• Journal of Information Processing Systems
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• v.18 no.3
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• pp.443-456
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• 2022

An efficient and reasonable resource allocation strategy can greatly improve the service quality of Internet of Vehicles (IoV). However, most of the current allocation methods have overestimation problem, and it is difficult to provide high-performance IoV network services. To solve this problem, this paper proposes a network resource allocation strategy based on deep learning network model DDQN. Firstly, the method implements the refined modeling of IoV model, including communication model, user layer computing model, edge layer offloading model, mobile model, etc., similar to the actual complex IoV application scenario. Then, the DDQN network model is used to calculate and solve the mathematical model of resource allocation. By decoupling the selection of target Q value action and the calculation of target Q value, the phenomenon of overestimation is avoided. It can provide higher-quality network services and ensure superior computing and processing performance in actual complex scenarios. Finally, simulation results show that the proposed method can maintain the network delay within 65 ms and show excellent network performance in high concurrency and complex scenes with task data volume of 500 kbits.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.5
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• pp.239-252
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• 2008

To facilitate the processes of e-learning resource description, discovery and reuse, e-learning objects should be appropriately described and classified using standard metadata that need to be published in a registry to reduce duplication of effort and enhance semantic interoperability. This paper describes how standard ebXML registries can be used for semantic grid computing for annotating, storing, discovering and retrieving e-learning object metadata. For semantic annotation of e-learning objects, IEEE Learning Object Metadata (LOM) is adopted as the metadata ontology. In order to support the e-learning metadata ontology in interoperable ebXML registries, a mapping scheme between LOM and ebXML Registry Information Model (RIM) is proposed. The usefulness of sharing e-learning object metadata is demonstrated by prototyping a semantic registry based on the scheme.

• ETRI Journal
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• v.44 no.6
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• pp.915-924
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• 2022

In this paper, we present a two-stage scalable channel estimator (TSCE), a deep learning (DL)-based scalable, and robust channel estimator for wireless cellular networks, which is made up of two DL networks to efficiently support different resource allocation sizes and reference signal configurations. Both networks use the transformer, one of cutting-edge neural network architecture, as a backbone for accurate estimation. For computation-efficient global feature extractions, we propose using window and window averaging-based self-attentions. Our results show that TSCE learns wireless propagation channels correctly and outperforms both traditional estimators and baseline DL-based estimators. Additionally, scalability and robustness evaluations are performed, revealing that TSCE is more robust in various environments than the baseline DL-based estimators.

• Educational Technology International
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• v.16 no.2
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• pp.201-229
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• 2015

Culture is a crucial concept that forms the thinking and behaviors of a group of people, and it influences interactions in learning. Thus, it is also essential to consider cultural sensitivity in online learning technologies and instructional design as education is a set of learning actions based on values and perceptions. MOOCs, the latest online learning platform, are global online learning platforms that provide global learners with free and various learning resources including courses from different world-class institutions. Despite globalization having brought learners closer to sharing similar learning resources, the actual experiences with the resource are expected to vary according to cultures, mainly because learning behavior is a set of outcomes based on cultural differences. Taking this into consideration, this study aims to examine MOOCs from a cultural perspective in order to facilitate global learners, especially Korean learners, to utilize MOOCs with user-friendly services and contents. To achieve this objective, the study first identified and developed an evaluation criteria to examine the cultural sensitivity of MOOCs and conducted case studies on courses from major MOOC providers including edX and Coursera. From the findings, design recommendations of contents and courses on MOOCs were suggested to provide Korean learners with optimal learning experiences.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.1
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• pp.115-129
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• 2019

This study aimed to develop methods for technical design education that can be intimately connected to the industrial field. For this, technical design jobs performed in the fields of the domestic and foreign fashion industries and their required competences were examined, and educational methods based on constructivism were proposed. Korean fashion technical designers' works were identified, and then the fashion technical designer's responsibilities and qualifications were collected and analyzed from global employment sites. On the basis of the collection and analysis, hands-on staff members and education experts were interviewed about required competences for the actual business and possible suitable methods for education. The results of research showed that in the case of the US, job systems and relevant duties for technical designers were clearly defined by clothing brands, whereas in Korea, businesses were systematized around vendors, not brands, and as a result the businesses of technical package composition and specification proposals were not performed properly. This study organized the contents of technical design education into fit development and specification, the composition of technical design packages, the evaluation and approval of samples, fit schedule management and fitting, block pattern setting and pattern correction, sewing specifications appropriate for styles and materials, grading, technical terms, and production management. As for the technical design education models, the cognitive apprenticeship model, resource-based learning, the problem-based and anchored model, and the problem-based and resource-based models were proposed.

• Journal of Fisheries and Marine Sciences Education
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• v.21 no.1
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• pp.16-27
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• 2009

The purpose of this study was to develop of learning strategy scale for college students. This study further classified several sub-areas and defined each concepts of learning strategy. Based upon the classification of each sub-areas, tentative test items were developed through the verification of validity by three professionals. A pilot study of the developed scale was administered to 239 college students. And the research collected major data from 1,012 college students. Data were analyzed to obtain item quality, reliability, and validity analysis. The results of this study were as follows. The scale for learning strategy was defined by eight factors and they were 'self-management strategy', 'examination-readiness strategy', 'cognitive strategy', 'memorizing strategy', 'reporting strategy', 'resource-utilization strategy', 'self-regulated strategy', 'cooperative learning strategy'. The results of the confirmatory factor analysis proved the eight factors in the learning strategy. And criterion validity evidence was also obtained from a correlation analysis of the level of academic achievement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.30-45
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• 2024

This study introduces an effective method for predicting individual local tax delinquencies using prevalent machine learning and deep learning algorithms. The evaluation of credit risk holds great significance in the financial realm, impacting both companies and individuals. While credit risk prediction has been explored using statistical and machine learning techniques, their application to tax arrears prediction remains underexplored. We forecast individual local tax defaults in Republic of Korea using machine and deep learning algorithms, including convolutional neural networks (CNN), long short-term memory (LSTM), and sequence-to-sequence (seq2seq). Our model incorporates diverse credit and public information like loan history, delinquency records, credit card usage, and public taxation data, offering richer insights than prior studies. The results highlight the superior predictive accuracy of the CNN model. Anticipating local tax arrears more effectively could lead to efficient allocation of administrative resources. By leveraging advanced machine learning, this research offers a promising avenue for refining tax collection strategies and resource management.

• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.69-77
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• 2017

In this paper, a disaster response scheme based on deep learning and augmented reality technology is proposed and a network resource reservation scheme is presented accordingly. The features of deep learning, augmented reality technology and its relevance to the disaster areas are explained. Deep learning technology can be used to accurately recognize disaster situations and to implement related disaster information as augmented reality, and to enhance disaster response capabilities by providing disaster response On-site disaster response agent, ICS (Incident Command System) and MCS (Multi-agency Coordination Systems). In the case of various disasters, the fire situation is focused on and it is proposed that a plan to strengthen disaster response capability effectively by providing fire situation recognition based on deep learning and augmented reality information. Finally, a scheme to secure network resources to utilize the disaster response method of this paper is proposed.

• Journal of Agricultural Extension & Community Development
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• v.17 no.2
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• pp.261-277
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• 2010

This study is undertaken to present the facilitation plan of English library that specialized the resource-based learning to provide learning that is suited for student's own learning style and self-leading learning as the method to learn contents required for individuals as a method for improving the English education environment in the rural areas. For this purpose, a study was conducted to find out the possibility of facilitating English library in the rural areas on the basis of consulting for structuring and operating English library in public libraries located in isolated areas clustered with low income class in the urban areas where the conditions are similar to the rural areas and results are shown as the followings. First, it displayed the possibility to have the rural area located with many closed schools or small-sized schools to facilitate the available facilities to build up the environment to specialize in English education that would be as comparable as any facilities in any urban setting. Second, it would enable the conditions to moderate the conflict on education environment for local residents who felt inequality in education by providing the benefit for fine education linked to public education through English library without going through private education. And third, English library that has the limitations in locality or economic means would actively participate by local educational institutions and volunteers to enhance the sense of master for the local residents and bring residents together to make positive impact on local economy facilitation.

• Asia-Pacific Journal of Business
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• v.11 no.3
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• pp.261-271
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• 2020

Purpose - This study was to establish a unified tourism management class for university students based on Gangwon-do. Community based learning(CBL) was applied to provide a tangible and intangible resource of tourism resources the theoretical approaches and the actual experiences of the community. Design/methodology/approach - In order to design a unified tourism management module, this study applied qualitative research and quantitative research methods to collect information on the direction of the module. the study conducted in-depth interviews and then an online survey. Findings - According to the results of the study, the main parts should include necessity of unification, inter-Korean tourism, inter-Korean cooperation, inter-Korean economy, and international relations. Research implications or Originality - The overall composition of the unification tourism management class should be designed as the unification tourism management theory to acquire the subject knowledge, the field trip to the border area for experiential learning, and the assignment of the field study task to understand the community.