• 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 Korean Society of Transportation
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• v.34 no.5
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• pp.409-420
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• 2016

Korea is expected to enter 'Super Aged Society' in 2026. However, as walking is the very basic human right of mobility, securing safe and convenient moving of elderly people comprising the majority of transportation vulnerable is thought to be the most basic welfare, which can be easily neglected. From this perspectives, this study provides the walking characteristics of elderly people to be used in design of pedestrian facilities. The analysis of the measurements using Motion Analysis Systems shows that all walking factors of elderly people is 75% level of the younger group. Elderly group shows slower movement, reduced shoulder movement and increased ankle movement compared to the others. Also, foots are risen less and ground repulsive force is increased. Cluster analysis shows that the group of the elderly shows high variability inside the group, and 2 or 3 clusters can be formed with factors of Walking, Balance and Muscles. These walking characteristics can be used in designing pedestrian road, slope and step height of roadway facilities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1458-1467
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• 2010

Recently, imitation and infringement rights of an intellectual property are being recognized as impediments to nation's industrial growth. To prevent the huge loss which comes from theses impediments, many researchers are studying protection and efficient management of an intellectual property in various ways. Especially, the prediction of patent registration is very important part to protect and assert intellectual property rights. In this study, we propose the patent document analysis method by using text mining to predict whether the patent is registered or rejected. In the first instance, the proposed method builds the database by using the word frequencies of the rejected patent documents. And comparing the builded database with another patent documents draws the similarity value between each patent document and the database. In this study, we used k-means which is partitioning clustering algorithm to select criteria value of patent rejection. In result, we found conclusion that some patent which similar to rejected patent have strong possibility of rejection. We used U.S.A patent documents about bluetooth technology, solar battery technology and display technology for experiment data.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.6
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• pp.89-98
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• 2017

The dynamic entrepreneurial activities of small businesses or individual entrepreneurs seeking to enter the global market based on innovative ideas and challenging spirit in the modern society, which is trending in entrepreneurial capitalism according to the times, Leading to new growth engines. In order to promote the establishment of universities in Korea, the government has been working on 'Five-Year Plan for University Entrepreneurship Education(2013-2017)', 'Efficiency of Government Start-up Support in 2015', and 'Five-Year Basic Plan for Activation of Industry-University Cooperation(2016-2020)'. However, there are still practical limitations in spite of the efforts made by universities and research institutes to revitalize start-ups. As a way to overcome these limitations, this study aims to systematize the entrepreneurship education of the university, and examines the role of changing universities and theory of clusters and the entrepreneurship education. In addition, we will look at the factors of creative university culture centering on the representative cases of the Innovation University in US, and present a conceptual framework for cluster-based entrepreneurship education for the purpose of 'successful entrepreneurship' which is different from 'start-up success'. The conceptual framework of cluster-based entrepreneurship education is based on the establishment of 'Integrated Entrepreneurship Education Platform' to revitalize start-ups centered on university technology. At the same time, this framework focuses on the three factors of talent, technology, and culture based on the relevant theories and examples, and emphasizes the clustering of entrepreneurial resources, entrepreneurial policies and leadership that should be involved in entrepreneurship education.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.590-592
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• 2018

Taxis that are illegally parked on the road to catch customer can cause traffic congestion and sometimes cause traffic accidents. Stop position of taxis is determined by the long term experience of taxi drivers. In this study, We provide information to taxi drivers and customer who visit in first time through finding stop position of taxis by time. To do this, we used the Internet of Vehicle (IoV) data collected from sensors installed in 40 taxis. Previous studies attempted by forming a cluster around a taxi. Since this method is centered on a taxi, the position of the cluster changes depending on the location of the taxi. In this study, we use a road segmentation algorithm to solve these problems. Unlike the previous studies, since the cluster is formed around the road, the position of the cluster is fixed and it is not affected by the number of taxis, so it is possible to grasp the stop position in real time. The road segmentation is made up of 30m units, and map the taxi location data divided into hourly, weekday, and weekend to the nearest point. As a result of the mapping, it was difficult to see a big difference in the time of week because there were few taxis to operate on weekends, but in case of weekdays, the difference of stop position between the commute time zone and the night time zone was confirmed. The results of this study suggest that it will be possible to propose the prevention of taxi illegally driving taxi and the location of the taxi stand.

• Trans-
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• v.15
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• pp.1-24
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• 2023

This study examines the application of data visualization technology using a clustered data algorithm called 'Tamed Cloud' to virtual spaces and seeks the possibility of implementing it in various types of realistic exhibition contents. To this end, we first attempt to classify virtual reality (VR) exhibition contents starting with COVID-19, and summarize technologies applied. Also, various realistic exhibition contents provide visitors with an opportunity to appreciate the artworks through online and virtual exhibitions. In this trend, virtual reality and augmented reality (AR) technologies have been introduced, allowing visitors to enjoy the artwork more immersively, and the possibility of realistic exhibition content with interaction between the artwork and the user is also being demonstrated. Based on this background, this study examines the history of exhibition contents by dividing them before and after the advent of virtual reality technology, and examines how the clustered algorithm technology called Tamed Cloud was applied to virtual space and implemented as a realistic exhibition content in <70mK> project. By synthesizing all of this, we propose a convergence method of data visualization, virtual reality, and realistic content, and propose it as a new alternative to realistic exhibition content in virtual space.

• Animal Bioscience
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• v.37 no.7
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• pp.1213-1224
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• 2024

Objective: Enterotypes (ETs) are the clustering of gut microbial community structures, which could serve as indicators of growth performance and carcass traits. However, ETs have been sparsely investigated in waterfowl. The objective of this study was to identify the ileal ETs and explore the correlation of the ETs with growth performance and carcass traits in Muscovy ducks. Methods: A total of 200 Muscovy ducks were randomly selected from a population of 5,000 ducks at 70-day old, weighed and slaughtered. The growth performance and carcass traits, including body weight, dressed weight and evidenced weight, dressed percentage, percentage of apparent yield, breast muscle weight, leg muscle weight, percentage of leg muscle and percentage of breast muscle, were determined. The contents of ileum were collected for the isolation of DNA and 16S rRNA gene sequencing. The ETs were identified based on the 16S rRNA gene sequencing data and the correlation of the ETs with growth performance and carcass traits was performed by Spearman correlation analysis. Results: Three ETs (ET1, ET2, and ET3) were observed in the ileal microbiota of Muscovy ducks with significant differences in number of features and α-diversity among these ETs (p<0.05). Streptococcus, Candida Arthritis, and Bacteroidetes were the presentative genus in ET1 to ET3, respectively. Correlation analysis revealed that Lactococcus and Bradyrhizobium were significantly correlated with percentage of eviscerated yield and leg muscle weight (p<0.05) while ETs were found to have a close association with percentage of eviscerated yield, leg muscle weight, and percentage of leg muscle in Muscovy ducks. However, the growth performance of ducks with different ETs did not show significant difference (p>0.05). Lactococcus were found to be significantly correlated with leg muscle weight, dressed weight, and percentage of eviscerated yield. Conclusion: Our findings revealed a substantial variation in carcass traits associated with ETs in Muscovy ducks. It is implied that ETs might have the potential to serve as a valuable biomarker for assessing duck carcass traits. It would provide novel insights into the interaction of gut microbiota with growth performance and carcass traits of ducks.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.45-67
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• 2017

According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.467-475
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• 2014

With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. A pathway is the biological deep knowledge that represents the relations of dynamics and interaction among proteins, genes and cells by a network. A pathway is wildly being used as an important part of a bio-medical big-data analysis. However, a pathway analysis requires a lot of time and effort because a pathway is very diverse and high volume. Also, multidimensional analysis systems for various pathways are nonexistent even now. In this paper, we proposed a pathway analysis system that collects user interest pathways from KEGG pathway database that supports the most widely used pathways, constructs a network based on a hierarchy structure of pathways and analyzes the relations of dynamics and interaction among pathways by clustering and selecting core pathways from the network. Finally, to verify the superiority of our pathway analysis system, we evaluate the performance of our system in various experiments.

• Horticultural Science & Technology
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• v.28 no.4
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• pp.664-671
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• 2010

A genetic linkage map was constructed using 188 $F_9$ RILs derived from a cross between $Solanum$ $lycopersicum$ H7996 (resistant to bacterial wilt) and $S.$ $pimpinellifolium$ WVa700 (highly susceptible to bacterial wilt). The map consisted of 361 markers including 260 DArTs, 74 AFLPs, 4 RFLPs, 1 SNP, and 22 SSRs. The resulting linkage map was comprised of 13 linkage groups covering 2042.7 cM. The genetic linkage map had an average map distance between markers of 5.7 cM, with an average DArT marker density of 1/7.9 cM. Based on the distribution of anchor SSR markers, 11 linkage groups were assigned to 10 chromosomes of tomato except chromosomes 5 and 12. The DArT markers were distributed across the genome in a similar way as other markers and showed the highest frequency of clustering (38.8%) at ${\leq}$ 0.5 cM intervals between adjacent markers, which is 3 times higher than AFLPs (13.5%). The present study is the first utilization of DArT markers in tomato linkage map construction.