• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.107-118
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• 2007

This study examined the standard how to deal with infringement of copyright legally, by looking at several examples of the infringement of copyright in local video works. When we look at precedents relating to copyrighted motion pictures, there are many times when two works seem quite similar but don't get conformed to the infringement of copyright by deliberating the similarities feebly. Although the Idea seems same, the creative expression is admitted and the substantial similarity is denied. For example, in the case of the soap opera, 'Kareiski', the court presented a standard of judgment by organizing the facts, based on the subjective element, dependence on proof and the objective element, the substantial similarity In the case of 'Fox and the Cotton Candy', the dependence on proof and the substantial similarity were examined as usual but when examining the substantial similarity, it was examined in more specific details. This case is a good reference for solving such a case in the future.

• Interdisciplinary Bio Central
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• v.3 no.4
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• pp.14.1-14.9
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• 2011

Protein homology detection is an important issue in comparative genomics. Because of the exponential growth of sequence databases, fast and efficient homology detection tools are urgently needed. Currently, for homology detection, sequence comparison methods using local alignment such as BLAST are generally used as they give a reasonable measure for sequence similarity. However, these methods have drawbacks in offering overall sequence similarity, especially in dealing with eukaryotic genomes that often contain many insertions and duplications on sequences. Also these methods do not provide the explicit models for speciation, thus it is difficult to interpret their similarity measure into homology detection. Here, we present a novel method based on Word Conservation Score (WCS) to address the current limitations of homology detection. Instead of counting each amino acid, we adopted the concept of 'Word' to compare sequences. WCS measures overall sequence similarity by comparing word contents, which is much faster than BLAST comparisons. Furthermore, evolutionary distance between homologous sequences could be measured by WCS. Therefore, we expect that sequence comparison with WCS is useful for the multiple-species-comparisons of large genomes. In the performance comparisons on protein structural classifications, our method showed a considerable improvement over BLAST. Our method found bigger micro-syntenic blocks which consist of orthologs with conserved gene order. By testing on various datasets, we showed that WCS gives faster and better overall similarity measure compared to BLAST.

• Journal of the Earthquake Engineering Society of Korea
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• v.24 no.5
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• pp.219-232
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• 2020

The slip-weakening model developed by Ohnaka and Yamashita is extended over the breakdown zone by equating the scaling relationships for the breakdown zone and the whole rupture area. For the extension, the study uses the relationship between rupture velocity and radiation efficiency, which was derived in the theory of linear elastic fracture mechanics, and the definition of f_max given in the specific barrier model proposed by Papageorgiou and Aki. The results clearly show that the extended scaling relationship is governed by the ratio of rupture velocity to S wave velocity, and the velocity ratio can be determined by the ratio of characteristic frequencies of a Fourier amplitude spectrum, which are corner frequency, f_c, and source-controlled cut-off frequency, f_max, or vice versa. The derived relationship is tested by using the characteristic frequencies extracted from previous studies of more than 130 shallow crustal events (focal depth less than 25 km, M_W 3.0~7.5) that occurred in Japan. Under the assumption of a dynamic similarity, the rupture velocity estimated from f_max/f_c and the modified integral timescale give quite similar scale-dependence of the rupture area to that given by Kanamori and Anderson. Also, the results for large earthquakes show good agreement to the values from a kinematic inversion in previous studies. The test results also indicate the unavailability of the spectral self-similarity proposed by Aki because of the scale-dependent rupture velocity and the rupture velocity-dependent f_max/f_c; however, the results do support the local similarity asserted by Ohnaka. It is also remarkable that the relationship between the rupture velocity and f_max/f_c is quite similar to Kolmogorov's hypothesis on a similarity in the theory of isotropic turbulence.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1418-1429
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• 2014

In this paper we suggest a new two-wheelers detection algorithm using local cell features. The first, we propose new feature vector matrix extraction algorithm using the correlation two cells based on local cell histogram and shifting from the result of histogram of oriented gradients(HOG). The second, we applied new weighting values which are calculated by the modified histogram intersection showing the similarity of two cells. This paper applied the Adaboost algorithm to make a strong classification from weak classification. In this experiment, we can get the result that the detection rate of the proposed method is higher than that of the traditional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3950-3964
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• 2017

With the increasing popularity of 3D technology such as 3D printing, 3D modeling, etc., there is a growing need to search for similar models on the internet. Matching non-rigid shapes has become an active research field in computer graphics. In this paper, we present an efficient and effective non-rigid model retrieval method based on topological structure and local volume. The integral geodesic distances are first calculated for each vertex on a mesh to construct the topological structure. Next, each node on the topological structure is assigned a local volume that is calculated using the shape diameter function (SDF). Finally, we utilize the Hungarian algorithm to measure similarity between two non-rigid models. Experimental results on the latest benchmark (SHREC' 15 Non-rigid 3D Shape Retrieval) demonstrate that our method works well compared to the state-of-the-art.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.914-927
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• 2017

Weighted network link prediction is a challenge issue in complex network analysis. Unsupervised methods based on local structure are widely used to handle the predictive task. However, the results are still far from satisfied as major literatures neglect two important points: common neighbors produce different influence on potential links; weighted values associated with links in local structure are also different. In this paper, we adapt an effective link prediction model-local naive Bayes model into a weighted scenario to address this issue. Correspondingly, we propose a weighted local naive Bayes (WLNB) probabilistic link prediction framework. The main contribution here is that a weighted cluster coefficient has been incorporated, allowing our model to inference the weighted contribution in the predicting stage. In addition, WLNB can extensively be applied to several classic similarity metrics. We evaluate WLNB on different kinds of real-world weighted datasets. Experimental results show that our proposed approach performs better (by AUC and Prec) than several alternative methods for link prediction in weighted complex networks.

• The Journal of the Convergence on Culture Technology
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• v.5 no.3
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• pp.339-344
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• 2019

Global sequence alignment in search of similarity or homology favors larger size of the sequence because it keeps looking for more similar section between two sequences in the hope that it adds up scores for matched part in the rest of the sequence. If a substantial size of mismatched section exists in the middle of the sequence, it greatly reduces the total alignment score. In this case a whole sequence would be better to be divided into multiple sections. Overall alignment score over the multiple sections of the sequence would increase as compared to global alignment. This method is called multiple local alignment. In this paper, we implement a multiple local alignment algorithm, an extension of Smith-Waterman algorithm and show the experimental results for the algorithm that is able to search for sub-optimal sequence.

• Journal of Internet Computing and Services
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• v.7 no.4
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• pp.33-43
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• 2006

This paper proposes a method to extract coronary arteries effectively in the angiography, In general. DSA(Digital Subtraction Angiography) is a well-established technique for the visualization of coronary arteries, DSA involves the subtraction of a mask image, an image of a heart before the injection of contrast medium, from a live image, However, this technique is sensitive to the movement of background and can cause wrong detection due to the variance of background intensity between two images. Therefore, this paper solves the structural problem resulted from background movement by selecting an image which has the least difference of movement through the similarity analysis of background texture, and it extracts only the blood vessels effectively through local intensity correction of the selected images, Experimental results show that the proposed method has the lower false-detection rate and higher accuracy rate than existing methods.

• Journal of Crop Science and Biotechnology
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• v.10 no.1
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• pp.27-32
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• 2007

RAPD, Inter-SSR, and AFLP markers were used to assess the genetic diversity of lettuce cultivars and the phylogenetic relationships in Lactuca spp. A total of 216 polymorphic bands from seven RAPD primers, four Inter-SSR primers, and five AFLP primer combinations were used to elucidate the genetic similarity among lettuce cultivars. Forty-four lettuce accessions were subdivided into discrete branches according to plant type: crisphead, butterhead, and stem type, with some exceptions. The leafy- and cos-type accessions were intermingled in other groups with no discrete branch indicating that these are more diverse than others. Three accessions, including the Korean cultivar 'Cheongchima', the Korean local landrace 'Jinjam', and the German cultivar 'Lolla Rossa' were classified as the most diverse accessions. Twenty bands were unique in specific cultivars. Among these, three were specific in a plant type; one in Korean leafy type, one in crisphead type, and one in cos type lettuce. In the phylogenetic analysis among Lactuca species, L. saligna, L. serriola, and L. georgica clustered in a sister branch of the L. sativa complex. Two L. virosa accessions show the highest intra-specific relationships. L. perennis outlied from all the other Lactuca species at a genetic similarity of 0.53 and clustered with two Cichorium species, C. intybus and C. endivia, with genetic similarity of 0.67. The phylogenetic tree was supported by data from polymorphism of chloroplast genome which was revealed by PCR-RFLP.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1223-1237
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• 2024

Autonomous vehicles use onboard sensors to sense the surrounding environment. In complex autonomous driving scenarios, the detection and recognition capabilities are constrained, which may result in serious accidents. An efficient way to enhance the detection and recognition capabilities is establishing collaborations with the neighbor vehicles. However, the collaborations introduce additional challenges in terms of the data heterogeneity, communication cost, and data privacy. In this paper, a novel personalized federated learning framework is proposed for addressing the challenges and enabling efficient collaborations in autonomous driving environment. For obtaining a global model, vehicles perform local training and transmit logits to a central unit instead of the entire model, and thus the communication cost is minimized, and the data privacy is protected. Then, the inference similarity is derived for capturing the characteristics of data heterogeneity. The vehicles are divided into clusters based on the inference similarity and a weighted aggregation is performed within a cluster. Finally, the vehicles download the corresponding aggregated global model and train a personalized model which is personalized for the cluster that has similar data distribution, so that accuracy is not affected by heterogeneous data. Experimental results demonstrate significant advantages of our proposed method in improving the efficiency of collaborative perception and reducing communication cost.