• Proceedings of the KSME Conference
• /
• 2003.04a
• /
• pp.1972-1979
• /
• 2003

Transport of a scalar quantity, such as chemical concentration or temperature, is important in many engineering applications and environmental flows. Here we report on results obtained from the large eddy simulations of flow and concentration fields inside the tank performed using a spectral multi-domain technique. The computations were driven by specifying the impeller-induced flow at the blade tip radius (Yoon et al. $^{(1)}$). This study focused on the concentration development at different molecular diffusivities in a stirred tank operated under turbulent conditions. The main objective of the work presented here is to study the large-scale mixing structure at different molecular diffusivities in a stirred tank by using the large eddy simulation. The time sequence of concentration and flow fields shows the flow dependency of the concentration development. The presence of spatial inhomogenieties is detailed by observing the time variation of local concentration at different positions.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.37 no.4
• /
• pp.187-192
• /
• 2014

Lot-streaming is the process of splitting a job (lot) into sublots to allow the overlapping of operations between successive machines in a multi-stage production system. A new genetic algorithm (NGA) is proposed for an n-job, m-machine, lot-streaming flow shop scheduling problem with equal-size sublots in which the objective is to minimize the total stretch. The stretch of a job is the ratio of the amount of time the job spent before its completion to its processing time. NGA replaces the selection and mating operators of genetic algorithms (GAs) by marriage and pregnancy operators and incorporates the idea of inter-chromosomal dominance and individuals' similarities. Extensive computational experiments for medium to large-scale lot-streaming flow-shop scheduling problems have been conducted to compare the performance of NGA with that of GA.

• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.297-298
• /
• 2006

In this paper, we propose a real-time surveillance system for security of important area such as military bases, prisons, and strategic infra structures. The proposed system recognizes the movement of objects in dark environments. First, the Multi-scale retinex (MSR) is processed to enhance the contrast of image captured in dark environments. Then, the enhanced input image is subtracted with the background image. Finally, each bounding box enclosing each objects are tracked. The center point of each bounding box obtained by the proposed algorithm provides more accurate tracking information. Experimental results show that the proposed system provides good performance even though an object moves very fast and the background is quite dark.

• Journal of Advanced Navigation Technology
• /
• v.14 no.6
• /
• pp.984-989
• /
• 2010

In this paper, parallel programming technique by using Java Thread is introduced so as to develop parallel design tool to analyze the small micro flow sensor. To estimate computing time for Thread-level parallelism, the performances of two experimental models for potential problem subject to Thermal transfer equation are examined. As a result, if the number of network PC is increase, computing time for parallelism on network environment is enhanced to be almost n times. The micro sensor design tool based on distributed computing can be utilized to analyze a large scale problem.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.23 no.54
• /
• pp.13-26
• /
• 2000

Machining route selection to produce parts should be based on shop flow information because of input data at scheduling tasks and is one of the main problem in process planning. This paper addresses the problem of machining route selection in multi-stage process with machine group included a similar function. The model proposed is formulated as 0-1 integer programing considering the relation of parts and machine table size, avaliable time of each machine for planning period, and delivery date. The objective of the model is to minimize the sum of processing, transportation, and setup time for all parts. Genetic algorithm approach is developed to solve this model. The efficiency of the approach is examined in comparison with the method of branch and bound technique for the same problem. Also, this paper is to solve large problem scale and provide it if the multiple machining routes are existed an optimal solution.

• Smart Structures and Systems
• /
• v.23 no.2
• /
• pp.123-139
• /
• 2019

Impact forces induced by external object collisions can cause serious damages to civil engineering structures. While accurate and prompt identification of such impact forces is a critical task in structural health monitoring, it is not readily feasible for civil structures because the force measurement is extremely challenging and the force location is unpredictable for full-scale field structures. This study proposes a novel approach for identification of impact force including its location and time history using a small number of multi-metric observations. The method combines an augmented Kalman filter (AKF) and Genetic algorithm for accurate identification of impact force. The location of impact force is statistically determined in the way to minimize the AKF response estimate error at measured locations and then time history of the impact force is accurately constructed by optimizing the error co-variances of AKF using Genetic algorithm. The efficacy of proposed approach is numerically demonstrated using a truss and a plate model considering the presence of modelling error and measurement noises.

• Journal of Broadcast Engineering
• /
• v.24 no.2
• /
• pp.357-360
• /
• 2019

We propose an efficient single convolutional neural network (CNN) for pedestrian detection on embedded GPUs. We first determine the optimal number of the convolutional layers and hyper-parameters for a lightweight CNN. Then, we employ a multi-scale approach to make the network robust to the sizes of the pedestrians in images. Experimental results demonstrate that the proposed algorithm is capable of real-time operation, while providing higher detection performance than conventional algorithms.

• Transactions of Materials Processing
• /
• v.30 no.4
• /
• pp.186-194
• /
• 2021

Finite element simulation is a widely applied method for practical purpose in various metal forming process. However, in the simulation of elasto-plastic behavior of porous material or in crystal plasticity coupled multi-scale simulation, it requires much calculation time, which is a limitation in its application in practical situations. A machine learning model that directly outputs the constitutive equation without iterative calculations would greatly reduce the calculation time of the simulation. In this study, we examined the possibility of artificial intelligence based constitutive equation with the input of existing state variables and current velocity filed. To introduce the methodology, we described the process of obtaining the training data, machine learning process and the coupling of machine learning model with commercial software DEFROM^TM, as a preliminary study, via rigid plastic finite element simulation.

• Journal of Information Processing Systems
• /
• v.19 no.3
• /
• pp.370-376
• /
• 2023

Aiming at the problems of low image enhancement accuracy, long enhancement time and poor image quality in the traditional robot sequence motion image enhancement methods, an adaptive enhancement method for robot sequence motion image is proposed. The feature representation of the image was obtained by Karhunen-Loeve (K-L) transformation, and the nonlinear relationship between the robot joint angle and the image feature was established. The trajectory planning was carried out in the robot joint space to generate the robot sequence motion image, and an adaptive homomorphic filter was constructed to process the noise of the robot sequence motion image. According to the noise processing results, the brightness of robot sequence motion image was enhanced by using the multi-scale Retinex algorithm. The simulation results showed that the proposed method had higher accuracy and consumed shorter time for enhancement of robot sequence motion images. The simulation results showed that the image enhancement accuracy of the proposed method could reach 100%. The proposed method has important research significance and economic value in intelligent monitoring, automatic driving, and military fields.

• Mycobiology
• /
• v.40 no.2
• /
• pp.100-106
• /
• 2012

Interest in commercial cultivation and product development of Cordyceps species has shown a recent increase. Due to its biochemical and pharmacological effects, Cordyceps militaris, commonly known as orange caterpillar fungus, is being investigated with great interest. Cultivation of C. militaris has been practiced on a large scale in order to fulfill a demand for scientific investigation and product development. Isolates of C. militaris can be easily established from both spores and tissue. For isolation of spores, ascospores released from mature stromata are trapped in sterile medium. Multi-ascospore isolates, as well as combinations of single ascospore strains, are used for production of fruiting bodies. Progeny ascospore strains can be isolated from artificial fruiting bodies, thus, the cycle of fruiting body production can be continued for a long period of time. In this study, we examined fruiting body production from multi-ascospore isolates and their progeny strains for three generations. $F_1$ progeny strains generally produced a larger number of fruiting bodies, compared with their mother multi-ascospore isolates; however, $F_2$ and $F_3$ progeny strains produced fewer fruiting bodies. Optimum preservation conditions could help to increase the vitality of the progeny strains. In order to retain the fruiting ability of the strains, further testing of various methods of preservation and different methods for isolation should be performed.