• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.6
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• pp.570-576
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• 2006

This paper describes a method for the detection of shorted-turn in the cylindrical synchronous generator rotor windings based on the discrete wavelet transform. Multi-resolution analysis(MRA) based on discrete wavelet transform provides a set of decomposed signals in independent frequency bands, which contain independent dynamic information due to the orthogonality of wavelet function. In the proposed method, shorted-turn detection in rotor windings is based on the decomposition of the rotor currents, where wavelet coefficients of these signals have been extracted. Comparing these extracted coefficients is used for diagnosing the healthy machine from faulty machine. Experimental results are presented for healthy, and machines with 25%, 42%, 67%, 83%, 99% inter-turn short circuits in a rotor slot. Deviation of wavelet coefficients in healthy mode from faulty modes depicts the inverse proportion of shorted-turns. Experimental results show the effectiveness of the proposed method for shorted-turn detection in the cylindrical synchronous generator rotor windings.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.217-228
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• 2024

LiDAR(Light Detection And Ranging) sensors, which play a pivotal role among cameras, RADAR(RAdio Detection And Ranging), and ultrasonic sensors for the safe operation of autonomous vehicles, can recognize and detect objects in 360 degrees. However, since LiDAR sensors use lasers to measure distance, they are vulnerable to attackers and face various security threats. In this paper, we examine several security threats against LiDAR sensors: relay, spoofing, and replay attacks, analyze the possibility and impact of physical jamming attacks, and analyze the risk these attacks pose to the reliability of autonomous driving systems. Through experiments, we show that jamming attacks can cause errors in the ranging ability of LiDAR sensors. With vehicle-to-vehicle (V2V) communication, multi-sensor fusion under development and LiDAR anomaly data detection, this work aims to provide a basic direction for countermeasures against these threats enhancing the security of autonomous vehicles, and verify the practical applicability and effectiveness of the proposed countermeasures in future research.

• Korean Institute of Interior Design Journal
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• v.16 no.1 s.60
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• pp.126-134
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• 2007

This study researches the effectiveness of virtual experiences as an evaluation method in design. For the study, I researched the result on the spatial recognition before, abstracted visual objects and factors in recognition process and made up 43 inquiries for the evaluation through the experts group. Besides, set the analytical code between recognition factor and spatial constituents, made analysis the result from it. From April 1st to June 30th in 2004, the virtual model of educational place, college main building and city library was established as a subject of the research and studied the result. The methods that are used for the study are frequent analysis, T-test, reliability analysis, factor analysis etc. and SPSSWIN Package is used for the statistic analysis. There were two times of analysis on the evaluation to analyze the effect of virtual models on the web basis, one group evaluated the virtual building same as real and the other group evaluated the building site. Then analyzed the differences and correlation between the two. In result, college building, the first subject of study, and the second city library shows that made little differences between on the spot evaluation and virtual evaluation. Therefore, it is considered that the design evaluation with virtual model on the web basis has a vantage. But some problems founded that solved between preceding and present research through the feedback. It is as follows, 1. detection of problems that insufficience validity in the first survey. 2. found some not-validity inquiries. 3. detection of necessities that qualitative improvement and technical repletion in virtual environment.

• Genomics & Informatics
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• v.5 no.3
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• pp.118-123
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• 2007

The current existing literature offers little guidance on how to decide which method to use to analyze one-channel microarray measurements when dealing with large, grouped samples. Most previous methods have focused on two-channel data;therefore they can not be easily applied to one-channel microarray data. Thus, a more reliable method is required to determine an appropriate combination of individual basic processing steps for a given dataset in order to improve the validity of one-channel expression data analysis. We address key issues in evaluating the effectiveness of basic statistical processing steps of microarray data that can affect the final outcome of gene expression analysis without focusingon the intrinsic data underlying biological interpretation.

• Smart Structures and Systems
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• v.8 no.2
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• pp.157-172
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• 2011

A new method for both local damage(s) identification and input excitation force identification of beam structures is presented using the dynamic response sensitivity-based finite element model updating method. The state-space approach is used to calculate both the structural dynamic responses and the responses sensitivities with respect to structural physical parameters such as elemental flexural rigidity and with respect to the force parameters as well. The sensitivities of displacement and acceleration responses with respect to structural physical parameters are calculated in time domain and compared to those by using Newmark method in the forward analysis. In the inverse analysis, both the input excitation force and the local damage are identified from only several acceleration measurements. Local damages and the input excitation force are identified in a gradient-based model updating method based on dynamic response sensitivity. Both computation simulations and the laboratory work illustrate the effectiveness and robustness of the proposed method.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.30 no.3
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• pp.1-19
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• 2017

Objectives : This study aimed to validate the effect of herbal medicine intervention to relieve the symptoms of psoriasis using systematic review and meta-analysis and provide the newest reason of effectiveness of Korean medicine to psoriasis. Methods : Data were collected through electronic database including Pubmed, Cochrane CENTRAL, NDSL OASIS, Koreantk. Two experts assessed risk of bias of randomized controlled trials by Cochrane group's Risk of Bias tool after searching, reviewing and selecting papers. Data were analyzed using Review Manager(RevMan) 5.3 and Comprehensive Meta Analysis 2.0. Results : Total number of selected trials was 16 randomized controlled trials. This study evaluated the risk of bias and effectiveness of herbal medicine to psoriasis. There were high frequency uncertain in selection bias, performance bias and detection bias. In this meta-analysis, Korean medicine treatment was more effective than western medicine (ES:0.507, 95%CI:0.147-0.867) and placebo (ES:0.955, 95%CI:0.598-1.312). Conclusions : Herbal medicine intervention can be an effective for treatment in psoriasis. But enhancing levels of evidence, we must try to accumulate clinical researches of herbal medicine to psoriasis in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.47-56
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• 2018

National-scale industrial control systems for gas, electric power, water processing, nuclear power, and traffic control systems increasingly use open networks and open standards protocols based on advanced information and communications technologies. The frequency of cyberattacks increases steadily because of the use of open networks and open standards protocols, but follow-up actions are limited. Therefore, the application of security solutions to an industrial control system is very important. However, it is not possible to apply security solutions to a real system because of the characteristics of industrial control systems. And a security system that can detect attacks without affecting the existing system is imperative. Therefore, in this paper, we propose an intrusion detection system based on packet analysis that can detect anomalous behaviors without affecting the industrial control system, and we verify the effectiveness of the proposed intrusion detection system by applying it in a test bed simulating a real environment.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.193-199
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• 2008

In this paper, it is proposed the implementation of face authentication system based on real-time image processing. We described the process implementing the two steps for real-time face authentication system. At first face detection steps, we describe the face detection by using feature of wavelet transform, LoG operator and hausdorff distance matching. In the second step we describe the new dual-line principal component analysis(PCA) for real-time face recognition. It is combines horizontal line to vertical line so as to accept local changes of PCA. The proposed system is affected a little by the video size and resolution. And then simulation results confirm the effectiveness of out system and demonstrate its superiority to other conventional algorithm. Finally, the possibility of performance evaluation and real-time processing was confirmed through the implementation of face authentication system.

• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.23-29
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• 2019

In this paper, a deep learning-based detection and classification using multi-band frequency signals is presented for detecting earthquakes prevalent in Korea. Based on an analysis of the previous earthquakes in Korea, it is observed that multi-band signals are appropriate for classifying earthquake signals. Therefore, in this paper, we propose a deep CNN (Convolutional Neural Network) using multi-band signals as training data. The proposed algorithm extracts the multi-band signals (Low/Medium/High frequency) by applying band pass filters to mel-spectrum of earthquake signals. Then, we construct three CNN architecture pipelines for extracting features and classifying the earthquake signals by a late fusion of the three CNNs. We validate effectiveness of the proposed method by performing various experiments for classifying the domestic earthquake signals detected in 2018.

• Journal of the Korea Society for Simulation
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• v.28 no.1
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• pp.23-39
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• 2019

The use of drone-bots is demanded in times regarding the reduction of military force, the spread of the life-oriented thought, and the use of innovative technology in the defense through the fourth industrial revolution. Especially, the drone's surveillance and reconnaissance are expected to play a big role in the future battlefield. However, there are not many cases in which the concept of operation is studied scientifically. In this study, We propose search algorithms for reconnaissance drone through simulation analysis. In the simulation, the drone and target move linearly in continuous space, and the target is moving adopting the Random-walk concept to reflect the uncertainty of the battlefield. The research investigates the effectiveness of existing search methods such as Parallel and Spiral Search. We analyze the probabilistic analysis for detector radius and the speed on the detection probability. In particular, the new detection algorithms those can be used when an enemy moves toward a specific goal, PS (Probability Search) and HS (Hamiltonian Search), are introduced. The results of this study will have applicability on planning the path for the reconnaissance operations using drone-bots.