• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.3
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• pp.215-221
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• 2012

In this paper, we introduce an optimization method to improve pursuit performance of a pursuer in a pursuit-evasion game (PEG). Pursuers build a probability map and employ a hybrid pursuit policy which combines the merits of local-max and global-max pursuit policies to search and capture evaders as soon as possible in a 2-dimensional space. We propose an episodic parameter optimization (EPO) algorithm to learn good values for the weighting parameters of a hybrid pursuit policy. The EPO algorithm is performed while many episodes of the PEG are run repeatedly and the reward of each episode is accumulated using reinforcement learning, and the candidate weighting parameter is selected in a way that maximizes the total averaged reward by using the golden section search method. We found the best pursuit policy in various situations which are the different number of evaders and the different size of spaces and analyzed results.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.11
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• pp.1067-1074
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• 2010

In this study, RBDO(Reliability Based Design Optimization) was performed for a supersonic double-wedge inlet. By considering uncertainty of design with given design space, the pressure recovery was transformed into the probabilistic constraint while the inlet drag was considered as a deterministic objective function. To save computational analysis cost and to search good design space, Latin-Hypercube design of experiment and the Kriging model were incorporated and then RBDO was performed. Monte-Carlo simulation was performed to verify the accuracy of AFORM(Advanced First Order Reliability Method). It was found that AFORM result agreed very well with the Monte-Carlo simulation result. The system reliability was guaranteed by considering uncertainty of the design variables. In case of considering diverse uncertainty of system design, RBDO was found to be useful.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.169-174
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• 2018

There are many CCTV cameras connected to the video surveillance and monitoring center for the safety of citizens, and it is difficult for a few monitoring agents to monitor many channels of videos. In this paper, we propose an intelligent video surveillance system utilizing a safety map to efficiently monitor many channels of CCTV camera videos. The safety map establishes the frequency of crime occurrence as a database, expresses the degree of crime risk and makes it possible for agents of the video surveillance center to pay attention when a woman enters the crime risk area. The proposed gender classification method is processed in the order of pedestrian detection, tracking and classification with deep training. The pedestrian detection and tracking uses Adaboost algorithm and probabilistic data association filter, respectively. In order to classify the gender of the pedestrian, relatively simple AlexNet is applied to determine gender. Experimental results show that the proposed gender classification method is more effective than the conventional algorithm. In addition, the results of implementation of intelligent video security system combined with safety map are introduced.

• The Journal of Society for e-Business Studies
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• v.13 no.2
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• pp.213-223
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• 2008

The efficient discovery of services from a large scale collection of services has become an important issue[7, 24]. We studied a syntactic method for Web service discovery, rather than a semantic method. We regarded a service discovery as a retrieval problem on the proprietary XML formats, which were service descriptions in a registry DB. We modeled services and queries as probabilistic values and devised similarity-based retrieval techniques. The benefits of our way are follows. First, our system supports ranked service retrieval by keyword search. Second, we considers both of UDDI data and WSDL definitions of services amid query evaluation time. Last, our technique can be easily implemented on the off-theshelf DBMS and also utilize good features of DBMS maintenance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.63-70
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• 2016

To increase throughput efficiency and improve performance, FTN(Faster Than Nyquist) method and LDPC(Low Density Parity Code) codes are employed in DVB-S3 system. In this paper, we proposed efficient turbo equalization model to minimize inter symbol interference induced by FTN transmission. This paper introduces two conventional scheme employing SIC(Successive Interference Cancellation) and BCJR equalizer. Then, we proposed new scheme to resolve problems in this two conventional scheme. To make performance improved in turbo equalization model, the outputs of LDPC and BCJR equalizer are iteratively exchange probabilistic information. In fed LDPC outputs as extrinsic informa tion of BCJR equalizer. we split LDPC output to separate bit probabilities. We compare performance of proposed scheme to that of conventional methods through using simulation in AWGN(Additive White Gaussian Noise) channel. We confirmed that performance was improved compared to conventional methods as increasing throughput parameters of FTN.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.2
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• pp.70-78
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• 2013

Plants which are having conditions of high temperature and pressure always are exposed to danger. In order to prevent unexpected accidents, safety management that can effectively and appropriately examine facilities is required in plant operation. RBI(Risk-Based Inspection) technology in API 581 is one of standard management technique for evaluating risk on petroleum plants. There are qualitative and quantitative assessments in RBI methodology. Quantitative evaluation step is complex and required much information, so high-risk facilities in plant are selected firstly by qualitative method. Qualitative RBI is performed by choosing the answer in prepared questionnaire. However, it is difficult to believe thoroughly results from survey including ambiguous information. In this study, the procedure of qualitative RBI analysis with considering probability distribution concept were proposed by using Monte Carlo simulation method in order to increase reliability in spite of uncertain factors. In addition, qualitative risk of cooling system for LNG plant was evaluated using proposed procedure. Although 20 items of total 39 assessment items are applied to uncertain factors, risk section of high probability(89%) were verified. The detailed results were described in manuscript.

• Journal of the Korea Society for Simulation
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• v.23 no.1
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• pp.33-42
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• 2014

In this paper we analyzed the search patterns for the anti-submarine warfare (ASW) surface ships cooperating with ASW helicopters. For this purpose, we modeled evasive motion of a submarine with a probabilistic method. And maneuvers and search actions of ships and helicopters participating in the anti-submarine search mission are designed. And for each simulation scenario, the case where a ship and a helicopter searches a submarine independently according to its optimized search pattern is compared with the case where the search platforms participate in the ASW mission cooperatively. Based on the simulation results, we proposed the reconfigured search patterns that help cooperative ASW surface ships increase the total cumulative detection probability (CDP).

• Journal of Wetlands Research
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• v.11 no.1
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• pp.49-64
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• 2009

Rainfall-runoff models are used for efficient management, distribution, planning, and design of water resources in accordance with the process of hydrologic cycle. The models simplify the transition of rainfall to runoff as rainfall through different processes including evaporation, transpiration, interception, and infiltration. As the models simplify complex physical processes, gaps between the models and actual rainfall events exist. For more accurate simulation, appropriate models that suit analysis goals are selected and reliable long-term hydrological data are collected. However, uncertainty is inherent in models. It is therefore necessary to evaluate reliability of simulation results from models. A number of studies have evaluated uncertainty ingrained in rainfall-runoff models. In this paper, Meta-Gaussian method proposed by Montanari and Brath(2004) was used to assess uncertainty of simulation outputs from rainfall-runoff models. The model, which estimates upper and lower bounds of the confidence interval from probabilistic distribution of a model's error, can quantify global uncertainty of hydrological models. In this paper, Meta-Gaussian method was applied to analyze uncertainty of simulated runoff outputs from $Vflo^{TM}$, a physically-based distribution model and HEC-HMS model, a conceptual lumped model.

• Journal of the Korea Institute of Building Construction
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• v.17 no.3
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• pp.287-294
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• 2017

Recently the construction project is becoming large-sized, complicated, and modernize. This has increased the uncertainty of construction risk. Therefore, studies should be followed regarding scientifically identifying the risk factors, quantifying the frequency and severity of risk factors in order to develop a model that can quantitatively evaluate and manage the risk for response the increased risk in construction. To address the problem, this study analyze the probability distribution of risk causes, the probability of occurrence and frequency of the specific risk level through Monte Carlo simulation method based on the accident data caused at construction sites. In the end, this study derives quantitative analysis by analyzing the amount of risk and probability distributions of accident causes. The results of this study will be a basis for future quantitative risk management models and risk management research.