• Journal of Korean Society for Quality Management
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• v.10 no.1
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• pp.13-15
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• 1982

A device is said to have three states if it has one good state and two mutually exclusive failure modes ; e. g., in one failure mode, it operates when it should not, in the other it doesn't operate when it Should. Some examples of such device include a fluid flow valve, an automatic machine, and an explosive. A Markov model is developed to obtain the availability Function of a 2-unit standby redundant system of such devices.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.193-206
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• 2005

This paper considers a new flow-shop scheduling problem where a different WIP (work-in-process) state has different weight on the duration time. For the two machine case, the recognition version is NP-Complete in the strong sense. Several special cases are solved by different polynomial time algorithms. Finally, we develop a heuristic and provide an upper-bound on relative error which is tight in limit.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.4
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• pp.1-7
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• 2008

Fine grained superplastic Zn-22%Al alloy was extruded using a laser machined micro-die to produce a micro-gear shaft. Extrusion process was conducted under a constant pressure at constant temperatures ranging from 503 to 563K. Laser machining was capable to machine a micro-die with close tolerances and adequate surface quality. The extrusion rate increased with extrusion load under constant extrusion temperature. The rate reached a steady state and became constant after a certain period. There was a small instantaneous stroke on application of the load and then a very brief primary stage which preceded steady-state flow. The micro-extrusion process was proven to produce a micro-gear shaft successfully using a fine grained superplastic Zn-22%Al alloy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2473-2489
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• 2022

Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.8
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• pp.731-737
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• 2014

This paper presents abnormal behavior detection in crowd within surveillance video. We have defined below two cases as a abnormal behavior; first as a sporadically spread phenomenon and second as a sudden running in same direction. In order to detect these two abnormal behaviors, we first extract the motion vector and propose a new descriptor which is combined MHOF(Multi-scale Histogram of Optical Flow) and DCHOF(Directional Change Histogram of Optical Flow). Also, binary classifier SVM(Support Vector Machine) is used for detection. The accuracy of the proposed algorithm is evaluated by both UMN and PETS 2009 dataset and comparisons with the state-of-the-art method validate the advantages of our algorithm.

• Polymer(Korea)
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• v.38 no.5
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• pp.640-644
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• 2014

As a process of plat panel display production, slot coating is widely used for the coating of photoresist on a wide glass substrate. A uniform coating thickness is important, and the coating uniformity is divided into nozzle and machine directions. The machine and nozzle directions coating uniformities are influenced by the operation condition of coater and flow uniformity inside the die, respectively. Non-uniform coating during steady coating process occurs according to those factors, however, non-uniform coating along the machine and nozzle directions has been observed at the beginning of coating by unsteady flow. In this study, steady and unsteady state flow simulations have been performed and compared with experiment to examine the causes of non-uniform coating. Computational results exhibited that it took a time to get a uniform pressure distribution at whole inside the die, and during this period of time edge regions showed lower exit velocity compared with center region. Subsequently edge regions had thinner coated layers than center region. However edge regions showed higher exit velocity than center region after steady state, and this made edge regions had thicker coated layer than center region.

• Nuclear Engineering and Technology
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• v.34 no.5
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• pp.468-481
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• 2002

There are 4 CANDU6 type reactors operating at Wolsong site. For fuelling operation of certain fuel channels (with flow less than 21.5 kg/s) a FARE flow Assist Ram Extension) device is used. During the refuelling operation, two remote controlled F/Ms (Fuelling Machines) are attached to a designated fuel channel and carry out refuelling job. The upstream F/M inserts new fuel bundles into the fuel channel while the downstream F/M discharges spent fuel bundles. In order to assist fuelling operation of channels that has lower coolant How rate, the FARE device is used instead of F/M C-ram to push the fuel bundle string. The FARE device is essentially a How restricting element that produces enough drag force to push the fuel bundle string toward downstream F/M. Channels that require the use of FARE device for refuelling are located along the outside perimeter of reactor. This paper presents the FARE device design feature, steady state hydraulic and operational characteristics and behavior of the device when coupled with fuel bundle string during fuelling operation. The study showed that the steady state performance of FARE device meets the design objective that was confirmed by downstream F/M C-ram force to be positive.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8B
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• pp.707-718
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• 2008

The methodology of classifying traffics is changing from payload based or port based to machine learning based in order to overcome the dynamic changes of application's characteristics. However, current state of traffic classification using machine learning (ML) algorithms is ongoing under the offline environment. Specifically, most of the current works provide results of traffic classification using cross validation as a test method. Also, they show classification results based on traffic flows. However, these traffic classification results are not useful for practical environments of the network traffic monitoring. This paper compares the classification results using cross validation with those of using split validation as the test method. Also, this paper compares the classification results based on flow to those based on bytes. We classify network traffics by using various feature sets and machine learning algorithms such as J48, REPTree, RBFNetwork, Multilayer perceptron, BayesNet, and NaiveBayes. In this paper, we find the best feature sets and the best ML algorithm for classifying traffics using the split validation.

• Journal of Digital Convergence
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• v.13 no.8
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• pp.289-294
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• 2015

This paper proposes an autonomous machine learning method applicable to the BCI(Brain-Computer Interface) is based on the self-organizing Kohonen method, one of the exemplary method of unsupervised learning. In addition we propose control method of learning region and self machine learning rule using an interactive function. The learning region control and machine learning was used to control the side effects caused by interaction function that is based on the self-organizing Kohonen method. After determining the winner neuron, we decided to adjust the connection weights based on the learning rules, and learning region is gradually decreased as the number of learning is increased by the learning. So we proposed the autonomous machine learning to reach to the network equilibrium state by reducing the flow toward the input to weights of output layer neurons.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.6
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• pp.189-194
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• 2012

The purpose of this study is to predict the performance of a cyclone drying machine and air ejector used in drying applications. This paper deals with optimization of the geometry of the ejector for sludge drying using computational fluid dynamics. To facilitate the design of a jet ejector for air drying machines, a numerical model of simultaneous mass and heat transfers between the liquid(sludge) and gas(air) phases in the jet ejector was developed. The steady-state model was based on unidimensional balance equations of mass, energy and momentum for the liquid and gas phases. It was shown that the optimum condition to minimize pressure and momentum loss of air in the ejector was d=220mm. It was found that sludge particles inside the cyclone was smoothly discharged by the conical wedge installed on the bottom of the cyclone.