• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.9-16
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• 2019

In this paper, it will analyze security problems, so technology's potential can apply to business security area. First, in order to deep learning do security tasks sufficiently in the business area, deep learning requires repetitive learning with large amounts of data. In this paper, to acquire learning ability to do stable business tasks, it must detect abnormal IP packets and attack such as normal software with malicious code. Therefore, this paper will analyze whether deep learning has the cognitive ability to detect various attack. In this paper, to deep learning to reach the system and reliably execute the business model which has problem, this paper will develop deep learning technology which is equipped with security engine to analyze new IP about Session and do log analysis and solve the problem of mathematical role which can extract abnormal data and distinguish infringement of system data. Then it will apply to business model to drop the vulnerability and improve the business performance.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.375-383
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• 2020

The study was to examine the mediating effect of self-efficacy in learning in the relationship between the learning satisfaction and motivation to transfer of nursing students who received the psychiatric nursing convergence simulation practicum using standardized patients. Participants were 144 third grade nursing students. Data were analyzed descriptive statistics, t-test, one-way ANOVA, Pearson's correlation coefficient analysis, and multiple regression following the Baron and Kenny's method and Sobel test for mediation. There were significant correlations between learning satisfaction and self-efficacy in learning(r=.686, p<.001), learning satisfaction and motivation to transfer(r=.633, p<.001) and self-efficacy in learning and motivation to transfer(r=.804, p<.001). Self-efficacy in learning showed partial mediating effects in the relationship between learning satisfaction and motivation to transfer(Z=7.63, p<.001). To increase the motivation to transfer, strategies to enhance the self-efficacy of nursing students are required.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.151-178
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• 2023

The purpose of this study is to investigate the effect of school library reading classes on the convergence literacy of adolescents based on the convergence reading education model. To achieve this, elements of convergence education for future-oriented competence were derived from the level of reading education based on previous studies and literature, and the effectiveness of education was measured by conducting a convergence literacy test targeting 50 general high school students. In this study, reading classes and tests were conducted over 12 sessions from April 2022 to November 2022, and the study participants were divided into two groups, and convergence reading education and self-reading education were applied respectively. The analysis results of this study are as follows. First, It was verified that there was a significant difference in the promotion of convergent literacy of adolescents according to the method of reading education. Second, it was verified that convergence reading education had a significant effect on convergence literacy of adolescents such as convergence, creativity, self-direction and communication ability. Third, as a result of verifying whether learning motivation plays a mediating role in convergence reading education influencing convergent literacy, learning motivation played a partial mediating role and had an indirect effect on creativity, self-direction, and communication ability between convergence reading education and convergence literacy, but showed no significant mediating effect on convergence ability.

• Journal of the Korea Convergence Society
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• v.7 no.2
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• pp.109-118
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• 2016

The purpose of this study was I cultivate practical ability to solve diverse and complex issues in the field of convergence and applied learning and practical training element through problem-based learning to preliminary sports leaders. Selected students in grades 3 to 28 Sports Science S university people to them as participants and through a qualitative case study methods, such as group interviews, participant observation, open questionnaire and the following results were obtained. First, the level of satisfaction on class was high and the class was evaluated with significant contemplation. Second, it has been collecting a variety of learning materials to understand, interpret and improve the ability to solve practical problems in the process of actively reconstruct their own knowledge structure. It also gave a positive impact on the creative and divergent thinking to accelerate the promotion of autonomy. Third, opinions about teamwork, sharing your thoughts with colleagues point is that you can see yourself in other people's positions were evaluated as positive effects.

• Journal of the Korea Convergence Society
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• v.10 no.8
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• pp.115-120
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• 2019

This study aims to prove the value of convergence-based mobile English curriculum for English education prior to its practical use. This is deferent from the existing studies in developing and studying a curriculum using an English program loaded in mobile to make an effective English learning. In order to find out how well teachers are aware of this curriculum, we performed qualitative researches. Some English teachers asked for feedback about the curriculum gave us positive feedback in most areas such as learning authentic English, repetition effects, cooperative learning, self-efficacy experience, and so on. As a negative feedback, they were afraid of students' easy and free attitudes because of the new learning environments. This problem can be solved by the very close communications between teacher and student through on and off line. Next time applying this curriculum to the field and analyzing will be expected.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.39-44
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• 2022

Mathematics franchise education companies are developing various online learning systems to provide on-off integrated education to learners. Most online learning systems deliver one-way lecture content to learners and perform quantitative problem-solving learning for learning results. However, each learner has different academic achievement competencies, and it is impossible to determine exactly where the level of understanding fell when solving a math method. and based on this, establish an online learning system to discover the weak points of learners and propose an effective learner management method. Through the developed learning method and system, it is expected to cultivate balanced problem-solving ability for learners and provide differentiated brand image and counseling service to franchise companies.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.185-190
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• 2022

The study of the meaning of learning began with the question of what causes people to start learning. Learning is humanization and personification. Learning is a basic human instinct, and the essence of learning is to understand other people and my life, learn community, and learn social capital. Learning gives humans nomadic judgment and provides an opportunity for a productive life for mankind, who must live in constant harmony with the social environment. Learning provides opportunities for self-management, communication with various generations, and self-actualization.

• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.369-376
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• 2020

This study was conducted to verify the effectiveness of learning using micro-running. To this end, the learning materials of the class were produced in three forms: micro-learning, existing e-learning, and handouts, to compare the learning satisfaction and learning effect for college students at Y and K universities located in K-do. First, when using learning materials in the form of micro-learning, learning satisfaction was the highest. Second, the learning effect was effective for both e-learning and micro-learning. And micro-learning was more effective when both types of learning materials were used. The results of this study look forward to activating micro-learning in university by researching micro-learning of the new learning type that emerged as a social phenomenon, highlighting the importance of micro-learning and presenting basic data for subsequent study.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.79-83
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• 2021

This paper proposes a novel image classification method based on few-shot learning, which is mainly used to solve model overfitting and non-convergence in image classification tasks of small datasets and improve the accuracy of classification. This method uses model structure optimization to extend the basic convolutional neural network (CNN) model and extracts more image features by adding convolutional layers, thereby improving the classification accuracy. We incorporated certain measures to improve the performance of the model. First, we used general methods such as setting a lower learning rate and shuffling to promote the rapid convergence of the model. Second, we used the data expansion technology to preprocess small datasets to increase the number of training data sets and suppress over-fitting. We applied the model to 10 monkey species and achieved outstanding performances. Experiments indicated that our proposed method achieved an accuracy of 87.92%, which is 26.1% higher than that of the traditional CNN method and 1.1% higher than that of the deep convolutional neural network ResNet50.