scholarly journals Gas Quality Parameter Computation in Intermeshed Networks

Biogas ◽  
10.5772/32585 ◽  
2012 ◽  
Author(s):  
Peter Hass
Keyword(s):  
Quality Parameter

Water quality parameter forecast based on grey neural network modeling

2009 ◽  
Vol 29 (6) ◽  
pp. 1529-1531 ◽  
Author(s):  
Wei-ren SHI ◽  
Yan-xia WANG ◽  
Yun-jian TANG ◽  
Min FAN
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Network Modeling ◽  
Quality Parameter ◽  
Water Quality Parameter ◽  
Neural Network Modeling

scholarly journals Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2298
Author(s):  
Pablo Cano Marchal ◽  
Chiara Sanmartin ◽  
Silvia Satorres Martínez ◽  
Juan Gómez Ortega ◽  
Fabio Mencarelli ◽  
...  
Keyword(s):  
Olive Oil ◽  
Low Cost ◽  
Virgin Olive Oil ◽  
General Purpose ◽  
Quality Parameter ◽  
Lasso Regression ◽  
Virgin Olive Oils ◽  
Electronic Noses ◽  
Olive Oils ◽  
Instrumental Technique

The organoleptic profile of a Virgin Olive Oil is a key quality parameter that is currently obtained by human sensory panels. The development of an instrumental technique capable of providing information about this profile quickly and online is of great interest. This work employed a general purpose e-nose, in lab conditions, to predict the level of fruity aroma and the presence of defects in Virgin Olive Oils. The raw data provided by the e-nose were used to extract a set of features that fed a regressor to predict the level of fruity aroma and a classifier to detect the presence of defects. The results obtained were a mean validation error of 0.5 units for the prediction of fruity aroma using lasso regression; and 88% accuracy for the defect detection using logistic regression. Finally, the identification of two out of ten specific sensors of the e-nose that can provide successful results paves the way to the design of low-cost specific electronic noses for this application.

scholarly journals Nutrient, pH, Alkalinity, and Ionic Property Levels in Runoff Containment Basins in Alabama, Louisiana, Maryland, Mississippi, and Virginia Ornamental Plant Nurseries

HortScience ◽  
2017 ◽  
Vol 52 (4) ◽  
pp. 641-648 ◽  
Author(s):  
Warren E. Copes ◽  
Haibo Zhang ◽  
Patricia A. Richardson ◽  
Bruk E. Belayneh ◽  
Andrew Ristvey ◽  
...  
Keyword(s):  
Water Quality ◽  
Ammonium Nitrogen ◽  
Quality Parameter ◽  
Ornamental Plant ◽  
Total Alkalinity ◽  
Water Quality Parameter ◽  
Runoff Water ◽  
Manganese Zinc ◽  
Water Ph ◽  
Parameter Values

Nine runoff containment basins (RCBs), used directly or indirectly for irrigating plants in ornamental plant nurseries, and one adjacent stream were sampled for water quality between Feb. and July 2013 in Maryland (MD), Mississippi (MS), and Virginia (VA). Triplicate water samples were taken monthly. Analysis was done for 18 water quality variables including nitrate-nitrogen (NO3−-N) and ammonium-nitrogen (NH4+-N), orthophosphate-phosphorus (PO4-P) and total-phosphorus (T-P), potassium, calcium, magnesium, sulfur, aluminum, boron (B), copper (Cu), iron (Fe), manganese, zinc (Zn), pH, total alkalinity (T-Alk), electrical conductivity (EC), and sodium. Additionally, 15 RCBs from 10 nurseries in Alabama (AL), Louisiana (LA), and MS were sampled in 2014 and 2016. Most prevalent correlations (P = 0.01) were between macronutrients, EC, B, Fe, and Zn, but none were prevalent across a majority of RCBs. Water quality parameter values were mostly present at low to preferred levels in all 25 waterways. Macronutrient levels were highest for a RCB that receives fertility from fertigation derived runoff. Water pH ranged from acidic to alkaline (>8). Results of this study show water quality in RCBs can be suitable for promoting plant health in ornamental plant nurseries, but also shows levels will vary between individual RCBs, therefore demonstrates need to verify water quality from individual water sources.

Assessment of biomass functions for calculating bark proportions and ash contents of refined biomass fuels derived from major boreal tree species

2012 ◽  
Vol 42 (1) ◽  
pp. 59-66 ◽  
Author(s):  
Torbjörn A. Lestander ◽  
Anders Lundström ◽  
Michael Finell
Keyword(s):  
Betula Pendula ◽  
Quality Parameter ◽  
Sample Population ◽  
Tree Biomass ◽  
Stem Biomass ◽  
Fuel Pellets ◽  
Current Limit ◽  
Forest Survey ◽  
Betula Pubescens Ehrh ◽  
Biomass Functions

Knowledge of the components of above-ground biomass of low-quality stems harvested to produce biofuel pellets is important, since bark has higher ash contents (a key quality parameter for the pellets) than wood. Therefore, single-tree biomass functions by Marklund (1988. Rep. 45. Department of Forest Survey, Swedish University of Agricultural Sciences, Umea, Sweden.) were evaluated using a sample population of 1612 Scots pine ( Pinus sylvestris L.), Norway spruce ( Pices abies (L.) Karst.), and birch ( Betula pendula Roth and Betula pubescens Ehrh.) trees and three methods to model bark proportions. Bark percentages calculated subtractively using functions for stem biomass over and under bark showed anomalous patterns, especially for pine and birch. However, additive use of biomass functions for bark biomass and stem biomass under bark resulted in similar patterns to bark percentages traditionally calculated from bark biomass and stem biomass over bark. Published ash contents of bark and stemwood indicate that pine, birch, and spruce stems with breast height (1.3 m) diameters of 4–40, 4–30, and >19 cm, respectively, have <0.7% ash contents (the current limit for the highest quality fuel pellets). However, if the highest recorded ash contents are used, only pine stems meet this criterion. Thus, material of different species and stem dimensions may need to be carefully mixed when whole-stem biomass is used as feedstock for pelletizing.

Endotoxin testing in inhalation grade lactose—a useful quality parameter?

2004 ◽  
Vol 275 (1-2) ◽  
pp. 211-215 ◽  
Author(s):  
Hartwig Steckel ◽  
Franz H Furkert
Keyword(s):  
Quality Parameter

scholarly journals Large-Scale Laboratory Experiments on Mussel Dropper Lines in Ocean Surface Waves

2020 ◽  
Vol 9 (1) ◽  
pp. 29
Author(s):  
Rebekka Gieschen ◽  
Christian Schwartpaul ◽  
Jannis Landmann ◽  
Lukas Fröhling ◽  
Arndt Hildebrandt ◽  
...  
Keyword(s):  
Large Scale ◽  
Laboratory Experiments ◽  
Blue Mussel ◽  
Farming Systems ◽  
Quality Parameter ◽  
Large Wave ◽  
Marine Aquaculture ◽  
Ocean Surface Waves ◽  
Wave Flume ◽  
Waves And Currents

The rapid growth of marine aquaculture around the world accentuates issues of sustainability and environmental impacts of large-scale farming systems. One potential mitigation strategy is to relocate to more energetic offshore locations. However, research regarding the forces which waves and currents impose on aquaculture structures in such conditions is still scarce. The present study aimed at extending the knowledge related to live blue mussels (Mytilus edulis), cultivated on dropper lines, by unique, large-scale laboratory experiments in the Large Wave Flume of the Coastal Research Center in Hannover, Germany. Nine-months-old live dropper lines and a surrogate of 2.0 m length each are exposed to regular waves with wave heights between 0.2 and 1.0 m and periods between 1.5 and 8.0 s. Force time histories are recorded to investigate the inertia and drag characteristics of live mussel and surrogate dropper lines. The surrogate dropper line was developed from 3D scans of blue mussel dropper lines, using the surface descriptor Abbott–Firestone Curve as quality parameter. Pull-off tests of individual mussels are conducted that reveal maximum attachment strength ranges of 0.48 to 10.55 N for mussels that had medium 3.04 cm length, 1.60 cm height and 1.25 cm width. Mean drag coefficients of CD = 3.9 were found for live blue mussel lines and CD = 3.4 for the surrogate model, for conditions of Keulegan–Carpenter number (KC) 10 to 380, using regular wave tests.

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