• Journal of Navigation and Port Research
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• v.41 no.3
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• pp.149-154
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• 2017

Recently, container terminal operators have made efforts to develop an efficient remarshalling plan in response to the increase in automation of equipment handling and transport of containers in the terminals. Usually, containers are handled by multiple AYCs(automated yard cranes) in-yard in an automated container terminal, and terminal operators establish a remarshalling plan using slack time to increase the efficiency of ship operation. This study develops the optimal mathematical model through mixed integer programming as a solution to the problem of dispatching multiple AYCs. Considering the difficulty of direct application to the field due to computation time, we analyze the five prototypical dispatching rules for real world adaptation. A numerical experiment found that the maximum weight ratio (MR) rule and the maximum weight (MW) rule are the ideal dispatching solutions to the multiple AYCs dispatching problem.

• Composites Research
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• v.23 no.6
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• pp.7-13
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• 2010

Type3 cylinder is a composite pressure vessel fully over-wrapped with carbon/epoxy composite layers over an aluminum liner, which is the most ideal and safe high pressure gas container for CNG vehicles due to the lightweight and the leakage-before-burst characteristics. During service in CNG vehicle, if a fiber cut damage occurs in outer composite layers, it can degrade structural performance, reducing cycling life from the original design life. In this study, finite element modeling and analysis technique for the composite cylinder with fiber-cut crack damage is presented. Because FE analysis of type3 cylinder is path dependant due to plastic deformation of aluminum liner in autofrettage process, method to introduce a crack into FE model affect analysis result. A crack should be introduced after autofrettage in analysis step considering real circumstances where crack occurs during usage in service. For realistic simulation of this situation, FE modeling and analysis technique introducing a crack in the middle of analysis step is presented and the results are compared with usual FE analysis which has initial crack in the model from the beginning of analysis. Proposed analysis technique can be used effectively in the evaluation of influence of damage on composite layers of type3 cylinder and establish inspection criteria of composite cylinder in service.

• Journal of Korean Neurosurgical Society
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• v.48 no.5
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• pp.391-398
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• 2010

Objective : This study was designed to validate the cell trafficking efficiency of the in vivo bioluminescence image (BLI) study in the setting of transplantation of the luciferase expressing bone marrow-derived mesenchymal stem cells (BMSC), which were delivered at each different time after transient middle cerebral artery occlusion (MCAO) in a mouse model. Methods : Transplanting donor BMSC were prepared by primary cell culture from transgenic mouse expressing luciferase (LUC). Transient focal infarcts were induced in 4-6-week-old male nude mice. The experiment mice were divided into five groups by the time of MSC transplantation : 1) sham-operation group, 2) 2-h group, 3) 1-day group, 4) 3-day group, and 5) 1-week group. BLI for detection of spatial distribution of transplanted MSC was performed by detecting emitted photons. Migration of the transplanted cells to the infarcted area was confirmed by histological examinations. Differences between groups were evaluated by paired t-test. Results : A focal spot of bioluminescence was observed at the injection site on the next day after transplantation by Signal intensity of bioluminescence. After 4 weeks, the mean signal intensities of 2-h, 1-day, 3-day, and 1-week group were $2.6{\times}10^7{\pm}7.4{\times}10^6$. $6.1{\times}10^6{\pm}1.2{\times}10^6$, $1.7{\times}10^6{\pm}4.4{\times}10^5$, and $8.9{\times}10^6{\pm}9.5{\times}10^5$, respectively. The 2-h group showed significantly higher signal intensity (p<0.01). The engrafted BMSC showed around the infarct border zones on immunohistochemical examination. The counts of LUC-positive cells revealed the highest number in the 2-h group, in agreement with the results of BLI experiments (p<0.01). Conclusion : In this study, the results suggested that the transplanted BMSC migrated to the infarct border zone in BLI study and the higher signal intensity of LUC-positive cells seen in 2 hrs after MSC transplantation in MCAO mouse model. In addition, noninvasive imaging in real time is an ideal method for tracking stem cell transplantation. This method can be widely applied to various research fields of cell transplantation therapy.

• Journal of The Korean Association For Science Education
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• v.38 no.3
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• pp.393-405
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• 2018

In this study, we classified the group model construction types in the actual classroom situation implementing the instructional strategy mixed with individual model construction and group model construction types. The purpose of this study is to analyze the information flow and the individual construction types of each group model construction type to obtain implications for model co-construction in a real classroom environment. A two-session class on sound propagation was carried out for thirty-three 8th grade students in Seoul. A total of 65 individual model construction and 16 group model construction processes were collected and analyzed. The group model construction types were classified as unchanged, enumerated, and elaborated. The unchanged type was found in 8 groups, the enumerated type in 3 groups, and the elaborated type in 5 groups. The isolated individual and independent construction (i.I) were found mostly in the unchanged group construction type (50.0%) and enumerated group construction type (54.5%). In the unchanged type, the radial shape of flow in which one student's information is transmitted to all the members of the group appeared. In the enumerated type, the starting point of the information flow was observed from two individuals. In the elaborated type, linear information flow appeared and both the second dissemination and reflective construction (2d.R) contributed to the group model construction (58.3%). This study suggests a viewpoint that enables to understand the process of complex model construction in an actual classroom context rather than in an ideal situation. The result of this study suggests the necessity of a modeling strategy considering the characteristics of Korean small group culture. It is expected that the discussion will progress through further studies.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.43-62
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• 2019

At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.411-419
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• 2004

When the imaging object rotates in image plane during MRI scan, its rotation causes phase error and non-uniform sampling to MRI signal. The model of the problem including phase error non-uniform sampling of MRI signal showed that the MRI signals corrupted by rotations about an arbitrary center and the origin in image plane are different in their phases. Therefore the following methods are presented to improve the quality of the MR image which includes the artifact. The first, assuming that the angle of 2-D rotational motion is already known and the position of 2-D rotational center is unknown, an algorithm to correct the artifact which is based on the phase correction is presented. The second, in case of 2-D rotational motion with unknown rotational center and unknown rotational angle, an algorithm is presented to correct the MRI artifact. At this case, the energy of an ideal MR image is minimum outside the boundary of the imaging object to estimate unknown motion parameters and the measured energy increases when the imaging object has an rotation. By using this property, an evaluation function is defined to estimate unknown values of rotational angle at each phase encoding step. Finally, the effectiveness of this presented techniques is shown by using a phantom image with simulated motion and a real image with 2-D translational shift and rotation.

• Journal of the Korean Society for Marine Environment & Energy
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• v.17 no.3
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• pp.182-188
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• 2014

In an oscillating water column (OWC)-type wave energy conversion system, the performance of the OWC chamber depends on the chamber shape, as well as the incident wave direction and pressure drop produced by the turbine. Although the previous studies on OWC chambers have focused on wave absorbing performance in ideal operating conditions, incident waves do not always arrive normally to the OWC chamber in real sea conditions, especially in fixed devices. The present study deals with experiments and numerical calculations to investigate the effects of wave direction on the performance of the OWC chamber. The experiments were carried out in a three-dimensional wave basin for five different wave directions, including the effect of turbine using the corresponding orifice. The wave elevation inside the chamber was measured at the center point under various incident wave conditions. The numerical study was conducted by using a numerical wave tank-based volume-of-fluid model to compare the results with experimental data and to reveal the detailed flows around the chamber.

• Journal of the Korean association of regional geographers
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• v.16 no.1
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• pp.1-15
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• 2010

A feng-shui map(山圖) represents the most ideal natural landform on a map of feng-shui space model, highlighting propitious spots and grave sites in terms of feng-shui. This study made an analysis into feng-shui maps featured in the Chinese feng-shui manual Jiriinjasuji published in the Ming dynasty of China and did research on the following points regarding the traits of landform expressions: viewpoints of feng-shui maps, perspective points, center-oriented maps, double map scales, mountain theories, detailed expressions of propitious spots, etc. The major characteristics of landform expressions in the Chinese feng-shui manual Jiriinjasuji are as follows: the viewpoint technique was aerial one; the maps were center-oriented, that is to say, the center of grave sites or propitious spot was depicted in detail; and often the important terrains around grave sites were exaggerated or delete compared with real landforms. In addition, other vital landforms not observed from grave sites were depicted with viewpoints moved and were represented in greater details' The part of mountain theories had the following points as their main subject matter: geographical locations, overall orientations of mountain ranges, topographical traits, grave seat directions, surrounding terrains and extent of fortune-bringing. The directions of the maps were relative and there was no definite concept of scales. But, there are many cases where the maps made use of the double scale technique when expressing the terrains that have propitious space, logistical cities or directional importance. Furthermore, they often utilized multiple scale in expressing near views, mid-range views and distant views.

• Journal of Chest Surgery
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• v.36 no.2
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• pp.63-72
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• 2003

Although a variety of synthetic vascular grafts are available in modern vascular surgery, no ideal prosthesis ha,4 yet been developed. Small-caliber vascular grafts with low flow, as used in the lower extremity, continue to become thrombosed at unacceptable rates. We have developed and evaluated the new antithrombogenic blood contacting surfaces in canine model. Material and Method: Two now antithrombogenic blood contacting surfaces(Polyvinylalcohol -Polyurethane(PVA-PU) blend and natural Graphite-polyurethane(G-PU) blend) have been developed and evaluated in canine model, using vascular grafts and patches. The luminal surfaces of the test vascular grafts(5 mm ID) were fabricated by dipping a glass rod in PVA-PU blend solution(50 % PVA) using phase separation method. Mongrel dogs of either sex weighing 18-22 kg were anesthetized by endotracheal intubation using halothane and their lungs were ventilated with a volume-cycled ventilator, Maintenance anesthesia with 0.5-1.0% halothane and supplemental oxygen was used. Two pairs were used for comparison in the bilateral femoral arteries for both vascular grafts(PVA-PU vs. PU) and vascular patches(G-PU vs. PU). Bilateral groin incisions were made and the arteries were exposed and clamped. After an excision of 1 cm of the artery between clamps, a grail of 2.5 cm in length was implanted end-to-end using 6-0 polypropylene suture. The vascular patch was implanted as a form of on-lay patch. Animals were sacrificed at 1, 2, 4, 6, 8 and 16 weeks for vascular grafts and 1, 2. 4 and 6 weeks for vascular patches. Result The vascular grafts of PVA-PU blends showed patent lumina in the 2 and 16 weeks animals, while those of PU showed a patent lumen in 2 weeks animal. PVA-PU graft of 16 weeks showed a fairly clean luminal surface. A light microscopic finding of this graft demonstrated good tissue infiltration through porosity, The animals with vascular patches showed patent arteries in both groups except 2 weeks animal. Scanning electron microscopy of the luminal surfaces of G-PU patches in 4 and 6 weeks animals showed endothelial cell covering with microvilli. PU patches showed qualitatively less endothelial cell covering. Conclusion: In conclusion, PVA-PU and G-PU blends can be a promising blood contacting surfaces for application in a synthetic vascualr graft. However, further animal study is needed to determine the real long-term effects of these methods of surface modifications.