In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with 97.50 (...) % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)

Recently, the sustainability concept has become a prominent topic in the tourism and hospitality field, particularly after the COVID-19 pandemic. In response, this study undertook a systematic review of 176 articles to identify the research trends in sustainability within the tourism and hospitality area in the post-COVID-19 era. Using thematic analysis, this study identified five key research trends. The findings offer a thorough overview of the changing research landscape regarding sustainability in the field of tourism and hospitality. Consequently, the study (...) provided recommendations for practitioners and researchers aiming to promote sustainability in the industry. (shrink)

Objective: Patients' satisfaction is one of the most important goals in complete denture therapy, and there are many factors influencing this parameter. This study aimed to determine patient satisfaction with conventional removable complete denture made by clinical year students at the Faculty of Dentistry, Al Azhar University - Gaza. Methods: A sample of 85 patient who had conventional removable complete denture made by clinical year students at the Faculty of Dentistry Al Azhar University - Gaza filled a questionnaire two months (...) after denture insertion. The questionnaire involving four sections including personal information, history, denture evaluation in aspects of mastication, speech, aesthetics and retention, and patient comfort. Results: Of the 85 patient studied, 81% were males, and the mean age was 60.3 years SD+-9.64. The majority (n= 67, 79 %) lost their teeth because of bad oral hygiene. The overall satisfaction level was (92.1%), and patients were more satisfied with their upper denture. A significant association was found between the patient satisfaction and prior denture use experience (p=0.013). No significant correlation was established between the patient satisfaction and their gender (p=0.188), age group (p=0.640) and employment status (p=0.667).Conclusion: The patients have shown a high level of overall satisfaction. A significant association was found between the overall satisfaction level of patients and prior denture use experience. No statistically significant association was observed between the overall satisfaction level of patients and with each of age group, employment status and gender. (shrink)

In resource-limited settings where healthcare services are limited and poverty is common, it is difficult to ethically conduct clinical research without providing patient-care. Therefore, integration of patient-care with clinical research appears as an attractive way of conducting research while providing patient-care. In this article, we discuss the ethical implications of such approach with perspectives from Papua New Guinea.

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with 97.50 (...) % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with 97.50 (...) % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)