Objectification of the evaluation of a pharmacological test with alpha-adrenergic blocking agents during uroflowmetry

Author(s):  
Vadim Valerievich Danilov ◽  
Vitaliy Vadimovich Danilov ◽  
Danilov Valeriy Vadimovich Danilov Valeriy Vadimovich

The tactics of treating dysuric disorders are largely determined by the pathophysiological and morpho-clinical basis: infravesical obstruction, impaired bladder contractility, complex neurogenic urination disorders, etc. Among the diseases that most often cause infravesical obstruction in men, the most common pathologies are benign prostatic hyperplasia, prostate cancer, prostate sclerosis, obstructive processes of the bladder neck (contractures, fibrosis), urethral strictures of various etiologies. The use of a comprehensive urodynamic study makes it possible to differentiate the causes of urinary disorders. One of the most common and non-invasive methods used in the urologist’s clinical practice is uroflowmetry. The use of the fuzzy logic algorithm described in the article for making a decision on the presence of obstructive urination allows one to assess the urodynamic situation using the home uroflow monitoring technique. Analytical urodynamics in conjunction with the fuzzy logic block increases the accuracy of describing the examination results, and the introduction of the proposed model into the software simplifies the work with diagnostic urological equipment and increases the efficiency of the examination.

2018 ◽  
Vol 10 (12) ◽  
pp. 4787 ◽  
Author(s):  
Muath Bani Salim ◽  
Dervis Emre Demirocak ◽  
Nael Barakat

In this paper, a new environmental sustainability indicator (ESI) is proposed to evaluate photovoltaic (PV) cells utilizing Life Cycle Analysis (LCA) principles. The proposed indicator is based on a model that employs a fuzzy logic algorithm to combine multiple factors, usually used in multiple LCAs, and produce results allowing a comprehensive interpretation of LCA phase sub-results leading to standardized comparisons of various PV cells. Such comparisons would be essential for policymakers and PV cell manufacturers and users, as they allow for fair assessment of the environmental sustainability of a particular type of PV with multiple factors. The output of the proposed model was tested and verified against published information on LCAs related to PV cells. A distinct feature of this fuzzy logic model is its expandability, allowing more factors to be included in the future, as desired by the users, or dictated by a new discovery. It also provides a platform that can be used to evaluate other families of products. Moreover, standardizing the comparison process helps in improving the sustainability of PV cells through targeting individual relevant factors for changes while tracking the combined final impact of these changes on the overall environmental sustainability of the PV cell.


2022 ◽  
Author(s):  
Mazen Mohammed ◽  
Lasheng Yu ◽  
Ali Aldhubri ◽  
Gamil R. S.Qaid

Abstract In recent times, sentiment analysis research has gained wide popularity. That situation is caused by the nature of online applications that allow users to express their opinions on events, services, or products through social media applications such as Twitter, Facebook, and Amazon. This paper proposes a novel sentiment classification method according to the Fuzzy rule-based system (FRBS) with crow search algorithm (CSA). FRBS is used to classify the polarity of sentences or documents, and the CSA is employed to optimize the best output from the fuzzy logic algorithm. The FRBS is applied to extract the sentiment and classify its polarity into negative, neutral, and positive. Sometimes, the outputs of the FRBS must be enhanced, especially since many variables are present and the rules between them overlap. For such cases, the CSA is used to solve this limitation faced by FRBS to optimize the outputs of FRBS and achieve the best result. We compared the performance of our proposed model with different machine learning algorithms, such as SVM, maximum entropy, boosting, and SWESA. We tested our model on three famous data sets collected from Amazon, Yelp, and IMDB. Experimental results demonstrated the effectiveness of the proposed model and achieved competitive performance in terms of accuracy, recall, precision, and the F–score.


2020 ◽  
Vol 4 ◽  
pp. 116-126
Author(s):  
Satya Prakash Kumar ◽  
V.K. Tewari ◽  
Abhilash K. Chandel ◽  
C.R. Mehta ◽  
Brajesh Nare ◽  
...  

Author(s):  
Kai Ren

In all kinds of traffic accidents, the unconscious departure of the vehicle from the lane is one of the most important reasons leading to the occurrence of these accidents. In view of the specific problem of lane departure, a lane departure decision-making method is established without calibration relying on the Kalman filtering fuzzy logic algorithm, according to the characteristics of expressway lanes, based on the machine vision and hearing fusion analysis of lane departure, integrating the extraction of the linear lane line model and the region of interest (ROI) in this paper to judge the degree of vehicle departure from the lane by integrating the slope values of the 2 lane lines in the road image. The results show that the system has good lane recognition capabilities and accurate departure decision-making capabilities, and meet the lane departure warning requirements in the expressway environment.


2002 ◽  
Vol 11 (4) ◽  
pp. 541-552 ◽  
Author(s):  
Kelly Cohen ◽  
Tanchum Weller ◽  
Joseph Z Ben-Asher

Author(s):  
Zakaria Shams Siam ◽  
Rubyat Tasnuva Hasan ◽  
Hossain Ahamed ◽  
Samiya Kabir Youme ◽  
Soumik Sarker Anik ◽  
...  

Different epidemiological compartmental models have been presented to predict the transmission dynamics of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we have proposed a fuzzy rule-based Susceptible-Exposed-Infectious-Recovered-Death ([Formula: see text]) compartmental model considering a new dynamic transmission possibility variable as a function of time and three different fuzzy linguistic intervention variables to delineate the intervention and transmission heterogeneity on SARS-CoV-2 viral infection. We have analyzed the datasets of active cases and total death cases of China and Bangladesh. Using our model, we have predicted active cases and total death cases for China and Bangladesh. We further presented the correspondence of different intervention measures in relaxing the transmission possibility. The proposed model delineates the correspondence between the intervention measures as fuzzy subsets and the predicted active cases and total death cases. The prediction made by our system fitted the collected dataset very well while considering different fuzzy intervention measures. The integration of fuzzy logic in the classical compartmental model also produces more realistic results as it generates a dynamic transmission possibility variable. The proposed model could be used to control the transmission of SARS-CoV-2 as it deals with the intervention and transmission heterogeneity on SARS-CoV-2 transmission dynamics.


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