• Journal of Information Technology Services
• /
• v.9 no.1
• /
• pp.27-42
• /
• 2010

Recently, many organizations are actively adopting Enterprise Architecture (EA) as a methodology to manage IT assets and build IT-based business system. However, most existing studies on EA have focused on the adoption stage of EA. Now the research concerning effective management and utilization of EA after adopting EA is keenly required. This study intended to empirically examine how the role of EA operating unit and the EA utilization capability of organizational members impact on EA performance at the post-adoption stage of EA. Based on Resource Based View (RBV), this study proposed the model and the hypotheses describing that the impact of the role of EA operating unit on EA performance is mediated by the EA utilization capability of organizational members. In order to test the hypotheses, the field survey whose respondents were seventy four Korean public agencies which have adopted EA was conducted by means of questionnaire. Data analysis was done with partial least square (PLS), which is a structural equation modeling (SEM) technique that uses a component-based approach to estimation. The results of the empirical analyses showed that the organizational operation ability of EA operating unit significantly influenced EA performance via the EA utilization capability of organizational members, but that EA education and training performed by EA operating unit did not. The results of this study provided a lot of theoretical and practical implications regarding EA management activities at the post-adoption stage of EA to enhance EA performance.

• Journal of the Korea Society for Simulation
• /
• v.26 no.1
• /
• pp.55-67
• /
• 2017

The requirement planning system of Korea military has used top down planning approach after introducing Joint Combat Development System since 2007. But this new system has not been propelled harmoniously because it does not have any connection with the current planning system. Due to current time-exhaustive analysis and assessment process in requirement planning system, it not only delays proper decision making, but also hinders understanding on the problem in a whole perspectiveand finding a reasonable solution to our problem. In this study, we present a methodology which can analyze and assess capability utilizing the weapon score of JICM(Joint Integrated Contingency Model). The process identifies capability gap from a mission-oriented perspective in the requirement planning phase and suggests an appropriate solution to our problem. A Quick Look tool which has been developed using Python Script to implement the methodology is also introduced in this study.

• Journal of Korean Society for Quality Management
• /
• v.33 no.4
• /
• pp.75-87
• /
• 2005

Generally speaking, weapon system is defined as a combination of primary system and support system which are evaluated by capability and operational availability respectively. Recently comparison of total life cycle cost shows that logistic support system is proved to be more important than primary system. However, until now systematic approach to support system development has not been applied in the area of developing support system. We need to construct a universal metric for effectiveness of logistic support system and to cut out whatever activities or support elements which do not contribute to the metric. This paper describes a new approach based on system engineering approach to logistic support system and also classifies five factors of failure, stock-out frequency, administrative delay time, active repair time and logistic delay time that have influence on operational availability of logistic support system.

• The Journal of Information Systems
• /
• v.19 no.4
• /
• pp.1-24
• /
• 2010

Over the past three decades, services have become the largest part of most industrialized nations' economies but it is the least-studied part of the economy. One approach is to develop a general theory of service with well-defined questions, tools, methods, and practical implications of society. The purpose of this study was to propose a service systems model to systematically approach a service research. For this purpose, we conducted literature review about business model and extant service systems researches. Based on a literature review, we propose a service systems model that comprises value proposition, participants, shared information/knowledge, organizational capability, value network, and technology. Implications for practice and recommendations for additional research were discussed.

• Structural Engineering and Mechanics
• /
• v.31 no.1
• /
• pp.25-38
• /
• 2009

Local failure of a primary structural component induced by direct air-blast loading may be itself a critical damage and lead to the partial or full collapse of the building. As an extensive research to mitigate blast-induced hazards in steel frame structure, a state-of-art analytical approach or high-fidelity computational nonlinear continuum modeling using computational fluid dynamics was described in this paper. The capability of the approach to produce reasonable blast pressures on a steel wide-flange section column was first evaluated. Parametric studies were conducted to observe the effects of section sizes and boundary conditions on behavior and failure of columns in steel frame structures. This study shows that the analytical approach is reasonable and effective to understand the nature of blast wave and complex interaction between blast loading and steel column behavior.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.32B no.5
• /
• pp.812-820
• /
• 1995

This paper proposes an approach of identifying nonlinear mappings from input/output data. The approach is based on the universal approximation by the fuzzy integration of local affine mappings. A connectionist model realizing the universal approximator is suggested by using a processing unit based on both the radial basis function and the weighted sum scheme. In addition, a learning method with self-organizing capability is proposed for the identifying of nonlinear mapping relationships with the given input/output data. To show the effectiveness of our approach, the proposed model is applied to the function approximation and the prediction of Mackey-Glass chaotic time series, and the performances are compared with other approaches.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.3
• /
• pp.231-240
• /
• 2001

Conventional expert systems has been criticized due to its lack of capability to adapt to the changing decision-making environments. In literature, many methods have been proposed to make expert systems more environment-adaptive by incorporating fuzzy logic and neural networks. The objective of this paper is to propose a new approach to building a self-evolving expert system inference mechanism by integrating fuzzy neural network and fuzzy rule extraction technique. The main recipe of our proposed approach is to fuzzify the training data, train them by a fuzzy neural network, extract a set of fuzzy rules from the trained network, organize a knowledge base, and refine the fuzzy rules by applying a pruning algorithm when the decision-making environments are detected to be changed significantly. To prove the validity, we tested our proposed self-evolving expert systems inference mechanism by using the bankruptcy data, and compared its results with the conventional neural network. Non-parametric statistical analysis of the experimental results showed that our proposed approach is valid significantly.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.1203-1204
• /
• 2007

In the methods for securing software quality and safety, two approaches - product centered approach and process centered approach - can be suggested. SPICE is a standard for the process improvement and the capability determination, which is planned for securing software quality and safety by the process centered approach. In this paper, general SPICE model, which is presented in ISO/IEC 15504 and Automotive SPICE model for automobile industry are analyzed. For securing railway software quality and safety, appropriate scheme to apply Automotive SPICE to railway software is proposed.

• Structural Engineering and Mechanics
• /
• v.59 no.1
• /
• pp.101-122
• /
• 2016

Elasticity solutions for bi-directional functionally graded beams subjected to arbitrary lateral loads are conducted, with emphasis on the end effects. The material is considered macroscopically isotropic, with Young's modulus varying exponentially in both axial and thickness directions, while Poisson's ratio remaining constant. In order to obtain an exact analysis of stress and displacement fields, the symplectic analysis based on Hamiltonian state space approach is employed. The capability of the symplectic framework for exact analysis of bi-directional functionally graded beams has been validated by comparing numerical results with corresponding ones in open literature. Numerical results are provided to demonstrate the influences of the material gradations on localized stress distributions. Thus, the material properties of the bi-directional functionally graded beam can be tailored for the potential practical purpose by choosing suitable graded indices.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.3
• /
• pp.16-26
• /
• 2024

Mobile edge computing (MEC) plays a crucial role in improving the performance of resource-constrained mobile devices by offloading computation-intensive tasks to nearby edge servers. However, existing methods often neglect the critical consideration of future task requirements when making offloading decisions. In this paper, we propose an innovative approach that addresses this limitation. Our method leverages recurrent neural networks (RNNs) to predict task sizes for future time slots. Incorporating this predictive capability enables more informed offloading decisions that account for upcoming computational demands. We employ genetic algorithms (GAs) to fine-tune fitness functions for current and future time slots to optimize offloading decisions. Our objective is twofold: minimizing total processing time and reducing energy consumption. By considering future task requirements, our approach achieves more efficient resource utilization. We validate our method using a real-world dataset from Google-cluster. Experimental results demonstrate that our proposed approach outperforms baseline methods, highlighting its effectiveness in MEC systems.