It is essential in various application areas of data mining and bioinformatics to effectively retrieve the occurrences of interesting patterns from sequence databases. For example, let's consider a network event management system that records the types and timestamp values of events occurred in a specific network component(ex. router). The typical query to find out the temporal casual relationships among the network events is as fellows: 'Find all occurrences of CiscoDCDLinkUp that are fellowed by MLMStatusUP that are subsequently followed by TCPConnectionClose, under the constraint that the interval between the first two events is not larger than 20 seconds, and the interval between the first and third events is not larger than 40 secondsTCPConnectionClose. This paper proposes an indexing method that enables to efficiently answer such a query. Unlike the previous methods that rely on inefficient sequential scan methods or data structures not easily supported by DBMSs, the proposed method uses a multi-dimensional spatial index, which is proven to be efficient both in storage and search, to find the answers quickly without false dismissals. Given a sliding window W, the input to a multi-dimensional spatial index is a n-dimensional vector whose i-th element is the interval between the first event of W and the first occurrence of the event type Ei in W. Here, n is the number of event types that can be occurred in the system of interest. The problem of‘dimensionality curse’may happen when n is large. Therefore, we use the dimension selection or event type grouping to avoid this problem. The experimental results reveal that our proposed technique can be a few orders of magnitude faster than the sequential scan and ISO-Depth index methods.hods.
Journal of the Korean Institute of Traditional Landscape Architecture
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제30권4호
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pp.14-22
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2012
The position, size and landscape of the former Donam SeoWon as well as the physical organization of the old site, are studied to extract data for the enhancement of the authenticity of Donam SeoWon since its registration as a world heritage site. The results are as follows. The 'Donam(豚巖)' encaved rock, the tombstone of teacher Sagye(沙溪), Kimjipsadang(金集祠堂), the head of the Gwangsan Kim family, the Sagye stream in front of them, and the Gyeryong and Daedun mountains in the distance are united in the former Donam SeoWon as landscape elements that clearly show the characteristics of the former site, which was called 'Donam-Wollim(豚巖園林).' Moreover Yangseongdangsipyoung(養性堂十詠), adds the garden elements of a medical herb field, twins pond, a bamboo forest, a school, and a peach field. On this site, one can also engage in activities that are related to the land and are closely related to Neo-Confucianism such as fish watching, conferencing, visit in seclusion(訪隱), looking for monks, and overseeing farming. The former site facing east is assumed to have Sau(祠宇) - Eungdodang(凝道堂) - Ipdeokmum(入德門) - Sanangru(山仰樓: estimated). Jeonsacheong seems to have been located to the left of the Sau area, Yangseongdang, which contained upper and lower twin lotus ponds, on the right and was surrounded by various plants. As it has been used as a lecture hall for the past 250 years, the former Donam SeoWon, located 1.8km away from the current area, must be preserved, and the landscape should be formed to establish the authenticity of Donam SeoWon.
The rear garden in Donggwol Palace which shared with the Changdeok Palace and the Changgyeong Palace is the salient places of technology and idea reflected the phases of the times of the Joseon Dynasty, so it is certainly one of the best Korean garden cultures. The rear garden in Donggwol which was not only the secret garden for the rest of royal family but also used as symbolic places for the various ceremonies and training its human resources has been considerably destroyed through the period of Japanese colonial rule. Thus the rear garden areas at north of Changkyung Palace were entirely transformed and a few territory from Juhabru(宙合樓) to Ongnyucheon(玉流川) keep up its surviving as the rear garden. The area of Jondeokjeong(尊德亭) which become subject on this studies from among these was constructed as flower garden after development of Ongnyucheon. The areas of Simchujeong(深秋亭), Cheoknoedang(滌惱堂), Pyemwoosa(?愚?), Mangchunjeong(望春亭), Chunhyagak(天香閣), Chungsimjeong(淸心亭) around Jondeokjeong, were situated among the beautiful scenery with the flowers and ponds. But there are only Jondeokjeong and Pyemwoosa at this moment, and the other pavilions was destroyed and transformed. For these reasons, in this studies, the formative purposes were investigated through analysing water elements, planting, ornaments and so on. According to these reasons, historical records and realities of garden construction of five pavilions : Simchujeong, Mangchunjeong, Cheoknoedang, Chunhyagak, Chungyeongak(淸燕閣) were considered to give authenticity to the restoration and reorganization as well as to accumulate basic knowledge about the conservation of environment surrounded garden architectures. These pavilions appeared at Gunggwolgi(宮闕志) and Joseonwangzosilok(朝鮮王朝實), but their names were not appeared at Donggwoldo(東闕圖). So they were ascertained through all of literatures on Donggwol Palace. Cheoknoedang and Simchujeong among these buildings could be found out as the existed buildings and the uncertain building at the northwest of Jondeokjeong was estimated as the name to Chunhyagak or Mangchunjeong. And the hypothesis that the wall surrounding Taichungmoon(太淸門) should be belong to Chungyeongak was supported. In addition, the area which did not known in connection with name and use on northeast at the Changdeok Palace, and had regarded as an impasses in the studies of Donggwoldo and the rear garden in Donggwol Palace, but the historical records of using by Yeonsangun(燕山君) and Sukjong(肅宗) were discovered at this study. And it could be uncovered that the obscure spatial space was a separate house only for king and he enjoyed play there unnoticing to others belong to palace.
Jo, Hyun-Woo;Chi, Kwang-Hoon;Cha, Sungeun;Kim, Eunji;Lee, Woo-Kyun
Korean Journal of Remote Sensing
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제33권5_1호
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pp.469-480
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2017
This study aims to understand the relationship between lineaments and epicenters in Geochang region, Gyungsangnam-do, South Korea. An instrumental observation of earthquakes has been started by Korea Meteorological Administration (KMA) since 1978 and there were 6 earthquakes with magnitude ranging 2 to 2.5 in Geochang region from 1978 to 2016. Lineaments were extracted from LANDSAT 8 satellite image and shaded relief map displayed in 3-dimension using Digital Elevation Model (DEM). Then, lineament density was statistically examined by hotspot analysis. Hexagonal grids were generated to perform the analysis because hexagonal pattern expresses lineaments with less discontinuity than square girds, and the size of the grid was selected to minimize a variance of lineament density. Since hotspot analysis measures the extent of clustering with Z score, Z scores computed with lineaments' frequency ($L_f$), length ($L_d$), and intersection ($L_t$) were used to find lineament clusters in the density map. Furthermore, the Z scores were extracted from the epicenters and examined to see the relevance of each density elements to epicenters. As a result, 15 among 18 densities,recorded as 3 elements in 6 epicenters, were higher than 1.65 which is 95% of the standard normal distribution. This indicates that epicenters coincide with high density area. Especially, $L_f$ and $L_t$ had a significant relationship with epicenter, being located in upper 95% of the standard normal distribution, except for one epicenter in $L_t$. This study can be used to identify potential seismic zones by improving the accuracy of expressing lineaments' spatial distribution and analyzing relationship between lineament density and epicenter. However, additional studies in wider study area with more epicenters are recommended to promote the results.
Kim, Dong-Seok;Kim, Seong-Hwan;Shim, Dong-Oh;Yoo, Hee-Jae
The Korean Journal of Nuclear Medicine Technology
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제15권1호
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pp.17-24
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2011
Purpose: Presently in the nuclear medicine field, the high-speed image reconstruction algorithm like the OSEM algorithm is widely used as the alternative of the filtered back projection method due to the rapid development and application of the digital computer. There is no to relate and if it applies the optimal parameter be clearly determined. In this research, the quality change of the Jaszczak phantom experiment and brain SPECT patient data according to the iteration times and subset number change try to be been put through and analyzed in 3D OSEM reconstruction method of applying 3D beam modeling. Materials and Methods: Patient data from August, 2010 studied and analyzed against 5 patients implementing the brain SPECT until september, 2010 in the nuclear medicine department of ASAN medical center. The phantom image used the mixed Jaszczak phantom equally and obtained the water and 99mTc (500 MBq) in the dual head gamma camera Symbia T2 of Siemens. When reconstructing each image altogether with patient data and phantom data, we changed iteration number as 1, 4, 8, 12, 24 and 30 times and subset number as 2, 4, 8, 16 and 32 times. We reconstructed in reconstructed each image, the variation coefficient for guessing about noise of images and image contrast, FWHM were produced and compared. Results: In patients and phantom experiment data, a contrast and spatial resolution of an image showed the tendency to increase linearly altogether according to the increment of the iteration times and subset number but the variation coefficient did not show the tendency to be improved according to the increase of two parameters. In the comparison according to the scan time, the image contrast and FWHM showed altogether the result of being linearly improved according to the iteration times and subset number increase in projection per 10, 20 and 30 second image but the variation coefficient did not show the tendency to be improved. Conclusion: The linear relationship of the image contrast improved in 3D OSEM reconstruction method image of applying 3D beam modeling through this experiment like the existing 1D and 2D OSEM reconfiguration method according to the iteration times and subset number increase could be confirmed. However, this is simple phantom experiment and the result of obtaining by the some patients limited range and the various variables can be existed. So for generalizing this based on this results of this experiment, there is the excessiveness and the evaluation about 3D OSEM reconfiguration method should be additionally made through experiments after this.
Lee, Jun Heui;Baek, Sung Ha;Lee, Soon Jo;Bae, Hae Young
Spatial Information Research
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제20권5호
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pp.99-109
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2012
Recently, due to the growth of social media and spread of smart-phone, the amount of data has considerably increased by full use of SNS (Social Network Service). According to it, the Big Data concept is come up and many researchers are seeking solutions to make the best use of big data. To maximize the creative value of the big data held by many companies, it is required to combine them with existing data. The physical and theoretical storage structures of data sources are so different that a system which can integrate and manage them is needed. In order to process big data, MapReduce is developed as a system which has advantages over processing data fast by distributed processing. However, it is difficult to construct and store a system for all key words. Due to the process of storage and search, it is to some extent difficult to do real-time processing. And it makes extra expenses to process complex event without structure of processing different data. In order to solve this problem, the existing Complex Event Processing System is supposed to be used. When it comes to complex event processing system, it gets data from different sources and combines them with each other to make it possible to do complex event processing that is useful for real-time processing specially in stream data. Nevertheless, unstructured data based on text of SNS and internet articles is managed as text type and there is a need to compare strings every time the query processing should be done. And it results in poor performance. Therefore, we try to make it possible to manage unstructured data and do query process fast in complex event processing system. And we extend the data complex function for giving theoretical schema of string. It is completed by changing the string key word into integer type with filtering which uses keyword set. In addition, by using the Complex Event Processing System and processing stream data at real-time of in-memory, we try to reduce the time of reading the query processing after it is stored in the disk.
The Yan mountain area of the northern part of Hebei province and its local neighbor area is categorized main-distribution area of the northern bronze culture of the Eastern Zhou period(770bc~221bc). Recently, it was discovered the concrete character of the culture by a large scale excavation of the Yuhuangmiao cemetery at Jundu mountain. In the chinese scholarship, the cultural character of this area has established the independent cultural type that is distinguished from the Bronze culture of existing. In this paper, I have as a target of analysis remains relate to the Yuhuangmiao culture of the mountain area of northern Hebei in the Eastern Zhou period. And I would like to judge about diverse infuluential relationships of the character of the Yuhuangmiao curture and the Bronze culture, especially burials, burial customs and the characters of the excavated article. In particular, diverse infuluential relationships of the upper Xiajiadian culture Ordos bronze culture and The Central Plains cultural from The Yan state have a important meaning to understand about the character of the Yuhuangmiao culture and the beginning development process. Ultimately, it is peculiar characters of the Yuhuangmiao culture that a shaft gave with stone compartment protecting a coffin as a symbolic form, mask-burial customs such as mainly burials of the living with the dead dogs, a drum shaped jar, a tripod jar with two handles, a short bronze sword with circle hilt, Central Plains cultural bronze containers, bronze halberd and horse-shaped accessories of cartage horse trapping are distinguished from a local neighbor, the bronze culture from northern. The territory of time-space of The Yuhuangmiao culture can be dominately recognized bewteen the upper Xiajiadian culture and Ordos bronze culture. It is the Yan culture after the middle Warring States Period considering with the peculiar chacters which reflected by burials and bural customs and diverse infuluential relationships with peripheral cultures.
Thanks to the growth of computing power and the recent development of data analytics, researchers have started to work on the data produced by users through the Internet or social media. This study is in line with these recent research trends and attempts to adopt data analytical techniques. We focus on the impact of "internal marketing" factors on firm performance, which is typically studied through survey methodologies. We looked into the job review platform Jobplanet (www.jobplanet.co.kr), which is a website where employees and former employees anonymously review companies and their management. With web crawling processes, we collected over 40K data points and performed morphological analysis to classify employees' reviews for internal marketing data. We then implemented econometric analysis to see the relationship between internal marketing and market capitalization. Contrary to the findings of extant survey studies, internal marketing is positively related to a firm's market capitalization only within a limited area. In most of the areas, the relationships are negative. Particularly, female-friendly environment and human resource development (HRD) are the areas exhibiting positive relations with market capitalization in the manufacturing industry. In the service industry, most of the areas, such as employ welfare and work-life balance, are negatively related with market capitalization. When firm size is small (or the history is short), female-friendly environment positively affect firm performance. On the contrary, when firm size is big (or the history is long), most of the internal marketing factors are either negative or insignificant. We explain the theoretical contributions and managerial implications with these results.
With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.
Zhao, Bi-Cheng;Rosli, Ahmad Nurzid;Jang, Chol-Hee;Lee, Kee-Sung;Jo, Geun-Sik
Journal of Intelligence and Information Systems
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제18권1호
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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.
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