• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.374-388
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• 2022

Cloud computing has been one of the most critical technology in the last few decades. It has been invented for several purposes as an example meeting the user requirements and is to satisfy the needs of the user in simple ways. Since cloud computing has been invented, it had followed the traditional approaches in elasticity, which is the key characteristic of cloud computing. Elasticity is that feature in cloud computing which is seeking to meet the needs of the user's with no interruption at run time. There are traditional approaches to do elasticity which have been conducted for several years and have been done with different modelling of mathematical. Even though mathematical modellings have done a forward step in meeting the user's needs, there is still a lack in the optimisation of elasticity. To optimise the elasticity in the cloud, it could be better to benefit of Machine Learning algorithms to predict upcoming workloads and assign them to the scheduling algorithm which would achieve an excellent provision of the cloud services and would improve the Quality of Service (QoS) and save power consumption. Therefore, this paper aims to investigate the use of machine learning techniques in order to predict the workload of Physical Hosts (PH) on the cloud and their energy consumption. The environment of the cloud will be the school of computing cloud testbed (SoC) which will host the experiments. The experiments will take on real applications with different behaviours, by changing workloads over time. The results of the experiments demonstrate that our machine learning techniques used in scheduling algorithm is able to predict the workload of physical hosts (CPU utilisation) and that would contribute to reducing power consumption by scheduling the upcoming virtual machines to the lowest CPU utilisation in the environment of physical hosts. Additionally, there are a number of tools, which are used and explored in this paper, such as the WEKA tool to train the real data to explore Machine learning algorithms and the Zabbix tool to monitor the power consumption before and after scheduling the virtual machines to physical hosts. Moreover, the methodology of the paper is the agile approach that helps us in achieving our solution and managing our paper effectively.

• 아동학회지
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• 제4권
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• pp.1-10
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• 1983

This study examined the characteristics of the relationship of home environment variables and preschool children's intelligence, learning readiness and socio-emotional developments. The subjects of this study were 63 children at age five and their mothers. Instruments included the children's intelligence test, preschool inventory for learning readiness, the socio-emtional rating scale and the inventory of HOME. The data of the present study were analyzed by the statistical methods of Pearson's product-moment correlation coefficient and step-wise multiple regression analysis. The kinds of HOME variables that significantly predict children's intelligence were "need gratification and avoidance of restriction" "quality of language environment" "play materials" "aspects of physical environment" "organization of stable and predictable environment". The variables that significantly predict children's socio-emotional developments were "breath of experience" "fostering maturity and independence" "developmental stimulation". All of the HOME variables were not significantly predict children's learning readiness. The kinds of HOME factors that significantly predict children's intelligence were factor II and factor III. Factor I predicted children's socio-emotional developments significantly. All of the HOME factors were not significantly predicted children's learning readiness.

• 한국컴퓨터정보학회논문지
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• 제23권11호
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• pp.175-183
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• 2018

In modern society, the optimal physical environment is constantly changing due to IT development, and it is provided with convenience. In this age environment, the children are growing up thinking that the value of community consciousness through relationship with others is not important in the social reality in which various ways and environments that can be done by themselves are succeeding. No matter how rapidly the world changes, a diverse learning environment is needed that establishes desirable human relationships and recognizes community consciousness and values. The purpose of this study was to investigate the effects of general children(elementary school 4th, 5th, and 6th graders) on the communication and peer relationship of the children participating in the archery experiential learning program, to emphasize the importance of physical activity programs, and also by analyzing the relationship between communication and improvement of peer relationship and to understand the effect of the archery experiential training learning which is one of exercise program. In order to verify the research problems, 30 experimental group and 30 comparative group were composed of 4th, 5th, and 6th grade elementary schools in Gwangsan-gu, Gwangju metropolitan city. The experiment group was participated in the archery experiential learning program for a total of 10 sessions, once a week for 60 minutes, and conducted a questionnaire survey. In this study, we examined the effect of archery experiential learning program on improving children 's communication and peer relationship ability. Thus, it showed that archery experiential learning program can be one of the important educational methods to promote the healthy character and development of children.

• Journal of Multimedia Information System
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• 제9권1호
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• pp.51-60
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• 2022

This paper raised the need to examine how the online education environment triggered by COVID-19 and the smart learning environment can be established in consideration of the improvement of education and learning through learning analysis. Many studies are being conducted in Korea, and the Ministry of Education is continuously striving to build a smart school by promoting strategies for promoting smart education on the way to a talent powerhouse. Nevertheless, there is no unified definition of smart learning, and it can be seen as customized (individualized) learning using smart devices. However, most of the discussions on the construction of smart schools so far have limitations in that they are limited to physical spaces. Accordingly, the opinions of teachers and learners were not sufficiently reflected in the establishment of the facility. This study intends to study smart learning in various departments. In addition, the subjects students in charge of the co-researcher of this study were analyzed. The total number of subjects was 951, and 434 responded to this study survey. In addition, students were well accepting the online environment, and in the future, regardless of COVID-19, research will be presented to improve mutual communication between professors and students in smart learning.

• 한국건설순환자원학회논문집
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• 제9권3호
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• pp.348-355
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• 2021

도로 포장에 널리 사용되는 아스팔트는 도로가 노출되는 환경에 따라 요구되는 물리적 특성이 상이하다. 이에 따라 첨가제의 배합에 따라 아스팔트가 어떤 물리적 특성을 나타내는지 평가하고 도로의 교통, 기후 환경에 맞추어 적절한 배합을 선택하는 것이 아스팔트 도로의 수명을 확보하기 위해 필수적이다. 아스팔트의 다양한 물리적 특성 중 소성변형에 대한 저항성을 측정하기 위해서는 Dynamic shear rheometer(DSR) 테스트를 주로 사용한다. 하지만 DSR 테스트는 실험 세팅에 따라 결과가 상이하고 특정 온도 범위 내에만 측정이 가능한 단점이 있다. 따라서 본 연구에서는 DSR 테스트의 단점을 극복하고자, Atomic force microscopy로부터 수집된 이미지를 학습하여 레올로지적 특성을 예측하고자 했다. 딥러닝 아키텍처 중 하나인 EfficientNet을 통해 이미지를 학습하였고 딥러닝 모델의 한계인 많은 데이터를 요구한다는 점을 극복하기 위해 전이학습을 이용하여 학습을 진행하였다. 학습된 모델은 이종의 첨가제를 사용하였음에도 높은 정확도로 아스팔트 바인더의 레올로지적 특성을 예측하였다. 특히, 전이학습을 사용하지 않았을 때와 비교하여 빠르게 학습이 가능했다.

• 한국응급구조학회지
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• 제7권1호
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• pp.5-28
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• 2003

The purpose of this study which was conducted by framing of standardized advanced emergency care instructor qualification course outline and training competent instructor Course development based on following educational principle and it would be expected more improved aspect. Advanced Emergency care Instructor Qualification Course Development (1) based on advanced emergency care instructor job analysis and paramedic job description. (2) Learning of emergency care instructor qualification course is continuous. It is important to begin at the learner's level of knowledge and to relate new learning to information the learner needs. (3) Learning of emergency care instructor qualification course is purposeful and must make sense to the learner. Progress in learning must make sense to the learner. Progress in learning must be constantly appraised through feedback. The purpose of learning BLS information and skills must be kept in sharp focus. (4) Learning involves as many senses as possible. The more stimulating a learner activity is to the senses, the longer the information will be retained. Conservative figures indicate that 75% of what is heard is for-gotten after 2 days. It has been said that learners remember (5) Learning activities must be appropriate for the emergency situation through the PBL educational method. In BLS lecture skill learning, the greatest proportion of class time should be spent in manikin practice, using performance sheets as a learning tool or guide. (6) Learning must be stimulating. Instructors can motivate learners by helping them achieve higher levels of proficiency and encouraging other levels of course completion, such as instructor and instructor trainer. (7) Learning is affected by the physical and social environment. The physical environment should be conducive to both the kind of learning taking place and the activities used for learning. Advanced emergency care instructor qualification course organized educational psychology, educational methodology I,II,III, educational material making skill, lecture & conversational skill, BLS theory & pratice lecture skill, minic lecture designed PBL module. test of minic lecture & pratice lecture skill. Advanced emergency care instructor qualification course continued to active instructor training and motivated to active EMS system.

• 한국보육지원학회지
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• 제14권5호
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• pp.137-152
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• 2018

Objective: The purpose of this study is to examine the effect of the childcare environment on childcare efficacy of childcare teachers. Methods: The participants in the study were 274 childcare teachers working at childcare centers. The childcare environment was divided into physical environment and the work support environment. Results: The results of this study are as follows. First, there was a significant difference in childcare efficacy depending on the age and career of the childcare teacher. Second, the childcare environment of the childcare center showed a static correlation with the childcare efficacy of the childcare teacher in both the physical environment and the work support environment. Third, the physical environment of the day care center had an affect on child care efficacy. Among the subfactors, furniture for routine care, play and learning had a significant impact. Fourth, the work support environment of the childcare center had an affect on childcare efficacy of the childcare teacher. Among the subfactors, staff interaction and cooperation, and opportunities for professional growth had a significant impact. Conclusion/Implications: In order to enhance childcare efficacy of childcare teachers, a high quality childcare environment should be established.

• 로봇학회논문지
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• 제14권2호
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• pp.122-130
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• 2019

Collecting a rich but meaningful training data plays a key role in machine learning and deep learning researches for a self-driving vehicle. This paper introduces a detailed overview of existing open-source simulators which could be used for training self-driving vehicles. After reviewing the simulators, we propose a new effective approach to make a synthetic autonomous vehicle simulation platform suitable for learning and training artificial intelligence algorithms. Specially, we develop a synthetic simulator with various realistic situations and weather conditions which make the autonomous shuttle to learn more realistic situations and handle some unexpected events. The virtual environment is the mimics of the activity of a genuine shuttle vehicle on a physical world. Instead of doing the whole experiment of training in the real physical world, scenarios in 3D virtual worlds are made to calculate the parameters and training the model. From the simulator, the user can obtain data for the various situation and utilize it for the training purpose. Flexible options are available to choose sensors, monitor the output and implement any autonomous driving algorithm. Finally, we verify the effectiveness of the developed simulator by implementing an end-to-end CNN algorithm for training a self-driving shuttle.

• 한국실내디자인학회:학술대회논문집
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• 한국실내디자인학회 1999년도 춘계학술발표대회 논문집
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• pp.83-86
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• 1999

The purpose of this study is to make interior environment which can support the education effectively through acceptance of the requirements of users about the environmental factors of learning spaces for the visually impaired students. For them, researcher investigated the literature cited and did the field survey. And also, this researcher analyzed user's satisfaction extent for structure, design, and technical environment factors by the evaluation elements. On the basis of the result of analysis, Two rooms which had big problems for physical environment were selected. And then the design recommendations focusing on environmental factors - circulation, furniture arrangement, colour, lighting etc. - were proposed by this researcher on the basis of space user's requriement.

• 교육시설 논문지
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• 제20권4호
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• pp.3-10
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• 2013

Basic precondition for effective curriculum on learning activities to take place, the internal and external environment of the school facilities, improve the environment of the classroom space and etc. Specifically, the use of classroom space, hardly learners improve their academic motivation to achievement tend to concentrate within the party regularly scheduled class hours. Physical environment surrounding them is giving considerable impact for behavioral psychological and bodily change of the learners. In this study, we are focused on the form of the learner in the general classroom space and classroom environment that can increase the learning effect will be examined. Consequently, What is appropriate classroom environment for learning increase the concentration of elements are presented.