• Journal of Korean Theatre Studies Association
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• no.53
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• pp.167-202
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• 2014

When video composes mise-en-scene during the performance, it reflects the aspect of contemporary image culture, where the individual as creator joins in the image culture through the device of cell phone and computer remediating the former video technology. It also closely related with the contemporary theatre culture in which 1960's and 1970's video art was weaved into the contemporary performance theatre. With these cultural background, theatre practitioners regarded media-friendly mise-en-scene as an alternative facing the cultural landscape the linear representational narrative did not correspond to the present culture. Nonetheless, it can not be ignored that video in the performance theatre is remediating its historical function: to criticize the social reality. to enrich the aesthetic or emotional reality. I focused video in the performance theatre could feature the object with the image by realizing the realtime relay, emphasizing the situation within the frame, and strengthening the reality by alluding the object as a gesutre. So I explored its two historical manuel. First, video recorded the spot, communicated the information, and arose the audience's recognition of the object to its critical function. Second, video in performance theatre could redistribute perceptual way according to the editing method like as close up, slow motion, multiple perspective, montage and collage, and transformation of the image to the aesthetic function. Reminding the historical function of video in contemporary performance theatre, I analyzed two shows, Schaubuhne's Hamlet and Lenea de Sombra's Amarillo which were introduced to Korean audiences during the 2010 Seoul Theatre Olympics. It is known to us that Ostermeir found real social reality as a text and made the play the context. In this, he used video as a vehicle to penetrate the social reality through the hero's perspective. It is also noteworthy that Ostermeir understood Hamlet's dilemma as these days' young generation's propensity. They delayed action while being involved in image culture. Besides his use of video in the piece revitalized the aesthetic function of video by hypermedial perceptual method. Amarillo combined documentary theatre method with installation, physical theatre, and video relay on the spot, and activated aesthetic function with the intermediality, its interacting co-relationship between the media. In this performance theatre, video has recorded and pursued the absent presence of the real people who died or lost in the desert. At the same time it fantasized the emotional aspect of the people at the moment of their death, which would be opaque or non prominent otherwise. As a conclusion, I found the video in contemporary performance theatre visualized the rupture between the media and perform their intermediality. It attempted to disturb the transparent immediacy to invoke the spectator's perception to the theatrical situation, to open its emotional and spiritual aspect, and to remind the realities as with Schaubuhne's Hamlet and Lenea de Sombra's Amarillo.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.279-289
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• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.6
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• pp.57-65
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• 2010

Physical activity of the people has decreased due to a sedentary lifestyle according to developing the economy throughout the world. It is thought to increase the risk of chronic diseases, including obesity, diabetes, etc. People are interested in walking, which is an easy activity to engage in as an antidote to chronic diseases. The aim of this study is to increase the diminishing physical activity of modem society by inducing walking as part of everyday life through building a walking-based activity-friendly city where people can live merrily, safely and pleasantly. For this purpose, this study conducted a satisfaction survey to dwellers of Jinhae on the physical pedestrian environments which affect determining walking participation and intentions of people, and also provided a valid model to evaluate the effects of the physical environmental factors on walking satisfaction using factor analysis and multiple linear regression analysis. The results are summarized as follows. The 18 variables of the physical pedestrian environments were selected based on pre-literature reviews. The results of the satisfaction surveys showed that the satisfaction of crossing aids in segments was highest, while the building feature was the lowest. Factor analysis was run through a two-step process. The first analysis was conducted to examine the adequacy of this factor analysis on the selected 18 variables. As a result, two variables were removed and the remaining 16 variables were extracted to the four factors by second analysis. Each factor was named function of path, effect of traffic, amenity and safety based on the each factor's commonality. Each factor score of the extracted four factors was set as the independent variable, while the overall walking satisfaction was set as the dependent variable. Then, the multiple linear regression analysis was conducted and showed that all four factors had a positive influence on the overall satisfaction of walking, especially the 'function of path' and 'amenity' factors, followed by 'effect of traffic' and 'safety'. The results of this research will be used as foundational data for creating a walking-based activity-friendly city.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.931-946
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• 2017

The purpose of this study is to observe and analyze soil moisture conditions with high resolution and to evaluate its application feasibility to agriculture. For this purpose, we used three Landsat-8 OLI (Operational Land Imager)/TIRS (Thermal Infrared Sensor) optical and thermal infrared satellite images taken from May to June 2015, 2016, and 2017, including the rural areas of Jeollabuk-do, where 46% of agricultural areas are located. The soil moisture conditions at each date in the study area can be effectively obtained through the SPI (Standardized Precipitation Index)3 drought index, and each image has near normal, moderately wet, and moderately dry soil moisture conditions. The temperature vegetation dryness index (TVDI) was calculated to observe the soil moisture status from the Landsat-8 OLI/TIRS images with different soil moisture conditions and to compare and analyze the soil moisture conditions obtained from the SPI3 drought index. TVDI is estimated from the relationship between LST (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) calculated from Landsat-8 OLI/TIRS satellite images. The maximum/minimum values of LST according to NDVI are extracted from the distribution of pixels in the feature space of LST-NDVI, and the Dry/Wet edges of LST according to NDVI can be determined by linear regression analysis. The TVDI value is obtained by calculating the ratio of the LST value between the two edges. We classified the relative soil moisture conditions from the TVDI values into five stages: very wet, wet, normal, dry, and very dry and compared to the soil moisture conditions obtained from SPI3. Due to the rice-planing season from May to June, 62% of the whole images were classified as wet and very wet due to paddy field areas which are the largest proportions in the image. Also, the pixels classified as normal were analyzed because of the influence of the field area in the image. The TVDI classification results for the whole image roughly corresponded to the SPI3 soil moisture condition, but they did not correspond to the subdivision results which are very dry, wet, and very wet. In addition, after extracting and classifying agricultural areas of paddy field and field, the paddy field area did not correspond to the SPI3 drought index in the very dry, normal and very wet classification results, and the field area did not correspond to the SPI3 drought index in the normal classification. This is considered to be a problem in Dry/Wet edge estimation due to outlier such as extremely dry bare soil and very wet paddy field area, water, cloud and mountain topography effects (shadow). However, in the agricultural area, especially the field area, in May to June, it was possible to effectively observe the soil moisture conditions as a subdivision. It is expected that the application of this method will be possible by observing the temporal and spatial changes of the soil moisture status in the agricultural area using the optical satellite with high spatial resolution and forecasting the agricultural production.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.19 no.2
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• pp.118-126
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• 1986

Vibrio vulnificus is a recently recognized halophilic organism that nay cause serious human infections. Patients infected with V. vulnificus often have a history of exposure to the sea, suggesting that the organism may be common inhabitant of marine environment. The purpose of this experiment is to investigate the distribution and bacteriological characteristics of V. vulnificus. The strain used in this experiment was isolated from sea water and sea products such as common octopus (Octopus variabilis), ark shell (Anadara broughtonii), blue crab (Ericheir japonica), and sea squirt (Synthia roretzi) collected in Pusan area from July to October in 1985. V. vulnificus was frequently isolated in August when temperature of sea water was around $26^{\circ}C$ and rarely isolated in October when temperature of sea water was around $18.5^{\circ}C$. The distinctive biochemical characteristics of V. vulnificus were ONPG hydrolysis positive and fermented lactose and not grown in peptone water contained $8\%$ NaCl. The optical density at 660 nm of the growth of V. vulnificus was reached maximum level after 8 hours of culture at $35^{\circ}C$ in brain heart infusion broth but that of V. vulnificus was little increased at $15^{\circ}C$ for 14 hours. Optimum temperature and pH for the growth of V. vulnificus were around $35^{\circ}C$ and 8.0. The specific growth rate and the generation time of V. vulnificus isolated from the samples were $1.21\;hr^{-1}$, 34 min at $35^{\circ}C$ and $0.61\;hr^{-1}$, 69 min at $25^{\circ}C$, respectively. V. vulnificus did not grow on eosin-methylene-blue agar, salmonella-shigella agar, deoxycholate agar but grew well on Endo agar, xylose-lysine-deoxycholate agar and hektoen enteric agar. On Endo agar, the colonies of V. vulnificus were red and achieved a diameter of 2 to 4 mm as a feature enabling differentiation of V. vulnificus from other Vibrio spp. V. vulnificus grow well on TCBS agar forming green colonies. V. vulnificus refrigerated at $4^{\circ}C$ exhibited a linear decline of its viablity as 1 log cycle in every 16 hours storage, while V. vulnificus freezed at $-18^{\circ}C$ almost became extinct.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.139-155
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• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

• Investigative Magnetic Resonance Imaging
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• v.18 no.1
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• pp.1-6
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• 2014

Purpose : $T_2{^*}$ relaxation time which includes susceptibility information represents unique feature of tissue. The objective of this study was to investigate $T_2{^*}$ relaxation times of the normal glandular tissue and fat of breast using a 3T MRI system. Materials and Methods: Seven-echo MR Images were acquired from 52 female subjects (age $49{\pm}12 $years; range, 25 to 75) using a three-dimensional (3D) gradient-echo sequence. Echo times were between 2.28 ms to 25.72 ms in 3.91 ms steps. Voxel-based $T_2{^*}$ relaxation times and $R_2{^*}$ relaxation rate maps were calculated by using the linear curve fitting for each subject. The 3D regions-of-interest (ROI) of the normal glandular tissue and fat were drawn on the longest echo-time image to obtain $T_2{^*}$ and $R_2{^*}$ values. Mean values of those parameters were calculated over all subjects. Results: The 3D ROI sizes were $4818{\pm}4679$ voxels and $1455{\pm}785$ voxels for the normal glandular tissue and fat, respectively. The mean $T_2{^*}$ values were $22.40{\pm}5.61ms$ and $36.36{\pm}8.77ms$ for normal glandular tissue and fat, respectively. The mean $R_2{^*}$ values were $0.0524{\pm}0.0134/ms$ and $0.0297{\pm}0.0069/ms$ for the normal glandular tissue and fat, respectively. Conclusion: $T_2{^*}$ and $R_2{^*}$ values were measured from human breast tissues. $T_2{^*}$ of the normal glandular tissue was shorter than that of fat. Measurement of $T_2{^*}$ relaxation time could be important to understand susceptibility effects in the breast cancer and the normal tissue.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.855-866
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• 2017

Several research cases using remote sensing methods to analyze changes of storage and dynamics of groundwater aquifer were reviewed in this paper. The status of groundwater storage, in an area with regional scale, could be qualitatively inferred from geological feature, surface water altimetry and topography, distribution of vegetation, and difference between precipitation and evapotranspiration. These qualitative indicators could be measured by geological lineament analysis, airborne magnetic survey, DEM analysis, LAI and NDVI calculation, and surface energy balance modeling. It is certain that GRACE and InSAR have received remarkable attentions as direct utilization from satellite data for quantification of groundwater storage and dynamics. GRACE, composed of twin satellites having acceleration sensors, could detect global or regional microgravity changes and transform them into mass changes of water on surface and inside of the Earth. Numerous studies in terms of groundwater storage using GRACE sensor data were performed with several merits such that (1) there is no requirement of sensor data, (2) auxiliary data for quantification of groundwater can be entirely obtained from another satellite sensors, and (3) algorithms for processing measured data have continuously progressed from designated data management center. The limitations of GRACE for groundwater storage measurement could be defined as follows: (1) In an area with small scale, mass change quantification of groundwater might be inaccurate due to detection limit of the acceleration sensor, and (2) the results would be overestimated in case of combination between sensor and field survey data. InSAR can quantify the dynamic characteristics of aquifer by measuring vertical micro displacement, using linear proportional relation between groundwater head and vertical surface movement. However, InSAR data might now constrain their application to arid or semi-arid area whose land cover appear to be simple, and are hard to apply to the area with the anticipation of loss of coherence with surface. Development of GRACE and InSAR sensor data preprocessing algorithms optimized to topography, geology, and natural conditions of Korea should be prioritized to regionally quantify the mass change and dynamics of the groundwater resources of Korea.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.30 no.4
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• pp.1-13
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• 2012

Landscape Garden tradition of excellent examples of places that are focused on hydroponics management. South Korea and China, this thing was noticeable among them South Korea which emphasizes the natural contours of the natural streams in accordance with the basic idea to use examples that feature will do. Gardens in China by constructing a flat terrain also naturally expect to find examples of conscious ideas depending on the water and the mountains are characterized. These differences and similarities through the Gardens of the tradition of separating the two countries to build their Garden by site Soswaewon and Zolzengwon appear in the target hand is to identify the characteristics between the director. Research methods literature survey, field survey of the natural environment through the plantation, background history, the people who intend to study, to configure the ground water space, Jian, construction and management has been studied in hydroponics. As a result, Damyang-gun, Jeollanam-do, South Korea in the Garden of the Soswaewon(瀟灑園) organization with inner garden and outer garden of a small, but the scale of production to Yang San-Bo's 'eunilgwan' implement security based rock mooring takes the form of a linear channel and the water came down from riding pending to avoid artifacts gathered again took the form of streams flowing into that. Hutton was a rubble pile structure Jian. Building an Gwangpunggak, Jewoldang, as Daebongdae consist, respectively, depending on the purpose of the mooring was deployed by focusing. The other hand, is located at Suzhou, Jiangsu of China Zolzengwon(拙政園) flat terrain is located on. Largely divided eastern gardens, Central Gardens and the Gardens of the West was conducted by five thirds of the total area of Water accounted for. Pavilion the center of the pond, Seokgasan achieve a variety of landscapes and architectural features that are most of the Ming. The two countries, each region's natural environment and human environment, different, unique characteristics to each other in the implementation of a unique hydroponic Garden tube and ideological backgrounds, but especially the 'eunilgwan' and the terrain that is divided according to the conditions of this study, so fulfilling Garden was conducted.