• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1516-1529
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• 2016

While global manufacturing is becoming more competitive due to variety of customer demand, increase in production cost and uncertainty in resource availability, the future ability of manufacturing industries depends upon the implementation of Smart Factory. With the convergence of new information and communication technology, Smart Factory enables manufacturers to respond quickly to customer demand and minimize resource usage while maximizing productivity performance. This paper presents the development of a big data analytics platform architecture for Smart Factory. As this platform represents a conceptual software structure needed to implement data-driven decision-making mechanism in shop floors, it enables the creation and use of diagnosis, prediction and optimization models through the use of data analytics and big data. The completion of implementing the platform will help manufacturers: 1) acquire an advanced technology towards manufacturing intelligence, 2) implement a cost-effective analytics environment through the use of standardized data interfaces and open-source solutions, 3) obtain a technical reference for time-efficiently implementing an analytics modeling environment, and 4) eventually improve productivity performance in manufacturing systems. This paper also presents a technical architecture for big data infrastructure, which we are implementing, and a case study to demonstrate energy-predictive analytics in a machine tool system.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.475-487
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• 2020

The paper aims to facilitate a discussion around how big data technologies and data from citizens can be used to help public administration, society, and policy-making to improve community's lives. This paper discusses opportunities and challenges of big data strategies for government, society, and policy-making. It employs the presentation of numerous practical examples from different parts of the world, where public-service delivery has seen transformation and where initiatives have been taken forward that have revolutionized the way governments at different levels engage with the citizens, and how governments and civil society have adopted evidence-driven policy-making through innovative and efficient use of big data analytics. The examples include the governments of the United States, China, the United Kingdom, and India, and different levels of government agencies in the public services of fraud detection, financial market analysis, healthcare and public health, government oversight, education, crime fighting, environmental protection, energy exploration, agriculture, weather forecasting, and ecosystem management. The examples also include smart cities in Korea, China, Japan, India, Canada, Singapore, the United Kingdom, and the European Union. This paper makes some recommendations about how big data strategies transform the government and public services to become more citizen-centric, responsive, accountable and transparent.

• International Journal of Knowledge Content Development & Technology
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• v.14 no.3
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• pp.77-91
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• 2024

This article aims to comprehensively analyze the crucial role played by data analytics and business intelligence (BI) strategies in propelling digital transformation within diverse industries. Through an extensive literature review and examination of real-world case studies, the study employs a systematic analysis of scholarly works and industry reports. This approach provides a panoramic view of how organizations utilize data-driven insights for competitive advantages, improved customer experiences, and fostering innovation. The findings underscore the pivotal significance of data analytics and BI strategies in influencing strategic decision-making, enhancing operational efficiency, and ensuring long-term sustainability across various industries. The study stands out in its originality by offering a unique synthesis of insights derived from scholarly works and real-world case studies, contributing to a holistic understanding of the transformative impact of data analytics and BI on contemporary business practices. While the study provides valuable insights, limitations include the scope of available literature and case studies. The implications call for further research to explore emerging trends and evolving challenges in the dynamic landscape of data analytics and BI. The practical implications highlight the tangible benefits organizations can derive from integrating data analytics and BI strategies, emphasizing their role in shaping strategic decisions and fostering operational efficiency. In a broader context, the study delves into the social implications of the symbiotic relationship between data analytics, BI, and digital transformation. It explores how these strategies impact broader societal and economic aspects, influencing innovation and sustainability.

• Safety and Health at Work
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• v.12 no.4
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• pp.462-470
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• 2021

Background: Fatigue is pervasive, under-reported, and potentially deadly where flight operations are concerned. The aviation industry appears to lack a standardized, practical, and easily replicable protocol for fatigue risk assessment which can be consistently applied across operators. Aim: Our paper sought to present a framework, supported by real-world data with subjective and objective parameters, to monitor aircrew fatigue and performance, and to determine the safe crew configuration for commercial airline operations. Methods: Our protocol identified risk factors for fatigue-induced performance degradation as triggers for fatigue risk and performance assessment. Using both subjective and objective measurements of sleep, fatigue, and performance in the form of instruments such as the Karolinska Sleepiness Scale, Samn-Perelli Crew Status Check, Psychomotor Vigilance Task, sleep logs, and a wearable actigraph for sleep log correlation and sleep duration and quality charting, a workflow flagging fatigue-prone flight operations for risk mitigation was developed and trialed. Results: In an operational study aimed at occupational assessment of fatigue and performance in airline pilots on a three-men crew versus a four-men crew for a long-haul flight, we affirmed the technical feasibility of our proposed framework and approach, the validity of the battery of assessment instruments, and the meaningful interpretation of fatigue and work performance indicators to enable the formulation of safe work recommendations. Conclusion: A standardized occupational assessment protocol like ours is useful to achieve consistency and objectivity in the occupational assessment of fatigue and work performance.

• Journal of Information Technology Applications and Management
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• v.28 no.3
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• pp.23-30
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• 2021

Korea currently provides long-term care benefits for the elderly with poor functionality, but most of the service providers are private businesses. This is the time when quality management of care services is required, which is just around the corner of the super-aged era. In this study, we would like to look at the case in which 'A company', which operates a long-term care institution, attempted to make voluntary changes ahead of social demands. The company tried to transform the social needs of quality management by judging them as opportunities, not threats, and establishing an integrated database of centers. First, the company processed data and built a cloud-based database system. Second, the company automatically linked data from existing systems for the efficiency of data utilization. Third, the company pursued visualization for the convenience of data utilization. This allowed the company to make data-driven strategic decisions internally. This is expected to increase sales as it will soon lead to securing new customers and pioneering new markets. It is also significant in that it can provide best practices for the long-term care industry.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.402-406
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• 2005

In this paper, we present a tool to calculate the distribution of amino acid contacts in proteins as well as in protein domains. The proteins are grouped according to the classification by Yanay Ofran and Burkhard Rost[1]. In addition, a protein's distribution was compared with that of proteins in the same group as well as the entire collection of proteins across all groups. With these statistics, biologists can pick out proteins which have characteristics that defer from the norm.

• Korean Management Science Review
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• v.32 no.4
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• pp.175-192
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• 2015

Due to the emergence of open innovation driven by development of network service technologies and convergence in ICT service industry, It is necessary for ICT service firms to examine their capabilities for open innovation. The purpose of this paper is to empirically examine determinants affecting open innovation in Korean ICT service industry. In order to analyze, this paper uses logistic and multiple regression models based on survey data of Korean ICT service firms. Estimation results show that external network for collaboration is positive on the technological innovation activity regardless of the innovation type. Specifically, user networks are significant in all types of technology innovation, revealing that it is important to innovation activities of the ICT service firms.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.254-259
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• 2008

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

• Computers and Concrete
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• v.28 no.6
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• pp.605-619
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• 2021

Building Information Modeling (BIM) models are a powerful tool for preserving and using architectural history. Manually creating information models for such a significant number and variety of architectural monuments as Dong drum towers is challenging. The building logic based on "actual measurement construction" was investigated using the metamodel idea, and a metamodel-based automated modeling approach for the wood framework of Dong drum towers was presented utilizing programmable algorithms. Metamodels of fundamental frame kinds were also constructed. Case studies were used to verify the automated modeling's correctness, completeness, and efficiency using metamodel. The results suggest that, compared to manual modeling, automated modeling using metamodel may enhance the model's integrity and correctness by 5-10% while also reducing time efficiency by 10-20%. Metamodel and construction logic offer a novel way to investigate data-driven autonomous information-based modeling.

• Wind and Structures
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• v.36 no.1
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• pp.15-29
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• 2023

To better estimate the non-Gaussian extreme wind pressures for high-rise buildings, a data-driven revised Hermitetype peak factor estimation model is proposed in this papar. Subsequently, a comparative study on three types of methods, such as Hermite-type models, short-time estimate Gumbel method (STE), and new translated-peak-process method (TPP) is carried out. The investigations show that the proposed Hermite-type peak factor has better accuracy and applicability than the other Hermite-type models, and its absolute accuracy is slightly inferior to the STE and new TPP methods for non-Gaussian wind pressures by comparing with the observed values. Moreover, these methods generally overestimate the Gaussian wind pressures especially the STE.