• Korean Journal of Construction Engineering and Management
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• v.7 no.4 s.32
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• pp.177-183
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• 2006

Risk-based estimation has been successfully introduced into the construction industry. By incorporating historical data associated with probability analysis, risk-based estimate is an effective decision support aid in considering whether to launch a particular project. The industry challenges, however, especially related with management issues, such as labor shortage, wage growth, and supply chain complexity, have often resulted in poor cost performance. The insufficient assessing the project characteristics (i.e., resource availability, project complexity, and project delivery method) can be the main reasons in the poor cost performance. Because the accuracy level of cost performance prediction can be enhanced by extensive evaluation of the subject project characteristics, a new approach for predicting cost performance in an earlier stage of a project can improve the Industry substantiality, in other words, value maximization. The purpose of this paper is to develop a new methodology in developing a risk-based estimate tool by incorporating extensive project characteristics. To do this, an extensive industry survey was conducted from both private and public sectors in building industry in Korea. In addition, significant project characteristics were identified in terms of cost performance indicator. Although the data collection is limited to Korean industry the suggested approach provides the industry with a straightforward methodology in risk management. As many researchers maintained that front-end planning efforts are crucial in achieving the successful outcome in building projects, the new method for risk-based estimation can Improve the cost performance as well as enhance the fulfillment in terms of business sustainability.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.256-261
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• 2011

Labor productivity is a significant factor related to control time, cost, and quality. Many researchers have developed models to define method of measuring the relationship between productivity and various constraints such as the size of working area, maximum working hours, and the crew composition. Most of the previous research has focused on estimating productivity; however, this research concentrates on estimating labor productivity and developing time and cost data for repetitive concrete pouring activity. In Korea, "Standard Estimating" only contains the average productivity data of the construction industry, and it is difficult to predict the time and cost of any particular project; hence, there are some errors in estimating duration and cost for individual activity and project. To address these issues, this research collects data, measures productivity, and develops time and cost data using labor productivity based on field conditions from the collected data. A probabilistic approach is also proposed to develop data. A case study is performed to validate this process using actual data collected from construction sites and it is possible that the result will be used as the EVMS baseline of cost management and schedule management.

• Structural Engineering and Mechanics
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• v.14 no.1
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• pp.57-70
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• 2002

This work presents an iterative mesh partitioning approach to improve the efficiency of parallel substructure finite element computations. The proposed approach employs an iterative strategy with a set of empirical rules derived from the results of numerical experiments on a number of different finite element meshes. The proposed approach also utilizes state-of-the-art partitioning techniques in its iterative partitioning kernel, a cost function to estimate the computational cost of each submesh, and a mechanism that adjusts element weights to redistribute elements among submeshes during iterative partitioning to partition a mesh into submeshes (or substructures) with balanced computational workloads. In addition, actual parallel finite element structural analyses on several test examples are presented to demonstrate the effectiveness of the approach proposed herein. The results show that the proposed approach can effectively improve the efficiency of parallel substructure finite element computations.

• Structural Engineering and Mechanics
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• v.49 no.1
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• pp.65-80
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• 2014

This paper reports on the development of a minimum cost design model and its application for obtaining economic designs for reinforced High Strength Concrete (HSC) T-sections in bending under ultimate limit state conditions. Cost objective functions, behavior constraint including material nonlinearities of steel and HSC, conditions on strain compatibility in steel and concrete and geometric design variable constraints are derived and implemented within the Conjugate Gradient optimization algorithm. Particular attention is paid to problem formulation, solution behavior and economic considerations. A typical example problem is considered to illustrate the applicability of the minimum cost design model and solution methodology. Results are confronted to design solutions derived from conventional design office methods to evaluate the performance of the cost model and its sensitivity to a wide range of unit cost ratios of construction materials and various classes of HSC described in Eurocode2. It is shown, among others that optimal solutions achieved using the present approach can lead to substantial savings in the amount of construction materials to be used. In addition, the proposed approach is practically simple, reliable and computationally effective compared to standard design procedures used in current engineering practice.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.256-263
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• 2009

For the power system to keep in a stable operating state, sufficient ancillary services must be available to respond to credible contingency events and return the power system to a satisfactory operating state in the case of contingencies as well as blackout events within specified predefined limits. The logical and reasonable bases of valuing and pricing the ancillary services are required to reach the common ground among market participants. The total amount of black start service transactions is quite small compared to the total ancillary service transactions as well as energy market transactions. Black start services must be provided as one of the ancillary services in the deregulated electricity market. In order to procure and remunerate black start services, it is necessary to quantify the value of the black start sources within the power system. In this paper, an approach to assess the value of the black start service is presented based on the cost-of-service solution. Financial simulation of the influence on market participants for the proposed approach on the service is carried out. The cost of the black start service is allocated in accordance with the principle of "causer pays", and the cost is shared by the producers and consumers equally that created the requirement for the service. Under the present electricity market, the mechanism to recover the cost is not implemented, a new approach to the ancillary services to provide incentive for the service providers has to be studied in the near future.

• 한국IT서비스학회:학술대회논문집
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• 2005.11a
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• pp.345-355
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• 2005

As the portion of information systems(IS) budget to the total government budget becomes greater, the cost estimation of IS development and maintenance projects is recognized as one of the most important problems to be resolved for quantitative and efficient management of IS budget. The primary concern in the cost estimation of IS projects is to estimate software development cost. In this paper, we propose a new method to estimate software cost using support vector regression(SVR), which has attracted considerable attention because of its good performance and theoretical clearness. The paper is the first study which apply SVR to software cost estimation.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.387-388
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• 2020

As the utilization of microservice architectural style in diverse applications are increasing, the microservice deployment cost became a concern for many companies. We propose an approach to reduce the deployment cost by generating an algorithm which minimizes the cost of basic operation of a physical machine and the cost of resources assigned to a physical machine. This algorithm will produce optimal resource allocation and deployment location based on genetic algorithm process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.149-158
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• 2019

The scheduling of planned maintenance problem of a system consisting of a number of components was studied. The purpose of maintenance scheduling is to minimize the cost of maintaining long-term operations. On the system side, the cost of a system shutdown can be minimized by grouping and inspecting a number of components. In addition, proper inspection cycles can be selected for each component to identify the failure sufficiently early to minimize the cost of the failure. To reduce the complexity of the calculations, the 'base interval approach' used in previous studies was applied and, in addition, the inspection cost savings from simultaneous inspections of multiple components were considered. To compare the effectiveness of inspection cost savings, this paper presents the results of simulation analysis performed by referring to the cases in the existing studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3182-3203
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• 2023

With the growing adoption of cloud-based technologies, maintaining the privacy and security of cloud data has become a pressing issue. Privacy-preserving encryption schemes are a promising approach for achieving cloud data security, but they require careful design and implementation to be effective. The integrated approach to cloud data security that we suggest in this work uses CogniGate: the orchestrated permissions protocol, index trees, blockchain key management, and unique Opacus encryption. Opacus encryption is a novel homomorphic encryption scheme that enables computation on encrypted data, making it a powerful tool for cloud data security. CogniGate Protocol enables more flexibility and control over access to cloud data by allowing for fine-grained limitations on access depending on user parameters. Index trees provide an efficient data structure for storing and retrieving encrypted data, while blockchain key management ensures the secure and decentralized storage of encryption keys. Performance evaluation focuses on key aspects, including computation cost for the data owner, computation cost for data sharers, the average time cost of index construction, query consumption for data providers, and time cost in key generation. The results highlight that the integrated approach safeguards cloud data while preserving privacy, maintaining usability, and demonstrating high performance. In addition, we explore the role of differential privacy in our integrated approach, showing how it can be used to further enhance privacy protection without compromising performance. We also discuss the key management challenges associated with our approach and propose a novel blockchain-based key management system that leverages smart contracts and consensus mechanisms to ensure the secure and decentralized storage of encryption keys.

• Journal of Energy Engineering
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• v.24 no.4
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• pp.146-158
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• 2015

A bottom-up approach has been conducted to estimate greenhouse gas (GHG) emission and to analyze the marginal abatement cost for the Korean horticulture energy sector. With the systematically derived activity and energy balance data, the BAUs have been estimated, along with the marginal abatement cost over the period 2010 through 2030. The result from the marginal abatement cost analysis may provide general guidelines and procedures for the establishment of GHG abatement polices.