• Journal of the Optical Society of Korea
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• v.19 no.6
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• pp.643-648
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• 2015

By comparing the results calculated by atan() and atan2() functions, the correctly estimated region of isoclinic phase map is determined using morphological techniques. The isoclinic phase map is automatically unwrapped in the true phase range -π/2 to π/2. Demonstrations of the method on a disc and a ring under diametral compression are performed. Test results compare well with the theoretical results. Furthermore, the influences of principal stress direction and the range of isoclinic phase upon stress separation are discussed.

• The Korean Journal of Ecology
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• v.21 no.6
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• pp.791-797
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• 1998

An attempt to clarify the landscape structure of urban areas was carried out on Mt. Hwangryung located in the center of Pusan, southern Korea. By means of aerial photographs and field survey, a vegetation map including land-use pattern was made. Landscape structure was described by analyzing the vegetation map. Landscape element types were classified into secondary forest, introduced plantation, and other elements including urbanized area. almus firma and Pinus thunbergii communities, introduced plantation elements, formed matrix and some secondary forest elements and the other artificial plantations of small scale tended to distribute as small patches in such matrix. The number of patches per unit area in secondary forest elements was more than that in introduced plantation element. The result on patech size was vice versa. As the results of landscape ecological analyses, it was estimated that differentiation of patches recognized in community level would be related to artificial interference and those in sub-communities levels to natural process such as progression of succession. On the other hand, restoration plans in viewpoints of restoration and landscape ecology were suggested to improve ecological quality of Mt. hwangryung.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.637-640
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• 2008

Flood control and river improvement works are carried out every year for the defense of the flood disaster, it is impossible to avoid the damage when there is a flood exceeding the capacity of hydraulic structures. Therefore, nonstructural counter plans such as the establishment of flood hazard maps, the flood warning systems are essential with structural counter plans. In this study, analysis of the internal inundation effect using rainfall runoff model such as PC-SWMM was applied to Woo Ee experimental stream basin. Also, the design frequency analysis for effects of the external inundation was accomplished by main parameter estimation for conclusive hydraulic routing using HEC-RAS model. Finally, inundated areas for flood hazard map were estimated at Woo Ee downstream basin according to flood frequency using HEC-GeoRAS model linked by Arc View GIS.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.290-296
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• 2022

Big Data is a data analysis technology empowered by late advances in innovations and engineering. In any case, big data involves a colossal responsibility of equipment and handling assets, making reception expenses of big data innovation restrictive to little and medium estimated organizations. Cloud computing offers the guarantee of big data execution to little and medium measured organizations. Big Data preparing is performed through a programming worldview known as MapReduce. Normally, execution of the MapReduce worldview requires organized joined stockpiling and equal preparing. The computing needs of MapReduce writing computer programs are frequently past what little and medium measured business can submit. Cloud computing is on-request network admittance to computing assets, given by an external element. Normal arrangement models for cloud computing incorporate platform as a service (PaaS), software as a service (SaaS), framework as a service (IaaS), and equipment as a service (HaaS).

• Journal of Soil and Groundwater Environment
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• v.23 no.1
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• pp.92-105
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• 2018

In this study, the projected land use area in 2030 for major crop production was estimated in Jeju Island using land cover map, and corresponding agricultural water demand for 40 sub-regions was quantitatively assessed using the future climate change scenario (RCP 4.5). Estimated basic unit of water demand in 2030 was the highest in the western region, and the lowest in the eastern region. Monthly maximum agricultural water demand analysis revealed that water demand in August of 2030 substantially increased, suggesting the climate of Jeju Island is changing to a subtropical climate in 2030. Agricultural water demand for sub-region in 2030 was calculated by multiplying the target area of the water supply excluding the area not in use in winter season by the basic unit of water demand, and the maximum and minimum values were estimated to be $306,626m^3/day$ at Seogwipo downtown region and $77,967m^3/day$ at Hallim region, respectively. Consequently, total agricultural water demand in Jeju Island in 2030 was estimated to be $1,848,010m^3/day$.

• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.332-336
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• 2008

The resource potentials biomass resources of South Korea are estimated as Preliminary stage using relevant National statistics. Biomass resources possibly be collected, used and converted to bioenergy in Korea are forest biomass, agricultural residue, livestock manure and municipal solid wastes. The potential biomass resources are classifying into total potential, available potential and technically feasible biomass resources, Total potential biomass resources in Korea are estimated to be around 140million tons of oil equivalent (toe). Available potentials are estimated to be around 11million annually. The technically feasible biomass resources with current technologies are estimated to be 2.3million toe annually. These estimated values are the minimum of all potentials since they are all estimated from explicit statistics. Although actually there exist huge amount of biomass on the land as well as in the sea, potential resources for bioenergy are believed to be limited. The potentials are to be inclosed with the improvement of bioenergy technologies.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.9
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• pp.95-103
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• 1998

This paper proposes an image segmentation algorithm based on fusion of range and intensity images. Based on Bayesian theory, a priori knowledge is encoded by the Markov random field (MRF). A maximum a posteriori (MAP) estimator is constructed using the features extracted from range and intensity images. Objects are approximated by local planar surfaces in range images, and the parametric space is constructed with the surface parameters estimated pixelwise. In intensity images the ${\alpha}$-trimmed variance constructs the intensity feature. An image is segmented by optimizing the MAP estimator that is constructed using a likelihood function based on edge information. Computer simulation results shw that the proposed fusion algorithm effectively segments the images independentl of shadow, noise, and light-blurring.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.5
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• pp.277-285
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• 2016

Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1159-1181
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• 2016

This study introduces an image-based 2D-to-3D conversion system that provides significant stereoscopic visual effects for humans. The linear and atmospheric perspective cues that compensate each other are employed to estimate depth information. Rather than retrieving a precise depth value for pixels from the depth cues, a direction angle of the image is estimated and then the depth gradient, in accordance with the direction angle, is integrated with superpixels to obtain the depth map. However, stereoscopic effects of synthesized views obtained from this depth map are limited and dissatisfy viewers. To obtain impressive visual effects, the viewer's main focus is considered, and thus salient object detection is performed to explore the significance region for visual attention. Then, the depth map is refined by locally modifying the depth values within the significance region. The refinement process not only maintains global depth consistency by correcting non-uniform depth values but also enhances the visual stereoscopic effect. Experimental results show that in subjective evaluation, the subjectively evaluated degree of satisfaction with the proposed method is approximately 7% greater than both existing commercial conversion software and state-of-the-art approach.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.327-330
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• 2016

Currently, the world's elderly population continues to grow at a dramatic rate. As the number of senior citizens increases, detection of someone falling has attracted increasing attention for visual surveillance systems. This paper presents a novel fall-detection algorithm using motion estimation and an integrated spatiotemporal energy map of the object region. The proposed method first extracts a human region using a background subtraction method. Next, we applied an optical flow algorithm to estimate motion vectors, and an energy map is generated by accumulating the detected human region for a certain period of time. We can then detect a fall using k-nearest neighbor (kNN) classification with the previously estimated motion information and energy map. The experimental results show that the proposed algorithm can effectively detect someone falling in any direction, including at an angle parallel to the camera's optical axis.