Performance Evaluation and Accuracy of Passive Capillary Samplers (PCAPs) for Estimating Real-Time Drainage Water Fluxes

2012 ◽  
Vol 28 (4) ◽  
pp. 537-542 ◽  
Author(s):  
J. D. Jabro ◽  
W. M. Iversen ◽  
R. G. Evans
Keyword(s):  
Performance Evaluation ◽  
Real Time ◽  
Drainage Water ◽  
Water Fluxes

A New Automated Passive Capillary Lysimeter for Logging Real-Time Drainage Water Fluxes

2017 ◽  
Vol 33 (6) ◽  
pp. 849-857
Author(s):  
J. D. Jabro ◽  
W. M. Iversen ◽  
W. B. Stevens ◽  
B. L. Allen ◽  
U. M. Sainju
Keyword(s):  
Real Time ◽  
Vadose Zone ◽  
Spread Spectrum ◽  
Root Zone ◽  
Sandy Loam ◽  
Irrigation System ◽  
Cropping Systems ◽  
Soil Surface ◽  
Drainage Water ◽  
Water Fluxes

Abstract.Effective monitoring of chemical transport through the soil profile requires accurate and appropriate instrumentation to measure drainage water fluxes below the root zone of cropping systems. The objectives of this study were to methodically describe in detail the construction and installation of a novel automated PCAP (passive capillary) lysimeter design, and to evaluate the efficacy of this design for logging and monitoring real-time drainage water fluxes occurring below the root zone of corn ( L.) and soybean ( L.) under an overhead sprinkler irrigation system. Sixteen cylindrical PCAP lysimeters with outside dimensions of 32.39 cm in diameter ×74.8 cm height (1000 cm2 surface area) were designed, constructed, and placed 90 cm below the soil surface in a Lihen sandy loam. Two watermark soil moisture and temperature sensors were positioned at 30 and 76 cm depths above each PCAP to monitor soil temperature and water potential continuously. This new design incorporated wireless spread spectrum technology to enable an automated datalogger to transmit drainage water amounts simultaneously every 15 min to a remote host. Logged drainage amounts were compared with those manually collected using several statistical methods. The root mean square error (RMSE), the logging efficacy (EF), and the mean difference (MD) were 0.0375, 0.964 and 0.0335 cm, respectively, for 4-yr combined data. The MD between logged and collected drainage amounts was very small and not significantly different from zero for 4-yr combined results. Statistical results indicated that the new lysimeter performed exceptionally well and was capable of monitoring drainage water fluxes in the vadose zone. Real-time seamless monitoring and logging drainage water fluxes was thus possible without the need for costly time-consuming supportive procedures. Keywords: Drainage, Lysimeter, Root zone, Vadose zone.

scholarly journals Power Hardware-in-the-Loop-Based Performance Analysis of Different Converter Controllers for Fast Active Power Regulation in Low-Inertia Power Systems

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3274
Author(s):  
Jose Rueda Torres ◽  
Zameer Ahmad ◽  
Nidarshan Veera Kumar ◽  
Elyas Rakhshani ◽  
Ebrahim Adabi ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Power Systems ◽  
Real Time ◽  
Control Strategies ◽  
Active Power ◽  
Power Electronic ◽  
Hardware In The Loop ◽  
Digital Controllers ◽  
Power Regulation ◽  
The Impact

Future electrical power systems will be dominated by power electronic converters, which are deployed for the integration of renewable power plants, responsive demand, and different types of storage systems. The stability of such systems will strongly depend on the control strategies attached to the converters. In this context, laboratory-scale setups are becoming the key tools for prototyping and evaluating the performance and robustness of different converter technologies and control strategies. The performance evaluation of control strategies for dynamic frequency support using fast active power regulation (FAPR) requires the urgent development of a suitable power hardware-in-the-loop (PHIL) setup. In this paper, the most prominent emerging types of FAPR are selected and studied: droop-based FAPR, droop derivative-based FAPR, and virtual synchronous power (VSP)-based FAPR. A novel setup for PHIL-based performance evaluation of these strategies is proposed. The setup combines the advanced modeling and simulation functions of a real-time digital simulation platform (RTDS), an external programmable unit to implement the studied FAPR control strategies as digital controllers, and actual hardware. The hardware setup consists of a grid emulator to recreate the dynamic response as seen from the interface bus of the grid side converter of a power electronic-interfaced device (e.g., type-IV wind turbines), and a mockup voltage source converter (VSC, i.e., a device under test (DUT)). The DUT is virtually interfaced to one high-voltage bus of the electromagnetic transient (EMT) representation of a variant of the IEEE 9 bus test system, which has been modified to consider an operating condition with 52% of the total supply provided by wind power generation. The selected and programmed FAPR strategies are applied to the DUT, with the ultimate goal of ascertaining its feasibility and effectiveness with respect to the pure software-based EMT representation performed in real time. Particularly, the time-varying response of the active power injection by each FAPR control strategy and the impact on the instantaneous frequency excursions occurring in the frequency containment periods are analyzed. The performed tests show the degree of improvements on both the rate-of-change-of-frequency (RoCoF) and the maximum frequency excursion (e.g., nadir).

scholarly journals Real-Time Identification of Patients Included in the CMS Bundled Payment Care Improvement (BPCI) Program

2020 ◽  
Vol 41 (S1) ◽  
pp. s367-s368
Author(s):  
Michael Korvink ◽  
John Martin ◽  
Michael Long
Keyword(s):  
Performance Evaluation ◽  
Real Time ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Care Providers ◽  
Meta Model ◽  
Bundled Payment ◽  
Clinical Cohort ◽  
Real Time Identification ◽  
Care Improvement

Background: The Bundled Payment Care Improvement Program is a CMS initiative designed to encourage greater collaboration across settings of care, especially as it relates to an initial set of targeted clinical episodes, which include sepsis and pneumonia. As with many CMS incentive programs, performance evaluation is retrospective in nature, resulting in after-the-fact changes in operational processes to improve both efficiency and quality. Although retrospective performance evaluation is informative, care providers would ideally identify a patient’s potential clinical cohort during the index stay and implement care management procedures as necessary to prevent or reduce the severity of the condition. The primary challenges for real-time identification of a patient’s clinical cohort are CMS-targeted cohorts are based on either MS-DRG (grouping of ICD-10 codes) or HCPCS coding—coding that occurs after discharge by clinical abstractors. Additionally, many informative data elements in the EHR lack standardization and no simple and reliable heuristic rules can be employed to meaningfully identify those cohorts without human review. Objective: To share the results of an ensemble statistical model to predict patient risks of sepsis and pneumonia during their hospital (ie, index) stay. Methods: The predictive model uses a combination of Bernoulli Naïve Bayes natural language processing (NLP) classifiers, to reduce text dimensionality into a single probability value, and an eXtreme Gradient Boosting (XGBoost) algorithm as a meta-model to collectively evaluate both standardized clinical elements alongside the NLP-based text probabilities. Results: Bernoulli Naïve Bayes classifiers have proven to perform well on short text strings and allow for highly explanatory unstructured or semistructured text fields (eg, reason for visit, culture results), to be used in a both comparative and generalizable way within the larger XGBoost model. Conclusions: The choice of XGBoost as the meta-model has the benefits of mitigating concerns of nonlinearity among clinical features, reducing potential of overfitting, while allowing missing values to exist within the data. Both the Bayesian classifier and meta-model were trained using a patient-level integrated dataset extracted from both a patient-billing and EHR data warehouse maintained by Premier. The data set, joined by patient admission-date, medical record number, date of birth, and hospital entity code, allows the presence of both the coded clinical cohort (derived from the MS-DRG) and the explanatory features in the EHR to exist within a single patient encounter record. The resulting model produced F1 performance scores of .65 for the sepsis population and .61 for the pneumonia population.Funding: NoneDisclosures: None

scholarly journals Assessments of Real-Time Communications over TSN Automotive Networks

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 556
Author(s):  
Lucia Lo Bello ◽  
Gaetano Patti ◽  
Giancarlo Vasta
Keyword(s):  
Performance Evaluation ◽  
Real Time ◽  
Communication System ◽  
Traffic Management ◽  
Mac Layer ◽  
Automated Driving ◽  
Real Time Traffic ◽  
Management Scheme ◽  
Event Driven ◽  
Automotive Networks

The IEEE 802.1Q-2018 standard embeds in Ethernet bridges novel features that are very important for automated driving, such as the support for time-driven communications. However, cars move in a world where unpredictable events may occur and determine unforeseen situations. To properly react to such situations, the in-car communication system has to support event-driven transmissions with very low and bounded delays. This work provides the performance evaluation of EDSched, a traffic management scheme for IEEE 802.1Q bridges and end nodes that introduces explicit support for event-driven real-time traffic. EDSched works at the MAC layer and builds upon the mechanisms defined in the IEEE 802.1Q-2018 standard.

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