• Korean Journal of Environment and Ecology
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• v.29 no.2
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• pp.200-209
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• 2015

This study was conducted to investigate the distributional characteristics of ground beetles and to provide basis information for biodiversity management including the ground beetles in the Naejangsan National Park area. Pitfall traps were installed throughout 20 sites within Naejangsan National Park during 2008 to 2011 to collect ground beetles. A total of 2,409 collected ground beetles were identified with 35 species belonging to 19 genera of 8 subfamilies. Coptolabrus jankowskii jankowskii, Eucarabus sternbergi sternbergi, and Pterosticus audax were dominant at the core area, while Pheropsophus jessoensis, Synuchus nitidus, Synuchus cycloderus, and Chlaenius naeviger were dominant at the border of the National Park and adjacent to the road or grassland. These differences of dominant species also affected to the similarity of species composition between core and border area, and caused increasing dissimilarities between sites with cluster analysis. Although the result of the present study was a case study using ground beetles, it will be helpful to develop a management strategy of biodiversity conservation in Naejangsan National Park and its surroundings.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.147-161
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• 2010

As broadcasting and communication are converged recently, communication is jointed to TV. TV viewing has brought about many changes. The IPTV (Internet Protocol Television) provides information service, movie contents, broadcast, etc. through internet with live programs + VOD (Video on demand) jointed. Using communication network, it becomes an issue of new business. In addition, new technical issues have been created by imaging technology for the service, networking technology without video cuts, security technologies to protect copyright, etc. Through this IPTV network, users can watch their desired programs when they want. However, IPTV has difficulties in search approach, menu approach, or finding programs. Menu approach spends a lot of time in approaching programs desired. Search approach can't be found when title, genre, name of actors, etc. are not known. In addition, inserting letters through remote control have problems. However, the bigger problem is that many times users are not usually ware of the services they use. Thus, to resolve difficulties when selecting VOD service in IPTV, a personalized service is recommended, which enhance users' satisfaction and use your time, efficiently. This paper provides appropriate programs which are fit to individuals not to save time in order to solve IPTV's shortcomings through filtering and recommendation-related system. The proposed recommendation system collects TV program information, the user's preferred program genres and detailed genre, channel, watching program, and information on viewing time based on individual records of watching IPTV. To look for these kinds of similarities, similarities can be compared by using ontology for TV programs. The reason to use these is because the distance of program can be measured by the similarity comparison. TV program ontology we are using is one extracted from TV-Anytime metadata which represents semantic nature. Also, ontology expresses the contents and features in figures. Through world net, vocabulary similarity is determined. All the words described on the programs are expanded into upper and lower classes for word similarity decision. The average of described key words was measured. The criterion of distance calculated ties similar programs through K-medoids dividing method. K-medoids dividing method is a dividing way to divide classified groups into ones with similar characteristics. This K-medoids method sets K-unit representative objects. Here, distance from representative object sets temporary distance and colonize it. Through algorithm, when the initial n-unit objects are tried to be divided into K-units. The optimal object must be found through repeated trials after selecting representative object temporarily. Through this course, similar programs must be colonized. Selecting programs through group analysis, weight should be given to the recommendation. The way to provide weight with recommendation is as the follows. When each group recommends programs, similar programs near representative objects will be recommended to users. The formula to calculate the distance is same as measure similar distance. It will be a basic figure which determines the rankings of recommended programs. Weight is used to calculate the number of watching lists. As the more programs are, the higher weight will be loaded. This is defined as cluster weight. Through this, sub-TV programs which are representative of the groups must be selected. The final TV programs ranks must be determined. However, the group-representative TV programs include errors. Therefore, weights must be added to TV program viewing preference. They must determine the finalranks.Based on this, our customers prefer proposed to recommend contents. So, based on the proposed method this paper suggested, experiment was carried out in controlled environment. Through experiment, the superiority of the proposed method is shown, compared to existing ways.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.109-125
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• 2020

The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.

• Journal of Korean Public Health Nursing
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• v.15 no.2
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• pp.363-375
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• 2001

The purpose of this study is to analyse the effects of obesity management program in food attitude and food habit, body composition(body fat ratio, body fat weight, lean body mass, total body water), abdominal girth(waist, hip, thigh), and serum lipid level(cholesterol, low density lipoprotein, triglyceride, phospholipid, NE fatty acid, high density lipoprotein) of middle aged women. Data for the study were collected from July 4 to August 25, 2000. The study objects were 20 middle aged women(10 controls and 10 experimental objects) from 40 to 50 years old who had body fat ratio more than $30\%$ and waist girth more than 80cm. The results were as follows: 1. Similarity test between experimental group and control group processed by serum HDL level showed the significant difference(t=3.25, p=0.004), but that processed by age, body weight, body fat ratio, body fat weight, lean body mass, total body water, waist girth, hip girth, thigh girth, cholesterol level, LDL level, triglyceride level, NE fatty acid level, food attitude and food habit score showed no significant difference(p>0.05). These findings imply that the two groups are similar in the sample distribution. 2. The effects of the abdominal obesity management program The obtained results indicate that the abdominal obesity management program in middle aged women changes the food attitude & the food habit. decreases the body fat ratio & the body fat weight and increases the lean body mass, and decreases the girth of waist & hip and the serum level of cholesterol & LDL. Therefore, it is concluded that the abdominal obesity management program can be applied for nursing intervention to decrease the body fat weight and abdominal obesity.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.183-192
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• 2003

With the availability of complete whole-genomes such as the human, mouse, fugu and chimpanzee chromosome 22, comparative analysis of large genomes from cross-species at varying evolutionary distances is considered one of a powerful approach for identifying coding and functional non-coding sequences. Here we describe a fast and efficient global alignment method especially for large genomic regions over mega bases pair. We used an approach for identifying all similarity regions by HSP (Highest Segment Pair) regions using local alignments and then large syntenic genome based on the both extension of anchors at HSP regions in two species and global conservation map. Using this alignment approach, we examined rearrangement loci in human chromosome 21 and chimpanzee chromosome 22. Finally, we extracted syntenic genome 30 Mb of human chromosome 21 with chimpanzee chromosome 22, and then identified genomic rearrangements (deletions and insertions ranging h size from 0.3 to 200 kb). Our experiment shows that all jnsertion/deletion (indel) events in excess of 300 bp within chimpanzee chromosome 22 and human chromosome 21 alignments in order to identify new insertions that had occurred over the last 7 million years of evolution. Finally we also discussed evolutionary features throughout comparative analyses of Ka/ks (non-synonymous / synonymous substitutions) rate in orthologous 119 genes of chromosome 21 and 53 genes of MHC-I class in human and chimpanzee genome.

• Journal of Korean Elementary Science Education
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• v.33 no.4
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• pp.674-682
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• 2014

This study aims to analyze STEAM-related articles and to look into the trend of research to present implications for research directions in the future. To achieve the research purpose, the researcher searched by key words, 'STEAM' and 'Convergence Education' through the RISS. Subjects of analysis were titles of 181 articles in journal articles and conference papers published from 2011 through 2013. Through an analysis of the frequency of the texts that appeared in the titles of the papers, key words were selected, the co-occurrence matrix of the key words was established, and using network maps, degree centrality and betweenness centrality, and structural equivalence, a network text analysis was carried out. For the analysis, KrKwic, KrTitle, UCINET and NetMiner Program were used, and the results were as follows: in the result of the text frequency analysis, the key words appeared in order of 'program', 'development', 'base' and 'application'. Through the network among the texts, a network built up with core hubs such as 'program', 'development', 'elementary' and 'application' was found, and in the degree centrality analysis, 'program', 'elementary', 'development' and 'science' comprised key issues at a relatively high value, which constituted the pivot of the network. As a result of the structural equivalence analysis, regarding the types of their respective relations, it was analyzed that there was a similarity in four clusters such as the development of a program (1), analysis of effects (2) and the establishment of a theoretical base (1).

• Journal of the Korean Society of Radiology
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• v.15 no.1
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• pp.9-14
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• 2021

Recently, magnetic resonance imaging (MRI), which can acquire images with good contrast without exposure to radiation, has been widely used for diagnosis. However, noise that reduces the accuracy of diagnosis is essentially generated when acquiring the MR images, and by adjusting the parameters, the noise problem can be solved to obtain an image with excellent characteristics. Among the parameters, the number of excitation (NEX) can acquire images with excellent characteristics without additional degradation of image characteristics. In contrast, appropriate NEX setting is required since the scan time increases and motion artifacts may occur. Therefore, in this study, after fixing all MRI parameters through the MRiLab simulation program, we tried to evaluate the tendency of image characteristics according to changing NEX through quantitative evaluation of brain T2 weighted images acquired by adjusting only NEX. To evaluate the noise level and similarity of the acquired image, signal to noise ratio (SNR), contrast to noise ratio (CNR), root mean square error (RMSE) and peak signal to noise ratio (PSNR) were calculated. As a result, both noise level and similarity evaluation factors showed improved values as NEX increased, while the increasing width gradually decreased. In conclusion, we demonstrated that an appropriate NEX setting is important because an excessively large NEX does not affect image characteristics improvement and cause motion artifacts due to a long scan.

• Journal of the Korean GEO-environmental Society
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• v.24 no.2
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• pp.5-12
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• 2023

In this study, the amount of heaving soil and the heave characteristics of the heaving soil generated at the actual site were quantitatively analyzed through DCM laboratory test construction. By reproducing a series of construction processes of the DCM method in a large-scale soil tank close to the actual site, the amount of heaving soil was predicted and the elevation characteristics such as elevation, diffusion range, diffusion angle and amount of elevation of the heaving soil were evaluated. As a result of the laboratory test construction, the actual elevation in terms of similarity within the DCM improvement section is 0~8.18m, and an average of 3.50m is observed. The actual diffusion range of the heaving soil converted to the similarity ratio is distributed from 28.0 to 38.0m on the left and right sides of the improvement section. The total amount of heaving soil calculated by the SUFFER program based on the results of the laboratory test construction is 19,901m³. Compared with the injected slurry amount of 16,992m³, the amount of heave compared to the injected amount is analyzed as 85.4%. The diffusion angle of DCM heaving soil, which analyzed the results of DCM laboratory test construction with the SUFFER program, is measured to be 30.0~38.0° at a depth of 50.0m, and is evaluated as an average of 34.0°. On the other hand, based on the DCM laboratory test construction and the analysis results using the program performed in this study, the amount of heaving soil at the DCM depths of 40.0m and 60.0m is predicted.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.37-47
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• 2013

Recently, lots of research results on program comparison have been reported since the code theft become frequent as the increase of code mobility. This paper proposes a plagiarism detection method using class structures. The proposed method constructs a graph representing the referential relationship between the member variables and the methods. This relationship is shown as a bipartite graph and the test for graph isomorphism is applied on the set of graphs to measure the similarity of the programs. In order to measure the effectiveness of this method, an experiment was conducted on the test set, the set of Java source codes submitted as solutions for the programming assignments in Object-Oriented Programming course of Pusan National University in 2012. In order to evaluate the accuracy of the proposed method, the F-measure is compared to those of JPlag and Stigmata. According to the experimental result, the F-measure of the proposed method is higher than those of JPlag and Stigmata by 0.17 and 0.34, respectively.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.11a
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• pp.129-129
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• 2017

In planning and evaluating government R&D programs, one of the first steps is to understand the government's current R&D investment portfolio - which fields or topics the government is now investing in in R&D. Analysis methods of an investment portfolio of government R&D tend traditionally to rely on keyword searches or ad-hoc two-dimensional classifications. The main drawback of these approaches is their limited ability to account for the characteristics of the whole government investment in R&D and the role of individual R&D program in it, which tends to depend on the relationship with other programs. This paper suggests a new method for mapping and analyzing government investment in R&D using a combination of methods from natural language processing (NLP) and network analysis. The NLP enables us to build a network of government R&D programs whose links are defined as similarity in R&D topics. Then methods from network analysis show the characteristics of government investment in R&D, including major investment fields, unexplored topics, and key R&D programs which play a role like a hub or a bridge in the network of R&D programs, which are difficult to be identified by conventional methods. These insights can be utilized in planning a new R&D program, in reviewing its proposal, or in evaluating the performance of R&D programs. The utilized (filtered) Korean text corpus consists of hundreds of R&D program descriptions in the budget requests for fiscal year 2017 submitted by government departments to the Korean Ministry of Strategy and Finance.