• Journal of Digital Convergence
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• v.9 no.2
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• pp.141-152
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• 2011

The data center has become an increasingly important part of most business operations. An increasing demand for computation has led to increasing industry energy consumption. Therefore, higher-than-normal rates of energy efficiency have become a core issue in the life cycle of data center. In this paper, we proposed the framework of level diagnosis for green data centre that can be used to diagnose the levels of capability maturity model. This framework contains the 5 key areas such as construction, air-conditioning, electricity, information technology, organization and indicators that can be applied as basic level diagnosis guide for green data center.

• Journal of Digital Convergence
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• v.5 no.2
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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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• v.13 no.2
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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.

• Journal of Service Research and Studies
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• v.4 no.1
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• pp.37-47
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• 2014

Researches in the services field have evolved tremendously in the last 20 years. However, researches in service innovation still follows the traditional approaches of product quality improvements. The current research reviews the relevant literature from the past, and analyzes limitations each research possess, thus suggest a service innovation framework. Also, we have developed a diagnostic tool that measures the level of service innovation driven from actual cases. The current research suggests a new road map to organizations that pursue service innovation as well as a new research direction to the researchers in the field of service innovation.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.2
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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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• v.19 no.3
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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.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.2
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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.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.179-186
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• 2019

Information system audit, which provides effective diagnosis and inspection of IT governance, is applied to all aspects from planning to development and operation. However, there is a difficulty in carrying out the audit because the system for the specialized university IT project is not developed. Therefore, it is necessary to set the internal system as the audit-based application framework in order to apply it to university IT governance. In this paper, we propose a audit-based application framework of university information system developed for university. The framework has a difference from the existing audit system. By using this framework, it is possible to present a standard for the university IT project and easily approach and use it in the field. And it can be used for direct audit through this framework in the level of the auditor as well as the HQ admin. The framework categorizes the audit into three major dimensions and suggests a method that can be applied to the university information system audit through the UAFP(University Audit Framework Process) and quality assurance.

• PNF and Movement
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• v.21 no.1
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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.

• Proceedings of the Technology Innovation Conference
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• 2000.06a
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• pp.65-83
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• 2000

In this study, we propose an expert system aided model necessary for extracting the rules, which can diagnose the success level of new product development project. For this purpose, first, we design a classification model to analyze the characteristics of $\ulcorner$parts development projects$\lrcorner$. Second, in order to select success factors, we explore literatures and interview with project managers working at large sized companies of electronic parts. And we conduct the enquete survey and statistical analysis to extract key success factors. Third, in order to decide the level of project success, we use the concept of 'Recearchitivity' as a framework of judgement criteria. Fourth, in order to extract diagnosis rules, we use expert system development tool.