• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.171-183
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• 2012

In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.1-21
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• 2012

In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Korean Journal of Plant Taxonomy
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• v.42 no.3
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• pp.215-221
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• 2012

Five Korean Calanthe species, C. discolor, C. bicolor, C. sieboldii, C. reflexa, and C. aristulifera, were studied using amplified fragment length polymorphism (AFLP) to assess their taxonomic and genetic relationships. Sixteen accessions belonging to five native Calanthe spp. and mutants with yellow tepal and white lip (YW mutants) were studied. We identified 50 putative markers using AFLP analysis. The results of AMOVA showed that genetic variance was higher between species than within species. Genetic dissimilarity when compared with the rest of the species was the lowest for individuals of the YW mutants and the highest for individuals of C. reflexa. The mutants clustered outside the major group. Calanthe bicolor clustered with C. discolor, suggesting that its genetic composition is closer to that of C. discolor. Though it is suggested to have originated as a result of natural hybridization between C. sieboldii and C. discolor, introgression is likely to have occurred in the direction of C. discolor based on the data of molecular marker, clustering and genetic dissimilarity. Calanthe reflexa and C. aristulifera were genetically the most diverse of the species studied. In conclusion, the results showed that there is genetic diversity in Korean Calanthe species, that C. bicolor introgressed in the direction of C. discolor and that the YW mutants are genetically closer to C. sieboldii.

• Horticultural Science & Technology
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• v.31 no.3
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• pp.344-351
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• 2013

Microsatellite is one of the most suitable marker for cultivar identification as it has great discrimination power for cultivars with narrow genetic variation. The polymorphism level between 358 microsatellite primer pairs and 11 commercial cucumber cultivars was investigated. Thirty-one primer pairs showed high polymorphism within cucumber cultivars with different fruit types. These markers were applied for the constructing DNA profile data base of 110 commercial cucumber cultivars through multiplex PCR and fluorescence based automatic detection system. A total of 139 polymorphic amplified fragments were obtained by using 31 microsatellite markers. The average of PIC value was 0.610 ranging from 0.253 to 0.873. One hundred and thirty nine microsatellite loci were used to calculate Jaccard's distance coefficients for UPGMA cluster analysis. A clustering group of varieties, based on the results of microsatellite analysis, were categorized into plant shape and fruit type. Almost the cultivars were discriminated by marker genotypes. This information may be useful to compare through genetic relationship analysis between existing variety and candidate varieties in distinctive tests and protection of plant breeders' intellectual property rights through variety identification.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.713-723
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• 2017

Since the panoramic image can overcome the limitation of the viewing angle of the camera and have a wide field of view, it has been studied effectively in the fields of computer vision and stereo camera. In order to generate a panoramic image, stitching images taken by a plurality of general cameras instead of using a wide-angle camera, which is distorted, is widely used because it can reduce image distortion. The image stitching technique creates descriptors of feature points extracted from multiple images, compares the similarities of feature points, and links them together into one image. Each feature point has several hundreds of dimensions of information, and data processing time increases as more images are stitched. In particular, when a panorama is generated on the basis of an image photographed by a plurality of unspecified cameras with respect to an object, the extraction processing time of the overlapping feature points for similar images becomes longer. In this paper, we propose a preprocessing process to efficiently process stitching based on an image obtained from a number of unspecified cameras for one object or environment. In this way, the data processing time can be reduced by pre-grouping images based on camera sensor information and reducing the number of images to be stitched at one time. Later, stitching is done hierarchically to create one large panorama. Through the grouping preprocessing proposed in this paper, we confirmed that the stitching time for a large number of images is greatly reduced by experimental results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.459-467
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• 2014

The importance of fusion and association using established spatial information has increased gradually with the production and supply of various spatial data by public institutions. The generation of necessary spatial information without field investigation and additional surveying can reduce time, labor, and financial costs. However, the study of the integration of the newly introduced road name address map with the digital map is very insufficient. Even though the use of the road name address map is encouraged for public works related to spatial information, the digital map is still widely used because it is the national basic map. Therefore, in this study, building matching and update were performed to associate the digital map with the road name address map. After geometric calibration using the block-based ICP (Iterative Closest Point) method, multi-scale corresponding pair searching with hierarchical clustering was applied to detect the multi-type match. The accuracy assessment showed that the proposed method is more than 95% accurate and the matched building layer of the two maps is useful for the integrated application and fusion. In addition, the use of the road name address map, which carries the latest and most frequently renewed data, enables cost-effective updating of new buildings.

• The Journal of Internal Korean Medicine
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• v.30 no.3
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• pp.510-524
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• 2009

Objective : This study was designed to find the correlation between Sasang Constitution and heart rate variability(HRV). Method : There were 665 subjects (280 men and 385 women), between 39 and 72 years old. in a rural community. Sasang Constitution was diagnosed by a Sasang constitutional specialist using PSSC (Phonetic System for Sasang Constitution), face and tongue photo and checkup-list. A structured-questionnaire was used to assess the general characteristics. HRV was recorded using SA-2000 (medi-core). HRV was assessed by time domain and by frequency domain analysis. Metabolic syndrome was defined on the basis of clustering of risk factors, when three or more of the following cardiovascular risk factors were included : blood pressure, fasting blood sugar, triglyceride HDL-cholesterol, and abdominal obesity (waist). Because of the skewness of the data, logarithmic transformation was performed on the absolute units of the spectral components of HRV, and the resulting logarithmic values and normalized units were compared between the groups by a logistic regression. The 95% confidence interval (CI) of the odds ratio was used and calculated from the data laid out for a cross sectional study. Results : 1. Odds ratios of Taeeumin and Soeumin in female adults below 60 years old were significantly lower than that of Soyangin in LF norm and LF/HF ratio. Odds ratios of Taeeumin and Soeumin in female adults below 60 years old were significantly higher than that of Soyangin in HF norm. 2. There was no significant correlation between HRV and Sasang Constitution in female adults from 60 years old and over. 3. There was no significant correlation between HRV and Sasang Constitution in male adults. Conclusion : There is a statistically significant correlation between the HRV and Sasang Constitution. There is a tendency of increase in the sympathetic activity in Soyangin. There is a tendency of decrease in the parasympathetic activity in Taeeumin and Soeumin.

• Journal of Preventive Medicine and Public Health
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• v.33 no.3
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• pp.323-333
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• 2000

Objectives : Chronic HBsAg carriers are the principal source of infection for other susceptible people, and are themselves at high risk of developing serious liver diseases. In Korea, it has been estimated that 65-75% of the HBsAg positives remained as persistent carriers. Additionally, familial clustering of MBV infection has frequently been observed among carriers. Some would become progressive, chronic hepatitis patients, and others would not. The aim of this study was to evaluate the association between various factors, such as the duration of infection, type of virus, mutation of precore/core region in HBV, major histocompatibility class-I, and developing chronic liver diseases among familial HBV carriers. Methods : Chronic carrier status was identified by repeated serological tests for HBsAg at intervals of six months or more. A familial chronic carrier was defined when the disease was observed in a family member over two generations. Two families were recruited, among which a total of 20 chronic HBsAg carriers(11 carriers in No.1, and 9 in No.2 family) were identified. Data on the general characteristics and liver disease status were collected. Identification of the HBV-DNA was successful only for 13 subjects among the 20 carriers. Analysis of viral DNA in terms of subtype, pre-core and core region mutations was carried out. The type of major histocompatibility class-1 for the 13 subjects was also analysed. Results & Conclusions : Seven of 10 chronic HBV carriers of the 1st generation and one of 10 of the 2nd generation were clinical patients with chronic hepatitis, the others, three of the 1 st and nine of the 2nd generation, were asymptomatic carriers. This data indicates that the duration of HBV carriage is one of the major factors for disease severity. The subtype of HBsAg analysed using MBV-DNA identified in 13 carriers were adr, and the pattern of precore nonsense mutation in HBV-DNA was identical among family members, which meads that the same virus strains were transmitted between the family members. The association between the precore or core mutations in HBV-DNA and the disease severity was not observed. While it was suggested that a specific type of MHC class-I may be related to disease progression.

• Journal of Korean Neurosurgical Society
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• v.50 no.6
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• pp.486-491
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• 2011

Objective : Structural genetic variation, including copy-number variation (CNV), constitutes a substantial fraction of total genetic variability, and the importance of structural variants in modulating susceptibility is increasingly being recognized. CNV can change biological function and contribute to pathophysiological conditions of human disease. Its relationship with common, complex human disease in particular is not fully understood. Here, we searched the human genome to identify copy number variants that predispose to moya-moya type cerebrovascular disease. Methods : We retrospectively analyzed patients who had unilateral or bilateral steno-occlusive lesions at the cerebral artery from March, 2007, to September, 2009. For the 20 subjects, including patients with moyamoya type pathologies and three normal healthy controls, we divided the subjects into 4 groups : typical moyamoya (n=6), unilateral moyamoya (n=9), progression unilateral to typical moyamoya (n=2) and non-moyamoya (n=3). Fragmented DNA was hybridized on Human610Quad v1.0 DNA analysis BeadChips (Illumina). Data analysis was performed with GenomeStudio v2009.1, Genotyping 1.1.9, cnvPartition_v2.3.4 software. Overall call rates were more than 99.8%. Results : In total, 1258 CNVs were identified across the whole genome. The average number of CNV was 45.55 per subject (CNV region was 45.4). The gain/loss of CNV was 52/249, having 4.7 fold higher frequencies in loss calls. The total CNV size was 904,657,868, and average size was 993,038. The largest portion of CNVs (613 calls) were 1M-10M in length. Interestingly, significant association between unilateral moyamoya disease (MMD) and progression of unilateral to typical moyamoya was observed. Conclusion : Significant association between unilateral MMD and progression of unilateral to typical moyamoya was observed. The finding was confirmed again with clustering analysis. These data demonstrate that certain CNV associate with moyamoya-type cerebrovascular disease.