• 디지털융복합연구
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• 제9권2호
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• pp.141-152
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• 2011

오늘날 데이터센터는 비즈니스에서 핵심영역으로 인식되고 있으며, 이들에 대한 많은 서비스 요구는 보다 많은 에너지 소비를 낳고 있다. 따라서 데이터센터의 높은 수준의 에너지 효율성은 구축, 운영, 폐기 등 그들의 생명주기에 있어서 핵심이슈로 등장하였다. 본 연구에서는 이러한 생명기상에서 데이터센터의 그린화 수준을 진단할 수 있도록 성숙도모델에 기초한 그린데이터센터 수준진단모델을 제시한다. 본 연구에서 제시한 수준진단 모델은 엑션추어 GMM, DCEEF 등 기존 에너지평가모델 및 그린데이터센터 성숙도평가 모델을 참조하였으며, 최종적으로 건축, 공조, 전기, IT, 조직 등 데이터센터의 5개 핵심영역에 대한 진단지표를 제안하였다.

• 디지털융복합연구
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• 제5권2호
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• pp.37-45
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• 2007

A lot of organizations have been recognized innovative activities as the required process for organizational effectiveness and efficiency in those. Especially, the perceptual scope of innovation indisputability has been extended to the central and local government, and the public organization, which ultimately have the goal of public benefits. This study is to investigate the feasibility of the assessment elements consisting of framework for making a diagnosis of the level of administration innovation of local government. The elements of framework are such seven elements as innovative leadership, innovation vision and strategies, systematic infrastructure, innovative problems, innovation management, education and learning of innovation, and the perceptual level of members. The research results can provide the implications to not only local governments but also the public policy organizations who wish to extract the innovative problems and diagnose the innovation level of themselves.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.536-564
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• 2019

Soft faults are inherent in wireless sensor networks (WSNs) due to external and internal errors. The failure of processes in a protocol stack are caused by errors on various layers. In this work, impact of errors and channel misbehavior on process execution is investigated to provide an error classification mechanism. Considering implementation of WSN protocol stack, inter-process correlations of stacked and peer layer processes are modeled. The proposed model is realized through local and global decision trees for fault diagnosis. A hybrid framework is proposed to implement local decision tree on sensor nodes and global decision tree on diagnostic cluster head. Local decision tree is employed to diagnose critical failures due to errors in stacked processes at node level. Global decision tree, diagnoses critical failures due to errors in peer layer processes at network level. The proposed model has been analyzed using fault tree analysis. The framework implementation has been done in Castalia. Simulation results validate the inter-process correlation model-based fault diagnosis. The hybrid framework distributes processing load on sensor nodes and diagnostic cluster head in a decentralized way, reducing communication overhead.

• 서비스연구
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• 제4권1호
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• pp.37-47
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• 2014

최근 20여 년 동안 서비스에 대한 연구는 지속적인 발전을 거듭해 왔다. 그러나 서비스 혁신에 대한 연구접근은 아직까지도 제조업의 제품 품질 개선이라는 전통적 관점을 탈피하지 못한 것이 사실이다. 이에 본 연구는 과거 20여 년 동안 수행된 서비스 혁신에 대한 분류 선행연구를 살펴보고 각각의 연구의 한계점을 분석한 후 서비스 혁신에 있어 시계열 성이 고려되고 전 조직 차원과 구성원 차원 그리고 고객차원에 이르는 서비스 혁신 단계모형을 제시하고자 하였다. 또한 제시된 8단계의 서비스 혁신 수준을 측정할 수 있는 진단도구의 초안을 사례 기반으로 개발하였다. 본 연구는 향후 서비스 혁신을 추구하는 조직에게 현재수준에 대한 진단을 통해 향후 나아갈 방향을 제시하는 참고 모델로 활용될 수 있을 것이며, 서비스 연구자에게는 서비스 혁신의 올바른 대상과 추진방법 연구의 방향을 제시하여 향후 서비스 연구를 활성화하는데 기여할 것이다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제14권2호
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• pp.252-261
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• 2014

A Bayesian network (BN) based fault diagnosis framework for semiconductor etching equipment is presented. Suggested framework contains data preprocessing, data synchronization, time series modeling, and BN inference, and the established BNs show the cause and effect relationship in the equipment module level. Statistically significant state variable identification (SVID) data of etch equipment are preselected using principal component analysis (PCA) and derivative dynamic time warping (DDTW) is employed for data synchronization. Elman's recurrent neural networks (ERNNs) for individual SVID parameters are constructed, and the predicted errors of ERNNs are then used for assigning prior conditional probability in BN inference of the fault diagnosis. For the demonstration of the proposed methodology, 300 mm etch equipment model is reconstructed in subsystem levels, and several fault diagnosis scenarios are considered. BNs for the equipment fault diagnosis consists of three layers of nodes, such as root cause (RC), module (M), and data parameter (DP), and the constructed BN illustrates how the observed fault is related with possible root causes. Four out of five different types of fault scenarios are successfully diagnosed with the proposed inference methodology.

• Journal of information and communication convergence engineering
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• 제19권3호
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• pp.175-179
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• 2021

Enhancing the reliability of the system is important for recent system-on-chip (SoC) designs. This importance has led to studies on fault diagnosis and tolerance. Fault-injection (FI) techniques are widely used to measure the fault-tolerance capabilities of resilient systems. FI techniques suffer from limitations in relation to environmental conditions and system features. Moreover, a hardware-based FI can cause permanent damage to the target system, because the actual circuit cannot be restored. Accordingly, we propose a simulation-based FI framework based on the Verilog Procedural Interface for measuring the failure rates of SoCs caused by soft errors. We execute five benchmark programs using an ARM Cortex M0 processor and inject soft errors using the proposed framework. The experiment has a 95% confidence level with a ±2.53% error, and confirms the reliability and feasibility of using proposed framework for fault analysis in SoCs.

• 대한산업공학회지
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• 제43권2호
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• pp.100-111
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• 2017

Evaluating the performance of R&D Activity is complicated because it is hard to quantify the R&D results unlike the traditional manufacturing or service industries. Recently, to overcome this, process-focused evaluation methods applying the philosophy of quality into R&D environment have been introduced. However, these quality activities are mainly conducted without feedback system after the evaluation work is done. The aim of this study is to present a R&D quality diagnosis framework to obtain the improvement opportunities from R&D process perspective. The research is designed as follows : First, R&D standard process and R&D quality elements are derived from a literature review. Second, the diagnosis objects are obtained by investigating the R&D quality elements at each R&D steps. Third, a two-dimensional diagnosis model, which enables the objective measurement of the 'system compatibility' and 'accomplish level', is presented. The proposed method can provide an effective way to find opportunities for efficient quality improvement of R&D process.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제8권5호
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• pp.179-186
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• 2019

IT 거버넌스의 효과적인 진단 및 점검을 이루는 정보시스템 감리는 전반적인 정보시스템 진단을 통해 계획부터 구축, 운영까지의 모든 부분에 적용된다. 하지만 특성화된 대학정보화를 위한 감리체계가 정립되지 않아, 감리수행에 어려움이 있다. 따라서 이를 대학정보화 거버넌스에 적용하기 위해 감리기반의 응용 프레임워크로 내부 감리체계를 정립할 필요성이 있다. 본 논문에서는 이러한 정보시스템 감리를 기반으로, 대학 정보화에 적용할 수 있도록 개발한 대학정보시스템의 감리 응용프레임워크를 제시한다. 프레임워크를 통해 기존 감리 시스템과의 차이점을 갖으며, 이를 활용하면 실제로 대학정보화 감리에 기준을 제시하고 현장에서 손쉽게 접근하여 활용할 수 있다. 그리고 정보화 업무담당자 뿐 아니라 감리인 차원에서도 프레임워크를 통해 직접 감리에 활용할 수 있다. 프레임워크는 감리를 3대 영역으로 분류하고 UAFP 및 품질보증을 통해 대학정보시스템 감리에 적용할 수 있는 방법을 제시한다.

• 센서학회지
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• 제33권2호
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• pp.112-116
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• 2024

Gas-sensor technology for volatile organic compounds (VOC) biomarker detection offers significant advantages for noninvasive diagnostics, including rapid response time and low operational costs, exhibiting promising potential for disease diagnosis. Colorimetric gas sensors, which enable intuitive analysis of gas concentrations through changes in color, present additional benefits for the development of personal diagnostic kits. However, the traditional method of visually monitoring these sensors can limit quantitative analysis and consistency in detection threshold evaluation, potentially affecting diagnostic accuracy. To address this, we developed a machine vision platform based on metal-organic framework (MOF) for colorimetric gas sensor arrays, designed to accurately detect disease-related VOC biomarkers. This platform integrates a CMOS camera module, gas chamber, and colorimetric MOF sensor jig to quantitatively assess color changes. A specialized machine vision algorithm accurately identifies the color-change Region of Interest (ROI) from the captured images and monitors the color trends. Performance evaluation was conducted through experiments using a platform with four types of low-concentration standard gases. A limit-of-detection (LoD) at 100 ppb level was observed. This approach significantly enhances the potential for non-invasive and accurate disease diagnosis by detecting low-concentration VOC biomarkers and offers a novel diagnostic tool.

• PNF and Movement
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• 제21권1호
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• pp.129-137
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• 2023

Purpose: The physical therapy diagnosis process requires high-level background knowledge, the ability to obtain added information from patients, accurate examination skills, and a framework for transforming thoughts into a diagnostic decision. Thus, the physical therapy diagnostic process is highly complicated and difficult work. To function as autonomous professionals, physical therapists must develop effective clinical diagnosis skills. As such, mobile application aids can help with accurate and scientific diagnoses. Therefore, this study aims to develop and evaluate the usability of a mobile application for physical therapy diagnoses. Methods: In this study, a diagnostic application was developed using App Inventor, the development environment was the Chrome web browser for Windows 10, and the mobile application was run on a Google Pixel 5. The developed application was evaluated for usability by 20 physical therapists with more than 5 years of clinical experience in the musculoskeletal physical therapy field, and a usability evaluation was conducted using a 5-point Likert scale for accuracy, convenience, satisfaction, and usability. The collected Likert scores were converted into percentages and analyzed as descriptive statistics. Results: The graphical user interface consisted of an initial screen with program guidance, 18 screens presenting the algorithm, and 12 screens presenting the estimated diagnosis based on the algorithm. As such, the usability evaluation of the developed application was as follows: accuracy 100%, convenience 90%, satisfaction 91%, and usability 88%. Conclusion: The newly developed mobile application for physical therapeutic diagnoses has a high accuracy, and it will aid in building an easy and reliable physical therapy diagnosis system.