• Journal of the Korean Geotechnical Society
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• v.33 no.11
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• pp.73-82
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• 2017

Recently, offshore bucket cut-off walls were developed to solve several problems in conventional offshore cut-off walls. In this study, a numerical analysis was carried out to investigate the seepage stability of offshore bucket cut-off walls. The ground was assumed as uniform homogeneous sand and steady state flow conditions were applied. The flow condition was compared among 2-dimensional flow (2-D), 2-dimensional concentrated flow (2-DC), and axisymmetric flow. The analysis results showed that the seepage velocities in axisymmetric flow were about 1.5 and 2 times larger than those of 2-DC and 2-D flow conditions, respectively. Thereafter, the axisymmetric flow condition was applied because the seepage flow was concentrated toward the center of the circular-shaped wall. A parametric study was performed varying bucket radius, penetration depth, total head difference between in and outside of the wall. The exit gradient, which used for the calculation of piping stability, decreased with increase of the penetration depth and bucket radius. Design charts were proposed to estimate the factor of safety and the exit gradient at various analysis conditions. Finally, the design equation was proposed to calculate the exit gradient for the preliminary design of the bucket cut-off wall.

• Nuclear Engineering and Technology
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• v.42 no.4
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• pp.442-449
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• 2010

Recently, the neutron irradiation for large diameter silicon (Si)-ingots of more than 8" diameter is requested to satisfy the demand for the neutron transmutation doping silicon (NTD-Si). By increasing the Si-ingot diameter, the radial non-uniformity becomes larger due to the neutron attenuation effect, which results in a limit of the feasible diameter of the Si-ingot. The current evaluation method has a certain limit to precisely evaluate the radial uniformity of Si-ingot because the current evaluation method does not consider the effect of the Si-ingot diameter on the radial uniformity. The objective of this study is to propose a new evaluation method of radial uniformity by improving the conventional evaluation approach. To precisely predict the radial uniformity of a Si-ingot with large diameter, numerical verification is conducted through comparison with the measured data and introducing the new evaluation method. A new concept of a gradient is introduced as an alternative approach of radial uniformity evaluation instead of the radial resistivity gradient (RRG) interpretation. Using the new concept of gradient, the normalized reaction rate gradient (NRG) and the surface normalized reaction rate gradient (SNRG) are described. By introducing NRG, the radial uniformity can be evaluated with one certain standard regardless of the ingot diameter and irradiation condition. Furthermore, by introducing SNRG, the uniformity on the Si-ingot surface, which is ignored by RRG and NRG, can be evaluated successfully. Finally, the radial uniformity flattening methods are installed by the stainless steel thermal neutron filter and additional Si-pipe to reduce SNRG.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.27 no.2
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• pp.109-114
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• 2021

The characteristics of vibrational stress (shock and vibration) during transport and the possibility of damage to the packaged pears by functional PLA tray were investigated. And this study was conducted to analyze how environmental conditions by simulated transport environment affect quality factors such as weight loss (%) and soluble solid content (SSC, %), and firmness (bioyield strength, kPa) of packaged pears by PLA tray and Expanded PET foam pad (Group 1), EPE cushion cup pad and net (Group 2) for exporting. Pears with or without vibration stress were stored for 30 days at low temperatures (5 ± 0.8℃, 80 ± 5% relative humidity). There was the statistically significant difference (p ≤ 0.05) between pears with and without vibration stress for weight loss, soluble solid content, and firmness (bioyield strength) after 30 days storage. Vibration stress accelerated pear quality deterioration during storage, resulting in increased weight loss, soluble solids content, and reduced hardness. The firmness (bioyield strength) and weight changes of pears with PLA trays were smaller than those of conventional packaging box systems. It was determined that the firmness of agricultural products was a quality factor closely related to the storage period and that PLA could be applied.

• Journal of Korean Society of Forest Science
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• v.100 no.1
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• pp.14-24
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• 2011

Anticancer activity of Acer mono aqueous extracts was enhanced by nano-encapsulation process of gelatin. The cytotoxicity on human normal lung cell (HEL299) of the extracts from WE (water extract at 100) showed 23.51%, lower than that from NE (nano-encapsulatioin of water extract of Acer mono) in adding the maximum concentration of 1.0 mg/mL. NE showed more potent scavenging effect as 73.15% than the WE. On SOD-like test, the NE showed highest activity as 32.33% at 1.0 mg/mL concentration. Human stomach adenocarcinoma, liver adenocarcinoma, breast adenocarcinoma and lung adenocarcinoma cell growth were inhibited up to about 59-73%, in adding 1.0 mg/mL of NE. NE was 15% higher than conventional water extraction. Among several cancer cell lines (stomach adenocarcinoma, liver adenocarcinoma), the growth of digestive related cancer cells were most effectively inhibited as about 71-73%. The size of nano particles was in the ranges of 100-200 nm, which can effectively the penetrate into the cells, it was observed by real time confocal microscope. It tells that the aqueous extracts of Acer mono bark could be definitely enhanced by nano-encapsulation process.

• Animal Bioscience
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• v.36 no.3
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• pp.451-460
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• 2023

Objective: This program aimed to reveal the association of feed intrinsic molecular structure with nutrient supply to animals from canola feedstocks and co-products from bio-oil processing. The special objective of this study was to quantify the relationship between molecular spectral feature and nutrient availability and develop nutrient prediction equation with vibrational molecular structure spectral profiles. Methods: The samples of feedstock (canola oil seeds) and co-products (meals and pellets) from different bio-oil processing plants in Canada (CA) and China (CH) were submitted to this molecular spectroscopic technique and their protein and carbohydrate related molecular spectral features were associated with the nutritional results obtained through the conventional methods of analyses for chemical and nutrient profiles, rumen degradable and intestinal digestible parameters. Results: The results showed that the spectral structural carbohydrates spectral peak area (ca. 1,487.8 to 1,190.8 cm^-1) was the carbohydrate structure that was most significant when related to various carbohydrate parameters of canola meals (p<0.05, r>0.50). And spectral total carbohydrate area (ca. 1,198.5 to 934.3 cm^-1) was most significant when studying the various carbohydrate parameters of canola seeds (p<0.05, r>0.50). The spectral amide structures (ca. 1,721.2 to 1,480.1 cm^-1) were related to a few chemical and nutrient profiles, Cornell Net Carbohydrate and Protein System (CNCPS) fractions, truly absorbable nutrient supply based on the Dutch protein system (DVE/OEB), and NRC systems, and intestinal in vitro protein-related parameters in co-products (canola meals). Besides the spectral amide structures, α-helix height (ca. 1,650.8 to 1,643.1 cm^-1) and β-sheet height (ca. 1,633.4 to 1,625.7 cm^-1), and the ratio between them have shown to be related to many protein-related parameters in feedstock (canola oil seeds). Multi-regression analysis resulted in moderate to high R² values for some protein related equations for feedstock (canola seeds). Protein related equations for canola meals and carbohydrate related equations for canola meals and seeds resulted in weak R² and low p values (p<0.05). Conclusion: In conclusion, the attenuated total reflectance Fourier transform infrared spectroscopy vibrational molecular spectroscopy can be a useful resource to predict carbohydrate and protein-relates nutritional aspects of canola seeds and meals.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.681-689
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• 2023

Purpose: Muons are characterized by a strong penetrating ability and can travel through thousands of meters of rock, making them ideal to image large volumes and substances typically impenetrable to, for example, electrons and photons. The feasibility of 3D image reconstruction and material identification based on a cosmic ray muons tomography (MT) system with triangular bar plastic scintillator detectors has been verified in this paper. Our prototype shows potential application value and the authors wish to apply this prototype system to 3D imaging. In addition, an MT experiment with the same detector system is also in progress. Methods: A simulation based on GEANT4 was developed to study cosmic ray muons' physical processes and motion trails. The yield and transportation of optical photons scintillated in each triangular bar of the detector system were reproduced. An image reconstruction algorithm and correction method based on muon scattering, which differs from the conventional PoCA algorithm, has been developed based on simulation data and verified by experimental data. Results: According to the simulation result, the detector system's position resolution is below 1 ~ mm in simulation and 2 mm in the experiment. A relatively legible 3D image of lead bricks in size of 20 cm × 5 cm × 10 cm used our inversion algorithm can be presented below 1× 10⁴ effective events, which takes 16 h of acquisition time experimentally. Conclusion: The proposed method is a potential candidate to monitor the cosmic ray MT accurately. Monte Carlo simulations have been performed to discuss the application of the detector and the simulation results have indicated that the detector can be used in cosmic ray MT. The cosmic ray MT experiment is currently underway. Furthermore, the proposal also has the potential to scan the earth, buildings, and other structures of interest including for instance computerized imaging in an archaeological framework.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.95-109
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• 2008

We numerically analyzed the nonlinear shoaling, a plunging breaker and its accompanying energetic suspension of sediment at a bed, and a redistribution of suspended sediments by a down rush of preceding waves and the following plunger using SPH with a Gaussian kernel function, Lagrangian Dynamic Smagorinsky model (LDS), Van Rijn's pick up function. In that process, we came to the conclusion that the conventional model for the tractive force at a bottom like a quadratic law can not accurately describe the rapidly accelerating flow over a swash zone, and propose new methodology to accurately estimate the bottom tractive force. Using newly proposed wave model in this study, we can successfully duplicate severely deformed water surface profile, free falling water particles, a queuing splash after the landing of water particles on the free surface and a wave finger due to the structured vortex on a rear side of wave crest (Narayanaswamy and Dalrymple, 2002), a circulation of suspended sediments over a swash zone, net transfer of sediments clouds suspended over a swash zone toward the offshore, which so far have been regarded very difficult features to mimic in the computational fluid mechanics.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

• Journal of The Korean Society of Grassland and Forage Science
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• v.4 no.3
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• pp.194-200
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• 1984

Effects of seed coating on establishment, early growth and herbage production were investigated in Pot, Soil box and Field experiments. Seed was coated with 60% Lime, 20% Phosphate and 20% Peatmoss(W/W), also finely sprayed 13% Arabic gum and 2% Methyl cellulose(W/V). Coating were generally 1:20, seed: coat(W/W). 1. In the general growth of the growing stages and different oversown species at 80 days, seed coated was promoted than none in early growth. (Table 2 and 3) 2. Stand counts at 60 days after oversown, seed coated was higher 15% than none, especially, there was advantage due to coating on the medium and large size seeds such as Orchardgrass, Perennial ryegrass and Kentucky bluegrass, but did not assist establishment of the large (Tall fescue) and small (Ladino clover) size seed. 3. Variation of sward composition was not quite different between two treatments, but seed coated was slightly increased the Percentage of sown grasses with advance of cutting time. 4. Total dry metter yield per unit area with seed coated was higher 17% than none in establishment year. 5. Variations in the chemical composition of the herbage and soil were influenced by coating materials in the coating regime (Table 8). 6. From these facts, seed coated also appeared that adequate seedling stands, early growth and herbage production could be obtained with higher than conventional overseeding method under a poor conditions.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.43-62
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• 2019

At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.