• Journal of Korean Academy of Nursing Administration
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• v.10 no.1
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• pp.121-140
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• 2004

Purpose: This study is to analyse and observe the college of oriental medicine related with nursing investment contents, its conversion process and output to get good qualified oriental nursing result, thus developing a matrix of oriental nursing management system on the basis of that project. Method: This study was nursing management system of matrix developmental study for Korea was performed to the objectives of 11 college of oriental medicine nursing directors and 328 nurses with more than three-year experiences in Korea. Result: We found difficulties to utilize knowledge obtained through the regular curriculum to the practice of oriental nursing because only me or two subjects were running or even no syllabus. Therefore, we recommend that oriental nursing in-service education program as well as oriental nursing practice preceptorship should be administered en site. The evaluation of oriental nursing and its feedback, duty related multiple evaluation, aggressive QI activity and feedback of the performance evaluation oriental nurse's role and duty manual also should be essentially organized. Conclusion: We urgently request that the consensus of nursing school and nurse association to be made about oriental nursing activity as a basic curriculum of compulsive subject.

• Nuclear Engineering and Technology
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• v.46 no.2
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• pp.125-146
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• 2014

This review aims to provide a synthesis of the knowledge generated and the lessons learned in roughly 15 years of UMo dispersion fuel R&D in Europe through a series of irradiation experiments. A lot of irradiations were also performed outside of Europe, particularly in the USA, Russia, Canada, Korea and Argentina. In addition, a large number of out-of-pile investigations were done throughout the world, providing support to the understanding of the phenomena governing the UMo behaviour in pile. However, the focus of this article will be on the irradiations and Post-Irradiation Examination (PIE) results obtained in European experiments. The introduction of the article provides a historic overview of the evolution and progress in the high density UMo dispersion fuel development. The ensuing sections then provide further details on the various phases of the development, from the UMo dispersion in a pure Al matrix through the addition of Si to the matrix to address the interaction layer formation and finally to the more advanced solutions to the excessive swelling encountered in various experiments. This review was based only on published results or results that are currently in the process of being published.

• Advances in nano research
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• v.16 no.5
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• pp.445-458
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• 2024

The objective of this paper is to present free vibration and static stability analyses of rotating composite beams reinforced with carbon nanotubes (CNTs) under uniform thermal loads. Beam structural equations and CNT-reinforced composite (CNTRC) beam formulations are derived based on Timoshenko beam theory (TBT). The temperature-dependent properties of the beam material, such as the elastic modulus, shear modulus, and material density, are assumed to vary over the thickness according to the rule of mixture. The beam material is modeled as a mixture of single-walled carbon nanotubes (SWCNTs) in an isotropic matrix. The SWCNTs are aligned and distributed in the isotropic matrix with different patterns of reinforcement, namely the UD (uniform), FG-O, FG-V, FG- Λ and FG-X distributions, where FG-V and FG- Λ are asymmetric patterns. Numerical examples are presented to illustrate the effects of several essential parameters, including the rotational speed, hub radius, effective material properties, slenderness ratio, boundary conditions, thermal force, and moments due to temperature variation. To the best of the authors' knowledge, this study represents the first attempt at the finite element modeling of rotating CNTRC Timoshenko beams under a thermal environment. The results are presented in tables and figures for both symmetric and asymmetric distribution patterns, and can be used as benchmarks for further validation.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.2
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• pp.168-176
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• 2015

Due to the reduction in device feature size, transient faults (soft errors) in logic circuits induced by radiations increase dramatically. Many researches have been done in modeling and analyzing the susceptibility of sequential circuit elements caused by soft errors. However, to the best knowledge of the authors, there is no work which has well considerated the feedback characteristics and the multiple clock cycles of sequential circuits. In this paper, we present a new method for evaluating the susceptibility of sequential circuit elements to soft errors. The proposed method uses four Error Propagation Probability Matrixs (EPPMs) to represent the error propagation probability of logic gates and flip-flops in current clock cycle. Based on the predefined matrix union operations, the susceptibility of circuit elements in multiple clock cycles can be evaluated. Experimental results on ISCAS'89 benchmark circuits show that our method is more accurate and efficient than previous methods.

• Journal for History of Mathematics
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• v.25 no.4
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• pp.101-119
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• 2012

The removal of the Go Stones is a game that anyone can play through simple rules. It is not only an interesting game but also a mathematical game that requires comprehensive knowledge of several mathematical theories. Through analyzing the rules and theories of this game, students can get a new mathematical perspective and recognize something that they didn't realize as important before. Furthermore, this game is given to students as a mathematical problem unconsciously. This helps them get a mathematical approach to understanding the actual concept of the problem as well as the basic principle of the problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2806-2825
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• 2018

Unsupervised learning has shown good performance on image, video and audio classification tasks, and much progress has been made so far. It studies how systems can learn to represent particular input patterns in a way that reflects the statistical structure of the overall collection of input patterns. Many promising deep learning systems are commonly trained by the greedy layerwise unsupervised learning manner. The performance of these deep learning architectures benefits from the unsupervised learning ability to disentangling the abstractions and picking out the useful features. However, the existing unsupervised learning algorithms are often difficult to train partly because of the requirement of extensive hyperparameters. The tuning of these hyperparameters is a laborious task that requires expert knowledge, rules of thumb or extensive search. In this paper, we propose a simple and effective unsupervised feature learning algorithm for image classification, which exploits an explicit optimizing way for population and lifetime sparsity. Firstly, a sparse target matrix is built by the competitive rules. Then, the sparse features are optimized by means of minimizing the Euclidean norm ($L_2$) error between the sparse target and the competitive layer outputs. Finally, a classifier is trained using the obtained sparse features. Experimental results show that the proposed method achieves good performance for image classification, and provides discriminative features that generalize well.

• Analytical Science and Technology
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• v.30 no.4
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• pp.167-173
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• 2017

In the era of the forth Industrial Revolution, open source code and open source hardware have gained much attention. In particular, 3D printing technology is expanding into the realms of classical science, technology and our daily lives. Relatedly, in the present study, we demonstrate the manufacture of a nano-LC MALDI spotter robot using 3D printing technology. The parts of the spotter robot were either made using a 3D printer or purchased as 3D printer parts from the 3D printer online market, so that anyone can make the robot without a deep knowledge of engineering or electronics, i.e., DIY (do-it-yourself) product. In the nano-LC MALDI spotter, the nano-LC eluent and MALDI matrix were mixed in a T-union and discharged from the capillary outlet. The eluent and matrix mixture could be spotted onto the movable MALDI plate. The MALDI plate was designed to translate in a two-dimensional space (xy plane), which was enabled by the movements of two stepper motors. In the paper, all computer-aided design (CAD) files for the parts and operation software are provided to help the reader manufacture their own spotter robot.

• The Journal of the Korea Contents Association
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• v.3 no.2
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• pp.24-30
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• 2003

Pre-existing authentication system such as token based method, knowledge-based and hybrid method have problems such as loss and wiretapping. for this, this paper describes the biometric authentication system which have the excellent convenience and security. In particular, a new biometric system by human face biometric features which have the non-enforcement and non-touch measurement is proposed. Firstly, facial features are extracted by Y- histogram and tilted face images we corrected by coordinate transformation and scaling has done for achieving independent of the camera positions. Secondly, feature vectors are extracted such as distance and intersection angles and similarities we measured by fuzzy relation matrix. finally, the effectiveness of this paper is demonstrated by experiments.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.63-72
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• 2013

Business Process Intelligence (BPI) is one of the emerging technologies in the knowledge discovery and analysis area. BPI deals with a series of techniques from discovering knowledge to analyzing the discovered knowledge in BPM-supported organizations. By means of the BPI technology, we are able to provide the full functionality of control, monitoring, prediction, and optimization of process-supported organizational knowledge. Particularly, we focus on the focal organizational knowledge, which is so-called the BPM activity-performer affiliation networking knowledge that represents the affiliated relationships between performers and activities in enacting a specific business process model. That is, in this paper we devise a statistical analysis method to be applied to the BPM activity-performer affiliation networking knowledge, and dubbed it the activity-performer correspondence analysis method. The devised method consists of a series of pipelined phases from the generation of a bipartite matrix to the visualization of the analysis result, and through the method we are eventually able to analyze the degree of correspondences between a group of performers and a group of activities involved in a business process model or a package of business process models. Conclusively, we strongly expect the effectiveness and efficiency of the human resources allotments, and the improvement of the correlational degree between business activities and performers, in planning and designing business process models and packages for the BPM-supported organization, through the activity-performer correspondence analysis method.

• Journal of Gifted/Talented Education
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• v.25 no.6
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• pp.927-949
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• 2015

The purpose of this study was to find out the difference between importance and performance regarding perception of core competence of gifted education teachers through importance-performance analysis (IPA). One hundred fourteen elementary gifted education teachers including math and science participated in the study. The collected survey data was analyzed with IPA matrix. As the result, firstly, there was significant difference between importance and performance regarding perception of core competence of gifted education teachers. Secondly, core competencies of 'understanding knowledge', 'research and instruction', 'passion and motivation', and 'ethics' are high in both perceptions of importance and performance. However, both 'communication and practices' and 'professional curriculum development' are low. Thirdly, there was a difference in core competence of gifted education teachers between math and science at the competence of 'passion and motivation'. Math gifted education teachers perceived 'passion and motivation' high in both importance and performance while science gifted education teachers perceived its importance low and performance high. In addition, math gifted education teachers showed lower performance compared to its importance in the sub-categories; 'knowledge of gifted development', 'gifted child assessment', 'information gathering and its literacy', and 'creative answers to various questions'. However, science gifted education teachers showed lower performance compared to its importance in sub-categories; 'higher-order thinking skills in its subject', 'teaching methodology for self-directed learning', 'problem behavior of the gifted', and 'counseling the gifted'.