• Journal of applied mathematics & informatics
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• v.28 no.5_6
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• pp.1055-1071
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• 2010

Recently, a number of algorithms have been proposed for numerical evaluation of Hankel transforms as these transforms arise naturally in many areas of science and technology. All these algorithms depend on separating the integrand $rf(r)J_{\upsilon}(pr)$ into two components; the slowly varying component rf(r) and the rapidly oscillating component $J_{\upsilon}(pr)$. Then the slowly varying component rf(r) is expanded either into a Fourier Bessel series or various wavelet series using different orthonormal bases like Haar wavelets, rationalized Haar wavelets, linear Legendre multiwavelets, Legendre wavelets and truncating the series at an optimal level; or approximating rf(r) by a quadratic over the subinterval using the Filon quadrature philosophy. The purpose of this communication is to take a different approach and replace rapidly oscillating component $J_{\upsilon}(pr)$ in the integrand by its Bernstein series approximation, thus avoiding the complexity of evaluating integrals involving Bessel functions. This leads to a very simple efficient and stable algorithm for numerical evaluation of Hankel transform.

• Structural Engineering and Mechanics
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• v.91 no.5
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• pp.443-457
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• 2024

At present, the traditional concrete surface inspection methods based on artificial vision have the problems of high cost and insecurity, while the computer vision methods rely on artificial selection features in the case of sensitive environmental changes and difficult promotion. In order to solve these problems, this paper introduces deep learning technology in the field of computer vision to achieve automatic feature extraction of structural damage, with excellent detection speed and strong generalization ability. The main contents of this study are as follows: (1) A method based on DeepLabV3+ convolutional neural network model is proposed for surface detection of post-earthquake structural damage, including surface damage such as concrete cracks, spaling and exposed steel bars. The key semantic information is extracted by different backbone networks, and the data sets containing various surface damage are trained, tested and evaluated. The intersection ratios of 54.4%, 44.2%, and 89.9% in the test set demonstrate the network's capability to accurately identify different types of structural surface damages in pixel-level segmentation, highlighting its effectiveness in varied testing scenarios. (2) A semantic segmentation model based on DeepLabV3+ convolutional neural network is proposed for the detection and evaluation of post-earthquake structural components. Using a dataset that includes building structural components and their damage degrees for training, testing, and evaluation, semantic segmentation detection accuracies were recorded at 98.5% and 56.9%. To provide a comprehensive assessment that considers both false positives and false negatives, the Mean Intersection over Union (Mean IoU) was employed as the primary evaluation metric. This choice ensures that the network's performance in detecting and evaluating pixel-level damage in post-earthquake structural components is evaluated uniformly across all experiments. By incorporating deep learning technology, this study not only offers an innovative solution for accurately identifying post-earthquake damage in civil engineering structures but also contributes significantly to empirical research in automated detection and evaluation within the field of structural health monitoring.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.06a
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• pp.147-148
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• 2009

Today, overall industry have been operated on the basis of information technology and have been rised that expectation and investment on it. The distribution industry have growing up importance of integrated material handling information network, the information investment have increase to efficient operate. however, Most efficiency analysis has not been thoroughgoing enough any research that effect on informatization level about the efficiency. The paper describes the evaluation of informatization level of importance is presented to efficient operate in a container terminal, the relative efficiency on informatization level is measured using Data Envelopment Analysis.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.4
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• pp.633-641
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• 2021

The study performed long-term performacne evaluation on the hot mix asphalt using the steel slag aggregates and Reclaimed Asphalt Pavement (RAP). The laboratory comparative evaluation was conducted between conventional Hot Mix Asphalt (HMA) which is entitled WC-2 and HMA containing steel slag and RAP which is entitled ES WC-2(R). Dynamic stability test, dynamic modulus test, and fatigue crack test were conducted during the comparative evaluation process. The dynamic stability test result showed that ES WC-2(R) was 140% higher than WC-2. It is noted that ES WC-2(R) showed no inflection point whereas WC-2 showed inflection point during the dynamic stability test which implies ES WC-2(R) has the higher moisture susceptability than WC-2. The dynamic modulus of ES WC-2(R) were 342.3%, 486.7%, and 350.0% higher than WC-2 at medium temperature of 21℃, low temperature of -10℃, and high temperature of 38℃ respectively. The test result showed that rutting resistance of ES WC-2(R) is higher than WC-2 at all temperature spectrum. The fatigue resistance of ES WC-2(R) were 31.7%, 325.3%, 899.9% higher at low stress level, medium stress level, and high stress level, respectively. The test result showed that ES WC-2(R) is higher than WC-2 at all stress levels. Based on the laboratory comparative evaluation, The in-situ scale Accelerated Pavement Test (APT) was conducted comparing WC-2 and WC-2(R). APT found that the rutting resistance of WC-2(R) was 45% higher than WC-2.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.191-204
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• 2011

Recently, many software companies are trying to improve the software quality and project outcome with more costs and efforts in development time. In the software convergence and integration environments, it is required efforts to gain high quality of software. In other words, it is required to utilize software engineering knowledge and technology for higher software quality and better software project productivity. The Software development productivity can be varied by software process capability according to building a framework for software development, selection and use of appropriate technology, human resource management. Software process capability will influence software project outcome which is the general opinion. This study provides empirical evidence about software engineering efforts and investment approach to lead software project performance. We measured the software engineering efforts by SW engineering level and analyzed the corelation between software engineering level and schedule deviation. And, we verified that this performance is affected by the size of software company. As a result, software process capability is important to build a infrastructure and develop systematically software project. The higher software engineering level can lead to improved software project performance.

• Korean Journal of Food Science and Technology
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• v.44 no.2
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• pp.247-250
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• 2012

Raw milk samples (n=28) obtained from milk tanks in 3 dairy plants of different regions and commercial milks (n=100) were collected from six cities. These samples were analyzed for the level of aflatoxin $M_1$ contamination using immunoaffinity columns and high performance liquid chromatography coupled with fluorescent detectors. Confirmation of aflatoxin $M_1$ ($AFM_1$) identified in positive samples was based on the formation of the hemiacetal derivative ($AFM_{2a}$) after derivatization with trifluroacetic acid. The average concentrations of aflatoxin $M_1$ in the raw milks were 25.1 ng/kg, and those values in commercial milks were 29.8 ng/kg. The highest level of aflatoxin $M_1$ in milk was 72.7 ng/kg. These results showed that the contamination of aflatoxin $M_1$ in milks consumed in the Korea was quite low compared to the standard in Korea Food Code (aflatoxin $M_1$ 500 ng/kg).

• Nuclear Engineering and Technology
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• v.35 no.6
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• pp.556-565
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• 2003

A quality assurance safety assessment database, called QUARK (QUality Assurance Program for Radioactive Waste Management in Korea), has been developed to manage both analysis information and parameter database for safety assessment of low- and intermediate-level radioactive waste (LILW) disposal facility in Korea. QUARK is such a tool that serves QA purposes for managing safety assessment information properly and securely. In QUARK, the information is organized and linked to maximize the integrity of information and traceability. QUARK provides guidance to conduct safety assessment analysis, from scenario generation to result analysis, and provides a window to inspect and trace previous safety assessment analysis and parameter values. QUARK also provides default database for safety assessment staff who construct input data files using SAGE(Safety Assessment Groundwater Evaluation), a safety assessment computer code.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.4
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• pp.91-103
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• 2006

This paper proposes a methodology to evaluate the quality and level of difficulty of fingerprint image databases, which leads to objective evaluation for the performance of fingerprint recognition system. Influencing factors to fingerprint matching are defined and the matching performance between two fingerprint images is evaluated using segmentation and orientation filed. In this study, a hierarchical processing method is proposed to measure an orientation field, which is able to improve the matching speed and accuracy. The results of experiments demonstrate that the defined influencing factors can describe the characteristics of fingerprint databases. Level of difficulty for fingerprint databases enables the performance of fingerprint recognition algorithms to be evaluated and compared even with different databases.

• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.45-49
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• 2024

Blockchain has gone beyond the proof-of-concept level and is converging with various industries and fields, moving toward the service development and commercialization stage. However, although various blockchain technologies and services are emerging, their development is quite slow and their widespread application to various industries is difficult. Accordingly, it is necessary to identify areas with high introduction utility when applying blockchain services in actual industries and to develop a method to evaluate the utility of blockchain services for this purpose. This paper proposes a framework for evaluating the utility of blockchain services using a multi-criteria decision-making model. Through a case study on the utility evaluation of blockchain services, the proposed framework was applied to domestic and foreign blockchain services to evaluate its utility and verify its applicability. It is expected that the proposed framework will be able to identify industrial and functional characteristics where actual blockchain services can be introduced and demonstrate effective utility and can be used to develop blockchain services in various industrial fields.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.409-414
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• 2024

This paper utilizes artificial intelligence to analyze vocational training evaluation data for people with disabilities and selects the optimal prediction model using various machine learning algorithms. It predicts the job categories most likely to employ trainees based on data such as gender, age, education level, type of disability, and basic learning abilities. The goal is to design customized training programs based on these predictions to enhance training efficiency and employment success rates.