A Workflow Approach to Life of Field Management

2004 ◽  
Author(s):  
Lei-Ming Yeow ◽  
Rosly Mohd Nor ◽  
Boo-Soon Lee ◽  
Kin-Wei Tsen
Keyword(s):  
Field Management

An expert system for real-time well field management

2012 ◽  
Vol 12 (5) ◽  
pp. 699-706 ◽  
Author(s):  
B. S. Marti ◽  
G. Bauser ◽  
F. Stauffer ◽  
U. Kuhlmann ◽  
H.-P. Kaiser ◽  
...  
Keyword(s):  
Drinking Water ◽  
Expert System ◽  
Knowledge Base ◽  
Real Time ◽  
Urban Areas ◽  
Industrial Sites ◽  
Water Wells ◽  
Well Field ◽  
Field Management ◽  
Historical Management

Well field management in urban areas faces challenges such as pollution from old waste deposits and former industrial sites, pollution from chemical accidents along transport lines or in industry, or diffuse pollution from leaking sewers. One possibility to protect the drinking water of a well field is the maintenance of a hydraulic barrier between the potentially polluted and the clean water. An example is the Hardhof well field in Zurich, Switzerland. This paper presents the methodology for a simple and fast expert system (ES), applies it to the Hardhof well field, and compares its performance to the historical management method of the Hardhof well field. Although the ES is quite simplistic it considerably improves the water quality in the drinking water wells. The ES knowledge base is crucial for successful management application. Therefore, a periodic update of the knowledge base is suggested for the real-time application of the ES.

scholarly journals Detection and Analysis of Degree of Maize Lodging Using UAV-RGB Image Multi-Feature Factors and Various Classification Methods

2021 ◽  
Vol 10 (5) ◽  
pp. 309
Author(s):  
Zixu Wang ◽  
Chenwei Nie ◽  
Hongwu Wang ◽  
Yong Ao ◽  
Xiuliang Jin ◽  
...  
Keyword(s):  
Crop Production ◽  
Accurate Determination ◽  
Management Strategies ◽  
Canopy Structure ◽  
Object Oriented ◽  
Texture Features ◽  
Sowing Date ◽  
Kappa Coefficient ◽  
Surface Model ◽  
Field Management

Maize (Zea mays L.), one of the most important agricultural crops in the world, which can be devastated by lodging, which can strike maize during its growing season. Maize lodging affects not only the yield but also the quality of its kernels. The identification of lodging is helpful to evaluate losses due to natural disasters, to screen lodging-resistant crop varieties, and to optimize field-management strategies. The accurate detection of crop lodging is inseparable from the accurate determination of the degree of lodging, which helps improve field management in the crop-production process. An approach was developed that fuses supervised and object-oriented classifications on spectrum, texture, and canopy structure data to determine the degree of lodging with high precision. The results showed that, combined with the original image, the change of the digital surface model, and texture features, the overall accuracy of the object-oriented classification method using random forest classifier was the best, which was 86.96% (kappa coefficient was 0.79). The best pixel-level supervised classification of the degree of maize lodging was 78.26% (kappa coefficient was 0.6). Based on the spatial distribution of degree of lodging as a function of crop variety, sowing date, densities, and different nitrogen treatments, this work determines how feature factors affect the degree of lodging. These results allow us to rapidly determine the degree of lodging of field maize, determine the optimal sowing date, optimal density and optimal fertilization method in field production.

The Clinical Presentation of Shoulder Instability Including on Field Management

1995 ◽  
Vol 14 (4) ◽  
pp. 761-776 ◽  
Author(s):  
Roald Bahr ◽  
Edward V. Craig ◽  
Lars Engebretsen
Keyword(s):  
Shoulder Instability ◽  
Clinical Presentation ◽  
Field Management

Compact EZ antenna arrays for field management in HPM applications

2014 ◽  
Author(s):  
Eric S. Ramon ◽  
J. Scott Tyo ◽  
Richard W. Ziolkowski ◽  
Michael C. Skipper ◽  
Michael D. Abdalla ◽  
...  
Keyword(s):  
Antenna Arrays ◽  
Field Management
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