• The Journal of Bigdata
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• v.6 no.1
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• pp.145-151
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• 2021

In recent years, digital data has been generated in all areas of human activity, and there are many attempts to safely store and process the data to develop useful services. A data lake refers to a data repository that is independent of the source of the data and the analytical framework that leverages the data. In this paper, we designed a tool to safely store various big data generated by smart cities in a data lake and ETL it so that it can be used in services, and a web-based tool necessary to use it effectively. Implement. A series of processes (ETLs) that quality-check and refine source data, store it safely in a data lake, and manage it according to data life cycle policies are often significant for costly infrastructure and development and maintenance. It is a labor-intensive technology. The mounting technology makes it possible to set and execute ETL work monitoring and data life cycle management visually and efficiently without specialized knowledge in the IT field. Separately, a data quality checklist guide is needed to store and use reliable data in the data lake. In addition, it is necessary to set and reserve data migration and deletion cycles using the data life cycle management tool to reduce data management costs.

• International Area Studies Review
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• v.20 no.2
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• pp.25-46
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• 2016

In order to newly expand and define the concept of "strategic servitization" based on Industry 4.0, this study tried to evaluate the existing status of domestic and foreign servitized manufacturing and investigated the servitization cases of some leading overseas companies. In addition, we chose 250 samples of manufacturing firms listed on KOSDAQ and collected a vast amount of data regarding servitized manufacturing, such as the current status about new businesses, profit model, and financial fluctuations of each company. Based on these data, we classified the main types of manufacturing-service convergence into a $2{\times}2$ framework and derived a new strategic servitization model for each type of signature. Furthermore, we divided the sample corporations into three groups, which are pure manufacturer, servitized firm, and strategic servitized firm, and through the mutual comparison of the real sales amounts and the estimated sales amounts by time-series extrapolation analysis, we statistically proved that the service sales of strategic servitized firms give positive impacts on ROA when compared with those of the other two groups. Finally, we selected 12 leading domestic strategic-servitized firms, interviewed them in depth, and not only organized the issues during this process and their solutions by categories but also suggested the policy demands for strategic servitization.

• Journal of vocational education research
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• v.36 no.4
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• pp.41-56
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• 2017

The purpose of this study is to analyze the level of current difference of education needs for instructional competency of lifelong education instructor and the level of importance of lifelong education for drawing priority. Through the literature review, this is divided the lifelong education instructor's competencies such as planning, implementation, management and support and analyzed the current level and importance with 35 items through t-test analysis. The priority for education needs is applied to Borich and the Locus for Focus model simultaneously. According to result for study, the largest item of competency for lifelong education instructor is verified with the current level and importance for building of social networking and managing competency. The top priority item of education needs for instructional competency of lifelong education instructor is located in the first quadrant of model and the Locus for Focus model, according to priority in needs for Borich and was showed in program competency. The second items in priority were derived by learning resources, information gathering, competency for focus development, equitable evaluation for student, competency for building team work. Therefore, these competencies are considered as factors for priority of lifelong instructor and will be developed in personal and organizational development.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.479-488
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• 2019

The flight test operational procedure artifact includes mission planning, execution methods, and safety measures for each step of test progress. As the development of guided missiles has become more advanced and strategic, flight test has become increasingly complex and broadened. Therefore, increased reliability of the flight test operation procedures was required to ensure test safety. Particularly, the design of the flight test operational procedures required verification through M&S to predict and prepare for the uncertainty in a new test. The relevant studies have published the optimal framework development for flight tests and the model-based improvements of flight test processes, but they lacked the specificity to be applied directly to the flight test operational procedures. In addition, the flight test operational procedures, which consist of document bases, have caused problems such as limitations of analysis capabilities, insensitive expressions, and lack of scalability for the behavior and performance analysis of test resources. To improve these problems, this paper proposes how to design operational procedure of guided missile flight test system by applying MBSE(Model-based Systems Engineering). This research has improved reliability by increasing the ability to analyze the behavior and performance of test resources, and increased efficiency with the scalability applicable to multiple flight tests. That can be also used continuously for the guided missile flight tests that will be developed in the future.

• Tunnel and Underground Space
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• v.31 no.4
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• pp.243-269
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• 2021

Since the early 2010s, the social importance of research and practical projects targeting deep geological disposal of high-level nuclear waste, underground CO₂ storage and characterization of deep subsurface by borehole investigation has been increasing. In this regard, there is also a significant increase in the need for in situ test technology to obtain quantitative and reliable information on the hydraulic characteristics of deep rock mass. Through years of research and development, we have independently set up Deep borehole Hydraulic Test System (DHTS) based on the key apparatuses designed and made with our own technology. Using this system, high precision constant pressure injection tests were successfully completed at the two 1 km boreholes located in Mesozoic granite and sedimentary rock regions, Gyeongju. During the field tests, it was possible to measure very low flow rate below 0.01 l/min with micro flow rate injection/control module. In this paper, the major characteristics of DHTS are introduced and also some results obtained from the high precision field tests under the deep and low permeable rock mass environment are briefly discussed.

• Trans-
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• v.10
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• pp.73-113
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• 2021

Previous studies show that VR images can influence consumers' attitudes and behaviors by evoking imagination. In this study, we introduce a reality-based closed-loop 3D image (hereafter Virtualgraph). Then we try to see whether such image would increase evocativeness in a mobile commerce environment and whether higher telepresence of the visual image of a product can increase the purchase intention of that product. In order to find the above, we developed a model comprised of constructs containing telepresence, perceived value price, perceived food quality, and vividness of visual imagery questionnaire (VVIQ). We used Virtualgraph application to conduct an experiment, and then conducted an interview as well as a survey. As results of the experiment, survey and interview, we found the followings. First, users evoke imagination better with Virtualgraph than with still images. Second, increased evocativeness affects purchase intention if the perceived quality of fresh food product is satif actory. Third, increased evocativeness makes users value products higher and do even much higher when the perceived quality of fresh food product is good. From the interview, we could find that the experimental group had higher purchase intentions and perceived products as more expensive ones. Also, they perceived images of products clearer and more vivid than did the control group. We also discuss the strategic implications of using Virtualgraph in mobile shopping malls.

• Journal of Korean Society of Archives and Records Management
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• v.21 no.4
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• pp.1-18
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• 2021

Today, record management has become more important in management as records generated from administrative work and data production have increased significantly, and the development of information and communication technology, the working environment, and the size and various functions of the government have expanded. It is explained as an example in connection with the concept of public records with the characteristics of big data and big data characteristics. Social, Technological, Economical, Environmental and Political (STEEP) analysis was conducted to examine such areas according to the big data generation environment. The appropriateness and necessity of applying big data technology in the field of public record management were identified, and the top priority applicable framework for public record management work was schematized, and business implications were presented. First, a new organization, additional research, and attempts are needed to apply big data analysis technology to public record management procedures and standards and to record management experts. Second, it is necessary to train record management specialists with "big data analysis qualifications" related to integrated thinking so that unstructured and hidden patterns can be found in a large amount of data. Third, after self-learning by combining big data technology and artificial intelligence in the field of public records, the context should be analyzed, and the social phenomena and environment of public institutions should be analyzed and predicted.

• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.

• Economic Analysis
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• v.27 no.2
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• pp.71-123
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• 2021

In this study, we present a methodology and model to estimate land prices and the value of land assets in North Korea in the absence of any data about land characteristics from North Korean authorities. Using this framework, we experimentally make market price-based estimates for land assets across the entire urban area of North Korea. First, we estimate the determinants of land prices in South Korea using data on market prices of land from the late 1970s, when it was estimated that the income level gap between South Korea and North Korea wasn't relatively large, and from the early 1980s, when urbanization levels in both of them were similar. Second, we calculate land prices and their relative ratios for each city and urban area in North Korea around 2015 by substituting proxy variables of determinants of land prices derived through a geographic information analysis of North Korea into the function of land prices that we have already estimated. Finally, we estimate the value of land assets in urban areas across North Korea by combining the ratio of housing transaction prices surveyed in several cities in North Korea with the relative prices estimated in this research. As a result, land prices in urban areas in North Korea, looking at the relative ratio of price by city, are estimated to be the highest, at 100.00, in Tongdaewon district of Pyongyang, and to be the lowest, at 1.70, in Phungso county, Ryanggang Province. Meanwhile, the value of land assets in urbanized areas was estimated at $21.6 billion in 2015, which was 1.2 to 1.3 times the GDP of North Korea that year. This ratio is similar to South Korea's in the 1978-1980 period, when the South Korean economy grew at an average rate of 6%. Considering North Korea's growth rate of about 1% in the 2013-2014 period, its ratio of land assets to GDP appears very high.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.