• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.281-286
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• 2003

A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.

• Archives of design research
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• v.18 no.3 s.61
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• pp.85-94
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• 2005

Most of product designers use 3D CAD system as a inevitable design tool nowadays and many new products are developed through a concurrent engineering process. However, it is very difficult for novice designers to get the sense of reality from modeling objects shown in the computer screens. Such a intangibility problem comes from the lack of haptic interactions and contextual information about the real space because designers tend to do 3D modeling works only in a virtual space of 3D CAD system. To address this problem, this research investigate the possibility of a interactive quantified structure simulation for product design using AR(augmented reality) which can register a 3D CAD modeling object on the real space. We built a quantified structure simulation system based on AR and conducted a series of experiments to measure how accurately human perceive and adjust the size of virtual objects under varied experimental conditions in the AR environment. The experiment participants adjusted a virtual cube to a reference real cube within 1.3% relative error(5.3% relative StDev). The results gave the strong evidence that the participants can perceive the size of a virtual object very accurately. Furthermore, we found that it is easier to perceive the size of a virtual object in the condition of presenting plenty of real reference objects than few reference objects, and using LCD panel than HMD. We tried to apply the simulation system to identify preference characteristics for the appearance design of a home-service robot as a case study which explores the potential application of the system. There were significant variances in participants' preferred characteristics about robot appearance and that was supposed to come from the lack of typicality of robot image. Then, several characteristic groups were segmented by duster analysis. On the other hand, it was interesting finding that participants have significantly different preference characteristics between robot with arm and armless robot and there was a very strong correlation between the height of robot and arm length as a human body.

• Restorative Dentistry and Endodontics
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• v.34 no.2
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• pp.87-94
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• 2009

The purpose of this study was to assess the current materials, methods and difficulties according to the year of licence and educational background of Korean dentists in Class II direct composite resin restorations. Total 17 questions were included in the questionnaire. Questions were broadly divided into two parts: first. operator's information. and second. the materials and methods used in Class II posterior composite restoration. The questionnaire was sent to dentists enrolled in Korean Dental Association via e-mail. Total 12,193 e-mails were distributed to dentists. 2,612 e-mails were opened, and 840 mails (32.2%) were received from respondents. The data was statically analyzed by chi-square test using SPSS(v. 12.0.1, SPSS Inc. Chicago, IL, USA). Male dentists among respondents was 79%. 60.3% of the respondents acquired their licences recently (1998-2007), and 77% practiced in private offices. 83.4% have acquired their knowledge through school lectures, conferences and seminars. For the Class II restorations, gold inlays were preferred by 65.7% of respondents, while direct composite resin restorations were used by 12.1 % amalgam users were only 4.4% of respondents. For the restorative technique, 74.4% of respondents didn't use rubber dam as needed. For the matrix. mylar strip (53.4%), metal matrix (33.8%) and Palodent system (6.5%) were used. 99.6% of respondents restored the Class II cavity by incremental layering. Obtaining of the tight interproximal contact was considered as the most difficult procedure (57.2%) followed by field isolation (21 %). Among various bonding systems, 22.6% of respondents preferred SE Bond and 20.2% used Single Bond. Z-250 was used most frequently among a variety of composite resins.

• The KIPS Transactions:PartA
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• v.13A no.2 s.99
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• pp.123-136
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• 2006

The prefetching technique is an effective way to reduce the latency caused memory access. However, excessively aggressive prefetch not only leads to cache pollution so as to cancel out the benefits of prefetch but also increase bus traffic leading to overall performance degradation. In this thesis, a prefetch filtering scheme is proposed which dynamically decides whether to commence prefetching by referring a filtering table to reduce the cache pollution due to unnecessary prefetches In this thesis, First, prefetch hashing table 1bitSC filtering scheme(PHT1bSC) has been shown to analyze the lock problem of the conventional scheme, this scheme such as conventional scheme used to be N:1 mapping, but it has the two state to 1bit value of each entries. A complete block address table filtering scheme(CBAT) has been introduced to be used as a reference for the comparative study. A prefetch block address lookup table scheme(PBALT) has been proposed as the main idea of this paper which exhibits the most exact filtering performance. This scheme has a length of the table the same as the PHT1bSC scheme, the contents of each entry have the fields the same as CBAT scheme recently, never referenced data block address has been 1:1 mapping a entry of the filter table. On commonly used prefetch schemes and general benchmarks and multimedia programs simulates change cache parameters. The PBALT scheme compared with no filtering has shown enhanced the greatest 22%, the cache miss ratio has been decreased by 7.9% by virtue of enhanced filtering accuracy compared with conventional PHT2bSC. The MADT of the proposed PBALT scheme has been decreased by 6.1% compared with conventional schemes to reduce the total execution time.

• The Korean Journal of Nuclear Medicine
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• v.36 no.6
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• pp.344-356
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• 2002

Purpose: RBC blood pool SPECT has been used to diagnose focal liver lesion such as hemangioma owing to its high specificity. However, low spatial resolution is a major limitation of this modality. Recently, ordered subset expectation maximization (OSEM) has been introduced to obtain tomographic images for clinical application. We compared this new modified iterative reconstruction method, OSEM with conventional filtered back projection (FBP) in imaging of liver hemangioma. Materials and Methods: Sixty four projection data were acquired using dual head gamma camera in 28 lesions of 24 patients with cavernous hemangioma of liver and these raw data were transferred to LINUX based personal computer. After the replacement of header file as interfile, OSEM was performed under various conditions of subsets (1,2,4,8,16, and 32) and iteration numbers (1,2,4,8, and 16) to obtain the best setting for liver imaging. The best condition for imaging in our investigation was considered to be 4 iterations and 16 subsets. After then, all the images were processed by both FBP and OSEM. Three experts reviewed these images without any information. Results: According to blind review of 28 lesions, OSEM images revealed at least same or better image quality than those of FBP in nearly all cases. Although there showed no significant difference in detection of large lesions more than 3 cm, 5 lesions with 1.5 to 3 cm in diameter were detected by OSEM only. However, both techniques failed to depict 4 cases of small lesions less than 1.5 cm. Conclusion: OSEM revealed better contrast and define in depiction of liver hemangioma as well as higher sensitivity in detection of small lesions. Furthermore this reconstruction method dose not require high performance computer system or long reconstruction time, therefore OSEM is supposed to be good method that can be applied to RBC blood pool SPECT for the diagnosis of liver hemangioma.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.959-974
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• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.271-278
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• 2021

As the current cyber attacks become more intelligent, the existing Intrusion Detection System is difficult for detecting intelligent attacks that deviate from the existing stored patterns. In an attempt to solve this, a model of a deep learning-based intrusion detection system that analyzes the pattern of intelligent attacks through data learning has emerged. Intrusion detection systems are divided into host-based and network-based depending on the installation location. Unlike network-based intrusion detection systems, host-based intrusion detection systems have the disadvantage of having to observe the inside and outside of the system as a whole. However, it has the advantage of being able to detect intrusions that cannot be detected by a network-based intrusion detection system. Therefore, in this study, we conducted a study on a host-based intrusion detection system. In order to evaluate and improve the performance of the host-based intrusion detection system model, we used the host-based Leipzig Intrusion Detection-Data Set (LID-DS) published in 2018. In the performance evaluation of the model using that data set, in order to confirm the similarity of each data and reconstructed to identify whether it is normal data or abnormal data, 1D vector data is converted to 3D image data. Also, the deep learning model has the drawback of having to re-learn every time a new cyber attack method is seen. In other words, it is not efficient because it takes a long time to learn a large amount of data. To solve this problem, this paper proposes the Siamese Convolutional Neural Network (Siamese-CNN) to use the Few-Shot Learning method that shows excellent performance by learning the little amount of data. Siamese-CNN determines whether the attacks are of the same type by the similarity score of each sample of cyber attacks converted into images. The accuracy was calculated using Few-Shot Learning technique, and the performance of Vanilla Convolutional Neural Network (Vanilla-CNN) and Siamese-CNN was compared to confirm the performance of Siamese-CNN. As a result of measuring Accuracy, Precision, Recall and F1-Score index, it was confirmed that the recall of the Siamese-CNN model proposed in this study was increased by about 6% from the Vanilla-CNN model.

• Korean Journal of Heritage: History & Science
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• v.51 no.4
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• pp.108-119
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• 2018

"The Collection of Yi Chungmugong" manuscript is a hand-written manuscript of the volume 1 consisting of the Collection, published in 1795 and it seems to have completed the contents of the book by correcting the first part of the book before print. The book adopted a form of Seonjangbon(線裝本) of Ochimanjeongbeop(五針眼訂法) and was urgently needed some measures to preserve because it has been much damaged by stains, loss and oxidation due to moisture on the bottom of it. In addition, a scientific investigation was applied to find out the features of the quality of paper and fiber used for the book, which would be reflected in the process of the preservation. The characteristics of paper were measurmented for size(cm), thickness(mm), weight(g), basis weight($g/m^2$), density($g/cm^3$), chain line and laid lines($3{\times}3cm$). The measurement showed that the characteristics of paper used in royal books published in the late Joseon Dynasty. For the paper-fiber of the book, C stain was used and the technique revealed that the book is made of bast fibre of paper mulberry and its binding strings are cotton. SEM-EDS analysis was performed to verify the existence of additives in paper. As a result of the analysis, The crystallized calcium was detected in addition to the main components carbon(C) and oxygen(O). This artifact is the unique final version of "The collection of Yi Chungmugong", which has considerable value in terms of academic research, besides it helps to understand how to print books of Joseon Dynasty. And it also has a very accurate information of when and where the book was made, which primarily could be resources to conserve and restore for other book heritage.

• Conservation Science in Museum
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• v.26
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• pp.161-182
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• 2021

A jungwangu, a type of medium-sized mortar, is a firearm with a barrel and a bowl-shaped projectileloading component. A bigyeokjincheonroe (bombshell) or a danseok (stone ball) could be used as a projectile. According to the Hwaposik eonhae (Korean Translation of the Method of Production and Use of Artillery, 1635) by Yi Seo, mortars were classified into four types according to its size: large, medium, small, or extra-small. A total of three mortars from the Joseon period have survived, including one large mortar (Treasure No. 857) and two medium versions (Treasure Nos. 858 and 859). In this study, the production method for medium mortars was investigated based on scientific analysis of the two extant medium mortars, respectively housed in the Jinju National Museum (Treasure No. 858) and the Korea Naval Academy Museum (Treasure No. 859). Since only two medium mortars remain in Korea, detailed specifications were compared between them based on precise 3D scanning information of the items, and the measurements were compared with the figures in relevant records from the period. According to the investigation, the two mortars showed only a minute difference in overall size but their weight differed by 5,507 grams. In particular, the location of the wick hole and the length of the handle were distinct. The extant medium mortars are highly similar to the specifications listed in the Hwaposik eonhae. The composition of the medium mortars was analyzed and compared with other bronze gunpowder weapons. The surface composition analysis showed that the medium mortars were made of a ternary alloy of Cu-Sn-Pb with average respective proportions of (wt%) 85.24, 10.16, and 2.98. The material composition of the medium mortars was very similar to the average composition of the small gun from the Joseon period analyzed in previous research. It also showed a similarity with that of bronze gun-metal from medieval Europe. The casting technique was investigated based on a casting defect on the surface and the CT image. Judging by the mold line on the side, it appears that they were made in a piece-mold wherein the mold was halved and using a vertical design with molten metal poured through the end of the chamber and the muzzle was at the bottom. Chaplets, an auxiliary device that fixed the mold and the core to the barrel wall, were identified, which may have been applied to maintain the uniformity of the barrel wall. While the two medium mortars (Treasure Nos. 858 and 859) are highly similar to each other in appearance, considering the difference in the arrangement of the chaplets between the two items it is likely that a different mold design was used for each item.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.497-510
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• 2022

Agricultural reservoirs are essential structures for water supplies during dry period in the Korean peninsula, where water resources are temporally unequally distributed. For efficient water management, systematic and effective monitoring of medium-small reservoirs is required. Synthetic Aperture Radar (SAR) provides a way for continuous monitoring of those, with its capability of all-weather observation. This study aims to evaluate the applicability of SAR in monitoring medium-small reservoirs using Sentinel-1 (10 m resolution) and Capella X-SAR (1 m resolution), at Chari (CR), Galjeon (GJ), Dwitgol (DG) reservoirs located in Ulsan, Korea. Water detected results applying Z fuzzy function-based threshold (Z-thresh) and Chan-vese (CV), an object detection-based segmentation algorithm, are quantitatively evaluated using UAV-detected water boundary (UWB). Accuracy metrics from Z-thresh were 0.87, 0.89, 0.77 (at CR, GJ, DG, respectively) using Sentinel-1 and 0.78, 0.72, 0.81 using Capella, and improvements were observed when CV was applied (Sentinel-1: 0.94, 0.89, 0.84, Capella: 0.92, 0.89, 0.93). Boundaries of the waterbody detected from Capella agreed relatively well with UWB; however, false- and un-detections occurred from speckle noises, due to its high resolution. When masked with optical sensor-based supplementary images, improvements up to 13% were observed. More effective water resource management is expected to be possible with continuous monitoring of available water quantity, when more accurate and precise SAR-based water detection technique is developed.