• Journal of Energy Engineering
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• v.15 no.1 s.45
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• pp.74-81
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• 2006

In this study, on the basis of an analytic hierarchy process (AHP) method and through a questionnaire on subjective preference and importance, various power supply systems were comprehensively compared with multiple decision criteria such as environmental, social, healthy, and economic viewpoints and then overall priority was assessed. When a decision-making problem is modelled by a hierarchy structure, the AHP method is regarded as a useful tool for extracting subjective opinions via the aforementioned questionnaire. Here, the overall preferences were obtained by linearly aggregating weighting vector and preference matrix. The energy systems such as nuclear, coal, and LNG power plants were selected because they took share over 90% of domestic electricity supply in Korea. Furthermore, wind power and photovoltaic solar systems were included as representative renewable energy systems in Korea. According to the results of this demonstration study, the following comprehensive comparison indicators were yielded: 1) weighting factors for 4 types of main criteria as well as for 11 types of sub-criteria; 2) preference valuation for 7 types of energy systems under consideration; 3) overall score for each energy systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.3841-3848
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• 2012

The process of an analysis of alternatives(AoA) attempts to select the best and balanced solution among a set of multiple candidate solutions under the constraints of cost, schedule, performance and risk(CSPR). The traditional AoA for the acquisition of a new weapon system has usually centered on the sequence of the requirement analysis, design synthesis, and cost estimation. An improved process for AoA is developed in this paper based on a multi-objective decision-making method, which is intended to be applied in the design concept refinement and material solution analysis stage for the acquisition of naval surface ships. The presentation of the proposed AoA approach is then followed by a case study for the next generation multi-purpose training ship based on the principles of systems engineering and also using the models of the effectiveness measure, cost estimation, and risk assessments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6C
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• pp.585-593
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• 2007

For the improvement of coding efficiency, the H.264 standard uses new coding tools such as VBS, 1/4-pel accurate ME, multiple references, intra prediction, loop filter, etc. Using these coding tools, H.264 has achieved significant improvements from rate-distortion point of view compared to existing standards. However, the encoder complexity is greatly increased due to these coding tools. We focus on the complexity reduction method of intra-mode decision. Our algorithm first restricts selective prediction modes of Intra4x4 using a simple preprocessing. The prediction modes of Intra4x4 are used for restricting those of the other inter-modes. Simulation results show that the proposed method outperforms other conventional methods and save about 82% of total encoding time.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.1
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• pp.1-10
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• 2013

Major issues in water supply service have changed from expansion of service area to improvement of service quality, i.e., water quality and safety, and early response to emergency situation. This change in the service concept triggers the perceptions of limitation with the current centralized water supply system and of necessities of decentralized (distributed) water supply system (DWSS), which can make up the limitations. DWSS can reduce the possibility of water supply outage by establishing multiple barriers such as emergency water supply system, and secure better water quality by locating treatment facilities neighboring consumers. On the other hand, fluctuation of water demand will be increased due to the reduced supply area, which makes difficult to promptly respond the fluctuating demand. In order to supplement this, hybrid water supply system was proposed, which combined DWSS with conventional water supply system using distributing reservoir to secure the stability of water supply. The Optimal connection point of DWSS to existing water supply network in urban area was determined by simulating a supply network using EPANET. Optimal location of decentralized water treatment plant (or connection point) is a nodal point where changes in pressure at other nodal points can be minimized. At the same time, the optimal point should be selected to minimize hydraulic retention time in supply network (water age) to secure proper water quality. In order to locate the point where these two criteria are satisfied optimally, Distance measure method, one of multi-criteria decision making was employed to integrate the two results having different dimensions. This methodology can be used as an efficient decision-support criterion for the location of treatment plant in decentralized water supply system.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.493-497
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• 2016

Infrared (IR) imaging is capable of detecting targets that are not visible at night, thus it has been widely used for the security and defense system. However, the quality of the IR image is often degraded by low resolution and noise corruption. This paper addresses target segmentation with the IR image. Multiple regions of interest (ROI) are extracted by the multi-level segmentation and targets are segmented from the individual ROI. Each level of the multi-level segmentation is composed of a k-means clustering algorithm an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering algorithm initializes the parameters of the Gaussian mixture model (GMM) and the EM algorithm iteratively estimates those parameters. Each pixel is assigned to one of clusters during the decision. This paper proposes the selection and the merging of the extracted ROIs. ROI regions are selectively merged in order to include the overlapped ROI windows. In the experiments, the proposed method is tested on an IR image capturing two pedestrians at night. The performance is compared with conventional methods showing that the proposed method outperforms others.

• Journal of Digital Convergence
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• v.16 no.1
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• pp.231-242
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• 2018

The efficient management of the Length of Stay(LOS) is important in hospital. It is import to reduce medical cost for patients and increase profitability for hospitals. In order to efficiently manage LOS, it is necessary to develop an artificial intelligence-based prediction model that supports hospitals in benchmarking and reduction ways of LOS. In order to develop a predictive model of LOS for acute stroke patients, acute stroke patients were extracted from 2013 and 2014 discharge injury patient data. The data for analysis was classified as 60% for training and 40% for evaluation. In the model development, we used traditional regression technique such as multiple regression analysis method, artificial intelligence technique such as interactive decision tree, neural network technique, and ensemble technique which integrate all. Model evaluation used Root ASE (Absolute error) index. They were 23.7 by multiple regression, 23.7 by interactive decision tree, 22.7 by neural network and 22.7 by esemble technique. As a result of model evaluation, neural network technique which is artificial intelligence technique was found to be superior. Through this, the utility of artificial intelligence has been proved in the development of the prediction LOS model. In the future, it is necessary to continue research on how to utilize artificial intelligence techniques more effectively in the development of LOS prediction model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1666-1689
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• 2021

The red line of Permanent Basic Farmland is the most important part in the "three-line" demarcation of China's national territorial development plan. The scientific and reasonable delineation of the red line is a major strategic measure being taken by China to improve its ability to safeguard the practical interests of farmers and guarantee national food security. The delineation of Permanent Basic Farmland zoning (DPBFZ) is essentially a multi-objective optimization problem. However, the traditional method of demarcation does not take into account the synergistic development goals of conservation of cultivated land utilization, ecological conservation, or urban expansion. Therefore, this research introduces the idea of artificial immune optimization and proposes a multi-objective model of DPBFZ red line delineation based on a clone selection algorithm. This research proposes an objective functional system consisting of these three sub-objectives: optimal quality of cropland, spatially concentrated distribution, and stability of cropland. It also takes into consideration constraints such as the red line of ecological protection, topography, and space for major development projects. The mathematical formal expressions for the objectives and constraints are given in the paper, and a multi-objective optimal decision model with multiple constraints for the DPBFZ problem is constructed based on the clone selection algorithm. An antibody coding scheme was designed according to the spatial pattern of DPBFZ zoning. In addition, the antibody-antigen affinity function, the clone mechanism, and mutation strategy were constructed and improved to solve the DPBFZ problem with a spatial optimization feature. Finally, Tongxu County in Henan province was selected as the study area, and a controlled experiment was set up according to different target preferences. The results show that the model proposed in this paper is operational in the work of delineating DPBFZ. It not only avoids the adverse effects of subjective factors in the delineation process but also provides multiple scenarios DPBFZ layouts for decision makers by adjusting the weighting of the objective function.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.806-816
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• 2011

Interest about social security has recently increased in favor of safety for infrastructure. In addition, advances in computer vision and pattern recognition research are leading to video-based surveillance systems with improved scene analysis capabilities. However, such video surveillance systems, which are controlled by human operators, cannot actively cope with dynamic and anomalous events, such as having an invader in the corporate, commercial, or public sectors. For this reason, intelligent surveillance systems are increasingly needed to provide active social security services. In this study, we propose a core technique for intelligent surveillance system that is based on swarm robot technology. We present techniques for invader enclosing using swarm robots based on multiple distributed object environment. The proposed methods are composed of three main stages: location estimation of the object, specified object tracking, and decision of the cooperative behavior of the swarm robots. By using particle filter, object tracking and location estimation procedures are performed and a specified enclosing point for the swarm robots is located on the interactive positions in their coordinate system. Furthermore, the cooperative behaviors of the swarm robots are determined via the result of path navigation based on the combination of potential field and wall-following methods. The results of each stage are combined into the swarm robot-based invader-enclosing technique on multiple distributed object environments. Finally, several simulation results are provided to further discuss and verify the accuracy and effectiveness of the proposed techniques.

• Journal of KIISE
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• v.43 no.2
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• pp.163-176
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• 2016

The contention overhead on the same channel in an NoC architecture can significantly increase a communication delay due to the simultaneous communication requests that occur. To reduce the overall overhead, we propose task-to-tile binding techniques for an NoC-based manycore platform, whereby it is assumed that the task mapping decision has already made. Since the NoC architecture may have multiple memory tiles as its size grows, memory clustering is used to balance the load of memory by making applications access different memory tiles. We assume that the information on the communication overhead of each application is known since it is specified in a dataflow task graph. Using this information, this paper proposes two heurisitics that perform binding of multiple tasks at once based on a proper memory clustering method. Experiments with an NoC simulator prove that the proposed heurisitic shows performance gains that are 25% greater than that of the previous binding heuristic.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.2A
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• pp.139-147
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• 2008

DVB-S2 (Digital Video Broadcasting-Satellite, Version 2) system transmits frames which adapt their structures based on the channel conditions, thus requiring simultaneous detection of the start of the Same (SoF) and the frame structure at the initial acquisition stage of the receiver. Also, a very low value of the minimum operating signal-to-noise ratio (SNR) for the acquisition necessitates a method utilizing multiple received frames to meet the required performance. In this paper, performance of joint time synchronization and frame structure detection methods using multiple DVB-S2 frames is evaluated by deriving the detection error probability. In particular, we evaluate the performance and complexity variations when the soft- and hard-decision values of the signal correlation output are used, present the synchronization parameters to optimize the performance, and verify the analysis results via computer simulations.