• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.55-61
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• 2005

Digital Elevation Model (DEM) generation from remotely sensed imagery is crucial for a variety of mapping applications such as ortho-photo generation, city modeling. High resolution imaging satellites such as SPOT-5, IKONOS, QUICK-BIRD, ORBVIEW constitute an excellent source for efficient and economic generation of DEM data. However, prerequisite knowledge in the areas of sensor modeling, epipolar resampling, and image matching is required to generate DEM from these high resolution satellite imagery. From the above requirements, epipolar resampling emerges as the most important factors. Research attempts in this area are still in high demand and short supply. Another cause that adds to the complication of the problem is that most studies of DEM generation from IKONOS scenes have been based on rational function model. In this paper, we proposed a new methodology for DEM generation from satellite scenes using parallel projection model which is sensor independent, makes it possible for sensor modeling and epipolar resampling by only few control points. The performance and feasibility of the developed methodology is evaluated through real dataset captured by IKONOS.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.101-108
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• 2011

Construction of the Jangbogo antarctic station was planned, and it requires detailed information on topography of the area around the station. The purpose of this research is to generate the topographic map to construct the Jangbogo antarctic station using the satellite image. To do this, surveying and pre-test of equipment were conducted. In addition, for sensor modeling of the GeoEye-1 satellite image, RPC-bias correction was done, and it showed that at least two control points are required. In generating the map, a 1/2,500 scale was deemed suitable in consideration of resolution of the image and the fact that supplementary topographic surveying would be impossible. In order to provide detailed information on the topography around the Jangbogo station, the digital elevation model based on image matching was created, and compared with GPS-RTK data, accuracy of vertical location about 0.6m was exhibited.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.7
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• pp.1137-1148
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• 2008

The purposes of this study were to investigate the differences in clothing consumption behaviors among female consumer groups in their twenties and to understand the type of consumer group pursuing fast fashion. Questionnaire survey was conducted to 230 female consumers residing in Seoul and Kyung Gi area from June 18 to 29 in 2007, and 178 were used for data analysis. Data analysis were conducted with SPSS 12 program on the reliability test, factor analysis, cluster analysis, correlation analysis, ANOVA, Duncan's multiple range test. Factors analyses were employed for the attitude toward fashion and shopping, and shopping motives. Four factors were formulated for the attitude toward fashion: interest in fashion, fashion-orientation, fashion leadership and fashion conformity. Six factors for the attitude toward shopping were found: information searching, shopping enjoyment, store patronage, impulse buying, brand-orientation and convenience. Buying motives for fashion goods were classified into 3 factors: for matching & occasion, to-be-in-fashion and for necessity. Four clusters were identified based on the attitude toward fashion: the fashion-interested, the fashion-indifferent, fashion leaders and the individuality-oriented. Among the groups, significant differences were found in information searching, shopping enjoyment and store patronage. Fashion leaders tended to spend more for expensive and up-to-dated fashion items, and for higher quantity than other groups. Consequently fashion leaders showed attractive customer characteristics for the fast fashion companies.

• Journal of Information Technology Applications and Management
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• v.26 no.3
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• pp.121-134
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• 2019

The Fourth Industrial Revolution has differentiated technologies such as artificial intelligence, IoT(Internet of things), big data, and mobile. As the civilization develops more and more, humanity enjoy the cultural activities more than economic activity for the food and shelter. The platform structure based on the advanced information technology of the present will expand the cultural contents area in a variety of ways. Cultural contents respond sensitively to changes in consumer and will be useful experiences of human activities. Therefore, it should be noted again that the contents industry should not be limited to the discussion of the application of the fourth technology, but should be produced with emphasis on useful experiences of human being. In other words, the discussion of human activities around cultural contents should be focused on how to apply beyond the use of fourth industrial technology. Therefore, it is necessary to analyze the basis of the successful storytelling of the planning stage to connect the fourth industrial technology and human useful experience as a method for developing cultural contents, and to build and propose a model as a strategic method. This study analyzes domestic and foreign cases made by using big data among the visual contents which show continuous increase of consumption among culture industry field, and draws success factors and limit points. Next, we extract what is the successful matching factor that influenced consumer 's consciousness, and find out that the structure of culture prototype has been applied in the long history of mankind, and presents it as a storytelling model. Through the above research, this study aims to present a new interpretation and creative activity of cultural contents by presenting a storytelling model as a methodology for connecting creative knowledge, away from the general interpretation of social phenomenon applied with big data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2730-2736
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• 2010

Recently, various networks have been introduced in the car of the internal and external sides. These have been integrated by one HMI(Human Machine Interface) to control devices of each network and provide information service. The existing vehicle navigation system, providing GPS based vehicle positioning service, has been included to these integrated networks as a default option. The GPS has been used to the most universal device to provide position information by using satellites' signal. But It is impossible to provide the position information when the GPS can't receive the satellites' signal in the area of tunnel, urban canyon, or forest canopy. Thus, this paper propose and implement the method of measuring vehicle position by using the sensing data of internal CAN network and external Wi-Fi network of the integrated car navigation circumstances when the GPS doesn't work normally. The results obtained by implementation shows the proposed method works well by map matching.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4B
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• pp.245-257
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• 2012

As one of the most challenging tasks in designing the Internet routers, packet classification is required to achieve the wire-speed processing for every incoming packet. Packet classification algorithm which applies binary search on trie levels to the area-based quad-trie is an efficient algorithm. However, it has a problem of unnecessary access to a hash table, even when there is no node in the corresponding level of the trie. In order to avoid the unnecessary off-chip memory access, we proposed an algorithm using Bloom filters along with the binary search on levels to multiple disjoint tries. For ACL, FW, IPC sets with about 1000, 5000, and 10000 rules, performance evaluation result shows that the search performance is improved by 21 to 33 percent by adding Bloom filters.

• Korean Journal of Agricultural Science
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• v.47 no.2
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• pp.315-326
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• 2020

In this study, a real-time crop recognition system was developed for an unmanned farm machine for upland farming. The crop recognition system was developed based on a stereo camera, and an image processing framework was proposed that consists of disparity matching, localization of crop area, and estimation of crop height with coordinate transformations. The performance was evaluated by attaching the crop recognition system to a tractor for five representative crops (cabbage, potato, sesame, radish, and soybean). The test condition was set at 3 levels of distances to the crop (100, 150, and 200 cm) and 5 levels of camera height (42, 44, 46, 48, and 50 cm). The mean relative error (MRE) was used to compare the height between the measured and estimated results. As a result, the MRE of Chinese cabbage was the lowest at 1.70%, and the MRE of soybean was the highest at 4.97%. It is considered that the MRE of the crop which has more similar distribution lower. the results showed that all crop height was estimated with less than 5% MRE. The developed crop recognition system can be applied to various agricultural machinery which enhances the accuracy of crop detection and its performance in various illumination conditions.

• Journal of Biosystems Engineering
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• v.27 no.2
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• pp.151-160
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• 2002

Cow image processing technique would be useful not only for recognizing an individual but also for establishing the image database and analyzing the shape of cows. A cow (Holstein) has usually the unique speckle pattern. In this study, the individual recognition of cow was carried out using the speckle pattern and the content-based image retrieval technique. Sixty cow images of 16 heads were captured under outdoor illumination, which were complicated images due to shadow, obstacles and walking posture of cow. Sixteen images were selected as the reference image for each cow and 44 query images were used for evaluating the efficiency of individual recognition by matching to each reference image. Run-lengths and positions of runs across speckle area were calculated from 40 horizontal line profiles for ROI (region of interest) in a cow body image after 3 passes of 5$\times$5 median filtering. A similarity measure for recognizing cow individuals was calculated using Euclidean distance of normalized G-frame histogram (GH). normalized speckle run-length (BRL), normalized x and y positions (BRX, BRY) of speckle runs. This study evaluated the efficiency of individual recognition of cow using Recall(Success rate) and AVRR(Average rank of relevant images). Success rate of individual recognition was 100% when GH, BRL, BRX and BRY were used as image query indices. It was concluded that the histogram as global property and the information of speckle runs as local properties were good image features for individual recognition and the developed system of individual recognition was reliable.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.3
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• pp.621-627
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• 2008

This paper presents a compact and miniaturized power detector utilizing low temperature co-fired ceramics(LTCC) technology for the application in wireless handset system to monitor the transmitting power at the frequency of 824-849MHz. The proposed power detector is composed of detector diode, lumped components for matching network, and LTCC stripline coupler based on LTCC substrate technology. A 20dB LTCC stripline direction coupler is designed and implemented with many bending section in order to reduce the practically occupied area for miniaturization. A zero bias schottky diode is adopted for detector design because of its high speed operation with minimized loss. The measured performances of fabricated detector agree well with the predicted results with a good linearity within the effective input RF power range.

• Journal of Ship and Ocean Technology
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• v.10 no.4
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• pp.12-23
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• 2006

In this paper, a numerical study is carried out to investigate the turbulent flow around a twin-skeg container ship model with rudders including propeller effects. A commercial CFD code, FLUENT is used with body forces distributed on the propeller disk to simulate the ship stem and wake flows with the propeller in operation. A multi-block, matching, structured grid system has been generated for the container ship hull with twin-skegs in consideration of rudders and body-force propeller disks. The RANS equations for incompressible fluid flows are solved numerically by using a finite volume method. For the turbulence closure, a Reynolds stress model is used in conjunction with a wall function. Computations are carried out for the bare hull as well as the hull with appendages of a twin-skeg container ship model. For the bare hull, the computational results are compared with experimental data and show generally a good agreement. For the hull with appendages, the changes of the stem flow by the rudders and the propellers have been analyzed based on the computed result since there is no experimental data available for comparison. It is found the flow incoming to the rudders has an angle of attack due to the influence of the skegs and thereby the hull surface pressure and the limiting streamlines are changed slightly by the rudders. The axial velocity of the propeller disk is found to be accelerated overall by about 35% due to the propeller operation with the rudders. The area and the magnitude of low pressure on the hull surface enlarge with the flow acceleration caused by the propeller. The propellers are found to have an effect on up to the position where the skeg begins. The propeller slipstream is disturbed strongly by the rudders and the flow is accelerated further and the transverse velocity vectors are weakened due to the flow rectifying effect of the rudder.