scholarly journals Comparative Analysis and Statistical Optimization of Fuel Economy for Sustainable Vehicle Routings

2021 ◽  
Vol 14 (1) ◽  
pp. 64
Author(s):  
Naif Alsaadi
Keyword(s):  
Statistical Analysis ◽  
Fuel Economy ◽  
Statistical Significance ◽  
Research Work ◽  
Statistical Optimization ◽  
Optimization Techniques ◽  
Statistical Hypothesis ◽  
Air Conditioner ◽  
Traffic Patterns ◽  
Tire Pressure

In this 21st century, there has been an increase in the usage of renewable products for the economic drifting of vehicle transportations systems. Furthermore, due to recent trends in climate change, researchers have started focusing on statistical optimization techniques for sustainable vehicle routings. However, until now, a major gap has been noticed in the multidomain statistical analysis for optimizing the parametric levels of the vehicle fuel economy. Therefore, in this research work, two widely utilized cars (Toyota and GMC Yukon) are considered on a particular route of Jeddah for the collection of the fuel economy data under the realistic conditions of air conditioner temperature, traffic patterns, and tire pressure. The outcomes of the factorial design of the experiment highlight that the fuel economy is optimal under the low air conditioner temperature, light traffic patterns, and 34 PSI tire pressure. Three replications of the fuel economy have been considered, and the statistical significance of the correlated variables has been justified by implementing the analysis of variance (ANOVA) approach on the various levels of fuel economy. During the analysis, the statistical hypothesis for random exogenous factors has been developed by incorporating a multivariate regression model. The outcomes highlight that both air conditioner temperature and traffic patterns in Jeddah have a significant negative effect on fuel economy. Results also depict that the effect of air conditioner temperature, traffic patterns, and tire pressure is substantially higher for heavy-engine automobiles such as the GMC Yukon compared to light-engine cars (Toyota Corolla). Furthermore, a normality test has also been considered to validate the outcomes of the proposed model. Therefore, it is highly recommended to utilize the proposed methodology in optimizing the trends of fuel economy for sustainable vehicle routings. Based on the findings of multidomain statistical analysis, it is also highly recommended the utilization of the Toyota Corolla car model for investigating the correlation of external undeniable factors (braking frequency, metrological conditions, etc.) with the trends of vehicle fuel economy.

Effective Implementation of Value Engineering Using Artificial Neural Network Aid of Optimization Techniques

2019 ◽  
Vol 27 (03) ◽  
pp. 1950022 ◽  
Author(s):  
M. Prem Swarup ◽  
A. Prabhu Kumar
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Research Work ◽  
Optimization Techniques ◽  
Value Engineering ◽  
Training Algorithms ◽  
Air Conditioner ◽  
Ann Model ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Value Engineering (VE) is a method for characterizing the developed requirements of a product, and it is concerned with the selection of less excessive conditions. VE can understand and improve the optimal outcome such as quantity, security, unwavering quality and convertibility of each managerial unit. It is an incredible solving tool that can diminish costs while preserving or improving performance and quality requirements. In this research work, VE is presented to calculate the heating cost and cooling cost of the air conditioner with the assistance of an Artificial Neural Network (ANN) with an optimization model. This ANN model effectively chooses the maximum number of sources obtainable and the source respective method with low functional cost and energy consumption. For improving the prediction accuracy of VE in the ANN model, we have incorporated some training algorithms and optimized the network hidden layer and hidden neuron by Opposition Genetic Algorithm (OGA). From the results, trained ANN with OGA predicts the output with 96.02% accuracy and also minimum errors compared with the existing GA process.

scholarly journals Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Lukas Vlcek ◽  
Shize Yang ◽  
Yongji Gong ◽  
Pulickel Ajayan ◽  
Wu Zhou ◽  
...  
Keyword(s):  
Effective Interaction ◽  
Mean Field ◽  
Interaction Model ◽  
Optimization Techniques ◽  
Statistical Hypothesis ◽  
Structure Property ◽  
Statistical Hypothesis Testing ◽  
Stochastic Representation ◽  
Scanning Transmission ◽  
Complex Structural

AbstractExploration of structure-property relationships as a function of dopant concentration is commonly based on mean field theories for solid solutions. However, such theories that work well for semiconductors tend to fail in materials with strong correlations, either in electronic behavior or chemical segregation. In these cases, the details of atomic arrangements are generally not explored and analyzed. The knowledge of the generative physics and chemistry of the material can obviate this problem, since defect configuration libraries as stochastic representation of atomic level structures can be generated, or parameters of mesoscopic thermodynamic models can be derived. To obtain such information for improved predictions, we use data from atomically resolved microscopic images that visualize complex structural correlations within the system and translate them into statistical mechanical models of structure formation. Given the significant uncertainties about the microscopic aspects of the material’s processing history along with the limited number of available images, we combine model optimization techniques with the principles of statistical hypothesis testing. We demonstrate the approach on data from a series of atomically-resolved scanning transmission electron microscopy images of MoxRe1-xS2 at varying ratios of Mo/Re stoichiometries, for which we propose an effective interaction model that is then used to generate atomic configurations and make testable predictions at a range of concentrations and formation temperatures.

scholarly journals Characteristics of anteroposterior curvatures of the spine in soccer and futsal players

2017 ◽  
Vol 18 (4) ◽  
Author(s):  
Krystyna Chromik ◽  
Anna Burdukiewicz ◽  
Jadwiga Pietraszewska ◽  
Aleksandra Stachoń ◽  
Paweł Wolański ◽  
...  
Keyword(s):  
College Students ◽  
Statistical Analysis ◽  
Injury Prevention ◽  
Analysis Of Variance ◽  
Statistical Significance ◽  
Body Posture ◽  
Soccer Players ◽  
Prevention Training ◽  
The Difference ◽  
Post Hoc

AbstractPurpose. The aim of the study was to determine differences in anteroposterior spine curvatures between futsal players, soccer players, and non-training students. The results may contribute to the development of present-day knowledge of posturometry, and its implementation in training can help reduce the risk of body posture disorders in athletes. Methods. The examined group consisted of 48 athletes and 38 non-training college students. Body posture parameters were measured with the use of Posturometr-S. The normality of distribution was checked with the Shapiro-Wilk test, and the differences between the groups were measured with ANOVA and the Bonferroni post-hoc test. The level of statistical significance was set at p < 0.05. Results. The analysis of angle values revealed the widest and most similar measurements in the group of futsal players and soccer players. The analysis of variance proved statistically significant differences between the soccer players and futsal players (p = 0.003). The difference between the soccer players and non-training students was statistically significant. The highest γ angular value was measured in non-training students, followed by futsal players and soccer players. The statistical analysis revealed significant differences between the non-training students and futsal players, as well as non-training students and soccer players (p < 0.001). Conclusions. A complex assessment of athletes’ body posture is crucial in injury prevention. Training overloads may often lead to disorders of the organ of locomotion and affect the correct body posture in athletes. This, in turn, may result in pains and injuries.

Do longitudinal orthodontic trials use appropriate statistical analyses? A meta-epidemiological study

2021 ◽  
Author(s):  
Samer Mheissen ◽  
Haris Khan ◽  
Mohammed Almuzian ◽  
Emad Eddin Alzoubi ◽  
Nikolaos Pandis
Keyword(s):  
Statistical Analysis ◽  
Epidemiological Study ◽  
Data Extraction ◽  
Statistical Significance ◽  
Repeated Measure ◽  
Exact Test ◽  
Optimal Analysis ◽  
Study Characteristics ◽  
Measure Analysis ◽  
Repeated Measure Analysis

Summary Background In orthodontic trials, longitudinal designs with multiple outcome measurements over time are common. The aim of this epidemiological study was to examine whether optimal statistical analysis approaches have been used in longitudinal orthodontic trials. Methods Pubmed was searched in August 2021 for longitudinal orthodontic trials with at least three time points of outcome assessment published in the 2017–20 period. Study selection and data extraction were done independently and in duplicate. The analysis approaches undertaken were tabulated and associations between study characteristics and the use of optimal analysis or not were assessed using Fisher’s exact test and logistic regression. Results One hundred forty-seven out of 563 unique records were deemed eligible for inclusion. Only 26.50% of these trials used an optimal statistical analysis for longitudinal data where the data structure is accounted for. None of the study characteristics except the statistical significance of the results were associated with the appropriateness of the statistical analysis. The odds of significant results in studies with suboptimal analyses were higher than that in studies with optimal longitudinal analyses (odds ratio: 3.48, 95% confidence interval: 1.62, 7.46, P = 0.001). For the studies with optimal analysis, the most frequent test was repeated-measure analysis of variance (RM-ANOVA). The reporting of the statistical analysis section was suboptimal in the majority of the trials. Conclusion Most longitudinal orthodontic trials are not analysed using optimal statistical approaches. Inferences and interpretation of their results are likely to be compromised.

Wybrane parametry jakości ucisku i relaksacji klatki piersiowej wykonywanej przez personel pielęgniarski w ramach pozaszpitalnego nagłego zatrzymania krążenia ? badanie pilotażowe

2018 ◽  
Vol 21 (4) ◽  
Author(s):  
Paweł Więch ◽  
Marek Muster ◽  
Dariusz Bazaliński ◽  
Grzegorz Kucaba ◽  
Izabela Sałacińska ◽  
...  
Keyword(s):  
Health Care ◽  
Primary Health Care ◽  
Statistical Analysis ◽  
Discharge Rate ◽  
Statistical Significance ◽  
Sudden Cardiac Arrest ◽  
Initial Examination ◽  
Relaxation Parameters ◽  
Primary Health

Introduction. Sudden cardiac arrest (SCA) in out-of-hospital conditions is a frequent condition of immediate life-emergency of cardiological background. The survival and discharge rate in SCA patients treated by medical services is still at a low level. Aim. The aim of the study was to analyze selected parameters of the quality of chest compressions and relaxation performed by nursing staff as part of out-of-hospital SCA. Material and methods. The study covered a group of 48 nurses working in primary health care in branches of conservative (PRE/C = 24 people, mean age 33.04 ± 9.20) and surgery profile (PRE/I = 24 people, average age 31.88 ± 9.97), participating in the research project of the Center for Medical and Natural Sciences Research and Innovation, University of Rzeszów in Rzeszów. Two months after the initial examination and intervention, the test was repeated. The assessment of selected compression and relaxation parameters was performed using the True CPR Resuscitation Assistant. The statistical analysis of the collected material was carried out with the SPSS Statistics 20 software. The statistical analysis used the analysis of variables using parametric and non-parametric tests. The statistical significance was assumed at p < 0.05. Results. Initially, a high percentage of the effectiveness of the most important compression and relaxation parameters of the chest was obtained during 2-minute out-of-hospital cardiopulmonary resuscitation with no statistically significant differences between the two groups (PRE/C: 51 mm depth, 83.92% relaxation, frequency 115.46 vs. PRE/I: depth: 47.58 mm, relaxation: 92.54, frequency: 109.96, p < 0.05). After two months, similar parametric values were observed with no statistical significance (p < 0.05). Conclusions. The initial high quality of compressions and relaxation was found in nurses participating in the simulated out-of-hospital SCA, while there were no significant differences between primary health care nurses working at conservative departments and nurses from surgical ones. After a two-month interval from the initial examination and training, high CPR effectiveness was observed based on the guidelines of the European Resuscitation Council from 2015.

The use of multifunctional statistical criteria in the development of technological aspects of self-design of students’ educational and professional activities

2020 ◽  
pp. 23-30
Author(s):  
Tatyana A. Erina ◽  
Natalya N. Motkina
Keyword(s):  
Statistical Significance ◽  
Statistical Processing ◽  
Automated System ◽  
Statistical Hypothesis ◽  
Self Management ◽  
Professional Activities ◽  
Selection Of ◽  
Angular Transformation ◽  
Statistical Criteria

Researchers in the humanities almost always have to deal with the problem of statistical processing of results and their interpretation. This is a rather laborious and painstaking work, which can be greatly simplified through the use of multifunctional statistical criteria. Within the framework of the study related to the problem of self-design of educational and professional ac-tivities of students, the analysis of the effectiveness of the introduction of technological elements using multifunctional criteria was carried out: φ* criterion – Fisher’s angular transformation and binomial criterion m. The statistical significance of the results of the introduction at a certain stage of the technology of the workshop is revealed, which makes it possible to study and apply the ele-ments of self-management in the educational and professional activities of students. For promising purposes, it is proposed to create an automated system that implements the selection of the appropriate criterion for the problem to be solved and the verification of the statistical hypothesis put forward by the researcher.

scholarly journals Reducing Mobile Air Conditioner (MAC) Power Consumption Using Active Cabin-Air-Recirculation in A Plug-In Hybrid Electric Vehicle (PHEV)

2018 ◽  
Vol 9 (4) ◽  
pp. 51 ◽  
Author(s):  
Chengguo Li ◽  
Eli Brewer ◽  
Liem Pham ◽  
Heejung Jung
Keyword(s):  
Air Quality ◽  
Power Consumption ◽  
Electric Vehicle ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Driving Cycle ◽  
Total Power ◽  
Air Conditioner ◽  
Hybrid Electric ◽  
Cabin Air Quality

Air conditioner power consumption accounts for a large fraction of the total power used by hybrid and electric vehicles. This study examined the effects of three different cabin air ventilation settings on mobile air conditioner (MAC) power consumption, such as fresh mode with air conditioner on (ACF), fresh mode with air conditioner off (ACO), and air recirculation mode with air conditioner on (ACR). Tests were carried out for both indoor chassis dynamometer and on-road tests using a 2012 Toyota Prius plug-in hybrid electric vehicle. Real-time power consumption and fuel economy were calculated from On-Board Diagnostic-II (OBD-II) data and compared with results from the carbon balance method. MAC consumed 28.4% of the total vehicle power in ACR mode when tested with the Supplemental Federal Test Procedure (SFTP) SC03 driving cycle on the dynamometer, which was 6.1% less than in ACF mode. On the other hand, ACR and ACF mode did not show significant differences for the less aggressive on-road tests. This is likely due to the significantly lower driving loads experienced in the local driving route compared to the SC03 driving cycle. On-road and SC03 test results suggested that more aggressive driving tends to magnify the effects of the vehicle HVAC (heating, ventilation, and air conditioning) system settings. ACR conditions improved relative fuel economy (or vehicle energy efficiency) to that of ACO conditions by ~20% and ~8% compared to ACF conditions for SC03 and on-road tests, respectively. Furthermore, vehicle cabin air quality was measured and analyzed for the on-road tests. ACR conditions significantly reduced in-cabin particle concentrations, in terms of aerosol diffusion charger signal, by 92% compared to outside ambient conditions. These results indicate that cabin air recirculation is a promising method to improve vehicle fuel economy and improve cabin air quality.

The Study of Fuel-Saving Technology of GSI

2014 ◽  
Vol 1070-1072 ◽  
pp. 392-397
Author(s):  
Jun Hui Xu ◽  
Ming Qiu Gao ◽  
Ji Qiang Gao ◽  
Xiang Bao
Keyword(s):  
Fuel Consumption ◽  
Fuel Economy ◽  
Rolling Resistance ◽  
Fuel Saving ◽  
Pressure Monitoring ◽  
Tire Pressure ◽  
Engine Efficiency ◽  
Tire Pressure Monitoring System ◽  
The Eu

In the background of the main technologies of fuel economy in automobiles developed to a certain stage, it is necessary to reduce fuel consumption and increase the engine efficiency by developing other auxiliary technologies such as improving the ratio of pure energy drive, low rolling resistance tires, tire pressure monitoring system and gear shift indicators (GSI). This article introduces the principle of GSI, analyses how GSI works in improving engine efficiency, and then evaluates the method for determination of the relative saving rate of fuel consumption, which method was introduced in the EU regulation EC No. 65/2012.

scholarly journals Three Evidence Based Methods to Compensate for a Lack of Subject Background when Ordering Chemistry Monographs

2008 ◽  
Vol 3 (3) ◽  
pp. 3
Author(s):  
Robert A. Wright
Keyword(s):  
Statistical Analysis ◽  
Statistical Significance ◽  
Evidence Base ◽  
Circulation Rate ◽  
Evidence Based ◽  
Practical Application ◽  
Present Evidence ◽  
Library System ◽  
Over Time ◽  
Selection Of

Objective – The aim of this article is to present evidence based methods for the selection of chemistry monographs, particularly for librarians lacking a background in chemistry. These methods will be described in detail, their practical application illustrated, and their efficacy tested by analyzing circulation data. Methods – Two hundred and ninety-five chemistry monographs were selected between 2005 and 2007 using rigorously-applied evidence based methods involving the Library's integrated library system (ILS), Google, and SciFinder Scholar. The average circulation rate of this group of monographs was compared to the average circulation rate of 254 chemistry monographs selected between 2002 and 2004 when the methods were not used or were in an incomplete state of development. Results – Circulations/month were on average 9% greater in the cohort of monographs selected with the rigorously-applied evidence based methods. Further statistical analysis, however, finds that this result can not be attributed to the different application of these methods. Conclusion – The methods discussed in this article appear to provide an evidence base for the selection of chemistry monographs, but their application does not change circulation rates in a statistically significant way. Further research is needed to determine if this lack of statistical significance is real or a product of the organic development and application of these methods over time, making definitive comparisons difficult.

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