• Journal of Korea Water Resources Association
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• v.46 no.2
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• pp.171-182
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• 2013

This paper presents the application of fuzzy set theory in multi criteria decision making (MCDM). FAHP (Fuzzy Analytic Hierarchy Process) method was used to rank alternatives to find the most reasonable and efficient way of agricultural reservoir water resources assessment. 6 criteria and 10 subcriteria had been identified and compared to secure agricultural water resources. Fuzzy numbers and linguistic variables were presented to address inherently uncertain or imprecise data. Comparison analysis of decision making method was also carried out to find a way of suitable decision making and validity of FAHP was discussed.

• Journal of the Korean Institute of Educational Facilities
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• v.25 no.1
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• pp.3-12
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• 2018

Educational facilities are more uncertain about maintenance costs due to their comprehensive and long life-cycle compared to commercial buildings. In addition, maintenance of the existing post management system can not maintain the original function of education facilities continuously and economically. In order to overcome this problem, it is necessary to analyze the repair and replacement cost for the uncertainty factor in maintenance. This study propose a model to determine repair and maintenance cost and cycle of educational facility based on probabilistic estimation concept. For the analysis, Monte Carlo simulation, a probabilistic analysis method, was applied based on the repair and maintenance history data of the educational facilities in Florida. The results of this study can be used as a guideline for quantitative facility management and facility management research.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.31-36
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• 2009

Bayesian networks are known as the best tools to express and predict the domain knowledge with uncertain environments. However, bayesian learning could be too difficult to do effective and reliable searching. To solve the problems of overtime demand, the nodes should be arranged orderly, so that effective structural learning can be possible. This paper suggests the classification learning model to reduce the errors in the independent condition, in which a lot of variables exist and data can increase the reliability by calculating the each entropy of probabilities depending on each circumstances. Also efficient learning models are suggested to decide the order of nodes, that has lowest entropy by calculating the numerical values of entropy of each node in K2 algorithm. Consequently the model of the most suitably settled Bayesian networks could be constructed as quickly as possible.

• Journal of Construction Engineering and Project Management
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• v.3 no.1
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• pp.1-9
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• 2013

Construction is a competitive industry and successful contractors must be able to win bids to obtain projects. Cash flow analysis not only determines actual profit at the end of the project, but also estimates required cash resources or cash ballances at the end of every month. Cash flow analysis is important in managing a construction project; however, it requires extensive information that is not immediately available to the general contractor. Before contractors can perform cash flow analysis, they must first complete a series of pre-requisites such as the quantity take off, scheduling, and cost estimating, followed by accurate assessments of project costs incurred and billable progress made. Consequently, cash flow analysis is currently a lengthy, uncertain process. This paper suggests improved cash flow analysis can be developed using data extraction in Building Information Modeling (BIM). BIM models contain a wealth of information and tools have been developed to automate a series of process such as quantity takeoff, scheduling, and estimating. This paper describes a prototype tool to support BIM-based, automated cash flow analysis.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.1
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• pp.9-16
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• 2012

This paper describes a measuring apparatus that can be used to appraise the effectiveness of nanofluids as new heat-transfer-enhancing fluids. A couple of apparatuses using fine hot wires as sensors have been proposed for this purpose; however, they have a technical weakness related to the uncertain working conditions of the sensor. The present method uses the convective heat transfer coefficient from a hot wire as an indication of the heat transfer effectiveness of the nanofluid, where the temperature of the wire remains constant during the experiment. The operating principle and experimental procedure are explained in detail, and the validity of the system is tested with pure base fluids. The effects of particle concentration, velocity, and temperature on the heat transfer coefficients of the nanofluids are discussed comprehensively using the experimental data for graphite nanolubrication oil.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.8
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• pp.585-591
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• 2003

A virtual force is generated and fed back to the operator to make the teleoperation more reliable, which reflects the relationship between a slave robot and an uncertain remote environment as a form of an impedance. In general, for the teleoperation, the teleoperated mobile robot takes pictures of the remote environment and sends the visual information back to the operator over the Internet. Because of the limitations of communication bandwidth and narrow view-angles of camera, it is not possible to watch certain regions, for examples, the shadow and curved areas. To overcome this problem, a virtual force is generated according to both the distance between the obstacle and the robot and the approaching velocity of the obstacle w.r.t the collision vector based on the ultrasonic sensor data. This virtual force is transferred back to the master (two degrees of freedom joystick) over the Internet to enable a human operator to estimate the position of obstacle at the remote site. By holding this master, in spite of limited visual information, the operator can feel the spatial sense against the remote environment. It is demonstrated by experiments that this collision vector based haptic reflection improves the performance of teleoperated mobile robot significantly.

• Journal of Acupuncture Research
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• v.30 no.3
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• pp.51-59
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• 2013

Objectives : This study was designed to evaluate clinical evidence of acupuncture treatment for peripheral facial palsy in South Korea. Methods : All process was independently proceeded by two investigators. Literature search was performed in 9 databases from their inception to February 2013. Searched reports was twice excluded for title, abstract and body. And then, data extract and analysis was done before assessing risk of bias by Cochrane Handbook. Results : 10 randomized controlled trials(RCT) were finally included. 4 RCT handled postauricular pain with facial palsy. All articles at least used in combination with two treatments. Interventions like pharmacopuncture, electroacupuncture, scalp acupuncture etcetera were conducted as treatment to evaluate efficacy, and some study reported advantageous effects of treatment group compared to baseline or control group. Adverse events didn't referd to in any studies. In assessing risk of bias, indefinite and uncertain information made all included trials to have a high risk of bias. Conclusions : Because of methodological deficit, there is no sufficient evidence to allow any conclusion about the efficacy of acupuncture for peripheral facial palsy. Therefore, well designed trials with high quality is needed from now on.

• Earthquakes and Structures
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• v.8 no.4
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• pp.935-956
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• 2015

Structural Health Monitoring (SHM) of steel towers has become a hot research topic. From the literature, it is impractical and impossible to develop a "general" method that can detect all kinds of damages for all types of structures. A practical method should make use of the characteristics of the type of structures and the kind of damages. This paper reports a feasibility study on the use of measured modal parameters for the detection of damaged braces of tower structures following the Bayesian probabilistic approach. A substructure-based structural model-updating scheme, which groups different parts of the target structure systematically and is specially designed for tower structures, is developed to identify the stiffness distributions of the target structure under the undamaged and possibly damaged conditions. By comparing the identified stiffness distributions, the damage locations and the corresponding damage extents can be detected. By following the Bayesian theory, the probability model of the uncertain parameters is derived. The most probable model of the steel tower can be obtained by maximizing the probability density function (PDF) of the model parameters. Experimental case studies were employed to verify the proposed method. The contributions of this paper are not only on the proposal of the substructure-based Bayesian model updating method but also on the verification of the proposed methodology through measured data from a scale model of transmission tower under laboratory conditions.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.03a
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• pp.111-118
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• 2002

Recent study of soft clay of Nakdong-River basin has been taken correlation between soil properties by regression analysis without distribution whether the sample is disturbed or not, or treated as a whole area without proposing local correlation equation to Jang-U or Dae-Joe which has a specific locality. Accordingly, Those tendency cause the reliability of correlation between compression index and void ratio low and then design underestimate and uncertain eventually. In this study, Distributing the soft clay of Nakdong-River basin with failure strain of 6%, the suggestion by Skempton(1957), TakeNaka(1966)-the more sample is undisturbed, the more the ratio of E$\_$50/ and ｑ$\_$u/, ${\alpha}$ = E$\_$50//(q$\_$u//2) = 1/$\varepsilon$$\_$50/ is high-is satisfied with the value of which ${\alpha}$ is 50 and It could be taken enough data in the condition of domestic. Besides other indices also make the distribution suitable. In conclusion, This study is supposed to propose the locally subdivided regression equation between compression index and void ratio considering the sample disturbance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.735-741
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• 2014

Edge in images appears when a great difference shows up in light and shade between pixels and includes data of the subject's size, location direction and etc. The edge is generally detected by the methods such as Sobel, Roberts, Laplacian, LoG(Laplacian of Gaussian) and etc. However, in AWGN(additive white Gaussian noise) added images, quality of the edge becomes slightly uncertain. Therefore, this paper proposed edge detection algorithm using modified mask of weighting to improve the quality of the existing methods. And in order to verify the performance efficiency of the proposed method, processed image and PFOM(Pratt's figure of merit) has been used as valuation standard for a comparison with the existing methods.