• 한국지구물리탐사학회:학술대회논문집
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• 2002.09a
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• pp.139-162
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• 2002

Since weak zones or geological lineaments are likely to be eroded, weak zones may develop beneath rivers, and a careful evaluation of ground condition is important to construct structures passing through a river. Dc resistivity surveys, however, have seldomly applied to the investigation of water-covered area, possibly because of difficulties in data aquisition and interpretation. The data aquisition having high quality may be the most important factor, and is more difficult than that in land survey, due to the water layer overlying the underground structure to be imaged. Through the numerical modeling and the analysis of case histories, we studied the method of resistivity survey at the water-covered area, starting from the characteristics of measured data, via data acquisition method, to the interpretation method. We unfolded our discussion according to the installed locations of electrodes, ie., floating them on the water surface, and installing at the water bottom, since the methods of data acquisition and interpretation vary depending on the electrode location. Through this study, we could confirm that the dc resistivity method can provide the fairly reasonable subsurface images. It was also shown that installing electrodes at the water bottom can give the subsurface image with much higher resolution than floating them on the water surface. Since the data acquired at the water-covered area have much lower sensitivity to the underground structure than those at the land, and can be contaminated by the higher noise, such as streaming potential, it would be very important to select the acquisition method and electrode array being able to provide the higher signal-to-noise ratio data as well as the high resolving power. The method installing electrodes at the water bottom is suitable to the detailed survey because of much higher resolving power, whereas the method floating them, especially streamer dc resistivity survey, is to the reconnaissance survey owing of very high speed of field work.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.45-58
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• 2014

The Korean Culture Contents spread out to Worldwide, because the Korean wave is sweeping in the world. The contents stand in the middle of the Korean wave that we are used it. Each country is ongoing to keep their Culture industry improve the national brand and High added value. Performing contents is important factor of arousal in the enterprise industry. To improve high arousal confidence of product and positive attitude by populace is one of important factor by advertiser. Culture contents is the same situation. If culture contents have trusted by everyone, they will give information their around to spread word-of-mouth. So, many researcher study to measure for person's arousal analysis by statistical survey, physiological response, body movement and facial expression. First, Statistical survey has a problem that it is not possible to measure each person's arousal real time and we cannot get good survey result after they watched contents. Second, physiological response should be checked with surround because experimenter sets sensors up their chair or space by each of them. Additionally it is difficult to handle provided amount of information with real time from their sensor. Third, body movement is easy to get their movement from camera but it difficult to set up experimental condition, to measure their body language and to get the meaning. Lastly, many researcher study facial expression. They measures facial expression, eye tracking and face posed. Most of previous studies about arousal and interest are mostly limited to reaction of just one person and they have problems with application multi audiences. They have a particular method, for example they need room light surround, but set limits only one person and special environment condition in the laboratory. Also, we need to measure arousal in the contents, but is difficult to define also it is not easy to collect reaction by audiences immediately. Many audience in the theater watch performance. We suggest the system to measure multi-audience's reaction with real-time during performance. We use difference image analysis method for multi-audience but it weaks a dark field. To overcome dark environment during recoding IR camera can get the photo from dark area. In addition we present Multi-Audience Engagement Index (MAEI) to calculate algorithm which sources from sound, audience' movement and eye tracking value. Algorithm calculates audience arousal from the mobile survey, sound value, audience' reaction and audience eye's tracking. It improves accuracy of Multi-Audience Engagement Index, we compare Multi-Audience Engagement Index with mobile survey. And then it send the result to reporting system and proposal an interested persons. Mobile surveys are easy, fast, and visitors' discomfort can be minimized. Also additional information can be provided mobile advantage. Mobile application to communicate with the database, real-time information on visitors' attitudes focused on the content stored. Database can provide different survey every time based on provided information. The example shown in the survey are as follows: Impressive scene, Satisfied, Touched, Interested, Didn't pay attention and so on. The suggested system is combine as 3 parts. The system consist of three parts, External Device, Server and Internal Device. External Device can record multi-Audience in the dark field with IR camera and sound signal. Also we use survey with mobile application and send the data to ERD Server DB. The Server part's contain contents' data, such as each scene's weights value, group audience weights index, camera control program, algorithm and calculate Multi-Audience Engagement Index. Internal Device presents Multi-Audience Engagement Index with Web UI, print and display field monitor. Our system is test-operated by the Mogencelab in the DMC display exhibition hall which is located in the Sangam Dong, Mapo Gu, Seoul. We have still gotten from visitor daily. If we find this system audience arousal factor with this will be very useful to create contents.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.73-85
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• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.79-94
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• 2013

Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.

• Trans-
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• v.12
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• pp.51-79
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• 2022

This study investigates the methods for deriving colors which can serve as a reference to users such as designers and or contents creators who search for online images from the web portal sites using specific words for color planning and more. Two experiments were conducted in order to accomplish this. Digital scenery photos within the geographic scope of Korea were downloaded from web portal sites, and those photos were studied to find out what colors were used to describe daytime and nighttime. Machine learning was used as the study methodology to classify colors in daytime and nighttime, and KSCA was used to derive the color frequency of daytime and nighttime photos and to compare and analyze the two results. The results of classifying the colors of daytime and nighttime photos using machine learning show that, when classifying the colors by 51~100%, the area of daytime colors was approximately 2.45 times greater than that of nighttime colors. The colors of the daytime class were distributed by brightness with white as its center, while that of the nighttime class was distributed with black as its center. Colors that accounted for over 70% of the daytime class were 647, those over 70% of the nighttime class were 252, and the rest (31-69%) were 101. The number of colors in the middle area was low, while other colors were classified relatively clearly into day and night. The resulting color distributions in the daytime and nighttime classes were able to provide the borderline color values of the two classes that are classified by brightness. As a result of analyzing the frequency of digital photos using KSCA, colors around yellow were expressed in generally bright daytime photos, while colors around blue value were expressed in dark night photos. For frequency of daytime photos, colors on the upper 40% had low chroma, almost being achromatic. Also, colors that are close to white and black showed the highest frequency, indicating a large difference in brightness. Meanwhile, for colors with frequency from top 5 to 10, yellow green was expressed darkly, and navy blue was expressed brightly, partially composing a complex harmony. When examining the color band, various colors, brightness, and chroma including light blue, achromatic colors, and warm colors were shown, failing to compose a generally harmonious arrangement of colors. For the frequency of nighttime photos, colors in approximately the upper 50% are dark colors with a brightness value of 2 (Munsell signal). In comparison, the brightness of middle frequency (50-80%) is relatively higher (brightness values of 3-4), and the brightness difference of various colors was large in the lower 20%. Colors that are not cool colors could be found intermittently in the lower 8% of frequency. When examining the color band, there was a general harmonious arrangement of colors centered on navy blue. As the results of conducting the experiment using two methods in this study, machine learning could classify colors into two or more classes, and could evaluate how close an image was with certain colors to a certain class. This method cannot be used if an image cannot be classified into a certain class. The result of such color distribution would serve as a reference when determining how close a certain color is to one of the two classes when the color is used as a dominant color in the base or background color of a certain design. Also, when dividing the analyzed images into several classes, even colors that have not been used in the analyzed image can be determined to find out how close they are to a certain class according to the color distribution properties of each class. Nevertheless, the results cannot be used to find out whether a specific color was used in the class and by how much it was used. To investigate such an issue, frequency analysis was conducted using KSCA. The color frequency could be measured within the range of images used in the experiment. The resulting values of color distribution and frequency from this study would serve as references for color planning of digital design regarding natural scenery in the geographic scope of Korea. Also, the two experiments are meaningful attempts for searching the methods for deriving colors that can be a useful reference among numerous images for content creator users of the relevant field.

• The Journal of Korean Society for Radiation Therapy
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• v.27 no.2
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• pp.157-166
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• 2015

Purpose : Cyber-Knife tumor tracking system, based on the correlation relationship between the position of a tumor which moves in response to the real time respiratory cycle signal and respiration was obtained by the LED marker attached to the outside of the patient, the location of the tumor to predict in advance, the movement of the tumor in synchronization with the therapeutic device to track real-time tumor, is a system for treating. The purpose of this study, in the cyber knife tumor tracking radiation therapy, trying to evaluate the accuracy of tumor tracking radiation therapy system due to the change in the form of unpredictable sudden breathing due to cough and sleep. Materials and Methods : Breathing Log files that were used in the study, based on the Respiratory gating radiotherapy and Cyber-knife tracking radiosurgery breathing Log files of patients who received herein, measured using the Log files in the form of a Sinusoidal pattern and Sudden change pattern. it has been reconstituted as possible. Enter the reconstructed respiratory Log file cyber knife dynamic chest Phantom, so that it is possible to implement a motion due to respiration, add manufacturing the driving apparatus of the existing dynamic chest Phantom, Phantom the form of respiration we have developed a program that can be applied to. Movement of the phantom inside the target (Ball cube target) was driven by the displacement of three sizes of according to the size of the respiratory vertical (Superior-Inferior) direction to the 5 mm, 10 mm, 20 mm. Insert crosses two EBT3 films in phantom inside the target in response to changes in the target movement, the End-to-End (E2E) test provided in Cyber-Knife manufacturer depending on the form of the breathing five times each. It was determined by carrying. Accuracy of tumor tracking system is indicated by the target error by analyzing the inserted film, additional E2E test is analyzed by measuring the correlation error while being advanced. Results : If the target error is a sine curve breathing form, the size of the target of the movement is in response to the 5 mm, 10 mm, 20 mm, respectively, of the average $1.14{\pm}0.13mm$, $1.05{\pm}0.20mm$, with $2.37{\pm}0.17mm$, suddenly for it is variations in breathing, respective average $1.87{\pm}0.19mm$, $2.15{\pm}0.21mm$, and analyzed with $2.44{\pm}0.26mm$. If the correlation error can be defined by the length of the displacement vector in the target track is a sinusoidal breathing mode, the size of the target of the movement in response to 5 mm, 10 mm, 20 mm, respective average $0.84{\pm}0.01mm$, $0.70{\pm}0.13mm$, with $1.63{\pm}0.10mm$, if it is a variant of sudden breathing respective average $0.97{\pm}0.06mm$, $1.44{\pm}0.11mm$, and analyzed with $1.98{\pm}0.10mm$. The larger the correlation error values in both the both the respiratory form, the target error value is large. If the motion size of the target of the sine curve breathing form is greater than or equal to 20 mm, was measured at 1.5 mm or more is a recommendation value of both cyber knife manufacturer of both error value. Conclusion : There is a tendency that the correlation error value between about target error value magnitude of the target motion is large is increased, the error value becomes large in variation of rapid respiration than breathing the form of a sine curve. The more the shape of the breathing large movements regular shape of sine curves target accuracy of the tumor tracking system can be judged to be reduced. Using the algorithm of Cyber-Knife tumor tracking system, when there is a change in the sudden unpredictable respiratory due patient coughing during treatment enforcement is to stop the treatment, it is assumed to carry out the internal target validation process again, it is necessary to readjust the form of respiration. Patients under treatment is determined to be able to improve the treatment of accuracy to induce the observed form of regular breathing and put like to see the goggles monitor capable of the respiratory form of the person.

• Journal of Acupuncture Research
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• v.22 no.3
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• pp.155-167
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• 2005

Objectives : The purpose of this study was to investigate the anti-inflammatory effect of Cobrotoxin on binding affinity of cobrotoxin with P50, $IKK{\alpa}$ and $IKK{\beta}$, activities of NF-${\kappa}B$, Cell viability of astrocyte, expressions of protein molecules of NF-${\kappa}B$ such as P50, P-$1{kappa}B$, $1{\kappa}B$ and iflammation related genes such as Cox-2, iNOS, cPLA2 in the SNP or LPS induced Inflammatory pathway of Rats' astrocytes. Methods : In this study, The expression of cytosolic phospholipase A2, Nitric oxcide, Cyclooxygenase-2 and inducible nitrogen oxide synthase was determined by western blotting with corresponding antibodies, and the generation of NF-${\kappa}B$ was assayed by EMSA method in astrocytes of rats. The Cell viability of astrocytes was determined by MTT assay, and Binding affinity of Cobrotoxin with P50, $IKK{\alpha}$ and $IKK{\beta}$ was assayed by Surface plasmon resonance analysis, and NF-${\kappa}B$ dependent luciferase activity was determined by luciferase analysis, and Uptake of cobrotoxin in astrocytes was identified by Confocal laser scanning microscope Results : 1. Compared with control, LPS-induced NF-${\kappa}B$ DNA binding activity was decreased significantly by 0.1, $0.5{\mu}g/m{\ell}$ of Cobrotoxin in Astrocyte. 2. Compared with control, LPS-induced NF-kB dependent luciferase expression was decreased significantly by 0.1, 0.5 and $1{\mu}g/m{\ell}$ of Cobrotoxin in Astrocyte. 3. Compared with control, SNP induced P50, $I{\kappa}B$ expressions in astrocyte were decreased significantly by 0.1, 0.5 and $1{\mu}g/m{\ell}$ of Cobrotoxin and P-$1{\kappa}B$ expression was decreased significantly by 0.5 and $1{\mu}g/m{\ell}$ of Cobrotoxin. 4. Compared with control, LPS induced P50, $1{\kappa}B$ expressions in astrocyte were decreased significantly by 0.5 and $1{\mu}g/m{\ell}$ of Cobrotoxin. 5. Compared with control, SNP induced Cox-2, iNOS, CPLA2 expressions in astrocyte were decreased significantly by $1{\mu}g/m{\ell}$ of Cobrotoxin. 6. Compared with control, LPS induced Cox-2, cPLA2 expressions in astrocyte were decreased significantly by 0.1, 0.5, $1{\mu}g/m{\ell}$ of Cobrotoxin and iNOS expression was decreased significantly by 0.5, $1{\mu}g/m{\ell}$ of Cobrotoxin. 7. Compared with $0.5{\mu}g/m{\ell}$ of Cobrotoxin, SNP-induced NF-${\kappa}B$ DNA bindins activity in astrocyte was increased significantly by Cobrotoxin $0.5{\mu}g/m{\ell}$ with DTT 1mM and Cobrotoxin $0.5{\mu}g/m{\ell}$ with DTT 5mM. 8. Compared with $0.5{\mu}g/m{\ell}$ of Cobrotoxin, LPS-induced NF-${\kappa}B$ DNA binding activity in astrocyte was increased significantly by Cobrotoxin $0.5{\mu}g/m{\ell}$ with DTT 1mM, Cobrotoxin $0.5{\mu}g/m{\ell}$ with DTT 5mM, Cobrotoxin $0.5{\mu}g/m{\ell}$with GSH 1mM and Cobrotoxin $0.5{\mu}g/m{\ell}$ with GSH 5mM 9. Compared with $0.1{\mu}g/m{\ell}$ of cobrotoxin, SNP induced P50 expressions in astrocyte were increased significantly by Cobrotoxin $0.5{\mu}g/m{\ell}$ with DTT 1mM, Cobrotoxin $0.5{\mu}g/m{\ell}$ with DTT 5mM Cobrotoxin $0.5{\mu}g/m{\ell}$ with GSH 1mM and Cobrotoxin $0.5{\mu}g/m{\ell}$ with GSH 5mM. 10. The uptake of the labeled cobrotoxin into the cells was shown under a confocal laser scanning microscope. cobrotoxin was uptaken into the membrane and nucleus of astrocytes. Conclusions : In summary, the present results demonstrate that cobrotoxin directly binds to sulfhydryl group of p50 and IKKS resulting In the reduction of translocation of p50 and IkB release, thereby inhibits activation of NF-${\kappa}B$, and suggest that pico to nanomolar range of cobrotoxin could inhibit the expression of genes in the NF-${\kappa}B$ signal pathway.

• MISULJARYO - National Museum of Korea Art Journal
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• v.96
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• pp.18-53
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• 2019

The paintings Gyeongpodae Pavilion and Chongseokjeong Pavilion were recently donated to the National Museum of Korea and unveiled to the public for the first time at the 2019 special exhibition "Through the Eyes of Joseon Painters: Real Scenery Landscapes of Korea." These two paintings carry significant implications for understanding Joseon art history. Because the fact that they were components of a folding screen produced after a sightseeing tour of the Gwandong regions in 1557 has led to a broadening of our understanding of sixteenth-century landscape painting. This paper explores the art historical meanings of Gyeongpodae Pavilion and Chongseokjeong Pavilion by examining the contents in the two paintings, dating them, analyzing their stylistic characteristics, and comparing them with other works. The production background of Gyeongpodae Pavilion and Chongseokjeong Pavilion can be found in the colophon of Chongseokjeong Pavilion. According to this writing, Sangsanilro, who is presumed to be Park Chung-gan (?-1601) in this paper, and Hong Yeon(?~?) went sightseeing around Geumgangsan Mountain (or Pungaksan Mountain) and the Gwandong region in the spring of 1557, wrote a travelogue, and after some time produced a folding screen depicting several famous scenic spots that they visited. Hong Yeon, whose courtesy name was Deokwon, passed the special civil examination in 1551 and has a record of being active until 1584. Park Chung-gan, whose pen name was Namae, reported the treason of Jeong Yeo-rip in 1589. In recognition of this meritorious deed, he was promoted to the position of Deputy Minister of the Ministry of Punishments, rewarded with the title of first-grade pyeongnan gongsin(meritorious subject who resolved difficulties), and raised to Lord of Sangsan. Based on the colophon to Chongseokjeong Pavilion, I suggest that the two paintings Gyeongpodae Pavilion and Chongseokjeong Pavilion were painted in the late sixteenth century, more specifically after 1557 when Park Chung-gan and Hong Yeon went on their sightseeing trip and after 1571 when Park, who wrote the colophon, was in his 50s or over. The painting style used in depicting the landscapes corresponds to that of the late sixteenth century. The colophon further states that Gyeongpodae Pavilion and Chongseokjeong Pavilion were two paintings of a folding screen. Chongseokjeong Pavilion with its colophon is thought to have been the final panel of this screen. The composition of Gyeongpodae Pavilion recalls the onesided three-layered composition often used in early Joseon landscape paintings in the style of An Gyeon. However, unlike such landscape paintings in the An Gyeon style, Gyeongpodae Pavilion positions and depicts the scenery in a realistic manner. Moreover, diverse perspectives, including a diagonal bird's-eye perspective and frontal perspective, are employed in Gyeongpodae Pavilion to effectively depict the relations among several natural features and the characteristics of the real scenery around Gyeongpodae Pavilion. The shapes of the mountains and the use of moss dots can be also found in Welcoming an Imperial Edict from China and Chinese Envoys at Uisungwan Lodge painted in 1557 and currently housed in the Kyujanggak Institute for Korean Studies at Seoul National University. Furthermore, the application of "cloud-head" texture strokes as well as the texture strokes with short lines and dots used in paintings in the An Gyeon style are transformed into a sense of realism. Compared to the composition of Gyeongpodae Pavilion, which recalls that of traditional Joseon early landscape painting, the composition of Chongseokjeong Pavilion is remarkably unconventional. Stone pillars lined up in layers with the tallest in the center form a triangle. A sense of space is created by dividing the painting into three planes(foreground, middle-ground, and background) and placing the stone pillars in the foreground, Saseonbong Peaks in the middle-ground, and Saseonjeong Pavilion on the cliff in the background. The Saseonbong Peaks in the center occupy an overwhelming proportion of the picture plane. However, the vertical stone pillars fail to form an organic relation and are segmented and flat. The painter of Chongseokjeong Pavilion had not yet developed a three-dimensional or natural spatial perception. The white lower and dark upper portions of the stone pillars emphasize their loftiness. The textures and cracks of the dense stone pillars were rendered by first applying light ink to the surfaces and then adding fine lines in dark ink. Here, the tip of the brush is pressed at an oblique angle and pulled down vertically, which shows an early stage of the development of axe-cut texture strokes. The contrast of black and white and use of vertical texture strokes signal the forthcoming trend toward the Zhe School painting style. Each and every contour and crack on the stone pillars is unique, which indicates an effort to accentuate their actual characteristics. The birds sitting above the stone pillars, waves, and the foam of breaking waves are all vividly described, not simply in repeated brushstrokes. The configuration of natural features shown in the above-mentioned Gyeongpodae Pavilion and Chongseokjeong Pavilion changes in other later paintings of the two scenic spots. In the Gyeongpodae Pavilion, Jukdo Island is depicted in the foreground, Gyeongpoho Lake in the middle-ground, and Gyeongpodae Pavilion and Odaesan Mountain in the background. This composition differs from the typical configuration of other Gyeongpodae Pavilion paintings from the eighteenth century that place Gyeongpodae Pavilion in the foreground and the sea in the upper section. In Chongseokjeong Pavilion, stone pillars are illustrated using a perspective viewing them from the sea, while other paintings depict them while facing upward toward the sea. These changes resulted from the established patterns of compositions used in Jeong Seon(1676~1759) and Kim Hong-do(1745~ after 1806)'s paintings of Gwandong regions. However, the configuration of the sixteenth-century Gyeongpodae Pavilion, which seemed to have no longer been used, was employed again in late Joseon folk paintings such as Gyeongpodae Pavilion in Gangneung. Famous scenic spots in the Gwandong region were painted from early on. According to historical records, they were created by several painters, including Kim Saeng(711~?) from the Goryeo Dynasty and An Gyeon(act. 15th C.) from the early Joseon period, either on a single scroll or over several panels of a folding screen or several leaves of an album. Although many records mention the production of paintings depicting sites around the Gwandong region, there are no other extant examples from this era beyond the paintings of Gyeongpodae Pavilion and Chongseokjeong Pavilion discussed in this paper. These two paintings are thought to be the earliest works depicting the Gwandong regions thus far. Moreover, they hold art historical significance in that they present information on the tradition of producing folding screens on the Gwandong region. In particular, based on the contents of the colophon written for Chongseokjeong Pavilion, the original folding screen is presumed to have consisted of eight panels. This proves that the convention of painting eight views of Gwangdong had been established by the late sixteenth century. All of the existing works mentioned as examples of sixteenth-century real scenery landscape painting show only partial elements of real scenery landscape painting since they were created as depictions of notable social gatherings or as a documentary painting for practical and/or official purposes. However, a primary objective of the paintings of Gyeongpodae Pavilion and Chongseokjeong Pavilion was to portray the ever-changing and striking nature of this real scenery. Moreover, Park Chung-gan wrote a colophon and added a poem on his admiration of the scenery he witnessed during his trip and ruminated over the true character of nature. Thus, unlike other previously known real-scenery landscape paintings, these two are of great significance as examples of real-scenery landscape paintings produced for the simple appreciation of nature. Gyeongpodae Pavilion and Chongseokjeong Pavilion are noteworthy in that they are the earliest remaining examples of the historical tradition of reflecting a sightseeing trip in painting accompanied by poetry. Furthermore, and most importantly, they broaden the understanding of Korean real-scenery landscape painting by presenting varied forms, compositions, and perspectives from sixteenth-century real-scenery landscape paintings that had formerly been unfound.