• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.79-84
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• 2021

The fundamental element to be kept for big data analysis, artificial intelligence technologies and asset management system is a data quality, which could directly affect the entire system reliability. For this reason, the momentum of data cleaning works is recently increased and data cleaning methods have been investigating around the world. In the field of electric power, however, asset data cleaning methods have not been fully determined therefore, automatic cleaning algorithm of asset data for transmission cables has been studied in this paper. Cleaning algorithm is composed of missing data treatment and outlier data one. Rule-based and expert opinion based cleaning methods are converged and utilized for these dirty data.

• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.93-118
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• 2022

Purpose - Export marketers may have incentives to attempt real earnings management to avoid low reported earnings. Therefore, we attempted to verify the relationship between cost stickiness and real earnings management in the context of export marketing. Design/methodology/approach - Data were collected from exporters that settle-accounts in December excluding financial businesses listed on the stock market from 2015 to 2019. Multiple regression analysis were employed to analyze the data. Findings - The results showed that there is a negative relationship between cost stickiness and real earnings management. In addition, the results showed that export marketers little attempt to offset the cost inefficiency caused by the increase in expense because of cost stickiness with opportunistic management activities through real earnings management. Rather, as the level of real earnings management appears lower, exporters showing cost stickiness are expected to report management performance based on actual marketing. Furthermore, exporters with a high level of managerial centrality or high managerial overconfidence little attempt to offset cost inefficiency caused by cost stickiness with real earnings management activities. Research implications or Originality - Our study is the first to investigate the quality of earnings information of exporters with cost stickiness. Based on the results, we suggested efficient marketing strategies for exporters.

• Journal of Information Technology Applications and Management
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• v.23 no.3
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• pp.25-34
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• 2016

Often we receive misled conclusion in the research if properly variables are not analyzed. In different functional issues of management it is very essential that all the latent and observed variable are properly understood so management decisions will be relevant and effective. The objective of this paper is to investigate the use of different multivariate tools for analyzing in the management research : applied or basic. The sources of data is primary as well as secondary. The primary includes the observation of different research articles of the proceedings of different conferences. And the secondary includes different publications related to multivariate analysis. The study has revealed the reasons of not using such tools of research. The preliminary finding reveals that most of the researches do not use such analytical tools in a comprehensive manner. Carelessness in design while fixing the design aspect is the main reasons of not using appropriate design.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.397-400
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• 2000

This paper provides a product data representation, a data schema and related operations, for the management of engineering changes. The computer Interpretable format of the representation enables itself to be realized through databases and their applications to a component of a product data management system. Supporting general operations for the engineering changes, it resolves problems of the existing information systems in the nested engineering changes and the simultaneous change application to multiple products. To show the feasibility, a prototype system is implemented based on the representation.

• The Journal of Industrial Distribution & Business
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• v.15 no.4
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• pp.27-33
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• 2024

Purpose: Arts and cultural management are a field with unique meaning and significance. This study is uniquely based on the focus of arts and cultural management on social and cultural sustainability sets it apart from other related study fields. Through delving into arts and cultural management, one can quickly gain skills vis-à-vis creativity and innovation in traditional and emerging media platforms. Research design, data and methodology: The current researcher relied on the descriptive research design, arriving at and evaluating the findings. The descriptive research design was the most ideal because of the need to evaluate the various literature sources systematically and later describe them without undue influence. Results: This research's core finding of art and cultural management in the current literature may be split up four findings, such as (1) Art and Cultural Management is Fast Embracing Digital Innovations and Related Elements, (2) Data and Analytics in Art and Cultural Management, (3) Interdisciplinary Nature of Arts and Cultural Management Elements, and (4) Arts and Cultural Management Face Numerous Challenges that Define it and its Future. Conclusions: All in all, based on the literature findings, the present research concludes that It is incumbent upon the various stakeholders, such as the government, to prioritize the arts and cultural management field through adequate budgeting and allocation of money.

• Journal of the Korean Society for information Management
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• v.40 no.3
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• pp.77-98
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• 2023

Large Language Models (LLMs) are becoming the major trend in the natural language processing field. These models were built based on research data, but information such as types, limitations, and risks of using research data are unknown. This research would present how to analyze and evaluate the LLMs that were built with research data: LLaMA or LLaMA base models such as Alpaca of Stanford, Vicuna of the large model systems organization, and ChatGPT from OpenAI from the perspective of research data. This quality evaluation focuses on the validity, functionality, and reliability of Data Quality Management (DQM). Furthermore, we adopted the Holistic Evaluation of Language Models (HELM) to understand its evaluation criteria and then discussed its limitations. This study presents quality evaluation criteria for LLMs using research data and future development directions.

• Journal of the military operations research society of Korea
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• v.25 no.1
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• pp.87-106
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• 1999

There are many technical datum in related with design, test & evaluation and logistic support which will be exchanged between geographically isolated units and heterogeneous hardwares & softwares in developing and operating the weapon systems. The paper proposes the conceptual database schema to establish configuration management information systems in which these datum can be automatically interchanged, tracked, audited and status-accounted without errors under the various environments. The paper investigates how to identify and classify the data in accordance with document identification, task analysis, system development, logistic support, system test & evaluation and data management. Furthermore, the investigation includes drawing the subject areas and modeling the conceptual database schema to explain the relationships between these datum. Thus, the paper results in the conceptual framework and data models of configuration management information systems, while additional customization efforts be required in applying the models to a specific weapon systems R&D.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.1-7
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• 2019

The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.811-825
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• 2023

In accordance with the government's stance of actively promoting intelligent administrative service policies through data utilization, in the disaster and safety management field, it also is proceeding with disaster and safety management policies utilizing data and constructing systems for responding efficiently to new and complex disasters and establishing scientific and systematic safety policies. However, it is difficult to quickly and accurately grasp the on-site situation in the event of a disaster, and there are still limitations in providing information necessary for situation judgment and response only by displaying vast data. This paper focuses on deriving specific needs to make disaster situation management work more intelligent and efficient by utilizing intelligent information technology. Through individual interviews with workers at the Central Disaster and Safety Status Control Center, we investigated the scope of disaster situation management work and the main functions and usability of the geographic information system (GIS)-based integrated situation management system by practitioners in this process. In addition, the data built in the system was reclassified according to purpose and characteristics to check the status of data in the GIS-based integrated situation management system. To derive needed to make disaster situation management more intelligent and efficient by utilizing intelligent information technology, 3 strategies were established to quickly and accurately identify on-site situations, make data-based situation judgments, and support efficient situation management tasks, and implementation tasks were defined and task priorities were determined based on the importance of implementation tasks through analytic hierarchy process (AHP) analysis. As a result, 24 implementation tasks were derived, and to make situation management efficient, it is analyzed that the use of intelligent information technology is necessary for collecting, analyzing, and managing video and sensor data and tasks that can take a lot of time of be prone to errors when performed by humans, that is, collecting situation-related data and reporting tasks. We have a conclusion that among situation management intelligence strategies, we can perform to develop technologies for strategies being high important score, that is, quickly and accurately identifying on-site situations and efficient situation management work support.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.601-605
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• 2009

The objective of this research is to develop a knowledge discovery framework which can help project teams discover useful patterns to improve energy efficient building design. This paper utilizes the technology of data mining to automatically extract concepts, interrelationships and patterns of interest from a large dataset. By applying data mining technology to the analysis of energy efficient building designs one can identify valid, useful, and previously unknown patterns of energy simulation modeling.