• International journal of advanced smart convergence
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• v.6 no.1
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• pp.82-88
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• 2017

Emergency lights and exit signs are an indispensable part of safety precautions for effective evacuation in case of emergency in public buildings. These emergency sign indicates safe escape routes and emergency doors, using an internationally recognizable sign. However visibility of those signs drops drastically in case of emergency situations like fire smoke, etc. and loss of visibility causes serious problems for safety evacuation. This paper propose a novel emergency light and exit sign built-in with Bluetooth Low Energy (BLE) Beacon to assist the emergency self-guiding evacuation using devices for crisis and emergency management to avoid panic condition inside the buildings. In this approach, the emergency light and exit sign with the BLE beacons deployed in the indoor environments and the smart devices detect their indoor positions, direction to move, and next exit sign position from beacon messages and interact with map server in the Internet / Intranet over the available LTE and/or Wi-Fi network connectivity. The map server generate an optimal emergency exit path according to the nearest emergency exit based on a novel graph generation method for less route computation for each smart device. All emergency exit path data interfaces among three system components, the emergency exit signs, map server, and smart devices, have been defined for modular implementation of our emergency evacuation system. The proposed exit sign experimental system has been deployed and evaluated in real-time building environment thoroughly and gives a good evidence that the modular design of the proposed exit sign system and a novel approach to compute emergency exit path route based on the BLE beacon message, map server, and smart devices is competitive and viable.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.597-599
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• 2010

In this paper, by considering the real UWA channel environments, the measured channel data is used to generate the UWA channel model and calculate the relative parameters for underwater OFDM systems. Practical least square (LS) based channel estimation with linear interpolation are adopted to obtain the channel state information (CSI) at receiver side. As multi-input multi-output (MIMO) processing techniques, Alamouti code is implemented and evaluated to perform for space time block coding (STBC) and space frequency block coding (SFBC) for UWA OFDM systems with the MIMO configuration of $2{\times}1$, at the same time, $1{\times}2$ maximum ratio combining (MRC) is performed for the purpose of comparison. The simulation results show that, with perfect channel estimation, SFBC failed to work duo to the serious frequency selectivity of UWA channel environments. When the practical channel estimation is applied, in the case of STBC, the proposed 4-column pilot pattern gives better performance about 7dB than SISO system.

• Journal of Korean Home Economics Education Association
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• v.13 no.3
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• pp.119-130
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• 2001

The purpose of this research is to discover how Practical Reasoning Home Economics Instruction(PRHEI) applied to food and nutrition units would impact on the morality of female high school students. The research sample was drawn from the two freshman classes of \"M\" High School far Girls. located in the Pusan area. One classroom of 50 students was used as the test group and the other of 47 as the control group for the total of 97 students. Measuring the intellectual and behavioral morality scores followed the pre-post test design under which the PRHEI was administered to the test group during the period of eight weeks in a semester. Whereas the control group received the conventional lecture-oriented instruction during the same period. The effects of PRHEI on morality were measured using the system developed in 1972 by Ontario Institute for Studies in Education. and translated by Kim. Ahn-Jung in 1982. The system developed by Yang. Byung-Han in 1994 was utilized to measure the behavioral morality score. In analyzing the collected data. SPSS/WIN was used to generate means standard deviation and t-test. The research findings are as follows : First. The students who have been taught under the PRHEI score higher on the intellectual morality scale than the control group receiving the lecture-oriented instruction. Second. The test croup students do not show any notable differences from the control group students receiving the lecture-oriented approach on the behavioral morality scale; however, the former do show statistically significant differences from the latter in the sub-factor of honesty scoring higher means over the control group.

• Convergence Security Journal
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• v.19 no.5
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• pp.107-118
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• 2019

Based on the Internet of Things technology, one of the core technologies of the fourth industrial revolution, our Ministry of Defense is also pushing to establish M-IoT in defense area to improve management efficiency, innovate military culture and strengthen military power. However, devices connected to the Military Internet of Things can be easily exposed to various of cyber threats as most of them are developed and with a focus on improving sensing and communication skills that collect and transmit data. And it is not easy to uniquely identify the numerous heterogeneous devices, and to establish a secure communication channel between devices or between devices and management servers. In this paper, based on PUF technology, we propose a novel key management scheme that can uniquely identify the various devices, and generate the secret keys needed for the establishment of a secure communication channel using non-replicable information generated by the PUF. We also analyze the efficiency of our proposed scheme through comparison with existing key management scheme and verify the logic and security using BAN Logic.

• Convergence Security Journal
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• v.20 no.2
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• pp.111-121
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• 2020

Deep neural networks (DNNs) provide good performance for machine learning tasks such as image recognition and object recognition. However, DNNs are vulnerable to an adversarial example. An adversarial example is an attack sample that causes the neural network to recognize it incorrectly by adding minimal noise to the original sample. However, the disadvantage is that it takes a long time to generate such an adversarial example. Therefore, in some cases, an attack may be necessary that quickly causes the neural network to recognize it incorrectly. In this paper, we propose a fast misclassification sample that can rapidly attack neural networks. The proposed method does not consider the distortion of the original sample when adding noise. We used MNIST and CIFAR10 as experimental data and Tensorflow as a machine learning library. Experimental results show that the fast misclassification sample generated by the proposed method can be generated with 50% and 80% reduced number of iterations for MNIST and CIFAR10, respectively, compared to the conventional Carlini method, and has 100% attack rate.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.12
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• pp.511-517
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• 2006

The key issues in high power, high energy applications such as electromagnetic launchers include safety, reliability, flexibility, efficiency, compactness, and cost. To explore some of the issues, a control scheme for a large current wave-forming was designed, built and experimentally verified using a 2.4MJ pulse power system (PPS). The PPS was made up of eight capacitors bank unit, each containing six capacitors connected in parallel. Therefore there were 48 capacitors in total, with ratings of 22kV and 50kJ each. Each unit is charged through a charging switch that is operated by air pressure. For discharging each unit has a triggered vacuum switch (TVS) with ratings of 200kA and 250kV. Hence, flexibility of a large current wave-forming can be obtained by controlling the charging voltage and the discharging times. The whole control system includes a personal computer(PC), RS232 and RS485 pseudo converter, electric/optical signal converters and eight 80C196KC micro-controller based capacitor-bank module(CBM) controllers. Hence, the PC based controller can set the capacitor charging voltages and the TVS trigger timings of each CBM controller for the current wave-forming. It also monitors and records the system status data. We illustrated that our control scheme was able to generate the large current pulse flexibly and safely by experiments. The our control scheme minimize the use of optical cables without reducing EMI noise immunity and reliability, this is resulting in cost reduction. Also, the reliability was increased by isolating ground doubly, it reduced drastically the interference of the large voltage pulse induced by the large current pulse. This paper contains the complete control scheme and details of each subsystem unit.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.82-89
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• 2015

The researches of image recognition have been processed traditionally. Especially, face recognition technology has been received attractions with advance and applied to various areas according as camera sensor embedded into many devices such as smart phone. In this study, we design and develop a feature vector generation technique of face for making animation caricatures using methods for face detection which are previous stage of face recognition. At first, we detect both face region and detailed eye region of component element by Viola&Johns's realtime detection method which are called as ROI(Region Of Interest). And then, we generate feature vectors of eye region by utilizing factors as opposed to the periphery and by using appearance information of eye. At this point, we focus on the embedded information in many color spaces to overcome the problems which can be occurred by using one color space. We propose a feature vector generation method using information from many color spaces. Finally, we experiment the test of feature vector generation by the proposed method with enough quantity of sample picture data and evaluate the proposed method for factors of estimating performance such as error rate, accuracy and generation time.

• Journal of Korean Elementary Science Education
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• v.33 no.1
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• pp.21-29
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• 2014

This study analyzed the inquiry activities in the 'matter' units from each science textbook for the fifth and the sixth graders developed by the 2007 revised national curriculum, using Practical Activity Analysis Inventory proposed by Millar(2009) to examine types of learning objectives, hands-on contents(what students have to do with objects and materials), minds-on contents(what students have to 'do' with ideas), and logical structure each activity had. The results of this study are as follows: First, most learning objectives of the inquiry activities seems to be suitable for the standards of 2007 revised national curriculum. Second, the standards of 2007 revised national curriculum are properly reflected in hands-on contents of inquiry activities. Third, minds-on contents of inquiry activities are well developed to meet the standards of 2007 revised national curriculum as a whole. Fourth, the logical structures of inquiry activities are mostly adequate for achieving the goals of the 2007 revised national curriculum. In the textbook for the fifth graders, however, all the activities are focusing too much on using students' current ideas to generate a prediction and collecting data to explore or test it. Based on these findings, this research has concluded that learning objectives, minds-on contents and logical structures of inquiry activities need to be designed carefully for students to be exposed to various activities when developing following textbooks.

• Journal of Ecology and Environment
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• v.32 no.1
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• pp.47-53
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• 2009

The soil carbon stock for a Pinus densiflora forest at Gwangneung, central Korea was estimated using the soil carbon model, Yasso. The soil carbon stock measured in the forest was 43.73 t C $ha^{-1}$, and the simulated initial (steady state) soil carbon stock and the simulated current soil carbon stock in 2007 were 39.19 t C $ha^{-1}$ and 38.90 t C $ha^{-1}$, respectively. Under the assumption of a $0.1^{\circ}C$ increase in mean annual temperature per year, the decomposition and litter fractionation rates increased from 0.28 to 0.56 % $year^{-1}$ and the soil carbon stock decreased from 0.03 to 0.12 % $year^{-1}$. Yasso is a simple and general model that can be applied in cases where there is insufficient input information. However, in order to obtain more accurate estimates in Korea, parameters need to be recalibrated under Korean climatic and vegetation conditions. In addition, the Yasso model needs to be linked to other models to generate better litter input data.

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.562-568
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• 2016

In this paper, we focus on recognition of speed-limit signs among a few types of traffic signs because speed-limit sign is closely related to safe driving of drivers. Although histogram of oriented gradient (HOG) and local binary patterns (LBP) are representative features for object recognition, these features have a weakness with respect to rotation, in that it does not consider the rotation of the target object when generating patterns. Therefore, this paper propose the fast rotation-invariant binary patterns (FRIBP) algorithm to generate a binary pattern that is robust against rotation. The proposed FRIBP algorithm deletes an unused layer of the histogram, and eliminates the shift and comparison operations in order to quickly extract the desired feature. The proposed FRIBP algorithm is successfully applied to German Traffic Sign Recognition Benchmark (GTSRB) datasets, and the results show that the recognition capabilities of the proposed method are similar to those of other methods. Moreover, its recognition speed is considerably enhanced than related works as approximately 0.47second for 12,630 test data.