• Journal of Acupuncture Research
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• v.39 no.2
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• pp.77-88
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• 2022

The purpose of this review was to identify research trends in acupuncture training systems and models and to analyze acupuncture training using phantom models. Articles on acupuncture training were retrieved from domestic and foreign electronic databases (PubMed, CNKI, CiNii, NDSL, KISS, RISS and KMBase). The search included studies conducted from January 1, 2010 to October 1, 2021. Acupuncture training was analyzed by categorization into acupoint location training and needling training. Acupuncture training was most frequently studied in China, acupoint location training was the most studied in 2012, and needling training was the most studied in 2013 and 2020. Among them, a silicone model with a sensor was used for training in acupoint location, and silicone and agarose gel were frequently used for needling training. Classifications of the phantom models for needling training by topic included phantom development, phantom-based education and evaluation system, phantom-based quantitative measurement, comparison of kinematic characteristics of hand motion between experts and beginners, and phantom models for acupoint location and needling training. Further research on the development of acupuncture practice training systems to improve practical skills is needed.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.04a
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• pp.233-240
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• 2000

Nuclear power plant structures may be exposed to aggressive environmental effects than may cause their strength and stiffness to decrease over their service lives, Although the physics of these damage mechanisms are reasonably well understood and quantitative evaluation of their effects on time-dependent structural behavior is possible in some instances such evaluations are generally very difficult and remain novel. The assessment of existing RC containment in nuclear power plants for continued service must provide quantitative evidence that they are able to withstand future extreme loads during a service period with an acceptable level of reliability. Rational methodologies to perform the reliability assessment can be developed from mechanistic models of structural deterioration using time-dependent structural reliability analysis to take earthquake loading uncertainties into account. The final goal of this study is to develop the reliability analysis of RC containment structures. The cause of the degrading is first clarified and the reliability assessment has been conducted. By introducing stochastic analysis based on random vibration theory the reliability analysis which can determine the failure probabilities has been established.

• Journal of Information Display
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• v.5 no.3
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• pp.35-40
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• 2004

In this study, we collected data used to formulate the relationship between quantitative metrological parameters in CRT display and the perceived focus quality. Human perception of the focusing quality was evaluated in terms of user feedback scores regarding the character legibility from four highly trained inspectors. Thirteen CRT monitors from five different manufacturers were compared relatively with respect to the norm monitor. The profile of electron beam such as spot size and the shape of distribution made by electron beam, contrast, convergence of RGB beams, and luminance characteristics were measured using a precision measurement system. Linear regression analysis and artificial neural network models were used to formulate the relationship between human perception and the quantitative measurements. The accuracy of the formulated linear regression model ($R^2$=0.515) was not satisfactory but the nonlinear neural network model ($R^2$=0.716) was fairly convincing and robust even the utilized data included subjective differences.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.229-232
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• 1999

Nuclear power plant structures may be exposed to aggressive environmental effects that may cause their damage mechanisms are reasonably well understood and quantitative evaluation of their effects on time-dependent structural behavior is possible in some instances, such evaluations are generally very difficult and remain novel. The assessment of existing steel containment in nuclear power plants for continued service must provide quantitative evidence that they are able to withstand future extreme loads during a service period with an acceptable level of reliability. Rational methodologies to perform the reliability assessment can be developed from mechanistic models of structural deterioration, using time-dependent structural reliability analysis to take loading and strength uncertainties into account. The final goal of this study is to develop the analysis method for the analysis for the reliability of containment structures. The cause and mechanism of corrosion is first clarified and the reliability assessment method has been established. By introducing the equivalent normal distribution, the procedure of reliability analysis which can determine the failure probabilities has been established.

• The Journal of Economics, Marketing and Management
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• v.10 no.5
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• pp.1-6
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• 2022

Purpose: To overcome the question that depends too much on expert's subjective judgment in traditional risk identification, this paper structure the multilevel generalized fuzzy comprehensive evaluation mathematics model of the risk identification of project, to research the risk identification of the project. Research design, data and methodology: This paper constructs the multilevel generalized fuzzy comprehensive evaluation mathematics model. Through iterative algorithm of AHP analysis, make sure the important degree of the sub project in risk analysis, then combine expert's subjective judgment with objective quantitative analysis, and distinguish the risk through identification models. Meanwhile, the concrete method of multilevel generalized fuzzy comprehensive evaluation is probed. Using the index weights to analyse project risks is discussed in detail. Results: The improved fuzzy comprehensive evaluation algorithm is proposed in the paper, at first the method of fuzzy sets core is used to optimize the fuzzy relation matrix. It improves the capability of the algorithm. Then, the method of entropy weight is used to establish weight vectors. This makes the computation process fair and open. And thereby, the uncertainty of the evaluation result brought by the subjectivity can be avoided effectively and the evaluation result becomes more objective and more reasonable. Conclusions: In this paper, we use an improved fuzzy comprehensive evaluation method to evaluate a railroad engineering project risk. It can give a more reliable result for a reference of decision making.

• KIEAE Journal
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• v.4 no.4
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• pp.61-68
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• 2004

Daylight is a critical factor in architecture, as it helps enhance the working efficiency and pleasantness of the people working inside, in addition to reduce the power consumption in heating and cooling and make the interior space brighter. There are many kinds of glazing and daylighting systems. At present, research and efforts for their development are carried out, alongside quantitative evaluation. This study aims to present basic materials to be used to design proper glazing and daylighting systems in architecture based on a quantitative evaluation by scale models of existing office buildings. The result of the study can be summarized as follows. 1)As a result of the experiment, it appeared that the ratio of the interior illumination (i.e. at the working table, ceiling and wall) against the outdoor illumination increases at a constant rate, as the transmittance of the glazing goes up. 2) It was found that the SIR(Sunlight Illuminance Ratio) of a separated window system goes up by 20-50% at the rear part than in the case of an ordinary window system.

• Korean Institute of Interior Design Journal
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• v.14 no.2 s.49
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• pp.217-224
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• 2005

The lack of objective decisive criteria and the absence of analyzing tools accrued from the experiments on various types developed from space design process makes it difficult to select and execute alternatives for them. As an attempt of coping with these problems, the aims of this study is to establish space analysis' models and to propose possibility of analyzing models by utilizing the technology of image process. It is now under study in the field of artificial intelligence based on the accomplishment of digital images. This study focused on establishment an analysis model based on accomplished digital images and image processing framework. It helps utilize various processing technologies that are currently in use of image processes, and problems of the study can be supplemented through further follow-up studies. Finally, analysis model can be constructed gradually huge design data in the analogue data to the digital image database and be proposed with index in design or evaluation step.

• Journal of Mechanical Science and Technology
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• v.17 no.5
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• pp.668-678
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• 2003

For the purpose to facilitate development of high-speed spindle units (SUs) running on rolling bearings, we have developed a beam element model, algorithms, and software for computer analysis of thermal characteristics of SUs. The thermal model incorporates a model of heat generation in rolling bearings, a model of heat transfer from bearings, and models for estimation of temperature and temperature deformations of SU elements. We have carried out experimental test and made quantitative evaluation of the effect of operation conditions on friction and thermal characteristics of the SUs of grinding and turning machines of typical structures. It is found out that the operation conditions make stronger effect on SU temperatures when rpm increases. A comparison between the results of analysis and experiment proves their good mutual correspondence and allows us to recommend application of the models and software developed for design and research of high-speed SUs running on rolling bearings.

• Journal of radiological science and technology
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• v.46 no.6
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• pp.535-542
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• 2023

This study aimed to implement a deep learning model that can perform quantitative quality control through ACTS software used for quantitative evaluation of ACR phantom in CT quality control and evaluate its usefulness. By changing the scanning conditions, images of three modules of the ACR phantom's slice thickness (ST), low contrast resolution (LC), and high contrast resolution (HC) were obtained and classified as ACTS software. The deep learning model used ResNet18, implementing three models in which ST, HC, and LC were learned with epoch 50 and an integrated model in which three modules were learned with Epoch 10, 30, and 50 at once. The performance of each model was evaluated through Accuracy and Loss. When comparing and evaluating the accuracy and loss function values of the deep learning models by ST, LC, and HC modules, the Accuracy and Loss of the HC model were the best with 100% and 0.0081, and in the integrated model according to the Epoch value, Accuracy and Loss with epoch 50 were the best with 96.29% and 0.1856. This paper showed that quantitative quality control is possible through a deep learning model, and it can be used as a basis and evidence for applying deep learning to the CT quality control.

• Earthquakes and Structures
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• v.1 no.1
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• pp.93-108
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• 2010

This paper investigates the seismic performance of existing reinforced concrete frames with wide beams mainly designed for gravity loads, as typically found in the seismic-prone Mediterranean area before the introduction of modern codes. The seismic capacity is evaluated in terms of the overall amount of input energy that the frame can dissipate/absorb up to collapse. This approach provides a quantitative evaluation that can be useful for selecting and designing an appropriate retrofit strategy. Six prototype frames representative of past construction practices in the southern part of Spain are designed, and the corresponding non-linear numerical models are developed and calibrated with purposely conducted tests on wide beam-column subassemblages. The models are subjected to sixteen earthquake records until collapse by applying the incremental dynamic analysis method. It is found that the ultimate energy dissipation capacity at the story level is markedly low (about 1.36 times the product of the lateral yield strength and yield displacement of the story), giving values for the maximum amount of energy that the frame can dissipate which are from one fourth to half of that required in moderate-seismicity regions.