• Journal of Korean Academy of Nursing
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• v.53 no.1
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• pp.87-100
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• 2023

Purpose: This study aimed to develop a nursing simulation learning module for coronavirus disease 2019 (COVID-19) patient-care and examine its effects on clinical reasoning competence, clinical competence, performance confidence, and anxiety in COVID-19 patient care for nursing students. Methods: A non-equivalent control group pre- and post-test design was employed. The study participants included 47 nursing students (23 in the experimental group and 24 in the control group) from G City. A simulation learning module for COVID-19 patient-care was developed based on the Jeffries simulation model. The module consisted of a briefing, simulation practice, and debriefing. The effects of the simulation module were measured using clinical reasoning competence, clinical competence, performance confidence, and anxiety in COVID-19 patient-care. Data were analyzed using χ²-test, Fisher's exact test, t-test, Wilcoxon signed-rank test, and Mann-Whitney U test. Results: The levels of clinical reasoning competence, clinical competence, and performance confidence of the experimental group were significantly higher than that of the control group, and the level of anxiety was significantly low after simulation learning. Conclusion: The nursing simulation learning module for COVID-19 patient-care is more effective than the traditional method in terms of improving students' clinical reasoning competence, clinical competence, and performance confidence, and reducing their anxiety. The module is expected to be useful for educational and clinical environments as an effective teaching and learning strategy to empower nursing competency and contribute to nursing education and clinical changes.

• Journal of Korean Biological Nursing Science
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• v.3 no.2
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• pp.63-68
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• 2001

Increasing interest in computer-mediated learning technologies has prompted educators to incorporate them into many learning environments ; however, there is still little evaluative evidence to support their effectiveness. This report describes the development and evaluation of a web-based instructional program on basic nursing science for nursing students. Researcher-designed questionnaires were used to assess the characteristics of our students, and to solicit their ratings of the instructional program on ease of use, accuracy of content, clarity of content, interest, and convenience of the program, using 5-point Likert scales. The respondents indicated that the package was easy and convenient to use, with high technical quality, and of a level challenging to some but not all of the students. On-line quizzes were most highly rated. Also it was confirmed that frequent users of electronic bulletin board showed much higher achievement score than that of nonfrequent users. It was also found that the effect of cyber education was dependent on the active participation of the students. These data suggest that the use of web-based instructional program as a distance education strategy can be an effective method for nursing students and nurses.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.185-196
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• 2022

The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.221-228
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• 2021

Recent improvements on the quality, fidelity and availability of biometric data have led to effective human physical activity detection (HPAD) in real time which adds significant value to applications such as human behavior identification, healthcare monitoring, and user authentication. Current approaches usually use machine-learning techniques for human physical activity recognition based on the data collected from wearable accelerometer sensor from a single wearable smart device on the user. However, collecting data from a single wearable smart device may not provide the complete user activity data as it is usually attached to only single part of the user's body. In addition, in case of the absence of the single sensor, then no data can be collected. Hence, in this paper, a continuous HPAD will be presented to effectively perform user activity detection with mobile service infrastructure using multiple wearable smart devices, namely smartphone and smartwatch placed in various locations on user's body for more accurate HPAD. A case study on a comprehensive dataset of classified human physical activities with our HAPD approach shows substantial improvement in HPAD accuracy.

• Journal of the Korean Institute of Educational Facilities
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• v.19 no.1
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• pp.25-35
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• 2012

The function and the role of school are changing according to various future-oriented education models such as open-ended learning cycle, community learning center, re-schooling, network system and de-schooling, which reflect recent social demands related to discussions on sustainability, low birth rate and ageing. what changes to our school buildings have been there? This study is aimed that shows the architectural change of school buildings and environments in 2000's. It reveals the architectural tendancy through some school buildings, 'the excellent facility school award' winner which Ministry of Education, Science and Technology have chosen annually since 1998. In the past decade, it is outstanding change that mass composition, window patterns and exterior wall materials are diversified greatly. The most of them have a opened main hall and multi-purpose spaces which give effective educational environment to students. Although visual changes are outstanding, we still need qualitative educational space program and improved school building design according to future-educational demands.

• Journal of the Korean earth science society
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• v.24 no.7
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• pp.625-634
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• 2003

This study was designed to analyze the differences in science achievement and satisfaction between the environments of Face-To-Face (FTF) and Computer Mediated Communication (CMC), and between the interactions of Teacher-Students (TS) and Students-Students (SS). The activities for the interaction in the FTF and the CMC were carried out in the environments of traditional classrooms and the on-line network of communication computer, respectively. These experiments for four different groups (CMC-TS, CMC-SS, FTF-TS and FTF-SS) were performed with respect to 103 students of three 10th grade classes at a girls' high school in Chungju city. The questionnaires were composed of 5questions for achievement, and 13 questions on Likert scale for satisfaction. The data was analyzed using ANOVA, and through examination of each question about the satisfaction. The mean of the science achievement in learning activity was significantly higher in the CMC environment than the FTF. Also, the score in the TS interaction was meaningfully higher than the SS. Under the common environment of the CMC, science achievement and satisfaction in the TS interaction were significantly higher than in the SS. A similar result has been obtained in the satisfaction case even in the common environment of the FTF. The itemized analysis for the satisfaction shows a high score in the individual condition of CMC and TS, compared to that of FTF and SS, respectively. Thus, the school activity, formed in the TS interaction in the CMC environment is more effective at improving science achievement and satisfaction in the teaching and learning of science.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.106-114
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• 2020

We propose appropriate criteria for obtaining fish species data and number of learning data, as well as for selecting the most appropriate convolutional neural network (CNN) to efficiently classify exotic invasive fish species for their extermination. The acquisition of large amounts of fish species data for CNN learning is subject to several constraints. To solve these problems, we acquired a large number of fish images for various fish species in a laboratory environment, rather than a natural environment. We then converted the obtained fish images into fish images acquired in different natural environments through simple image synthesis to obtain the image data of the fish species. We used the images of largemouth bass and bluegill captured at a pond as test data to confirm the effectiveness of the proposed method. In addition, to classify the exotic invasive fish species accurately, we evaluated the trained CNNs in terms of classification performance, processing time, and the number of data; consequently, we proposed a method to select the most effective CNN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4177-4190
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• 2015

Current research on Internet of Things (IoT) has primarily addressed the means to enhancing smart resource allocation, automatic network operation, and secure service provisioning. In particular, providing satisfactory security service in IoT systems is indispensable to its mission critical applications. However, limited resources prevent full security coverage at all times. Therefore, these limited resources must be deployed intelligently by considering differences in priorities of targets that require security coverage. In this study, we have developed a new application of Cognitive Radio (CR) technology for IoT systems and provide an appropriate security solution that will enable IoT to be more affordable and applicable than it is currently. To resolve the security-related resource allocation problem, game theory is a suitable and effective tool. Based on the Blotto game model, we propose a new strategic power allocation scheme to ensure secure CR communications. A simulation shows that our proposed scheme can effectively respond to current system conditions and perform more effectively than other existing schemes in dynamically changeable IoT environments.

• Steel and Composite Structures
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• v.51 no.6
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• pp.679-695
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• 2024

This paper presents a novel technique that combines machine learning (ML) with moth-flame optimization (MFO) methods to predict the axial compressive strength (ACS) of concrete filled double skin steel tubes (CFDST) columns. The proposed model is trained and tested with a dataset containing 125 tests of the CFDST column subjected to compressive loading. Five ML models, including extreme gradient boosting (XGBoost), gradient tree boosting (GBT), categorical gradient boosting (CAT), support vector machines (SVM), and decision tree (DT) algorithms, are utilized in this work. The MFO algorithm is applied to find optimal hyperparameters of these ML models and to determine the most effective model in predicting the ACS of CFDST columns. Predictive results given by some performance metrics reveal that the MFO-CAT model provides superior accuracy compared to other considered models. The accuracy of the MFO-CAT model is validated by comparing its predictive results with existing design codes and formulae. Moreover, the significance and contribution of each feature in the dataset are examined by employing the SHapley Additive exPlanations (SHAP) method. A comprehensive uncertainty quantification on probabilistic characteristics of the ACS of CFDST columns is conducted for the first time to examine the models' responses to variations of input variables in the stochastic environments. Finally, a web-based application is developed to predict ACS of the CFDST column, enabling rapid practical utilization without requesting any programing or machine learning expertise.

• International Commerce and Information Review
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• v.13 no.3
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• pp.229-248
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• 2011

The increasing complexity of business and social settings bas lead to innovation becoming a strategic imperative. The need for innovation in the quest for competitive advantage also means that firms must be dynamic and flexible. This is often achieved through collaborative arrangements such as strategic alliances or strategic network Many organizations form alliances by leveraging their resources to gain access to the partner's skills and capabilities; ultimately to enhance innovation and performance. We demonstrate empirically that the "chain of innovation" is central to the process of innovation in global alliances. This chain comprises the creativity and learning processes and knowledge stock in alliances. Our empirical analysis is based on a survey of alliances that resulted in 114 responses. For management, this research bas significant potential in guiding attention to the chain of innovation, to better manage the overall process of innovation in alliances. Our work shows that more effective creativity and learning processes and a greater knowledge stock lead to a more effective alliance innovation process. Managers therefore, need to concentrate on creating environments wherein the processes of creativity and learning are fostered, increasing the alliance knowledge stock and in turn, increasing innovative output via an effective innovation process.