• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.305-313
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• 2019

Recently, spatial information is being constructed actively based on the images obtained by drones. Because occlusion areas occur due to buildings as well as many obstacles, such as trees, pedestrians, and banners in the urban areas, an efficient way to resolve the problem is necessary. Instead of the traditional way, which replaces the occlusion area with other images obtained at different positions, various models based on deep learning were examined and compared. A comparison of a type of feature descriptor, HOG, to the machine learning-based SVM, deep learning-based DNN, CNN, and RNN showed that the CNN is used broadly to detect and classify objects. Until now, many studies have focused on the development and application of models so that it is impossible to select an optimal model. On the other hand, the upgrade of a deep learning-based detection and classification technique is expected because many researchers have attempted to upgrade the accuracy of the model as well as reduce the computation time. In that case, the procedures for generating spatial information will be changed to detect the occlusion area and replace it with simulated images automatically, and the efficiency of time, cost, and workforce will also be improved.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.347-352
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• 2016

Recently, IoT technology has been applied in various field. In particular, the technology focuses on analysing large amount of data that has been gathered from the environmental sensors, to provide valuable information. This technique has been actively researched in the agro-industrial sector. Many researches are underway in the monitoring and control for growth crop environment in agro-industrial. Normally, the average weather data is provided by the manual agro-control method but the value may differ due to the different region's weather and environment that may cause problem in the disease and insect-pest prevention. In order to develop a suitable integrated system for fruit tree, all the necessary information is obtained from the Jeollanam-do province, which has the high production rate in the Korea. In this paper, we propose an integrated support platform for the growing crops, to minimize the damage caused due to the weather disaster through image analysis, forecasting models, by using the micro-climate weather information collection and CCTV. The fruit tree damage caused by the weather disaster are controlled by utilizing various IoT technology by maintaining the growth environment, which helps in the disease and insect-pest prevention and also helps farmers to improve the expected production.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.726-734
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• 2015

Relational databases used by structuralizing data are the most widely used in data management at present. However, in relational databases, service becomes slower as the amount of data increases because of constraints in the reading and writing operations to save or query data. Furthermore, when a new task is added, the database grows and, consequently, requires additional infrastructure, such as parallel configuration of hardware, CPU, memory, and network, to support smooth operation. In this paper, in order to improve the web information services that are slowing down due to increase of data in the relational databases, we implemented a model to extract a large amount of data quickly and safely for users by processing Hadoop Distributed File System (HDFS) files after sending data to HDFSs and unifying and reconstructing the data. We implemented our model in a Web-based civil affairs system that stores image files, which is irregular data processing. Our proposed system's data processing was found to be 0.4 sec faster than that of a relational database system. Thus, we found that it is possible to support Web information services with a Hadoop-based big data processing technique in order to process a large amount of data, as in conventional relational databases. Furthermore, since Hadoop is open source, our model has the advantage of reducing software costs. The proposed system is expected to be used as a model for Web services that provide fast information processing for organizations that require efficient processing of big data because of the increase in the size of conventional relational databases.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.33-41
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• 2011

In the information communication technology, it is world-widely apparent that trend movement from internet web to smartphone app by users demand and developers environment. So it needs kinds of appropriate technological responses from geo-spatial domain regarding this trend. However, most cases in the smartphone app are the map service and location recognition service, and uses of geo-spatial contents are somewhat on the limited level or on the prototype developing stage. In this study, app for extraction of corner point features using geo-spatial imagery and their linkage to database system are developed. Corner extraction is based on Harris algorithm, and all processing modules in database server, application server, and client interface composing app are designed and implemented based on open source. Extracted corner points are applied LOD(Level of Details) process to optimize on display panel. Additional useful function is provided that geo-spatial imagery can be superimposed with the digital map in the same area. It is expected that this app can be utilized to automatic establishment of POI (Point of Interests) or point-based land change detection purposes.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.167-178
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• 2020

KOMPSAT-3A images have been used in various kinds of applications, since its launch in 2015. However, there were limits to scientific analysis and application extensions of these data, such as vegetation index estimation, because no tool was developed to obtain the surface reflectance required for analysis of the actual land environment. The surface reflectance is a product of performing an absolute atmospheric correction or calibration. The objective of this study is to quantitatively verify the accuracy of top-of-atmosphere reflectance and surface reflectance of KOMPSAT-3A images produced from the OTB open-source extension program, performing the cross-validation with those provided by a site measurement data of RadCalNet, an international Calibration/Validation (Cal/Val) portal. Besides, surface reflectance was obtained from Landsat-8 OLI images in the same site and applied together to the cross-validation process. According to the experiment, it is proven that the top-of-atmosphere reflectance of KOMPSAT-3A images differs by up to ± 0.02 in the range of 0.00 to 1.00 compared to the mean value of the RadCalNet data corresponding to the same spectral band. Surface reflectance in KOMPSAT-3A images also showed a high degree of consistency with RadCalNet data representing the difference of 0.02 to 0.04. These results are expected to be applicable to generate the value-added products of KOMPSAT-3A images as analysisready data (ARD). The tools applied in thisstudy and the research scheme can be extended as the new implementation of each sensor model to new types of multispectral images of compact advanced satellites (CAS) for land, agriculture, and forestry and the verification method, respectively.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.475-486
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• 2020

Climate change scenarios are the basis of research to cope with climate change, and consist of large-scale spatio-temporal data. From the data point of view, one scenario has a large capacity of about 83 gigabytes or more, and the data format is semi-structured, making it difficult to utilize the data through means such as search, extraction, archiving and analysis. In this study, a tool for analyzing extreme climate events based on spatial information is developed to improve the usability of large-scale, multi-period climate change scenarios. In addition, a pilot analysis is conducted on the time and space in which the heavy rain thresholds that occurred in the past can occur in the future, by applying the developed tool to the RCP8.5 climate change scenario. As a result, the days with a cumulative rainfall of more than 587.6 mm over three days would account for about 76 days in the 2080s, and localized heavy rains would occur. The developed analysis tool was designed to facilitate the entire process from the initial setting through to deriving analysis results on a single platform, and enabled the results of the analysis to be implemented in various formats without using specific commercial software: web document format (HTML), image (PNG), climate change scenario (ESR), statistics (XLS). Therefore, the utilization of this analysis tool is considered to be useful for determining future prospects for climate change or vulnerability assessment, etc., and it is expected to be used to develop an analysis tool for climate change scenarios based on climate change reports to be presented in the future.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.653-666
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• 2020

Understanding the vegetation structure is important to manage forest resources for sustainable forest development. With the recent development of technology, it is possible to apply new technologies such as drones and deep learning to forests and use it to estimate the vegetation structure. In this study, the vegetation structure of Gongju, Samchuk, and Seoguipo area was identified by fusion of drone-optical images and LiDAR data using Artificial Neural Networks(ANNs) with the accuracy of 92.62% (Kappa value: 0.59), 91.57% (Kappa value: 0.53), and 86.00% (Kappa value: 0.63), respectively. The vegetation structure analysis technology using deep learning is expected to increase the performance of the model as the amount of information in the optical and LiDAR increases. In the future, if the model is developed with a high-complexity that can reflect various characteristics of vegetation and sufficient sampling, it would be a material that can be used as a reference data to Korea's policies and regulations by constructing a country-level vegetation structure map.

• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.66-76
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• 2013

Although there has been much advance in the development of 3D displays of various purpose, 3D contents are not yet so used as expected in those displays. One well-known obstacle in the enjoyment of 3D contents is visual fatigue, but another major issue is image distortion of 3D contents. In the previous research, Shin, Li, & Kim (2012) reported systematic linear relationship between screen disparity and size perception of a simple object whose retinal size was constant across different disparities. In this research, we intended to generalize the previous finding by using various 3D stimuli in the test of the relationship between screen disparity and size perception of those stimuli. Consistent with previous findings, our data indicated that size perception linearly changes as a function of screen disparity and the linearity was observed in all stimuli types we used in this research. We described the empirical relationship between screen disparity and size perception in the form of prediction function for size perception in which visual angle is the predictor. This function will be very useful in the creation of 3D contents as one can make reasonable predictions on the to-be-perceived size of an object being filmed using screen disparity of their camera setting.

• Korean Journal of Community Nutrition
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• v.12 no.6
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• pp.724-741
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• 2007

This study was carried out to investigate the body weight controls and eating disorders of university students in Gunsan. The subject of the present study included 229 male students (53.8%) and 197 female students (46.2%), totalling 426 students from Kunsan University. The subjects consisted of 56 underweight (13.1%), 265 with normal weight (62.2%), and 105 overweight (24.6%). Especially, in females, 20.8% of them were underweight, which is 6.6% higher than males, showing a significant difference (p<0.001). Regarding body image, 21.8% of the males thought they were fat, while 40.6% of the females thought they were fat. Regarding the perceived body type, shown in the difference between their own size and the ideal size, males recorded 0.03, while females recorded 1.75, showing a major significant difference (p<0.001). Regarding body satisfaction, 33.2% of the males were unsatisfied, while 52.8% of the females were unsatisfied (p<0.001). The social expectations of the male subjects' sizes and weights recorded 2.04, while that of females recorded -2.51, showing that people's opinions expected the female subjects' bodies to be thinner (p<0.001). Additionally, the social expectation of the subjects' weight control recorded an average of 15.22 (13.92 for males, 16.73 for females), showing that the female subjects' felt that people's opinions wished them to lose their weight (p<0.001). Regarding the recognition on weight control, interested males were 49.4%, while interested females were 86.8%, showing the females superior rate (p<0.001). The beliefs in relation to weight control recorded an average of 62.01, with the score of females of 67.89 being significantly higher than that of males which was 56.96. The subjects showed a relatively positive response towards weight control (p<0.001). EAT-26 score was employed to determine the eating attitudes in relation to gender. Here, the final score of males was 15.46, which was significantly lower than that of females, which was 22.21 (p<0.001). Furthermore, regarding the score of eating attitudes in relation to obesity index, the eating disorder scale scores on the questions related to bulimia and diets to lose weight as weight increases were high. However, the eating disorder scale score on oral control, which actually controls food, was low. To control the expansion of excessive weight control attempts and their side effects, the recognition of the students' body types needs to be corrected, and nutrition education programs on eating habits and eating disorders to foster proper weight loss are deemed necessary.

• Journal of Conservation Science
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• v.26 no.1
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• pp.69-76
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• 2010

As the tangible evidence, documentary art records are permanent records to reflect the historical, symbolical, cultural and artistic value. Also, documentary art records are related with mission fulfillment of public institution and it is documentary with administrative, cultural and artistic values as the works of documentary production and application of the administrative image. "The public records management law" was the first time that administration documents were incorporated and in the act No. 3 of administrative records management, the preservation and management system of documentary art records became legislated. The management of documentary art records are difficult to categorize only by the reflect of characteristics or materials. Because documentary art records are collected in many ways and made with materials. It needs to be collected with many informations on basic materials and with the appropriate conservation and management category. Documentary art records do not have lots of demands but the level of consciousness is improving and the possibility of opening to public is increasing for improvement with the right to know. In near future, the documentary art records will be used for the interpretation of historical and cultural preservation and modern cultural heritage could have the value as it is expected. Primarily to prevent deterioration on documentary art records the standard survey card should be made to categorize the damage rate and to check the status on each documentary art records. In addition, establishing a systematic management plan for various documentary art records are needed with the training of professionals for the conservation of documentary art records.