• Journal of Digital Convergence
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• v.19 no.6
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• pp.355-362
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• 2021

This study was attempted to examine the effectiveness of mobile-based military WithYou programs. The research design was a quasi-experimental study with one group pretest-posttest design. Data were collected from 17 December to 23 December 2020. 42 and 37 members of the Air base in City C participated in the pretest and posttest, respectively. A video education program developed to inspire bystander intervention efficacy and the intention of helping peers and strangers was provided on mobile. The data collected before and after attending the program were analyzed using descriptive statistics and t-test. The results showed that mobile-based military WithYou program was effective in increasing the intention to help friends and others. Attempts to develop and apply educational content using mobile devices for military personnel will be meaningful.

• Convergence Security Journal
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• v.20 no.5
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• pp.65-74
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• 2020

Recently, with the rapid development of eXtended Reality(XR) technology, the development and use of education and training systems using XR technology is increasing significantly. In particular, in areas that involve great risks and high costs such as military training and counter-terrorism training, the use of XR based simulators is preferred because they can improve training performance, reduce training costs, and minimize the risk of safety issues that may occur in actual training, by creating a training environment similar to actual training. In this paper, we propose a plan to build and evaluate an XR based hyper-realistic counter-terrorism education, training, and evaluation system to improve the ROK police's ability to respond to terrorist situations using the 5G and AR based Integrated Command and Control Platform previously developed by the Korea Military Academy. The proposed system is designed to improve counter-terrorism capabilities with virtual training for individual and team units based on hyper-realistic content and training scenarios. Futhermore, it can also be used as a on-site command and control post in connection with a simulation training site and an actual operation site.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.4
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• pp.29-39
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• 2017

Various electronic warfare situations drive the need to develop an integrated electronic warfare simulator that can perform electronic warfare modeling and simulation on radar threats. In this paper, we analyze the components of a simulation system to reversely model the radar threats that emit electromagnetic signals based on the parameters of the electronic information, and propose a method to gradually maintain the reverse extrapolation model of RF threats. In the experiment, we will evaluate the effectiveness of the incremental model update and also assess the integration method of reverse extrapolation models. The individual model of RF threats are constructed by using decision tree, naive Bayesian classifier, artificial neural network, and clustering algorithms through Euclidean distance and cosine similarity measurement, respectively. Experimental results show that the accuracy of reverse extrapolation models improves, while the size of the threat sample increases. In addition, we use voting, weighted voting, and the Dempster-Shafer algorithm to integrate the results of the five different models of RF threats. As a result, the final decision of reverse extrapolation through the Dempster-Shafer algorithm shows the best performance in its accuracy.

• International Journal of Highway Engineering
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• v.9 no.1 s.31
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• pp.1-15
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• 2007

The objective of this paper is the establishment of finite element analysis frame work for pavement research. Finite element analysis results simulating various loading experiments are verified with sensor measurements obtained from the KHC Test Road. The accuracy of the finite element analysis can be supported by these efforts so that it helps spread out the finite element analysis to pavement research and design processes. The finite element model used in this research is the full 3D nonlinear model including concrete slab, lean concrete base, subbase, shoulder, dowel, and tie-bar. In order to accomplish the accurate verification, the loading condition and the pavement temperature distribution are exactly simulated with field measured data. The curling behavior and the strain distribution are compared with measured responses from the loading tests with a truck and the FWD. Strain and curling predictions from the concrete slab are matched well with measured responses but the strain prediction from the lean concrete base is not matched with measured response. In addition, the magnitude of permanent curling is evaluated with the finite element analysis.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.158-167
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• 2016

This study evaluates potential sources of errors in k-NN(k-nearest neighbor) algorithm such as procedures, variables, and input data. Previous research has been thoroughly reviewed for understanding fundamentals of k-NN algorithm that has been widely used for short-term traffic states prediction. The framework of this algorithm commonly includes historical data smoothing, pattern database, similarity measure, k-value, and prediction horizon. The outcomes of this study suggests that: i) historical data smoothing is recommended to reduce random noise of measured traffic data; ii) the historical database should contain traffic state information on both normal and event conditions; and iii) trial and error method can improve the prediction accuracy by better searching for the optimum input time series and k-value. The study results also demonstrates that predicted error increases with the duration of prediction horizon and rapidly changing traffic states.

• Journal of the Korean Regional Science Association
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• v.34 no.2
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• pp.49-64
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• 2018

In this study, we propose a methodology of center setting based on commuter traffic in the Seoul metropolitan area, and compared with the center setting method in previous studies. For this purpose, the center was derived by performing factor analysis and spatial autocorrelation analysis using the interregional commuting traffic for the administrative districts of the metropolitan area. In addition, we compared the results of applying each methodology of previous studies by classifying the methodologies into four categories: single index - based, multiple index - based, nonparametric, and spatial statistical method. As a result, some similar centers including major centers in Seoul were derived, but different results were obtained for each methodology and it was found that there were limitations in setting the multi sub-centers. Through this study, it can be reaffirmed that it is necessary to establish and supplement the spatial structure plan based on the new center system in the situation where the seoul metropolitan area of the polycentric spatial structure is now being discussed in the context of the urban realms.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.251-263
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• 2019

Recently the huge demand for Internet media streaming has dramatically increased the cost of the CDN (Content Delivery Network) and the need for a means to reduce it is increasing day by day. In this situation, a P2P-assisted DASH technology has recently emerged, which uses P2P (Peer-to-Peer) communications based on WebRTC (Web Real-Time Communication) standards to reduce the CDN cost. This paper proposes an algorithm that can significantly improve CDN cost savings in this technology by selecting peers based on the transport history. Also we implemented this algorithm in an experimental system and, after setting experimental conditions that emulate the actual mobile network environment, we measured the performance of the experimental system. As a result, we demonstrated that the proposed algorithm can achieve higher CDN cost savings compared to the conventional algorithm where peers are selected at random.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.759-767
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• 2020

This paper proposes a new Recurrent neural network (RNN) based spectrum sensing technique for cognitive radio communications. The proposed technique determines the existence of primary user's signal without any prior information of the primary users. The method performs high-speed sampling by considering the whole sensing bandwidth and then converts the signal into frequency spectrum via fast Fourier transform (FFT). This spectrum signal is cut in sensing channel bandwidth and entered into the RNN to determine the channel vacancy. The performance of the proposed technique is verified through computer simulations. According to the results, the proposed one is superior to more than 2 [dB] than the existing threshold-based technique and has similar performance to that of the existing Convolutional neural network (CNN) based method. In addition, experiments are carried out in indoor environments and the results show that the proposed technique performs more than 4 [dB] better than both the conventional threshold-based and the CNN based methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.282-293
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• 2019

Purpose: After developing and imparting knowledge of a simulation-based emergency airway management education program for nursing students, this study identified the effects of the education by evaluating emergency airway management knowledge, Clinical Performance Ability, self-efficacy, and critical thinking disposition. Method: The participants were 30 nursing students. Data were collected from October 14 to November 11, 2017, and analyzed using IBM SPSS Version 22.0. Results: The simulation-based nursing education program was developed and applied based on the ADDIE model involving five stages: analysis, design, development, implementation and evaluation. Comparing the pre-and post-education results, we observed statistically significant improvement when considering emergency airway management knowledge (t=-9.98, p<0.001), Clinical Performance Ability (t=-23.90, p<0.001), self-efficacy (t=-16.77, p<0.001), and critical thinking disposition (t=-5.04, p<0.001). Conclusions: Simulation-based emergency airway management training program is an effective educational program that enhances the emergency airway management knowledge, Clinical Performance Ability, self-efficacy, and critical thinking disposition of nursing students. We believe that the program developed in this study contributes towards improvement of patient nursing quality by enhancing the ability of nursing students to cope with emergencies in practice. Furthermore, it can be applied for educating new nursing students, and contribute to the development of nursing practices.

• Korean Journal of Cognitive Science
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• v.14 no.3
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• pp.23-36
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• 2003

A comprehension-based approach to learning assumes that incoming information and background knowledge are integrated to form a mental representation which is subsequently used to incorporate new knowledge. It is demonstrated that this approach can be validated by comparing human and computational model performance in the prompt learning context. A computational model (ADAPT-UNIX) based on the construction-integration theory of comprehension (Kintsch, 1988; 1998) predicted how users learn from help prompts which are designed to assist UNIX composite command production. In addition, the comparison also revealed high similarity in composite production task performance between model and human. Educational implications of present research are discussed on the basis of the fact that prompt instructions have differential effect on learning and application as background knowledge varies.