• Title/Summary/Keyword: VF2 algorithm

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Development of a Semi-automatic Search Program for Crown Delineation Based on Watershed and Valley Following Algorithms

  • Sim, Woodam;Park, Jeongmook;Lee, Jungsoo
    • Journal of Forest and Environmental Science
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    • v.34 no.2
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    • pp.142-144
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    • 2018
  • This paper discusses the development of semi-automatic search program for crown delineation in stand level. The crown of an individual tree was delineated by applying the Watershed (WS) and Valley Following (VF) algorithms. Unmanned Aerial Vehicle (UAV) images were used in the semi-automatic search program to delineate the crown area. The overall accuracy and Khat were used in accuracy assessment. WS algorithm's model showed the overall accuracy and Khat index of 0.80 and 0.59, respectively, in Plot 1. However, the overall accuracy and Khat of VF algorithm's model were 0.78 and 0.51, respectively, in Plot 2.

An SPC-Based Forward-Backward Algorithm for Arrhythmic Beat Detection and Classification

  • Jiang, Bernard C.;Yang, Wen-Hung;Yang, Chi-Yu
    • Industrial Engineering and Management Systems
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    • v.12 no.4
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    • pp.380-388
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    • 2013
  • Large variation in electrocardiogram (ECG) waveforms continues to present challenges in defining R-wave locations in ECG signals. This research presents a procedure to extract the R-wave locations by forward-backward (FB) algorithm and classify the arrhythmic beat conditions by using RR intervals. The FB algorithm shows forward and backward searching rules from QRS onset and eliminates lower-amplitude signals near the baseline using a statistical process control concept. The proposed algorithm was trained the optimal parameters by using MIT-BIH arrhythmia database (MITDB), and it was verified by actual Holter ECG signals from a local hospital. The signals are classified into normal (N) and three arrhythmia beat types including premature ventricular contraction (PVC), ventricular flutter/fibrillation (VF), and second-degree heart block (BII) beat. This work produces 98.54% accuracy in the detection of R-wave location; 98.68% for N beats; 91.17% for PVC beats; and 87.2% for VF beats in the collected Holter ECG signals, and the results are better than what are reported in literature.

Three-Phase 4-Wire Isolated Wind Energy Conversion System Employing VSC with a T-Connected Transformer for Neutral Current Compensation

  • Kasal, Gaurav Kumar;Singh, Bhim
    • Journal of Electrical Engineering and Technology
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    • v.4 no.2
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    • pp.211-218
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    • 2009
  • This paper presents a voltage and frequency controller (VFC) for a 4-wire stand-alone wind energy conversion system (WECS) employing an asynchronous generator. The proposed VF con-troller consists of a three leg IGBT (Insulated Gate Bipolar Junction Transistor) based voltage source converter and a battery at its DC bus. The neutral terminal for the consumer loads is created using a T-connected transformer, which consists of only two single phase transformers. The control algorithm of the VF controller is developed for the bidirectional flow capability of the active power and reactive power control by which it controls the WECS voltage and frequency under different dynamic conditions, such as varying consumer loads and varying wind speeds. The WECS is modeled and simulated in MATLAB using Simulink and PSB toolboxes. Extensive results are presented to demonstrate the capability of the VF controller as a harmonic eliminator, a load balancer, a neutral current compensator as well as a voltage and frequency controller.

An Improved Position Estimation Algorithm of Vehicles Using Semantic Information of Maps (지도의 의미 정보를 이용한 개선된 차량 위치 추정 알고리즘)

  • Lee, Chang Gil;Choi, Yoon Ho;Park, Jin Bae
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.9
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    • pp.753-758
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    • 2016
  • In this paper, we propose a novel method for estimating a vehicle's current position, even on roads that have similar patterns. In the proposed method, we classified the semantic information of the nodes in detail and added the semantic information of the link to solve the problem due to similar and repeated patterns. We also improved the mapping method by comparing the result of the duplicated matching with that of the only matching obtained just before corresponding duplicated matching. From the simulation results, we verify that the performance of the proposed method is better than that of the existing method.

Hybrid Buffer Structured Optical Packet Switch with the Limited Numbers of Tunable Wavelength Converters and Internal Wavelengths (제한된 수의 튜닝 가능한 파장변환기와 내부파장을 갖는 하이브리드 버퍼 구조의 광 패킷 스위치)

  • Lim, Huhn-Kuk
    • Journal of Internet Computing and Services
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    • v.10 no.2
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    • pp.171-177
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    • 2009
  • Optical packet switching(OPS) is a strong candidate for the next-generation internet, since it has a fine switching granularity at the packet level for providing flexible bandwidth, and provides seamless integration between WDM layer and IP layer. Optical packet switching have been studied in two categories: OPS in synchronous and OPS in asynchronous networks. In this article we are focused on contention resolution of OPS in asynchronous networks. The hybrid buffer have been addressed, to reduce packet loss further as one of the alternative buffer structures for contention resolution of asynchronous and variable length packets, which consists of the FDL buffer and the electronic buffer. The OPS design issue for the limited number of TWCs and internal wavelengths is important in the aspect of switch cost and resource efficiency. Therefore, an hybrid buffer structured optical packet switch and its scheduling algorithm is presented for considering the limited number of TWCs and internal wavelengths, for contention resolution of asynchronous and variable length packets. The proposed algorithm could lead to the packet loss improvement compared to the legacy LAUC-VF algorithm with only the FDL buffer.

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EMD based Cardiac Arrhythmia Classification using Multi-class SVM (다중 클래스 SVM을 이용한 EMD 기반의 부정맥 신호 분류)

  • Lee, Geum-Boon;Cho, Beom-Joon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.1
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    • pp.16-22
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    • 2010
  • Electrocardiogram(ECG) analysis and arrhythmia recognition are critical for diagnosis and treatment of ill patients. Cardiac arrhythmia is a condition in which heart beat may be irregular and presents a serious threat to the patient recovering from ventricular tachycardia (VT) and ventricular fibrillation (VF). Other arrhythmias like atrial premature contraction (APC), Premature ventricular contraction (PVC) and superventricular tachycardia (SVT) are important in diagnosing the heart diseases. This paper presented new method to classify various arrhythmias contrary to other techniques which are limited to only two or three arrhythmias. ECG is decomposed into Intrinsic Mode Functions (IMFs) by Empirical Mode Decomposition (EMD). Burg algorithm was performed on IMFs to obtain AR coefficients which can reduce the dimension of feature vector and utilized as Multi-class SVM inputs which is basically extended from binary SVM. We chose optimal parameters for SVM classifier, applied to arrhythmias classification and achieved the accuracies of detecting NSR, APC, PVC, SVT, VT and VP were 96.8% to 99.5%. The results showed that EMD was useful for the preprocessing and feature extraction and multi-class SVM for classification of cardiac arrhythmias, with high usefulness.