• Journal of information and communication convergence engineering
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• 제14권2호
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• pp.97-105
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• 2016

With the increasing demand for interoperability among existing learning resource systems in order to enable the sharing of learning resources, such resources need to be annotated with ontologies that use different metadata standards. These different ontologies must be reconciled through ontology mediation, so as to cope with information heterogeneity problems, such as semantic and structural conflicts. In this paper, we propose an ontology-mapping technique using Semantic Web Rule Language (SWRL) to generate semantic mapping rules that integrate learning resources from different systems and that cope with semantic and structural conflicts. Reasoning rules are defined to support a semantic search for heterogeneous learning resources, which are deduced by rule-based inference. Experimental results demonstrate that the proposed approach enables the integration of learning resources originating from multiple sources and helps users to search across heterogeneous learning resource systems.

• 공학교육연구
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• 제26권6호
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• pp.19-29
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• 2023

This study aims to develop and apply a metaverse-based instructional design model for the education in science and technology. It analyzed the concept and characteristics of metaverse, existing non-contact education models, and major teaching strategies systematically. Based on the prior researches, an instructional design model using metaverse is developed that presents metaverse-related teaching strategies and design principles for the before-, during-, and after-lesson phases. Then, this model was applied to a project-based learning program, conducted a perception survey on instructors and learners, and revised the metaverse instructional design model based on the results of the survey. In the Metaverse Instructional Design Model, before-lesson phase is a physical and psychological preparation stage for class participation, which includes familiarization with the Metaverse learning environment, formation of expectations for education, and self-directed pre-learning. During the lesson, to effectively deliver the lesson content, it is necessary to build confidence in the learning environment, promote learning participation, provide reference materials, perform team projects and provide feedback, digest learning content, and transfer learning content. The after-lesson phase provides strategies for ongoing interaction between learners and mentors. This study introduces a new instructional design model that utilizes metaverse and shows the potential of metaverse-based education in science and technology. It also has important implications in that it provides practical guidelines for the effective design and implementation of metaverse-based education.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.165-165
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• 2023

Streamflow prediction is a critical task in water resources management and essential for planning and decision-making purposes. However, the streamflow prediction is challenging due to the complexity and non-linear nature of hydrological processes. The transfer learning is a powerful technique that enables a model to transfer knowledge from a source domain to a target domain, improving model performance with limited data in the target domain. In this study, we apply the transfer learning using the Informer model, which is a state-of-the-art deep learning model for streamflow prediction. The model was trained on a large-scale hydrological dataset in the source basin and then fine-tuned using a smaller dataset available in the target basin to predict the streamflow in the target basin. The results demonstrate that transfer learning using the Informer model significantly outperforms the traditional machine learning models and even other deep learning models for streamflow prediction, especially when the target domain has limited data. Moreover, the results indicate the effectiveness of streamflow prediction when knowledge transfer is used to improve the generalizability of hydrologic models in data-sparse regions.

• International Journal of Internet, Broadcasting and Communication
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• 제15권3호
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• pp.231-238
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• 2023

As the demand for distance education increases, interest in the management of learners' rights is increasing. Blockchain technology is a technology that guarantees the integrity of the learner's learning history, and enables learner-led learning control, data security, and sharing of learning resources. In this paper, we proposed a blockchain technology-based learning management system based on Hyperledger Fabric that can be verified through permission between nodes among blockchain platforms. Learning resources can be shared differentially according to the learning progress. Also the percentage of individual learners that can be managed. As a result of the study, the superiority of the platform in terms of convenience compared to the existing platform was demonstrated. As a result of the performance evaluation for the research in this paper, it was confirmed that the convenience was improved by more than 5%, and the performance was 4-5% superior to the existing platform in terms of learner satisfaction.

• 한국도서관정보학회지
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• 제38권1호
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• pp.423-441
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• 2007

독서능력은 학생의 문제해결능력과 자기주도 학습능력 그리고 평생학습능력을 위한 핵심능력이며, 학습독서는 자원기반학습이나 탐구기반학습을 통해서 이루어진다. 본 연구에서는 학습독서의 한 방법으로서 통합교육과정을 제시하고 있는데, 이 방법은 교과교사와의 협력을 통해서 완성된다. 특히 본 연구에서는 통합교육과정과 협동수업을 위한 구체적인 학습모형으로서 독서기반 정보문제 해결모형을 소개한다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• 한국과학교육학회지
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• 제42권4호
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• pp.477-486
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• 2022

본 연구에서는 상황 학습 이론과 실행 기반의 과학 교육에 관한 문헌들에 대한 고찰을 통해 과학적 실행 중심의 수업에서 과학 개념학습의 가능성을 살펴보았다. 먼저, 상황 학습 이론이 학생들의 과학적 실행에의 참여를 강조하는 최근 과학 교육 개혁의 흐름과 관련이 깊으며, 상황 학습의 관점에서 개념 학습은 학습자가 개념을 자원으로 활용하며 실행에 참여하는 동안 개념적 행위 주체성을 발현하여 개념을 지속적으로 발전시키는 과정을 통해 이루어진다는 것을 알 수 있었다. 또, 이러한 상황 학습 이론은 과학적 실행 기반의 수업에서 과학 개념을 학습하는 데에도 적용된다는 것을 확인하였다. 즉, 과학적 실행 중심의 과학 수업에서는 과학 개념이 자원으로 활용되며, 과학 개념을 자원으로 활용하는 동안 학생들은 과학적 실행에 더 잘 참여할 수 있고, 과학적 실천에의 참여는 개념적 행위 주체성의 발현을 통해 개념 학습을 더욱 촉진할 수 있다. 이러한 고찰의 내용이 학교 과학 교육에 주는 시사점을 논의하였다.

• The Journal of Asian Finance, Economics and Business
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• 제6권1호
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• pp.205-215
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• 2019

Researchers have confirmed the relationship between ambidexterity learning and innovation performance, but according to the resource-based theory, the relationship between ambidexterity learning and innovation performance is also affected by the internal resources of the organization. Internal resources are an important factor affecting the transformation of learning outcomes into performance. In addition, few scholars have pointed out whether different types of learning have different effects on different types of innovation performance. This study collects data from 170 High-tech enterprises in Shandong, china, and discusses the effects of exploitative learning and explorative learning on management innovation performance and technological innovation performance. This study further examines the moderating role of slack resource on the relationship between ambidexterity learning and innovation performance. Results show that ambidexterity learning has positive effect on innovation performance. Compared with exploitative learning, explorative learning has a greater impact on management innovation performance; compared with explorative learning, exploitative learning has a greater impact on technological innovation performances. Slack resource has positive moderating role between the relationship of exploitative learning, explorative learning and technology innovation performance. But Slack resource has no moderating role between the relationship of exploitative learning, explorative learning and management innovation performance.

• International Journal of Computer Science & Network Security
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• 제23권6호
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• pp.13-16
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• 2023

This study aims to explore the status of e-learning in the public sector institutes of the Sukkur region in Pakistan. A survey was conducted to collect data from students and teachers regarding their awareness, access, and use of e-learning resources. The results showed that although there is a widespread use of the internet and mobile devices for accessing information, there is a lack of awareness and access to e-learning resources. Barriers to accessing e-learning content and a lack of familiarity with e-learning content development technologies were also identified. The study concludes that there is a need for improved e-learning facilities and curriculum in the public sector institutes of the Sukkur region in Pakistan. Recommendations are provided for developing a correctness-centered e-learning based curriculum that is tailored to the specific needs of the students in the region. It is hoped that the findings of this study will inform efforts to improve the teaching and learning process in the region and provide students with greater flexibility and access to study materials.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3663-3679
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• 2020

Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms.