scholarly journals Research on Novel Correlation Coefficient of Neutrosophic Cubic Sets and Its Applications

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Huiling Xue ◽  
Minrong Yu ◽  
Chunfang Chen
Keyword(s):  
Pattern Recognition ◽  
Comparative Analysis ◽  
Correlation Coefficient ◽  
Good Tool ◽  
Decision Method

Single-valued neutrosophic cubic set is a good tool to solve the vague and uncertain problems because it contains more information. The article first gives the correlation coefficient of single-valued neutrosophic cubic sets. Then, a decision method is proposed, and an application in pattern recognition is considered. Finally, examples are given to explain the feasibility of this method. At the same time, the comparative analysis shows the superiority of this method.

Comparative Analysis of Two Volumetrical Ultrafiltration Monitors for Hemodialysis

1986 ◽  
Vol 9 (3) ◽  
pp. 163-166
Author(s):  
J.H.M. Berden ◽  
J.M.P. Wokke ◽  
R.A.P. Koene
Keyword(s):  
Comparative Analysis ◽  
Correlation Coefficient ◽  
Hollow Fiber ◽  
Clinical Setting ◽  
Parallel Flow ◽  
The Other ◽  
Dialysis Modality ◽  
Volumetric Measurement ◽  
Dialysate Flow ◽  
Regression Correlation

Controlled ultrafiltration (UF) during hemodialysis may prevent dialysis associated hypotension. A prerequisite for controlled ultrafiltration is an accurate measurement of ultrafiltration. Volumetric measurement is the best currently available method for this purpose. In this study we compared in a clinical setting two volumetric ultrafiltration monitors (UFM): one device constructed in our hospital using oval flowmeters (UFM-N) and the other using electromagnetic flow transducers (UFM-G: UFM 10-2, Gambro Lund Sweden). The UF measurements of both UFM's were compared with UF calculated from bedscales weight monitoring and standard scales determinations. During dual needle hemodialysis (n = 8) with a hollow fiber dialyzer the accuracy of the UFM-N was 91% and that of the UFM-G 97%. During dual needle dialysis with a parallel flow dialyzer the UFM-N appeared to be more sensitive for pulsatile changes in the dialysate flow due to the greater compliance of this type of dialyzer. The accuracy of the UFM-N in this setting was 80%, while that of the UFM-G was 87% (n = 11). During single needle dialysis with a parallel flow dialyzer (n = 14) only the UFM-G was tested and it measured UF with an accuracy of 92%. Finally the UFM-G can control UF actively by adjusting the TMP to obtain a given UF rate. The accuracy of the UFM-G in this setting was 94%, and the lineair regression correlation coefficient between planned UF and actually obtained UF was 0.974 (n - 61). In conclusion volumetric monitoring of UF is accurate and reliable, but its accuracy is dependent on the type of dialyzer used. The UFM-G proved to be useful in every dialysis modality tested, while the UFM-N can be used in dual-needle dialysis using hollow fiber dialyzers.

Research on the Relation of Thunderstorm Days and Lightning Density in Jiangsu Province

2013 ◽  
Vol 807-809 ◽  
pp. 699-703
Author(s):  
Zhong Jiang Yang ◽  
Tian Zhang ◽  
Ming Xue Feng ◽  
Xue Jiao ◽  
Bin Bin Lin
Keyword(s):  
Comparative Analysis ◽  
Correlation Coefficient ◽  
Relative Error ◽  
Jiangsu Province ◽  
Average Relative Error ◽  
Density Data ◽  
Actual Application ◽  
Standard Equation ◽  
Weather Stations ◽  
Curve Equation

Thunderstorm days are used to show the lightning frequency happened somewhere. Through comparative analysis on the thunderstorm days data of 66 weather stations in Jiangsu province and lightning data of ADTD lightning monitoring, it presents that the correlation coefficient r became the largest at 11 km range, and the longest distance of thunderstorm artificial observation is 11-14 km. According to the study of lightning activities in Jiangsu province to get the statistical fitting function curve equation by thunderstorm days and ground flash density data. Test the actual application effect of fitting equation by calculating the average relative error of fitting equation and standard equation, then make sure the actual thunderstorm days in Jiangsu province and the cloud to ground flash density formula is Ng=0.0224 Td1.48.

scholarly journals A Systematic Comparative Analysis of Clustering Techniques

2020 ◽  
Vol 25 (2) ◽  
pp. 87-104
Author(s):  
Satinder Bal Gupta ◽  
Rajkumar Yadav ◽  
Shivani Gupta
Keyword(s):  
Machine Learning ◽  
Pattern Recognition ◽  
Information Retrieval ◽  
Comparative Analysis ◽  
Time Complexity ◽  
Clustering Methods ◽  
Clustering Techniques ◽  
Day By Day

AbstractClustering has now become a very important tool to manage the data in many areas such as pattern recognition, machine learning, information retrieval etc. The database is increasing day by day and thus it is required to maintain the data in such a manner that useful information can easily be extracted and used accordingly. In this process, clustering plays an important role as it forms clusters of the data on the basis of similarity in data. There are more than hundred clustering methods and algorithms that can be used for mining the data but all these algorithms do not provide models for their clusters and thus it becomes difficult to categorise all of them. This paper describes the most commonly used and popular clustering techniques and also compares them on the basis of their merits, demerits and time complexity.

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