AN APPROACH TO PREDICTION OF THE TELECOMMUNICATION NETWORK QUALITY PARAMETERS UNDER THE CONDITIONS OF NON-STOCHASTIC UNCERTAINTY

2017 ◽  
Vol 76 (11) ◽  
pp. 1027-1032
Author(s):  
N. О. Korolyuk
Keyword(s):  
Telecommunication Network ◽  
Quality Parameters ◽  
Stochastic Uncertainty ◽  
Network Quality

scholarly journals Modelling the Interaction between Air Pollutant Emissions and Their Key Sources in Poland

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 6891
Author(s):  
Alicja Kolasa-Więcek ◽  
Dariusz Suszanowicz ◽  
Agnieszka A. Pilarska ◽  
Krzysztof Pilarski
Keyword(s):  
Sensitivity Analysis ◽  
Real Data ◽  
Quality Parameters ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Network Quality ◽  
Input Variables ◽  
Environmental Air ◽  
Experimental Values ◽  
Mlp Neural Networks

The main purpose of this study is to investigate the relationships between key sources of air pollutant emissions (sources of energy production, factories which are particularly harmful to the environment, the fleets of cars, environmental protection expenditure) and the main environmental air pollution (SO2, NOx, CO and PM) in Poland. Models based on MLP neural networks were used as predictive models. Global sensitivity analysis was used to demonstrate the significant impact of individual network input variables on the output variable. To verify the effectiveness of the models created, the actual data were compared with the data obtained through modelling. Projected courses of changes in the variables under study correspond with the real data, which confirms that the proposed models generalize acquired knowledge well. The high MLP network quality parameters of 0.99–0.85 indicate that the network generalizes the acquired knowledge accurately. The sensitivity analysis for NOx, CO and PM pollutants indicates the significance of all input variables. For SO2, it showed significance for four of the six variables analysed. The predictions made by the neural models are not very different from the experimental values.

Monitoring of essential oils during storage by selected quality parameters

Planta Medica ◽  
2010 ◽  
Vol 76 (12) ◽  
Author(s):  
C Turek ◽  
S Ritter ◽  
F Stintzing
Keyword(s):  
Essential Oils ◽  
Quality Parameters

Creating adaptive predictions for packaging-critical quality parameters using advanced analytics and machine learning

TAPPI Journal ◽  
2019 ◽  
Vol 18 (11) ◽  
pp. 679-689
Author(s):  
CYDNEY RECHTIN ◽  
CHITTA RANJAN ◽  
ANTHONY LEWIS ◽  
BETH ANN ZARKO
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Predictive Analytics ◽  
Paper Industry ◽  
Quality Parameters ◽  
Fast Change ◽  
The Face ◽  
Model Tuning ◽  
Reducing Costs ◽  
Time Critical

Packaging manufacturers are challenged to achieve consistent strength targets and maximize production while reducing costs through smarter fiber utilization, chemical optimization, energy reduction, and more. With innovative instrumentation readily accessible, mills are collecting vast amounts of data that provide them with ever increasing visibility into their processes. Turning this visibility into actionable insight is key to successfully exceeding customer expectations and reducing costs. Predictive analytics supported by machine learning can provide real-time quality measures that remain robust and accurate in the face of changing machine conditions. These adaptive quality “soft sensors” allow for more informed, on-the-fly process changes; fast change detection; and process control optimization without requiring periodic model tuning. The use of predictive modeling in the paper industry has increased in recent years; however, little attention has been given to packaging finished quality. The use of machine learning to maintain prediction relevancy under everchanging machine conditions is novel. In this paper, we demonstrate the process of establishing real-time, adaptive quality predictions in an industry focused on reel-to-reel quality control, and we discuss the value created through the availability and use of real-time critical quality.

The Effect of Service Quality on Customers' Satisfaction in Mobile Phone Services in the UAE

2020 ◽  
Vol 8 (1) ◽  
pp. 75-94
Author(s):  
Emad Yusuf Masoud
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Mobile Phone ◽  
Service Providers ◽  
Mobile Service ◽  
Behavioural Difference ◽  
Mobile Industry ◽  
Quality Dimensions ◽  
Service Quality Dimensions ◽  
Network Quality

This study aims to determine the dimensions of mobile service quality and to examine their effect on customer satisfaction in UAE mobile phone service providers while also investigating the behavioural differences between mobile phone customers with prepaid and postpaid subscriptions. A combination of the SERVPERF model has been adopted as the main framework for analyzing service quality. A structured questionnaire instrument was designed for data collection. The present study concentrates on the level of customers’ satisfaction for leading service providers in the UAE mobile industry. Etisalat and Du were chosen for this study. A sample of (452) mobile phone users in Abu Dhabi city was selected at random using convenience-sampling. We found a positive effect of both functional and technical service quality (network quality) on customers’ satisfaction. Functional and technical dimensions were good predictors of customer satisfaction and confirmed the multidimensional nature of service quality. Also, the service quality dimensions; reliability, assurances, and responsiveness are found to be significant predictors of customer satisfaction. Behavioural difference between mobile phone customers is also significant in predicting customer satisfaction for postpaid subscribers. However, only reliability and network quality are significant predictors of customer satisfaction for prepaid subscribers. The model developed in this study provides marketers and researchers with a diagnostic tool to assess service quality from the perspectives of customers to meet the customer’s expectations and ensure customer satisfaction.

Quality of ram spermatozoa separated with modified swim up method

2018 ◽  
Vol 33 (2) ◽  
pp. 62-70 ◽  
Author(s):  
A Hossain ◽  
MM Islam ◽  
F Naznin ◽  
RN Ferdousi ◽  
FY Bari ◽  
...  
Keyword(s):  
Semen Quality ◽  
Membrane Integrity ◽  
Quality Parameters ◽  
Fluid Medium ◽  
Normal Morphology ◽  
The Mean ◽  
Mass Activity ◽  
Fresh Semen ◽  
Artificial Vagina

Semen was collected from four rams, using artificial vagina and viability%, motility% and plasma membrane integrity% were measured. Fresh ejaculates (n = 32) were separated by modified swim-up separation using modified human tubal fluid medium. Four fractions of supernatant were collected at 15-minute intervals. The mean volume, mass activity, concentration, motility%, viability%, normal morphology and membrane integrity% (HOST +ve) of fresh semen were 1.0 ± 0.14, 4.1 ± 0.1 × 109 spermatozoa/ml, 85.0 ± 1.3, 89.4 ± 1.0, 85.5 ± 0.7, 84.7 ± 0.5 respectively. There was no significant (P>0.05) difference in fresh semen quality parameters between rams. The motility%, viability% and HOST +ve % of first, second, third and fourth fractions were 53.4 ± 0.5, 68.2 ± 0.3, 74.8 ± 0.3 and 65.5 ± 0.4; 55.5 ± 0.4, 66.2 ± 0.4, 74.5 ± 0.3 and 73.6 ± 0.3 and 66.7 ± 0.5, 66.8 ± 0.5, 65.2 ± 0.4 and 74.7 ± 0.5 respectively. The motility%, viability% and membrane integrity% of separated semen samples differed significantly (P<0.05) between four fractions. The mean motility% and viability% were significantly higher (P<0.05) in third fraction (74.8 ± 0.3%), whereas the mean HOST +ve% was significantly higher (P<0.05) in fourth fraction (74.7 ± 0.5). All quality parameters of separated spermatozoa were significantly (P<0.05) lower than that of fresh semen. The pregnancy rates were higher with fresh semen (71%) in comparison to that of separated sample (57%).Bangl. vet. 2016. Vol. 33, No. 2, 62-70

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