• Title/Summary/Keyword: Technology Identification

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A Simple and Fast Anti-collision Protocol for Large-scale RFID Tags Identification

  • Jia, Xiaolin;Feng, Yuhao;Gu, Yajun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.4
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    • pp.1460-1478
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    • 2020
  • This paper proposes a novel anti-collision protocol for large-scale RFID tags identification, named Bi-response Collision Tree Protocol (BCT). In BCT, two group of tags answer the reader's same query in two response-cycles respectively and independently according to the bi-response pattern. BCT improves the RFID tag identification performance significantly by decreasing the query cycles and the bits transmitted by the reader and tags during the identification. Computation and simulation results indicate that BCT improves the RFID tag identification performance effectively, e.g. the tag identification speed is improved more than 13.0%, 16.9%, and 22.9% compared to that of Collision Tree Protocol (CT), M-ary Collision Tree Protocol (MCT), and Dual Prefix Probe Scheme (DPPS) respectively when tags IDs are distributed uniformly.

Trends in Low Altitude Small Drone Identification Technology and Standardization (저고도 소형드론 식별 기술 및 표준화 동향)

  • Kang, K.M.;Park, J.C.;Choi, S.N.;Oh, J.H.;Hwang, S.H.
    • Electronics and Telecommunications Trends
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    • v.34 no.6
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    • pp.164-174
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    • 2019
  • This article presents low altitude small drone identification trends at home and abroad. To reduce the dysfunction caused by the proliferation of drones worldwide, there is a growing interest in remote identification technologies that can identify the basic information of the drone. First, this article introduces policy trends in major countries. US, Europe, and China have recently provided recommendations regarding technologies available for the remote identification and tracking of a drone. Next, standardization activities on identification communications and identification systems are introduced. For this, standards organizations for the small drone identification, such as the International Organization for Standardization, IEEE 802, Radio Technical Commission for Aeronautics, International Civil Aviation Organization, and $3^{rd}$ Generation Partnership Project, are investigated. Finally, drone identification technology trends are introduced. In the US and Europe, various drone identification technologies have been studied to identify a drone owner and drone registration information with a drone identifier. In South Korea, drone identification technology is still in its infancy, whereas drone detection and physical counterattack technologies are somewhat more developed. As such, major drone manufacturers are also currently studying and developing drone identification systems.

Harmonic Analysis of the Effects of Inverter Nonlinearity on the Offline Inductance Identification of PMSMs Using High Frequency Signal Injection

  • Wang, Gaolin;Wang, Ying;Ding, Li;Yang, Lei;Ni, Ronggang;Xu, Dianguo
    • Journal of Power Electronics
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    • v.15 no.6
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    • pp.1567-1576
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    • 2015
  • Offline inductance identification of a permanent magnet synchronous motor (PMSM) is essential for the design of the closed-loop controller and position observer in sensorless vector controlled drives. On the base of the offline inductance identification method combining direct current (DC) offset and high frequency (HF) voltage injection which is fulfilled at standstill, this paper investigates the inverter nonlinearity effects on the inductance identification while considering harmonics in the induced HF current. The negative effects on d-q axis inductance identifications using HF signal injection are analyzed after self-learning of the inverter nonlinearity characteristics. Then, both the voltage error and the harmonic current can be described. In addition, different cases of voltage error distribution with different injection conditions are classified. The effects of inverter nonlinearities on the offline inductance identification using HF injection are validated on a 2.2 kW interior PMSM drive.

Camera Source Identification of Digital Images Based on Sample Selection

  • Wang, Zhihui;Wang, Hong;Li, Haojie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3268-3283
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    • 2018
  • With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.

Comparative study on modal identification methods using output-only information

  • Yi, Jin-Hak;Yun, Chung-Bang
    • Structural Engineering and Mechanics
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    • v.17 no.3_4
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    • pp.445-466
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    • 2004
  • In this paper, several modal identification techniques for output-only structural systems are extensively investigated. The methods considered are the power spectral method, the frequency domain decomposition method, the Ibrahim time domain method, the eigensystem realization algorithm, and the stochastic subspace identification method. Generally, the power spectral method is most widely used in practical area, however, the other methods may give better estimates particularly for the cases with closed modes and/or with large measurement noise. Example analyses were carried out on typical structural systems under three different loading cases, and the identification performances were examined throught the comparisons between the estimates by various methods.

Design of IFF(Identification of Friend and Foe) Landmine using RFID Technology (RFID 기술을 이용한 피아식별 지뢰 설계)

  • Jang, Jong Hun
    • Journal of the Korea Institute of Military Science and Technology
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    • v.16 no.4
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    • pp.414-421
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    • 2013
  • In this paper, a novel IFF(Identification of Friend and Foe) landmine system has been designed and fabricated using RFID(Radio Frequency Identification) wireless communication system. The IFF landmine system is composed of RECOMS(Remote Controlled Munition System), RFID reader and RFID tag. When the friendly forces have been identified by RFID wireless communication, the IFF landmine is unloaded automatically and indicates the warning message to the operator. Through the discussion, the detailed designs and the test results of identification distance have been described and antenna revision plans for improving the performance have been mentioned.

Target identification for visual tracking

  • Lee, Joon-Woong;Yun, Joo-Seop;Kweon, In-So
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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    • pp.145-148
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    • 1996
  • In moving object tracking based on the visual sensory feedback, a prerequisite is to determine which feature or which object is to be tracked and then the feature or the object identification precedes the tracking. In this paper, we focus on the object identification not image feature identification. The target identification is realized by finding out corresponding line segments to the hypothesized model segments of the target. The key idea is the combination of the Mahalanobis distance with the geometrica relationship between model segments and extracted line segments. We demonstrate the robustness and feasibility of the proposed target identification algorithm by a moving vehicle identification and tracking in the video traffic surveillance system over images of a road scene.

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Video Camera Model Identification System Using Deep Learning (딥 러닝을 이용한 비디오 카메라 모델 판별 시스템)

  • Kim, Dong-Hyun;Lee, Soo-Hyeon;Lee, Hae-Yeoun
    • The Journal of Korean Institute of Information Technology
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    • v.17 no.8
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    • pp.1-9
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    • 2019
  • With the development of imaging information communication technology in modern society, imaging acquisition and mass production technology have developed rapidly. However, crime rates using these technology are increased and forensic studies are conducted to prevent it. Identification techniques for image acquisition devices are studied a lot, but the field is limited to images. In this paper, camera model identification technique for video, not image is proposed. We analyzed video frames using the trained model with images. Through training and analysis by considering the frame characteristics of video, we showed the superiority of the model using the P frame. Then, we presented a video camera model identification system by applying a majority-based decision algorithm. In the experiment using 5 video camera models, we obtained maximum 96.18% accuracy for each frame identification and the proposed video camera model identification system achieved 100% identification rate for each camera model.

IDENTIFICATION OF THERMODYNAMIC PARAMETERS OF ARCTIC SEA ICE AND NUMERICAL SIMULATION

  • Xiw, Chao;Feng, Enmin;Li, Zhijun;Peng, Lu
    • Journal of applied mathematics & informatics
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    • v.26 no.3_4
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    • pp.519-530
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    • 2008
  • This paper studies the multi-domain coupled system of one dimensional Arctic temperature field and establishes identification model about the thermodynamic parameters of sea ice (heat storage capacity, density and conductivity) by the so-called output least-square estimate according to the temperature data acquired by a monitor buoy installed in the Arctic ocean. By the optimal control theory, the existence and dependability of weak solution and the identifiability of identification model have been given. Moreover, necessary optimality condition is proposed. Furthermore, the optimal algorithm for the identification model is constructed. By using the optimal thermodynamic parameters of Arctic sea ice, the numerical simulation is implemented, and the numerical results of temperature distribution of Arctic sea ice are demonstrated.

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Idle Slots Skipped Mechanism based Tag Identification Algorithm with Enhanced Collision Detection

  • Su, Jian;Xu, Ruoyu;Yu, ShiMing;Wang, BaoWei;Wang, Jiuru
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.5
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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.