Kim, Myoung Soon;Shin, Yoon Seung;Lee, Se Won;Seo, Jai Wha
Korean Journal of Childcare and Education
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v.12
no.4
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pp.151-181
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2016
This study examined professional development systems in America, England, and Australia, and devised ways to enhance early childhood teachers' professional development in Korea. To suggest effective ways to improve current professional development system and its operation, this research aimed to investigate first, advanced professional development systems and policies in three countries, America, England, and Australia, second, the process of teacher qualification and requirements for acquiring teacher credential and its maintenance, and lastly, the effort of quality control for professional development, its operation, and evaluation systems in three countries. Based on the analysis of the three country's systems, five solutions for effective professional development are suggested. First, it is necessary to differentiate requirements for teachers by the level of teacher credentials. Second, an incessant training process for professional development is required. Third, an individualized professional development plan should be set for an individual teacher for the best outcomes in professional competence. Fourth, instructors for professional development trainings are needed to ensure the quality of training. Lastly, individuals, organizations, and policy and its operation systems need to be considered holistically as a whole in the perspective of convergence in policy making and its operation for effective professional development.
Pendharkar, Umesh;Patel, K.A.;Chaudhary, Sandeep;Nagpal, A.K.
Steel and Composite Structures
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v.18
no.3
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pp.547-563
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2015
Deflection in a beam of a composite frame is a serviceability design criterion. This paper presents a methodology for rapid prediction of long-term mid-span deflections of beams in composite frames subjected to service load. Neural networks have been developed to predict the inelastic mid-span deflections in beams of frames (typically for 20 years, considering cracking, and time effects, i.e., creep and shrinkage in concrete) from the elastic moments and elastic mid-span deflections (neglecting cracking, and time effects). These models can be used for frames with any number of bays and stories. The training, validating, and testing data sets for the neural networks are generated using a hybrid analytical-numerical procedure of analysis. Multilayered feed-forward networks have been developed using sigmoid function as an activation function and the back propagation-learning algorithm for training. The proposed neural networks are validated for an example frame of different number of spans and stories and the errors are shown to be small. Sensitivity studies are carried out using the developed neural networks. These studies show the influence of variations of input parameters on the output parameter. The neural networks can be used in every day design as they enable rapid prediction of inelastic mid-span deflections with reasonable accuracy for practical purposes and require computational effort which is a fraction of that required for the available methods.
Diesel engines have low specific fuel consumption, but high particulate emissions, mainly soot. Diesel soot is suspected to have significant effects on the health of living beings and might also affect global warming. Hence stringent measures have been put in place in a number of countries and will be even stronger in the near future. Diesel engines require either advanced integrated exhaust after treatment systems or modified engine models to meet the statutory norms. Experimental analysis to study the emission characteristics is a time consuming affair. In such situations, the real picture of engine control can be obtained by the modeling of trend prediction. In this article, an effort has been made to predict emissions smoke and NO$_{x}$ using cylinder combustion derived parameters and diesel particulate filter data, with artificial neural network techniques in MATLAB environment. The model is based on three layer neural network with a back propagation learning algorithm. The training and test data of emissions were collected from experimental set up in the laboratory for different loads. The network is trained to predict the values of emission with training values. Regression analysis between test and predicted value from neural network shows least error. This approach helps in the reduction of the experimentation required to determine the smoke and NO$_{x}$ for the catalyst coated filters.
As the new century begins, it is clear that K-l2 education is going through a major change. The increasing power and affordability of personal computers along with wide spread use of the Internet has not only changed the landscape for communication but it has opened up new and exciting opportunities for education. One of the ways that Internet could help improve education is to act as an interactive communication link to gather the knowledge and experience of all the teachers and to serve as an open forum for discussing and exchanging innovative ideas. But developing a successful site is not an easy task since the success of the site depends on the level of participation and cooperation of teachers. In this paper, learnings derived from the development of an interactive web based resource center for K-12 mathematics teacher are described and recommendations for developing an effective site for teachers are suggested. The development of an interactive resource center for mathematics teachers showed that while interest for a web based resource is very high, the main obstacle for effective teacher participation is lack of easy accessibility of internet by teachers, and lack of computer and internet training for teachers. The technical issues regarding hardware installation, software development and cost were minimal. Accessibility will improve in time as more and more schools are connected to the internet, but this alone will not be enough. The study suggests that in order to bring together teachers on the internet more effort needs to be made in training teachers on the use of computers and the internet.
International Journal of Advanced Culture Technology
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v.10
no.4
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pp.383-388
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2022
This thesis explores the principle of a performer's organic action by means of his/her bodily responses on stage. This research has been developed to define the nature of a performer's central task in order to constitute empirical understanding of acting and the purpose of training in addressing the question of what sort of qualitative bodily training is necessary to be in a state of the full body involvement. This study investigates to articulate a performer's fundamental task at the most rudimentary level by utilizing those theatre artists' concepts with practical assumptions. In particular, the key terms, happen and change signifies the quality of a performer's body that has to fit into the given environment in which the performer's body can be subordinated through the moment on stage. Here, we argue that a performer's essential task parallel to make the following moment to happen and change by means of progressing a set of the next moment. In this manner, we also argue that a moment of displaying the performer's conscious effort, forceful and externalizing the visible elements under the use of erroneous language leads his/her body not to function on stage, a state of disengagement from his/her body. Finally, we provide a way to facilitate a performer's organic action by focused on his/her lived experience to create the functional moment which is opposite to the predominance of a representation, maintaining the performer's intellectual sense.
A specialist in the medical field is probably one of the most time-consuming professions to train for before one is considered an expert. Inclusive of medical school, it can take as long as 20 or more years of structured training before one graduates as a new specialist in a particular surgical subspecialty or medical field. A fellowship is often the last official phase in this professional marathon, typically defined as a 1 to 2-year full-on clinical subspecialty experience. One would expect this important "finishing school" to be well researched and written about, however, as compared to other professionals and fields, there is scanty literature on how one can get into a good fellowship program. This is a perspective piece on the intricacies of securing a position in a good fellowship program, drawn from the collective experience of the authors, their colleagues and friends. There are several ways to achieve this and many processes one will encounter. A variety of factors one will need to consider, decide and works towards in this effort of optimizing of their chances of success in getting into their fellowship program of choice. The thought processes, suggestions and solutions at each phase may be helpful. In conclusion, obtaining a choice fellowship position is as much an art as a science, and maybe some luck. Many factors, some more obvious and objective, some softer and more subtle, can all influence the outcome in one way or another.
The purpose of this study was to examine the awareness of dental hygienists about on-the-job training in public health sector in an effort to stir up their on-the-job training(OJT) and to facilitate the planning of successful educational programs. A survey was conducted nationwide for two months in October and November 2006, and the answer sheets from 811 dental hygienists were analyzed. The findings of the study were as follows: 1. 40.7 percent of the dental hygienists investigated never underwent OJT geared toward public officials, which wasn't linked to oral health. 2. As for the experiences of professional oral health education(or OJT) as members of local public dental clinics by service term, 64.9 percent of the dental hygienists who had worked for less than 10 years never received that kind of education, and 70.5 percent of those with a 15-year or more career received that education just once(p<0.05). The dental hygienists who received that education viewed it favorably, as they found that to be conducive to their job performance. In the event of those who didn't receive that education, a lack of chance to do that was the most common reason. 3. In regard to motivation of receiving professional oral health education(or OJT), the largest rate of the dental hygienists who stood at 71.9 percent received that education voluntarily in pursuit of self-development and better job performance. The training programs provided by the oral health division of the Ministry for Health, Welfare and Family Affairs were excluded in this study. As to educational spending by the dental hygienists or their employers over the past two years, 56.9 percent paid 100 thousand to less than 500 thousand won. 46.6 percent never paid for that, and about 15.5 percent received education at their own expenses. Concerning the form of OJT, lectures were provided to 50.3 percent. 4. The dental hygienists who worked in local public health clinics hoped for more intensive and better education and training related to oral health projects.
In the field of defense M&S, we are actively pursuing researches that interoperable multiple war game models to simulate various combat environments at the same time. Although the 'unit DB(Database)' for operating the war game models is originated from the identical data, it has been recognized that the method of expressing the attribute of the data is different and the cross reference is impossible. As a result, it makes unnecessary time and effort in establishing the same unit DB in the organizations that operate the war game model. In this study, a method of reusing the unit DB of the training war game model to the analysis war game model with similar resolution and simulated logic was applied to the actual field. For this purpose, we defined the procedure for converting the unit DB by analyzing metadata of the 'Chang-Jo21', a combat training model for corps and division, and the 'Vision21', an analysis model for corps and division operation plan. And we introduced an algorithm that can map different metadata of two unit DBs. This study was meaningful as the first attempt to map and integrate heterogeneous metadata semantically for the reuse of unit DB between different war game models in defense M&S field. Also, it provided implications for the necessity of paradigm shift that reuse of the unit DB between two different war game models is possible and the need for standardization of the unit DB metadata in the defense M&S filed.
As more and more the number of a couple working together for living has increased and an interest in early education has risen, daycare centers have made an effort to provide effective and good service beyond 'nursery care'. The most important thing in building in the event of disasters is safe evacuation of occupants. Having 'safe evacuation route' is required to reduce damage caused by disasters, It is necessary to give continuous and repeated training for right evacuation to infant and children so that they can evacuation successfully. This study examined problems that need improvement so that evacuation instrument installed in daycare centers can be used better by analyzing a survey of evacuation related facilities on daycare centers. This study found that laws and regulations on safety should be improved, evacuation facilities prepared against should be maintained regularly by relevant authorities, training for coping with disasters should be provied and evacuation instruments which are suitable for children.
Journal of Korean Association for Spatial Structures
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v.20
no.2
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pp.51-58
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2020
Recently, deep learning that is the most popular and effective class of machine learning algorithms is widely applied to various industrial areas. A number of research on various topics about structural engineering was performed by using artificial neural networks, such as structural design optimization, vibration control and system identification etc. When nonlinear semi-active structural control devices are applied to building structure, a lot of computational effort is required to predict dynamic structural responses of finite element method (FEM) model for development of control algorithm. To solve this problem, an artificial neural network model was developed in this study. Among various deep learning algorithms, a recurrent neural network (RNN) was used to make the time history response prediction model. An RNN can retain state from one iteration to the next by using its own output as input for the next step. An eleven-story building structure with semi-active tuned mass damper (TMD) was used as an example structure. The semi-active TMD was composed of magnetorheological damper. Five historical earthquakes and five artificial ground motions were used as ground excitations for training of an RNN model. Another artificial ground motion that was not used for training was used for verification of the developed RNN model. Parametric studies on various hyper-parameters including number of hidden layers, sequence length, number of LSTM cells, etc. After appropriate training iteration of the RNN model with proper hyper-parameters, the RNN model for prediction of seismic responses of the building structure with semi-active TMD was developed. The developed RNN model can effectively provide very accurate seismic responses compared to the FEM model.
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