• Korean Journal of Construction Engineering and Management
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• v.14 no.5
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• pp.26-34
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• 2013

Recently, many companies recognize the individual human resource as a core asset of the corporate value creation and devote a lot of effort to develop and manage competency-based human resource in order to strengthen the corporate competitiveness. As the integrated construction company taking the major portion in Korean construction industry, its construction engineers perform the construction supervision task with various related parties at each stage of the life cycle of the construction project. Therefore, the competency of a construction engineer is an important factor which have a direct impact on the success of the construction project. However, the current capability evaluation scheme of the domestic construction engineers is mainly oriented on the qualification factors such as the certificates or the seniority and this is quite different from evaluating the actual ability for construction management tasks. In this point of view, this study proposes the appropriate level of proficiency in cost management by analyzing the work process and its detailed items of the cost management that is the one of the basic management items of the construction industry. Based on this, this study analyzes the current competency level of the construction engineer by comparing with the required competency of each job position and also performs the engineer's work competency analysis of each work step.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.433-441
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• 2003

We propose a new resource reservation scheme called MC-HMRSVP(Mobile clustering based-Hierarchical mobile ReSource reserVation Protcol) that is an extension of HMRSVP[3,4]. MC-HMRSVP always establishes a virtual cluster called Mobile Cluster, which includes its immediately adjacent MA(Mobile Agent) for passive reservation as well as the current MA for active reservation to which MH(Mobile Host) belongs. Our scheme also establishes the MC regardless of intra/inter region movement by GMA(Gateway Mobile Agent) function when a MH moves. To provide a general formulation on analyzing the performance in terms of reservation cost, we also model the resource reservation cost by using a simple recursive equation. Then, we show that our scheme decreases the reservation cost in comparison with the existing HMRSVP extentions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• ETRI Journal
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• v.43 no.1
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• pp.53-63
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• 2021

Cloud computing has drastically reduced the price of computing resources through the use of virtualized resources that are shared among users. However, the established large cloud data centers have a large carbon footprint owing to their excessive power consumption. Inefficiency in resource utilization and power consumption results in the low fiscal gain of service providers. Therefore, data centers should adopt an effective resource-management approach. In this paper, we present a novel load-balancing framework with the objective of minimizing the operational cost of data centers through improved resource utilization. The framework utilizes a modified genetic algorithm for realizing the optimal allocation of virtual machines (VMs) over physical machines. The experimental results demonstrate that the proposed framework improves the resource utilization by up to 45.21%, 84.49%, 119.93%, and 113.96% over a recent and three other standard heuristics-based VM placement approaches.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.35-41
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• 2002

This research introduces the development of a project-level cash flow forecasting model in construction stage based on the planned earned value and the cost from a general contractors view on a jobsite. Most previous models have been developed to assist contractors in their pre-tendering or planning stage cash flow forecasts. The critical key to cash flow forecasting at the project level is how to build a cash-out model. The basic concept is to use moving weights of cost categories in a budget over project duration. The cost categories are classified to compile resources with almost the same time lags that are based on contracting payment conditions and credit times given by suppliers or venders. For cash-in, net planned monthly-earned values are simply transferred to the cash-in forecast, to be applied there with billing time and retention money. Validation of the model involves applying data from on-going 4 projects in progress for 12 months. Based on the results of the comparative analyses through the simulation of the proposed model and the existing models, the proposed model is more accurate, flexible and simpler than traditional models to the employee of construction jobsite who is not oriented financial knowledge.

• Environmental and Resource Economics Review
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• v.18 no.4
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• pp.745-766
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• 2009

It is not valid to measure the degree of market power based on the markup of price over marginal market cost in an industry for which the market price of some inputs is not available because those inputs are then excluded in estimating the dual total cost function. If the roles of those inputs are ignored, the markup of price over marginal market cost is likely to be positive in the perfectly competitive industry. In order to have accurate market power markups for the environmentally regulated Korean iron and steel industry, in which the market price of raw material and the price of abatement capital are hard to obtain, in this paper, a dual cost function is derived given the optimal quantities of raw material and abatement capital, and then estimated jointly with the supply relation. The annual average degree of market power for the industry is estimated to be 0.49 over the period 1982~2001. Ignoring environmental regulation would overstate the degree of market power by about 8 percent.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.7
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• pp.219-230
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• 2014

In the cloud computing environment, cloud service users purchase and use the virtualized resources from cloud resource providers on a pay as you go manner. Typically, there are two billing plans for computing resource allocation adopted by large cloud resource providers such as Amazon, Gogrid, and Microsoft, on-demand and reserved plans. Reserved Virtual Machine(VM) instance is provided to users based on the lengthy allocation with the cheaper price than the one of on-demand VM instance which is based on shortly allocation. With the proper mixture allocation of reserved and on-demand VM corresponding to users' requests, cloud service providers are able to reduce the resource allocation cost. To do this, prior researches about VM allocation scheme have been focused on the optimization approach with the users' request prediction techniques. However, it is difficult to predict the expected demands exactly because there are various cloud service users and the their request patterns are heavily fluctuated in reality. Moreover, the previous optimization processing techniques might require unacceptable huge time so it is hard to apply them to the current cloud computing system. In this paper, we propose the cloud brokering system with the adaptive VM allocation schemes called A3R(Adaptive 3 Resource allocation schemes) that do not need any optimization processes and kinds of prediction techniques. By using A3R, the VM instances are allocated to users in response to their service demands adaptively. We demonstrate that our proposed schemes are able to reduce the resource use cost significantly while maintaining the acceptable Quality of Service(QoS) of cloud service users through the evaluation results.

• ETRI Journal
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• v.22 no.1
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• pp.30-37
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• 2000

Existing tree construction mechanisms are classified into source-based trees and center-based trees. The source-based trees produce a source-rooted tree with a low delay. However, for the applications with multiple senders, the management overheads for routing tables and resource reservations are too high. The center-based trees are easy to implement and manage, but a priori configuration of candidate center nodes is required, and the optimization mature such as tree cost and delay is not considered. In this paper, we propose a new multicast tree building algorithm. The proposal algorithm basically builds a non-center based shared tree. In particular, any center node is not pre-configured. In the purposed algorithm, a multicast node among current tree nodes is suitably assigned to each incoming user: Such a node is selected in a fashion that tree cost and the maximum end-to-end delay on the tree are jointly minimized. The existing and proposed algorithms are compared by experiments. In the simulation results, it is shown that the proposed algorithm approximately provides the cost saving of 30% and the delay saving of 10%, compared to the existing approaches. In conclusion, we see that the cost and delay aspects for multicast trees can be improved at the cost of additional computations.

• Health Policy and Management
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• v.5 no.2
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• pp.202-229
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• 1995

In Korea, Resource-Based Relative Value Scale(RBRVS) is suggesting to the alternative of Korean Medical Fee Schedule. This study developed to methodology of RBRVS applicable to Korean situation and applied to services of internal medicine and general surgery. Our methodology of RBRVS is basically same to Hsiao's. But there are some differences between our method and H냐매's because Korean medical situation differs to American. The first difference is method of measurement of work. The Unit of work in our study is total work including intra-servic work and pre-/post-service work. Secondly, in extrapolation, we use primary data gathered to small group of physician. Tertially, in measurement of practice cost, we directly survey to budget data of hosptials and analyse practice costs by service. Some results are presented in a companion article.

• Journal of the Optical Society of Korea
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• v.20 no.1
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• pp.36-41
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• 2016

Visible Light Communication (VLC) using Light Emitting Diodes (LEDs) within the existing lighting infrastructure can reduce the implementation cost and may gain higher throughput than radio frequency (RF) or Infrared (IR) based wireless systems. Current indoor VLC systems may suffer from poor downlink resource allocation problems and small system throughput. To address these two issues, we propose an algorithm called a conflict graph scheduling (CGS) algorithm, including a conflict graph and a scheme that is based on the conflict graph. The conflict graph can ensure that users are able to transmit data without interference. The scheme considers the user fairness and system throughput, so that they both can get optimum values. Simulation results show that the proposed algorithm can guarantee significant improvement of system throughput under the premise of fairness.