• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.679-686
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• 2012

KTX step 1 April 2004, after the opening, the second phase of the project was opened in November 2010. High-speed rail after the opening and continue to increase the demand of high-speed rail, Have the speed of competitive advantage compared too the means of transportation. The opening of these high-speed rail has led to changes of the move, the company's position, and the spatial structure of the population of reorganization, such as the social, economic, transportation. In this study, survey data using the High Speed Rail Station EMME/2 of the program to take advantage of the 2-Dimentional Blancing trip distribution to investigate the passage through the trip distribution by the estimation of the parameters of the model to estimate the distribution of the means of access and high-speed rail station to reproduce and Analysis of the results by means of access parameters (${\theta}$) autos 0.0395, buses 0.0390, subway 0.0650, taxi 0.0415, the frequency distribution (Trip Length Frequency Distribution: TLFD) were analyzed survey data value model with the results of comparing $R^2$ cars analysis and model values similar survey data 0.909 bus 0.923, subway 0.745 to 0.922, taxi, F test P value analysis is smaller than 0.05 at the 95% confidence level as a note that was judged to have been. Trip frequency distribution analysis, but in the future, set the unit to 5km-trip frequency distribution middle zone Units from small zone units (administrative district) segmentation research is needed, and can reflect the trip distance 0~5 km interval combined function to take advantage of the gravity model and the 3-Dimentional Blancing applied research is needed to be considered.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.1
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• pp.174-182
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• 2014

To monitor the wind-induced responses of buildings, conventional real-time kinematic (RTK) methods based on two global positioning system (GPS) receivers (e.g., a reference and a rover) are widely applied. However, these methods can encounter problems such as difficulty in securing and maintaining a space for a reference station. With the recently developed virtual reference station (VRS)-RTK approach, the position of a structure can be measured using only a rover receiver. In this study, to evaluate the applicability of VRS-RTK methods in monitoring the lateral structural responses of frame structures, we performed free vibration tests on a one-story frame model (the first natural frequency of 1 Hz) and a three-story frame model (the first natural frequency of 0.85 Hz). To assess the reliability of the displacement and acceleration responses measured by the GPS, we performed a concurrent measurement using laser displacement sensors and an accelerometer. The accelerometer results were consistent with the GPS measurements in terms of the time history and frequency content. Furthermore, to derive an appropriate sampling rate for the continuous monitoring of buildings, the errors in the displacement responses were evaluated at different GPS sampling rates (5, 10, 20 Hz). The results indicate that as the sampling rate increased, the errors in the displacement responses decreased. In addition, in the three-story model, all modal components (first, second, and third modes) could be recorded at a sampling rate of 20 Hz.

• Korean Journal of Environment and Ecology
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• v.37 no.5
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• pp.337-346
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• 2023

Although wildlife bridge are built as a way to reduce habitat fragmentation caused by road construction, there is still a lot of debate about their effectiveness. Monitoring methods such as footprint traps and camera traps are used evaluate the effectiveness of wildlife bridge, but there is a limit to evaluate of effectiveness. In this study, the degree of use the wildlfe bridge was surveyed by striped field mouse that is likely use the wildlife bridge and surrounding as a habitat with capture-mark-recapture method.(Apodemus agraius). The distance and route of movement were identified by connecting the capture points, and the environmental factors on the use of the wildlife bridge implemented a generalized linear model(GLM) with the capture number of captured as a dependent variable. Consequently of capture, no individuals crossing the wildlife bridge, striped field mouse use the wildlife bridge as a habitat.The environmental factors affecting the use of mice were vegetation cover(1~2m, 2~8m, over 8m), vegetation construction, maximum diameter at breast height were positively correlated and slope was nagatively correlated. In conclusion, it is expected that the effectiveness of the wildlife bridge will be further improved by planting shrubs and trees and preventing high slope and cut slope increasing the utilization of the rat, such as being used as a food source in the ecosystem.

• Journal of the Korean association of regional geographers
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• v.22 no.4
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• pp.887-911
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• 2016

The empirical law that transverse dunes migrate inversely with their heights leads logically to the prediction that multiple dune ridges will converse to a single huge dune by merging. This contradicts the existence of the steady state dune fields on the Earth. The recent studies have emphasized dune collisions as a key mechanism to the stability of dunefield. The roles of wind shadow aspect ratio, however, have yet to be fully explored. This research aims to investigate the potential roles of wind shadow aspect ratio in the dynamical behaviors of transverse dune field. The simplified model is established for this, based upon allometric properties of transverse dunes, wind speedup on the stoss slope and sand trapping efficiency. The derived governing equations can be transformed to the zoning criteria and vector field for dune evolution. The dynamics analysis indicates that wind shadow aspect ratios do not produce convergent areas on the behavior space; rather, they just act as one of the factors that affect the trajectories of dune evolution. Though the model cannot represent the stability of dune field, but seem to produce a reasonable exponent for dune spacing-height relations.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.253-260
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• 2006

As media and product became variety, the propensity of the people is be coming various. From diversity, there we could search for some popularity is called 'the mania.' When Mania takes shape, the product will being longer even masses in these days only have short-term life. Also there are hundreds of animations that has short-term life whom people forgot everyday they watch. However, the animations could lasting its value which has the Mania. This thesis is a studies on the constitution of Mania from animation 'Fullmetal Alchemist's Character The BONES had made. We can learn that the audience were not just like the animation, but get crazy for it by comparing Japanese animation industry in those days; before it has been shrinking and manufacturing various contents from Fullmetal Alchemist means there is enough consumtions. There are many reasons to form Mania group, but specially the character symbols at the works as a whole. From this study is to know a cause of how the animation 'Fullmetal Alchemist' made huge Mania group, and significance value of the work those group left.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• The korean journal of orthodontics
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• v.28 no.4 s.69
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• pp.563-580
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• 1998

This study was designed to analysis the displacement and stress distribution of individual tooth by orthodontic force during distal on masse movement of the maxillary dentition. In this study, three dimensional finite element analysis was used. Author made the finite element model of maxillary teeth, periodontal ligament, alveolar bone and bracket with anatomic and physiologic characteristics on computer. Author analysed and evaluated the displacement and stress distribution of individual tooth when extraoral force, Class II intermaxillary elastics, ideal arch wire, MEAW and tip back bend were used for distal on masse movement of the maxillary dentition. These analyses were also applied in the case of the maxillary second molar were not extracted. Author compared the results of the cases which maxillary second molar were extracted or not. The results were expressed quantitatively and visually. Author obtained following results, 1. When anterior headgear was applied, the posterior translation, posterior tipping, and vertical displacement of teeth were produced more in the anterior segment of the dentition. 2. When Class II intermaxillary elastics were applied in the ideal arch wire, the teeth displacement were usually produced in the anterior segment. But when tip back bend were added in the ideal arch wire, the orthodontic force produced by elastics were transmitted to the posterior segment. As increasing the tip back bend, posterior translation and lingual tipping of anterior teeth were decreased, posterior translation and tipping displacement of posterior teeth were increased, and extrusion of anterior teeth by Class II elastics were decreased 3. When MDAW and Class II elastics were applied, the teeth movement were sir flu with the case of ideal arch wire and Class II elastics, but more small and uniform teeth displacement were produced Compared with the ideal arch wire, posterior tipping of the posterior segment were more produced than lingual tipping displacement of the anterior segment. 4. When the maxillary second molar without orthodontic appliance existed, the displacement of maxillary first molar were decreased.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.4
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• pp.467-478
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• 2016

In this paper, we try to find the optimal locations of NeNB(Nomadic evolved NodeB)s for maximizing the overall throughput of the PS-LTE networks. Since finding optimal locations of all NeNBs in a given area is NP-hard(Non-deterministic Polynomial time-hard) problem, we proposed a PSO-based heuristic approach. In order to evaluate the performance, we conducted two experiments. We compared performance with other schemes such as Exhaustive Search, Random Walk Search, and locating neighboring NeNBs with the same NeNB-to-NeNB distance. The proposed method showed the similar results to the exhaustive search method in terms of locating optimal position and user's data throughput. The proposed method, however, has the fast and consistent convergence time.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.3
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• pp.217-227
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• 2012

On 31 March 2007, the abnormal wave occurred along western coast of Korean including Yeonggwang. In this paper, this event is studied using available field measurement data for the event analysis and numerical model for reproducing the unknown waves. We found several 1-min interval tidal elevation and mean sea level pressure (MSLP) data along the western coast of Korea and analyzed it using wavelet technique. We computed the arrival time and the propagation direction of abnormal wave using wavelet results and performed the numerical simulation using 2 dimensional shallow water wave model. The sea level under the forcing of air pressure jump was obviously amplified by the Proudman resonant effect. The computed sea levels compared with observations are underestimated, but the order of arrival time at the tidal station showed good agreement.

• Journal of Navigation and Port Research
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• v.45 no.3
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• pp.165-172
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• 2021

Breaking wave is one of the important design factors in the design of coastal and port structures as they are directly related to various physical phenomena occurring on the coast, such as onshore currents, sediment transport, shock wave pressure, and energy dissipation. Due to the inherent complexity of the breaking wave, many empirical formulas have been proposed to predict breaker indices such as wave breaking height and breaking depth using hydraulic models. However, the existing empirical equations for breaker indices mainly were proposed via statistical analysis of experimental data under the assumption of a specific equation. In this study, a new Munk-type empirical equation was proposed to predict the height of breaking waves based on a representative linear supervised machine learning technique with high predictive performance in various research fields related to regression or classification challenges. Although the newly proposed breaker height formula was a simple polynomial equation, its predictive performance was comparable to that of the currently available empirical formula.