The Experts below are selected from a list of 15 Experts worldwide ranked by ideXlab platform

Tah-hsiung Chu - One of the best experts on this subject based on the ideXlab platform.

  • port reduction methods for scattering matrix measurement of an n port network
    IEEE Transactions on Microwave Theory and Techniques, 2000
    Co-Authors: Tah-hsiung Chu
    Abstract:

    The port reduction method (PRM) is a method to acquire the scattering matrix of an n-port network from the scattering matrix measured at a reduced port order by terminating certain ports. This then relaxes the Instrumentation Requirement and calibration procedure. As the port order is reduced to two, the scattering matrix of an n-port network can be obtained from the measurement using a conventional two-port vector network analyzer. In this paper, we describe two novel PRMs, which can reduce the order of measured ports to two. The experimental results show good accuracy. These two PRMs can provide a simpler calibration procedure and Instrumentation than those directly using an n-port network analyzer. In addition, they give more accurate results than those measured by a two-port network analyzer with the assumption of using ideal terminators.

Thomas J Trout - One of the best experts on this subject based on the ideXlab platform.

  • Minimizing Instrumentation Requirement for estimating crop water stress index and transpiration of maize
    Irrigation Science, 2013
    Co-Authors: Saleh Taghvaeian, Kendall C. Dejonge, Walter C Bausch, José L. Chávez, Thomas J Trout
    Abstract:

    Research was conducted in northern Colorado in 2011 to estimate the crop water stress index (CWSI) and actual transpiration (Ta) of maize under a range of irriga- tion regimes. The main goal was to obtain these parameters with minimum Instrumentation and measurements. The results confirmed that empirical baselines required for CWSI calculation are transferable within regions with similar climatic conditions, eliminating the need to develop them for each irrigation scheme. This means that maize CWSI can be determined using only two instruments: an infrared thermometer and an air temperature/relative humidity sensor. Reference evapotranspiration data obtained from a modified atmometer were similar to those estimated at a standard weather station, suggesting that maize Ta can be calculated based on CWSI and by adding one additional instrument: a modified atmometer. Esti- mated CWSI during four hourly periods centered on solar noon was largest during the 2 h after solar noon. Hence, this time window is recommended for once-a-day data acquisition if the goal is to capture maximum stress level. Maize Ta based on CWSI during the first hourly period (10:00-11:00) was closest to Ta estimates from a widely used crop coefficient model. Thus, this time window is recommended if the goal is to monitor maize water use. Average CWSI over the 2 h after solar noon and during the study period (early August to late September, 2011) was 0.19, 0.57, and 0.20 for plots under full, low-frequency deficit, and high-frequency deficit irrigation regimes, respectively. During the same period (50 days), total maize Ta based on the 10:00-11:00 CWSI was 218, 141, and 208 mm for the same treatments, respectively. These val- ues were within 3 % of the results of the crop coefficient approach.

Saleh Taghvaeian - One of the best experts on this subject based on the ideXlab platform.

  • Minimizing Instrumentation Requirement for estimating crop water stress index and transpiration of maize
    Irrigation Science, 2013
    Co-Authors: Saleh Taghvaeian, Kendall C. Dejonge, Walter C Bausch, José L. Chávez, Thomas J Trout
    Abstract:

    Research was conducted in northern Colorado in 2011 to estimate the crop water stress index (CWSI) and actual transpiration (Ta) of maize under a range of irriga- tion regimes. The main goal was to obtain these parameters with minimum Instrumentation and measurements. The results confirmed that empirical baselines required for CWSI calculation are transferable within regions with similar climatic conditions, eliminating the need to develop them for each irrigation scheme. This means that maize CWSI can be determined using only two instruments: an infrared thermometer and an air temperature/relative humidity sensor. Reference evapotranspiration data obtained from a modified atmometer were similar to those estimated at a standard weather station, suggesting that maize Ta can be calculated based on CWSI and by adding one additional instrument: a modified atmometer. Esti- mated CWSI during four hourly periods centered on solar noon was largest during the 2 h after solar noon. Hence, this time window is recommended for once-a-day data acquisition if the goal is to capture maximum stress level. Maize Ta based on CWSI during the first hourly period (10:00-11:00) was closest to Ta estimates from a widely used crop coefficient model. Thus, this time window is recommended if the goal is to monitor maize water use. Average CWSI over the 2 h after solar noon and during the study period (early August to late September, 2011) was 0.19, 0.57, and 0.20 for plots under full, low-frequency deficit, and high-frequency deficit irrigation regimes, respectively. During the same period (50 days), total maize Ta based on the 10:00-11:00 CWSI was 218, 141, and 208 mm for the same treatments, respectively. These val- ues were within 3 % of the results of the crop coefficient approach.

Walter C Bausch - One of the best experts on this subject based on the ideXlab platform.

  • Minimizing Instrumentation Requirement for estimating crop water stress index and transpiration of maize
    Irrigation Science, 2013
    Co-Authors: Saleh Taghvaeian, Kendall C. Dejonge, Walter C Bausch, José L. Chávez, Thomas J Trout
    Abstract:

    Research was conducted in northern Colorado in 2011 to estimate the crop water stress index (CWSI) and actual transpiration (Ta) of maize under a range of irriga- tion regimes. The main goal was to obtain these parameters with minimum Instrumentation and measurements. The results confirmed that empirical baselines required for CWSI calculation are transferable within regions with similar climatic conditions, eliminating the need to develop them for each irrigation scheme. This means that maize CWSI can be determined using only two instruments: an infrared thermometer and an air temperature/relative humidity sensor. Reference evapotranspiration data obtained from a modified atmometer were similar to those estimated at a standard weather station, suggesting that maize Ta can be calculated based on CWSI and by adding one additional instrument: a modified atmometer. Esti- mated CWSI during four hourly periods centered on solar noon was largest during the 2 h after solar noon. Hence, this time window is recommended for once-a-day data acquisition if the goal is to capture maximum stress level. Maize Ta based on CWSI during the first hourly period (10:00-11:00) was closest to Ta estimates from a widely used crop coefficient model. Thus, this time window is recommended if the goal is to monitor maize water use. Average CWSI over the 2 h after solar noon and during the study period (early August to late September, 2011) was 0.19, 0.57, and 0.20 for plots under full, low-frequency deficit, and high-frequency deficit irrigation regimes, respectively. During the same period (50 days), total maize Ta based on the 10:00-11:00 CWSI was 218, 141, and 208 mm for the same treatments, respectively. These val- ues were within 3 % of the results of the crop coefficient approach.

José L. Chávez - One of the best experts on this subject based on the ideXlab platform.

  • Minimizing Instrumentation Requirement for estimating crop water stress index and transpiration of maize
    Irrigation Science, 2013
    Co-Authors: Saleh Taghvaeian, Kendall C. Dejonge, Walter C Bausch, José L. Chávez, Thomas J Trout
    Abstract:

    Research was conducted in northern Colorado in 2011 to estimate the crop water stress index (CWSI) and actual transpiration (Ta) of maize under a range of irriga- tion regimes. The main goal was to obtain these parameters with minimum Instrumentation and measurements. The results confirmed that empirical baselines required for CWSI calculation are transferable within regions with similar climatic conditions, eliminating the need to develop them for each irrigation scheme. This means that maize CWSI can be determined using only two instruments: an infrared thermometer and an air temperature/relative humidity sensor. Reference evapotranspiration data obtained from a modified atmometer were similar to those estimated at a standard weather station, suggesting that maize Ta can be calculated based on CWSI and by adding one additional instrument: a modified atmometer. Esti- mated CWSI during four hourly periods centered on solar noon was largest during the 2 h after solar noon. Hence, this time window is recommended for once-a-day data acquisition if the goal is to capture maximum stress level. Maize Ta based on CWSI during the first hourly period (10:00-11:00) was closest to Ta estimates from a widely used crop coefficient model. Thus, this time window is recommended if the goal is to monitor maize water use. Average CWSI over the 2 h after solar noon and during the study period (early August to late September, 2011) was 0.19, 0.57, and 0.20 for plots under full, low-frequency deficit, and high-frequency deficit irrigation regimes, respectively. During the same period (50 days), total maize Ta based on the 10:00-11:00 CWSI was 218, 141, and 208 mm for the same treatments, respectively. These val- ues were within 3 % of the results of the crop coefficient approach.