Analyzing Contacts and Behavior from High Frequency Tracking Data Using the wildlifeDI R Package

2021 ◽  
Author(s):  
Jed A. Long ◽  
Stephen L. Webb ◽  
Seth M. Harju ◽  
Kenneth L. Gee
2019 ◽  
Vol 11 (2) ◽  
pp. 91
Author(s):  
Asep Prastiawan

Malaria is becoming the most widely distributed disease in the world. There were 212 million cases of malaria and 429,000 of them died in the year 2015. Enviromental, behavior, knowledge and health care factors play an important role in the incidence of malaria in endemic areas. The purpose of this study was analyze the influence of mobility and behavioral factors on malaria import incidence in the Kecamatan Watulimo, Kabupaten Trenggalek. This research was an observational, used case control study design. The research samples were 42 people. Data were statistics analyzed using logistic regression test. The results of this research were influence between high frequency of mobility (p=0.023; OR=16.670), duration of stay in endemic areas for a bit (p=0.014; OR=35.940), less knowledge (p=0.022; OR=11.946), and less practice (p=0.010; OR=25.534) against malaria import incidence in the Kecamatan Watulimo, Kabupaten Trenggalek. But there was not influence attitude (p=0.470) against malaria import incidence in the Kecamatan Watulimo, Kabupaten Trenggalek. The high frequency of mobility factor ≥ 3 times and duration of stay in endemic areas for a bit 1-2 months, behavior factor less knowledge and practice can lead to increased risk of malaria import incidence in the Kecamatan Watulimo, Kabupaten Trenggalek. We recommended to increased the community knowledge and practice on malaria and its prevention with counseling. Increased JMD empowerment, revitalization of Posmaldes, provision of chemoprophylaxis malaria and insecticide mosquito net at the village level.


Author(s):  
Justin M. Calabrese ◽  
Christen H. Fleming ◽  
Michael J. Noonan ◽  
Xianghui Dong

ABSTRACTEstimating animal home ranges is a primary purpose of collecting tracking data. All conventional home range estimators in widespread usage, including minimum convex polygons and kernel density estimators, assume independently sampled data. In stark contrast, modern GPS animal tracking datasets are almost always strongly autocorrelated. This incongruence between estimator assumptions and empirical reality leads to systematically underestimated home ranges. Autocorrelated kernel density estimation (AKDE) resolves this conflict by modeling the observed autocorrelation structure of tracking data during home range estimation, and has been shown to perform accurately across a broad range of tracking datasets. However, compared to conventional estimators, AKDE requires additional modeling steps and has heretofore only been accessible via the command-line ctmm R package. Here, we introduce ctmmweb, which provides a point-and-click graphical interface to ctmm, and streamlines AKDE, its prerequisite autocorrelation modeling steps, and a number of additional movement analyses. We demonstrate ctmmweb’s capabilities, including AKDE home range estimation and subsequent home range overlap analysis, on a dataset of four jaguars from the Brazilian Pantanal. We intend ctmmweb to open AKDE and related autocorrelation-explicit analyses to a wider audience of wildlife and conservation professionals.


2011 ◽  
Vol 328-330 ◽  
pp. 1747-1750
Author(s):  
Cui Yun Gao ◽  
Wen Jing Li ◽  
Ming Liu ◽  
Ru Han

The paper propose the digital frequency multiplying method based on frequency de-noising on FPGA, aiming at the frequency aliasing of the high frequency interference in the power system frequency tracking circuit. The basic principle and hardware realization are discussed.The performance of the system is tested using two different system clock, the experiments show that: This method can eliminate the error caused by frequency aliasing, and improve the interference immunity of the system. In addition, experiments also proved that using higher system clock can improve accuracy absolutely.


2017 ◽  
Vol 17 (1) ◽  
pp. 48-52 ◽  
Author(s):  
Ting-ao Shen ◽  
Hua-nan Li ◽  
Qi-xin Zhang ◽  
Ming Li

Abstract The convergence rate and the continuous tracking precision are two main problems of the existing adaptive notch filter (ANF) for frequency tracking. To solve the problems, the frequency is detected by interpolation FFT at first, which aims to overcome the convergence rate of the ANF. Then, referring to the idea of negative feedback, an evaluation factor is designed to monitor the ANF parameters and realize continuously high frequency tracking accuracy. According to the principle, a novel adaptive frequency estimation algorithm based on interpolation FFT and improved ANF is put forward. Its basic idea, specific measures and implementation steps are described in detail. The proposed algorithm obtains a fast estimation of the signal frequency, higher accuracy and better universality qualities. Simulation results verified the superiority and validity of the proposed algorithm when compared with original algorithms.


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