• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.2
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• pp.79-87
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• 2009

Pot experiments using sand culture were conducted in 2004 under greenhouse conditions to evaluate the effect of nitrogen deficiency on red pepper biomass. Nitrogen stress was imposed by implementing 6 levels (40% to 140%) of N in Hoagland's nutrient solution for red pepper. Canopy reflectance measurements were made with hand held spectral sensors including $GreenSeeker^{TM}$, $Crop\;Circle^{TM}$, and $Field\;Scout^{TM}$ Chlorophyll meter, and a spectroradiometer as well as Minolta SPAD-502 chlorophyll meter. Canopy reflectance and dry weight of red pepper were measured at five growth stages, the 30th, 40th, 50th, 80th and 120th day after planting(DAT). Dry weight of red pepper affected by nitrogen stress showed large differences between maximum and minimum values at the 120th DAT ranged from 48.2 to $196.6g\;plant^{-1}$, respectively. Several reflectance indices obtained from $GreenSeeker^{TM}$, $Crop\;Circle^{TM}$ and Spectroradiometer including chlorophyll readings were compared for evaluation of red pepper biomass. The reflectance indices such as rNDVI, aNDVI and gNDVI by the $Crop\;Circle^{TM}$ sensor showed the highest correlation coefficient with dry weight of red pepper at the 40th, 50th, and 80th DAT, respectively. Also these reflectance indices at the same growth station was closely correlated with dry weight, yield, and nitrogen uptake of red pepper at the 120th DAT, especially showing the best correlation coefficient at the 80th DAT. From these result, the aNDVI at the 80th DAT can significantly explain for dry weight of red pepper at the 120th DAT as well as for application level of nitrogen fertilizer. Consequently ground remote sensing as a non-destructive real-time assessment of plant nitrogen status was thought to be a useful tool for in season nitrogen management for red pepper providing both spatial and temporal information.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.77-86
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• 2018

For the past few years, KISTI has been servicing an online simulation execution platform, called EDISON, allowing users to conduct simulations on various scientific applications supplied by diverse computational science and engineering disciplines. Typically, these simulations accompany large-scale computation and accordingly produce a huge volume of output data. One critical issue arising when conducting those simulations on an online platform stems from the fact that a number of users simultaneously submit to the platform their simulation requests (or jobs) with the same (or almost unchanging) input parameters or files, resulting in charging a significant burden on the platform. In other words, the same computing jobs lead to duplicate consumption computing and storage resources at an undesirably fast pace. To overcome excessive resource usage by such identical simulation requests, in this paper we introduce a novel framework, called IceSheet, to efficiently manage simulation data based on execution metadata, that is, provenance. The IceSheet framework captures and stores each provenance associated with a conducted simulation. The collected provenance records are utilized for not only inspecting duplicate simulation requests but also performing search on existing simulation results via an open-source search engine, ElasticSearch. In particular, this paper elaborates on the core components in the IceSheet framework to support the search and reuse on the stored simulation results. We implemented as prototype the proposed framework using the engine in conjunction with the online simulation execution platform. Our evaluation of the framework was performed on the real simulation execution-provenance records collected on the platform. Once the prototyped IceSheet framework fully functions with the platform, users can quickly search for past parameter values entered into desired simulation software and receive existing results on the same input parameter values on the software if any. Therefore, we expect that the proposed framework contributes to eliminating duplicate resource consumption and significantly reducing execution time on the same requests as previously-executed simulations.

• The Journal of Korean Society for Radiation Therapy
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• v.21 no.1
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• pp.1-7
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• 2009

Purpose: The purpose is to evaluate the accuracy of correcting the targeting error through the Target Location System (TLS) for the location change error of the reference point which arises from the movement or motion of patient during the treatment using the CyberKnife. Materials and Methods: In this test, Gafchromic MD-55 film was inserted into the head and neck phantom to analyze the accuracy of the targeting, and then the 6 MV X-ray of CyberKnife (CyberKnife Robotic Radiosurgery System G4, Accuray, US) was irradiated. End to End (E2E) program was used to analyze the accuracy of targeting, which is provided by Accuray Corporation. To compute the error of the targeting, the test was carried out with the films that were irradiated 12 times by maintaining the distance within the rage of $0{\pm}0.2\;mm$ toward x, y, z from the reference point and maintaining the angle within the rage of $0{\pm}0.2^{\circ}$ toward roll, pitch, yaw, and then with the films which were irradiated 6 times by applying intentional movement. And the correlation in the average value of the reference film and the test film were analyzed through independent samples t-test. In addition, the consistency of dose distribution through gamma-index method (dose difference: 3%) was quantified, compared, and analyzed by varying the distance to agreement (DTA) to 1 mm, 1.5 mm, 2 mm, respectively. Results: E2E test result indicated that the average error of the reference film was 0.405 mm and the standard deviation was 0.069 mm. The average error of the test film was 0.413 mm with the standard deviation of 0.121 mm. The result of independent sampling t-test for both averages showed that the significant probability was P=0.836 (confidence level: 95%). Besides, by comparing the consistency of dose distribution of DTA through 1 mm, 1.5 mm, 2 mm, it was found that the average dose distribution of axial film was 95.04%, 97.56%, 98.13%, respectively in 3,314 locations of the reference film, consistent with the average dose distribution of sagittal film that was 95.47%, 97.68%, 98.47%, respectively. By comparing with the test film, it was found that the average dose distribution of axial film was 96.38%, 97.57%, 98.04%, respectively, at 3,323 locations, consistent with the average dose distribution of sagittal film which was 95.50%, 97.87%, 98.36%, respectively. Conclusion: Robotic CyberKnife traces and complements in real time the error in the location change of the reference point caused by the motion or movement of patient during the treatment and provides the accuracy with the consistency of over 95% dose distribution and the targeting error below 1 mm.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.73-94
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• 2010

The attending system is a medical system that allows doctors in clinics to use the extra equipment in hospitals-beds, laboratory, operating room, etc-for their patient's care under a contract between the doctors and hospitals. Therefore, the system is very beneficial in terms of the efficiency of the usage of medical resources. However, it is necessary to develop a strong support system to strengthen its weaknesses and supplement its merits. If doctors use hospital beds under the attending system of hospitals, they would be able to check a patient's condition often and provide them with nursing care services. However, the current attending system lacks delivery and assistance support. Thus, for the successful performance of the attending system, a networking system should be developed to facilitate communication between the doctors and nurses. In particular, the nursing records in the attending system could help doctors monitor the patient's condition and provision of nursing care services. A nursing record is the formal documentation associated with nursing care. It is merely a data repository that helps nurses to track their activities; nursing records thus represent a resource of primary information that can be reused. In order to maximize their usefulness, nursing records have been introduced as part of computerized patient records. However, nursing records are internal data that are not disclosed by hospitals. Moreover, the lack of standardization of the record list makes it difficult to share nursing records. Under the attending system, nurses would want to minimize the amount of effort they have to put in for the maintenance of additional records. Hence, they would try to maintain the current level of nursing records in the form of record lists and record attributes, while doctors would require more detailed and real-time information about their patients in order to monitor their condition. Therefore, this study developed a system for assisting in the maintenance and sharing of the nursing records under the attending system. In contrast to previous research on the functionality of computer-based nursing records, we have emphasized the practical usefulness of nursing records from the viewpoint of the actual implementation of the attending system. We suggested that nurses could design a nursing record dictionary for their convenience, and that doctors and nurses could confirm the definitions that they looked up in the dictionary through negotiations with intelligent agents. Such an agent-based system could facilitate networking among medical institutes. Multi-agent systems are a widely accepted paradigm for the distribution and sharing of computation workloads in the scientific community. Agent-based systems have been developed with differences in functional cooperation, coordination, and negotiation. To increase such communication, a framework for a multi-agent based system is proposed in this study. The agent-based approach is useful for developing a system that promotes trade-offs between transactions involving multiple attributes. A brief summary of our contributions follows. First, we propose an efficient and accurate utility representation and acquisition mechanism based on a preference scale while minimizing user interactions with the agent. Trade-offs between various transaction attributes can also be easily computed. Second, by providing a multi-attribute negotiation framework based on the attribute utility evaluation mechanism, we allow both the doctors in charge and nurses to negotiate over various transaction attributes in the nursing record lists that are defined by the latter. Third, we have designed the architecture of the nursing record management server and a system of agents that provides support to the doctors and nurses with regard to the framework and mechanisms proposed above. A formal protocol has also been developed to create and control the communication required for negotiations. We verified the realization of the system by developing a web-based prototype. The system was implemented using ASP and IIS5.1.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.954-961
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• 2010

Ground-based remote sensing can be used as one of the non-destructive, fast, and real-time diagnostic tools for quantifying yield, biomass, and nitrogen (N) stress during growing season. This study was conducted to assess biomass and nitrogen (N) status of paddy rice (Oryza sativa L.) plants under N stress using passive and active ground-based remote sensors. Nitrogen application rates were 0, 70, 100, and 130 kg N $ha^{-1}$. At each growth stage, reflectance indices measured with active sensor showed higher correlation with DW, N uptake and N concentration than those with the passive sensor. NIR/Red and NIR/Amber indices measured with Crop Circle active sensors generally had a better correlation with dry weight (DW), N uptake and N content than vegetation indices from Crop Circle passive sensor and NDVIs from active sensors. Especially NIR/Red and NIR/amber ratios at the panicle initiation stage were most closely correlated with DW, N content, and N uptake. Rice grain yield, DW, N content and N uptake at harvest were highly positively correlated with canopy reflectance indices measured with active sensors at all sampling dates. N application rate explains about 91~92% of the variability in the SI calculated from NIR/Red or NIR/Amber indices measured with Crop Circle active sensors on 12 July. Therefore, the in-season sufficiency index (SI) by NIR/Red or NIR/Amber index from Crop Circle active sensors can be used for determination of N application rate.

• Journal of Environmental Impact Assessment
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• v.30 no.4
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• pp.225-236
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• 2021

The master plan for the Four Rivers Restoration Project (June 2009) was devised, the procedure of pre-environmental review (June 2009) and environmental impact assessment (Nov. 2009), and post-environmental impact survey were implemented, and 4 times audits also inspected. and finally the Ministry of Environment's Four Rivers Investigation and Evaluation Planning Committee proposed the dismantling or partial dismantling of the five weirs of the Geum River and Yeongsan River. But controversies and conflicts are still ongoing. Therefore, this study intend to reestablish the management plan for the four major rivers by reviewing and analyzing the process so far. The results are as follows. First, a cost-benefit analysis should be performed by comparing the water quality impact of weir operation and weir opening. Therefore, it is inevitably difficult to conduct cost-benefit analysis. Second, according to the results of cost-benefit analysis on the dismantling of the Geum River and the Yeongsan River, the dismantling of the weir and the regular sluice gate opening was decided. However, there is a problem in the validity of the decision to dismantle the weir because the cost-benefit analysis for maintaining the weir is not carried out. Third, looking at the change in water quality of 16 weirs before and after the Four Major Rivers Restoration Project, COD and Chl-a were generally deteriorated, and BOD, SS, T-N, and T-P improved. However, in the cost-benefit analysis related to water quality at the time of weir dismantling, only COD items were targeted. Therefore, the cost of BOD, SS, T-N, and T-P items improved after the project were not reflected in the cost-benefit analysis of dismantling weirs, so the water quality benefits were exaggerated. Fourth, in the case of Gongju weir and Juksan weir, most of them are movable weirs, so opening the weir alone can have the same effect as dismantling when the water quality deteriorates. Since the same effect can be expected, there is little need to dismantle the weirs. Fifth, in order to respond to frequent droughts and floods, it is desirable to secure the agricultural water supply capacity to the drought areas upstream of the four majorrivers by constructing a waterway connected to the weir. At present it is necessary to keep weirs rather than dismantling them.

• The Journal of Korean Society for Radiation Therapy
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• v.33
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• pp.25-33
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• 2021

Purpose : The purpose of this study is to evaluate the accuracy and usefulness of the Trigger mode for the Respiratory Gated Radiation Therapy (RGRT) Materials and methods : A QUASAR respiratory phantom that inserted a 3 mm fiducial marker (a gold marker) was used to estimate the accuracy of the Trigger mode. And the 20 bpm was used as reference respiration rate in this study. The marker that placed at the center of the phantom was contoured, and the lower threshold of a gating window was fixed at 2.0 mm using an OBI with Truebeam STx^TM. The upper threshold was measured every 0.5 mm from 1.0 mm to 3.0 mm. The respiration rates were changed every 10 bpm from 10 bpm to 60 bpm. We repeatedly measured five times to check the error rate of the trigger mode in the same condition. Result : The differences of a distance from a peak phase to upper threshold, 1.0 to 3.0 mm at a 20 bpm as a reference for 3 days in a row were 0.68±0.05 mm, 0.91±0.03 mm, 1.23±0.03 mm, 1.42±0.04 mm, and 1.66±0.06 mm, respectively. Measurement result of changes in respiratory rate compared to baseline respiratory rate in maximum absolute difference. The coefficient of determination (R2) to estimate the correlation between the respiration velocity and variation of absolute difference was on average 0.838, 0.887, 0.770, 0.850, and 0.906. The p-values of all the variables were below 0.05. Conclusion : Using Trigger mode during respiratory gated radiation therapy (RGRT), accuracy and usefulness of trigger mode at reference breathing rate were confirmed. However, inaccuracies depending on the rate of breathing it could be uncertain in case of respiration rate is faster than 20 bpm as a standard respiration rate compared to slower than 20 bpm. Consequently, when conducting a RGRT using the trigger mode, real time monitoring is required with well educated respiration.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1827-1836
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• 2022

Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.231-238
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• 2023

Since there is a limit to the physically visible horizon that sensors for autonomous driving can perceive, complementary utilization of digital map data such as a Local Dynamic Map (LDM) along the probable route of an Autonomous Vehicle (AV) is proposed for safe and efficient driving. Although the amount of digital map data may be insignificant compared to the amount of information collected from the sensors of an AV, efficient management of map data is inevitable for the efficient information processing of AVs. The objective of this study is to analyze the efficiency of information use and information processing time of AV according to the expansion of the active section of LDM-based static road and traffic information. To carry out this objective, a microscopic simulator model, VISSIM and VISSIM COM, was employed, and an area of about 9 km × 13 km was selected in the Busan Metropolitan Area, which includes heterogeneous traffic flows (i.e., uninterrupted and interrupted flows) as well as various road geometries. In addition, the LDM information used in AVs refers to the real high-definition map (HDM) built on the basis of ISO 22726-1. As a result of the analysis, as the electronic horizon area increases, while short links are intensively recognized on interrupted urban roads and the sum of link lengths increases as well, the number of recognized links is relatively small on uninterrupted traffic road but the sum of link lengths is large due to a small number of long links. Therefore, this study showed that an efficient range of electronic horizon for HDM data collection, processing, and management are set as 600 m on interrupted urban roads considering the 12 links corresponding to three downstream intersections and 700 m on uninterrupted traffic road associated with the 10 km sum of link lengths, respectively.