• Journal of Convergence for Information Technology
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• v.9 no.1
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• pp.116-122
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• 2019

In recent years, small and medium-sized businesses are rapidly changing to an industrial structure where process/quality/energy data aggregates can be automatically or real-time to achieve global competitiveness. In particular, real-time information analysis produced in the production process of small businesses is evolving into a new process process that analyzes, predicts, prescribes and implements significant performance of small businesses. In this paper, we propose a platform-building model that can transform the automated production information system of small businesses into big data so that they can upgrade data that is generated by small businesses. The proposed model has the capability to support operational efficiency (consulting and training) and strategic decision making of small businesses by utilizing a variety of data on the basic information of products produced by small businesses for data collection by smart SMEs. In addition, the proposed model is characterized by close cooperation between small and medium-sized businesses with different regional characteristics and areas of information sharing and system linkage.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.409-422
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• 2017

TOD (Transit-Oriented Development) is one of the urban structure concentrated on the multifunctional space/district with public transportation system, which is introduced for maintaining sustainable future cities. With such trends, the project of building complex transferring centers located at a urban railway station has widely been spreaded and a comprehensive and systematic analytical framework is required to clarify and readily understand the complicated procedure of estimation with the large scale of the project. By doing so, this study is to develop a comprehensive analytical framework for estimating a pedestrian OD matrix using a spatial information and an integrated smart card data, which is so called a data depository and it has been applied to the Samseong station for the model validation. The proposed analytical framework contributes on providing a chance to possibly extend with digitalized and automated data collection technologies and a BigData mining methods.

• Journal of The Korean Association of Information Education
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• v.26 no.1
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• pp.45-53
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• 2022

The need for artificial intelligence education has emerged, and countries around the world are announcing artificial intelligence strategies. Artificial intelligence education is reflected in the main points of the 2022 revised curriculum general published in Korea. Along with this interest, programs related to artificial intelligence education are being developed, but it is difficult to find artificial intelligence programs for lower grades of elementary school. This study aims to develop a data collection education program for the lower grades of elementary school through a series of analysis-design-development-application-evaluation processes and apply it to first-grade elementary school students to verify its effectiveness. Through the developed program, it is expected that students will be able to understand and feel interested in artificial intelligence, and develop an attitude of collecting data in their daily lives through the process of searching for various types of data in their daily lives.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2801-2816
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• 2016

Owing to their low scalability, weak support on big data, insufficient data collaborative analysis and inadequate situational awareness, the traditional methods fail to meet the needs of the security data analysis. This paper proposes visualization methods to fuse the multi-source security data and grasp the network situation. Firstly, data sources are classified at their collection positions, with the objects of security data taken from three different layers. Secondly, the Heatmap is adopted to show host status; the Treemap is used to visualize Netflow logs; and the radial Node-link diagram is employed to express IPS logs. Finally, the Labeled Treemap is invented to make a fusion at data-level and the Time-series features are extracted to fuse data at feature-level. The comparative analyses with the prize-winning works prove this method enjoying substantial advantages for network analysts to facilitate data feature fusion, better understand network security situation with a unified, convenient and accurate mode.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.81-99
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• 2020

Origin-destination data have been collected and utilized for demand analysis and service design in various fields such as public transportation and traffic operation. As the utilization of big data becomes important, there are increasing needs to store raw origin-destination data for big data analysis. However, it is not practical to store and analyze the raw data for a long period of time since the size of the data increases by the power of the number of the collection points. To overcome this storage limitation and long-period pattern analysis, this study proposes a methodology for compression and origin-destination data analysis with the compressed data. The proposed methodology is applied to public transit data of Sejong and Seoul. We first measure the reconstruction error and the data size for each truncated matrix. Then, to determine a range of principal components for removing random data, we measure the level of the regularity based on covariance coefficients of the demand data reconstructed with each range of principal components. Based on the distribution of the covariance coefficients, we found the range of principal components that covers the regular demand. The ranges are determined as 1~60 and 1~80 for Sejong and Seoul respectively.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.269-270
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• 2016

빅데이터 분석을 통한 여러 산업 군과 융합으로 시너지를 발생시키기 위해서, 다양한 유형의 데이터 수집을 통해 빅데이터를 구성하는 것이 첫 번째 단계이며 기상, 교통, 인터넷 활동, 상권 등의 다양한 출처로부터 데이터 연계를 수행하고 사물인터넷과 같은 실시간으로 발생하는 로그 성 데이터 수집을 고려한 실시간 처리 시스템을 설계 하였다. 이를 통해 서로 다른 유형의 데이터가 빅데이터로 수집 되면 여러 산업 군에서 요구되는 인사이트 기반의 빅데이터 분석을 통해 B2B 또는 B2C 서비스에 응용 될 수 있다.

• Annual Conference of KIPS
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• 2017.11a
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• pp.48-51
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• 2017

빅데이터는 저장되지 않았거나 저장되더라도 분석되지 못하고 버리게 되는 방대한 양의 데이터를 말한다. 실제로도 빅데이터는 페이스북, 트위터등의 소셜 네트워크에서 많이 발생하고 있는데, 이러한 방대한 데이터들을 어떻게 효율적으로 저장하고 분석하는지에 대한 관심이 많아지고 있다. 따라서 본 논문에서는 빅데이터의 개념, 빅데이터의 향후 동향과 이슈들에 대해 살펴보고, 빅데이터 시스템이 데이터를 수집하고 저장하는 것에 대한 고려할만한 사항들과 효율적인 해결방안에 대해 제시하였다.

• Safety and Health at Work
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• v.8 no.1
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• pp.72-76
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• 2017

Background: Workplace victimization is considered a major social stressor with significant implications for the wellbeing of employees and organizations. The aim of this study was to examine the influences of employees' personality traits and organizational politics on workplace victimization among Ghanaian employees. Methods: Using a cross-sectional design, data were collected from 631 employees selected from diverse occupations through convenience sampling. Data collection tools were standardized questionnaires that measured experiences of negative acts at work (victimization), the Big Five personality traits, and organizational politics. Results: The results from hierarchical multiple regression analysis showed that among the personality traits neuroticism and conscientiousness had significant, albeit weak relationships with victimization. Organizational politics had a significant positive relationship with workplace victimization beyond employees' personality. Conclusion: The study demonstrates that compared with personal characteristics such as personality traits, work environment factors such as organizational politics have a stronger influence on the occurrence of workplace victimization.

• Journal of information and communication convergence engineering
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• v.18 no.4
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• pp.216-221
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• 2020

Artificial intelligence (AI), an essential skill of the Fourth Industrial Revolution, is being actively taught in higher education; however, AI education is only in the preparatory stage in elementary, middle, and high schools. Investigating various newspaper articles related to AI education to date can aid in basic data collection, which is an important process in the preparatory stage. Accordingly, 13,378 newspaper articles were collected from a total of 21 newspapers, and five topics were extracted using the latent Dirichlet allocation (LDA)-based topic model along with frequency analysis. Newspaper articles from the early 2000s expanded to technologies related to the Fourth Industrial Revolution. Accordingly, education in AI fields should be linked with education in AI-based technology. In addition, efforts should be made to secure the continuity and sequence of AI education in cooperation with related higher institutions and companies.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.317-320
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• 2015

Documenting work-in-progress on construction sites using images captured with smartphones, point-and-shoot cameras, and Unmanned Aerial Vehicles (UAVs) has gained significant popularity among practitioners. The spatial and temporal density of these large-scale site image collections and the availability of 4D Building Information Models (BIM) provide a unique opportunity to develop BIM-driven visual analytics that can quickly and easily detect and visualize construction progress deviations. Building on these emerging sources of information this paper presents a pipeline for model-driven visual analytics of construction progress. It particularly focuses on the following key steps: 1) capturing, transferring, and storing images; 2) BIM-driven analytics to identify performance deviations, and 3) visualizations that enable root-cause assessments on performance deviations. The information requirements, and the challenges and opportunities for improvements in data collection, plan preparations, progress deviation analysis particularly under limited visibility, and transforming identified deviations into performance metrics to enable root-cause assessments are discussed using several real world case studies.