• Journal of Welding and Joining
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• v.35 no.3
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• pp.35-43
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• 2017

A 3D transient heat transfer model is developed by ABAQUS software to study the temperature distribution during friction stir welding process at different rotational speeds. Furthermore, AA 5083-O plates were joined by FSW technique. For this purpose, a universal milling machine was used to perform the welding process and a mechanical vice was used to fix the work pieces in the proper position. The joints were friction stir welded at a constant travel speed 50 mm/min and two rotational speed values; 400 rpm and 630 rpm using two types of tools; cylindrical threaded pin and tapered smooth one. At each welding condition the temperature was measured using infra-red thermal image camera to verify the simulated temperature distribution. The welded joints were visually inspected as well as by macro- and microstructure evolutions. In addition, the welded joints were mechanically tested for hardness and tensile strength. The maximum peak temperature obtained was at higher rotational speed using the threaded tool pin profile. The results showed that the rotational speed affects the peak temperature, defects formation and sizes, and the mechanical properties of friction stir welded joints. Moreover, the threaded tool gives superior mechanical properties than the tapered one at lower rotational speed.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.878-881
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• 2003

To acquire an appointed speaker's clear voice signal from inspect-camera, picture-conference or hands free microphone eliminating interference noises needs to be preceded speaker's position automatically. Presumption of sound source position's basic algorithm is about measuring TDOA(Time Difference Of Arrival) from reaching same signals between two microphones. This main project uses ADF(Adaptive Delay Filter) [4] and CPS(Cross Power Spectrum) [5] which are one of the most important analysis of TDOA. From these analysis this project proposes presumption of real time sound source position and improved model NI-ADF which makes possible to presume both directions of sound source position. NI-ADF noticed that if auditory sense of humankind reaches above to some specified level in specified frequency, it will accept sound through activated nerve. NI-ADF also proposes practicable algorithm, the presumption of real time sound source position including both directions, that when microphone loads to some specified system, it will use sounds level difference from external system related to sounds of diffraction phenomenon. In accordance with the project, when existing both direction adaptation filter's algorithm measures sound source, it increases more than twice number by measuring one way. Preserving this weak point, this project proposes improved algorithm to presume real time in both directions.

• Ocean Systems Engineering
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• v.9 no.4
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• pp.409-422
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• 2019

Sloshing is a phenomenon which may lead to dynamic stability and damages on the local structure of the tank. Hence, several anti-sloshing devices are introduced in order to reduce the impact pressure and free surface elevation of liquid. A fixed baffle is the most prevailing anti-sloshing mechanism compared to the other methods. However, the additional of the baffle as the internal structure of the LNG tank can lead to frequent damages in long-term usage as this structure absorbs the sloshing loads and thus increases the maintenance cost and downtime. In this paper, a novel type of floating baffle is proposed to suppress the sloshing effect in LNG tank without the need for reconstructing the tank. The sloshing phenomenon in a membrane type LNG tank model was excited under sway motion with 30% and 50% filling condition in the model test. A regular motion by a linear actuator was applied to the tank model at different amplitudes and constant period at 1.1 seconds. Three pressure sensors were installed on the tank wall to measure the impact pressure, and a high-speed camera was utilized to record the sloshing motion. The floater baffle was modeled on the basis of uniform-discretization of domain and tested based on parametric variations. Data of pressure sensors were collected for cases without- and with-floating baffle. The results indicated successful reduction of surface run-up and impulsive pressure by using a floating baffle. The findings are expected to bring significant impacts towards safer sea transportation of LNG.

• Animal Bioscience
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• v.36 no.6
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• pp.980-989
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• 2023

Objective: Iris pattern recognition system is well developed and practiced in human, however, there is a scarcity of information on application of iris recognition system in animals at the field conditions where the major challenge is to capture a high-quality iris image from a constantly moving non-cooperative animal even when restrained properly. The aim of the study was to validate and identify Black Bengal goat biometrically to improve animal management in its traceability system. Methods: Forty-nine healthy, disease free, 3 months±6 days old female Black Bengal goats were randomly selected at the farmer's field. Eye images were captured from the left eye of an individual goat at 3, 6, 9, and 12 months of age using a specialized camera made for human iris scanning. iGoat software was used for matching the same individual goats at 3, 6, 9, and 12 months of ages. Resnet152V2 deep learning algorithm was further applied on same image sets to predict matching percentages using only captured eye images without extracting their iris features. Results: The matching threshold computed within and between goats was 55%. The accuracies of template matching of goats at 3, 6, 9, and 12 months of ages were recorded as 81.63%, 90.24%, 44.44%, and 16.66%, respectively. As the accuracies of matching the goats at 9 and 12 months of ages were low and below the minimum threshold matching percentage, this process of iris pattern matching was not acceptable. The validation accuracies of resnet152V2 deep learning model were found 82.49%, 92.68%, 77.17%, and 87.76% for identification of goat at 3, 6, 9, and 12 months of ages, respectively after training the model. Conclusion: This study strongly supported that deep learning method using eye images could be used as a signature for biometric identification of an individual goat.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.10
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• pp.1265-1273
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• 1999

PIV(Particle Image Velocimetry) velocity field measurements inside the snout of a1/10 scale model of the Zn plating process were carried out at the strip speed $V_s=1.5m/s$. Aluminum powder particles ($1{\mu}m$) and atomized olive oil ($3{\mu}m$) were used as seeding particles to simulate the molten Zinc flow and deoxidization gas flow, respectively. A pulsed Nd:Yag laser and a $2K{\times}2K$ high-resolution CCD camera were synchronized for the PIV velocity field measurement. From flow visualization study, it is found that the liquid flow in the Zn pot is dominantly governed by the uprising flow caused by the rotating sink roll, with its effect on the steel strip inside the snout largely diminished by installing of the snout. The deoxidization gas flow in front of the strip inside the snout can be characterized by a large-scale vortex rotating clockwise direction formed by the moving strip. In the rear side of the strip, a counter-clockwise vortex is formed and some of the flow entrained by the moving strip impinges on the free surface of molten zinc. The liquid flow in front of the strip is governed by the flow entering the snout, caused by the spinning sink roll. Just below the free surface a counter-clockwise vortex is formed near the snout wall. The moving strip affects dominantly the flow behind the strip inside the snout, and large amount of the liquid flow follows the moving strip toward the sink roll. The thickness of the flow following the strip is very thin in the front side due to the uprising flow, however thick boundary layer is formed in the rear side of the strip. Its thickness is increased as moving downstream toward the sink roll. Inside the snout, the deoxidization gas flow above the free surface is much faster than the liquid flow in the zinc pot. Due to the larger influx of the flow following the moving strip in the rear side of the strip, higher percentage of imperfection can be anticipated on the rear surface of the strip.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.148-159
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• 2018

Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.

• Explosives and Blasting
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• v.30 no.2
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• pp.29-42
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• 2012

Variables influencing the free face movement due to rock blasting include the physical and mechanical properties, in particular the discontinuity characteristics, explosive type, charge weight, burden, blast-hole spacing, delay time between blast-holes or rows, stemming conditions. These variables also affects the blast vibration, air blast and size of fragmentation. For the design of surface blasting, the priority is given to the safety of nearby buildings. Therefore, blast vibration has to be controlled by analyzing the free face movement at the surface blasting sites and also blasting operation needs to be optimized to improve the fragmentation size. High-speed digital image analysis enables the analyses of the initial movement of free face of rock, stemming optimality, fragment trajectory, face movement direction and velocity as well as the optimal detonator initiation system. Even though The high-speed image analysis technique has been widely used in foreign countries, its applications can hardly be found in Korea. This thesis aims at carrying out a fundamental study for optimizing the blast design and evaluation using the high-speed digital image analysis. A series of experimentation were performed at two large surface blasting sites with the rock type of shale and granite, respectively. Emulsion and ANFO were the explosives used for the study. Based on the digital images analysis, displacement and velocity of the free face were scrutinized along with the analysis fragment size distribution. In addition, AUTODYN, 2-D FEM model, was applied to simulate detonation pressure, detonation velocity, response time for the initiation of the free face movement and face movement shape. The result show that regardless of the rock type, due to the displacement and the movement velocity have the maximum near the center of charged section the free face becomes curved like a bow. Compared with ANFO, the cases with Emulsion result in larger detonation pressure and velocity and faster reaction for the displacement initiation.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.149-162
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• 2005

This paper suggest a way to detect a specific wanted figure in public places such as subway stations and banks by comparing color face images extracted from the real time CCTV with the face images of designated specific figures. Assuming that the characteristic of the surveillance camera allows the face information in screens to change arbitrarily and to contain information on numerous faces, the accurate detection of the face area was focused. To solve this problem, the normalization work using subsampling with $20{\times}20$ pixels on arbitrary face images, which is based on the Perceptron Neural Network model suggested by R. Rosenblatt, created the effect of recogning the whole face. The optimal linear filter and the histogram shaper technique were employed to minimize the outside interference such as lightings and light. The addition operation of the egg-shaped masks was added to the pre-treatment process to minimize unnecessary work. The images finished with the pre-treatment process were divided into three reception fields and the information on the specific location of eyes, nose, and mouths was determined through the neural network. Furthermore, the precision of results was improved by constructing the three single-set network system with different initial values in a row.

• Economic and Environmental Geology
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• v.28 no.3
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• pp.199-211
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• 1995

The deep sea camera system could render it possible to obtain the detailed information of the nodule distribution, but difficult to estimate nodule abundance quantitatively. In order to estimate nodule abundance quantitatively from deep seabed photographs, the nodule abundance equation was derived from the box core data obtained in KODOS area(long.: $154^{\circ}{\sim}151^{\circ}W$, lat.: $9^{\circ}{\sim}12^{\circ}N$) during two survey cruises carried out in 1989 and 1990. The regression equation derived by considering extent of burial of nodule to Handa's equation compensates for the abundance error attributable to partial burial of some nodules by sediments. An average long axis and average extent of burial of nodules in photographed area are determined according to the surface textures of nodules, and nodule coverage is calculated by the image analysis method. Average nodule abundance estimated from seabed photographs by using the equation is approximately 92% of the actual average abundance in KODOS area. The measured sampling points by box core or free fall grab are in general very sparse and hence nodule abundance distribution should be interpolated and extrapolated from measured data to uncharacterized areas. The another goal of this study is to depict continuous distribution of nodule abundance in KODOS area by using PC-version of geostatistical model in which several stages are systematically proceeded. Geostatistics was used to analyse spatial structure and distribution of regionalized variable(nodule abundance) within sets of real data. In order to investigate the spatial structure of nodule abundance in KODOS area, experimental variograms were calculated and fitted to a spherical models in isotropy and anisotropy, respectively. The spherical structure models were used to map out distribution of the nodule abundance for isotropic and anisotropic models by using the kriging method. The result from anisotropic model is much more reliable than one of isotropic model. Distribution map of nodule abundance produced by PC-version of geostatistical model indicates that approximately 40% of KODOS area is considered to be promising area(nodule abundance > $5kg/m^2$) for mining in case of anisotropy.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.125-126
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• 2007

In this paper, the floating body with vertical plate is introduced with a study on the flow patterns and characteristics in around the floating body by using 2 frame particle tracking method. This paper introduce an analysis method to predict the characteristics if flow around the neighboring fields if Floating Body with vertical plate in order to investigate a high performance model. Flow visualization has conducted in a drcu1ating water channel by a high speed camera and etc. Flow phenomena according to turbulence intensity distribution and flow separation around the floating body with vertical plate were obtained by two-dimensional PIV system.