• Asia pacific journal of information systems
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• v.15 no.4
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• pp.27-60
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• 2005

The purpose of this study is to call attention to the consensus of stakeholders of corporate e-Learning system for the sake of its success. We identified the critical success factors(contents, technical features, management, and organizational support) as major components of corporate e-Learning systems and questioned whether stakeholders' consensus on the importance of these components facilitates the successful implementation of these components. We also questioned whether the influence of these components on user satisfaction could be moderated by contextual factors. Based on empirical testing of 18 e-Learning user companies, we verified that the consensus of stakeholders regarding the importance of content, technological features, and organizational support has a positive influence on the perceived quality of these factors in their e-Learning systems, which in turn is positively related to user satisfaction. The learning subjects and learning style did significantly moderate the influences of these perceived qualities on user satisfaction.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.737-739
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• 2015

To accommodate today's higher education student, fewer textbooks are printed and more are becoming digital. Keeping with the modern era, hybrid versions of textbooks have all end-of-chapter assessment content moved to digital learning systems such as MindTap$^{TM}$ by Cengage $Learning^{(R)}$. In this work, we introduce new pedagogical strategies to combat academic e-cheating, specifically cheating on assessments given in online astronomy courses. The strategies we present in this work are employed in Horizons: Exploring the Universe, Hybrid, 13th Edition, and Universe, Hybrid, 8th Edition, by Seeds, Backman, and Montgomery.

• Journal of the Korea Society of Computer and Information
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• v.21 no.7
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• pp.93-100
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• 2016

This paper shows what kind of influence the learning motivation factors have on the effectiveness of Flipped Learning Model through the case of operating a JAVA programming subject. The Flipped Learning Approach consisting of Before Class, Before or At Start of Class, and In Class provides the students with learning motivation as well as satisfies Keller's ARCS(Attention, Relevance, Confidence, Satisfaction) to keep them studying steadily. This research conducts the operation of Flipped Learning and gets Exploratory Factor Analysis and Reliability Analysis from the result of the course experience questionnaire at the end of the class. Given this survey result, Flipped Learning approach improves the learners' satisfaction in class and the effectiveness in the fields of understanding learning context more than does the previous lecture-based learning approach by pacing learning procedure and conducting self-directed learning.

• Educational Technology International
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• v.16 no.2
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• pp.85-110
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• 2015

This study investigated whether college students' self-efficacy, learning strategy utilization, academic burnout, and school support predict course satisfaction and learning persistence. To this end, self-efficacy, learning strategy utilization, academic burnout, and school support were used as prediction variables; and course satisfaction and learning persistence, as criterion variables. The subjects were 178 students who registered for online and mobile "Culture and Art History" courses at K online university. They participated in an online survey. Multiple regression analysis revealed that self-efficacy and learning strategy utilization positively predicted course satisfaction and learning persistence, academic burnout negatively predicted them, and school support predicted neither. Accordingly, we suggest that raising self-efficacy and learning strategy utilization, and reducing academic burnout in the learning environment will improve the course satisfaction and learning persistence of online learners.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.527-535
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• 2007

The number of SMEs taking up information systems such as Enterprise Resource Planning has been growing rapidly, and many of those organizations have stepped into the stage of ongoing use at this point. Thus, research which takes into account idiosyncratic nature of SME environment is more important than before. Through an empirical study using survey method, we tried to examine the importance of end user's feedback seeking behavior in SMEs and how environmental factors affecting such behavior reinforce and interact with the feedback seeking behavior itself. The result shows that end user's active role as a voluntary feedback seeker is important in utilizing information systems in accordance with the initial design intention in ongoing use environment. Furthermore, in order to facilitate such feedback seeking behavior in SME environment, it is essential that management's involvement and communicating to its employees the importance of effectively utilizing the information systems as well as the support of peer IT champ.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2086-2098
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• 2018

Security plays a vital role and is the key challenge in Mobile Ad-hoc Networks (MANET). Infrastructure-less nature of MANET makes it arduous to envisage the genre of topology. Due to its inexhaustible access, information disseminated by roaming nodes to other nodes is susceptible to many hazardous attacks. Intrusion Detection and Prevention System (IDPS) is undoubtedly a defense structure to address threats in MANET. Many IDPS methods have been developed to ascertain the exceptional behavior in these networks. Key issue in such IDPS is lack of fast self-organized learning engine that facilitates comprehensive situation awareness for optimum decision making. Proposed "Intelligent Behavioral Hybridized Intrusion Detection and Prevention System (IBH_IDPS)" is built with computational intelligence to detect complex multistage attacks making the system robust and reliable. The System comprises of an Intelligent Client Agent and a Smart Server empowered with fuzzy inference rule-based service engine to ensure confidentiality and integrity of network. Distributed Intelligent Client Agents incorporated with centralized Smart Server makes it capable of analyzing and categorizing unethical incidents appropriately through unsupervised learning mechanism. Experimental analysis proves the proposed model is highly attack resistant, reliable and secure on devices and shows promising gains with assured delivery ratio, low end-to-end delay compared to existing approach.

• The Journal of Economics, Marketing and Management
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• v.11 no.4
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• pp.31-39
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• 2023

Purpose: This study attempted to systematize a support system that can enhance teaching core competencies by establishing a scale for diagnosing teaching core competencies at University A. Research design, data and methodology : To this end, the first Delphi was conducted With six experts related to university core competency modeling research by extracting factors and designing structured questionnaires through a literature review process that collects and analyzes prior research related to domestic and foreign university teaching competency. The derived questions were diagnosed on 27 professors, and independent sample t-verification and ANOVA were conducted using SPSS 24.0 for analysis by key teaching competency factors. Result: What is the standard suitability of KMO. It was shown as 929 (KMO standard conformity value is close to 1), and Barlett's sphericity verification showed χ2=5773.295, df=1081, p<.It appeared as 001 and confirmed that it was suitable for conducting factor analysis. Conclusions: The core competencies of A University teachers were set based on the educational goals of A University, such as basic teaching competency, creative teaching competency, practical teaching competency, and communication teaching competency. This means that the concept and factors of the core competency of professors are likely to change, and in the end, continuous efforts to upgrade and apply research on core competency of professors are essential to quickly and organically respond to changes in competency required to increase the competitiveness of universities.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.1-8
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• 2021

With the rapid growth of intelligent devices and communication technologies, 5G network environment has become more heterogeneous and complex in terms of service management and orchestration. 5G architecture requires supportive technologies to handle the existing challenges for improving the Quality of Service (QoS) and the Quality of Experience (QoE) performances. Among many challenges, traffic steering is one of the key elements which requires critically developing an optimal solution for smart guidance, control, and reliable system. Mobile edge computing (MEC), software-defined networking (SDN), network functions virtualization (NFV), and deep learning (DL) play essential roles to complementary develop a flexible computation and extensible flow rules management in this potential aspect. In this proposed system, an accurate flow recommendation, a centralized control, and a reliable distributed connectivity based on the inspection of packet condition are provided. With the system deployment, the packet is classified separately and recommended to request from the optimal destination with matched preferences and conditions. To evaluate the proposed scheme outperformance, a network simulator software was used to conduct and capture the end-to-end QoS performance metrics. SDN flow rules installation was experimented to illustrate the post control function corresponding to DL-based output. The intelligent steering for network communication traffic is cooperatively configured in SDN controller and NFV-orchestrator to lead a variety of beneficial factors for improving massive real-time Internet of Things (IoT) performance.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.423-436
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• 2017

This paper presents a deep learning-based road segmentation framework from very high-resolution orthophotos. The proposed method uses Deep Convolutional Autoencoders for end-to-end mapping of orthophotos to road segmentations. In addition, a set of post-processing steps were applied to make the model outputs GIS-ready data that could be useful for various applications. The optimization of the model's parameters is explained which was conducted via grid search method. The model was trained and implemented in Keras, a high-level deep learning framework run on top of Tensorflow. The results show that the proposed model with the best-obtained hyperparameters could segment road objects from orthophotos at an average accuracy of 88.5%. The results of optimization revealed that the best optimization algorithm and activation function for the studied task are Stochastic Gradient Descent (SGD) and Exponential Linear Unit (ELU), respectively. In addition, the best numbers of convolutional filters were found to be 8 for the first and second layers and 128 for the third and fourth layers of the proposed network architecture. Moreover, the analysis on the time complexity of the model showed that the model could be trained in 4 hours and 50 minutes on 1024 high-resolution images of size $106{\times}106pixels$, and segment road objects from similar size and resolution images in around 14 minutes. The results show that the deep learning models such as Convolutional Autoencoders could be a best alternative to traditional machine learning models for road segmentation from aerial photographs.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.152-161
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• 2024

The purpose of this study sought to determine the impact of shared leadership perceived by organizational members on team effectiveness and team learning behavior. For this purpose, the results of the empirical analysis of 206 organizational members are as follows. First, shared leadership was analyzed to improve team effectiveness. Second, shared leadership had a positive effect on team learning behavior. Third, team learning behavior was statistically significantly analyzed for team effectiveness. This study confirmed the importance of shared leadership, which has a positive impact on team effectiveness and team learning behavior. This may require building a new culture that can demonstrate the inherent leadership of organizational members in the influence relationship between shared leadership, team effectiveness, and team learning behavior. In other words, in order to systematically demonstrate and implement shared leadership, the execution ability of executives, managers, and working-level managers is important. To this end, it is necessary to build an organizational culture that matches the characteristics of the organization and develop and continuously implement human resource development systems and programs that can implement this.