• Journal of the Korean Wood Science and Technology
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• v.37 no.1
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• pp.37-47
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• 2009

For the inspection of wood, machine vision is the most common automated inspection method used at present. It is required to sort wood products by grade and to locate surface defects prior to cut-up. Many different sensing methods have been applied to inspection of wood including optical, ultrasonic, X-ray sensing in the wood industry. Nowadays the scanning system mainly employs CCD line-scan camera to meet the needs of accurate detection of lumber defects and real-time image processing. But this system needs exact feeding system and low deviation of lumber thickness. In this study low cost CCD area sensor was used for the development of image processing system for lumber being fed. When domestic red pine being fed on the conveyer belt, lumber images of irregular term of captured area were acquired because belt conveyor slipped between belt and roller. To overcome incorrect image merging by the unstable feeding speed of belt conveyor, it was applied template matching algorithm which was a measure of the similarity between the pattern of current image and the next one. Feeding the lumber over 13.8 m/min, general area sensor generates unreadable image pattern by the motion blur. The red channel of RGB filter showed a good performance for removing background of the green conveyor belt from merged image. Threshold value reduction method that was a image-based thresholding algorithm performed well for knot detection.

• Journal of the Korean Wood Science and Technology
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• v.37 no.1
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• pp.56-64
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• 2009

The purpose of this study was to investigate and develop an eco-friendly wood adhesive based on vegetable oil (especially soybean oil), the renewable and sustainable natural resources, using ozonification technology for the chemical structure modification. The soybean oil (SBO) was reacted with $O_3$ at the rate of 7.13 g/h for different times, 15 minutes, 30 minutes, 60 minutes, and 120 minutes. The investigation of the modified chemical structure of the ozonized SBOs were conducted using FT-IR, $^1H$-NMR, MALDI-TOF MS, and GC/MS. As ozonification time increased, the peak of the unsaturated double bonds was disappeared and aldehyde or carboxyl peak appeared because ozonification broke the oil into small molecules. The plywoods were made at $110^{\circ}C$ with 30 seconds/mm hot-press time using the different ozonized SBO/pMDI adhesives and were tested for the dry, wet, cyclic boil test according to the Korea Industrial Standard F3101 Ordinary plywood. The bond strengths gradually increased with increasing ozonification time. The weight ratio 1:1 (ozonized SBO/pMDI), all strengths in 15, 30 and 60 minuets, exceeded constantly the dry, wet, cyclic boiling standard requirement. The range of ozonification time and weight ratio can fulfil1 the requirment of the wet test standard were 30~60 minutes and more than 0.5 pMDI. From the comprehensive view on the results of above experiments, it could be confirmed through experiments that ozonized SBO/pMDI has characteristics of effective reactivity and wet stability showed as an excellent candidate of wood adhesive applications.

• Journal of the Korean Wood Science and Technology
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• v.35 no.6
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• pp.118-125
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• 2007

To obtain design data for built-up beams used as headers in light-frame timber construction, three members of $2{\times}6$ ($38{\times}140 mm$), $2{\times}8$ ($38{\times}184 mm$), $2{\times}10$ ($38{\times}235 mm$) and $2{\times}12$ ($38{\times}286 mm$) were built up as specimens of bending tests. The bending strengths of built-up headers were obtained through bending tests of these specimens, and it was considered that span tables can be calculated for various loading conditions based on the bending strengths of built-up headers. The bending strengths of built-up headers were determined as the bending stresses at 10 mm deflection of specimens from the results of bending tests of built-up beam specimens. Span tables for built-up headers were considered to be obtained by assuming five loading conditions for headers used in exterior walls and two loading conditions for headers used in interior walls. Among these 7 loading conditions, 5 loading conditions applied to headers in exterior walls included dead loads, live loads and snow loads and 2 loading conditions applied to headers in interior walls included dead loads and live loads.

• Journal of Soil and Groundwater Environment
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• v.20 no.4
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• pp.1-7
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• 2015

The degradation of off-flavors which is 2-Methylisoborneol (2-MIB) and geosmin by means of ultrasound (US) and pulsed ultraviolet (PUV) irradiation and its combination with catalyst (wire mesh, wire mesh coated TiO₂, and TiO₂) and additive (H₂O₂) were investigated via water system. A combination treatment of TiO₂ and H₂O₂ heterogeneity with US (24 kHz) and PUV (6000 W) has shown improved results in destroying 2-MIB and geosmin, which may be attributed to chain reactions by the enhanced formation of hydroxyl radicals (·OH) through H₂O₂ dissociation and reactive oxide ions of TiO₂ addition. Rapid degradation of off-flavors occurred within 2 min under PUV process with H₂O₂ 100 mg/L (81.5% for 2- MIB; 79.3% for geosmin) and TiO₂ 100 mg/L (83.7% for 2-MIB; 79.8% for geosmin), while compared with H2O2 100 mg/L (58.4% for 2-MIB; 58.0% for geosmin) and TiO₂ 100 mg/L (59.2% for 2-MIB; 38.5% for geosmin) within 5 min under US process. Surprisingly, the emphasis was given on the comparison with the same injected energies between PUV and US on degradation efficiency. Based on the injected energy comparison, the US provided better degradation performance under equal input power of 200 kJ with H₂O₂ 100 mg/L, while compared with H₂O₂ 100 mg/L under PUV process. Our findings suggest that US can be more effective compared to PUV for the degradation of off-flavors in aspect of energy consumptions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.51-58
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• 2018

Recently, various satellite sensors have been developed and it is becoming more convenient to acquire multitemporal satellite images. Therefore, various researches are being actively carried out in the field of utilizing change detection techniques such as disaster and land monitoring using multitemporal satellite images. In particular, researches related to the development of unsupervised change detection techniques capable of extracting rapidly change regions have been conducted. However, there is a disadvantage that false detection occurs due to a spectral difference such as a seasonal change. In order to overcome the disadvantages, this study aimed to reduce the false alarm detection due to seasonal effects using the direction vector generated by applying the $S^2CVA$ (Sequential Spectral Change Vector Analysis) technique, which is one of the unsupervised change detection methods. $S^2CVA$ technique was applied to RapidEye images of the same and different seasons. We analyzed whether the change direction vector of $S^2CVA$ can remove false positives due to seasonal effects. For the quantitative evaluation, the ROC (Receiver Operating Characteristic) curve and the AUC (Area Under Curve) value were calculated for the change detection results and it was confirmed that the change detection performance was improved compared with the change detection method using only the change magnitude vector.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.317-325
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• 2020

UAV (Unmanned Aerial Vehicle) photogrammetry has recently emerged as a means of obtaining highly precise and rapid spatial information due to its cost-effectiveness and high efficiency. However, current procedures or regulations for quantitative quality verification methods and certification processes for UAV-images are insufficient. In addition, the current verification method for image quality is not evaluated by an MTF (Modulation Transfer Function) analysis or edge response analysis, which can analyze the degree of contrast including image resolution, and only relies on the GSD (Ground Sample Distance) analysis. Therefore, in this study, the edge response analysis using a Slanted edge target was performed along with GSD analysis to confirm the necessity of analyzing edge response analysis in UAV-images quality analysis. Furthermore, a Matlab GUI-based software tool was developed to help streamline the edge response analysis. As a result, we confirmed the need for edge response analysis since the outputs of the edge response analysis from the same GSD had significantly different outcomes. Additionally, we found that the quality of the edge response analysis of UAV-images is proportional to the performance of the camera mounted on the UAV.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.204-205
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• 2011

In thin film silicon solar cells, p-i-n structure is adopted instead of p/n junction structure as in wafer-based Si solar cells. PECVD is a most widely used thin film deposition process for a-Si:H or ${\mu}c$-Si:H solar cells. For best performance of thin film silicon solar cell, the dopant profiles at p/i and i/n interfaces need to be as sharp as possible. The sharpness of dopant profiles can easily achieved when using multi-chamber PECVD equipment, in which each layer is deposited in separate chamber. However, in a single-chamber PECVD system, doped and intrinsic layers are deposited in one plasma chamber, which inevitably impedes sharp dopant profiles at the interfaces due to the contamination from previous deposition process. The cross-contamination between layers is a serious drawback of a single-chamber PECVD system in spite of the advantage of lower initial investment cost for the equipment. In order to resolve the cross-contamination problem in single-chamber PECVD systems, flushing method of the chamber with NH3 gas or water vapor after doped layer deposition process has been used. In this study, a new plasma process to solve the cross-contamination problem in a single-chamber PECVD system was suggested. A single-chamber VHF-PECVD system was used for superstrate type p-i-n a-Si:H solar cell manufacturing on Asahi-type U FTO glass. A 80 MHz and 20 watts of pulsed RF power was applied to the parallel plate RF cathode at the frequency of 10 kHz and 80% duty ratio. A mixture gas of Ar, H2 and SiH4 was used for i-layer deposition and the deposition pressure was 0.4 Torr. For p and n layer deposition, B2H6 and PH3 was used as doping gas, respectively. The deposition temperature was $250^{\circ}C$ and the total p-i-n layer thickness was about $3500{\AA}$. In order to remove the deposited B inside of the vacuum chamber during p-layer deposition, a high pulsed RF power of about 80 W was applied right after p-layer deposition without SiH4 gas, which is followed by i-layer and n-layer deposition. Finally, Ag was deposited as top electrode. The best initial solar cell efficiency of 9.5 % for test cell area of 0.2 $cm^2$ could be achieved by applying the in-situ plasma cleaning method. The dependence on RF power and treatment time was investigated along with the SIMS analysis of the p-i interface for boron profiles.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.239-240
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• 2012

With advancements in semiconductor device technologies, manufacturing processes are getting more complex and it became more difficult to maintain tighter process control. As the number of processing step increased for fabricating complex chip structure, potential fault inducing factors are prevail and their allowable margins are continuously reduced. Therefore, one of the key to success in semiconductor manufacturing is highly accurate and fast fault detection and classification at each stage to reduce any undesired variation and identify the cause of the fault. Sensors in the equipment are used to monitor the state of the process. The idea is that whenever there is a fault in the process, it appears as some variation in the output from any of the sensors monitoring the process. These sensors may refer to information about pressure, RF power or gas flow and etc. in the equipment. By relating the data from these sensors to the process condition, any abnormality in the process can be identified, but it still holds some degree of certainty. Our hypothesis in this research is to capture the features of equipment condition data from healthy process library. We can use the health data as a reference for upcoming processes and this is made possible by mathematically modeling of the acquired data. In this work we demonstrate the use of recurrent neural network (RNN) has been used. RNN is a dynamic neural network that makes the output as a function of previous inputs. In our case we have etch equipment tool set data, consisting of 22 parameters and 9 runs. This data was first synchronized using the Dynamic Time Warping (DTW) algorithm. The synchronized data from the sensors in the form of time series is then provided to RNN which trains and restructures itself according to the input and then predicts a value, one step ahead in time, which depends on the past values of data. Eight runs of process data were used to train the network, while in order to check the performance of the network, one run was used as a test input. Next, a mean squared error based probability generating function was used to assign probability of fault in each parameter by comparing the predicted and actual values of the data. In the future we will make use of the Bayesian Networks to classify the detected faults. Bayesian Networks use directed acyclic graphs that relate different parameters through their conditional dependencies in order to find inference among them. The relationships between parameters from the data will be used to generate the structure of Bayesian Network and then posterior probability of different faults will be calculated using inference algorithms.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.2
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• pp.118-126
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• 2004

Grid is a new Information Technology (IT) concept of "super Internet" for high-performance computing: worldwide collections of high-end resources such as supercomputers, storage, advanced instruments and immerse environments. The Grid is expected to bring together geographically and organizationally dispersed computational resources, such as CPUs, storage systems, communication systems, real-time data sources and instruments, and human collaborators. The term "the Grid" was coined in the mid1990s to denote a proposed distributed computing infrastructure for advanced science and engineering. The term computational Grids refers to infrastructures aimed at allowing users to access and/or aggregate potentially large numbers of powerful and sophisticated resources. More formally, Grids are defined as infrastructure allowing flexible, secure, and coordinated resource sharing among dynamic collections of individuals, institutions and resources referred to as virtual Organizations. GRID is an emerging IT as a kind of next generation Internet technology which will fit very well with agrometeorological services in the future. I believe that it would contribute to the resource sharing in agrometeorology by providing super computing power, virtual storage, and efficient data exchanges, especially for developing countries that are suffering from the lack of resources for their agmet services at national level. Thus, the establishment of CAgM-GRID based on existing RADMINSII is proposed as a part of FWIS of WMO.part of FWIS of WMO.

• Journal of Biosystems Engineering
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• v.42 no.4
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• pp.314-322
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• 2017

Purpose: This study was conducted to investigate the hot air drying characteristics of squash slices depending on the drying conditions (input air velocity, input air temperature, and sample thickness). Methods: The developed drying system was equipped with a controllable air blower and electric finned heater, drying chamber, and ventilation fan. Squash (summer squash called Korean zucchini) samples were cut into slices of two different thicknesses (5 and 10 mm). These were then dried at two different input air temperatures (60 and $70^{\circ}C$) and air velocities (5 and 7 m/s). Six well-known drying models were tested to describe the experimental drying data. A non-linear regression analysis was applied to determine model constants and statistical indices such as the coefficient of determination ($R^2$), reduced chi-square (${\chi}^2$), and root mean square error (RMSE). In addition, the effective moisture diffusivity ($D_{eff}$) was estimated based on the curve of ln(MR) versus drying time. Results: The results clearly showed that drying time decreased with an increase in input air temperature. Slice thickness also affected the drying time. Air velocity had a greater influence on drying time at $70^{\circ}C$ than at $60^{\circ}C$ for both thicknesses. All drying models accurately described the drying curve of squash slices regardless of slice thickness and drying conditions; the Modified Henderson and Pabis model had the best performance with the highest R2 and the lowest RMSE values. The effective moisture diffusivity ($D_{eff}$) changes, obtained from Fick's diffusion method, were between $1.67{\times}10^{-10}$ and $7.01{\times}10^{-10}m^2/s$. The moisture diffusivity was increased with an increase in input air temperature, velocity, and thickness. Conclusions: The drying time of squash slices varied depending on input temperature, velocity, and thickness of slices. The further study is necessary to figure out optimal drying condition for squash slices with retaining its original quality.