• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.1099-1110
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• 2020

This research tests the effects of institutional pressures, the use of performance measurement systems and accountability, and moderation effects of human resource capability between institutional pressures and the use of performance measurement systems in the Local Government institutions in Indonesia. The research aims to provide empirical evidence both quantitatively and qualitatively that isomorphism institutional pressures occurred in the scope of implementation of the performance measurement system and accountability in the public sector organizations and to show the importance of human resource capability enhancement in reducing external pressure impact. In addition, it tries to develop the correlation model of institutional pressures, human resource capability, implementation of the performance measurement system, and accountability of public sector organizations. The research used mixed methods with sequential explanatory design. The data collection used surveys and interviews in 209 regency/Special Region of Yogyakarta and Central Java local governments as samples. The research result indicated that the institutionalization process of the performance measurement is influenced by institutional pressures, especially coercive and mimetic pressures. Human resource capability was unable to weaken institutional pressures effects in the performance measurement system implementation. The research also proved that the use of a performance measurement system was able to improve local government institution accountability.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.46-51
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• 2015

The explosive growth of data and the rapidly changing technical social evolution new analysis paradigm for predicting and reacting the future the past and present ig data. Prescriptive analysis has a fundamental difference because can support specific behaviors and results according to user's goals with defin researchers establish judgments and activities achiev the goals. However research methods not widely implemented and even the terminology, Prescriptive analysis, is still unfamiliar. This paper thus propose an infrastructure in the prescriptive analysis field with key considerations for enhancing capability of researchers through a case study based on InSciTe Advisory developed with scientific big data. InSciTe Advisory system s developed in 2013, and offers a prescriptive analytics report which contains various As-Is analysis results and To-Be analysis results 5W1H methodology. InSciTe Advisory therefore shows possibility strategy aims to reach a target role model group. Through the availability and reliability of the measurement model the evaluation results obtained relative advantage of 118.8% compared to Elsevier SciVal.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.1025-1026
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• 2006

The approach, for ensuring the quality and safety of a railway software can be considered with two points of views seeing from products, and from processes. The process point of view is to validate maturity of the organizations in accordance to the judging processes of organizations, which are specified by CMMI(Capability Maturity Model Integration) or SPICE(Software Process Improvement and Capability dEtermination : ISO/IEC15504). In this paper, we are trying to find approaches to estimate the maturity of manufacturer and assessment organization in the railway system.

• 한국연소학회:학술대회논문집
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• 2005.10a
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• pp.58-63
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• 2005

As fuel cells approach commercialization, hydrogen production becomes a critical step in the overall energy conversion pathway. Reforming is a process that produces a hydrogen-rich gas from hydrocarbon fuels. Hydrogen production via autothermal reforming (ATR) is particularly attractive for applications that demand a quick start-up and response time in a compact size. However, further research is required to optimize the performance of autothermal reformers and accurate models of reactor performance must be developed and validated. The design includes the requirement of accommodating a wide range of experimental set ups. Factors considered in the design of the reformer are capability to use multiple fuels, ability to vary stoichiometry, precise temperature and pressure control, implementation of enhancement methods, capability to implement variable catalyst positions and catalyst arrangement, ability to monitor and change reactant mixing, and proper implementation of data acquisition. A model of the system was first developed in order to calculate flowrates, heating, space velocity, and other important parameters needed to select the hardware that comprises the reformer. Predicted performance will be compared to actual data once the reformer construction is completed. This comparison will quantify the accuracy of the model and should point to areas where further model development is required. The end result will be a research tool that allows engineers to optimize hydrogen production via autothermal reformation.

• Journal of Mechanical Science and Technology
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• v.20 no.6
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• pp.864-873
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• 2006

As fuel cells approach commercialization, hydrogen production becomes a critical step in the overall energy conversion pathway. Reforming is a process that produces a hydrogen-rich gas from hydrocarbon fuels. Hydrogen production via autothermal reforming (ATR) is particularly attractive for applications that demand a quick start-up and response time in a compact size. However, further research is required to optimize the performance of autothermal reformers and accurate models of reactor performance must be developed and validated. The design includes the requirement of accommodating a wide range of experimental set ups. Factors considered in the design of the reformer are capability to use multiple fuels, ability to vary stoichiometry, precise temperature and pressure control, implementation of enhancement methods, capability to implement variable catalyst positions and catalyst arrangement, ability to monitor and change reactant mixing, and proper implementation of data acquisition. A model of the system was first developed in order to calculate flowrates, heating, space velocity, and other important parameters needed to select the hardware that comprises the reformer. Predicted performance will be compared to actual data once the reformer construction is completed. This comparison will quantify the accuracy of the model and should point to areas where further model development is required. The end result will be a research tool that allows engineers to optimize hydrogen production via autothermal reformation.

• Journal of Korea Technology Innovation Society
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• v.17 no.2
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• pp.380-420
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• 2014

We increasingly see the importance of employees acquiring enough expert capability or innovation capability to prepare for ever growing uncertainties in their operation domains. However, despite the above circumstances, there have not been an enough number of researches on how operational input components for employees' innovation outcome, innovation activities such as acquisition, exercise and promotion effort of employee's innovation capability, and their resulting innovation outcome interact with each other. This trend is believed to have been resulted because most of the current researches on innovation focus on the units of country, industry and corporate entity levels but not on an individual corporation's innovation input components, innovation outcome and innovation activities themselves. Therefore, this study intends to avoid the currently prevalent study frames and views on innovation and focus more on the strategic policies required for the enhancement of an organization's innovation capabilities by quantitatively analyzing employees' innovation outcomes and their most suggested relevant innovation activities. The research model that this study deploys offers both linear and structural model on the trio of learning, innovation capability and innovation outcome, and then suggests the 4 relevant hypotheses which are quantitatively tested and analyzed as follows: Hypothesis 1] The different levels of innovation capability produce different innovation outcomes (accepted, p-value = 0.000<0.05). Hypothesis 2] The different amounts of learning time produce different innovation capabilities (rejected, p-value = 0.199, 0.220>0.05). Hypothesis 3] The different amounts of learning time produce different innovation outcomes. (accepted, p-value = 0.000<0.05). Hypothesis 4] the innovation capability acts as a significant parameter in the relationship of the amount of learning time and innovation outcome (structural modeling test). This structural model after the t-tests on Hypotheses 1 through 4 proves that irregular on-the-job training and e-learning directly affects the learning time factor while job experience level, employment period and capability level measurement also directly impacts on the innovation capability factor. Also this hypothesis gets further supported by the fact that the patent time absolutely and directly affects the innovation capability factor rather than the learning time factor. Through the 4 hypotheses, this study proposes as measures to maximize an organization's innovation outcome. firstly, frequent irregular on-the-job training that is based on an e-learning system, secondly, efficient innovation management of employment period, job skill levels, etc through active sponsorship and energization community of practice (CoP) as a form of irregular learning, and thirdly a model of Yί=f(e, i, s, t, w)+${\varepsilon}$ as an innovation outcome function that is soundly based on a smart system of capability level measurement. The innovation outcome function is what this study considers the most appropriate and important reference model.

• International Journal of Quality Innovation
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• v.6 no.1
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• pp.109-118
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• 2005

The parameter design is the most emphasized measure by researchers for a new products development. It is critical for makers to achieve simultaneously in both the time-to-market production and the quality enhancement. However, there are difficulties in practical application, such as (1) complexity and nonlinear relationships co-existed among the system's inputs, outputs and control parameters, (2) interactions occurred among parameters, (3) where the adjustment factors of Taguchi's two-phase optimization procedure cannot be sure to exist in practice, and (4) for some reasons, the data became lost or were never available. For these incomplete data, the Taguchi methods cannot treat them well. Neural networks have a learning capability of fault tolerance and model free characteristics. These characteristics support the neural networks as a competitive tool in processing multivariable input-output implementation. The successful fields include diagnostics, robotics, scheduling, decision-making, prediction, etc. This research is a case study of spherical annealing model. In the beginning, an original model is used to pre-fix a model of parameter design. Then neural networks are introduced to achieve another model. Study results showed both of them could perform the highest spherical level of quality.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.74-83
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• 2018

It is very crucial activities that Korean army have to detect and recognize enemy's locations and types of weapon of their artillery firstly for effective operation of friendly force's artillery weapons during wartime. For these activities, one of the most critical artillery weapon systems is the anti-artillery radar (hereafter; radars) for immediate counter-fire operations against the target. So, in early wartime these radar's roles are very important for minimizing friendly force's damage because arbiters have to recognize a several enemy's artillery positions quickly and then to take an action right away. Up to date, Republic of Korea Army for tactical artillery operations only depends on individual commander's intuition and capability. Therefore, we propose these radars allocation model based on integer programming that combines ArcGIS (Geographic Information System) analysis data and each radar's performances which include allowable specific ranges of altitude, azimuth (FOV; field of view) and distances for target detection, and weapons types i.e., rocket, mortars and cannon ammo etc. And we demonstrate the effectiveness of their allocation's solution of available various types of radar asset through several experimental scenarios. The proposed model can be ensured the optimal detection coverage, the enhancement of artillery radar's operations and assisting a quick decision for commander finally.

• Journal of Astronomy and Space Sciences
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• v.39 no.4
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• pp.181-194
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• 2022

Korea Pathfinder Lunar Orbiter (KPLO), also known as Danuri, was successfully launched on 4 Aug. from Cape Canaveral Space Force Station using a Space-X Falcon-9 rocket. Flight dynamics (FD) operational readiness was one of the critical parts to be checked before the flight. To demonstrate FD software's readiness and enhance the operator's contingency response capabilities, KPLO FD specialists planned, organized, and conducted four simulations and two rehearsals before the KPLO launch. For the efficiency and integrity of FD simulation and rehearsal, different sets of blind test data were prepared, including the simulated tracking measurements that incorporated dynamical model errors, maneuver execution errors, and other errors associated with a tracking system. This paper presents the simulation and rehearsal results with lessons learned for the KPLO FD operational readiness checkout. As a result, every functionality of FD operation systems is firmly secured based on the operation procedure with an enhancement of contingency operational response capability. After conducting several simulations and rehearsals, KPLO FD specialists were much more confident in the flight teams' ability to overcome the challenges in a realistic flight and FD software's reliability in flying the KPLO. Moreover, the results of this work will provide numerous insights to the FD experts willing to prepare deep space flight operations.

• The Journal of Information Systems
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• v.27 no.3
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• pp.1-24
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• 2018

Purpose The purpose of this study is to attempt to incorporate power theory to evaluate information capability of SCM adopters. Therefore, this study focuses on the relationship of information sharing, partnership quality, and information capacity according to the power intensity of the variables of SCM. and CSV value creation. Design/methodology/approach The questionnaire of SCM builder was conducted and 302 samples were analyzed. Based on the theoretical background of power and information capacity, we set up a structural equation model. Hypothesis testing and statistical analysis were done through AMOS and SPSS. Findings First, it shows that the compensation power among the constrained power has a positive effect on the partnership quality, and the legitimacy power has the positive influence only on the information sharing. Compulsive power, compensation, and legitimacy, which are generally restrictive powers, may reduce the quality of information sharing and partnership, but the results of this study are rather higher. Second, both non-binding power expertise and criterion have a positive effect on information sharing and partnership quality. Third, information sharing has a positive effect on partnership quality. Supporting a number of research results, it is well reflected in SCM attributes where interdependence is important. Fourth, information sharing and partnership quality have a positive effect on information capacity. Information literacy has become an essential element in modern management. Fifth, the enhancement of CSV value creation plays a role of a controlling variable to further strengthen information sharing through non - binding power attribute, expertise and conformity. In addition, the strengthening of CSV value creation has been shown to play a role as a controlling variable to further strengthen the quality of partnership through the non-binding power attribution, but expertise has been rejected.