• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.357-363
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• 2024

As AR display virtual technology enters public learning life extensively, the way in which reality and virtual connection are connected is also changing. The purpose of this paper is to study the expression between the 3D connection sensory information visualization experience and virtual reality enhancement through the visual direction sensory information visualization experience of the plane. It is analyzed by examining the basic setting method compared to the current application of AR display and flat visualization cases. The scope of this paper is to enable users to have a better experience through the relationship with sensory visualization, centering on eye tracking technology in the four categories of AR display connection design: gesture connection, eye tracking, voice connection, and sensor. Focusing on eye tracking technology through AR display interaction and current application and comparative analysis of flat visualization cases, the geometric consistency of visual figures, light and color consistency, combination of multi-sensory interaction methods, rational content display, and smart push presented sensory visualization in virtual reality more realistically and conveniently, providing a simple and convenient sensory visualization experience to the audience.

• Spatial Information Research
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• v.11 no.3
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• pp.261-274
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• 2003

The effective probability-based tile pre-fetching algorithm and the collaborative cache replacement algorithm are able to reduce the response time for user's requests by transferring tiles which will be used in advance and determining tiles which should be removed from the restrictive cache space of a client based on the future access probabilities in Web GISs(Geographical Information Systems). The Web GISs have multi-level abstracted data for the quick response time when zoom-in and zoom-out queries are requested. But, the previous pre-fetching algorithm is applied on only two-dimensional pre-fetching space, and doesn't consider expanded pre-fetching space for multi-level abstracted data in Web GISs. In this thesis, a probability-based pre-fetching algorithm for multi-level abstracted in Web GISs was proposed. This algorithm expanded the previous two-dimensional pre-fetching space into three-dimensional one for pre-fetching tiles of the upper levels or lower levels. Moreover, we evaluated the effect of the proposed pre-fetching algorithm by using a simulation method. Through the experimental results, the response time for user requests was improved 1.8%∼21.6% on the average. Consequently, in Web GISs with multi-level abstracted data, the proposed pre-fetching algorithm and the collaborative cache replacement algorithm can reduce the response time for user requests substantially.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.4
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• pp.593-601
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• 2016

This study was carried out to establish an effective marketing strategy based on Importance-Performance Analysis (IPA) of rice-convenience foods. IPA is one of the most efficient and simple methods to evaluate product quality. Data were collected from 652 people (320 males and 332 females) and analyzed by SPSS 19.0. Subjects consumed rice-convenience foods as a snack substitute (19.3%), breakfast (20.7%), lunch (37.4%), dinner (15.2%), and late-night meal (7.4%). The purpose for consumption of rice-convenience foods were as follows: light meal (34.8%), lack of time to prepare meal (42.2%), favorite restaurant is not nearby (2.3%), save money (3.4%), and outdoor activities (9.7%). All attributes about rice-convenience foods were categorized into intrinsic property and extrinsic property. As a result of factor analysis, health, sensibility, and diversity factors were extracted from intrinsic property. In addition, dependence and appearance factors were drawn from extrinsic property. In analyzing the differences between importance and performance, there were significant differences; 16 items in the intrinsic property (P<0.01), and 10 items in the extrinsic property (P<0.001). The IPA matrix is composed of four quadrants, and each represents different strategies; the first, 'keep up the good work', the second, 'possible overkill', the third, 'low priority for management', and the fourth, 'concentrate management'. As a result, factors of rice-convenience foods positioned in the fourth quadrant were 'safety (from food additives, etc.)' and 'price' in the intrinsic property and 'nutrition label' and 'safety of packaging material' in the extrinsic property. They need to be improved immediately. In this study, rice-convenience food factors for continuous maintenance and concentrative improvement were compared by IPA. Based upon the results of this study, it is necessary to develop methods to make efficient use of limited resources and practical marketing strategies.

• Korean Journal of Heritage: History & Science
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• v.53 no.1
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• pp.24-33
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• 2020

In excavated bronze artifacts, corrosion products of various shapes and colors are observed due to multiple corrosion factors coexisting in the burial environment, and these corrosion products can constitute important data not only in terms of long-term corrosion-related information, but also in connection with preservation of artifacts. As such, scientific analysis is being carried out on the corrosion layer and corrosion products of bronze artifacts, and the corrosion mechanism and the characteristics of corrosion products elucidated, which is essential for interpreting the exposed burial environment and its association with corrosion factors inside the burial environment. In this study, after classifying excavated bronze artifacts according to alloy ratio and fabrication technique, comprehensive analysis of the surface of corrosion artifacts, corrosion layer, and corrosion products was carried out to investigate the corrosion mechanism, formation process of the corrosion layer, and characteristics of corrosion products. The study designated two groups according to alloy ratio and fabrication technique. In Group 1, which involved a Cu-Sn-Pb alloy and had no heat treatment, the surface was rough and external corrosion layers were formed on a part, or both sides, of the inside and the outside, and the surface was observed as being green or blue. α+δ phase selection corrosion was found in the metal and some were found to be concentrated in an empty space with a purity of 95 percent or more after α+δ phase corrosion. The Cu-Sn alloy and heat-treated Group 2 formed a smooth surface with no external corrosion layer, and a dark yellow surface was observed. In addition, no external corrosion layer was observed, unlike Group 1, and α corrosion was found inside the metal. In conclusion, it can be seen that the bronze artifacts excavated from the same site differ in various aspects, including the formation of the corrosion layer, the shape and color of the corrosion products, and the metal ion migration path, depending on the alloy ratio and fabrication technique. They also exhibited different corrosion characteristics in the same material, which means that different forms of corrosion can occur depending on the exposure environment in the burial setting. Therefore, even bronze artifacts excavated from the same site will have different corrosion characteristics depending on alloy ratio, fabrication technique, and exposure environment. The study shows one aspect of corrosion characteristics in specific areas and objects; further study of corrosion mechanisms in accordance with burial conditions will be required through analysis of the corrosive layer and corrosive product characteristics of bronze artifacts from various regions.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1332-1344
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• 2004

Upon development of information super-highway and multimedia-related technoiogies in recent years, more efficient technologies to transmit, store and retrieve the multimedia data are required. Among such technologies, firstly, it is common that the semantic-based image retrieval is annotated separately in order to give certain meanings to the image data and the low-level property information that include information about color, texture, and shape Despite the fact that the semantic-based information retrieval has been made by utilizing such vocabulary dictionary as the key words that given, however it brings about a problem that has not yet freed from the limit of the existing keyword-based text information retrieval. The second problem is that it reveals a decreased retrieval performance in the content-based image retrieval system, and is difficult to separate the object from the image that has complex background, and also is difficult to extract an area due to excessive division of those regions. Further, it is difficult to separate the objects from the image that possesses multiple objects in complex scene. To solve the problems, in this paper, I established a content-based retrieval system that can be processed in 5 different steps. The most critical process of those 5 steps is that among RGB images, the one that has the largest and the smallest background are to be extracted. Particularly. I propose the method that extracts the subject as well as the background by using an Image, which has the largest background. Also, to solve the second problem, I propose the method in which multiple objects are separated using RGB channel selection techniques having optimized the excessive division of area by utilizing Watermerge's threshold value with the object separation using the method of RGB channels separation. The tests proved that the methods proposed by me were superior to the existing methods in terms of retrieval performances insomuch as to replace those methods that developed for the purpose of retrieving those complex objects that used to be difficult to retrieve up until now.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1319-1326
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• 2019

The KARI(Korea Aerospace Research Institute) operates the government satellite information application consultation to cope with ever-increasing demand for satellite images in the public sector, and carries out various support projects including the generation and provision of mosaic images on the Korean Peninsula every year to enhance user convenience and promote the use of satellite images. In particular, the government has wanted to increase the utilization of mosaic images on the Korean Peninsula and seek to classify and update mosaic images so that users can use them in their businesses easily. However, it is necessary to test and verify whether the classification results of the mosaic images can be utilized in the field since the original spectral information is distorted during pan-sharpening and color balancing, and there is a limitation that only R, G, and B bands are provided. Therefore, in this study, the reliability of the classification result of the mosaic image was compared to the result of KOMPSAT-3 image. The study found that the accuracy of the classification result of KOMPSAT-3 image was between 81~86% (overall accuracy is about 85%), while the accuracy of the classification result of mosaic image was between 69~72% (overall accuracy is about 72%). This phenomenon is interpreted not only because of the distortion of the original spectral information through pan-sharpening and mosaic processes, but also because NDVI and NDWI information were extracted from KOMPSAT-3 image rather than from the mosaic image, as only three color bands(R, G, B) were provided. Although it is deemed inadequate to distribute classification results extracted from mosaic images at present, it is believed that it will be necessary to explore ways to minimize the distortion of spectral information when making mosaic images and to develop classification techniques suitable for mosaic images as well as the provision of NIR band information. In addition, it is expected that the utilization of images with limited spectral information could be increased in the future if related research continues, such as the comparative analysis of classification results by geomorphological characteristics and the development of machine learning methods for image classification by objects of interest.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.

• Journal of Wetlands Research
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• v.17 no.3
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• pp.251-263
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• 2015

This study suggested a novel approach of estimating the optimal probability density function (OPDF) of the annual maximum rainfall time series (AMRT) combining the L-moment ratio diagram and the geographical information system. This study also reported several interesting geographical characteristics of the AMRT in Korea. To achieve this purpose, this study determined the OPDF of the AMRT with the duration of 1-, 3-, 6-, 12-, and 24-hours using the method of L-moment ratio diagram for each of the 67 rain gages in Korea. Then, a map with the Thiessen polygons of the 67 rain gages colored differently according the different type of the OPDF, was produced to analyze the spatial trend of the OPDF. In addition, this study produced the color maps which show the fitness of a given probability density function to represent the AMRT. The study found that (1) both L-skewness and L-kurtosis of the AMRT have clear geographical trends, which means that the extreme rainfall events are highly influenced by geography; (2) the impact of the altitude on these two rainfall statistics is greater for the mountaneous region than for the non-mountaneous region. In the mountaneous region, the areas with higher altitude are more likely to experience the less-frequent and strong rainfall events than the areas with lower altitude; (3) The most representative OPDFs of Korea except for the Southern edge are Generalized Extreme Value distribution and the Generalized Logistic distribution. The AMRT of southern edge of Korea was best represented by the Generalized Pareto distribution.

• Journal of the Korean earth science society
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• v.32 no.7
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• pp.809-831
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• 2011

Sea Surface Temperature (SST) is one of the most important oceanic variables to understand rapidly-changing climate, so that accurate and error-free SST images should be presented in school science textbooks. However, satelliteobserved SST images in the high-school textbooks presented some errors caused by various reasons. This study analyzed 36 satellite images for SST presented in 24 kinds of high-school textbooks (earth science I and II textbooks on the basis of the 7th National Curriculum) for 17 items. This study investigated errors in image processing such as cloud removal, land masking, color bar, geological and time information, and some erroneous expressions related to the fundamental information of satellites. Twenty five pre-service teachers filled out a survey about several problematic satellite images, and their responses were analyzed. As a result, most of the pre-service teachers did not recognize the errors associated with image processing and tended to comprehend the SST errors as real oceanographic phenomena such as sea ice, river outflow, or cold current. Therefore, satellite SST images in the textbooks should be accurately presented by including detailed items suggested in this study.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.20-27
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• 2006

Multi-level thresholding is a method that is widely used in image segmentation. However most of the existing methods are not suited to be directly used in applicable fields and moreover expanded until a step of image segmentation. This paper proposes region-based multi-level thresholding as an image segmentation method. At first we classify pixels of each color channel to two clusters by using EWFCM(Entropy-based Weighted Fuzzy C-Means) algorithm that is an improved FCM algorithm with spatial information between pixels. To obtain better segmentation results, a reduction of clusters is then performed by a region-based reclassification step based on a similarity between regions existing in a cluster and the other clusters. The clusters are created using the classification information of pixels according to color channel. We finally perform a region merging by Bayesian algorithm based on Kullback-Leibler distance between a region and the neighboring regions as a post-processing method as many regions still exist in image. Experiments show that region-based multi-level thresholding is superior to cluster-, pixel-based multi-level thresholding, and the existing mettled. And much better segmentation results are obtained by the post-processing method.