• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.2
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• pp.189-196
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• 2001

Photoelasticity is one of the most widely used methods for whole field stress analysis. In photoelasticity, the difference and the directions of the principal stresses we given isochromatic and isoclinic fringe patterns. Conventionally, principal stress directions are measured manually by relating the polarizer and analyzer of a plane polariscope at the same time. This is known to be the Tardy compensation method. This measurement can be very tedious and time consuming in whole field analysis. It is not possible to separate isoclincs from photoelastic fringes by conventional photoelastic technique. In this study, photoelastic theory is represented by Jones matrices and 4-steps and 8-steps phase shifting methods are described A feasibility study using computer simulation is done to separate isoclincs and isochomatics from photoelastic fringes of a circular disk under diametrical compression. Fringe patterns of the disk are generated using stress optic law. The magnitudes of isoclincs and isochromatics obtained from 8-step phase shifting method are compared with those of theories. From computer simulation, it is verified to separate isoclincs and isochomatics from photoelastic fringes.

• Journal of Korea Water Resources Association
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• v.33 no.5
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• pp.537-550
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• 2000

In this study, Neural Networks models were used to forecast daily streamflow at Jindong station of the Nakdong River basin. Neural Networks models consist of CASE 1(5-5-1) and CASE 2(5-5-5-1). The criteria which separates two models is the number of hidden layers. Each model has Fletcher-Reeves Conjugate Gradient BackPropagation(FR-CGBP) and Scaled Conjugate Gradient BackPropagation(SCGBP) algorithms, which are better than original BackPropagation(BP) in convergence of global error and training tolerance. The data which are available for model training and validation were composed of wet, average, dry, wet+average, wet+dry, average+dry and wet+average+dry year respectively. During model training, the optimal connection weights and biases were determined using each data set and the daily streamflow was calculated at the same time. Except for wet+dry year, the results of training were good conditions by statistical analysis of forecast errors. And, model validation was carried out using the connection weights and biases which were calculated from model training. The results of validation were satisfactory like those of training. Daily streamflow forecasting using Neural Networks models were compared with those forecasted by Multiple Regression Analysis Mode(MRAM). Neural Networks models were displayed slightly better results than MRAM in this study. Thus, Neural Networks models have much advantage to provide a more sysmatic approach, reduce model parameters, and shorten the time spent in the model development.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.425-432
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• 2009

The purposes of the study were to examine cerebellar areas and lateralization responsible for visuospatial and verbal tasks using functional Magnetic Resonance Imaging(fMRI). Eight healthy male college students($21.5\;{\pm}\;2.3$ years) and eight male college students($23.3\;{\pm}\;0.5$ years) participated in this fMRI study of visuospatial and verbal tasks, respectively. Functional brain images were taken from 3T MRI using the single-shot EPI method. All functional images were aligned with anatomical images using affine transformation routines built into SPM99. The experiment consisted of four blocks. Each block included a control task(1 minute) and a cognitive task(1 minute). A run was 8 minutes long. Using the subtraction procedure, activated areas in the cerebellum during the visuospatial and verbal tasks were color-coded by t-score. A cerebellar lateralization index was calculated for both cognition tasks using number of activated voxels. The activated cerebellar regions during the both cognition tasks of this study agree with previous results. Since the number of activated voxels of the left and right cerebellar hemisphere was almost same, there was no cerebellar lateralization for both cognition tasks.

• Korean Journal of Food Science and Technology
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• v.39 no.3
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• pp.276-282
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• 2007

In this study, attempts were made to develop a garlic juice extraction method that would result in minimum changes in quality. Protopectinase and a mutienzyme containing cellulase, pectinesterase, ${\beta}-glucanase$, etc. were applied to garlic residue after first extraction, and the yields of garlic juice and the flavor component changes of the juices were investigated. Enzyme concentrations of 0.04, 0.08, and 0.12% which were based on pulp weight before extraction were added and allowed to hydrolyze for 30, 60, 90 and 120 min,. respectively. Increase in the garlic juice yield was observed according to the amount of enzyme added and the reaction time until reaching a maximum point. When 0.12% protopectinase was applied to the garlic residue for 90 min, the yield increased by 13.8%. Under the same conditions, when multienzyme was applied to the garlic residue, the yield increased by 14.5%, which was considered the maximum. The flavor compounds decreased when compared with the total GC peak area of garlic juice prepared without enzymes(control). The volatile flavor compounds in garlic juice prepared with 0.12% protopectinase for 60 min decreased by 6%. The free sugars profile of the garlic juice prepared with 0.12% protopectinase for 60 min was similar to that of the control. The type of enzyme used did not affect the free amino acid profile of the garlic juice. These results indicate that the optimum conditions for extraction of garlic juice are hydrolyzing the residue with 0.12% protopectinase for 60 min, extracting garlic juice from the hydrolyzed reside, and then combining the extracted juice with the first extraction.

• Korean Journal of Food Science and Technology
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• v.43 no.5
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• pp.553-557
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• 2011

Garlic specific organic compounds were separated and purified using a recycling preparative high-performance liquid chromatography (HPLC) from blanched garlic cloves. Identification of the compounds involved comparing the previously reported HPLC retention times as well as other identification methods including $^1H$- and $^{13}C$-nuclear magnetic resonance and liquid chromatography-mass spectrometry. The yields of garlic specific organic compounds were 12.2, 42.5, 1.6, 1.2, and 4.8% on wet weight basis of garlic for alliin(S-allyl-L-cysteine sulfoxide), isoalliin(S-1-propenyl-L-cysteine sulfoxide), ${\gamma}$-glutamyl-S-allylcysteine, ${\gamma}$-glutamyl-S-1-propenylcysteine and ${\gamma}$-glutamyl-phenylalanine, respectively. All the compounds, except for ${\gamma}$-glutamylphenylalanine, contained sulfur.

• Journal of KIISE:Information Networking
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• v.37 no.4
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• pp.272-283
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• 2010

Wireless Mesh Networks (WMNs) have gained a lot of attention recently. Based on the characteristic of WMNs as a highly connected wireless infrastructure, many efforts from research organizations are made in order to improve the performance of the flow throughput in WMNs. Therefore, it is very critical issue to establish efficient routing paths for multiple concurrent ongoing flows. In this paper, we propose a general modeling methodology to analyze the end-to-end throughput of multiple concurrent flows by analytical calculation taking into account the carrier sensing behaviors, interference and the IEEE 802.11 Distributed Coordination Function mechanism. After the comparison of the average service time for each successful transmission at each node, we analyze the bottlenecks of flows, and hence obtain the maximum end-to-end throughput of them. By using our proposed model, it is possible to predicate the throughput of several candidate routing paths for multiple concurrent ongoing data flows, so we can select the most efficient route that can achieve the highest throughput. We carry out simulations with various traffic patterns of multiple flows in WMNs to validate our modeling and our efficient route selection mechanism.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.5
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• pp.292-303
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• 2010

On-chip cache memories play an important role in both performance and energy consumption points of view in resource-constrained embedded systems by filtering many off-chip memory accesses. We propose a 2-level data cache architecture with a low energy-delay product tailored for the embedded systems. The L1 data cache is small and direct-mapped, and employs a write-through policy. In contrast, the L2 data cache is set-associative and adopts a write-back policy. Consequently, the L1 data cache is accessed in one cycle and is able to provide high cache bandwidth while the L2 data cache is effective in reducing global miss rate. To reduce the penalty of high miss rate caused by the small L1 cache and power consumption of address generation, we propose an ECP(Early Cache hit Predictor) scheme. The ECP predicts if the L1 cache has the requested data using both fast address generation and L1 cache hit prediction. To reduce high energy cost of accessing the L2 data cache due to heavy write-through traffic from the write buffer laid between the two cache levels, we propose a one-way write scheme. From our simulation-based experiments using a cycle-accurate simulator and embedded benchmarks, the proposed 2-level data cache architecture shows average 3.6% and 50% improvements in overall system performance and the data cache energy consumption.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.972-978
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• 2009

In order to achieve color constancy, this paper proposes a method that can detect an invariant direction that affects formation of an intrinsic image significantly, using eigenvector in the $\chi$-chromaticity space. Firstly, image is converted into datum in the $\chi$-chromaticity space which was suggested by Finlayson et al. Secondly, it removes datum, like noises, with low probabilities that may affect an invariant direction. Thirdly, so as to detect the invariant direction that is consistent with a principal direction, the eigenvector corresponding to the largest eigenvalue is calculated from datum extracted above. Finally, an intrinsic image is acquired by recovering datum with the detected invariant direction. Test images were used as parts of the image data presented by Barnard et al., and detection performance of invariant direction was compared with that of entropy minimization method. The results of experiment showed that our method detected constant invariant direction since the proposed method had lower standard deviation than the entropy method, and was over three times faster than the compared method in the aspect of detection speed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.373-381
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• 2017

Kyeonggi Provincial Government is considering double decker bus service to solve the problem of heavy rush hour traffic. However, the height-to-width ratio is more than 1.16 times larger than that of a general high-speed single decker bus, and the center of gravity is higher. This could cause driving stability problems, such as turnover and breakaway from the lane, especially under strong side-wind conditions at high speed. In this numerical study, the driving characteristics of a model double decker bus were reviewed under side-wind and superelevation conditions at high driving speed. The rolling, pitching, and yawing moment of the model bus were calculated with CFD numerical simulation, and the results were compared to the recovery angular moments of the model bus to evaluate the dynamic stability under given driving conditions. As the model vehicle moves on a straight level road, it is stable under any side-wind conditions. However, on a curved road under side-wind conditions, it could reach unstable conditions dynamically. There is a chance that the bus will turn over when it moves on a curved road with a radius of gyration less than 100 m under side-wind (15 m/s). However, there is a very small chance of breakaway from the lane under any driving conditions.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1367-1383
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• 2007

A sensor network consists of a network of sensors that can perform computation and also communicate with each other through wireless communication. Some important characteristics of sensor networks are that the network should be self administered and the power efficiency should be greatly considered due to the fact that it uses battery power. In sensor networks, when large amounts of various stream data is produced and multiple queries need to be processed simultaneously, the power efficiency should be maximized. This work proposes a technique to create an index on multiple monitoring queries so that the multi-query processing performance could be increased and the memory and power could be efficiently used. The proposed SMILE tree modifies and combines the ideas of spatial indexing techniques such as k-d trees and R+-trees. The k-d tree can divide the dimensions at each level, while the R+-tree improves the R-tree by dividing the space into a hierarchical manner and reduces the overlapping areas. By applying the SMILE tree on multiple queries and using it on stream data in sensor networks, the response time for finding an indexed query takes in some cases 50% of the time taken for a linear search to find the query.