• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.530-536
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• 2008

Localization is one of the fundamental problems in wireless sensor networks (WSNs) that forms the basis for many location-aware applications. Localization in WSNs is to determine the position of node based on the known positions of several nodes. Most of previous localization method use triangulation or multilateration based on the angle of arrival (AOA) or distance measurements. In this paper, we propose an enhanced centroid localization method based on edge weights of adjacent nodes using fuzzy modeling and genetic algorithm when node connectivities are known. The simulation results shows that our proposed centroid method is more accurate than the simple centroid method using connectivity only.

• Journal of KIISE
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• v.42 no.5
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• pp.642-651
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• 2015

A vanishing point is a point where parallel lines converge, and they become evident when a camera's lenses are used to project 3D space onto a 2D image plane. Vanishing point detection is the use of the information contained within an image to detect the vanishing point, and can be utilized to infer the relative distance between certain points in the image or for understanding the geometry of a 3D scene. Since parallel lines generally exist for the artificial structures within images, line-detection-based vanishing point-detection techniques aim to find the point where the parallel lines of artificial structures converge. To detect parallel lines in an image, we detect edge pixels through edge detection and then find the lines by using the Hough transform. However, the various textures and noise in an image can hamper the line-detection process so that not all of the lines converging toward the vanishing point are obvious. To overcome this difficulty, it is necessary to assign a different weight to each line according to the degree of possibility that the line passes through the vanishing point. While previous research studies assigned equal weight or adopted a simple weighting calculation, in this paper, we are proposing a new method of assigning weights to lines after noticing that the lines that pass through vanishing points typically belong to artificial structures. Experimental results show that our proposed method reduces the vanishing point-estimation error rate by 65% when compared to existing methods.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.9-15
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• 2021

With the recent development of 5G and artificial intelligence technologies, it is interested in AIOT technology to collect, process, and analyze information in cloud edge environments. AIIoT technology is being applied to various smart environments, but research is needed to perform fast response processing through accurate analysis of collected information. In this paper, we propose a technique to minimize bandwidth and processing time by blocking the connection processing between AIOT information through fast processing and accurate analysis/forecasting of information collected in the smart environment. The proposed technique generates seeds for data indexes on AIOT devices by multipointing information collected by blockchain, and blocks them along with collection information to deliver them to the data center. At this time, we deploy Deep Neural Network (DNN) models between cloud and AIOT devices to reduce network overhead. Furthermore, server/data centers have improved the accuracy of inaccurate AIIoT information through the analysis and predicted results delivered to minimize latency. Furthermore, the proposed technique minimizes data latency by allowing it to be partitioned into a layered multilayer network because it groups it into blockchain by applying weights to AIOT information.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.3
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• pp.343-357
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• 2012

The Seoul metropolitan subway system can be represented by a graph which consists of nodes and edges. In this paper, we study classification of subway stations and trip behaviour of subway passengers through partitioning the graph of the subway system into roughly equal groups. A weight of each edge of the graph is set to the number of passengers who pass the edge, where the number of passengers is extracted from the transportation card transaction database. Since the graph partitioning problem is NP-complete, we propose a heuristic algorithm to partition the subway graph. The heuristic algorithm uses one of two alternative objective functions, one of which is to minimize the sum of weights of edges connecting nodes in different groups and the other is to maximize the ratio of passengers who get on the subway train at one subway station and get off at another subway station in the same group to the total subway passengers. In the experimental results, we illustrate the subway stations and edges in each group by color on a map and analyze the trip behaviour of subway passengers by the group origin-destination matrix.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.465-473
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• 2002

Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.127-135
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• 2013

In order to acquire images in low-light environments, it is usually necessary to adopt long exposure times or resort to flash lights. However, flashes often induce color distortion, cause the red-eye effect and can be disturbing to subjects. On the other hand, long-exposure shots are susceptible to subject-motion, as well as motion-blur due to camera shake when performed hand-held. A recently introduced technique to overcome the limitations of traditional low-light photography is that of multi-spectral flash. Multi-spectral flash images are a combination of UV/IR and visible spectrum information. The general idea is that of retrieving details from the UV/IR spectrum and color from the visible spectrum. However, multi-spectral flash images themselves are subject to color distortion and noise. This works presents a method to compute multi-spectral flash images so that noise can be reduced and color accuracy improved. The proposed approach is a previously seen optimization method, improved by the introduction of a weight map used to discriminate uniform regions from detail regions. The weight map is generated by applying canny edge operator and it is applied to the optimization process for discriminating the weights in uniform region and edge. Accordingly, the weight of color information is increased in the uniform region and the detail region of weight is decreased in detail region. Therefore, the proposed method can be enhancing color reproduction and removing artifacts. The performance of the proposed method has been objectively evaluated using long-exposure shots as reference.

• Journal of the Korea Computer Graphics Society
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• v.14 no.3
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• pp.1-9
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• 2008

This paper presents a novel optimization-based saliency-preserving method for converting color images to grayscale in a manner consistent with conventional approaches of black-and-white photographers. In black-and-white photography, a colored filter called a contrast filter has been commonly employed on a camera to lighten or darken selected colors. In addition, local exposure controls such as dodging and burning techniques are typically employed in the darkroom process to change the exposure of local areas within the print without affecting the overall exposure. Our method seeks a digital version of a conventional contrast filter to preserve visually-important image features. Furthermore, conventional burning and dodging techniques are addressed, together with image similarity weights, to give edge-aware local exposure control over the image space. Our method can be efficiently optimized on GPU. According to the experiments, CUDA implementation enables 1 megapixel color images to be converted to grayscale at interactive frames rates.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.4
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• pp.721-726
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• 2012

In this paper, we proposed an efficient algorithm based on SPFA(shortest path faster algorithm), which is an improved the Bellman-Ford algorithm. The Bellman-Ford algorithm can be used on graphs with negative edge weights unlike Dijkstra's algorithm. And SPFA algorithm used a queue to store the nodes, to avoid redundancy, though the Bellman-Ford algorithm takes a long time to update the nodes table. In this improved algorithm, an adjacency list is also used to store each vertex of the graph, applying dynamic optimal approach. And a queue is used to store the data. The improved algorithm can find the optimal path by continuous relaxation operation to the new node. Simulations to compare the efficiencies for Dijkstra's algorithm, SPFA algorithm and improved Bellman-Ford were taken. The result shows that Dijkstra's algorithm, SPFA algorithm have almost same efficiency on the random graphs, the improved algorithm, although the improved algorithm is not desirable, on grid maps the proposed algorithm is very efficient. The proposed algorithm has reduced two-third times processing time than SPFA algorithm.

• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.902-915
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• 2011

Recently in the area-based stereo matching field, Adaptive Support-Weight (ASW) method that weights matching cost adaptively according to the luminance intensity and the geometric difference shows promising matching performance. However, ASW requires more computational cost than other matching algorithms do and its real-time implementation becomes impractical. By applying Integral Histogram technique after approximating to the Bilateral filter equation, the computational time of ASW can be restricted in constant time regardless of the support window size. However, Integral Histogram technique causes loss of the matching accuracy during approximation process of the original ASW equation. In this paper, we propose a novel algorithm that maintains the ASW algorithm's matching accuracy while reducing the computational costs. In the proposed algorithm, we propose Sub-Block method that groups the pixels within the support area. We also propose the method adjusting the disparity search range depending on edge information. The proposed technique reduces the calculation time efficiently while improving the matching accuracy.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.28 no.1
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• pp.35-48
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• 1995

To develop the optimal design method for the longline type scallop culturing facilities in the open sea numerical calculations and hydraulic model experiments are carried out for the stability and function optimization. Using the results for the motion and tension of the facilities, stable design concepts and effects of motion control system by vertical anchor and resistance discs art discussed. The results of this study that can be applied to the design are as follows: 1) Total external forces by design wave $(H_{1/3}\;=\;6,7\;m,\;T_{1/3}\;=\;12sec)$ at the coastal waters of Jumunjin for unit facility (one main line) are estimated to 5-20 tons, and required anchor weights are 10-40 tons in the case of 2-point mooring system. Though the present facilities are stable to steady currents, but is unstable to the extreme wave condition of return period of 10 years. 2) The dimensions and depth of array systems must be designed considering the ecological environments as well as the physical characteristics including the mooring and holding forces that are proportional to the length and relative depth of main line to wave length, and the number of buoys and nets. 3) Oscillation of the facility is influenced by water particle motion and the weight of hanging net, and is excited at both edge, especially at the lee side. To reduce the motion of the nets, the vertical anchoring system and the resistence disc method are recommended by the experimental results, 4) The damage of rope near the anchor by abrasion should be prevented using the ring-type connection parts or anchor chains.