• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.85-94
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• 2014

This paper studied the detection technique using file DNA-based behavior pattern analysis in order to minimize damage to user system by malicious programs before signature or security patch is released. The file DNA-based detection technique was applied to defend against zero day attack and to minimize false detection, by remedying weaknesses of the conventional network-based packet detection technique and process-based detection technique. For the file DNA-based detection technique, abnormal behaviors of malware were splitted into network-related behaviors and process-related behaviors. This technique was employed to check and block crucial behaviors of process and network behaviors operating in user system, according to the fixed conditions, to analyze the similarity of behavior patterns of malware, based on the file DNA which process behaviors and network behaviors are mixed, and to deal with it rapidly through hazard warning and cut-off.

• Journal of KIISE:Software and Applications
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• v.35 no.7
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• pp.442-451
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• 2008

Most plagiarism detection systems evaluate the similarity of source codes and detect plagiarized program pairs. If we use the source codes in plagiarism detection, the source code security can be a significant problem. Plagiarism detection based on target code can be used for protecting the security of source codes. In this paper, we propose a new plagiarism detection technique for Java programs using bytecodes without referring their source codes. The plagiarism detection procedure using bytecode consists of two major steps. First, we generate the token sequences from the Java class file by analyzing the code area of methods. Then, we evaluate the similarity between token sequences using the adaptive local alignment. According to the experimental results, we can find the distributions of similarities of the source codes and that of bytecodes are very similar. Also, the correlation between the similarities of source code pairs and those of bytecode pairs is high enough for typical test data. The plagiarism detection system using bytecode can be used as a preliminary verifying tool before detecting the plagiarism by source code comparison.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.347-356
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• 2006

A video stream can be represented by a sequence of data points in a multidimensional space. In this paper, we introduce a trend vector that approximates values of data points in a sequence and represents the moving trend of points in the sequence, and present a pattern similarity matching method for data sequences using the trend vector. A sequence is partitioned into multiple segments, each of which is represented by a trend vector. The query processing is based on the comparison of these vectors instead of scanning data elements of entire sequences. Using the trend vector, our method is designed to filter out irrelevant sequences from a database and to find similar sequences with respect to a query. We have performed an extensive experiment on synthetic sequences as well as video streams. Experimental results show that the precision of our method is up to 2.1 times higher and the processing time is up to 45% reduced, compared with an existing method.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.624-632
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• 2017

Automatic butterfly identification using images is one of the interesting research fields because it helps the related researchers studying species diversity and evolutionary and development process a lot in this field. The performance of the butterfly species identification system is dependent heavily on the quality of selected features. In this paper, we propose color intensity (CI) entropy by using the distribution of color intensities in a butterfly image. We show color intensity entropy can increase the recognition rate by 10% if it is used together with previously suggested branch length similarity entropy. In addition, the performance comparison with other features such as Eigenface, 2D Fourier transform, and 2D wavelet transform is conducted against several well known machine learning methods.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.775-784
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• 2019

Image stitching is a technique for solving the problem of narrow field of view of a camera by composing multiple images. Recently, as the use of content such as Panorama, Super Resolution, and 360 VR increases, the need for faster and more accurate image stitching technology is increasing. So far, many algorithms have been proposed to satisfy the required performance, but the objective evaluation method for measuring the accuracy has not been standardized. In this paper, we present the problems of PSNR and SSIM(Structural similarity index method) measurement methods and propose a Local Differential Pixel Mean method. The LDPM evaluation method that includes geometric similarity and brightness measurement information is proved through a test, and the advantages of the evaluation method are revealed through comparison with SSIM.

• Fashion & Textile Research Journal
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• v.23 no.2
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• pp.247-260
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• 2021

While it is an important element of clothing construction, research has so far been very limited on the similarities between virtual and real clothing in terms of the type of neckline. The purpose of this study is to verify the similarity, accuracy of virtualization, and actuality of neckline, which all play an important role in individual impressions and image formation, and require considerable modification when fitting real samples. A total of 5 neckline models were selected through the analysis of dress composition textbooks. The selected designs were then planned and manufactured in muslin. The specimen clothes were then tested on a female model in her 20s. 2 kinds of virtual bodies were created in order to compare the real and the virtual dressing. The first virtual body was made through an Artec 3D Eva scan of the model, and the other was made by entering the model's measurements in a CLO 3D program. A visual image of the front, side, and back image of both the real and virtual dressing were subsequently collected. The collected images were then evaluated by 20 professional fashion workers who checked the similarity between the real and the virtual versions. The current study found that the similarity between the actual and virtual wearing of the five neckline designs with reality appeared higher with the virtual wearing image using the 3D-scanned body. The results of this study could provide further information on the selection of appropriate avatars to clothing companies that check the fit of clothing by utilizing 3D virtualized programs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.169-174
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• 2019

In this study, I use surveillance data collection and data mining, clustered by clustering method, and use supervised learning to judge similarity. I aim to use feature extraction algorithms and supervised learning to analyze the suitability of the correlations of personality. After conducting the questionnaire survey, the researchers refine the collected data based on the questionnaire, classify the data sets through the clustering techniques of WEKA, an open source data mining tool, and judge similarity using supervised learning. I then use feature extraction algorithms and supervised learning to determine the suitability of the results for personality. As a result, it was found that the highest degree of similarity classification was obtained by EM classification and supervised learning by Naïve Bayes. The results of feature classification and supervised learning were found to be useful for judging fitness. I found that the accuracy of each Big-5 personality was changed according to the addition and deletion of the items, and analyzed the differences for each personality.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.51-57
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• 2019

On increasing illegal software copyright, the need for similarity analysis is now rising. The reliability of object material are becoming important when it's moving from developer to evaluation experts. Object material as a comparison data, is the important data to the evaluation expert which is delivered from agencies such as courts and police stations. The object material is submitted at first to the Copyright Commission and then delivered to the evaluation expert with safe. However, if the similarity result is not satisfied to the both side, they will claim to the reliability of the object material such as source code modification or revision etc. Software objects is produced in a file format and are recognized as being able to be modified. Therefore, the reliability to the object material is studied in various ways, and a forensic is proposed as one method. This study showed the suggestion to keep reliability of the object material through the actual evaluation cases.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.250-260
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• 2023

Background: Crabgrass (Digitaria ciliaris, Poaceae) is a globally distributed weed, including in Afro-Eurasia, America, and Australia. As a highly gregarious plant, crabgrass is an important habitat for a diverse array of insects, and a potential habitat for agricultural pests. To compare the insect communities associated with the crabgrass community, insects were sampled using sweep sampling (100 sweeps per sample) at five sites, including Daejeon (Daejeon and Gap rivers), Anseong, Namhae, and Inje, with a focus on the Daejeon River. Results: A total of 5,888 individual insects belonging to eight orders, 42 families, and 115 species were collected from the five sites. Both the number of species and individuals of Hemiptera were the highest at all of the sites. In the present study, 73% of the insect population fed on D. ciliaris as a host plant. The dominant species in the D. ciliaris community was Laodelphax striatellus (Delphacidae), being ubiquitous at all the sites which showed a high abundance of rice pests in the communities and the suitability of D. ciliaris as an alternative host plant for them. The Shannon-Wiener diversity index was highest in Inje on 17 September (2.88), and the Chao1-bc diversity index was highest in the Gap River on 5 September (80). The sampling efficiency of 100 sweep samples (sample coverage) was calculated to be as high as 90%. The results of the samples taken from September to November in the Daejeon River showed that the number of species and individuals decreased gradually over time, and the number of dominant species decreased sharply between September and October. Similarity analysis indicated that sampling dates that were closer together yielded sampled assemblages with higher faunal similarity. In addition, in each sampling, the difference in the minimum temperature during the two-week period prior to sampling and faunal similarities were negatively correlated. Conclusions: This study provides foundational data that could enhance our understanding of insect diversity in D. ciliaris. The data can facilitate ecological conservation and management of Korean grasslands generally, as well as identification of potential pests that may disperse from D. ciliaris communities to nearby farmland.

• Journal of Science Education
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• v.47 no.2
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• pp.180-191
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• 2023

The purpose of this study was to investigate the preferred SSI topics of students and teachers in elementary, middle, and high schools. It analyzed the similarity of students' and teachers' preferred SSI topics by school level using the cosine similarity measure. A total of 566 students and 327 teachers from elementary, middle, and high schools participated in the study. Sixty topics were identified and listed in the areas of environment, science and technology, health and medicine, and other social issues based on the literature and SSI programs. Students and teachers were asked to select five of their favorite topics. The data was collected online using SurveyMonkey. The collected data was divided into six groups of students and teachers, and the frequency of topic selection was analyzed within each group. The topic preference similarity was analyzed by calculating vector values based on the frequency of the selected topics and measuring the cosine similarity between students, teachers, and teachers and students by school level. The results are as follows: First, the cosine similarity of SSI Preferred Topics between students' school-level cohorts was higher between middle and high school students (0.982) than between elementary and middle school students (0.651) or between elementary and high school students (0.662). Second, the cosine similarity of SSI Preferred Topics between teachers' school-level cohorts was similar for all comparison groups between elementary, middle, and high school. Third, the SSI topic preference similarity between students and teachers by school level had a higher cosine similarity between the elementary student and teacher cohorts (0.974) than the other school level comparisons, middle school (0.621) or high school (0.645). Access to topics of interest to students in SSI education is strongly associated with motivation and persistence in learning, as well as an enjoyable learning experience and positive attitudes toward learning. Therefore, when designing SSI lessons, it is important to examine topics from the perspective of student interest, especially if the teacher has selected SSI topics that are different from students' preferences. Careful instructional design will be needed to overcome the gap.