• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1708-1727
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• 2021

In the advent of the twenty-first century, human beings began to closely interact with technology. Today, technology is developing, and as a result, the world wide web (www) has a very important place on the Internet and the significant task is fulfilled by Web services. A lot of Web services are available on the Internet and, therefore, it is difficult to find matching Web services among the available Web services. The recommendation systems can help in fixing this problem. In this paper, our observation was based on the recommended method such as the collaborative filtering (CF) technique which faces some failure from the data sparsity and the cold-start problems. To overcome these problems, we first applied an ontology-based clustering and then the k-nearest neighbor (KNN) algorithm for each separate cluster group that effectively increased the data density using the past user interests. Then, user ratings were predicted based on the model-based approach, such as singular value decomposition (SVD) and the predictions used for the recommendation. The evaluation results showed that our proposed approach has a less prediction error rate with high accuracy after analyzing the existing recommendation methods.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.1
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• pp.117-126
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• 2018

The purpose of this study is to analyze the spatial distribution characteristics and spatial changes of Automatic Weather Stations (AWS) in mountainous areas with altitude more than 200 meters in South Korea. In order to analyze the spatial distribution patterns, spatial analysis was performed on 203 Automatic Mountain Meteorology Observation Station (AMOS) points from 2012 to 2016 by Euclidean distance analysis, nearest neighbor index analysis, and Kernel density analysis methods. As a result, change of the average distance between 2012 and 2016 decreased up to 16.4km. The nearest neighbor index was 0.666632 to 0.811237, and the result of Z-score test was -4.372239 to -5.145115(P<0.01). The spatial distributions of AMOSs through Kernel density analysis were analyzed to cover 129,719ha/a station in 2012 and 50,914ha/a station in 2016. The result of a comparison between 2012 and 2016 on the spatial distribution has decreased about 169,399ha per a station for the past 5 years. Therefore it needs to be considered the mountainous regions with low density when selecting the site of AMOS.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.323-330
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• 2004

In this paper, we propose a design method of PID controller using an improved Tabu Search. Tabu Search is improved by neighbor solution creation using Gaussian random distribution and generalized Hermite Biehler Theorem for stable bounds. The range of admissible proportional gains are determined first in closed form. Next the optimal PID gains are selected by improved Tabu Search. The results of Computer simulations represent that the proposed Tabu Search algorithm shows a fast convergence speed and a good control performance.

• Cartoon and Animation Studies
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• s.40
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• pp.211-242
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• 2015

Recently, the shrunk influence of printed cartoon has been superseded by the influence of Webtoon in the comic industry. Webtoon has gained popularity and interest by being served on internet quickly and easily. Their novel material and sympathetic topic have made it possible for many Webtoons to be reproduced into tv dramas and movies, so, the influence of them has been increased as the copyright industry of culture contents industry. The increasing interest for Webtoon has induced academic studies for the subject. Among the various studies in need on Webtoon, the most important study topics in need are 'Story' and 'Quality' which are criterion for readers to choose Webtoons to read. To create the Webtoon that are great at 'Story' and 'Quality', the study on plots should be preceded, which recast episodes organically through a logical causal relationship. Therefore, in this study, the plots of Webtoons have been analyzed through Rescue plot in and the Riddle plot in selected from the Kang Full's Webtoon series, 'mystery psychology horror season', which are evaluated as the great work at 'Story' and 'Quality.' The analysis was implemented based on Tobias' theory which suggests 'the characteristics of plot' and '8 principles for good plot.' First, Kang Full's webtoons were analyzed through 'the characteristics of plot' and '6 principles for good plot' which is modified from '8 principles of good plot' based on Tobias' theory. Applicability was checked if Tobias' theory could be applied to Kang Full's Webtoon checking through the scenes and contents of the Webtoon. (1) Tobias' 'the characteristics of plot' could be applied to both Rescue plot in and the Riddle plot in . (2) Among '6 principles for good plot', 5 principles are shown in The Lighting Store and all of the 6 principles in Neighbor. The result shows that Tobias theory could be applied to the plot of Webtoon. The fact that Kang Full's Webtoons are composed in a formulaic form could be identified through 'the characteristics of plot' and '6 principles for good plot' shown in Rescue plot in and the Riddle plot in .

• Journal of Life Science
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• v.33 no.3
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• pp.227-233
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• 2023

The purpose of this paper was to describe a statistical analysis for the spatial distribution of geographical distances of Erythronium japonicum at Mt. Geumjeong in Korea. The spatial pattern of E. japonicum was analyzed according to the nearest neighbor rule, population aggregation under different plot sizes by dispersion indices, and spatial autocorrelation. Most natural plots of E. japonicum were uniformly distributed in the forest community. Disturbed plots were aggregately distributed within 5 m × 5 m of one another. Neighboring patches of E. japonicum were predominantly 7.5~10 m apart on average. If the natural populations of E. japonicum were disturbed by human activities, then the aggregation occurred in a shorter distance than the 7.5~10 m distance scale. The Morisita index (IM) is related to the patchiness index (PAI) that showed the 2.5 m × 5 m plot had an overly steep slope at the west and south areas when the area was smaller than 5 m × 5 m. When the patch size was one 2.5 m × 5 m quadrat at the west distributed area of Mt. Geumjeong, the cluster was determined by both species characteristics and environmental factors. The comparison of Moran's I values to a logistic regression indicated that individuals in E. japonicum populations at Mt. Geumjeong could be explained by isolation by distance.

• Journal of the Korean Magnetics Society
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• v.3 no.3
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• pp.179-184
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• 1993

The X-ray diffraction pattern of amorphous $Fe_{78}Si_{9}B_{13}$ alloy was analyzed to obtain the radial distribution function (RDF) where the first peak was in the form of Gaussian function. The calculated coordination number of the form of Gaussian functiono The calculated coordination number of the sample is 13.5, the mean distance betweeon near-neighbor atoms $r_{0}$ is $2.595{\AA}$ and a Gaussian parametet ${\delta}r$ indicating near-neighbor atomic distri-bution is $0.27{\AA}$. The temperature dependence of saturated magnetization at low temperature could be explained by spin wave excitations theory yielding the spin wave stiffness constant as $117.8\;meV\;{\AA}^2$. Also, we tried to fit the observed temperature dependence of saturated magnetization with the Handrich's equation of the modified molecular field theory for the amorphous ferromagnet. Nice fittings are obtained when we used the parameters ${\Delta}=0.32$(S=1/2) and ${\Delta}=0.23$(S=1), respectively. Finally, the calculated spin wave stiffness constant using the parameters and the structural data are $149\;meV\;{\AA}^2$ for S=1/2 and $138\;meV\;{\AA}^2$ for S=1, respectively. The mean exchange coupling integral between near-neighbor atoms was estimated to be 17.9 meV for S=1/2 and 6.7 meV for S=1.

• Journal of Korean Society of Transportation
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• v.33 no.5
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• pp.497-507
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• 2015

Nonrecurrent congestion of freeway was primarily caused by incident. The main cause of incident was known as a traffic accident. Therefore, accurate prediction of traffic incident clearance time is very important in accident management. Traffic accident data on freeway during year 2008 to year 2014 period were analyzed for this study. KNN(K-Nearest Neighbor) algorithm was hired for developing incident clearance time prediction model with the historical traffic accident data. Analysis result of accident data explains the level of accident significantly affect on the incident clearance time. For this reason, incident clearance time was categorized by accident level. Data were sorted by classification of traffic volume, number of lanes and time periods to consider traffic conditions and roadway geometry. Factors affecting incident clearance time were analyzed from the extracted data for identifying similar types of accident. Lastly, weight of detail factors was calculated in order to measure distance metric. Weight was calculated with applying standard method of normal distribution, then incident clearance time was predicted. Prediction result of model showed a lower prediction error(MAPE) than models of previous studies. The improve model developed in this study is expected to contribute to the efficient highway operation management when incident occurs.

• Korean Journal of Plant Resources
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• v.24 no.4
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• pp.358-369
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• 2011

The internal transcribed spacer (ITS) regions of nuclear ribosomal DNA from genus Chrysosplenium were sequenced to address phylogenetic relationship. ITS including 5.8S sequence varied in length from 647 bp to 653 bp. Among them, 219 sites were variable sites with parsimony-informative. The aligned sequences were analyzed by maximum parsimony (MP) and neighbor-joining (NJ) methods. In the strict consensus trees of parsimony analysis, the monophyly of Chrysosplenium was supported by 100% bootstrap value. The first clade, C. pseudofauriei was at the basal position of the genus, and others formed two clades with high bootstrap support. The second clade included Ser. Pilosa and Ser. Oppositifolia and third clade included Ser. Alternifolia and Ser. Flagellifera. The NJ trees showed essentially the same topology. Finally, DNA sequences of ITS regions were useful phylogenetic marker in this genus. Based on the ITS and ridge seed morphological results, C. sphaerospermum Maxim. and C. valdepilosum (Ohwi) S.H. Kang & J.W. Han were discussed their scientific names and taxonomic positions.

• Journal of KIISE:Databases
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• v.36 no.2
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• pp.73-83
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• 2009

In this paper we propose an object similarity matching method based on shape characteristics of an object in an image. The proposed method extracts edge points from edges of objects and generates a log polar histogram with respect to each edge point to represent the relative placement of extracted points. It performs the matching in such a way that it compares polar histograms of two edge points sequentially along with edges of objects, and uses a well-known k-NN(nearest neighbor) approach to retrieve similar objects from a database. To verify the proposed method, we've compared it to an existing Shape-Context method. Experimental results reveal that our method is more accurate in object matching than the existing method, showing that when k=5, the precision of our method is 0.75-0.90 while that of the existing one is 0.37, and when k=10, the precision of our method is 0.61-0.80 while that of the existing one is 0.31. In the experiment of rotational transformation, our method is also more robust compared to the existing one, showing that the precision of our method is 0.69 while that of the existing one is 0.30.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.835-845
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• 2013

Travel-time is considered the most typical and preferred traffic information for intelligent transportation systems(ITS). This paper proposes a real-time travel-time prediction method for a national highway. In this paper, the K-nearest neighbor(KNN) method is used for travel time prediction. The KNN method (a nonparametric method) is appropriate for a real-time traffic management system because the method needs no additional assumptions or parameter calibration. The performances of various models are compared based on mean absolute percentage error(MAPE) and coefficient of variation(CV). In real application, the analysis of real traffic data collected from Korean national highways indicates that the proposed model outperforms other prediction models such as the historical average model and the Kalman filter model. It is expected to improve travel-time reliability by flexibly using travel-time from the proposed model with travel-time from the interval detectors.