• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.25-34
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• 2012

In this study, in the process of testing before the release of the software products designed, software testing manager in advance should be aware of the testing-information. Therefore, the effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and applied property of learning effect based on truncated time and delayed S-shaped software reliability. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than autonomous errors-detected factor that is generally efficient model can be confirmed. This paper, a failure data analysis was performed, using time between failures, according to the small sample and large sample sizes. The parameter estimation was carried out using maximum likelihood estimation method. Model selection was performed using the mean square error and coefficient of determination, after the data efficiency from the data through trend analysis was performed.

• The Journal of Korean Academic Society of Nursing Education
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• v.17 no.2
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• pp.208-217
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• 2011

Purpose The purpose of this study was to explore the experience of service-learning in connection with the major of nursing. Method: This is qualitative research based on the application of a focus-group research method and Glaser's grounded theory. The nine participants of the research participated in the process of developing a service-learning program to promote health in the elderly. They operated the program by acting as instructors for more than 12 months. Results: The basic socio-psychological problems hared by the participants of the research is 'burden'. The basic social process required to solve the problem is 'self-realization' which has been successively shown in the order of the stage of experiencing a surge of will, the stage of recognizing the occurrence of internal and external changes, the stage of being confident, and the stage of obtaining self-respect. Throughout the process, the participants solved 'burden' in a positive way through reflections and reciprocity, developing and strengthening their capabilities. Conclusion: Based on the results, it is necessary to consider the development of a service-learning program in connection with the nursing major in order to provide the students studying nursing with the opportunity to have various learning experiences.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.12
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• pp.1-7
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• 2021

The deep learning image processing technique was used to prevent accidents in lathe work caused by worker negligence. During lathe operation, when the chuck is rotated, it is very dangerous if the operator's hand is near the chuck. However, if the chuck is stopped during operation, it is not dangerous for the operator's hand to be in close proximity to the chuck for workpiece measurement, chip removal or tool change. We used YOLO (You Only Look Once), a deep learning image processing program for object detection and classification. Lathe work images such as hand, chuck rotation and chuck stop are used for learning, object detection and classification. As a result of the experiment, object detection and class classification were performed with a success probability of over 80% at a confidence score 0.5. Thus, we conclude that the artificial intelligence deep learning image processing technique can be effective in preventing incidents resulting from worker negligence in future manufacturing systems.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.25-32
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• 2020

In the context-aware system, rule-based AI technology has been used in the abstraction process for getting context information. However, the rules are complicated by the diversification of user requirements for the service and also data usage is increased. Therefore, there are some technical limitations to maintain rule-based models and to process unstructured data. To overcome these limitations, many studies have applied machine learning techniques to Context-aware systems. In order to utilize this machine learning-based model in the context-aware system, a management process of periodically injecting training data is required. In the previous study on the machine learning based context awareness system, a series of management processes such as the generation and provision of learning data for operating several machine learning models were considered, but the method was limited to the applied system. In this paper, we propose a training data generating method of a machine learning model to extend the machine learning based context-aware system. The proposed method define the training data generating model that can reflect the requirements of the machine learning models and generate the training data for each machine learning model. In the experiment, the training data generating model is defined based on the training data generating schema of the cardiac status analysis model for older in health status notification service, and the training data is generated by applying the model defined in the real environment of the software. In addition, it shows the process of comparing the accuracy by learning the training data generated in the machine learning model, and applied to verify the validity of the generated learning data.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1239-1242
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• 2003

The neural networks are a famous model to learn the nonlinear function or nonlinear system. The main point of neural network is that the difference actual output from desired output is used to update weights. Usually, the gradient descent method is used for the learning process. On training process, if learning rate is too large, neural networks hardly guarantee convergence of neural networks. On the other hand, if learning rate is too small, the training spends much time. Therefore, one major problem in use of neural networks are to decrease the teaming time while neural networks are guaranteed convergence. In this paper, we suggest the model of fuzzy logic to neural networks to calibrate learning rate. This method is to tune learning rate dynamically according to error and demonstrates the optimization of training.

• International Journal of Contents
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• v.10 no.2
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• pp.42-46
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• 2014

This study suggests a teaching-learning method to improve creative design abilities of students majoring in design. By suggesting a creative design-inducing (CDI) teaching-learning method process and a creative design-inducing (CDI) teaching-learning method, this study aims to expand creative thinking among students with the aim of producing produce creative output as well as improving the effectiveness of design teaching. It also presents a case of the teaching-learning method in a design-related department, the process of teaching where the new method is applied is also examined. The teaching method this study suggests has the following merits: First, it allows the teacher to use various tools depending on the creative thinking abilities of individuals. By providing students with custom-made teaching, the method motivates and focuses students during the lesson. Second, it is easier for students to generate creative ideas than with other teaching methods.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.3
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• pp.148-157
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• 1996

Availability of input trajectories corresponding to desired output trajectories is often important in designing control systems for batch and other transient processes. In this paper, we propose a predictive control-type model-based iterative learning algorithm which is applicable to finding the nominal input trajectories of a linear time-invariant batch process. Unlike the other existing learning control algorithms, the proposed algorithm can be applied to nonsquare systems and has an ability to adjust noise sensitivity as well as convergence rate. A simple model identification technique with which performance of the proposed learning algorithm can be significantly enhanced is also proposed. Performance of the proposed learning algorithm is demonstrated through numerical simulations.

• East Asian mathematical journal
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• v.36 no.2
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• pp.273-289
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• 2020

This study introduces the process and results of developing an adaptive math learning program for self-directed learning. It presented the process and results of developing an adaptive math learning program that takes into account the level of learners using artificial intelligence. We wanted to get some suggestions on developing programs for artificial intelligence-based mathematics. The program was developed as Math4U, an application based on smart devices in the "character and expression" area for 7th grade. The Application Math4U may be used differently depending on its purpose. It is also expected to be a useful tool for providing self-directed learning to students as the basis for educational research using smart devices in a changing educational environment.

• English Language & Literature Teaching
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• v.15 no.4
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• pp.137-156
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• 2009

This case study examines language learners' oral interactive practices and what they learn along with these practices. Language learners who study abroad take on the challenge of living in a foreign place and undergo difficulties in communicating and interacting with people in their new country. These difficulties, caused by cultural differences, are experienced most particularly in their daily interactions. Language learners' trials and efforts to learn English while dealing with a different culture and the difficulties are mainly observed for this paper. The process of learning a second culture is closely related to the process of learning a second language. Oral interactive practices can give the study abroad language learners opportunities to learn their target culture. Therefore, the purpose of this paper is to discuss how participating in interactive practices assists the learners in understanding their target culture while they deal with their difficulties inherent in studying abroad. This study adds weight to the notion that culture is an essential and major factor in learning a language, and that only active participation in interactions can be effective in learning both a language and its culture.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.176-183
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• 2020

This study inquired about the convergence learning program for childhood based on Erikson's play theory and design education for children's behavior development. I analyzed the convergence learning programs of Summer Camps in the Pacific Science Center, Galileo Learning. The contents of the programs show the most used imaginary and symbolic contents that represent the real-world problems which are related design thinking process. The curriculums and structure of the programs are based on the design thinking method and K-12 theory. The visual thinking method and the applications are used for expressing their creativity and approaching the technical skills easily. The play concept theory is an affirmative way to strengthen the children's psychological and social development. Therefore, the convergence learning program should integrate the design thinking process and apply the play concept theory for supporting and developing the children's behavior.