• Korean Journal of Cognitive Science
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• v.22 no.2
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• pp.145-172
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• 2011

Prospective memory (PM) is memory for activities to be performed in the future, such as remembering to purchase a piece of fruit on the way home or remembering to give someone a telephone message. Theoretically, PM retrieval can be accomplished either by controlled monitoring of intended action or by a more automatic process that spontaneously responds to the presence of intended event. The present study examined the effect of meta-cognitive awareness in PM retrieval process. In Experiment 1, we manipulated PM condition with a salient cue to stimulate participants' meta-cognitive awareness. Results showed the salient cue condition spontaneously triggered remembering to perform an intended action. In Experiment 2, we manipulated participants' meta-cognitive awareness about PM task difficulty and about the degree to which cognitive capacity is required to realize the PM task. Results showed that PM retrieval process varied with meta-cognitive awareness (i.e., more resources were allocated if the PM task was expected to be difficult). These results imply that participants' meta-cognitive awareness play an important role in PM retrieval process.

• Journal of KIISE:Information Networking
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• v.29 no.6
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• pp.722-737
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• 2002

As the number of multimedia applications increases, various protocols and architectures have been proposed to provide QoS(Quality of Service) guarantees in the Internet. Most of these techniques, though, bear inherent contradiction between the scalability and the capability of providing QoS guarantees. In this paper, we propose a protocol, named DQSP(Dynamic QoS Support Protocol), which provides the dynamic resource allocation and admission control for QoS guarantees in a scalable way. In DQSP, the core routers only maintain the per source-edge router resource allocation state information. Each of the source-edge routers maintains the usage information for the resources allocated to itself on each of the network links. Based on this information, the source edge routers perform admission control for the incoming flows. For the resource reservation and admission control, DQSP does not incur per flow signaling at the core network, and the amount of state information at the core routers depends on the scale of the topology instead of the number of user flows. Simulation results show that DQSP achieves efficient resource utilization without incurring the number of user flow related scalability problems as with IntServ, which is one of the representative architectures providing end-to-end QoS guarantees.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.337-347
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• 2007

An embedded system is called a multi-mode embedded system if it performs multiple applications by dynamically reconfiguring the system functionality. Further, the embedded system is called a multi-mode multi-task embedded system if it additionally supports multiple tasks to be executed in a mode. In this Paper, we address a HW/SW partitioning problem, that is, HW/SW partitioning of multi-mode multi-task embedded applications with timing constraints of tasks. The objective of the optimization problem is to find a minimal total system cost of allocation/mapping of processing resources to functional modules in tasks together with a schedule that satisfies the timing constraints. The key success of solving the problem is closely related to the degree of the amount of utilization of the potential parallelism among the executions of modules. However, due to an inherently excessively large search space of the parallelism, and to make the task of schedulabilty analysis easy, the prior HW/SW partitioning methods have not been able to fully exploit the potential parallel execution of modules. To overcome the limitation, we propose a set of comprehensive HW/SW partitioning techniques which solve the three subproblems of the partitioning problem simultaneously: (1) allocation of processing resources, (2) mapping the processing resources to the modules in tasks, and (3) determining an execution schedule of modules. Specifically, based on a precise measurement on the parallel execution and schedulability of modules, we develop a stepwise refinement partitioning technique for single-mode multi-task applications. The proposed techniques is then extended to solve the HW/SW partitioning problem of multi-mode multi-task applications. From experiments with a set of real-life applications, it is shown that the proposed techniques are able to reduce the implementation cost by 19.0% and 17.0% for single- and multi-mode multi-task applications over that by the conventional method, respectively.

• Korean Journal of Construction Engineering and Management
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• v.13 no.4
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• pp.16-24
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• 2012

The objective of this paper is to suggest the improvement of estimating system for construction management (CM) service fee through the analysis of the previous literatures and criteria and case study. In order to do this, this paper considered the relevance of existing criteria to estimate the CM service fee, the condition of input ratio of engineering resources in the real cases, and current utilization strategy of nonresident technical engineers. Based on the analysis, the following problems were identified; a) the different estimating system for CM fee and construction supervision fee, b) impractical estimating system for the CM fee, and c) inappropriate allocation of human resources for CM. Consequently, this paper suggested the following 4 items for the improvement of the existing system; (1) modification of the current structure of CM fee calculation, (2) rationalization of current level of the CM fee which is required to be raised approximately 5.4 percent compared to design or supervision fee, (3) securement of elasticity of the input ratio of engineering resources from the inception phase, and (4) development of the utilization strategy of nonresident engineers based on the technical requirement of the jobsite. Thus, it is anticipated that this research would affect the compensation package of CM in order to make the estimation process of CM service fee more efficient and to revitalize CM as business.

• Journal of Korea Water Resources Association
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• v.41 no.1
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• pp.35-47
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• 2008

The low flow analysis is an important part in water resources engineering. Also, the results of low flow frequency analysis can be used for design of reservoir storage, water supply planning and design, waste-load allocation, and maintenance of quantity and quality of water for irrigation and wild life conservation. Especially, for identification of the uncertainty in frequency analysis, the Bayesian approach is applied and compared with conventional methodologies in at-site low flow frequency analysis. In the first manuscript, the theoretical background for the Bayesian MCMC (Bayesian Markov Chain Monte Carlo) method and Metropolis-Hasting algorithm are studied. Two types of the prior distribution, a non-data- based and a data-based prior distributions are developed and compared to perform the Bayesian MCMC method. It can be suggested that the results of a data-based prior distribution is more effective than those of a non-data-based prior distribution. The acceptance rate of the algorithm is computed to assess the effectiveness of the developed algorithm. In the second manuscript, the Bayesian MCMC method using a data-based prior distribution and MLE(Maximum Likelihood Estimation) using a quadratic approximation are performed for the at-site low flow frequency analysis.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1075-1086
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• 2019

Recently, as the incidence of climate warming and abnormal climate increases, the forecasting of hydrological factors such as precipitation and river flow is getting more complicated, and the risk of water shortage is also increasing. Therefore, this study aims to develop a model for predicting the amount of water intake in mid-term. To this end, the correlation between water intake and meteorological factors, including temperature and precipitation, was used to select input factors. In addition, the amount of water intake increased with time series and seasonal characteristics were clearly shown. Thus, the preprocessing process was performed using the time series decomposition method, and the support vector machine (SVM) was applied to the residual to develop the river intake prediction model. This model has an error of 4.1% on average, which is higher accuracy than the SVM model without preprocessing. In particular, this model has an advantage in mid-term prediction for one to two months. It is expected that the water intake forecasting model developed in this study is useful to be applied for water allocation computation in the permission of river water use, water quality management, and drought measurement for sustainable and efficient management of water resources.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.727-739
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• 1998

The main objectives o reservoir optimal operation can be described as follows : maximization of the benefits through optimal allocation of the limited water resources for various purpose; minimization of t도 costs by the flood damage in potential damaging regions and risk of dam failure, etc. through safe drainage of a bulky volume of excessive water by a proper reservoir operation. Reviewing the past research works related to reservoir operation, we can find that the study on the matter of the former has been extensively carried out in last decades rather than the matter of the latter. This study is focused on developing a methodology of optimal reservoir operation for flood control, and a case study is performed on the Chungju multipurpose reservoir in Korea. The final goal of the study is to establish a reservoir optimal operation system which can search optimal policy to compromise two conflicting objectives: downstream flood damage and dam safety-upstream flood damage. In order to reach the final goal of the study, the following items were studied : (1)validation of hydrological data using HYMOS: (2)establishment of a downstream flood routing model coupling a rainfall-runoff model and SOBEK system for 1-D hydrodynamic flood routing; (3)replication of a flood damage estimation model by a neural network; (4)development of an integrated reservoir optimization module for an optimal operation policy.

• Journal of Korean Society of Forest Science
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• v.98 no.3
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• pp.247-254
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• 2009

In this study, linear programming was applied to a case study in Gwangreung Experimental Forest of Korea Forest Research Institute investigating the effect of the desired future conditions on forest management. Considering the social, economic and ecological demands of people from the forest, the forest functions were classified into four including natural conservation, timber production, water yield and scenic conservation. The forest land areas were divided into four-types of forest functional zones and forest management prescriptions including the desired future conditions by the forest function type were established. The Model II linear programming was used in optimizing the forest management planning. The model includes management policies, as the constraints, for non-declining yield, allowable cutting area, allowable % age class distribution and allowable % species allocation as well as the land and other accounting regimes. Maximization of timber production was used the objective function. Based on the Model II formulations, the effects of the desired future conditions by the forest function type on forest management planning were investigated in terms of timber production, net present value and stand structures over time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.187-193
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• 2015

The ICT healing platform sets a couple of goals including preventing chronic diseases and sending out early disease warnings based on personal information such as bio-signals and life habits. The 2-step open system(TOS) had a relay designed between the healing platform and the storage of personal health data. It also took into account a publish/subscribe(pub/sub) service based on large-scale connections to transmit(monitor) the data processing process in real time. In the early design of TOS pub/sub, however, the same buffers were allocated regardless of connection idling and type of message in order to encode connection messages into a deflate algorithm. Proposed in this study, the dynamic buffer allocation was performed as follows: the message transmission type of each connection was first put to queuing; each queue was extracted for its feature, computed, and converted into vector through tf-idf, then being entered into a k-means cluster and forming a cluster; connections categorized under a certain cluster would re-allocate the resources according to the resource table of the cluster; the centroid of each cluster would select a queuing pattern to represent the cluster in advance and present it as a resource reference table(encoding efficiency by the buffer sizes); and the proposed design would perform trade-off between the calculation resources and the network bandwidth for cluster and feature calculations to efficiently allocate the encoding buffer resources of TOS to the network connections, thus contributing to the increased tps(number of real-time data processing and monitoring connections per unit hour) of TOS.

• Journal of Korea Water Resources Association
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• v.38 no.11
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• pp.937-946
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• 2005

The objective of the study is to develop a reservoir optimal operation model and to suggest the appropriate amount of additional water supply and optimal operation rule. The model uses multiple objective function and a global search method, SCE-UA method. The objective function is set up to maintain the storage at target level, to satisfy the water demand, and to maximize the hydropower product. To evaluate the model's applicability, the model was applied for allocating the optimal water depending on storage level changes of Seomjin dam. The results comparing optimal operation and historical data showed that hydropower product increased from $-2.29\%$ to $14.51\%$, $-5.94\%$ to $3.98\%$, and $-0.43\%$ to $6.35\%$ with varying target levels in wet, dry, and normal period, respectively. Also, The model was applied for assessing water supply capacity of Seomjin dam to satisfy increasing water demand. The dam was operated by the model on consideration of downstream flow as 0.17, 0.50, 0.70, 1.0, 1.5, and $3.0\;m^3/sec$. The results showed that in case of operating the dam with downstream flow less than $0.70\;m^3/sec$ and with target water level lower than 194.0 m, hydropower product was more than the historical operation data and existing amount of water supply was less influenced.