• Journal of the Korean housing association
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• v.25 no.4
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• pp.19-29
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• 2014

The study is aimed to suggest user-oriented improvement strategies for spatial plan of senior centers that provide the elderly with leisure and welfare functions for in rural areas. Five counties with the highest ratio of the elderly of 65 or over were selected from Gyeongsangbuk-do rural areas. The study classified the senior centers into 5 types depending on their floor plan, conducted individual interviews on the representatives and users of the centers using open-end questions through one-day observation on the spot, and performed actual measurement of the floor and analysis of current use. Based on above research, the result was drawn by physical characteristics, the current use, and requirements. The study is intended to serve as preliminary data for future plan of senior centers in rural areas.

• Industrial Engineering and Management Systems
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• v.11 no.3
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• pp.266-275
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• 2012

The rise of crowdsourcing and web 2.0 opens plenty of opportunities for companies who want to exploit external sources of ideas for internal innovation. Utilization of crowdsourcing for product design and development has been attracting the attention of both enterprises and researchers. Many cases of implementation of crowdsourcing for product design and development such as: Threadless, FIAT Mio, Lego online Factory, etc., have made crowdsourcing a promising alternative source of innovative power. Although crowdsourcing gained access due to improved Internet access and web 2.0, it is little understood how the crowd, with respect to participation, behaves for any crowdsourcing project. To investigate this, we conducted an experiment on a real crowd of engineering related individuals to figure out the crowd participation pattern for various product design and development phases of a new product development project. The experiment results give a quantitative view of the participation of the crowd (i.e., crowd participation pattern) in various phases of a product design and development process that utilizes crowdsourcing, provide a practical guidance for companies to harness the power of the crowd sensibly, and provide experimental data for further research in this field.

• The Journal of Industrial Distribution & Business
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• v.13 no.12
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• pp.9-22
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• 2022

Purpose: Establishing a competitive advantage in the aviation market is essential as the competition among domestic airlines intensifies. Therefore, this study examined the management strategies of both large domestic airlines and low-cost airlines. Research design, data, and methodology: This study classified domestic airlines into Full Service Airlines (FSA) and Low Cost Carriers (LCC), examined each airline's current status and characteristics, and conducted case analyses of FSA and LCC based on Porter's generic competitive strategy. Results: The analyses determined that LCC primarily implemented a cost-advantage strategy, and FSA implemented a differentiation strategy. However, as competition intensified, FSA pursued cost-advantage strategies while establishing LCC through subsidiaries. There are various specific cost reduction methods, including service simplicity, scalability, high utilization, low landing fees, low-cost unit, and point-to-point flight strategies. Conclusions: LCCs are focusing on cost advantage strategies that reduce costs; however, the FSA also runs special price events that are as good as LCCs and are comparable to LCCs on some routes. Furthermore, LCC has recently expanded its mid- and long-distance routes, making competition for long-distance routes with major airlines unavoidable.

• Journal of Distribution Science
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• v.21 no.3
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• pp.123-134
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• 2023

Purpose: The no-contact and economic downturn caused by COVID-19 have further grown the used market. The second-hand trading industry has established itself as a popular consumption culture, leading to exponential growth in the size of the market. This study aims to identify the types of shopping motivation for used products targeting Korean consumers, and to examine the relationship between shopping motivations for second-hand transactions, consumption values, and re-use intentions. Research design, data and methodology: The first study was conducted on 63 used trading platform users and the second study was conducted on 441 used trading platform users to identify the types of consumers' motivation for shopping for used products. Results: As a result of the first study, the shopping motivation types of Korean used product consumers were classified into convenience motivation, economic motivation, hedonistic motivation, information Acquisition motivation, and free time utilization motivation. As a result of the second study, it was found that convenience motivation had the greatest influence on functional values and hedonic motivation had the greatest influence on emotional values, and that functional values had a great influence on platform reuse intentions. Conclusions: This study provides practical implications for the establishment of marketing strategies for used trading platforms and academic implications for research related to used trading.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.48-60
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• 2024

With the exponential growth of satellite data utilization, machine learning has become pivotal in enhancing innovation and cybersecurity in satellite systems. This paper investigates the role of machine learning techniques in identifying and mitigating vulnerabilities and code smells within satellite software. We explore satellite system architecture and survey applications like vulnerability analysis, source code refactoring, and security flaw detection, emphasizing feature extraction methodologies such as Abstract Syntax Trees (AST) and Control Flow Graphs (CFG). We present practical examples of feature extraction and training models using machine learning techniques like Random Forests, Support Vector Machines, and Gradient Boosting. Additionally, we review open-access satellite datasets and address prevalent code smells through systematic refactoring solutions. By integrating continuous code review and refactoring into satellite software development, this research aims to improve maintainability, scalability, and cybersecurity, providing novel insights for the advancement of satellite software development and security. The value of this paper lies in its focus on addressing the identification of vulnerabilities and resolution of code smells in satellite software. In terms of the authors' contributions, we detail methods for applying machine learning to identify potential vulnerabilities and code smells in satellite software. Furthermore, the study presents techniques for feature extraction and model training, utilizing Abstract Syntax Trees (AST) and Control Flow Graphs (CFG) to extract relevant features for machine learning training. Regarding the results, we discuss the analysis of vulnerabilities, the identification of code smells, maintenance, and security enhancement through practical examples. This underscores the significant improvement in the maintainability and scalability of satellite software through continuous code review and refactoring.

• Journal of Advanced Navigation Technology
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• v.18 no.2
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• pp.191-199
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• 2014

Recently, researches to facilitate utilization by small and medium business (SMB) of cloud computing and big data paradigm, which is the booming adoption of IT area, has been on the increase. As one of these efforts, in this paper, we design and implement the prototype to tentatively build up Hadoop cluster under private cloud infrastructure environments. Prototype implementation are made on each hardware type such as single board, PC, and server and performance is measured. Also, we present the integrated verification results for the data analysis performance of the analysis software system running on top of realized prototypes by employing ASA (American Standard Association) Dataset. For this, we implement the analysis software system using several open sources such as R, Python, D3, and java and perform a test.

• Journal of Internet Computing and Services
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• v.15 no.5
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• pp.33-41
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• 2014

The purpose of this study is to provide statistical analysis based suggestions on effective methods to take advantage of social network service (SNS) for educational purposes based on investigations of undergraduate students with high utilization of SNS. To achieve this, we conducted an open questionnaire survey and qualitatively analyzed the data using NVivo 10 program. Additionally, to visualize the analysis by education subject of the SNS educational methods, we have divided the data into 3 categories of teacher, student and common area. As a result, our analysis showed that the exchange opinions and discussions, information sharing and learning of contents of questions and answers, surveys, intimacy formation, counseling etc. were of the common area. Furthermore, teacher area included the notice announcement, teaching materials sharing, real-time assessment (quiz), attendance check, assignment grading and feedback, etc. Finally the student area was of project activities (group/individual), prepare and review the shared data, video self learning, peer review and feedback of projects, lecture evaluation, etc.

• Smart Media Journal
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• v.11 no.4
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• pp.9-18
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• 2022

Recently, research and system using AI is rapidly increasing in various fields. Smart farm using artificial intelligence and information communication technology is also being studied in agriculture. In addition, data-based precision agriculture is being commercialized by convergence various advanced technology such as autonomous driving, satellites, and big data. In Korea, the number of commercialization cases of facility agriculture among smart agriculture is increasing. However, research and investment are being biased in the field of facility agriculture. The gap between research and investment in facility agriculture and open-air agriculture continues to increase. The fields of fruit trees and plant factories have low research and investment. There is a problem that the big data collection and utilization system is insufficient. In this paper, we are proposed the system for determining the fruit tree growth stage using a deep learning-based object detection model. The system was proposed as a hybrid app for use in agricultural sites. In addition, we are implemented an object detection function for the fruit tree growth stage determine.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.485-496
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• 2022

This study is for the software implementation to generate atmospheric and surface reflectance products from RapidEye satellite imagery. The software is an extension based on Orfeo Toolbox (OTB) and an open-source remote sensing software including calibration modules which use an absolute atmospheric correction algorithm. In order to verify the performance of the program, the accuracy of the product was validated by a test image on the Radiometric Calibration Network (RadCalNet) site. In addition, the accuracy of the surface reflectance product generated from the KOMPSAT-3A image, the surface reflectance of Landsat Analysis Ready Data (ARD) of the same site, and near acquisition date were compared with RapidEye-based one. At the same time, a comparative study was carried out with the processing results using QUick Atmospheric Correction (QUAC) and Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) tool supported by a commercial tool for the same image. Similar to the KOMPSAT-3A-based surface reflectance product, the results obtained from RapidEye Extension showed accuracy of agreement level within 5%, compared with RadCalNet data. They also showed better accuracy in all band images than the results using QUAC or FLAASH tool. As the importance of the Red-Edge band in agriculture, forests, and the environment applications is being emphasized, it is expected that the utilization of the surface reflectance products of RapidEye images produced using this program will also increase.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.117-124
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• 2015

As the acceptance of statistical analysis has been increased because of Big Data, the needs for an advanced second generation of statistical analysis method like Structural Equation Model are also increasing. This study suggests how R-Program, as open software, can be utilized when Partial Least Square Model, one of the SEMs, is applied to statistical analysis. R is a free software as a part of GNU projects as well as a powerful and useful tool for statistical analysis including Big Data. The study utilized R and SmartPLS, a representative statistical package of PLS-SEM, and analyzed internal consistency reliability, convergent validity, and discriminant validity of the measurement model. The study also analyzed path coefficients and moderator effects of the structural model and compared the results, respectively. The results indicated that R showed the same results with SmartPLS on the measurement model and the structural model. Therefore, the study confirmed that R could be a powerful tool that is alternative to a commercial statistical package in the future.