• Radiation Oncology Journal
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• v.34 no.2
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• pp.106-112
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• 2016

Purpose: To identify possible predictors of pathologic complete response (pCR) of rectal cancer after preoperative concurrent chemoradiotherapy (CCRT). Materials and Methods: We conducted a retrospective review of 53 patients with rectal cancer who underwent preoperative CCRT followed by radical surgery at a single center between January 2007 and December 2012. The median radiotherapy dose to the pelvis was 54.0 Gy (range, 45.0 to 63.0 Gy). Five-fluorouracil-based chemotherapy was administered via continuous infusion with leucovorin. Results: The pCR rate was 20.8%. The downstaging rate was 66%. In univariate analyses, poor and undifferentiated tumors (p = 0.020) and an interval of ${\geq}7$ weeks from finishing CCRT to surgery (p = 0.040) were significantly associated with pCR, while female gender (p = 0.070), initial carcinoembryonic antigen concentration of <5.0 ng/dL (p = 0.100), and clinical stage T2 (p = 0.100) were marginally significant factors. In multivariate analysis, an interval of ${\geq}7$ weeks from finishing CCRT to surgery (odds ratio, 0.139; 95% confidence interval, 0.022 to 0.877; p = 0.036) was significantly associated with pCR, while stage T2 (odds ratio, 5.363; 95% confidence interval, 0.963 to 29.877; p = 0.055) was a marginally significant risk factor. Conclusion: We suggest that the interval from finishing CCRT to surgery is a predictor of pCR after preoperative CCRT in patients with rectal cancer. Stage T2 cancer may also be an important predictive factor. We hope to perform a robust study by collecting data during treatment to obtain more advanced results.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 1997.11a
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• pp.439-449
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• 1997

Studies have been carried out to determine the effect of sprinklers on fires typical of a number of occupancies including simulated of office furniture, supermarkets, carpet displays, libraries, video stores and liquor stores. After surveys of actual fire loads, the experiments were conducted in a specially designed sprinklered fire-calorimeter with a collecting hood 6 m x6 m leading to a vertical duct 1 m in diameter. Details of the rig are given elsewhere [1]. Only well ventilated fires were studied. Rate of heat release and production of various toxic chemicals were monitored during the tests. Both sprinklered and unsprinklered fires were used. The results were used to establish the unsprinklered burning behaviour and the fire-control effects of sprinklers. Before sprinkler operation, the rate of fire growth could be modelled as 12_fires as given in NFPA 92B (1991 Edition) [2]. It was found that operation of sprirnklers controlled but did not extinguish the fires. This was expected as parts of the fire load were shielded from the spray. Also there were significant increases in the concentration of carbon monoxide when the sprinklers operated. Sprinklers had little effect on the concentrations of other toxic products measured. The results from the tests were extrapolated to large single storey buildings for the same occupancy classes and the results used to compare the required and the available escape times for different occupancies, particularly whether the use of sprinklers would improve the chances of escape from those premises. It was found that in most of the cases studied, adequate escape times will be available without any special measures. For very rapid fire growths, however, special measures, such as availability of trained staff may be needed. Standard response sprinklers will have little impact.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.113-118
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• 2019

A solar power plant is a facility that produces electricity. As the risk of fire and electric shock accidents is diversified, the risk of workers, surrounding people, and facilities is increased, preventing safety accidents and promptly responding to safety accidents Is emerging. In light of the necessity of such development, it is necessary to develop a solar power generation management system that can diagnose and maintain the problems of the power generation system in real time by developing technologies for collecting and analyzing the data produced by the solar power generation system As a result, the utilization rate and the maintenance cost can be reduced. In order to do this, it is necessary to accurately predict the solar power generation amount in the present state, to diagnose the abnormality of the current power generation state and to grasp the abnormal position, and to use the model considering economical efficiency when the abnormal position is grasped, And the time and other information should be provided.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.493-519
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• 2021

The purpose of this study is to propose a plan to implement the comprehensive linking system centered on identifiers in order to provide seamless academic information services to researchers. To achieve this goal, interviews were conducted with 17 researchers from five centers and one secretariat belonging to KISTI. The contents of the interview are about the establishment and management status of the identifier of the academic information service DB. As a result of the interview, it was found that the identification rate for identifiers such as KOI was high in the case of domestic articles DB, but the identification rate for global identifiers such as ORCID was low in the case of foreign articles DB except for DOI. To solve this problem, this study proposes the council for joint use of a comprehensive linking system to build the comprehensive linking system model centered on identifiers. The joint use council will be organized around domestic academic information distribution institutions, and the council is expected to discover and implement new services through ID linkage by collecting foreign identifiers.

• Geomechanics and Engineering
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• v.31 no.6
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• pp.545-556
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• 2022

Evaluation and optimization of tunnel wall convergence (TWC) plays a vital role in preventing potential problems during tunnel construction and utilization stage. When convergence occurs at a high rate, it can lead to significant problems such as reducing the advance rate and safety, which in turn increases operating costs. In order to design an effective solution, it is important to accurately predict the degree of TWC; this can reduce the level of concern and have a positive effect on the design. With the development of soft computing methods, the use of deep learning algorithms and neural networks in tunnel construction has expanded in recent years. The current study aims to employ the long-short-term memory (LSTM) deep neural network predictor model to predict the TWC, based on 550 data points of observed parameters developed by collecting required data from different tunnelling projects. Among the data collected during the pre-construction and construction phases of the project, 80% is randomly used to train the model and the rest is used to test the model. Several loss functions including root mean square error (RMSE) and coefficient of determination (R²) were used to assess the performance and precision of the applied method. The results of the proposed models indicate an acceptable and reliable accuracy. In fact, the results show that the predicted values are in good agreement with the observed actual data. The proposed model can be considered for use in similar ground and tunneling conditions. It is important to note that this work has the potential to reduce the tunneling uncertainties significantly and make deep learning a valuable tool for planning tunnels.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.157-166
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• 2022

In the case of a die-casting process, defects that are difficult to confirm by visual inspection, such as shrinkage bubbles, may occur due to an error in maintaining a vacuum state. Since these casting defects are discovered during post-processing operations such as heat treatment or finishing work, they cannot be taken in advance at the casting time, which can cause a large number of defects. In this study, we propose an approach that can predict the occurrence of casting defects by defect type using machine learning technology based on casting parameter data collected from equipment in the die casting process in real time. Die-casting parameter data can basically be collected through the casting equipment controller. In order to perform classification analysis for predicting defects by defect type, labeling of casting parameters must be performed. In this study, first, the defective data set is separated by performing the primary clustering based on the total defect rate obtained during the post-processing. Second, the secondary cluster analysis is performed using the defect rate by type for the separated defect data set, and the labeling task is performed by defect type using the cluster analysis result. Finally, a classification learning model is created by collecting the entire labeled data set, and a real-time monitoring system for defect prediction using LabView and Python was implemented. When a defect is predicted, notification is performed so that the operator can cope with it, such as displaying on the monitoring screen and alarm notification.

• Journal of Korean Library and Information Science Society
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• v.55 no.1
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• pp.1-26
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• 2024

The purpose of this study is to derive an integration plan for bibliographic records by applying a duplicate verification algorithm to the item-based catalog in public libraries. To this, G Library, which was opened recently in Busan, was selected. After collecting OPAC data from G Library through web crawling, multipart monographs of Korean Literature (KDC 800) were selected and KERIS duplicate verification algorithm was applied. After two rounds of data correction based on the verification results, the duplicate verification rate increased by a total of 2.74% from 95.53% to 98.27%. Even after data correction, 24 books that were judged to be similar or inconsistent were identified as data from other published editions after receiving separate ISBN such as revised versions or hard copies. Through this, it was confirmed that the duplicate verification rate could be improved through catalog data correction work, and the possibility of using the KERIS duplicate verification algorithm as a tool to convert duplicate item-based records from public libraries into manifestation-based records was confirmed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.4
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• pp.22-32
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• 2013

Since the percentage of vehicles equipped with Hi-pass, an electronic toll collecting device, has increased rapidly, it is very crucial to determine the optimal location of Hi-pass lanes at a toll plaza in terms of traffic control and operation. In this study, the appropriateness of existing Hi-pass lanes of a toll plaza is evaluated considering its physical geometry and traffic characteristics. A new evaluating criterion called "traffic dispersion rate" is developed in order to measure the level of traffic spreading across the toll booth lanes at a toll plaza. Logistic regression models are constructed to estimate the relationship between the traffic dispersion rate and its affecting variables. The model estimation results show that several variables including Hi-pass lane traffic volume, length of toll plaza, entering/exiting taper lengths, and locations of Hi-pass lanes. The results also suggest that traffic dispersion rate can be increased by adjusting the location of Hi-pass lanes. The study enables us to quantify traffic dispersion rate which can be used to optimize the location and operation of Hi-pass lanes at toll plazas.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.4
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• pp.263-273
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• 2016

The effect of recirculated exhaust gas on performance and exhaust emissions with FGR rate are investigated by using a natural circulation, pressurized draft and water tube boiler with FGR system operating at several boiler loads and over fire air damper openings. The purpose of this study is to apply the FGR system to a power plant boiler for reducing $NO_x$ emissions. To activate the combustion, the OFA with 0 to 20% is supplied into the flame. When the suction damper of two stage combustion system installed in the upper side of wind box is opened by handling the lever between $0^{\circ}$ and $90^{\circ}$, also, the combustion air supplied to burner is changed. It is found that the fuel consumption rate per evaporation rate did not show an obvious tendency to increase or decrease with rising the FGR rate, and $NO_x$ emissions at the same OFA damper opening are decreased, as FGR rates are elevated and boiler loads are dropped. While a trace amount of soot is emitted without regard to the operation conditions of boiler load, OFA damper opening and FGR rate, because soot emissions are eliminated by the electrostatic precipitator with a collecting efficiency of 86.7%.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.893-903
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• 2018

The necessity of automatic precise georeferencing is increasing with the increase applications of high-resolution satellite imagery. One of the methods for collecting ground control points (GCPs) for precise georeferencing is to use chip images obtained by extracting a subset of an image map such as an ortho-aerial image, and can be automated using an image matching technique. In this case, the importance of the image matching success rate is increased due to the limitation of the number of the chip images for the known reference points such as the unified control point. This study aims to propose a method to improve the success rate of image matching between KOMPSAT-3A images and GCP chip images from aerial ortho-images. We performed the image matching with 7 cases of band pair using KOMPSAT-3A panchromatic (PAN), multispectral (MS), pansharpened (PS) imagery and GCP chip images, then compared matching success rates. As a result, about 10-30% of success rate is increased to about 40-50% when using PS imagery by using PAN and MS imagery. Therefore, using PS imagery for image matching of KOMPSAT-3A images and aerial ortho-images would be helpful to improve the matching success rate.