• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.2
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• pp.52-62
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• 2013

A stochastic Markov process (MP) model has been developed for evaluating the probability of failure of the armor unit of rubble-mound breakwaters as a function of time. The mathematical MP model could have been formulated by combining the counting process or renewal process (CP/RP) on the load occurrences with the damage process (DP) on the cumulative damage events, and applied to the armor units of rubble-mound breakwaters. Transition probabilities have been estimated by Monte-Carlo simulation (MCS) technique with the definition of damage level of armor units, and very well satisfies some conditions constrained in the probabilistic and physical views. The probabilities of failure have been also compared and investigated in process of time which have been calculated according to the variations of return period and safety factor being the important variables related to design of armor units of rubble-mound breakwater. In particular, it can be quantitatively found how the prior damage levels can effect on the sequent probabilities of failure. Finally, two types of methodology have been in this study proposed to evaluate straightforwardly the repair times which are indispensable to the maintenance of armor units of rubble-mound breakwaters and shown several simulation results including the cost analyses.

• Journal of Korea Water Resources Association
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• v.32 no.5
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• pp.565-577
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• 1999

The geometric patterns of a stream network in a drainage basin can be viewed as a "fractal" with fractal dimensions. Fractals provide a mathematical framework for treatment of irregular, ostensively complex shapes that show similar patterns or geometric characteristics over a range of scale. GIUH (Geomorphological Instantaneous Unit Hydrograph) is based on the hydrologic response of surface runoff in a catchment basin. This model incorporates geomorphologic parameters of a basin using Horton's order ratios. For an ordered drainage system, the fractal dimensions can be derived from Horton's laws of stream numbers, stream lengths and stream areas. In this paper, a fractal approach, which is leading to representation of a 2-parameter Gamma distribution type GIUH, has been carried out to incorporate the self similarity of the channel networks based on the high correlations between the Horton's order ratios. The shape and scale parameter of the GIUH-Nash model of IUH in terms of Horton's order ratios of a catchment proposed by Rosso(l984J are simplified by applying the fractal dimension of main stream length and channel network of a river basin. basin.

• Structural Engineering and Mechanics
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• v.58 no.2
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• pp.277-300
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• 2016

Cold-formed steel (CFS) sections are becoming an increasingly popular solution for constructing floors in residential, healthcare and education buildings. Their reduced weight, however, makes them prone to excessive vibrations, increasing the need for accurate prediction of CFS floor modal properties. By combining experimental modal analysis of a full-scale CFS framed building and its floors and their numerical finite element (FE) modelling this paper demonstrates that the existing methods (based on the best engineering judgement) for predicting CFS floor modal properties are unreliable. They can yield over 40% difference between the predicted and measured natural frequencies for important modes of vibration. This is because the methods were adopted from other floor types (e.g., timber or standard steel-concrete composite floors) and do not take into account specific features of CFS floors. Using the adjusted and then updated FE model, featuring semi-rigid connections led to markedly improved results. The first four measured and calculated CFS floor natural frequencies matched exactly and all relevant modal assurance criterion (MAC) values were above 90%. The introduction of flexible supports and more realistic modelling of the floor boundary conditions, as well as non-structural $fa{\c{c}}ade$ walls, proved to be crucial in the development of the new more successful modelling strategy. The process used to develop 10 identified and experimentally verified FE modelling parameters is based on published information and parameter adjustment resulting from FE model updating. This can be utilised for future design of similar lightweight steel floors in prefabricated buildings when checking their vibration serviceability, likely to be their governing design criterion.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.1
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• pp.51-58
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• 2005

The development of the high-efficiency machine-tools equipment and new cutting tool materials with high hardness, heat- and wear-resistance has opened the way to application of high-speed cutting process. The basic argument of using of high-speed cutting processes is the reduction of time and the respective increase of machining productivity. In this sense, the spindle units may be regarded as one of the most important units, directly affecting many parameters of high-speed machining efficiency. One of the possible types of spindle units for high-speed cutting is the air-bearing type. In this paper, we propose the mathematical model of the dynamic behavior of the air-bearing spindle. To provide the high-level of speed capacity and spindle rotation accuracy we need the adequate model of "spindle-bearings" system. This model should consider characteristics of the interactions between system components and environment. To find the working characteristics of spindle unit we should derive the equations of spindle axis movement under the affecting factors, and solve these equations together with equations which describe the behavior of lubricant layer in bearing (bearing stiffness equations). In this paper, the three influence coefficients are introduced, which describe the center of spindle mass displacement, angle of shaft rotation around the axes under the unit force application and that under the unit torque application. These coefficients are operated in the system of differential equations, which describes the spindle axis spatial movement. This system is solved by Runge-Kutta method. Obtained trajectories and amplitude-frequency characteristics were then compared to experimental ones. The analysis shows good agreement between theoretical and experimental results, which confirms that the proposed model of air-bearing spindle is correctis correct

• Journal of Korean Society of Transportation
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• v.26 no.6
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• pp.123-132
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• 2008

Dynamic origin-destination (OD) trip matrix has been widely used for transportation fields such as dynamic traffic assignment, traffic operation and travel demand management, which needs precise OD trip matrix to be collected. This paper presents a quasi-dynamic OD matrix estimation model and applies it to real road network for collecting the dynamic OD matrix. The estimation model combined with dynamic traffic assignment program, DYNASMART-P, is based on GPS embedded in PDA, which developed for collecting sample dynamic OD matrix. The sample OD matrix should be expanded by the value of optimal sampling ratio calculated from minimization program. From application to real network of Jeju, we confirm that the model and its algorithm produce a reasonable solution.

• Journal of the Korea Safety Management & Science
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• v.6 no.3
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• pp.249-273
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• 2004

Finding an optimal solution in MADN[(Multi-Attribute Decision-Making) problems is difficult, when the number of alternatives, or that of attributes is relatively large Most of the existing mathematical approaches arrive at a final solution on the basis of many unrealistic assumptions, without reflecting the decision-maker's preference structure exactly. In this paper we suggest a model that helps us find a group consensus without assessing these parameters in specific cardinal values. Therefore, This research provides a comprehensive Decision Making of the theory and methods applicable to the analysis of decisions that involve risk and multiple criteria attributes. after, The emphasis of the procedure will be on developments from the fields of decisions analysis and utility theory of Taguchi Method. This theoretical development will be illustrated through the discussion of several real-world application and a case study. When the multiple number of decision makers are involved in the decision making procedure, the problem of uncertainties invariably occurs, because of the different views between them. In this paper, New decision making model using Taguchi Method is applied to effectively model the multi-attribute-decision making(MADM) procedure in the uncertainties dominated two area(quantitative and qualitative factors), Quantitative factors evaluation is used Loss Function of Taguchi, qualitative factors evaluation is used 50 ratio by each specialist. thus it can be used for aiding of preferable alternative. as a result, We will be proved efficiency about New decision making model of applied Taguchi Method with Analytical presentation of all the expecting outcomes when a specific strategy or an alternative plan is selected under expecting future environment.

• Clean Technology
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• v.2 no.1
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• pp.80-95
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• 1996

A mathematical model has been developed for simulating the spray dryer absorber (SDA) used in semi-dry flue gas desulfurization process. Fundamental equations include the component mass and heat balances in both gas and droplet phases and the equation of motion for a single droplet. The model developed described the pilot-plant data much better than the existing SPRAYMOD-M model. The effect of the process variables, whose values were chosen within the operation limits of the actual pilot plants, on % $SO_2$ removal or conversion of the sorbent were calculated, and discussed in terms of $SO_2$ absorption rate, the residence time of flue gas, the velocity and drying time of droplets. Finally, the % $SO_2$ removal was calculated with two independent process variables and the results were shown on three-dimensional or two-dimensional diagrams with the lines of constant % $SO_2$ removal, so that they can be easily applied to preliminary design of the SDA.

• Journal of the Korea Society for Simulation
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• v.27 no.3
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• pp.23-36
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• 2018

Discrete Event System Specification (DEVS) has been used for decades as it provides sound semantics for hierarchical modular specification of discrete event systems. Instead of the mathematical specification, the DEVS diagram, based on the structured DEVS formalism, has provided more intuitive and convenient representation of complex DEVS models. This paper proposes a clean room process for implementation and verification of a DEVS diagram model specification into a simulation software source code. Specifically, it underlies a sequence of transformation steps from conformance and integrity checking of a given diagram model, translation into a corresponding tabular model, and finally conversion to a simulation source code, with each step being inversely verifiable for traceability. A simple example helps developers to understand the proposed process with associated transformation methods; a case study shows that the proposed process is effective for and adaptable to practical simulation software development.

• Journal of Construction Engineering and Project Management
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• v.2 no.2
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• pp.18-27
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• 2012

Despite the rapid development in the construction industry due to the changing new technologies, many projects still fail to meet target deadlines. Shortage in manpower and skilled laborers is one of the main reasons for such delays. Markets with high economic growth and economic expansion (such as Gulf Countries in the Middle East) may have pronounced labor the shortages. Labor subcontracting practices are used sometimes to increase production rates and meet project deadlines. This paper explains and analyses labor subcontracting practices currently being used in many places around the world (and especially in the Gulf Countries) and in particular defines a maximum overtime rate for laborers in the laborer-subcontracting method ensuring that the contractor gains both the time saved during overtime and also reduces the cost per unit produced. The mathematical model used formalizes a closed-form equation for overtime pay in similar situations and as such can be applicable worldwide. Data was collected from representative projects that employed such practices from various trades. Validation of the model and formula has been tested successfully by analyzing historic data. The results prove that contractors often do not reach the optimum use of their practices resulting in a higher cost per unit. The presented model and the analysis should be of interest to many contractors currently involved in the practice or considering its use and to those who wish to find new methods that would help in eliminating as much wastes as possible by allocating their resources in the most efficient way.

• Journal of Information Technology Services
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• v.18 no.2
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• pp.143-159
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• 2019

Machine learning (ML) is a method of fitting given data to a mathematical model to derive insights or to predict. In the age of big data, where the amount of available data increases exponentially due to the development of information technology and smart devices, ML shows high prediction performance due to pattern detection without bias. The feature engineering that generates the features that can explain the problem to be solved in the ML process has a great influence on the performance and its importance is continuously emphasized. Despite this importance, however, it is still considered a difficult task as it requires a thorough understanding of the domain characteristics as well as an understanding of source data and the iterative procedure. Therefore, we propose methods to apply deep learning for solving the complexity and difficulty of feature extraction and improving the performance of ML model. Unlike other techniques, the most common reason for the superior performance of deep learning techniques in complex unstructured data processing is that it is possible to extract features from the source data itself. In order to apply these advantages to the business problems, we propose deep learning based methods that can automatically extract features from transaction data or directly predict and classify target variables. In particular, we applied techniques that show high performance in existing text processing based on the structural similarity between transaction data and text data. And we also verified the suitability of each method according to the characteristics of transaction data. Through our study, it is possible not only to search for the possibility of automated feature extraction but also to obtain a benchmark model that shows a certain level of performance before performing the feature extraction task by a human. In addition, it is expected that it will be able to provide guidelines for choosing a suitable deep learning model based on the business problem and the data characteristics.