Performance evaluation of multiple ground based sensors mounted on a commercial wild blueberry harvester to sense plant height, fruit yield and topographic features in real-time

2013 ◽  
Vol 91 ◽  
pp. 135-144 ◽  
Author(s):  
Aitazaz A. Farooque ◽  
Young K. Chang ◽  
Qamar U. Zaman ◽  
Dominic Groulx ◽  
Arnold W. Schumann ◽  
...  
2017 ◽  
Vol 33 (5) ◽  
pp. 655-666
Author(s):  
Aitazaz Ahsan Farooque ◽  
Qamar Uz Zaman ◽  
Travis Esau ◽  
Young Ki Chang ◽  
Arnold Walter Schumann ◽  
...  

Abstract. Spatial variability in fruit losses in relation to fruit yield, plant height, and ground slope can help to automate the wild blueberry harvester to improve picking performance. Currently, harvester operators adjust harvester’s head height, ground speed, and revolutions per minute (rpm) manually. This is not only laborious but also stressful for operators, as they encounter spatial variability during harvesting. The goal of this work was to identify the automation potential of the harvester to improve harvestable yield and reduce operator’s stress, keeping in view the spatial variability. Two fields were selected and test plots were constructed to examine the performance of the harvester in five zones of plant height, fruit yield, and ground slope. Fruit yield plant height and ground slope were recorded from each plot manually to examine their impact on total fruit loss. Keywords: Automation, Fruit losses, Spatial variability, Wild blueberry, Zonal analysis.Results confirmed significant variability in fruit yield, plant height, and ground slope. Fruit losses were significantly influenced by the spatial variations. Fruit losses increased with an increase in fruit yield and ground slope during mechanical harvesting. The picking performance of the blueberry harvester was significantly lower in short and very tall plants within selected fields. The dependence of fruit losses on fruit yield, plant height, and ground slope emphasize the need for real-time adjustments in machine operating parameters to improve berry recovery. Based on the results, it is concluded that there is a significant advantage of harvester’s automation to increase profit margins for growers with no additional cost. Keywords: Automation, Fruit losses, Spatial variability, Wild blueberry, Zonal analysis.


2017 ◽  
Vol 157 ◽  
pp. 35-44 ◽  
Author(s):  
Young K. Chang ◽  
Qamar U. Zaman ◽  
Tanzeel U. Rehman ◽  
Aitazaz A. Farooque ◽  
Travis Esau ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3274
Author(s):  
Jose Rueda Torres ◽  
Zameer Ahmad ◽  
Nidarshan Veera Kumar ◽  
Elyas Rakhshani ◽  
Ebrahim Adabi ◽  
...  

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).


2020 ◽  
Vol 41 (S1) ◽  
pp. s367-s368
Author(s):  
Michael Korvink ◽  
John Martin ◽  
Michael Long

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


Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 556
Author(s):  
Lucia Lo Bello ◽  
Gaetano Patti ◽  
Giancarlo Vasta

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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