Vector quantization algorithm based on fuzzy clustering has been widely used in the field of data compression since the use of fuzzy clustering analysis in the early stages of a vector quantization process can make this process less sensitive to its initialization. However, the process of fuzzy clustering is computationally very intensive because of its complex framework for the quantitative formulation of the uncertainty involved in the training vector space. To overcome the computational burden of the process, this paper introduces an array architecture for the implementation of fuzzy vector quantization (FVQ). The arrayarchitecture, which consists of 4,096 processing elements (PEs), provides a computationally efficient solution by employing an effective vector assignment strategy during the clustering process. Experimental results indicatethat the proposed parallel implementation providessignificantly greater performance and efficiency than appropriately scaled alternative array systems. In addition, the proposed parallel implementation provides 1000x greater performance and 100x higher energy efficiency than other implementations using today's ARMand TI DSP processors in the same 130nm technology. These results demonstrate that the proposed parallel implementation shows the potential for improved performance and energy efficiency.
This study was done to identify a status of home visiting project as a community health nursing system, that was the organization. personal who have age, educational background, marital status, position, experience of the home visiting in the public sectors in part of Seoul. Kyonggi, Kang-won area, It was done to provide basis data for the development of effective visiting nurses project in the health sectors, where was Health Centers in urban and rural. Branch of Health Center in rural and Health posts. The question airs were distributed 352 public health workers who working place was 118 health workers in 12 health centers in Seoul. 56 public health workers among 39 health center and other public health sectors in Kyonggi and 178 public health workers among health center and health care sectors. Data collected from October to December. 2000. The analysis by SAS system with F test, percentage and frequency. The major result were as follows. The general characteristics of the respondent show that most of them were graduates from community college and RN-BS with broadcast that they had not completed CPHN course but only two health workers have trained for the visiting nurses project. As for their grade in the position, the most of health workers have seventh level and the other CHP were above sixth level in the health care post that in the government structure. This indicates that workers do not have great authority in decision making, the most period of works in the position was one and two years indicating that they change jobs frequently. On an average their clinical experience was 4.11 years which is ideal for the total service. As for preparation of staff for home visiting workers education on visiting nurses program have to receive short term or longer term training course for strong emphasis. The analysis showed that public health visiting workers responds about active job performance that based on an area, approach of acting by districts, education and position are shown statistically significant difference between acceptance of the visiting nursing job show the same as well as visiting nurses project. Special concerns for visiting Nursing care spread came to burden, many of activity carry out main solution is covered the health problem connective support system needs of quality and quantity which out health problem. As 71.1% of visiting health service held on the poor population was under the guardianship of the law, but people who health insurance wide application under law shown a tendency to increase gradually. The general characteristics of the patients showed 56.2% of female on average of age was 66.1 years old, they have health problem was the most of 47.6% of high blood pressure and stroke, the other and as a problem that economics, which is complex welfare with out health problem. Community health care service should be combined health and social work program. The form of delivery of visiting health care given the most guide and education with counselling and support. (33.6%) Among the six category of visiting care service shown statistically significant difference and next is fundamental care, remedy care with priority.
Journal of The Korean Association For Science Education
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v.34
no.1
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pp.33-42
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2014
There are complex interactions between personal and contextual features in teaching in a science museum. In order to analyze two teachers' holding classes in a science museum, the CHAT (cultural historical activity theory) was used as an analysis tool in a case study. The analyses of the results revealed that both teachers had difficulties teaching in a science museum due to the contradictions among the factors of subject, rules, community, and division of labor in the activity system. Although both teachers had trouble with similar contradictions, there appeared to be different sets of internalization and externalization of such conflicts depending on the difference in the teacher's perceptions and experiences about teaching in a science museum, the passion and the motivation of the teachers. These suggested that efforts should be preceded to foster the activity system providing both emotional and social supports to teachers in order to activate teaching in a science museum. Taking a teacher training course on teaching in a science museum was also found to fail to function as mediating artifacts. The course should provide not only the experience of executing proper teaching strategies for teaching in a science museum and the feedback on their teaching, but also the guidance on how to lead to optimal expansion of the factors in the activity system.
The Taiwanese liquid crystal display (LCD) industry has traditionally produced a huge amount of waste glass that is placed in landfills. Waste glass recycling can reduce the material costs of concrete and promote sustainable environmental protection activities. Concrete is always utilized as structural material; thus, the concrete compressive strength with a variety of mixtures must be studied using predictive models to achieve more precise results. To create an efficient waste LCD glass concrete (WLGC) design proportion, the related studies utilized a multivariable regression analysis to develop a compressive strength waste LCD glass concrete equation. The mix design proportion for waste LCD glass and the compressive strength relationship is complex and nonlinear. This results in a prediction weakness for the multivariable regression model during the initial growing phase of the compressive strength of waste LCD glass concrete. Thus, the R ratio for the predictive multivariable regression model is 0.96. Neural networks (NN) have a superior ability to handle nonlinear relationships between multiple variables by incorporating supervised learning. This study developed a multivariable prediction model for the determination of waste LCD glass concrete compressive strength by analyzing a series of laboratory test results and utilizing a neural network algorithm that was obtained in a related prior study. The current study also trained the prediction model for the compressive strength of waste LCD glass by calculating the effects of several types of factor combinations, such as the different number of input variables and the relevant filter for input variables. These types of factor combinations have been adjusted to enhance the predictive ability based on the training mechanism of the NN and the characteristics of waste LCD glass concrete. The selection priority of the input variable strategy is that evaluating relevance is better than adding dimensions for the NN prediction of the compressive strength of WLGC. The prediction ability of the model is examined using test results from the same data pool. The R ratio was determined to be approximately 0.996. Using the appropriate input variables from neural networks, the model validation results indicated that the model prediction attains greater accuracy than the multivariable regression model during the initial growing phase of compressive strength. Therefore, the neural-based predictive model for compressive strength promotes the application of waste LCD glass concrete.
Recently, various public transportation activation policies are being implemented in order to mitigate traffic congestion in metropolitan areas. Especially in the metropolitan area, the bus information system has been introduced to provide information on the current location of the bus and the estimated arrival time. However, it is difficult to predict the travel time due to repetitive traffic congestion in buses passing through complex urban areas due to repetitive traffic congestion and bus bunching. The previous bus travel time study has difficulties in providing information on route travel time of bus users and information on long-term travel time due to short-term travel time prediction based on the data-driven method. In this study, the path based long-term bus travel time prediction methodology is studied. For this purpose, the training data is composed of 2015 bus travel information and the 2016 data are composed of verification data. We analyze bus travel information and factors affecting bus travel time were classified into departure time, day of week, and weather factors. These factors were used into clusters with similar patterns using self organizing map. Based on the derived clusters, the reference table for bus travel time by day and departure time for sunny and rainy days were constructed. The accuracy of bus travel time derived from this study was verified using the verification data. It is expected that the prediction algorithm of this paper could overcome the limitation of the existing intuitive and empirical approach, and it is possible to improve bus user satisfaction and to establish flexible public transportation policy by improving prediction accuracy.
Kim, Yong Cheol;Kim, Young Soo;Yang, Jeong Ok;Lee, Bom Jin;Lee, Joong Sook
Journal of the Korean Data and Information Science Society
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v.24
no.6
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pp.1241-1251
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2013
The purpose of this study was to investigate and compare the effects of aerobic and complex exercise on body composition and blood lipids in the middle-aged women. Sixteen women whose ages ranged in 40 to 50 years were included in the sample of the study. The sample was divided into two groups: (a) aerobic exercise group (n = 8) and (b) combined exercise training group (n = 8). The aerobic exercise program consisted of bicycle ergometer, stepper, and treadmill, whereas; the combined exercise program was designed to improve muscular strength and aerobic capacity. Both programs took place 4 times a week for 12 weeks with the gradual increase of intensity (HRmax 60% 75% and 1 RM 60% 80%). Data were analyzed by nonparametric methods for pre-post within group mean differences (Wilcoxon signed rank test) and for between group mean differences (Wilcoxon rank sum test). Results indicated that there were statistically significant differences in BMI, body fat mass, and triglyceride within the sample of combined exercise; whereas, no significance existed in any variables within the aerobic exercise group. Results also revealed that statistical significance did exist in body fat mass between the combined and aerobic exercise group. These results implies that the combined exercise may be superior to aerobic only excercise for the body composition and blood lipid of the middle-aged women.
Journal of the Korean Society for Library and Information Science
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v.25
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pp.83-150
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1993
Traditionally, the emphasis of the information services had been placed on the information provider's knowledge of information sources or information systems. However, in view of the increasing complexity of the information environment. and changes taking place in information professions the evaluation of the information services has callded for further research in interpersonal communication aspects of the librarian user interface especially that which links to user satisfaction. This experimental study was carried out for the purpose of exploring the implications of nonverbal behaviors in measuring user satisfaction in the light of the fact that the meaning of nonverbal clues includes more than verbal communication especially in dealing with variable barriers even though they operate at low levels of awareness. In this sense, among the wide range of nonverbal communication areas in particular kinesics, artifacts and the proximics were examined to suggest alternative model which can be applied effectively in our specific set of information work environment. Two major university libraries and two research libraries in Korea were chosen and visited for the anlysis and per each refernce/information interview the librarian's nonverbal behaviors were checked on the observer's checklist and the qustionnaires completed by the user at a time. On the basis of these data firstly, the relation of user satisfaction concerned with the librarian's nonverbal communication to user satisfaction with information services was analyzed and the possible communication barriers were investigated. In addition, the effect of training the information librarian with positive nonverbal communication skills on the user's satisfaction was analyzed in a SAS computer program in the area of kinesics. On the other hand, the effect of other nonverbal behaviors such as proximics and artifacts known very important clues to improving a complex human interaction was discussed along with their experimental results. In conclusion, it was found that most of users were not sensitive to the importance of nonverbal behaviors exposed by the information librarian, but it was proved that the ultimate user satisfaction and the satisfaction of the librarian's nonverbal behaviors are correlated positively, Moreover, nonverbal behaviors displayed by the trained librarian toward the user had a considerable effect on the user's evalution of information services compared with those by the untrained. These findings imply that in order to control the librarian's nonverbal behaviors and to help the user overcome his barriers the information librarian as a specialist needs to assure and modify willilingly his communication behavior. Without making effective use of such nonverbal communication, information librarian could not expect to meet the user's information needs either. However, when these positive nonverbal behaviors are applied it would be highly desirable to be aware of cultural and contextual differences. With regard to increasing information services success the applicable nonverbal communication model for library management and education can be suggested as below.
Complex ethical issues of Emergency Medical Techinician (EMT) out-of hospital emergency medical scene and the ER (Emergency Room) behaviors were studied. The survey was conducted by 500 EMT group members working in the field of ambulance work and general hospital and it was about their work ethics, discussions and solutions about the transferred patients, and ethics regarding Do Not Attempt Resuscitate (DNAR). The survey includes work ethics, awareness about the target job, a discussion on the transfer of patients, measures, and deathbed. Discussions about the patient's condition and diagnosis results were majorly absent during patient transportation at the emergency care scene. More than 90% of emergency care transfer were inappropriate. Sometimes, EMT working in the field facing morally unethical problems beyond their responsibility. When EMT, who can not make death diagnosis, received deathbed related DNAR issues, they gone through severe ethical conflicts. The institutional support and therapy for EMT was weak. In Korea, especially in the accident site, ethical issues education is more needed than DNAR prevalence of education and guidance. If ethics training and guidance are given to EMT, a lot of moral errors in the field can be resolved.
Journal of the Korean Society for Aeronautical & Space Sciences
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v.33
no.2
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pp.84-91
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2005
For long time, the takeoff and landing control of airship was worked by human handling. With the development of the autonomous control system, the exact controls during the takeoff and landing were required and lots of methods and algorithms were suggested. This paper presents the result of airship take-off and landing by buoyancy control using air ballonet volume change and performance control of pitch angle for stable flight within the desired altitude. For the complexity of airship's dynamics, firstly, simple PID controller was applied. Due to the various atmospheric conditions, this controller didn't give satisfactory results. Therefore, new control method was designed to reduce rapidly the error between designed trajectory and actual trajectory by learning algorithm using an artificial neural network. Generally, ANN has various weaknesses such as large training time, selection of neuron and hidden layer numbers required to deal with complex problem. To overcome these drawbacks, in this paper, the RBFN (radial basis function network) controller developed. The weight value of RBFN is acquired by learning which to reduce the error between desired input output through and airship dynamics to impress the disturbance. As a result of simulation, the controller using the RBFN is superior to PID controller which maximum error is 15M.
KIPS Transactions on Computer and Communication Systems
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v.9
no.8
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pp.171-180
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2020
Smart Factory consists of digital automation solutions throughout the production process, including design, development, manufacturing and distribution, and it is an intelligent factory that installs IoT in its internal facilities and machines to collect process data in real time and analyze them so that it can control itself. The smart factory's equipment works in a physical combination of numerous hardware, rather than a virtual character being driven by a single object, such as a game. In other words, for a specific common goal, multiple devices must perform individual actions simultaneously. By taking advantage of the smart factory, which can collect process data in real time, if reinforcement learning is used instead of general machine learning, behavior control can be performed without the required training data. However, in the real world, it is impossible to learn more than tens of millions of iterations due to physical wear and time. Thus, this paper uses simulators to develop grid sortation systems focusing on transport facilities, one of the complex environments in smart factory field, and design cooperative multi-agent-based reinforcement learning to demonstrate efficient behavior control.
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