• 대한임베디드공학회논문지
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• 제12권6호
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• pp.395-403
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• 2017

Image processing for object detection and identification has been studied for supply chain management application with various approaches. Among them, feature pointed detection algorithm is used to track an object or to recognize a position in automated supply chain systems and a depth image based feature point detection is recently highlighted in the application. The result of feature point detection is easily influenced by image noise. Also, the depth image has noise itself and it also affects to the accuracy of the detection results. In order to solve these problems, we propose a novel hybrid filtering mechanism for depth image based feature point detection, it shows better performance compared with conventional hybrid filtering mechanism.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.2294-2309
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• 2020

In this article, a new Aloha-based tag identification protocol is presented to improve the reading efficiency of the EPC C1 Gen2-based UHF RFID system. Collision detection (CD) plays a vital role in tag identification process which determines the efficiency of anti-collision protocols since most Aloha-based protocols optimize the incoming frame length based on the collisions in current frame. Existing CD methods are ineffective in identifying collision, resulting in a degradation of identification performance. Our proposed algorithm adopts an enhanced CD (ECD) scheme based on the EPC C1 Gen2 standard to optimize identification performance. The ECD method can realize timely and effective CD by detecting the pulse width of the randomly sent by tags. According to the ECD, the reader detects the slot distribution and predicts tag cardinality in every collision slot. The tags involved in each collision slot are identified by independently assigned sub-frames. A large number of numerical results show that the proposed solution is superior to other existing anti-collision protocols in various performance evaluation metrics.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권4호
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• pp.238-245
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• 2016

Inverters are considered the basic building blocks of industrial electrical drive systems that are widely used for various applications; however, the failure of electronic switches mainly affects the constancy of these inverters. For safe and reliable operation of an electrical drive system, faults in power electronic switches must be detected by an efficient system that is capable of identifying the type of faults. In this paper, an open switch fault identification technique for a three-phase inverter is presented. Single, double, and triple switching faults can be diagnosed using this method. The detection mechanism is based on stator current analysis. Discrete wavelet transform (DWT) using Daubechies is performed on the Clarke transformed (-) stator current and features are extracted from the wavelets. An artificial neural network is then used for the detection and identification of faults. To prove the feasibility of this method, a Simulink model of the DWT-based feature extraction scheme using a neural network for the proposed fault detection system in a three-phase inverter with an induction motor is briefly discussed with simulation results. The simulation results show that the designed system can detect faults quite efficiently, with the ability to differentiate between single and multiple switching faults.

• Structural Engineering and Mechanics
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• 제55권6호
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• pp.1223-1239
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• 2015

A method for structural damage identification based on Chaotic Artificial Bee Colony (CABC) algorithm is presented. ABC is a heuristic algorithm with simple structure, ease of implementation, good robustness but with slow convergence rate. To overcome the shortcoming, the tournament selection mechanism is chosen instead of the roulette mechanism and chaotic search mechanism is also introduced. Residuals of natural frequencies and modal assurance criteria (MAC) are used to establish the objective function, ABC and CABC are utilized to solve the optimization problem. Two numerical examples are studied to investigate the efficiency and correctness of the proposed method. The simulation results show that the CABC algorithm can identify the local damage better compared with ABC and other evolutionary algorithms, even with noise corruption.

• 한국멀티미디어학회논문지
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• 제16권6호
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• pp.735-745
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• 2013

The emergence of Web 2.0 technologies, such as blogs and wiki, enable even naive users to easily create and share content on the Web using freely available content sharing tools. Wide availability of almost free data and promiscuous sharing of content through social networking platforms created a content borrowing phenomenon, where the same content appears (in many cases in the form of extensive quotations) in different outlets. An immediate side effect of this phenomenon is that identifying which content is re-used by whom is becoming a critical tool in social network analysis, including expert identification and analysis of information flow. Internet-scale reuse detection, however, poses extremely challenging scalability issues: considering the large size of user created data on the web, it is essential that the techniques developed for content-reuse detection should be fast and scalable. Thus, in this paper, we propose a $qSign_{lsh}$ algorithm, a mechanism for identifying multi-sentence content reuse among documents by efficiently combining sentence-level evidences. The experiment results show that $qSign_{lsh}$ significantly improves the reuse detection speed and provides high recall.

• Journal of Communications and Networks
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• 제14권1호
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• pp.34-39
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• 2012

Collisions between tags greatly reduce the identification speed in radio frequency identification (RFID) systems and increase communication overhead. In particular for an active RFID system, tags are powered by small batteries, and a large number of re-transmissions caused by collisions can deteriorate and exhaust the tag energy which may result in missing tags. An efficient collision-free arbitration protocol for active RFID systems is proposed in this paper. In this protocol, a new mechanism involving collision detection, collision avoidance, and fast tag access is introduced. Specifically, the pulse burst duration and busy-tone-detection delay are introduced between the preamble and data portion of a tag-to-reader (T-R) frame. The reader identifies tag collision by detecting pulses and transmits a busy tone to avoid unnecessary transmission when collision occurs. A polling process is then designed to quickly access the collided tags. It is shown that the use of the proposed protocol results in a system throughput of 0.612, which is an obvious improvement when compared to the framed-slotted ALOHA (FSA) arbitration protocol for ISO/IEC 18000-7 standard. Furthermore, the proposed protocol greatly reduces communication overhead, which leads to energy conservation.

• 사물인터넷융복합논문지
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• 제9권1호
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• pp.1-7
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• 2023

랜섬웨어에 의해 개인용 단말 또는 서버 등이 감염되는 사례가 급증하고 있다. 랜섬웨어는 자체 개발한 암호화 모듈을 이용하거나 기존의 대칭키/공개 키 암호화 모듈을 결합하여 공격자만이 알고 있는 키를 이용하여 피해 시스템 내에 저장된 파일을 불법적으로 암호화 하게 된다. 따라서 이를 복호화 하기 위해서는 사용된 키 값을 알아야만 하며, 복호화 키를 찾는 과정에 많은 시간이 걸리므로 결국 금전적인 비용을 지불하게 된다. 이때 랜섬웨어 악성코드는 대부분 바이너리 파일 내에 은닉된 형태로 포함되어 있어 프로그램 실행시 사용자도 모르게 악성코드에 감염된다. 그러므로 바이너리 파일 형태의 랜섬웨어 공격에 대응하기 위해서는 사용된 암호화 모듈에 대한 식별 과정이 필요하다. 이에 본 연구에서는 바이너리 파일 내 은닉된 악성코드에 적용 된 암호화 모듈을 역분석하여 탐지하고 식별할 수 있는 메커니즘을 연구하였다.

• Smart Structures and Systems
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• 제17권2호
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• pp.167-194
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• 2016

This paper investigates the Synergetics based Damage Detection Method (SDDM) for frame structures by using surface-bonded PZT (Lead Zirconate Titanate) patches. After analyzing the mechanism of pattern recognition from Synergetics, the operating framework with cooperation-competition-update process of SDDM was proposed. First, the dynamic identification equation of structural conditions was established and the adjoint vector (AV) set of original vector (OV) set was obtained by Generalized Inverse Matrix (GIM).Then, the order parameter equation and its evolution process were deduced through the strict mathematics ratiocination. Moreover, in order to complete online structural condition update feature, the iterative update algorithm was presented. Subsequently, the pathway in which SDDM was realized through the modified Synergetic Neural Network (SNN) was introduced and its assessment indices were confirmed. Finally, the experimental platform with a two-story frame structure was set up. The performances of the proposed methodology were tested for damage identifications by loosening various screw nuts group scenarios. The experiments were conducted in different damage degrees, the disturbance environment and the noisy environment, respectively. The results show the feasibility of SDDM using piezoceramic sensors and actuators, and demonstrate a strong ability of anti-disturbance and anti-noise in frame structure applications. This proposed approach can be extended to the similar structures for damage identification.

• Archives of Pharmacal Research
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• 제7권1호
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• pp.65-68
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• 1984

Mechanism of the monoamine oxidase inhibition by tranylcypromine was studied in relation to its metabolism to reactive apecies. A metabolic study performed to collect general biotransformation pathway in rats provided GC/MS evidence for the detection of two new metabolites, N-acetyl and hydroxylated N-acetyltranylacypromine.

• 한국지리정보학회지
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• 제15권2호
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• pp.103-112
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• 2012

SAR(Synthetic Aperture Radar) 영상과 AIS(Automatic Identification System) 자료를 활용하여 선박 탐지 실험을 수행하였다. 2010년 5월, 2주간 서해안(인천 근해)의 다중시기 해외위성 SAR 영상인 TerraSAR-X, Cosmo-SkyMed(X-밴드), Radarsat-2(C-밴드)와 AIS 자료를 이용하였다. SAR 영상 분석을 위해 해양과 선박의 산란 특성과 SAR 영상과 AIS 자료의 기초 처리 방법을 기술하였다. 선박 식별을 위해서 임계값 설정 기법을 사용하였다. 선박 탐지 결과로 시계열 변화 탐지와 AIS 연동 선박 탐지 사례를 보인다. 이 결과를 통해 위성 SAR 영상과 AIS를 이용한 선박 탐지는 해양 관리에 유용하게 사용될 수 있을 것으로 사료된다.