• KEPCO Journal on Electric Power and Energy
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• v.7 no.2
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• pp.301-307
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• 2021

After the spread of the data collection devices such as smart meters, energy data is increasingly collected in a variety of ways, and its importance continues to grow. However, due to technical or practical limitations, errors such as missing or outliers in the data occur during data collection process. Especially in the case of customer-related data, billing problems may occur, so energy companies are conducting various research to process such data. In addition, efforts are being made to create added value from data, which makes it difficult to provide such services unless reliability of data is guaranteed. In order to solve these challenges, this research analyzes prior research related to bad data processing specifically in the energy field, and propose new missing value processing methods to improve the reliability and field utilization of energy data.

• ETRI Journal
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• v.32 no.2
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• pp.302-311
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• 2010

In this study, we analyzed consumers' choices of various broadcasting and telecommunication convergence services and time consumption for chosen services by using survey data. A multivariate probit model was used to model consumers' choices of various broadcasting and telecommunication convergence services, and an ordered probit model was used to model consumers' time consumption for chosen services. Factors affecting consumers' choices and time-consumption behavior were identified, and simulation results of market competition and substitution were obtained. Based on these results, it was found that for the time being, consumers are highly locked into existing broadcasting services and are likely to become more price-sensitive to the new broadcasting and telecommunication convergence services. Also, the ways in which individual characteristics affect choices and time consumption were found to be very diverse service by service.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.2
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• pp.139-155
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• 2003

The aim of this study is to identify the data traffic capacity of 3G mobile communication networks, especially of cdma2000-1X networks. Three-layered ON/OFF traffic model is used to describe the dynamics of data traffics and the process of data transmission such as packet scheduling. We construct a simulator fully incorporating packet handling process of cdma2000-lX data network as well as three-layered ON/OFF traffic model describing the behavior of source data traffics. To get influence of traffic parameters on performance measures, the extensive simulations were performed for several data sets which are obtained from real trace data or previous studies. The experimental results show that the engineered throughput satisfying QoS criteria is approximately 25% of total capacity. Finally, some proposals to improve the system capacity are followed.

• Journal of Information Technology Services
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• v.12 no.2
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• pp.335-348
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• 2013

Vessel PMS (Planned Maintenance System) is a paper and/or software based system to monitor vessel engine equipment including main propulsion, steering, auxiliary machinery and cargo handling information. This is one of mandatory survey for vessel introduced by IMO (International Maritime Organization). The planned maintenance as well as documentation must be performed according to a system to be approved by classification agencies. Recently, vessel owners have preferred software based systems to collect and preserve accurate data. However, not ship specific and not taking into account the user are said by end users as operational difficulties. To relieve these concerns, this research analyzes vessel PMS data, suggests a middleware to support automatic collection and design consideration of user interface.

• Journal of the Korean Society for information Management
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• v.31 no.2
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• pp.7-40
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• 2014

This study proposes to identify digital library services applying cutting-edge technologies, and attempt to investigate the applicability of these technologies and services to domestic libraries. To this end, we reviewed main research which discusses next generation digital libraries, and examined thoroughly main technologies which can be applied to future libraries. As a result, the core technologies, concepts, and tools of the next generation of digital library are: cloud services, space for infinite creating (makerspace), big data, augmented reality, context-aware technologies, Google-glass, a revolutionary display technology, open linked-content-offering method, and so on. Specific cases of libraries already utilizing these technologies are also discussed.

• Knowledge Management Research
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• v.20 no.2
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• pp.59-86
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• 2019

As the era of the 4th Industrial Revolution evolves, not only private companies but also government agencies and institutions in public sector are adopting cloud computing services converged by new information technologies such as IoT, big data, and artificial intelligence to strengthen competitiveness and create new business values. The purpose of this study is to investigate the relationship between innovation characteristics, innovation resistance, and acceptance of innovative technologies from the perspective of cloud computing services in the public sector. In this study, we collected the survey data from 190 employees of IT division in the public sector, and analyzed the causal relationship between innovation characteristics, technostress, innovation resistance, and intention to adopt the cloud computing service that they perceived. As a result of the analysis, we demonstrated that innovation characteristics, technostress have significant effect on innovation resistance and acceptance intention, and that top executive commitment and innovation resistance also have significant effect on acceptance intention. This study provides meaningful practical implications for the staffs preparing for adoption of cloud computing services and the executives who make the final decision in public sector.

• Journal of Distribution Science
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• v.22 no.4
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• pp.23-35
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• 2024

This study investigates the organizational factors including firm size, adaptive capability, absorptive capability, innovative capability, and executive support to determine internet of things, production and services, and organizational performance. Research design, data, and methodology: A quantitative methodology was employed, involving the distribution of surveys to 460 employees occupying managerial and strategic roles. These individuals have accrued a minimum of one year of experience within 20 leading manufacturing and distribution companies in Thailand, each boasting a workforce exceeding 250 employees. Sampling techniques utilized encompass judgmental, quota, and snowball sampling. Furthermore, analysis of the data was conducted through Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM). Results: The findings indicate that factors such as firm size, adaptive capability, absorptive capability, and innovative capability exert significant influence on the Internet of Things (IoT). In addition, IoT significantly impacts both production and services. Furthermore, the study highlights the significant influence of production and services on organizational performance. However, the anticipated relationship between executive support and IoT lacks support according to the results. Conclusions: This study highlights the transformative potential of IoT for the manufacturing and distribution sector, paving the way for enhanced efficiency, competitiveness, and sustainability in a rapidly evolving business landscape.

• The Journal of Economics, Marketing and Management
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• v.6 no.1
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• pp.9-16
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• 2018

Purpose - Benefit delay type services have a characteristic of benefit delay that does not immediately appear at the time of delivery of service. Due to a characteristic of benefit delay, the customer's participation in the service delivery system is hindered, and the quality of service declines. As a result, customer satisfaction would be reduced. The purpose of this study is to construct an analytical framework to analyze a mechanism that promotes customer participation in benefit delay type services. Research design, data, and Methodology - Existing research has considered only the performance of service companies to enhance the quality of service and customer satisfaction. This study focused on customer participation as a factor affecting the quality of service and customer satisfaction and attempted to construct an analytical framework based on a theoretical perspective of motivational research. Results - By adopting the motivation theory, this research derived three concepts, the possibility of gaining benefits, the emotional experience, and the desire of benefit. And motivation is created when the three factors interact with each other. Conclusions - This paper has constructed an analytical framework for analyzing factors that promote customer participation in the benefit delay service and finally has proposed case study for further research.

• Journal of Information Management
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• v.43 no.3
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• pp.97-115
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• 2012

This paper derives determining factor for the management of oceanographic data in two ways. 1) The type of oceanographic observation and the raw data which were collected from marine physics, marine chemistry, marine biology, marine geology area were analyzed. 2) The services of the KODC(Korea Oceangraphic Data Center), NFRDI(National Fisheries Research & Development Institute), KHOA(Korea Hydrographic and Oceanographic Administration) were analyzed to derive metadata elements for retrieval. After analyze, the 42 deciding factor were derived in the 9 areas (general, Observer, satellites, observation instruments, observatories, space, information, projects, and observational data, data processing).

• Knowledge Management Research
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• v.19 no.1
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• pp.119-132
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• 2018

Many advanced products and services are emerging in the market thanks to data-based technologies such as Internet (IoT), Big Data, and AI. The construction of a system for data processing under the IoT network environment is not simple in configuration, and has a lot of restrictions due to a high cost for constructing a high performance server environment. Therefore, in this paper, we will design a development environment for large data analysis computing platform using open source with low cost and practicality. Therefore, this study intends to implement a big data processing system using Raspberry Pi, an ultra-small PC environment, and open source API. This big data processing system includes building a portable server system, building a web server for web mining, developing Python IDE classes for crawling, and developing R Libraries for NLP and visualization. Through this research, we will develop a web environment that can control real-time data collection and analysis of web media in a mobile environment and present it as a curriculum for non-IT specialists.