• ALGAE
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• v.30 no.2
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• pp.89-101
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• 2015

Ecklonia cava Kjellman is a common kelp found in shallow subtidal in warm-temperate waters in the northwest Pacific Ocean. This species has shown substantial morphological variation along with subsistence in different locations and local environments. We quantified the magnitude of morphological variation of E. cava from six populations along ~700 km of coastline from Jeju Island to Dokdo in Korea. In addition, we examined genetic distance among the populations using random amplified polymorphic DNA (RAPD) analysis. Most morphological characteristics investigated were significantly different among locations. Multivariate analyses indicated two phenetically distinct groups (nearshore, sheltered vs. offshore, exposed), indicating wave exposure with turbidity are presumably major factors for the separation. With RAPD data, results of Nei's diversity (H) and AMOVA showed considerable variations in within- and between-populations. Pairwise ${\Phi}_{ST}$ and $N_m$ values indicated moderate gene flow between the six locations. Results of Nei's analysis revealed three genetically distinct groups, not consistent with the morphological groupings, indicating that a time gap may exist between morphological and genetic variations. This study also suggests dispersal distance of this kelp may be longer than what is commonly thought and genetic similarity in the populations was largely reflected by the direction of ocean current rather than just geographical distance.

• Journal of Environmental Impact Assessment
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• v.19 no.6
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• pp.591-605
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• 2010

Cool roofs are currently being emerged as one of important mechanism to save energy in relation to the building. This paper reviews worldwide experiences (USA, Japan and EU etc) for the potential benefits cool roofs offer in relation to building energy saving for comparison purposes. It is confirmed that there is a significant potential to the energy saving by introducing the cool roof in a Korean climate because of similarity in terms of HDD (Heating Degree Day) and CDD (Cooling Degree Day) as those countries reviewed. Such a comparative study highlights that the type of measurements performed and the quantitative parameters reported from the countries should be standardized in Korean context in order to implement further comparable experiments for scientifically sound investigations. It is anticipated that this research output could be used as a valuable reference in implementing a Nation-wide cool roofing strategy in the central and local governments since a suitable technical, more objective direction has been proposed based on the measured, fully quantitative performance of the involved components of a cool roof system in the global context. From this critical review, a very important step has been made concerning the practicality of cool roof in Korean context. Ultimately, the suggestion in this paper will greatly contribute to opening new possibilities for introducing cool roof in this country, proposed as an initial aim of this paper.

• Journal of the Society of Disaster Information
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• v.8 no.3
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• pp.258-266
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• 2012

There are some problems for the designation criteria of metropolitan railroad project such as the similarity between urban railroad and metropolitan railroad, and the discriminative government subsidy. In this paper, the revised designation criteria is suggested. The ratio of commuter trips over all trips should be over 5% and the radius from the CBD of the central city be below 50km for the range of metropolitan railroad. The journey speed of metropolitan railroad should be over 60km/h. The revised criteria suggested in this paper can prevent the waste of central government subsidy and raise the responsibility of the local government.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.522-541
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• 2016

Network virtualization provides an effective way to overcome the Internet ossification problem. As one of the main challenges in network virtualization, virtual network embedding refers to mapping multiple virtual networks onto a shared substrate network. However, existing heuristic embedding algorithms evaluate the embedding potential of the nodes simply by the product of different resource attributes, which would result in an unbalanced embedding. Furthermore, ignoring the hops of substrate paths that the virtual links would be mapped onto may restrict the ability of the substrate network to accept additional virtual network requests, and lead to low utilization rate of resource. In this paper, we introduce and extend five node attributes that quantify the embedding potential of the nodes from both the local and global views, and adopt the technique for order preference by similarity ideal solution (TOPSIS) to rank the nodes, aiming at balancing different node attributes to increase the utilization rate of resource. Moreover, we propose a novel two-stage virtual network embedding algorithm, which maps the virtual nodes onto the substrate nodes according to the node ranks, and adopts a shortest path-based algorithm to map the virtual links. Simulation results show that the new algorithm significantly increases the long-term average revenue, the long-term revenue to cost ratio and the acceptance ratio.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.111-119
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• 2006

Video viewers can not understand enough entire video contents because most video is long length data of large capacity. This paper propose efficient scene change detection and video abstracting using new shot clustering to solve this problem. Scene change detection is extracted by method that was merged color histogram with $\chi2$ histogram. Clustering is performed by similarity measure using difference of local histogram and new shot merge algorithm. Furthermore, experimental result is represented by using Real TV broadcast program.

• Journal of Ubiquitous Convergence Technology
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• v.2 no.1
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• pp.18-26
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• 2008

The invariance relation existing in the non-negative matrix factorization (NMF) is used for constructing robust image hashes in this work. The image is first re-scaled to a fixed size. Low-pass filtering is performed on the luminance component of the re-sized image to produce a normalized matrix. Entries in the normalized matrix are pseudo-randomly re-arranged under the control of a secret key to generate a secondary image. Non-negative matrix factorization is then performed on the secondary image. As the relation between most pairs of adjacent entries in the NMF's coefficient matrix is basically invariant to ordinary image processing, a coarse quantization scheme is devised to compress the extracted features contained in the coefficient matrix. The obtained binary elements are used to form the image hash after being scrambled based on another key. Similarity between hashes is measured by the Hamming distance. Experimental results show that the proposed scheme is robust against perceptually acceptable modifications to the image such as Gaussian filtering, moderate noise contamination, JPEG compression, re-scaling, and watermark embedding. Hashes of different images have very low collision probability. Tampering to local image areas can be detected by comparing the Hamming distance with a predetermined threshold, indicating the usefulness of the technique in digital forensics.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.3
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• pp.1061-1073
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• 1996

Vortex tube is a simple device which splits a compressed gas stream into a cold stream and a hot stream without any chemical reactions. The phenomena of energy separation taking place in a vortex tube has been investigated experimentally. Recently, vortex tube is widely used to local cooler of industrial equipments and air conditioner of special purpose. In this study, experimental study on vortex tube efficiency was performed with various cold end orifices and nozzles type. The experimental results indicate that there is an optimum diameter of cold end orifice and nozzle type for the best cooling performance. The variation of the maximum wall temperature along the vortex tube surface provides useful information about the location of the stagnation point of the flow field at the axis of the vortex tube. The similarity relation for the prediction of the temperature of the cold exit air was obtained.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.663-676
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• 2020

Plant leaf classification is a significant application of image processing techniques in modern agriculture. In this paper, a multi-granular angle description method is proposed for plant leaf classification and retrieval. The proposed method can describe leaf information from coarse to fine using multi-granular angle features. In the proposed method, each leaf contour is partitioned first with equal arc length under different granularities. And then three kinds of angle features are derived under each granular partition of leaf contour: angle value, angle histogram, and angular ternary pattern. These multi-granular angle features can capture both local and globe information of the leaf contour, and make a comprehensive description. In leaf matching stage, the simple city block metric is used to compute the dissimilarity of each pair of leaf under different granularities. And the matching scores at different granularities are fused based on quotient space theory to obtain the final leaf similarity measurement. Plant leaf classification and retrieval experiments are conducted on two challenging leaf image databases: Swedish leaf database and Flavia leaf database. The experimental results and the comparison with state-of-the-art methods indicate that proposed method has promising classification and retrieval performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.135-142
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• 2012

In this paper, we proposed a new architecture called radial basis function-based polynomial neural networks classifier that consists of heterogeneous neural networks such as radial basis function neural networks and polynomial neural networks. The underlying architecture of the proposed model equals to polynomial neural networks(PNNs) while polynomial neurons in PNNs are composed of Fuzzy-c means-based radial basis function neural networks(FCM-based RBFNNs) instead of the conventional polynomial function. We consider PNNs to find the optimal local models and use RBFNNs to cover the high dimensionality problems. Also, in the hidden layer of RBFNNs, FCM algorithm is used to produce some clusters based on the similarity of given dataset. The proposed model depends on some parameters such as the number of input variables in PNNs, the number of clusters and fuzzification coefficient in FCM and polynomial type in RBFNNs. A multiobjective particle swarm optimization using crowding distance (MoPSO-CD) is exploited in order to carry out both structural and parametric optimization of the proposed networks. MoPSO is introduced for not only the performance of model but also complexity and interpretability. The usefulness of the proposed model as a classifier is evaluated with the aid of some benchmark datasets such as iris and liver.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.213-231
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• 2014

Existing image search systems allow users to search images by keywords, or by example images through content-based image retrieval (CBIR). On the other hand, users might learn more relevant textual information about an image from its text captions or surrounding contexts within documents or Web pages. Without such contexts, it's difficult to extract semantic description directly from the image content. In this paper, we propose an annotation watermarking system for users to embed text descriptions, and retrieve more relevant textual information from similar images. First, tags associated with an image are converted by two-dimensional code and embedded into the image by discrete wavelet transform (DWT). Next, for images without annotations, similar images can be obtained by CBIR techniques and embedded annotations can be extracted. Specifically, we use global features such as color ratios and dominant sub-image colors for preliminary filtering. Then, local features such as Scale-Invariant Feature Transform (SIFT) descriptors are extracted for similarity matching. This design can achieve good effectiveness with reasonable processing time in practical systems. Our experimental results showed good accuracy in retrieving similar images and extracting relevant tags from similar images.