Quantifying detection performance of a passive low-frequency RFID system in an environmental preference chamber for laying hens

2015 ◽  
Vol 114 ◽  
pp. 261-268 ◽  
Author(s):  
G.T. Sales ◽  
A.R. Green ◽  
R.S. Gates ◽  
T.M. Brown-Brandl ◽  
R.A. Eigenberg
Keyword(s):  
Laying Hens ◽  
Low Frequency ◽  
Detection Performance ◽  
Environmental Preference ◽  
Rfid System

Laying hens do not have a preference for high-frequency versus low-frequency compact fluorescent light sources

1996 ◽  
Vol 76 (2) ◽  
pp. 177-181 ◽  
Author(s):  
T. M. Widowski ◽  
I.J.H. Duncan
Keyword(s):  
High Frequency ◽  
Laying Hens ◽  
Low Frequency ◽  
Fluorescent Light ◽  
Feed Water ◽  
Light Sources ◽  
Frequency Distributions ◽  
Video Cameras ◽  
Fluorescent Lamps ◽  
Testing Chamber

To determine whether hens find the flicker of some fluorescent light aversive, the preferences of 16 light hybrid laying hens for light produced by high-frequency or low-frequency compact fluorescent lamps were tested individually in a two-room testing chamber in which each room could be illuminated by either source. The spectral distributions of the lamps and levels of illumination (ca. 14 lx) in the two rooms were carefully matched and both rooms contained feed, water, and a nesting area. Overhead video cameras recorded the position and behaviour of the birds during a 6-h test period on each of 2 d. The light sources in the rooms were switched on the second test day to balance for any preferences for chamber room.On both test days, the birds spent similar amounts of time in fluorescent light produced by high-frequency and low-frequency lamps (P > 0.10). When data from both test days were combined, the birds spent on average 48.2% of time in light from high-frequency lamps and 51.8% from low-frequency. The frequency distributions of individual activities indicated that the birds performed all activities in light produced by both types of lamps. The results indicate that the laying hens in this experiment did not exhibit a preference for high-frequency fluorescent lamps over low-frequency lamps. We conclude that at the illumination levels used in this experiment, the hens did not perceive the flicker of low-frequency light or they perceived it but did not find it aversive. Low-frequency fluorescent light does not appear to adversely affect the welfare of hens. Key words: Lighting, fluorescent, flicker, behaviour, poultry

Low Frequency RFID system for identification and localization in smart cities - Comparison with UHF RFID

2018 ◽  
Vol 8 (4) ◽  
pp. 191-211 ◽  
Author(s):  
Vighnesh Gharat ◽  
Geneviève Baudoin ◽  
Elizabeth Colin ◽  
Damien Richard
Keyword(s):  
Smart Cities ◽  
Low Frequency ◽  
Uhf Rfid ◽  
Rfid System

scholarly journals Read Range Optimization of Low Frequency RFID System in Hostile Environmental Conditions by Using RSM Approach

Evergreen ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 396-403
Author(s):  
Shilpa Choudhary ◽  
Abhishek Sharma ◽  
Kashish Srivastava ◽  
Hemant Purohit ◽  
Mudita Vats
Keyword(s):  
Environmental Conditions ◽  
Low Frequency ◽  
Rfid System ◽  
Read Range

scholarly journals Experimental Investigation and Statistical Analysis of Low Frequency RFID System

2021 ◽  
Author(s):  
Shilpa Choudhary ◽  
◽  
Abhishek Sharma ◽  
Arpana Mishra ◽  
◽  
...  
Keyword(s):  
Experimental Investigation ◽  
Statistical Analysis ◽  
Layer Thickness ◽  
Sandy Soil ◽  
Soil Layer ◽  
Low Frequency ◽  
Atmospheric Conditions ◽  
Asset Tracking ◽  
Rfid System ◽  
Read Range

In today’s era RFID system plays a key role in the field of asset tracking but its maximum read range or detectability may get degraded due to the challenges which are being provided by varying atmospheric conditions. So, to study the effect of these challenging atmospheric conditions, experimental investigation and statistical analysis of RFID system detectability has been carried out. Varying surrounding temperature, humidity and the presence of soil layer thickness in between RFID reader and tag and its five different grain sizes were considered as input parameters. All these observations were carried out for three different soils i.e. sandy soil, Silt and clay. Execution of test was carried out according to the MINITAB 17 tool. According to ANOVA analysis as well as from interaction plot it was found that soil layer thickness have more impact on RFID system read range and R2 value was found to be 96.91%, 99.64% and 99.78% for RRSS, RRS and RRC respectively. Composite desirability of optimization was found to be 0.8425. Optimum values of process parameters Temperature, Soil Layer Thickness, Relative Humidity and Soil Grain Size were found to be 303.3°K, 2.5 cm, 40.1 %, 1.92 mm respectively. Best values of responses were found to be 10.94 cm for (Read Range in presence of Clay); 11.02 cm (Read Range in presence of Silt) and 10.97 cm (Read Range in presence of Sandy Soil).

Behavioral responses of laying hens to atmospheric ammonia in an environmental preference chamber

2018 ◽  
Author(s):  
Christina M Tucker ◽  
Angela R Green-Miller ◽  
Richard S Gates ◽  
San Myint ◽  
Janeen Salak-Johnson
Keyword(s):  
Laying Hens ◽  
Behavioral Responses ◽  
Atmospheric Ammonia ◽  
Environmental Preference

scholarly journals Quantifying the Snowfall Detection Performance of the GPM Microwave Imager Channels over Land

2017 ◽  
Vol 18 (3) ◽  
pp. 729-751 ◽  
Author(s):  
Yalei You ◽  
Nai-Yu Wang ◽  
Ralph Ferraro ◽  
Scott Rudlosky
Keyword(s):  
Water Vapor ◽  
High Frequency ◽  
Model Simulation ◽  
Low Frequency ◽  
Detection Performance ◽  
Probability Of Detection ◽  
Frequency Channel ◽  
Microwave Imager ◽  
Type 3 ◽  
Global Precipitation

Abstract This study uses Global Precipitation Measurement (GPM) Microwave Imager (GMI) and Ka-precipitation radar observations to quantify the snowfall detection performance for different channel (frequency) combinations. Results showed that the low-frequency-channel set contains limited snow detection information with a 0.34 probability of detection (POD). Much better performance is evident using the high-frequency channels (i.e., POD = 0.74). In addition, if only one high-frequency channel is allowed to be added to the low-frequency-channel set, adding the 183 ± 3 GHz channel presents the largest POD improvement (from 0.34 to 0.50). However, this does not imply that the water vapor is the key information for snowfall detection. Only using the high-frequency water vapor channels showed poor snowfall detection with POD at 0.13. Further analysis of all 8191 possible GMI channel combinations showed that the 166-GHz channels are indispensable for any channel combination with POD greater than 0.70. This suggests that the scattering signature, not the water vapor effect, is essential for snowfall detection. Data analysis and model simulation support this explanation. Finally, the GPM constellation radiometers are grouped into six categories based on the channel availability and their snowfall detection capability is estimated, using channels available on GMI. It is found that type-4 radiometer (all channels) has the best snowfall detection performance with a POD of 0.77. The POD values are only slightly smaller for the type-3 radiometer (high-frequency channels) and type-5 radiometer (all channels except 183 channels).

scholarly journals Prestimulus frontal-parietal coherence predicts auditory detection performance in rats

2014 ◽  
Vol 111 (10) ◽  
pp. 1986-2000 ◽  
Author(s):  
Linnea Herzog ◽  
Kia Salehi ◽  
Kaitlin S. Bohon ◽  
Michael C. Wiest
Keyword(s):  
Long Range ◽  
Parietal Cortex ◽  
Low Frequency ◽  
Detection Performance ◽  
Beta Band ◽  
Low Frequencies ◽  
Auditory Detection ◽  
Local Synchronization ◽  
Motivational Changes ◽  
External Stimuli

Electrophysiology in primates has implicated long-range neural coherence as a potential mechanism for enhancing sensory detection. To test whether local synchronization and long-range neural coherence support detection performance in rats, we recorded local field potentials (LFPs) in frontal and parietal cortex while rats performed an auditory detection task. We observed significantly elevated power at multiple low frequencies (<15 Hz) preceding the target beep when the animal failed to respond to the signal (misses), in both frontal and parietal cortex. In terms of long-range coherence, we observed significantly more frontal-parietal coherence in the beta band (15–30 Hz) before the signal on misses compared with hits. This effect persisted after regressing away linear trends in the coherence values during a session, showing that the excess frontal-parietal beta coherence prior to misses cannot be explained by slow motivational changes during a session. In addition, a trend toward higher low-frequency (<15 Hz) coherence prior to miss trials compared with hits became highly significant when we rereferenced the LFPs to the mean voltage on each recording array, suggesting that the results are specific to our frontal and parietal areas. These results do not support a role for long-range frontal-parietal coherence or local synchronization in facilitating the detection of external stimuli. Rather, they extend to long-range frontal-parietal coherence previous findings that correlate local synchronization of low-frequency (<15 Hz) oscillations with inattention to external stimuli and synchronization of beta rhythms (15–30 Hz) with voluntary or involuntary prolongation of the current cognitive or motor state.

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