• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.1-7
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• 2019

Nowadays learning has developed to a new way of anywhere and anytime by using mobile devices called m-learning which can provide flexibility, independency and creativity in academic environment. Most studies about m-learning are for higher education and the most users of m-learning are higher education students. Although developed countries are using m-learning in educational sectors, most of the Middle East countries are far from m-learning, and facing number of challenges. In Iran m-learning is still in early stage of implementation in higher education and in terms of technical and infrastructural aspects there is a vast gap in compare with developed countries. Although technical and infrastructural difficulties are one of the significant aspects in implementation and integration of m-learning technologies in education, the technology will not be successful if could not adopt with users. Due to the importance of user adoption with m-learning, there are limited studies about m-learning adoption in higher education of Iran. This paper attempts to review on technical and infrastructural aspects that facilitate m-learning which have effect on adoption of Iran higher education system. The review of the trend in the literature provides a reference for higher education institutes for decision making in developing m-learning for their students.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7474-7484
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• 2015

This study was conducted by implementing a structural analysis regarding adult learners' learning outcomes and their affecting factors in the lifelong educational institutions in Daejeon area with 960 adult learners. Research result was as following. First, learner and educational characteristics were confirmed to have an indirect impact on learning outcomes, which were mediated by learning satisfaction and commitment. Second, adult learner's characteristics directly influenced to learning commitment and satisfaction as well as educational institutions did. Third, learning commitment also directly affected learning satisfaction and outcomes. Fourth, learning satisfaction had a strong influence on learning outcomes. By all accounts, learning outcomes was directly influenced by learner, educational characteristics, and learning satisfaction. In addition, learning outcomes was indirectly impacted by mediating with learning satisfaction and commitment. Therefore, lifelong educational institutions should reinforce any strategies in order to enhance learning outcomes such as developing and providing more variable programs, making better class atmosphere and facility, positioning highly qualified teachers, and one-stop administration services.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.137-152
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• 2005

In this Paper, we Propose an efficient web-based video learning evaluation system that is tailored to individual student's characteristics through the use of user profile-based information filtering. As a means of giving video-based questions, keyframes are extracted based on the location, size, and color information, and question-making intervals are extracted by means of differences in gray-level histograms as well as time windows. In addition, through a combination of the category-based system and the keyword-based system, questions for examination are given in order to ensure efficient evaluation. Therefore, students can enhance school achievement by making up for weak areas while continuing to identify their areas of interest.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.271-281
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• 2022

Manual seed classification challenges can be overcome using a reliable and autonomous seed purity identification and classification technique. It is a highly practical and commercially important requirement of the agricultural industry. Researchers can create a new data mining method with improved accuracy using current machine learning and artificial intelligence approaches. Seed classification can help with quality making, seed quality controller, and impurity identification. Seeds have traditionally been classified based on characteristics such as colour, shape, and texture. Generally, this is done by experts by visually examining each model, which is a very time-consuming and tedious task. This approach is simple to automate, making seed sorting far more efficient than manually inspecting them. Computer vision technologies based on machine learning (ML), symmetry, and, more specifically, convolutional neural networks (CNNs) have been widely used in related fields, resulting in greater labour efficiency in many cases. To sort a sample of 3000 seeds, KNN, SVM, CNN and CNN-SVM hybrid classification algorithms were used. A model that uses advanced deep learning techniques to categorise some well-known seeds is included in the proposed hybrid system. In most cases, the CNN-SVM model outperformed the comparable SVM and CNN models, demonstrating the effectiveness of utilising CNN-SVM to evaluate data. The findings of this research revealed that CNN-SVM could be used to analyse data with promising results. Future study should look into more seed kinds to expand the use of CNN-SVMs in data processing.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.10-16
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• 2023

The ever-increasing amount of data generated by various industries and systems has led to the development of data mining techniques as a means to extract valuable insights and knowledge from such data. The electrical energy industry is no exception, with the large amounts of data generated by SCADA systems. This study focuses on the analysis of historical data recorded in the SCADA database of the Libyan Electricity Company. The database, spanned from January 1st, 2013, to December 31st, 2022, contains records of daily date and hour, energy production, temperature, humidity, wind speed, and energy consumption levels. The data was pre-processed and analyzed using the WEKA tool and the Apriori algorithm, a supervised machine learning technique. The aim of the study was to extract association rules that would assist decision-makers in making informed decisions with greater efficiency and reduced costs. The results obtained from the study were evaluated in terms of accuracy and production time, and the conclusion of the study shows that the results are promising and encouraging for future use in the Libyan Electricity Company. The study highlights the importance of data mining and the benefits of utilizing machine learning technology in decision-making processes.

• Journal of The Korean Association For Science Education
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• v.22 no.1
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• pp.54-63
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• 2002

The purpose of this study was to investigate the effect of decision-making activities in lesson on improving decision-making ability to meet bioethical issues in everyday situation. Worksheet for decision-making was consisted of six steps: Identification of problem, searching relevant information, generation of alternatives, identification of values for selection criteria, evaluation of alternatives, review of consequence. The results of this study showed that the scores of decision-making were increased by the activities of worksheets. The scores of identification of problem, generation of alternatives, and evaluation of alternatives were increased meaningfully. However, the scores of searching relevant information, identification of values for selection criteria, and review of consequence were not increased. It seems that all steps of decision-making ability could not improve by short-term learning. Low level performance was appeared on the step of searching relevant information and evaluation of alternatives. This result indicated that students could not apply the biological knowledge to decision-making in the face of bioethical issues. In conclusion, the learning experience of decision-making is essential to foster rational decision-making ability. The activity of decision-making should be included in science class and curriculum.

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.9-20
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• 2014

Making good predictions about the outcome of one's actions would seem to be essential in the context of social interaction and decision-making. This paper proposes a computational model for learning articulated motion patterns for action recognition, which mimics biological-inspired visual perception processing of human brain. Developed model of cortical architecture for the unsupervised learning of motion sequence, builds upon neurophysiological knowledge about the cortical sites such as IT, MT, STS and specific neuronal representation which contribute to articulated motion perception. Experiments show how the model automatically selects significant motion patterns as well as meaningful static snapshot categories from continuous video input. Such key poses correspond to articulated postures which are utilized in probing the trained network to impose implied motion perception from static views. We also present how sequence selective representations are learned in STS by fusing snapshot and motion input and how learned feedback connections enable making predictions about future input sequence. Network simulations demonstrate the computational capacity of the proposed model for motion recognition.

• Educational Technology International
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• v.19 no.2
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• pp.199-228
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• 2018

The main purposes of this study were (a) to analyze the research trend of educational use of tangible technology, (b) to identify tangible learning mechanisms, and potential benefits of learning with tangible technology, and (c) to provide references and future research directions. We conducted a systematic literature review to search for academic papers published in recent five years (from 2013 to 2017) in the major databases. Forty papers were coded and analyzed by the established coding framework in four dimensions: (a) basic publication information, (b) learning context, (c) learning mechanism, and (d) learning benefits. Overall, the results show that tangible technology has been used more for young learners in the kindergarten and primary school contexts mainly for science learning, to achieve both cognitive and affective learning outcomes, by coupling tangible objects with tabletops and desktop computers. From the synthesis of the review findings, this study suggests that the affordances of tangible technology useful for learning include embodied interaction, physical manipulations, and the physical-digital representational mapping. With such technical affordances, tangible technologies have the great potential in three particular areas in education: (a) learning spatial relationships, (b) making the invisible visible, and (c) reinforcing abstract concepts through the correspondence of representations. In conclusion, we suggest some areas for future research endeavors.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.439-443
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• 1996

A fuzzy teaming controller is experimentally designed to control the ball k beam system in this paper. Although most fuzzy controllers have been built just to emulate human decision-making behavior, it is necessary to construct the rule bases by using a learning method with self-improvement when it is difficult or impossible to get them only by expert's experience. The algorithm introduces a reference model to generate a desired output and minimizes a performance index function based on the error and error-rate using the gradient-decent method. In our balancing experiment of the ball ＆ beam system, this paper shows that the fuzzy control rules by learning are superior to the expert's experience.

• Korean Journal of Human Ecology
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• v.2 no.1
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• pp.89-98
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• 1999

Kimchi is a traditional food in Korea. It is a fermented food made by several vegetables. Kimchies have traditionally made at home, but the use of commercial Kimchies is increasing. The purpose of this study was to evaluate the intake and evaluation of commercial Kimchies and the perception of desirable learning methods making Kimchies among female high-school students. Three hundred and seventy one female high-school students living in Chonbuk province were participated in the survey. The results obtained were as follows: 1. The percentage of subjects who had consumed commercial Kimchies at least once was 49.7%. It was higher in the subjects living in the rural area(65.6%) than in the urban area(37.9%) at p${\le}$0.001. 2. Positive reasons for the consume of commercial Kimchies was: ‘saving time($4.11{\pm}0.74$)’, ‘convenience to buy when it is needed($4.03{\pm}0.78$)’, ‘variety($3.59{\pm}0.86$)’ and ‘looking good($3.21{\pm}0.98$)’. However, commercial Kimchi received low scores for: ‘sanitation($2.24{\pm}0.96$)’, ‘taste($2.84{\pm}0.96$)’, and ‘economy($2.89{\pm}1.02$)’. 90.5% of the subjects believed that the use of commercial Kimchi will be increased. 3. 24.3% of the subjects had an experience of making Kimchi alone, and 88.7% of the subjects had assisted their mother making Kimchi. 88.9% of the subjects reported that they would like to learn how to make Kimchi from their mothers. 84.0% of the subjects want to make Kimchi by themselves at home when they will be housewives. In conclusion, this report suggests that commercial Kimchi should be produced under more sanitary conditions and Kimchi producers should also develop a variety of tastes to match consumer＇s preferences. There is also a need for education for making high quality Kimchies in school programs of Home Economics. (Korean J of Human Ecology 2(1) : 89-98, 1999)