• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.477-484
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• 2016

Small industrial appliances such as fan, audio, electric rice cooker mostly consist of ABS, PP, PS materials. In colored plastics, it is possible to classify by near infrared(NIR) spectroscopy, while in black plastics, it is very difficult to classify black plastic because of the characteristic of black material that absorbs the light. So the RBFNNs pattern classifier is introduced for sorting electrical and electronic waste plastics through LIBS(Laser Induced Breakdown Spectroscopy) spectrometer. At the preprocessing part, PCA(Principle Component Analysis), as a kind of dimension reduction algorithms, is used to improve processing speed as well as to extract the effective data characteristics. In the condition part, FCM(Fuzzy C-Means) clustering is exploited. In the conclusion part, the coefficients of linear function of being polynomial type are used as connection weights. PSO and 5-fold cross validation are used to improve the reliability of performance as well as to enhance classification rate. The performance of the proposed classifier is described based on both optimization and no optimization.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.15-22
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• 2020

The 4th industrial revolution and the rapid change in the data environment revealed technical limitations in the existing relational database(RDB). As a new analysis method for unstructured data in all fields such as IDC/finance/insurance, interest in graph database(GDB) technology is increasing. The graph database is an efficient technique for expressing interlocked data and analyzing associations in a wide range of networks. This study extended the existing RDB to the GDB model and applied machine learning algorithms (pattern recognition, clustering, path distance, core extraction) to detect new abnormal signs. As a result of the performance analysis, it was confirmed that the performance of abnormal behavior(about 180 times or more) was greatly improved, and that it was possible to extract an abnormal symptom pattern after 5 steps that could not be analyzed by RDB.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.163-167
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• 2003

This paper investigates the lifestyles in Korean market. We will classify the groups using cluster analysis, and exploit the characteristics of innovators. These groups can be verified by multiple comparisons. This research is accomplished by sample survey between June 92003 and June 27 2003. Korean market for innovation can be classified into four groups such as innovators, early adopters, late majority, and laggards, which are similar to Rodger's classification. The ratios of four groups are 11%, 24.4%, 48.9%, 15.7% respectively. innovators, and late majority are heavy groups in that early adopter group is omitted on the contrary. Whereas innovators have a tendency to adopt the innovation quickly, rest groups have resistance for innovations and adopt slowly. The brief demographic characteristics of innovators are that the ratio of students is 44.44%, the ratio of single is 69.44%, the age between 15 and 25 is 56.95%, and the salary is relatively low compared with other cluster. The summary of lifestyle of innovators is that they are active, want to do worldwide business, want to have good relationship with high society, want to know the information of innovations, etc.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.15-40
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• 2020

Due to the explosive growth of mobile application services, categorizing mobile application services is in need in practice from both customers' and developers' perspectives. Despite the fact, however, there have been limited studies regarding systematic categorization of mobile application services. In response, this study proposed a method for categorizing mobile application services, and suggested a service taxonomy based on the network clustering results. Total of 1,607 mobile healthcare services are collected through the Google Play store. The network analysis is conducted based on the similarity of descriptions in each application service. Modularity detection analysis is conducted to detects communities in the network, and service taxonomy is derived based on each cluster. This study is expected to provide a systematic approach to the service categorization, which is helpful to both customers who want to navigate mobile application service in a systematic manner and developers who desire to analyze the trend of mobile application services.

• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.120-129
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• 2016

This study aimed to develop an optimal sizing system and a draping pattern for hip protector based on an analysis of anthropometric characteristics of Korean older women. A hip protector is a specialized form of pants or underwear containing pads along the outside of each hip. The 3D body scan data of Korean older women were analyzed to identify their anthropometric characteristics and a four-size system with 93% of population accommodation was developed by clustering analysis based on key dimensions derived from factor analysis. The sizing system consists of small/short, large/short, small/tall, and large/tall. A 3D physical model and hip pads were fabricated; then, a hip protector was draped on the 3D model and hip pads. The sizing system of hip protector was analyzed in terms of size and shape and a draping pattern was compared on back center, back side, front side, front center and pad. Lastly, the pattern deformation and clothing pressure were analyzed using the virtual clothing system CLO. Virtual system have disadvantage of not to suggest the objective value. In the future research the wearing comfort and impact absorption of the hip protector needs to be tested and then a hip protector design will be finalized by considering the hip protector's size, material, comfort testing results, aesthetic appeal, protection effectiveness, and practical utility of everyday use.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.155-168
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• 2018

In this study, we studied the directional pattern of entering the intersection from the intersection upstream link prior to predicting short future (such as 5 or 10 minutes) intersection direction traffic volume on the interrupted flow, and examined the possibility of traffic volume prediction using traffic assignment model. The analysis method of this study is to investigate the similarity of patterns by performing cluster analysis with the ratio of traffic volume by intersection direction divided by 2 hours using taxi DTG (Digital Tachograph) data (1 week). Also, for linking with the result of the traffic assignment model, this study compares the impact area of 5 minutes or 10 minutes from the center of the intersection with the analysis result of taxi DTG data. To do this, we have developed an algorithm to set the impact area of intersection, using the taxi DTG data and traffic assignment model. As a result of the analysis, the intersection entry pattern of the taxi is grouped into 12, and the Cubic Clustering Criterion indicating the confidence level of clustering is 6.92. As a result of correlation analysis with the impact area of the traffic assignment model, the correlation coefficient for the impact area of 5 minutes was analyzed as 0.86, and significant results were obtained. However, it was analyzed that the correlation coefficient is slightly lowered to 0.69 in the impact area of 10 minutes from the center of the intersection, but this was due to insufficient accuracy of O/D (Origin/Destination) travel and network data. In future, if accuracy of traffic network and accuracy of O/D traffic by time are improved, it is expected that it will be able to utilize traffic volume data calculated from traffic assignment model when controlling traffic signals at intersections.

• Mycobiology
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• v.47 no.4
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• pp.527-532
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• 2019

We designed 170 new simple sequence repeat (SSR) markers based on the whole-genome sequence data of button mushroom (Agaricus bisporus), and selected 121 polymorphic markers. A total of 121 polymorphic markers, the average major allele frequency (M_AF) and the average number of alleles (N_A) were 0.50 and 5.47, respectively. The average number of genotypes (N_G), observed heterozygosity (H_O), expected heterozygosity (H_E), and polymorphic information content (PIC) were 6.177, 0.227, 0.619, and 0.569, respectively. Pearson's correlation coefficient showed that M_AF was negatively correlated with N_G (-0.683), N_A (-0.600), H_O (-0.584), and PIC (-0.941). N_G, N_A, H_O, and PIC were positively correlated with other polymorphic parameters except for M_AF. UPGMA clustering showed that 26 A. bisporus accessions were classified into 3 groups, and each accession was differentiated. The 121 SSR markers should facilitate the use of molecular markers in button mushroom breeding and genetic studies.

• Journal of recreation and landscape
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• v.12 no.4
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• pp.45-58
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• 2018

Place memory is a new way of seeing as a new concept of cultural landscape research. Various research works and discussions have recently spread in landscape studies. In particular, the, which is visible and material, is a medium in which collective memory is embedded in place memory. The purpose of this study is to extract places of memory from the collective memory of residents of Janghang, Korea, and to visualize it through semantic relations. For this purpose, semi-standardized interviews (34 persons) were conducted with residents, and frequency analysis and semantic network analysis were used. As a result, the interviewees recalled only 127 places in Janghang that existed between 1920 and 2010. Locals remember the city based on places of memory. This means that the city could be illustrated according to specific places that are frequently mentioned. For instance, the top 25 places (top 20%) explain 65.6% of all the places in the city, and the top 39 places (top 30.8%) could describe 78.7% of the places. Some places are referred to more frequently when they are in the city's symbolic landscape, and the city's identity is projected on them. Some places were mentioned only infrequently but were nevertheless very important places by which to understand Janghang. These places of memory have not appeared in the documentary records before, which shows the value of the collective memory of the locals and the effectiveness of the interviewing method. In the clustering of the semantic network, six groups of places appeared. The local residents remembered the modern industrial city and recalled it in connection with the sites of daily life. This shows the possibility of looking not only at public memory and famous heritage as a macro history but also at daily life and meaningful places as a micro history about locals. This study has significance as an initial research that identified and visualized places of memory from the perspective of local residents. Such an approach could be useful in the study of everyday life and the conservation of modern heritage.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.473-484
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• 2017

This study analyzed collaborative R&D projects funded by the Korean government from 2013-2015. For this analysis, input and output variables of projects were considered, and a combination of those variables was itemized. The output-oriented variable return to scale (VRS) model extended from the DEA methodology was adopted to evaluate the cooperation efficiency of the types of R&D collaboration, which were classified according to the project leader's organizations. In addition, hierarchical cluster analysis was conducted using the efficiency results of the scientific, technical, and economical outcome models. The results showed that cooperation efficiency between large companies and public research institutions was relatively high. Conversely, cooperation among medium-sized companies, small businesses and universities was particularly inefficient. The clustering results demonstrated the various strengths and weaknesses of the types depending on publications, patents, technical loyalties and the number of commercialization. In conclusion, this study suggests differentiated investment portfolios and strategies based on the efficiency results of diverse cooperation types among industries, universities and public research institutions.