed to establish every five years since 1998. This study was prepared for the Roadmap with a focus on Construction Management System based on the 4th CALS master plan, which was performed to establish the 2012 year. To this end, the construction environment and several information systems were investigated and analyzed. The problems of the construction project information system were derived using SWOT analysis, the vision, goal, direction, strategy, main tasks, specific tasks, and timetable of the Construction Project Management System are presented. This roadmap is designed to be used as operational indicators of a future construction project management system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.317-324
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• 2021

This study deals with keywords from social media on domestic portal sites related to COVID-19, which is spreading widely. The data were collected between January 20 and August 15, 2020, and were divided into three stages. The precursor period is before COVID-19 started spreading widely between January 20 and February 17, the serious period denotes the spread in Daegu between February 18 and April 20, and the stable period is the decrease in numbers of confirmed infections up to August 15. The top 50 words were extracted and clustered based on TF-IDF. As a result of the analysis, the precursor period keywords corresponded to congestion of the Situation. The frequent keywords in the serious period were Nation and Infection Route, along with instability surrounding the Treatment of COVID-19. The most common keywords in all periods were infection, mask, person, occurrence, confirmation, and information. People's emotions are becoming more positive as time goes by. Cafes and blogs share text containing writers' thoughts and subjectivity via the internet, so they are the main information-sharing spaces in the non-face-to-face era caused by COVID-19. However, since selectivity and randomness in information delivery exists, a critical view of the information produced on social media is necessary.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.720-734
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• 2023

To understand the spatiotemporal distribution pattern of zooplankton and the environmental factors influencing zooplankton abundance in Gomso Bay, major harvesting area of Manila clam (Venerupis philippinarum) in South Korea, zooplankton sampling was conducted four times in autumn (October 2022), winter (January 2023), early spring (March 2023), and spring (May 2023). Among the environmental factors of Gomso Bay, water temperature, chlorophyll a concentration (Chl-a), dissolved oxygen (DO), and pH observed different patterns, while salinity and suspended particulate matter(SPM) showed no significant statistical differences between the survey periods. The zooplankton in Gomso Bay occurred 33, 29, 27, and 29 taxonomic groups during each respective survey period. In October 2022 and May 2023, arthropod plankton were dominated, while in January and March 2023, protozoa were primarily dominant. Among the Arthropods, copepods including Acartia hongi, Paracalanus parvus s. l., Corycaeus spp., and Oithona spp. commonly found along Korean coastal areas of the Yellow Sea, were dominated. Cluster analysis based on zooplankton abundance indicated a single community (stable condition) in each season, attributed to low dissimilarity distances, while three distinct clusters (autumn, winter-early spring, spring) between seasons indicated a highly seasonal environment in Gomso Bay.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.3
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• pp.67-93
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• 2017

This study aims to investigate research trends on disaster safety Information based on the language network analysis methods. To accomplish it, we collected 312 Korean thesis and scholarly articles on disaster safety information published between 2008 and 2017 from RISS (Research Information Sharing Service) site. With the collected data, this study performed the statistical analysis based on bibliographic data. Also, this study performed the analysis of frequency and language network on keyword extracted from titles on the collected scholarly articles and thesis. This study found out that researches recently on Bigdata related to disaster safety information have been rapidly increased. Also, the needs of sharing and utilizing disaster safety information have increased. Also the various types of disaster safety information such as spatial data, real-time information, geographic information has been used for the disaster response.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.453-462
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• 2016

Since the Internet provides a way of expressing and sharing Internet users' mindsets, corporate marketers want to acquire measurable and actionable insights from web data. In the past, companies used to analyze the attitude, satisfaction, and loyalty of consumers toward their brands using survey data, whereas nowadays this is done using the big data extracted from Social Network Services. In this study, we propose a framework for clustering brand names using the social metrics gathered on social media. We also conduct a case study of the automobile industry to verify the feasibility of the proposed framework. We calculate the brand name distance for each pair of brand names based on the total number of times that they are mentioned together. These distances are used to project the brand name onto a 3-dimensional space using multidimensional scaling. After the projection, we found the clusters of brand names and identified the characteristics of each cluster. Furthermore, we concluded this paper with a discussion of the limitations and future directions of this research.