• Title/Summary/Keyword: 공간 빅데이터

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Analysis of Borrows Demand for Books in Public Libraries Considering Cultural Characteristics (문화적 특성을 고려한 공공도서관 도서 대출수요 분석 : 대구광역시 시립도서관을 사례로)

  • Oh, Min-Ki;Kim, Kyung-Rae;Jeong, Won-Oong;Kim, Keun-Wook
    • Journal of Digital Convergence
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    • v.19 no.3
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    • pp.55-64
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    • 2021
  • Public libraries are a space where residents learn a wide range of knowledge and ideologies, and as they are directly connected to life, various related studies have been conducted. In most previous studies, variables such as population, traffic accessibility, and environment were found to be highly relevant to library use. In this study, it can be said that the difference from previous studies is that the book borrow demand and relevance were analyzed by reflecting the variables of cultural characteristics based on the book borrow history (1,820,407 cases) and member information (297,222 persons). As a result of the analysis, it was analyzed that as the increase in borrows for social science and literature books compared to technical science books, the demand for book borrows increased. In addition, various descriptive statistical analyzes were used to analyze the characteristics of library book borrow demand, and policy implications and limitations of the study were also presented based on the analysis results. and considering that cultural characteristics change depending on the location and time of day, it is believed that related research should be continued in the future.

Analysis of public library book loan demand according to weather conditions using machine learning (머신러닝을 활용한 기상조건에 따른 공공도서관 도서대출 수요분석)

  • Oh, Min-Ki;Kim, Keun-Wook;Shin, Se-Young;Lee, Jin-Myeong;Jang, Won-Jun
    • Journal of Digital Convergence
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    • v.20 no.3
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    • pp.41-52
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    • 2022
  • Although domestic public libraries achieved quantitative growth based on the 1st and 2nd comprehensive library development plans, there were some qualitative shortcomings, and various studies have been conducted to improve them. Most of the preceding studies have limitations in that they are limited to social and economic factors and statistical analysis. Therefore, in this study, by applying the spatiotemporal concept to quantitatively calculate the decrease in public library loan demand due to rainfall and heatwave, by clustering areas with high demand for book loan due to weather changes and areas where it is not, factors inside and outside public libraries and After the combination, changes in public library loan demand according to weather changes were analyzed. As a result of the analysis, there was a difference in the decrease due to the weather for each public library, and it was found that there were some differences depending on the characteristics and spatial location of the public library. Also, when the temperature was over 35℃, the decrease in book loan demand increased significantly. As internal factors, the number of seats, the number of books, and area were derived. As external factors, the public library access ramp, cafe, reading room, floating population in their teens, and floating population of women in their 30s/40s were analyzed as important variables. The results of this analysis are judged to contribute to the establishment of policies to promote the use of public libraries in consideration of the weather in a specific season, and also suggested limitations of the study.

A Study on Intuitive IoT Interface System using 3D Depth Camera (3D 깊이 카메라를 활용한 직관적인 사물인터넷 인터페이스 시스템에 관한 연구)

  • Park, Jongsub;Hong, June Seok;Kim, Wooju
    • The Journal of Society for e-Business Studies
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    • v.22 no.2
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    • pp.137-152
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    • 2017
  • The decline in the price of IT devices and the development of the Internet have created a new field called Internet of Things (IoT). IoT, which creates new services by connecting all the objects that are in everyday life to the Internet, is pioneering new forms of business that have not been seen before in combination with Big Data. The prospect of IoT can be said to be unlimited in its utilization. In addition, studies of standardization organizations for smooth connection of these IoT devices are also active. However, there is a part of this study that we overlook. In order to control IoT equipment or acquire information, it is necessary to separately develop interworking issues (IP address, Wi-Fi, Bluetooth, NFC, etc.) and related application software or apps. In order to solve these problems, existing research methods have been conducted on augmented reality using GPS or markers. However, there is a disadvantage in that a separate marker is required and the marker is recognized only in the vicinity. In addition, in the case of a study using a GPS address using a 2D-based camera, it was difficult to implement an active interface because the distance to the target device could not be recognized. In this study, we use 3D Depth recognition camera to be installed on smartphone and calculate the space coordinates automatically by linking the distance measurement and the sensor information of the mobile phone without a separate marker. Coordination inquiry finds equipment of IoT and enables information acquisition and control of corresponding IoT equipment. Therefore, from the user's point of view, it is possible to reduce the burden on the problem of interworking of the IoT equipment and the installation of the app. Furthermore, if this technology is used in the field of public services and smart glasses, it will reduce duplication of investment in software development and increase in public services.

Estimation of Representative Wave Period and Optimal Probability Density Function Using Wave Observed Data around Korean Western Coast (국내 서해안 파랑 관측자료를 이용한 대표주기 산정 및 최적 확률밀도함수 추정)

  • Uk-Jae Lee;Hong-Yeon Cho;Jin Ho Park;Dong-Hui Ko
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.35 no.6
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    • pp.146-154
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    • 2023
  • In this study, the peak wave period Tp and mean wave period T02 and Tm-1, 0, which are major parameters for classifying ocean characteristics, were calculated using water surface elevation data observed from the second west coast oceanographic and meteorological observation tower. In addition, the ratio of abnormal data, correlation analysis, and optimal probability density function were estimated. In the case of Tp among the calculated representative periods, the proportion of abnormal data was 5.73% and 0.67% at each point, and T02 was 4.35% and 0.01%. Tm-1, 0 was found to be 2.82% and 0.03%. Meanwhile, as a result of analyzing the relationship between T02 and Tp, the relationship was calculated to be 0.53 and 0.63 for each point. The relationship between Tm-1, 0 and Tp was 1.15 and 1.32, respectively, and T02, Tm-1, 0 was 1.18 and 1.22. As a result of estimating the optimal probability density function of the calculated representative period, Tp followed the 'Log-normal' and 'Normal' distributions at each point, and T02 was 'Gamma', 'Normal' distribution and Tm-1, 0 showed that 'Log-normal' and 'Normal' distribution were dominant, respectively. It is decided that these results can be used as basic data for wave analysis conducted on the west coast.

Steel Plate Faults Diagnosis with S-MTS (S-MTS를 이용한 강판의 표면 결함 진단)

  • Kim, Joon-Young;Cha, Jae-Min;Shin, Junguk;Yeom, Choongsub
    • Journal of Intelligence and Information Systems
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    • v.23 no.1
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    • pp.47-67
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    • 2017
  • Steel plate faults is one of important factors to affect the quality and price of the steel plates. So far many steelmakers generally have used visual inspection method that could be based on an inspector's intuition or experience. Specifically, the inspector checks the steel plate faults by looking the surface of the steel plates. However, the accuracy of this method is critically low that it can cause errors above 30% in judgment. Therefore, accurate steel plate faults diagnosis system has been continuously required in the industry. In order to meet the needs, this study proposed a new steel plate faults diagnosis system using Simultaneous MTS (S-MTS), which is an advanced Mahalanobis Taguchi System (MTS) algorithm, to classify various surface defects of the steel plates. MTS has generally been used to solve binary classification problems in various fields, but MTS was not used for multiclass classification due to its low accuracy. The reason is that only one mahalanobis space is established in the MTS. In contrast, S-MTS is suitable for multi-class classification. That is, S-MTS establishes individual mahalanobis space for each class. 'Simultaneous' implies comparing mahalanobis distances at the same time. The proposed steel plate faults diagnosis system was developed in four main stages. In the first stage, after various reference groups and related variables are defined, data of the steel plate faults is collected and used to establish the individual mahalanobis space per the reference groups and construct the full measurement scale. In the second stage, the mahalanobis distances of test groups is calculated based on the established mahalanobis spaces of the reference groups. Then, appropriateness of the spaces is verified by examining the separability of the mahalanobis diatances. In the third stage, orthogonal arrays and Signal-to-Noise (SN) ratio of dynamic type are applied for variable optimization. Also, Overall SN ratio gain is derived from the SN ratio and SN ratio gain. If the derived overall SN ratio gain is negative, it means that the variable should be removed. However, the variable with the positive gain may be considered as worth keeping. Finally, in the fourth stage, the measurement scale that is composed of selected useful variables is reconstructed. Next, an experimental test should be implemented to verify the ability of multi-class classification and thus the accuracy of the classification is acquired. If the accuracy is acceptable, this diagnosis system can be used for future applications. Also, this study compared the accuracy of the proposed steel plate faults diagnosis system with that of other popular classification algorithms including Decision Tree, Multi Perception Neural Network (MLPNN), Logistic Regression (LR), Support Vector Machine (SVM), Tree Bagger Random Forest, Grid Search (GS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The steel plates faults dataset used in the study is taken from the University of California at Irvine (UCI) machine learning repository. As a result, the proposed steel plate faults diagnosis system based on S-MTS shows 90.79% of classification accuracy. The accuracy of the proposed diagnosis system is 6-27% higher than MLPNN, LR, GS, GA and PSO. Based on the fact that the accuracy of commercial systems is only about 75-80%, it means that the proposed system has enough classification performance to be applied in the industry. In addition, the proposed system can reduce the number of measurement sensors that are installed in the fields because of variable optimization process. These results show that the proposed system not only can have a good ability on the steel plate faults diagnosis but also reduce operation and maintenance cost. For our future work, it will be applied in the fields to validate actual effectiveness of the proposed system and plan to improve the accuracy based on the results.

Exploring the Temporal Relationship Between Traffic Information Web/Mobile Application Access and Actual Traffic Volume on Expressways (웹/모바일-어플리케이션 접속 지표와 TCS 교통량의 상관관계 연구)

  • RYU, Ingon;LEE, Jaeyoung;CHOI, Keechoo;KIM, Junghwa;AHN, Soonwook
    • Journal of Korean Society of Transportation
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    • v.34 no.1
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    • pp.1-14
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    • 2016
  • In the recent years, the internet has become accessible without limitation of time and location to anyone with smartphones. It resulted in more convenient travel information access both on the pre-trip and en-route phase. The main objective of this study is to conduct a stationary test for traffic information web/mobile application access indexes from TCS (Toll Collection System); and analyzing the relationship between the web/mobile application access indexes and actual traffic volume on expressways, in order to analyze searching behavior of expressway related travel information. The key findings of this study are as follows: first, the results of ADF-test and PP-test confirm that the web/mobile application access indexes by time periods satisfy stationary conditions even without log or differential transformation. Second, the Pearson correlation test showed that there is a strong and positive correlation between the web/mobile application access indexes and expressway entry and exit traffic volume. In contrast, truck entry traffic volume from TCS has no significant correlation with the web/mobile application access indexes. Third, the time gap relationship between time-series variables (i.e., concurrent, leading and lagging) was analyzed by cross-correlation tests. The results indicated that the mobile application access leads web access, and the number of mobile application execution is concurrent with all web access indexes. Lastly, there was no web/mobile application access indexes leading expressway entry traffic volumes on expressways, and the highest correlation was observed between webpage view/visitor/new visitor/repeat visitor/application execution counts and expressway entry volume with a lag of one hour. It is expected that specific individual travel behavior can be predicted such as route conversion time and ratio if the data are subdivided by time periods and areas and utilizing traffic information users' location.