• Journal of Gastric Cancer
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• v.3 no.4
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• pp.195-200
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• 2003

Purpose: Advancement of computed tomography (CT) hardware and software has allowed thin section scanning and reconstruction of fascinating 2-dimentional (2D) and 3- dimentional (3D) images. Especially, the reconstruction of 3D images of gastrointestinal tract has been used in the detection and diagnosis of pre-malignant and malignant diseases. To compare the efficacy of CT gastrography with conventional upper gastrointenstinal series (UGIs) in gastric cancer patients. Materials and Methods: During Nov. 2002 and Mar. 2003, twenty-seven patients who had gastric cancer received both double contrast upper GI series and CT gastrography prior to radical surgery. Among these patients, nineteen had early gastric cancer (EGC) and 8 had advanced gastric cancer (AGC). Fifteen patients were male and 12 were female. The mean age was 54 yrs (range, $27\∼75$ yrs). The patients were placed on NPO and Stomach was distended with gas in fasting state prior to CT scanning. Double contrast upper GI series were performed as routine manual. CT scan was conducted in all patients using 8 or 16-channel multidetector CT in this study. The collimation and reconstruction for CT scanning were set at 2.5 mm and 1.25 mm, respectively. CT scanning was performed in the supine position. For image processing, CT gastrography, in which raysum and surface rendering images were constructed, virtual and 2D image in coronal and sagittal images were performed. The detectability of gastric cancer was assessed between UGIs and CT gastrography. Results: In AGCs, the detection rate of cancer using CT gastrography and virtual gastroscopy was higher than EGC cases. However, CT gastrography and virtual gastroscopy showed less favorable results than UGIs. Even though only a small number of cases had been studied, we might conclude that CT gastrography and virtual gastroscopy could replace UGIs in the detection of AGC cases. Conclusion: The detection rate used with CT gastrography and Virtual gastroscopy is not better than that of UGIs in early gastric cancer, however, in advanced gastric cancer cases, it is nearly equal to that of UGIs.

• Smart Structures and Systems
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• v.21 no.5
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• pp.687-694
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• 2018

The problem of wheel tread defects has become a major challenge for the health management of high-speed rail as a wheel defect with small radius deviation may suffice to give rise to severe damage on both the train bogie components and the track structure when a train runs at high speeds. It is thus highly desirable to detect the defects soon after their occurrences and then conduct wheel turning for the defective wheelsets. Online wheel condition monitoring using wheel impact load detector (WILD) can be an effective solution, since it can assess the wheel condition and detect potential defects during train passage. This study aims to develop an FBG-based track-side wheel condition monitoring method for the detection of wheel tread defects. The track-side sensing system uses two FBG strain gauge arrays mounted on the rail foot, measuring the dynamic strains of the paired rails excited by passing wheelsets. Each FBG array has a length of about 3 m, slightly longer than the wheel circumference to ensure a full coverage for the detection of any potential defect on the tread. A defect detection algorithm is developed for using the online-monitored rail responses to identify the potential wheel tread defects. This algorithm consists of three steps: 1) strain data pre-processing by using a data smoothing technique to remove the trends; 2) diagnosis of novel responses by outlier analysis for the normalized data; and 3) local defect identification by a refined analysis on the novel responses extracted in Step 2. To verify the proposed method, a field test was conducted using a test train incorporating defective wheels. The train ran at different speeds on an instrumented track with the purpose of wheel condition monitoring. By using the proposed method to process the monitoring data, all the defects were identified and the results agreed well with those from the static inspection of the wheelsets in the depot. A comparison is also drawn for the detection accuracy under different running speeds of the test train, and the results show that the proposed method can achieve a satisfactory accuracy in wheel defect detection when the train runs at a speed higher than 30 kph. Some minor defects with a depth of 0.05 mm~0.06 mm are also successfully detected.

• Investigative Magnetic Resonance Imaging
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• v.4 no.2
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• pp.113-119
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• 2000

Purpose : To know the possibility of clinical application of MRI using oxygen inhalation as a perfusion MRI Materials and methods : Two healthy volunteers and three patients of one moyamoya disease, one acute infarction and one meningioma were studied using a 1.5 Tesla MRI unit. Oxygen (15 liters/min) mixed with room air was given using face mask from 8 second to 35 second during the study. Images were acquired 25 times (scan time per study were 1.6 seconds) using susceptibility contrast EPI (echo planar image) sequence. Difference maps were acquired by early (study 12-18), and late (study 19-25) O2 inhalation image groups minus pre-O2 inhalation image group (study 3-9) with a Z-score of 0.7-1.0 using VB31C program of Magneton Vision. The resulting perfusion images were created by superimposition of difference maps on corresponding T1 weighted anatomic images. On moyamoya patient, similar perfusion images were acquired after Gd-DTPA injection, and compared with O2 inhalation perfusion images. Results ; The author can get the perfusion images of the brain by oxygen inhalation with susceptibility contrast EPI sequence at the volunteers, and the patient of moyomoya disease, acute infarction and meningioma. On moyamoya patient, perfusion images with O2 inhalation are similar with perfusion images by Gd-DTPA injection. Conclusion 1 This study has demonstrated that the susceptibility contrast EPI by oxygen inhalation can be used as the clinically useful perfusion MRI technique

• The KIPS Transactions:PartC
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• v.11C no.1
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• pp.47-54
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• 2004

The growth of computer resource and network speed has increased requests for the use of remotely located computer systems by connecting through computer networks. This phenomenon has hoisted research activities for application service provision that uses server-based remote computing paradigm. The server-based remote computing paradigm has been developed as the ASP (Application Service Provision) model, which provides remote users through application sharing protocol to application programs. Security requirement such as confidentiality, availability, integrity should be satisfied to provide ASP service using centralized computing system. Existing Telnet or FTP service for a remote computing systems have satisfied security requirement by a simple access control to files and/or data. But windows-based centralized computing system is vulnerable to confidentiality, availability, integrity where many users use the same application program installed in the same computer. In other words, the computing system needs detailed security level for each user different from others, such that only authorized user or group of users can run some specific functional commands for the program. In this paper, we propose windows based centralized computing system that sets security policies for each user for the use of instructions of the application programs, and performs access control to the instructions based on the security policies. The system monitors all user messages which are executed through graphical user interface by the users connecting to the system. Ail Instructions, i.e. messages, for the application program are now passed to authorization process that decides if an Instruction is delivered to the application program based on the pre-defined security polices. This system can be used as security clearance for each user for the shared computing resource as well as shared application programs.

• Journal of KIISE:Databases
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• v.34 no.2
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• pp.119-132
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• 2007

In molecular biology, approximate subsequence search is one of the most important operations. In this paper, we propose an accurate and efficient method for approximate subsequence search in large DNA databases. The proposed method basically adopts a binary trie as its primary structure and stores all the window subsequences extracted from a DNA sequence. For approximate subsequence search, it traverses the binary trie in a breadth-first fashion and retrieves all the matched subsequences from the traversed path within the trie by a dynamic programming technique. However, the proposed method stores only window subsequences of the pre-determined length, and thus suffers from large post-processing time in case of long query sequences. To overcome this problem, we divide a query sequence into shorter pieces, perform searching for those subsequences, and then merge their results. To verify the superiority of the proposed method, we conducted performance evaluation via a series of experiments. The results reveal that the proposed method, which requires smaller storage space, achieves 4 to 17 times improvement in performance over the suffix tree based method. Even when the length of a query sequence is large, our method is more than an order of magnitude faster than the suffix tree based method and the Smith-Waterman algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.466-472
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• 2020

The purpose of this study is to explore how to use location data for peer relations of infants in free-choice play activities. For this study, location data was collected using wearable devices for 14 students in one class at an early childhood education institution in Chungnam. For the pre-processing of the collected location data, a smoothing technique was applied to recover missing values during the collection process, and the data was visualized using Python's Matplotlib. Subsequently, the movement distance, distance between infants, and interaction types of infants were extracted from the location data using the formula. As a result of the study, it was possible to derive 1) change in moving distance, cumulative value, average value, 2) change in distance and average distance value between infants, and 3) change and trend in interaction type according to the passage of time. These results can provide valuable information on the process of forming peer groups for infants in situations where it is difficult for a teacher to closely observe all members, and can be used as meaningful information for the design and operation of educational programs.

• Journal of the Korean association of regional geographers
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• v.23 no.2
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• pp.376-387
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• 2017

This paper attempts to analyze the geographical characters of Twitter data and presents analysis potentials for social network analysis in geography. First, this paper suggests a methodology for a topic modeling-based approach in order to identify the geographical characteristics of tweets, including an analysis flow of Twitter data sets, tweet data collection and conversion, textural pre-processing and structural analysis, topic discovery, and interpretation of tweets' topics. GPS coordinates referencing tweets(geotweets) were extracted among sampled Twitter data sets because it contains the tweet place where it was created. This paper identifies a correlated relationship between some specific topics and local places in Jeju. This correlation is closely associated with some place names and local sites in Jeju Island. We assume it is the intention of tweeters to record their tweet places and to share and retweet with other tweeters in some cases. A surface density map shows the hotspots of tweets, detecting around some specific places and sites such as Jeju airport, sightseeing sites, and local places in Jeju Island. The hotspots show similar patterns of the floating population of Jeju, especially the thirty-year age group. In addition, a topic modeling algorithm is applied for the geographical topic discovery and comparison of the spatial patterns of tweets. Finally, this empirical analysis presents that Twitter data, as social network data, provide geographical significance, with topic modeling approach being useful in analyzing the textural features reflecting the geographical characteristics in large data sets of tweets.

• Journal of Biomedical Engineering Research
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• v.23 no.3
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• pp.197-205
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• 2002

The objectives of this Paper is to implement a diagnostic classifier of differential laryngeal diseases from acoustic signals acquired in a noisy room. For this Purpose, the voice signals of the vowel /a/ were collected from Patients in a soundproof chamber and got mixed with noise. Then, the acoustic Parameters were analyzed, and hierarchical neural networks were applied to the data classification. The classifier had a structure of five-step hierarchical neural networks. The first neural network classified the group into normal and benign or malign laryngeal disease cases. The second network classified the group into normal or benign laryngeal disease cases The following network distinguished polyp. nodule. Palsy from the benign laryngeal cases. Glottic cancer cases were discriminated into T1, T2. T3, T4 by the fourth and fifth networks All the neural networks were based on multilayer perceptron model which classified non-linear Patterns effectively and learned by an error back-propagation algorithm. We chose some acoustic Parameters for classification by investigating the distribution of laryngeal diseases and Pilot classification results of those Parameters derived from MDVP. The classifier was tested by using the chosen parameters to find the optimum ones. Then the networks were improved by including such Pre-Processing steps as linear and z-score transformation. Results showed that 90% of T1, 100% of T2-4 were correctly distinguished. On the other hand. 88.23% of vocal Polyps, 100% of normal cases. vocal nodules. and vocal cord Paralysis were classified from the data collected in a noisy room.

• Cartoon and Animation Studies
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• s.43
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• pp.363-386
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• 2016

This research is to design basic framework for developing teaching and learning method in the field of art and design major in university. Especially taking off from oneway e-learning teaching method, it is focused on increasing reality of student learning situation with applying AR contents process to augment virtual condition on reality condition. The processing of framework design and developing teaching and learning method are about practice education based on AR for model experiment research which was published "The E-Learning for Practice Training Using Augmented Reality in the College Education". This thesis is supposed to be a precedent study of the pre-published, and the purpose of those two studies were for experiment test in earnest in studying effect research. The classification of learning method divided basically as Face-to-Face Learning(FFL), Blended Learning(BL), fully E-Learning(EL), and Augmented Reality based E-Learning(AREL). This research compares and analyzes each frame of FFL, BL, and EL. And then, designed framework lead to the over-all conclusion with the type of AREL. Additionally, AREL for PBE suggests the ways of advanced teaching learning.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.433-433
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• 2012

As the requirement in patterning geometry continuously shrinks down, the termination of etch process at the exact time became crucial for the success in nano patterning technology. By virtue of real-time optical emission spectroscopy (OES), etch end point detection (EPD) technique continuously develops; however, it also faced with difficulty in low open ratio etching, typically in self aligned contact (SAC) and one cylinder contact (OCS), because of very small amount of optical emission from by-product gas species in the bulk plasma glow discharge. In developing etching process, one may observe that coupon test is being performed. It consumes costs and time for preparing the patterned sample wafers every test in priority, so the coupon wafer test instead of the whole patterned wafer is beneficial for testing and developing etch process condition. We also can observe that etch open area is varied with the number of coupons on a dummy wafer. However, this can be a misleading in OES study. If the coupon wafer test are monitored using OES, we can conjecture the endpoint by experienced method, but considering by data, the materials for residual area by being etched open area are needed to consider. In this research, we compare and analysis the OES data for coupon wafer test results for monitoring about the conditions that the areas except the patterns on the coupon wafers for real-time process monitoring. In this research, we compared two cases, first one is etching the coupon wafers attached on the carrier wafer that is covered by the photoresist, and other case is etching the coupon wafers on the chuck. For comparing the emission intensity, we chose the four chemical species (SiF2, N2, CO, CN), and for comparing the etched profile, measured by scanning electron microscope (SEM). In addition, we adopted the Dynamic Time Warping (DTW) algorithm for analyzing the chose OES data patterns, and analysis the covariance and coefficient for statistical method. After the result, coupon wafers are over-etched for without carrier wafer groups, while with carrier wafer groups are under-etched. And the CN emission intensity has significant difference compare with OES raw data. Based on these results, it necessary to reasonable analysis of the OES data to adopt the pre-data processing and algorithms, and the result will influence the reliability for relation of coupon wafer test and whole wafer test.