scholarly journals Application of the Level Method for Computing Locational Convex Hull Prices

Author(s):  
Nicolas Stevens ◽  
Anthony Papavasiliou
Keyword(s):  
1989 ◽  
Vol 136 (6) ◽  
pp. 530
Author(s):  
G.R. Wilson ◽  
B.G. Batchelor
Keyword(s):  

2005 ◽  
Author(s):  
K. Parker ◽  
S. Rose-Pehrsson ◽  
D. Kidwell

2019 ◽  
Vol 31 (5) ◽  
pp. 761
Author(s):  
Xiao Lin ◽  
Zuxiang Liu ◽  
Xiaomei Zheng ◽  
Jifeng Huang ◽  
Lizhuang Ma

Processes ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1000
Author(s):  
Anamaria Călugăr ◽  
Teodora Emilia Coldea ◽  
Carmen Rodica Pop ◽  
Tiberia Ioana Pop ◽  
Anca Cristina Babeș ◽  
...  

The aim of this work was to compare the variations of alcohols compounds in white wine Muscat Ottonel variety aged in the presence of untoasted oak chips, toasted oak chips and untoasted barrel, considering three ageing periods—30, 60, and 90 days. The liquid-liquid extraction and gas chromatography coupled to mass spectrometry were used to compare the concentrations of the volatile constituents of Muscat Ottonel wines. A total of 51 volatile compounds were quantified. Alcohols, terpenic and carboxylic acids decreased with ageing time, whereas esters, lactones, and phenolic compounds increased due esterification processes. The chips toast level, method, and duration of ageing, significantly influenced the content of aromatic compounds. Partial least squares regression (PLS-R) clearly discriminated the initial wine and also the wines aged with toasted and untoasted medium. The compounds (alcohols and terpenes) that impart distinctive aroma of Muscat Ottonel were enhanced by untoasted medium. Light toasted oak chips enhanced wood volatile components (acetovanillone and p-vinyl guaiacol). This study provides important scientific results on the ageing of Muscat Ottonel wines with practical economic benefits to winemakers. Alternative less expensive ageing methods and improved control on the wood components extraction process, may contribute to obtaining high-quality wines.


2019 ◽  
Vol 82 ◽  
pp. 16-31 ◽  
Author(s):  
Jie Xue ◽  
Yuan Li ◽  
Ravi Janardan
Keyword(s):  

Author(s):  
Bochang Zou ◽  
Huadong Qiu ◽  
Yufeng Lu

The detection of spherical targets in workpiece shape clustering and fruit classification tasks is challenging. Spherical targets produce low detection accuracy in complex fields, and single-feature processing cannot accurately recognize spheres. Therefore, a novel spherical descriptor (SD) for contour fitting and convex hull processing is proposed. The SD achieves image de-noising by combining flooding processing and morphological operations. The number of polygon-fitted edges is obtained by convex hull processing based on contour extraction and fitting, and two RGB images of the same group of objects are obtained from different directions. The two fitted edges of the same target object obtained at two RGB images are extracted to form a two-dimensional array. The target object is defined as a sphere if the two values of the array are greater than a custom threshold. The first classification result is obtained by an improved K-NN algorithm. Circle detection is then performed on the results using improved Hough circle detection. We abbreviate it as a new Hough transform sphere descriptor (HSD). Experiments demonstrate that recognition of spherical objects is obtained with 98.8% accuracy. Therefore, experimental results show that our method is compared with other latest methods, HSD has higher identification accuracy than other methods.


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