• Korean Journal of Construction Engineering and Management
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• v.14 no.5
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• pp.35-43
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• 2013

Nowadays the widely used media in architecture include visualizations, animations and three-dimensional models. 3D digital methods using active CAM(Computer Aided Manufacturing) and CNC(Computerized Numerical Control) imaging have been developed for accurate shape and 3D measurements in freeform buildings. In contrast to a conventional building using auto CAD system and others, the proposed digital optimization method is based on a combination of 3D numerical data and parametric 3D model for design and construction. The objective of this paper is therefore to present digital optimization process for constructability of freeform building. The method can be useful in the effective implementation of an error-proofing process of freeform building during design and construction phase. 3D digital coordinate data can be used effectively to identify correct size of structural and finish members and installation location of each members in construction field. In addition, architects, engineers and contractors can evaluate design, materials, constructability and identify error-proofing opportunities. Other project participants can also include representatives from all levels of management, departments as well as workers and key subcontractors' personnel, if necessary. The 3D digital optimization process is therefore appropriate to serious variations in freeform shape. For future study, the developed digital optimization method is necessary to be carried out to verify the robustness and accuracy for constructability in construction field.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.969-976
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• 2020

Urban Air Mobility is attracting attention as a future innovation industry around the world, and leading industries are considering the application of composite materials for structural robustness and lightening in the designing and manufacturing new concept eVTOL aircraft. To apply composite materials to the new concept of eVTO aircraft, this paper was analyzed about composite material qualification system of FAA & EASA and institutionalized by Korea Government, including the procedures and methods, the organization to carry out the material verification for domestic conditions. The domestic composite material qualification system will not only make it easier for manufacturers of eVTOL aircraft with a new concept to apply composite materials to domestic aircraft through pre-material qualification, but also reduce the burden of material qualification within the period of type certification. In addition, domestic manufacturers of composite materials with qualified material quality and performance will be easy to enter for domestic aircraft applications and composite material manufacturers with experience in applying to aircraft will have a positive impact on overseas exports. This system will be able to promote the development eVTOL aircraft industry of a new concept and enhance international credibility of made aircraft in Korea.

• Journal of the Korea Institute of Building Construction
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• v.23 no.5
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• pp.537-546
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• 2023

For the purpose of fire delineation within buildings, steel walls in Korea are mandated to undergo rigorous certification as fire-resistant entities, substantiated via a series of qualitative assessments. Predominantly, these evaluations comprise the fire resistance test paired with supplementary examinations; specifically for steel walls, these encompass the gas hazard and panel bending strength tests. Given the prevalence of semi-noncombustible core materials, gas hazard tests are largely rendered superfluous, pivoting the focus solely onto the panel bending strength test during the certification trajectory. This particular test is designed to gauge the flexural robustness of individual wall panels. An enhanced bending strength is postulated to fortify both the structural integrity and thermal insulation of the wall by mitigating potential deformations. In this scholarly exploration, an analytical deep dive was undertaken into extant, valid certification test datasets. The endeavor aimed to ascertain the depth of correlation between the designated fire resistance metric and the bending strength, the latter being the sole supplementary assessment for steel walls. In distilling the findings, it was discerned that temperature elevations beyond baseline values exhibited no statistically salient linkage with the panel's bending strength.

• 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.

• Information Systems Review
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• v.14 no.3
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• pp.75-97
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• 2012

Fostering trusting belief in financial transactions is a challenging task in Internet banking services. Authenticated Certificate had been regarded as an effective method to guarantee the trusting belief for online transactions. However, previous research claimed that this method has some loopholes for such abusers as hackers, who intend to attack the financial accounts of innocent transactors in Internet. Two types of methods have been suggested as alternatives for securing user identification and activity in online financial services. Control transparency uses information over the transaction process to verify and to control the transactions. Outcome feedback, which refers to the specific information about exchange outcomes, provides information over final transaction results. By using these two methods, financial service providers can send signals to involved parties about the robustness of their security mechanisms. These two methods-control transparency and outcome feedback-have been widely used in the IS field to enhance the quality of IS services. In this research, we intend to verify that these two methods can also be used to reduce risks and to increase the security protections in online banking services. The purpose of this paper is to empirically test the effects of the control transparency and the outcome feedback on the risk perceptions in Internet banking services. Our assumption is that these two methods-control transparency and outcome feedback-can reduce perceived risks involved with online financial transactions, while increasing perceived trust over financial service providers. These changes in user attitudes can increase the level of user satisfactions, which may lead to the increased user loyalty as well as users' willingness to pay for the financial transactions. Previous research in IS suggested that the increased level of transparency on the process and the result of transactions can enhance the information quality and decision quality of IS users. Transparency helps IS users to acquire the information needed to control the transaction counterpart and thus to complete transaction successfully. It is also argued that transparency can reduce the perceived transaction risks in IS usage. Many IS researchers also argued that the trust can be generated by the institutional mechanisms. Trusting belief refers to the truster's belief for the trustee to have attributes for being beneficial to the truster. Institution-based trust plays an important role to enhance the probability of achieving a successful outcome. When a transactor regards the conditions crucial for the transaction success, he or she considers the condition providers as trustful, and thus eventually trust the others involved with such condition providers. In this process, transparency helps the transactor complete the transaction successfully. Through the investigation of these studies, we expect that the control transparency and outcome feedback can reduce the risk perception on transaction and enhance the trust with the service provider. Based on a theoretical framework of transparency and institution-based trust, we propose and test a research model by evaluating research hypotheses. We have conducted a laboratory experiment in order to validate our research model. Since the transparency artifact(control transparency and outcome feedback) is not yet adopted in online banking services, the general survey method could not be employed to verify our research model. We collected data from 138 experiment subjects who had experiences with online banking services. PLS is used to analyze the experiment data. The measurement model confirms that our data set has appropriate convergent and discriminant validity. The results of testing the structural model indicate that control transparency significantly enhances the trust and significantly reduces the risk perception of online banking users. The result also suggested that the outcome feedback significantly enhances the trust of users. We have found that the reduced risk and the increased trust level significantly improve the level of service satisfaction. The increased satisfaction finally leads to the increased loyalty and willingness to pay for the financial services.