• 한국정밀공학회지
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• 제13권12호
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• pp.63-69
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• 1996

As the significance of quality in the sense of customer satisfaction is growing, the management of quality becomes one of the main interests in the manufacturing systems research. This paper presents the concept of quality-driven CIM(Computer Integrated Manufacturing) system which is composed of a business process domain and a quality domain. In the business process domain, business functions are integrated by conventional design and manufacturing databases on the one hand, and an integrated quality system is interlinked to them via several quality modules on the other hand. Quality information model connects the business process domain with the quality domain where various types of quality data are stored in the form of quality database. This framework helps a manufacturing enterprise to implement the quality-driven CIM system to achieve its final objective "customer satisfaction".ion".uot;.

• 정보화정책
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• 제28권3호
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• pp.95-111
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• 2021

데이터 기반 정책의사결정시스템 구현을 목표로 현재 기획재정부는 관련 추진단을 구성하여 활발히 구축 중에 있다. 본 시스템은 현재 단순 재정행정업무 지원을 벗어나 데이터 기반의 재정업무가 가능하도록 구축 중이다. 미국은 증거 기반의 정책의사 결정법을 제정하여 관련 업무를 적극 추진 중이다. 우리나라도 작년부터 데이터기반 행정법이 시행되어 데이터 기반 행정업무를 할 수 있도록 법제도적 근거가 마련되었다. 차세대 예산회계시스템이 데이터 기반의 시스템으로 그 역할을 다하려면 많은 정책과 노력이 필요하다. 데이터 관리, 법제도, 관련 시스템 구축 등 다양한 부분에서 혁신과 변화가 필요하다. 이런 상황에서 우리나라보다 먼저 재정시스템을 구축하여 운영하고 있는 미국, 영국 등 세계 선진국의 재정시스템과 정책을 거버넌스 차원에서 비교 분석하는 것은 매우 시기적절하다고 볼 수 있다. 이들의 재정정보시스템을 비교 분석하여 차세대 예산회계시스템에 적용한다면 한층 더 나은 시스템이 될 것으로 기대한다. 본 연구에서는 미국, 영국, 프랑스, 캐나다 등 주요 선진국을 대상으로 데이터 거버넌스를 정책적, 시스템적, 법제도적, 추진체계, 서비스적 차원에서 비교 분석하였다. 그리고 결론에서는 디지털 대전환시대, 코로나19 등 최근 어려운 경제위기 환경에 대해 신속히 대처하고 국민이 원하는 국가재정정책시스템으로서의 역할과 방향도 제안하였다.

• 한국멀티미디어학회논문지
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• 제21권11호
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• pp.1353-1361
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• 2018

With the availability of real-time educational data collection and analysis techniques, the education paradigm is shifting from educator-centric to data-driven lectures. However, most offline and online education frameworks collect students' feedback from question-answering data that can summarize their understanding but requires instructor's attention when students need additional help during lectures. This paper proposes a content restructure recommendation framework based on collected student feedback. We list the types of student feedback and implement a web-based framework that collects both implicit and explicit feedback for content restructuring. With a case study of four-week lectures with 50 students, we analyze the pattern of student feedback and quantitatively validate the effect of the proposed content restructuring measured by the level of student engagement.

• Communications for Statistical Applications and Methods
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• 제26권4호
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• pp.411-430
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• 2019

Tumor development is driven by complex combinations of biological elements. Recent advances suggest that molecularly distinct subtypes of breast cancers may respond differently to pathway-targeted therapies. Thus, it is important to dissect pathway disturbances by integrating multiple molecular profiles, such as genetic, genomic and epigenomic data. However, missing data are often present in the -omic profiles of interest. Motivated by genomic data integration and imputation, we present a new statistical framework for pathway significance analysis. Specifically, we develop a new strategy for imputation of missing data in large-scale genomic studies, which adapts low-rank, structured matrix completion. Our iterative strategy enables us to impute missing data in complex configurations across multiple data platforms. In turn, we perform large-scale pathway analysis integrating gene expression, copy number, and methylation data. The advantages of the proposed statistical framework are demonstrated through simulations and real applications to breast cancer subtypes. We demonstrate superior power to identify pathway disturbances, compared with other imputation strategies. We also identify differential pathway activity across different breast tumor subtypes.

• International journal of advanced smart convergence
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• 제13권3호
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• pp.150-155
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• 2024

Genomic data plays a transformative role in medicine, biology, and forensic science, offering insights that drive advancements in clinical diagnosis, personalized medicine, and crime scene investigation. Despite its potential, the integration and analysis of diverse genomic datasets remain challenging due to compatibility issues and the specialized nature of existing tools. This paper presents the GenomeSync system, designed to overcome these limitations by utilizing the Hadoop framework for large-scale data handling and integration. GenomeSync enhances data accessibility and analysis through SQL-based search capabilities and machine learning techniques, facilitating the identification of genetic traits and the resolution of forensic cases. By pre-processing DNA profiles from crime scenes, the system calculates similarity scores to identify and aggregate related genomic data, enabling accurate prediction models and personalized treatment recommendations. GenomeSync offers greater flexibility and scalability, supporting complex analytical needs across industries. Its robust cloud-based infrastructure ensures data integrity and high performance, positioning GenomeSync as a crucial tool for reliable, data-driven decision-making in the genomic era.

• 한국IT서비스학회지
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• 제19권6호
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• pp.177-189
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• 2020

The OECD has assessed Korea as the third highest in trade facilitation worldwide. The paperless trade of Korea is world class based on uTradeHub : national e-trade service's infrastructure for trade community. Over 800 trade-related document standards provide interoperability of message exchange and trade process automation among exporters, importers, banks, customs, airlines, shippers, forwarders and trade authorities. Most one-to-one unit processes are perfectly paperless & online; however, from the perspective of process flow, there is a lack of streamlining end-to-end trade processes spread over many different parties. This situation causes the trade community to endure repetitive-redundant load for handling trade documents. The trade community has a strong demand for seamless trade flow. For streamlining the trade process, processes with data should flow seamlessly to multilateral parties. Flowing data with an optimized process is the critical success factor to accomplish seamless trade. This study proposes four critical digital trade infrastructures as a platform service : (1) data-centric Intelligent Document Recognition(IDR), (2) data-driven Digital Document Flow (DDF), (3) platform based Digital Collaboration & Communication(DCC), and (4) new digital Trade Facilitation Index (dTFI) for precise assessment of K-Trade Digital Trade Framework. The results of new dTFI analyses showed that redundant reentry load was reduced significantly over the whole trade and logistics process. This study leads to the belief that if put into real-world application can provide huge economic gains by building a new global value chain of the K-trade eco network. A new digital trade framework will be invaluable in promoting national soft power for enhancing global competitiveness of the trade community. It could become the advanced reference model of next trade facilitation infrastructure for developing countries.

• Fashion, Industry and Education
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• 제14권2호
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• pp.11-23
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• 2016

This study investigated the comparative advantages of the Bangladeshi and Vietnamese apparel industries using Global Value Chain (GVC) framework. In this study, the GVC framework was expanded to include social and environmental sustainability issues. Secondary data, for the 2012 - 2013 period, were collected and analyzed for each component of the apparel GVC. The findings indicated that while both countries have unique comparative advantages, Vietnam clearly emerged as a leader on many GVC components. Bangladesh's comparative advantage lies in lower wages, producing high volume orders, and lean manufacturing. In spite of Vietnam's higher labor costs, it has comparative advantages in higher productivity, skilled and trained workers, manufacturing of intricate styles of high quality, agility and flexible manufacturing, more developed infrastructure and logistic services as well as greater social and environmental compliances. This study contributes towards insight into best sourcing fit for fashion brand business models. Based on the findings, fashion driven companies offering more complex styles at a faster rate will benefit from choosing Vietnam. In contrast, Bangladesh might be a better choice for high volume driven companies that offer basic apparel and better value for their consumers. From theoretical perspective, the research makes an important contribution by expanding the GVC framework.

• Journal of Information Science Theory and Practice
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• 제12권3호
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• pp.49-62
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• 2024

Strategy monitoring is essential for business management and for administrators, including managers and executives, to build a data-driven organization. Having a tool that is able to visualize strategic data is significant for business intelligence. Unfortunately, there are gaps between business users and information technology departments or business intelligence experts that need to be filled to meet user requirements. For example, business users want to be self-reliant when using business intelligence systems, but they are too inexperienced to deal with the technical difficulties of the business intelligence systems. This research aims to create an automatic matching framework between the key performance indicators (KPI) formula and the data in database systems, based on ontology concepts, in the case study of Prince of Songkla University. The mapping data schema with ontology (MapDSOnto) framework is created through knowledge adaptation from the literature review and is evaluated using sample data from the case study. String similarity methods are compared to find the best fit for this framework. The research results reveal that the "fuzz.token_set_ratio" method is suitable for this study, with a 91.50 similarity score. The two main algorithms, database schema mapping and domain schema mapping, present the process of the MapDS-Onto framework using the "fuzz.token_set_ratio" method and database structure ontology to match the correct data of each factor in the KPI formula. The MapDS-Onto framework contributes to increasing self-reliance by reducing the amount of database knowledge that business users need to use semantic business intelligence.

• Structural Engineering and Mechanics
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• 제83권4호
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• pp.537-549
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• 2022

In this paper, a novel multi-feature model predictive control (MPC) framework with real-time and adaptive performances is proposed for intelligent structural control in which some drawbacks of the algorithm including, complex control rule and non-optimality, are alleviated. Hence, Linear Programming (LP) is utilized to simplify the resulted control rule. Afterward, the Whale Optimization Algorithm (WOA) is applied to the optimal and adaptive tuning of the LP weights independently at each time step. The stochastic control rule is also achieved using Kalman Filter (KF) to handle noisy measurements. The Extreme Learning Machine (ELM) is then adopted to develop a data-driven and real-time control algorithm. The efficiency of the developed algorithm is then demonstrated by numerical simulation of a twenty-story high-rise benchmark building subjected to earthquake excitations. The competency of the proposed method is proven from the aspects of optimality, stochasticity, and adaptivity compared to the KF-based MPC (KMPC) and constrained MPC (CMPC) algorithms in vibration suppression of building structures. The average value for performance indices in the near-field and far-field (El earthquakes demonstrates a reduction up to 38.3% and 32.5% compared with KMPC and CMPC, respectively.

• 한국건설관리학회논문집
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• 제25권1호
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• pp.50-61
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• 2024

사용자의 공간 요구사항 중심의 평면계획에 대한 수요가 증가함에 따라 소형 주택시장이 지속적으로 성장하고 있다. 하지만 건축주는 공간 구성이나 비용 견적과 같은 근거를 기반으로 평면요구사항을 개진하는데 매우 제한적인 수단을 활용하고 있어 건축가와 같은 전문가들과의 소통에 많은 어려움을 겪고 있다. 본 연구의 목적은 스케치 정보 기반의 공간 요구사항을 BIM 모델의 3D 건물구성요소로 자동 변환하여 사용자의 공간에 대한 이해를 돕고, 초기 설계단계에서 예산 산정을 지원하기 위한 건물성능분석 정보를 제공할 수 있는 프레임워크 개발에 있다. 본 연구의 방법론은 프로세스 모델 개발, 프레임워크 구현 및 검증단계로 구성되었다. 프로세스 모델 개발은 프레임워크의 데이터 흐름을 묘사하고 프레임워크에 필요한 기능을 정의하는 단계이며, 프레임워크 구현은 프로세스 모델을 기반으로 시스템 인터페이스와 사용자 인터페이스를 개발하고, 이종 시스템 간의 연동 방식을 정의하는 단계이다. 검증단계는 개발된 프레임워크가 스케치 정보로 표현된 공간 요구사항을 BIM 모델의 벽, 바닥, 지붕과 같은 건물 구성요소 객체들로 자동 변환할 수 있는가를 검증하였다. 또한 프레임워크가 BIM 모델을 기반으로 재료 및 에너지 비용을 자동으로 산출할 수 있는가를 검증하였다. 프레임워크를 통해 사용자는 스케치 정보를 기반으로 3D 건물 구성요소를 효율적으로 생성할 수 있으며, 생성된 BIM 모델을 통해 공간을 이해하고 건물성능분석 정보를 제공받을 수 있다.