• Informatization Policy
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• v.22 no.1
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• pp.28-46
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• 2015

Although the demand for the use of public data increases in accordance with the expansion of Government 3.0, the poor level of data quality and its management currently implemented is becoming obstacles to opening data to the public. To improve the efficiency of management, linkage and usage for data, standardized processes for data quality management have to be prepared and appropriate data quality assessment criteria should be established. In this paper, we propose the organizational maturity model that can assess the public data quality management level. This model consists of the process reference model and the measurement framework. Fifteen processes grouped by the PDCA cycle are defined in the process reference model. The measurement framework measures the organizational maturity level based on process capability levels. The organizational maturity model can be used to establish objectives and directions for public data quality improvement by diagnosis of current level of public data quality management and problem solving. This model can also facilitate open to the private sector and activate usage of stable public data through reliability enhancement.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.13-22
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• 2020

Reinforcement steel fixing is a skilled and manually intensive construction trade. Current practice for the quality assessment of reinforcement steel fixing is normally performed by fabricators and has high potential in having errors due to the tedious nature of the work. In order to overcome the current inspection limitation, this study presents an approach that provides visual assistance and inspection enhancement for inspectors to assess the dimensional layout of reinforcement steel fixing. To this end, this study aims to establish an end-to-end framework for rebar layout quality inspection using laser scanning and Augmented Reality (AR). The proposed framework is composed of three parts: (1) the laser-scanned rebar data processing; (2) the rebar inspection procedure integrating with AR; and (3) the checking and fixing the rebar layout through AR visualization. In order to investigate the feasibility of the proposed framework, a case study assessing the rebar layout of a lab-scaled formwork containing two rebar layers is conducted. The results of the case studies demonstrate that the proposed approach using laser scanning and AR has the potential to produce an intuitive and accurate quality assessment for the rebar layout.

• The Journal of Information Systems
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• v.2
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• pp.194-206
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• 1993

Intelligent remote learning system is a system that incorporate communication technology and others : a database engine, an intelligent tutorial system. Learners can study by themselves through the intelligent tutorial system. The existence of a communication, database and artificial intelligence enhance the capability of IRLS. According to Parsaye, an intelligent databases should have the following features : 1) Knowledge discovery. 2) Data integrity and quality control. 3) Hypermedia management. 4) Data presentation and display. 5) Decision support and scenario analysis. 6) Data format management. 7) Intelligent system design tools. I hope that this research of framework for IRLS paves for the future research. As mentioned in the above, the future work will include an intelligent database, self-learning mechanism using neural network.

• Korean Management Science Review
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• v.26 no.1
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• pp.137-159
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• 2009

An organizational performance measurement practice is a function of performance measurement system and performance management system they are currently employing, and its quality is determined by evaluating the followings in a comprehensive manner: first, if they are measuring right things; second, if they are measuring in a right way; third, if they are actively facilitating a process of data collection, structuring, analysis, interpretation, and dissemination; and fourth, if they are using performance measurement results for the primary purposes of performance measurement. This study proposes a diagnostic framework for evaluating the performance measurement practices of public broadcasting which include the qualities of performance measurement and performance management, and develop a structured questionnaire for that purpose. The framework proposed in this study does not serve only as a useful tool for public broadcasting to revise their respective performance measures and performance measurement systems, but it also make their respective performance measurement practices a strategic management tool as well as an operational management one.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.302-313
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• 2023

This paper aims to develop a framework that can fully automate the quality management of training data used in large-scale Artificial Intelligence (AI) models built by the Ministry of Science and ICT (MSIT) in the 'AI Hub Data Dam' project, which has invested more than 1 trillion won since 2017. Autonomous driving technology using AI has achieved excellent performance through many studies, but it requires a large amount of high-quality data to train the model. Moreover, it is still difficult for humans to directly inspect the processed data and prove it is valid, and a model trained with erroneous data can cause fatal problems in real life. This paper presents a dataset reconstruction framework that removes abnormal data from the constructed dataset and introduces strategies to improve the performance of AI models by reconstructing them into a reliable dataset to increase the efficiency of model training. The framework's validity was verified through an experiment on the autonomous driving dataset published through the AI Hub of the National Information Society Agency (NIA). As a result, it was confirmed that it could be rebuilt as a reliable dataset from which abnormal data has been removed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1249-1265
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• 2022

Video streaming has become one of the most popular applications for mobile devices. The network bandwidth required for video streaming continues to exponentially increase as video quality increases and the user base grows. Multi-Path TCP (MPTCP), which allows devices to communicate simultaneously through multiple network interfaces, is one of the solutions for providing robust and reliable streaming of such high-definition video. However, mobile video streaming over MPTCP raises new concerns, e.g., power consumption and cellular data usage, since mobile device resources are constrained, and users prefer to minimize such costs. In this work, we propose a mobile video streaming framework over MPTCP (mDASH) to reduce the costs of energy and cellular data usage while preserving feasible streaming quality. Our evaluation results show that by utilizing knowledge about video behavior, mDASH can reduce energy consumption by up to around 20%, and cellular usage by 15% points, with minimal quality degradation.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.2_2
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• pp.445-456
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• 2024

This study aims to suggest service improvement opportunities by analyzing user review data of the top three OTT service apps(Netflix, Coupang Play, and TVING) on Google Play Store. To achieve this objective, we proposed a framework for uncovering service opportunities through the analysis of negative user reviews from OTT service providers. The framework involves automating the labeling of identified topics and generating service improvement opportunities using topic modeling and prompt engineering, leveraging GPT-4, a generative AI model. Consequently, we pinpointed five dissatisfaction topics for Netflix and TVING, and nine for Coupang Play. Common issues include "video playback errors", "app installation and update errors", "subscription and payment" problems, and concerns regarding "content quality". The commonly identified service enhancement opportunities include "enhancing and diversifying content quality". "optimizing video quality and data usage", "ensuring compatibility with external devices", and "streamlining payment and cancellation processes". In contrast to prior research, this study introduces a novel research framework leveraging generative AI to label topics and propose improvement strategies based on the derived topics. This is noteworthy as it identifies actionable service opportunities aimed at enhancing service competitiveness and satisfaction, instead of merely outlining topics.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.91-100
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• 2022

Major developed countries are seriously considering smart factories to increase their manufacturing competitiveness. Smart factory is a customized factory that incorporates ICT in the entire process from product planning to design, distribution and sales. This can reduce production costs and respond flexibly to the consumer market. The smart factory converts physical signals into digital signals, connects machines, parts, factories, manufacturing processes, people, and supply chain partners in the factory to each other, and uses the collected data to enable the smart factory platform to operate intelligently. Enhancing personalized value is the key. Therefore, it can be said that the success or failure of a smart factory depends on whether big data is secured and utilized. Standardized communication and collaboration are required to smoothly acquire big data inside and outside the factory in the smart factory, and the use of big data can be maximized through big data analysis. This study examines big data analysis and standardization in smart factory. Manufacturing innovation by country, smart factory construction framework, smart factory implementation key elements, big data analysis and visualization, etc. will be reviewed first. Through this, we propose services such as big data infrastructure construction process, big data platform components, big data modeling, big data quality management components, big data standardization, and big data implementation consulting that can be suggested when building big data infrastructure in smart factories. It is expected that this proposal can be a guide for building big data infrastructure for companies that want to introduce a smart factory.

• The Journal of Information Systems
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• v.9 no.1
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• pp.217-234
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• 2000

This paper is to develop an information infrastructure to support managing process in design, planning, production, and quality control. Multi-media data set of design, product, and management information flow between organizational units of a virtual enterprise. The process is the logical organization of people, technology and practices incorporated into work activities to make an end product. The core of the infrastructure is the enterprise framework which coordinates activities and controls the process. The proposed framework manages collaborative activities across space and time, and between users and computers who share information in virtual community. It utilizes knowledge distributed through virtual community and fosters cooperation between organizations. The framework provides the following facilities； coordinating activities, sharing data and processes, visualizing multi-media data, customizing and updating processes, reusing data and processes. This paper covers design and manufacturing activities but our focus is initially targeted at design area.

• 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.