• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2946-2952
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• 2014

Among the Example based Super Resolution(SR) techniques, Neighbor embedding(NE) has been inspired by manifold learning method, particularly locally linear embedding. However, the poor generalization of NE decreases the performance of such algorithm. The sizes of local training sets are always too small to improve the performance of NE. We propose the Learning Sparse-Neighbor Image Representation baesd on SVR having an excellent generalization ability to solve this problem. Given a low resolution image, we first use bicubic interpolation to synthesize its high resolution version. We extract the patches from this synthesized image and determine whether each patch corresponds to regions with high or low spatial frequencies. After the weight of each patch is obtained by our method, we used to learn separate SVR models. Finally, we update the pixel values using the previously learned SVRs. Through experimental results, we quantitatively and qualitatively confirm the improved results of the proposed algorithm when comparing with conventional interpolation methods and NE.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.6
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• pp.627-637
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• 2009

Composite materials have been employed in the various engineering applications due to high mechanical performances including high strength-weight ratio and high degree of free formability. Due to complex manufacturing process, however, it can have intrinsic randomness in the material constants which affect the deterministic behavior of the composite structures. In this study, we suggest a formulation for stochastic finite element analysis considering the spatial randomness of Poisson's ratio. Considering the reciprocal relation between elastic moduli and Poisson's ratios in the two mutually orthogonal axes, one of two values of Poisson's ratio can be expressed in terms of the other. Using this, the relation between stress resultants and strains is derived in the ascending order of power of the stochastic field function, which can be directly used in the formulation to obtain the coefficient of variation of responses. The adequacy of the proposed scheme is demonstrated by comparison with the results of Monte Carlo analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3A
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• pp.249-253
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• 2006

We propose a new beamforming algorithm, which is based on simplex downhill optimization method in the presence of pilot channels in cdma2000 reverse-link, for the rake structure antenna array in DS/CDMA communication system. Our approach uses the desired signal(pilot) covariance matrix and the interference covariance matrix. The beamforming weights are made according to maximum SINR criteria using simplex downhill optimization procedure. Our proposed scheme provides lower computational load, better convergence speed, better performance than existingadaptive beamforming algorithm. The simplex downhill method is well suited to finding the optimal or sub-optimal weight vector, since they require only the value of the deterministic function to be optimized. The rake beamformer performances are also evaluated under several set of practical parameter values with regard to spatial channel model. We also compare the performance between conventional rake receiver and the proposed one under same receiving power.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.95-108
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• 2010

In this paper, we present a hybrid neural network model for dynamic hand gesture recognition. The model consists of two modules, feature extraction module and pattern classification module. We first propose a modified CNN(convolutional Neural Network) a pattern recognition model for the feature extraction module. Then we introduce a weighted fuzzy min-max(WFMM) neural network for the pattern classification module. The data representation proposed in this research is a spatiotemporal template which is based on the motion information of the target object. To minimize the influence caused by the spatial and temporal variation of the feature points, we extend the receptive field of the CNN model to a three-dimensional structure. We discuss the learning capability of the WFMM neural networks in which the weight concept is added to represent the frequency factor in training pattern set. The model can overcome the performance degradation which may be caused by the hyperbox contraction process of conventional FMM neural networks. From the experimental results of human action recognition and dynamic hand gesture recognition for remote-control electric home appliances, the validity of the proposed models is discussed.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.1 s.19
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• pp.59-66
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• 2002

The rapid change of industrial structure causes to increase distribution cost and requires necessity of physical distribution system urgently. Traffic situation is getting extremely worse and traffic jam has led to increasing expense of physical distribution delivery which dominates 20% of distribution cost. In this situation, the shortest and most suitable path search system is required by modern people who must waste a lot of time for moving with a car or on the street as well as many companies. for these reasons, we developed the shortest-path-searching system applying the dijkstra algorithm which is one of the effective shortest path algorithm to GIS, and it was constructed by considering realistic urban traffic and the pattern of street in a physical situation. Also, this system was developed to be updated weight data automatically, considering the dynamic change of traffic situation such as a traffic information service which will be served in real time. Finally, we designed this system to serve on web by using MapObjects IMS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2717-2723
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• 2015

Recently, digital image processing is being applied in various areas of broadcasting, communication, computer graphic and medical science. But, degradation of images occurs in the process of digital image acquisition, processing and transmission. Therefore, in order to remove the mixed noise, this paper suggested the image restoration algorithm to process salt and pepper noise with weighted filters according to 4 direction pixel changes after judging the noise and to process AWGN with weighted filters which have individually different characteristics. Regarding the processed results by applying Boat images which were corrupted by salt and pepper noise(P=40%), suggested algorithm showed the improvement by 1.33[dB], 1.41[dB], 0.51[dB] respectively compared with the existing CWMF, AWMF, MMF.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.46 no.2
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• pp.126-138
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• 2010

To investigate seasonal variation of fisheries resources composition and their correlationships with environmental factors in the coastal ecosystem of the middle Yellow Sea of Korea, shrimp beam trawl were carried out for the fisheries survey. Fisheries resources of 81 species, 57 families, and 6 taxa totally were collected by shrimp beam trawl in the middle coastal ecosystem of Yellow Sea of Korea. Species were included 6 species in Bivalvia, 6 in Cephalopoda, 22 in Crustacea, 2 in Echinodermata, 5 in Gastropoda, and 40 in Pisces. Diversity indices (Shannon index, H') showed seasonal variation with low value of 2.14 in winter, and high value of 2.67 in spring. Main dominant species were Oratosquilla oratoria, Octopus ocellatus, Acanthogobius lactipes, Cynoglossus joyneri, Rapana venosa venosa, Loligo beka, Chaeturichthys stigmatias, Raja kenojei, Microstomus achne and Paralichthys olivaceus, that were occupied over 58% of total individuals, and 55% of wet weight. Fisheries organism made four coordinative seasonal groups by the principal component analysis (PCA), showing stronger seasonal variation than spatial variation. PC from PCA showed statistically significant cross-correlationships with seawater temperature, $NH_4$-N, TP and chlorophyll a (P < 0.05).

• Economic and Environmental Geology
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• v.38 no.1
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• pp.33-43
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• 2005

The purpose of this study is to make and validate landslide susceptibility map using artificial neural network and GIS in Kangneung area. For this, topography, soil, forest, geology and land cover data sets were constructed as a spatial database in GIS. From the database, slope, aspect, curvature, water system, topographic type, soil texture, soil material, soil drainage, soil effective thickness, wood type, wood age, wood diameter, forest density, lithology, land cover, and lineament were used as the landslide occurrence factors. The weight of the each factor was calculated, and applied to make landslide susceptibility maps using artificial neural network. Then the maps were validated using rate curve method which can predict qualitatively the landslide occurrence. The landslide susceptibility map can be used to reduce associated hazards, and to plan land use and construction as basic data.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.99-109
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• 2001

In order to establish effective fishing ground environment equipment and artificial reef in coastal area, the methodology to select the most suitable area for artificial reef should be applied after analyzing the correlation between fishing ground environment and ocean environment. In this paper, thematic maps were prepared by using satellite remote sensing and GIS for the sea surface temperature, chlorophyll, transparency, the depth of sea water and the condition of submarine geologic which are considered as the most elements when selecting suitable area for artificial reef in Tong-Yong bay. Then, the most suitable area for artificial reef was selected by giving weight score depending on the suitable condition of this area and analyzing spatial data. The results showed it makes possible for this methodology, which selects the suitable area for artificial reef using satellite remote sensing and GIS, to manage the institution of artificial reef more entirely and efficiently through analyzing and visualizing.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.303-313
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• 2019

After a disaster happens in urban areas, many people need support for a quick evacuation. This work aims to develop a method for the calculation of the most feasible evacuation route inside buildings. In the methodology we simplify the geometry of the structural and non structural elements from the BIM (Building Information Modeling) to store them in a spatial database which follows standards to support vector data. Then, we apply the multicriteria analysis with the allocation of prioritization values and weight factors validated through the AHP (Analytic Hierarchy Process), in order to obtain the Importance Index S(n) of the elements. The criteria consider security conditions and distribution of the building's facilities. The S(n) is included as additional heuristic data for the calculation of the evacuation route through an algorithm developed as a variant of the $A^*$ pathfinding, The experimental results in the simulation of evacuation scenarios for vulnerable people in healthy physical conditions and for the elderly group, shown that the conditions about the wide of routes, restricted areas, vulnerable elements, floor roughness and location of facilities in the building applied in the multicriteria analysis has a high influence on the processing of the developed variant of $A^*$ algorithm. The criteria modify the evacuation route, because they considers as the most feasible route, the safest instead of the shortest, for the simulation of evacuation scenarios for people in healthy physical conditions. Likewise, they consider the route with the location of facilities for the movement of the elderly like the most feasible in the simulation of evacuation route for the transit of the elderly group. These results are important for the assessment of the decision makers to select between the shortest or safest route like the feasible for search and rescue activities.