• Structural Engineering and Mechanics
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• v.51 no.6
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• pp.973-988
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• 2014

This paper presents a factor-analysis based questionnaire categorization method to improve the reliability of the evaluation of working conditions without influencing the completeness of the questionnaire both in Taiwanese and Chinese construction enterprises for structural engineering applications. The proposed approach springs from the AI application and expert systems in structural engineering. Questions with a similar response pattern are grouped into or categorized as one factor. Questions that form a single factor usually have higher reliability than the entire questionnaire, especially in the case when the questionnaire is complex and inconsistent. By classifying questions based on the meanings of the words used in them and the responded scores, reliability could be increased. The principle for classification was that 90% of the questions in the same classified group must satisfy the proposed classification rule and consequently the lowest one was 92%. The results show that the question classification method could improve the reliability of the questionnaires for at least 0.7. Compared to the question deletion method using SPSS, 75% of the questions left were verified the same as the results obtained by applying the classification method.

• Journal of Power Electronics
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• v.16 no.2
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• pp.436-446
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• 2016

A novel step-up DC-DC converter with a switched-coupled-inductor-capacitor (SCIC) which successfully integrates three-winding coupled inductors and switched-capacitor techniques is proposed in this paper. The primary side of the coupled inductors for the SCIC is charged by the input source, and the capacitors are charged in parallel and discharged in series by the secondary windings of the coupled inductor to achieve a high step-up voltage gain with an appropriate duty ratio. In addition, the passive lossless clamped circuits recycle the leakage energy and reduce the voltage stress on the main switch effectively, and the reverse-recovery problem of the diodes is alleviated by the leakage inductor. Thus, the efficiency can be improved. The operating principle and steady-state analyses of the converter are discussed in detail. Finally, a prototype circuit at a 50 kHz switching frequency with a 20-V input voltage, a 200-V output voltage, and a 200-W output power is built in the laboratory to verify the performance of the proposed converter.

• Journal of Magnetics
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• v.22 no.1
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• pp.49-54
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• 2017

The significant reduction of the image quality caused by the magnetic field of samples is a major problem affecting the application of SEM (scanning electron microscopy) in the analysis of electronic devices. The main reason for this is that the electron trajectory is deflected by the Lorentz force. The usual solution to this problem is degaussing the sample at high temperatures. However, due to the poor heat resistance of some electronic components, it is imperative to find a method that can reduce the impact of magnetic field on the image quality and is straightforward and easy to operate without destroying the sample. In this paper, the influence of different magnetic field directions on the imaging quality was discussed by combining the experiment and software simulation. The principle of the method was studied, and the best observation direction was obtained.

• Advances in pediatric surgery
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• v.12 no.2
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• pp.192-201
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• 2006

There are considerable controversies in the management of congenital diaphragmatic hernia. By 1997, early operation, routine chest tube on the ipsilateral side and maintainingrespiratory alkalosis by hyperventilation were our principles (period I). With a transition period from 1998 to 1999, delayed operation with sufficient resuscitation, without routine chest tube, and permissive hypercapnia were adopted as our practice. High frequency oscillatory ventilation (HFOV) and nitric oxide (NO) were applied, if necessary, since year 2000(period II). Sixty-seven cases of neonatal Bochdalek hernia from 1989 to 2005 were reviewed retrospectively. There were 33 and 34 cases in period I and II, respectively. The neonatal survival rates were 60.6 % and 73.5 %, respectively, but the difference was not significant. In period I, prematurity, low birth weight, prenatal diagnosis, inborn, and associated anomalies were considered as the significant poor prognostic factors, all of which were converted to nonsignificant in period II. In summary, improved survival was not observed in later period. The factors considered to be significant for poor prognosis were converted to be nonsignificant after change of the management principle. Therefore, we recommend delayed operation after sufficient period of stabilization and the avoidance of the routine insertion of chest tube. The validity of NO and HFOV needs further investigation.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.4
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• pp.403-415
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• 1999

To properly assess air pollution levels, application of quality assurance and quality control(QA/QC) is believed to be an essential step. In order to cope with such scientific principle, a field study was designed with an aim of comparing: 1) the methods of calibration for airborne pollutants and 2) the protocols developed for their measurements. Measurements were made at Han Yang University, Seoul during 29 May through 1 June 1998 under the management of the Division of Measurements and Analysis(DMA) of Korean Society for Atmospheric Environment(KOSAE). In this work, we report our results of intercomparative measurements on several gaseous criteria pollutants that were investigated mainly by the two institutes-Seoul National University(SNU) and the Korean Research Institute for Standards and Science(KRISS). Although measurements of major gaseous pollutants had been made routinely by many scientific institutes and organizations in Korea, most scientists involved in those studieswere obliged to do their experiments on the basis of their own procedural steps spaning from the preparation of gaseous standards to the methodological selections for the calibration. Hence, this campaign offered a unique opportunity to examine many important aspects on the measurements of these important gaseous pollutants. In the course of our study, we investigated the compatibility of data sets obtained by the two institutes in concert with reference data sets collected concurrently from a government-managed monitoring station. On the basis of our study, we conclude that different data sets made by different participants during this campaign agree well within the reasonable range of uncertainties.low, which indicated that during this period the potential acidity of precipitation was high but the neutralizing capacity was low. For Spring, pAi was very low but pH was slightly high. This was likely due to the large amount of $CaCO_3$ in the soil particles transported over a long range from the Chinese continent that were incorporated into the precipitation, and then neutralized the acidifying species with its high concentraton.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.279-285
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• 2022

In this paper, as a liberal arts course for non-majors, we developed a basic practice case for convolutional neural networks, which is essential for designing a basic convolutional neural network course curriculum. The developed practice case focuses on understanding the working principle of the convolutional neural network and uses a spreadsheet to check the entire visualized process. The developed practice case consisted of generating supervised learning method image training data, implementing the input layer, convolution layer (convolutional layer), pooling layer, and output layer sequentially, and testing the performance of the convolutional neural network on new data. By extending the practice cases developed in this paper, the number of images to be recognized can be expanded, or basic practice cases can be made to create a convolutional neural network that increases the compression rate for high-quality images. Therefore, it can be said that the utility of this convolutional neural network basic practice case is high.

• Journal of the International Relations & Interdisciplinary Education
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• v.1 no.1
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• pp.61-79
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• 2021

In order to implement an artificial intelligence lawyer, this study looked at how to structure legal principles, and then gave specific examples of how structured legal principles can be expressed in predicate logic. While previous studies suggested a method of introducing predicate logic for the reasoning engine of artificial intelligence lawyers, this study focused on the method of expressing legal principles with predicate logic based on the structural appearance of legal principles. Jurisprudence was limited to the content of articles and precedents, and the vertical hierarchy leading to 'law facts - legal requirements - legal effect' and the horizontal hierarchy leading to 'legal effect - defense - defense' were examined. In addition, legal facts were classified and explained that most of the legal facts can be usually expressed in unary or binary predicates. In future research, we plan to program the legal principle expressed in predicate logic and realize an inference engine for artificial intelligence lawyers.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.491-498
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• 2022

In this paper, as a liberal arts course for non-major students, a case study of recurrent neural network SW practice, which is essential for designing a basic recurrent neural network subject curriculum, was developed. The developed SW practice case focused on understanding the operation principle of the recurrent neural network, and used a spreadsheet to check the entire visualized operation process. The developed recurrent neural network practice case consisted of creating supervised text completion training data, implementing the input layer, hidden layer, state layer (context node), and output layer in sequence, and testing the performance of the recurrent neural network on text data. The recurrent neural network practice case developed in this paper automatically completes words with various numbers of characters. Using the proposed recurrent neural network practice case, it is possible to create an artificial intelligence SW practice case that automatically completes by expanding the maximum number of characters constituting Korean or English words in various ways. Therefore, it can be said that the utilization of this case of basic practice of recurrent neural network is high.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.1-13
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• 2021

This study tried to suggest ways to improve the indicator system to strengthen the personal information protection. For this purpose, the components of indicator system are derived through domestic and foreign literature, and it was selected as main the diagnostic indicators through FGI/Delphi analysis for personal information protection experts and a survey for personal information protection officers of public institutions. As like this, this study was intended to derive an inspection standard that can be reflected as a separate index system for personal information protection, by classifying the specific IT technologies of the 4th industrial revolution, such as big data, cloud, Internet of Things, and artificial intelligence. As a result, from the planning and design stage of specific technologies, the check items for applying the PbD principle, pseudonymous information processing and de-identification measures were selected as 2 common indicators. And the checklists were consisted 2 items related Big data, 5 items related Cloud service, 5 items related IoT, and 4 items related AI. Accordingly, this study expects to be an institutional device to respond to new technological changes for the continuous development of the personal information management level diagnosis system in the future.

• Communications of Mathematical Education
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• v.37 no.1
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• pp.65-84
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• 2023

The method of Lagrange multipliers, one of the most fundamental algorithms for solving equality constrained optimization problems, has been widely used in basic mathematics for artificial intelligence (AI), linear algebra, optimization theory, and control theory. This method is an important tool that connects calculus and linear algebra. It is actively used in artificial intelligence algorithms including principal component analysis (PCA). Therefore, it is desired that instructors motivate students who first encounter this method in college calculus. In this paper, we provide an integrated perspective for instructors to teach the method of Lagrange multipliers effectively. First, we provide visualization materials and Python-based code, helping to understand the principle of this method. Second, we give a full explanation on the relation between Lagrange multiplier and eigenvalues of a matrix. Third, we give the proof of the first-order optimality condition, which is a fundamental of the method of Lagrange multipliers, and briefly introduce the generalized version of it in optimization. Finally, we give an example of PCA analysis on a real data. These materials can be utilized in class for teaching of the method of Lagrange multipliers.