• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.101-107
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• 2014

With the development of online service, recent forms of databases have been changed from static database structures to dynamic stream database structures. Previous data mining techniques have been used as tools of decision making such as establishment of marketing strategies and DNA analyses. However, the capability to analyze real-time data more quickly is necessary in the recent interesting areas such as sensor network, robotics, and artificial intelligence. Landmark window-based frequent pattern mining, one of the stream mining approaches, performs mining operations with respect to parts of databases or each transaction of them, instead of all the data. In this paper, we analyze and evaluate the techniques of the well-known landmark window-based frequent pattern mining algorithms, called Lossy counting and hMiner. When Lossy counting mines frequent patterns from a set of new transactions, it performs union operations between the previous and current mining results. hMiner, which is a state-of-the-art algorithm based on the landmark window model, conducts mining operations whenever a new transaction occurs. Since hMiner extracts frequent patterns as soon as a new transaction is entered, we can obtain the latest mining results reflecting real-time information. For this reason, such algorithms are also called online mining approaches. We evaluate and compare the performance of the primitive algorithm, Lossy counting and the latest one, hMiner. As the criteria of our performance analysis, we first consider algorithms' total runtime and average processing time per transaction. In addition, to compare the efficiency of storage structures between them, their maximum memory usage is also evaluated. Lastly, we show how stably the two algorithms conduct their mining works with respect to the databases that feature gradually increasing items. With respect to the evaluation results of mining time and transaction processing, hMiner has higher speed than that of Lossy counting. Since hMiner stores candidate frequent patterns in a hash method, it can directly access candidate frequent patterns. Meanwhile, Lossy counting stores them in a lattice manner; thus, it has to search for multiple nodes in order to access the candidate frequent patterns. On the other hand, hMiner shows worse performance than that of Lossy counting in terms of maximum memory usage. hMiner should have all of the information for candidate frequent patterns to store them to hash's buckets, while Lossy counting stores them, reducing their information by using the lattice method. Since the storage of Lossy counting can share items concurrently included in multiple patterns, its memory usage is more efficient than that of hMiner. However, hMiner presents better efficiency than that of Lossy counting with respect to scalability evaluation due to the following reasons. If the number of items is increased, shared items are decreased in contrast; thereby, Lossy counting's memory efficiency is weakened. Furthermore, if the number of transactions becomes higher, its pruning effect becomes worse. From the experimental results, we can determine that the landmark window-based frequent pattern mining algorithms are suitable for real-time systems although they require a significant amount of memory. Hence, we need to improve their data structures more efficiently in order to utilize them additionally in resource-constrained environments such as WSN(Wireless sensor network).

• The Korean Journal of Nuclear Medicine
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• v.33 no.6
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• pp.484-492
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• 1999

Purpose: This study was to evaluate the clinical usefulness of $^{99m}Tc$-MDP bone scintigraphy for assessing vascular ingrowth into the ocular implants after enucleation or evisceration. Materials and Methods: Twenty-four patients (M:F=7:17, mean age: 36 years), who buried a coralline hydroxyapatite after uncomplicated enucleation or evisceration surgery were studied. Dynamic and static scintigraphy on the orbit fossa were obtained after injection of 740 MBq $^{99m}Tc$-MDP to evaluate the status of vascularization. The study was performed from the 3 to 33 weeks after surgery. According to the visual analysis, activity greater than nasal bridge was graded as 4, equal to the nasal bridge as 3, less than nasal bridge but greater than normal orbit as 2, greater than normal orbit but less than grade 2 as 1. Uptake ratio was also calculated by measuring the implants activity (H) and contralateral orbit activity (N). Grading score and uptake ratio were compared with clinical outcome of vascularization. Additionally, we also analyzed the vascularization status as time lapse between primary surgery and scintigraphic study and surgical methods. Results: Twenty-one patients who had bone scintigraphy at 11 weeks after surgery showed increased uptake above grade 2 and greater H/N ratio than 1.16. Of these, 19 patients who had drilling surgery for permanent peg application showed adequate bleeding during the procedure. The activity grade and uptake ratio were inversely correlated with vascular ingrowth. Higher than grade 2 or greater than 1.56 in H/N ratio seemed to be an indicator for better prognosis. Accomplishment of vascularization was not affected by the surgical way such as enucleation or evisceration. Conclusion: $^{99m}Tc$-MDP bone scintigraphy can be a useful method to evaluate the vascularized status of implants. Adequate time for $^{99m}Tc$-MDP bone scintigraphy may be 11-20 weeks after enucleation or evisceration.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.243-250
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• 2004

Monitoring is used to see if a real-time system provides a service on time. Generally, monitoring for real-time focuses on investigating the current status of a real-time system. To support a stable performance of a real-time system, it should have not only a function to see the current status of real-time process but also a function to predict executions of real-time processes, however. The legacy prediction model has some limitation to apply it to a real-time monitoring. First, it performs a static prediction after a real-time process finished. Second, it needs a statistical pre-analysis before a prediction. Third, transition probability and data about clustering is not based on the current data. We propose the execution prediction model based on learning algorithm to solve these problems and apply it to real-time monitoring. This model gets rid of unnecessary pre-processing and supports a precise prediction based on current data. In addition, this supports multi-level prediction by a trend analysis of past execution data. Most of all, We designed the model to support dynamic prediction which is performed within a real-time process' execution. The results from some experiments show that the judgment accuracy is greater than 80% if the size of a training set is set to over 10, and, in the case of the multi-level prediction, that the prediction difference of the multi-level prediction is minimized if the number of execution is bigger than the size of a training set. The execution prediction model proposed in this model has some limitation that the model used the most simplest learning algorithm and that it didn't consider the multi-regional space model managing CPU, memory and I/O data. The execution prediction model based on a learning algorithm proposed in this paper is used in some areas related to real-time monitoring and control.

• Journal of the Korean association of regional geographers
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• v.6 no.3
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• pp.117-138
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• 2000

This study is, from the view point of constructive social studies which is the foundation of the 7th curriculum, to explore whether there is any viable program and to investigate it by which students, using photo resources in social studies, can organize their knowledge in the way of self-directed thinking. The main results are as follows: If it is a principle of knowledge construction process of constructive social studies that individual construction (cognitive construction) develops into communal construction(social construction) and yet communal construction develops itself, interacting with individual construction, it will be meet the objectives of social studies. In social studies, photos are a powerful communication tool. communicating with photos enables to invoke not only the visual aspects but also invisible aspects of social phenomena from photos. It, therefore, can help develop thinking power through inquiry learning, which is one of the emphasis of the 7th curriculum. Having analyzed photo resources appeared on the regional textbooks in elementary social studies, they have been appeared that even though the importance and amount of space photo resources occupy per page is big with regard to total resources, most of the photos failed to lad to self-directed thinking but just assistant material in stead. Besides, there appeared some problems with the title, variety, size, position, tone of color, visibility of the photos, and further with the combination of the photos. Developing of photo resources for constructive social studies is to overcome some problems inherent in current text books and to reflect the theoretical background of the 7th curriculum. To develop the sort of photo that can realize the point just mentioned, it would be highly preferable to provide photo database to facilitate study with homepage through web-based interaction. To take advantage of constructive photo resources, the instruction is strategized in four stages, intuition, conflict, accommodation, and equilibration stage. With the advancement of the era of image culture, curriculum developers are required to develop dynamic, multidimensional digital photos rather than static photos when develop text books.

• The Korean Journal of Nuclear Medicine
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• v.28 no.1
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• pp.62-68
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• 1994

This study was aimed to compare the density of the functional microcirculation of hepatocellular carcinoma (HCC) with normal liver and to investigate the effect of hepatic-arterial oily chemoembolization (HAE) by radionuclide examination. Methods : Eight patients with HCC proven by biopsy in five, and clinically and radiologically in three were included. The mixture of 2 cc normal saline with three to four mCi of $^{99m}Tc$-MAA was infused through a hepatic-arterial catheter for a minute. Dynamic images were obtained at a rate of 4 sec per frame for a minute, and static images and SPECT were followed. Results : In three patients who underwent hepatic arterial angiography (HAA) alone, radioactivity was markedly increased in tumors compared to the adjacent liver immediately after infusion of $^{99m}Tc$-MAA. The ratios of tumoral and extratumoral up-take (T/E ratio) were above 6.5 (range; $6.5{\sim}l9$, mean; 12.5). In four of the five patients who under-went superselective HAE, T/E ratio were remark-ably decreased ($0.5{\sim}1.3$). The areas of embolization were better delineated in radionuclide study than in postembolization HAA. In the other one who was considered to be embolized completely on HAA, strong radiouptake in the tumor was disclosed (T/E ratio; 7.0). Conclusions : Therefore hepatic-arterial flow study with radionuclide imaging using $^{99m}Tc$-MAA can be a valuable method to assess the accurate embolization effect in HCC.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.11 no.1
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• pp.12-20
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• 2008

Purpose: Chronic pulmonary disease may be caused by aspiration of gastric contents secondary to gastroesophageal reflux. At present, there is no gold standard for documenting pulmonary aspiration. The purpose of this study was to investigate the usefulness of radionuclide scintigraphy in the detection of gastroesophageal reflux and pulmonary aspiration. Methods: Thirty-five patients with suspected aspiration pneumonia, and five normal control subjects, were included in the study. All subjects underwent gastroesophageal reflux scintigraphy after the ingestion of a $^{99m}Tc$-tin colloid mixture. Dynamic images to detect gastroesophageal reflux were obtained for 1 hour. Additional static images of the chest, to detect lung aspiration, were obtained at 6 and 24 hours after oral ingestion of the tin colloid. In addition to visual analysis, pulmonary aspiration was quantitated by counting the number of pixels labeled with radioactive isotope in the region of interest (ROI) of both lung fields. Aspiration index (AI) was obtained by subtracting the pixel counts of the background from the pixel counts of the ROI. Results: Among 35 patients with suspected aspiration pneumonia, 23 proved to have gastroesophageal reflux by scintigraphy. One patient showed definite pulmonary accumulation of activity by visual analysis of the 6-hour image. Thirty of 35 (85.7%) patients showed higher AI beyond the upper limit of AI in the healthy controls. When we compared the reflux group with the non-reflux group, there was a significantly higher AI at 6 hours in the reflux group (p<0.05). Conclusion: The results suggest that radionuclide scintigraphy is useful in detecting small pulmonary aspiration in patients with suspected aspiration pneumonia secondary to reflux.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.3
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• pp.43-52
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• 1984

This paper is concerned with the strain characteristics of the time effect on the remoulded saturated day sampled from the downstream of the Yeongsan river, and the constitutive equation that can generally explain time-dependent behaviors of norma1ly consolidated clay. This paper examines whether or not the afore-said constitutive equation can be applied to the remoulded Mooan-clay. Throughout this study, the conclusions obtained are as follows. 1. Throughout the isotropic consolidation test for 7 days and the isotropic relaxation test, the existence of the static and dynamic yielding surfaces is confirmed respectively. 2. The characteristics of time effect of the deformation, namely, the existence of a unique stress-strain-time relation, is conformed from the experimental result on the Mooan-clay. 3. The prodictions of the stress path and the strain on the Cam-clay theory is not consistent with those observed during the experiments. 4. Constitutive equation(2-3-12) obtained by applying Cam-clay theory to Perzyna's elastic-viscoplasticity theory can explain the behavior of pore water pressure during isotropic stress relaxation, concerned with time dependency under undrained condition. The equation can also explain the results of the undrained triaxial compression test for the clay with different strain rate under the same or different consolidation history. 5. This constitutive equation has eight material parameters which can be determined from triaxial compression tests.

• Journal of the Korea Institute of Building Construction
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• v.18 no.2
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• pp.141-149
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• 2018

In this study, compacting, passing performance, segregation resistance and rheological properties were tested to improve the stability of fresh concrete in the production and construction of self-compacting concrete (SCC) using hollow glass powder(GB). As a result, T50 reaching time was shortened up to amount of GB $2.0kg/m^3$. The compacting according to the amount of GB was improved by ball bearing effect of GB. However, T50 reaching time was slightly increased at $4.0kg/m^3$. In the case of passing performance, the result showed that plain was Class 1, GB $0.5{\sim}2.0kg/m^3$ was Class 0, GB $4.0kg/m^3$ was Class 1. Therefore, the passing performance was improved with 'No blocking' up to amount of GB $2.0kg/m^3$. Passing performance Block step (PJ) number by J-ring method was also best at GB $1.0kg/m^3$. In the case of segregation resistance according to the amount of GB, dynamic segregation resistance was increased compared to plain regardless of the amount of GB. And static segregation resistance showed 2.5% of segregation rate at GB $1.0kg/m^3$. Therefore, it was greatly improved compared to plain (12.5%). In the case of rheology property according to the amount of GB, plastic consistency by increasing of GB content didn't show big difference. However, yield stress by increasing of GB content was decreased with GB $1.0kg/m^3$. In conclusion, GB $1.0kg/m^3$ was effective for improvement of compacting, passing performance and yield stress. Also, it will be useful for stability of SCC by improving segregation.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.31 no.2
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• pp.43-57
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• 2013

The purpose of this study is to identify potential semantic landscape makeup of "the Forty Eight Poems of Soswaewon" according to Yin-Yang and Five Elements Principle(陰陽五行論). that speculation system between human's nature and cosmical universal order. Existing academic discussions made so far concerning this topic can be summed up as follows: 1. Among Yin-Yang-based landscape makeups of the Forty Eight Poems of Soswaewon, poetic writings for embodiment of interactions between nature and human behaviors focused on depicting dynamic aspects of a poetic narrator when he appreciates or explores hills and streams as of to live free from worldly cares. Primarily, many of those writings were created on the east and south primarily through assignment of yang. On the other hand, poetic writings for embodiment of nature and seasonal scenery - as static landscape makeup of yin - were often created on or near the north and west for many times. Those writings focusing on embodiment of nature and artificial scenery as a work are divided into two categories: One category refers to author Kim In-hu's expression of semantic landscape from seasonal scenery in nature. The other refers to his depiction of realistic garden images as they are. In the Forty Eight Poems of Soswaewon, the poetic writings show that author Kim focused on embodying seasonal scenery rather than expressing human behaviors. In addition, both Poem No. 1 and Poem No. 48(last poem; titled 'Jangwon Jeyeong') were created in a same place, which author Kim sought to understand the place as a space of beginning and end where yin and yang - i.e. the principle of natural cycle - are inherent. 2. According to construction about landscape in the Forty Eight Poems of Soswaewon on the basis of Ohaeng-ron (five natural element principle), it was found that tree(木) and fire(火) are typical examples of a world combined by emanation. First, many of poetic writings depicting the sentiments of tree focused on embodying seasonal scenery and were located in the place of Ogogmun(五曲門) area in the east, from overall perspective of Soswaewon. The content of these poems shows generation and curve / straightness in flexibility and simplicity. Many of poems depicting the sentiments of fire(火) focused on embodying human behaviors, and they were created in Aeyangdan area on the south of Soswaewon over which sun rises at noon. These poems are all on a status of side movement that is characterized by emanation and ascension which belong to attributes of yang. 3. With regard to Ohaeng-ron's interpretation about landscape in the Forty Eight Poems of Soswaewon, it was found that metal(金) and water(水) are typical examples of world combined by convergence. First, it was found that all of poems depicting sentiments of metal focused on embodying seasonal scenery, and were created in a bamboo grove area on the west from overall perspective of Soswaewon. They represent scenery of autumn among 4 seasons to symbolize faithfulness vested in a man of virtue(seonbi) with integrity and righteousness. Poems depicting sentiments of water were created in vicinity of Jewoldang on the north, possibly topmost of Soswaewon. They were divided into two categories: One category refers to poems embodying actions of welcoming the first full moon deep in the night after sunset, and the other refers to poems embodying natural scenery of snowscape. All of those poems focused on expressing any atmosphere of turning into yin via convergence. 4. With regard to Ohaeng-ron's interpretation of landscape in the Forty Eight Poems of Soswaewon, it was found that poems depicting sentiments of earth(土), a complex body of convergence and emanation, were created in vicinity of mountain stream around Gwangpunggak which is located in the center of Soswaewon. These poems focused on carrying actions of author Kim by way of natural phenomena and artificial scenery.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.