• Structural Engineering and Mechanics
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• v.71 no.6
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• pp.739-749
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• 2019

This article deals with the application of reliability analysis for determining the safety of simply supported beam under the uniformly distributed load. The uncertainties of the existing methods were taken into account and hence reliability analysis has been adopted. To accomplish this aim, Generalized Regression Neural Network (GRNN), Extreme Learning Machine (ELM) and Gaussian Process Regression (GPR) models are developed. Reliability analysis is the probabilistic style to determine the possibility of failure free operation of a structure. The application of probabilistic mathematics into the quantitative aspects of a structure and improve the qualitative aspects of a structure. In order to construct the GRNN, ELM and GPR models, the dataset contains Modulus of Elasticity (E), Load intensity (w) and performance function (${\delta}$) in which E and w are inputs and ${\delta}$ is the output. The achievement of the developed models was weighed by various statistical parameters; one among the most primitive parameter is Coefficient of Determination ($R^2$) which has 0.998 for training and 0.989 for testing. The GRNN outperforms the other ELM and GPR models. Other different statistical computations have been carried out, which speaks out the errors and prediction performance in order to justify the capability of the developed models.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.257-269
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• 2021

Intellectual capital is becoming a crucial factor for a firm's long-term profit and performance in the knowledge-based economy as more firms identify their core competence as invisible assets rather than visible assets (Itami, 1987). The company was encouraged to measure financial and non-financial factors, including the customer perspective groups, the internal business process, learning and growth perspective, then to link all these measurements in a coherent system. This paper seeks to investigate the influence of intellectual capital elements on company performance, as well as the relationship among intellectual capital elements from a cause-effect perspective. Resource-Based View (RBV) considers intellectual capital as resource and capability to sustain competitive advantage on company performance. The partial least squares approach is used to examine listed banks in Indonesia Stock Exchange for year 2017-2019. Results show that human capital directly has positive influences on innovation capital, customer capital, and process capital. Innovation capital has positive, but less significant influence on process capital, which in turn influences customer capital. Human capital and process capital also influence customer capital. Finally, customer capital contributes to performance. This study helps management to identify relevant intellectual capital elements as competitive advantage and their indicators to enhance business performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.933-935
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• 2013

국내 시스템 구축(System Integration) 및 유지보수(System Maintenance) 사업은 긴 사업 기간과 함께 하나의 사업을 다양한 업체와 함께 협력하여 개발을 하며 운영되고 있다. 이 중 대형 IT서비스업체는 컨설팅 및 제안을 통해 고객의 업무와 요구사항을 파악하며, 프로젝트를 이끌기 위해 방법론을 적용하여 사업 체계 관리 및 운영을 주로 담당한다. 그런데 이와 같은 관리 위주의 사업을 진행함으로써 임직원들의 개발 역량 부족 문제가 발견되고, 이것은 시스템에 대한 이해도 부족으로 다양한 업체와 협력하는데 있어 커뮤니케이션 문제로 직결되어 시스템의 품질 및 결함에 영향을 주기 때문에 이에 대한 대책 및 예방활동이 필요하다. 또한, 작은 국내 시장에서는 이미 경쟁이 심화 되어 포화 되었으며, 대부분의 IT서비스기업은 SI사업에서 솔루션사업으로 변모하기 위해 노력 중이고 국내 시장에서 해외 시장으로 눈을 돌리고 있으므로 직원들에 대한 기술 역량이 시급한 실정이다. 이와 같은 상황에 기업은 준비가 미흡할 뿐만 아니라 해당 활동을 수행하기 위한 필요한 지식 및 방법을 익히는데 어려움이 있는 상황이다. 본 논문에서는 이러한 상황을 극복하기 위해 대형 IT서비스업체에서 진행된 개발역량강화 학습조직 적용 사례에 대해 소개를 하고, 이에 대한 효과 검증을 해보고자 한다.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.20 no.2
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• pp.209-229
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• 2022

This work provided a review of three techniques-(1) spectrochemical, (2) electrochemical, and (3) spectroelectrochemical-for molten salt medias. A spectroelectrochemical system was designed by utilizing this information. Here, we designed a spectroelectrochemical cell (SEC) and calibrated temperature controllers, and performed initial tests to explore the system's capability limit. There were several issues and a redesign of the cell was accomplished. The modification of the design allowed us to assemble, align the system with the light sources, and successfully transferred the setup inside a controlled environment. A preliminary run was executed to obtain transmission and absorption background of NaCl-CaCl₂ salt at 600℃. It shows that the quartz cuvette has high transmittance effects across all wavelengths and there were lower transmittance effects at the lower wavelength in the molten salt media. Despite a successful initial run, the quartz vessel was mated to the inner cavity of the SEC body. Moreover, there was shearing in the patch cord which resulted in damage to the fiber optic cable, deterioration of the SEC, corrosion in the connection of the cell body, and fiber optic damage. The next generation of the SEC should attach a high temperature fiber optic patch cords without introducing internal mechanical stress to the patch cord body. In addition, MACOR should be used as the cell body materials to prevent corrosion of the surface and avoid the mating issue and a use of an adapter from a manufacturer that combines the free beam to a fiber optic cable should be incorporated in the future design.

• Journal of Drive and Control
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• v.19 no.4
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• pp.97-103
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• 2022

Low fertility rates and increased life expectancy further exacerbate the process of an aging society. This is also reflected in the gradual increase in the proportion of vulnerable groups in the social population. The demand for improved mobility among vulnerable groups such as the elderly or the disabled has greatly driven the growth of the electric-assisted mobility device market. However, such mobile devices generally require a certain operating capability, which limits the range of vulnerable groups who can use the device and increases the cost of learning. Therefore, autonomous driving technology needs to be introduced to make mobility easier for a wider range of vulnerable groups to meet their needs of work and leisure in different environments. This study uses mini PC Odyssey, Velodyne Lidar VLP-16, electronic device and Linux-based ROS program to realize the functions of working environment recognition, simultaneous localization, map generation and navigation of electric powered mobile devices for vulnerable groups. This autonomous driving mobility device is expected to be of great help to the vulnerable who lack the immediate response in dangerous situations.

• Smart Structures and Systems
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• v.29 no.4
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• pp.523-533
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• 2022

A novel metaheuristic search method, namely black widow optimization (BWO) is employed to increase the accuracy of slope stability analysis. The BWO is a recently-developed optimizer that supervises the training of an artificial neural network (ANN) for predicting the factor of safety (FOS) of a single-layer cohesive soil slope. The designed slope bears a loaded foundation in different distances from the crest. A sensitivity analysis is conducted based on the number of active individuals in the BWO algorithm, and it was shown that the best performance is acquired for the population size of 40. Evaluation of the results revealed that the capability of the ANN was significantly enhanced by applying the BWO. In this sense, the learning root mean square error fell down by 23.34%. Also, the correlation between the testing data rose from 0.9573 to 0.9737. Therefore, the postposed BWO-ANN can be promisingly used for the early prediction of FOS in real-world projects.

• Educational Technology International
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• v.23 no.2
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• pp.157-181
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• 2022

Scale scores for cognitive domains have been used as an important indicator for both academic achievement and clinical diagnosis. For example, in education, Cognitive Abilities Test (CogAT) has been used to measure student's capability in academic learning. In a clinical setting, Cognitive Impairment Screening Test utilizes items measuring cognitive ability as a dementia screening test. We demonstrated a procedure of generating cognitive ability test items similar as in CogAT but the theory associated with the generation is totally different. When creating cognitive test items, we applied automatic item generation (AIG) that reduces errors in predictions of cognitive ability but attains higher reliability. We selected two cognitive ability test items, categorized as a time estimation item for measuring quantitative reasoning and a paper-folding item for measuring visualization. As CogAT has widely used as a cognitive measurement test, developing an AIG-based cognitive test items will greatly contribute to education field. Since CLASS is the only LMS including AIG technology, we used it for the AIG software to construct item models. The purpose of this study is to demonstrate the item generation process using AIG implemented within CLASS, along with proving quantitative and qualitative strengths of AIG. In result, we confirmed that more than 10,000 items could be made by a single item model in the quantitative aspect and the validity of items could be assured by the procedure based on ECD and AE in the qualitative aspect. This reliable item generation process based on item models would be the key of developing accurate cognitive measurement tests.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.412-434
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• 2023

This study discusses the high-order diffusion method in the wavelet domain. It aims to improve the edge protection capability of the high-order diffusion method using wavelet coefficients that can reflect image information. During the first step of the proposed diffusion method, the wavelet packet decomposition is a more refined decomposition method that can extract the texture and structure information of the image at different resolution levels. The high-frequency wavelet coefficients are then used to construct the edge detection function. Subsequently, because accurate wavelet coefficients can more accurately reflect the edges and details of the image information, by introducing the idea of state weight, a scheme for recovering wavelet coefficients is proposed. Finally, the edge detection function is constructed by the module of the wavelet coefficients to guide high-order diffusion, the denoised image is obtained. The experimental results showed that the method presented in this study improves the denoising ability of the high-order diffusion model, and the edge protection index (SSIM) outperforms the main methods, including the block matching and 3D collaborative filtering (BM3D) and the deep learning-based image processing methods. For images with rich textural details, the present method improves the clarity of the obtained images and the completeness of the edges, demonstrating its advantages in denoising and edge protection.

• Structural Engineering and Mechanics
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• v.87 no.6
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• pp.555-574
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• 2023

An efficient optimization algorithm and damage-sensitive objective function are two main components in optimization-based Finite Element Model Updating (FEMU). A suitable combination of these components can considerably affect damage detection accuracy. In this study, a new hybrid damage-sensitive objective function is proposed based on combining two different objection functions to detect the location and extent of damage in structures. The first one is based on Generalized Pseudo Modal Strain Energy (GPMSE), and the second is based on the element's Generalized Flexibility Matrix (GFM). Four well-known population-based metaheuristic algorithms are used to solve the problem and report the optimal solution as damage detection results. These algorithms consist of Cuckoo Search (CS), Teaching-Learning-Based Optimization (TLBO), Moth Flame Optimization (MFO), and Jaya. Three numerical examples and one experimental study are studied to illustrate the capability of the proposed method. The performance of the considered metaheuristics is also compared with each other to choose the most suitable optimizer in structural damage detection. The numerical examinations on truss and frame structures with considering the effects of measurement noise and availability of only the first few vibrating modes reveal the good performance of the proposed technique in identifying damage locations and their severities. Experimental examinations on a six-story shear building structure tested on a shake table also indicate that this method can be considered as a suitable technique for damage assessment of shear building structures.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.637-639
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• 2003

As the number of spectral bands of high spectral resolution data increases, the capability to detect more detailed classes should also increase, and the classification accuracy should increase as well. Often, it is impossible to access enough training pixels for supervise classification. For this reason, the performance of traditional classification methods isn't useful. In this paper, we propose a new model for classification that operates based on decision fusion. In this classifier, learning is performed at two steps. In first step, only training samples are used and in second step, this classifier utilizes semilabeled samples in addition to original training samples. At the beginning of this method, spectral bands are categorized in several small groups. Information of each group is used as a new source and classified. Each of this primary classifier has special characteristics and discriminates the spectral space particularly. With using of the benefits of all primary classifiers, it is made sure that the results of the fused local decisions are accurate enough. In decision fusion center, some rules are used to determine the final class of pixels. This method is applied to real remote sensing data. Results show classification performance is improved, and this method may solve the limitation of training samples in the high dimensional data and the Hughes phenomenon may be mitigated.