• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2002.05a
• /
• pp.104-107
• /
• 2002

Traditional queueing analyses are very useful for designing a network's capacity and predicting there performances, however most of the predicted results from the queueing analyses are quite different from the realistic measured performance. And recent empirical studies on LAN, WAN and VBR traffic characteristics have indicated that the models used in the traditional Poisson assumption can't properly predict the real traffic properties due to under estimation of the long range dependence of network traffic and self-similarity. In this paper self-similar characteristics over statistical approaches and real time network traffic measurements are estimated. It is also shown that the self-similar traffic reflects network traffic characteristics by comparing source model.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.7B
• /
• pp.620-627
• /
• 2003

Ethernet passive optical networks (EPONs) are an emerging access network technology that provide a low-cost method of deploying optical access lines between a carrier's central office and customer sites. Dynamic bandwidth allocation (DBA) provides statistical multiplexing between the optical network units for efficient upstream channel utilization. To support dynamic bandwidth distribution, 1 propose an cyclic polling-based DBA algorithm for differentiated classes of service in EPONs. And, I show that an interleaved polling scheme severely decreases downstream channel capacity for user traffics when the upstream network load is low. To obtain realistic simulation results, I used synthetic traffic that exhibits the properties of self-similarity and long-range dependence I then analyzed the network performance under various loads, specifically focusing on packet delays for different classes of traffic.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2010.11a
• /
• pp.705-708
• /
• 2010

An eigen color co-occurrence approach is proposed that exploits the correlation between color channels to identify the degree of image similarity. This method is based on traditional co-occurrence matrix method and histogram equalization. On the purpose of feature extraction, eigen color co-occurrence matrices are computed for extracting the statistical relationships embedded in color images by applying Principal Component Analysis (PCA) on a set of color co-occurrence matrices, which are computed on the histogram equalized images. That eigen space is created with a set of orthogonal axes to gain the essential structures of color co-occurrence matrices, which is used to identify the degree of similarity to classify an input image to be tested for various purposes. In this paper RGB, Gaussian color space are compared with grayscale image in terms of PCA eigen features embedded in histogram equalized co-occurrence features. The experimental results are presented.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.35 no.1 s.120
• /
• pp.59-68
• /
• 2007

This article statistically analyzed contributive levels of district image based on an effect and a similarity index through the evaluation of citizens and suggested the efficient management system of a city image according to the results. For this study, Busan City was selected as a case city by the preceding literature and was investigated concerning district image and city image through a questionnaire. The new evaluation method for analysis of a city image was presented in this process. The results of this research are as follows: 1. Busan City has a substantial positive and culturally unique image, and each of its districts have other image characteristics. for example, the CBD district has a positive image, and the sea shore district has a busy and prosperous image, but the backward sea shore district has an image of stagnancy. 2. The image of Yeonje-gu has the largest effect on the image of Busan. Next in influence are Jung-gu, Saha-gu, Suyoung-gu, respectively. The effect index is closely connected with the variance of evaluative adjectives. 3. Busanjin-gu and Haeundae-gu have similar images to Busan City. Next in similarity are Nam-gu, Jung-gu, Youngdo-gu, Suyoung-gu, respectively. The similarity index is closely connected with the correlation of evaluative adjectives. Busan City and its districts can establish their image strategies with the above analyzed results. This study is meaningful in that a statistical evaluative method was proposed. With continued follow-up research, this study may serve as a systematic and logical model to improve the urban landscape and image.

• The Korean Journal of Applied Statistics
• /
• v.34 no.2
• /
• pp.191-204
• /
• 2021

Visual Question Answering (VQA) and image captioning are tasks that require understanding of the features of images and linguistic features of text. Therefore, co-attention may be the key to both tasks, which can connect image and text. In this paper, we propose a model to achieve high performance for VQA by image caption generated using a pretrained standard transformer model based on MSCOCO dataset. Captions unrelated to the question can rather interfere with answering, so some captions similar to the question were selected to use based on a similarity to the question. In addition, stopwords in the caption could not affect or interfere with answering, so the experiment was conducted after removing stopwords. Experiments were conducted on VQA-v2 data to compare the proposed model with the deep modular co-attention network (MCAN) model, which showed good performance by using co-attention between images and text. As a result, the proposed model outperformed the MCAN model.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.25 no.3
• /
• pp.29-45
• /
• 2022

For biodiversity conservation, the importance of beta-diversity which is changes in the composition of species according to environmental changes has become emphasized. However, given the systematic investigation of species distribution and the accumulation of large amounts of data in the Republic of Korea(ROK), research on the spatialization of beta-diversity using them is insufficient. Accordingly, this research investigated the applicability of the Generalized Dissimilarity Modeling(GDM) to ROK, which can predict and map the similarity of compositional turnover (beta-diversity) based on environmental variables. A brief overview of the statistical description on using GDM was presented, and a model was fitted using the flora distribution data(410,621points) from the National Ecosystem Survey and various environmental spatial data including climate, soil, topography, and land cover. Procedures and appropriated spatial units required to improve the explanatory power of the model were presented. As a result, it was found that geographical distance, temperature annual range, summer temperature, winter precipitation, and soil factors affect the dissimilarity of the vegetation community composition. In addition, as a result of predicting the similarity of vegetation composition across the nation, and classifying them into 20 and 100 zones, the similarity was high mainly in the central inland area, and tends to decrease toward the mountainous areas, southern coastal regions, and island including Jeju island, which means the composition of the vegetation community is unique and beta diversity is high. In addition, it was identified that the number of common species between zones decreased as the geographic distance between zones increased. It classified the spatial distribution of plant community composition in a quantitative and objective way, but additional research and verification are needed for practical application. It is expected that research on community-level biodiversity modeling in the ROK will be conducted more actively based on this study.

• 한국균학회소식:학술대회논문집
• /
• 2014.05a
• /
• pp.19-19
• /
• 2014

This study included the analysis of mushroom data collected from Mt. Chiak in Gangwon-do using various methods. Former studies of Korean mushrooms are limited by regional characters and there is less species diversity among the regions. This study tried to find a way for the forecast of mushroom distribution and appearance by indexes of species diversity. The indexes used in this study include the number of fungi (N), the number of species (S), similarity index (C), richness index (R1, R2), variety index (V1, V2), evenness index (E1, E2, E3, E4, E5), and dominance index (D1) to analyze variety of species diversity. Analyses of data of fungi using a multistage cluster sampling indicate that the average value of C for years was higher than the average value of C for areas. The mushrooms consisted of 208 species in 686 individuals in limited fungal collection from 2002 to 2003. One hundred thirty nine species in 393 individuals were collected in 2002, and 122 species 293 individuals were collected in 2003. The individuals collected in 2003 were smaller than 2002's individuals. Similarity, richness, and variety indexes' values of 2003 were reduced than 2002's values but dominance index of 2003 was increased than 2002's value. Generally the species diversity of the environment to evaluate the index of similarity, richness, and variety was a higher index; dominance index was lower than that of the surrounding environment, suggesting a good diversity. As a result, the occurrence of mushrooms in the surrounding environment and the various factors seem fell in 2002 compared to 2003. The majority genus of the limited fungal collection was Mycena genus in 63 individuals; the majority species was Laccaria laccata in 34 individuals. Ninety three species in 106 individuals were collected by the extended collection and the majority genus of the extended collection was Amanita genus in 17 individuals; the majority species was Amanita citrina (Schaeff.) Pers. which was found in 5 individuals. This demonstrates that periodical similarity's value was 0.159 is higher than special similarity's 0.119. This indicates that the probability of the appearance of same mushrooms in the same area in following year is higher than the probability of the appearance of same mushrooms in the surrounding area in same year. The value of coefficient of variation (CV), in which the amount of change is much or less by N is higher than the CV value by S. CV value of dominance index(D) was the highest r point among other indexes, and evenness index (E) was the lowest point among other indexes. The correlation matrix with 66 combinations between the indexes, the combinations with correlations was 46 combinations. These results revealed that indexes of R1, V2, and E1 were proper to represent species diversity of fungi based on the correlation matrix and the theory of statistical independence which means there is no or less mutual association. This research would contribute to the study about variable living creature by measuring method and in the future this would be used to figure out regulation about fungi with their correlation, values in ecosystem, develop improving new models about agricultural fungi species and numbers by investigating agricultural variable species.

• The Journal of Society for e-Business Studies
• /
• v.23 no.2
• /
• pp.83-96
• /
• 2018

Extracting keywords representing documents is very important because it can be used for automated services such as document search, classification, recommendation system as well as quickly transmitting document information. However, when extracting keywords based on the frequency of words appearing in a web site documents and graph algorithms based on the co-occurrence of words, the problem of containing various words that are not related to the topic potentially in the web page structure, There is a difficulty in extracting the semantic keyword due to the limit of the performance of the Korean tokenizer. In this paper, we propose a method to select candidate keywords based on semantic similarity, and solve the problem that semantic keyword can not be extracted and the accuracy of Korean tokenizer analysis is poor. Finally, we use the technique of extracting final semantic keywords through filtering process to remove inconsistent keywords. Experimental results through real web pages of small business show that the performance of the proposed method is improved by 34.52% over the statistical similarity based keyword selection technique. Therefore, it is confirmed that the performance of extracting keywords from documents is improved by considering semantic similarity between words and removing inconsistent keywords.

• Journal of Digital Convergence
• /
• v.14 no.6
• /
• pp.133-142
• /
• 2016

The purpose of this study is to test the effects of brand image and product similarity with the original on the attitude toward the counterfeit of prestige brand. Especially this study is focused on the moderating effect of perceived bland globalness (PBG) and the influence of the original attitude on the counterfeit one. The results of this study are as follows 1) brand image has a positive impact on the counterfeit attitude as well as the original one. And symbolic image is more positive than functional image on the both of them. 2)The moderating effect of PBG appeared between brand image and attitude. Namely, there is no statistical difference according to PBG in the effect of brand image on the original attitude. But the effect of brand image on the counterfeit attitude is higher in case of high PBG. 3) Product similarity of the counterfeit with the original has a positive impact on only the counterfeit attitude. And the similarity of perceived quality is more positive than appearance similarity on the counterfeit attitude. 4) The original attitude has a positive impact on the counterfeit one.

• Journal of Korean Society for Geospatial Information Science
• /
• v.24 no.1
• /
• pp.89-98
• /
• 2016

In this paper, we proposed an automated areal feature matching method based on geometric similarity without user intervention and is applied into areal features of many-to-many relation, for confusion of spatial data-sets of different scale and updating cycle. Firstly, areal feature(node) that a value of inclusion function is more than 0.4 was connected as an edge in adjacency matrix and candidate corresponding areal features included many-to-many relation was identified by multiplication of adjacency matrix. For geometrical matching, these multiple candidates corresponding areal features were transformed into an aggregated polygon as a convex hull generated by a curve-fitting algorithm. Secondly, we defined matching criteria to measure geometrical quality, and these criteria were changed into normalized values, similarity, by similarity function. Next, shape similarity is defined as a weighted linear combination of these similarities and weights which are calculated by Criteria Importance Through Intercriteria Correlation(CRITIC) method. Finally, in training data, we identified Equal Error Rate(EER) which is trade-off value in a plot of precision versus recall for all threshold values(PR curve) as a threshold and decided if these candidate pairs are corresponding pairs or not. To the result of applying the proposed method in a digital topographic map and a base map of address system(KAIS), we confirmed that some many-to-many areal features were mis-detected in visual evaluation and precision, recall and F-Measure was highly 0.951, 0.906, 0.928, respectively in statistical evaluation. These means that accuracy of the automated matching between different spatial data-sets by the proposed method is highly. However, we should do a research on an inclusion function and a detail matching criterion to exactly quantify many-to-many areal features in future.