This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hailing. According to the final model, the attitude of the commuters towards the speed of ride-hailing over hailing regular taxis was the most important and presented in all probability conditions. Several related studies also identified ride-hailing speed as one of the top reasons for using this travel option. The findings of this study imply that commuters still compare the ride-hailing services with the traditional taxis in Kuala Lumpur, especially in terms of complementarity to other modes, ease of payment, ease of access, and speed. It is critical to have a sustainable strategy for keeping commuters’ satisfaction at the highest level because if the ride-hailing services cannot meet the commuters’ expectations, they may switch back to conventional transport options.
Periodontitis is a chronic inflammation affecting the tooth-supporting periodontal tissues. It is diagnosed by measuring periodontal parameters. However, documenting this data takes effort and may not discover early periodontitis. Biomarkers may help diagnose and assess periodontitis. This study aimed to evaluate the potential diagnostic of the salivary tumor necrosis factor-α (TNF-α) and receptor-activator of nuclear factor ĸ-B-ligand (RANKL) in distinguishing between periodontitis and healthy periodontium.
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The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
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The prevalence of gastrointestinal symptoms of COVID-19 is variable with different types of presentations. Some of them many present with manifestations mimicking surgical emergencies. Yet, the pathophysiology of acute abdomen in the context of COVID-19 remains unclear. We present a case of a previously healthy child who presented with acute appendicitis with multisystemic inflammatory syndrome. We also highlight the necessity of considering the gastrointestinal symptoms of COVID-19 infection in pediatric patients in order to avoid misdiagnosis and further complications. |
Background: University dental students perceived a higher level of stress prior to the final exam associated with raised salivary cortisol levels which could be considered as a useful noninvasive biomarker for measuring acute stress. Using a Helkimo anamnestic and clinical dysfunction scoring for temporomandibular disorders can give a better insight about the association of this marker and temporomandibular joint disorders. The aim of this study was to evaluation level of salivary cortisol in stressor students with temporomandibular disorder and the relation between this marker in relation to temporomandibular disorder severity. This might give a better understanding to the role of psychological stress as an etiological factor for developin
... Show MoreThe objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <
... Show MoreThe continued acceleration in the business environment has led to the need for organizations great attention to quality applied in organizations to meet the needs of customers and stay in the market for as long as possible.
Search launched from the underlying problem is the presence of concentrations of defects and waste plaguing the company and to achieve the goal of the study detects the level of quality applied in the factory vessels and reservoirs of the General Company for Heavy Engineering Equipment, As well as calculate wastage rates occurring in the production process and find a relationship between the level of quality and ratios defective in each type of waste, it has been used quantitative meas
... Show MoreThe ground state charge, neutron, proton and matter densities, the associated nuclear radii and the binding energy per nucleon of 8B, 17Ne, 23Al and 27P halo nuclei have been investigated using the Skyrme–Hartree–Fock (SHF) model with the new SKxs25 parameters. According to the calculated results, it is found that the SHF model with these Skyrme parameters provides a good description on the nuclear structure of above proton-rich halo nuclei. The elastic charge form factors of 8B and 17Ne halo nuclei and those of their stable isotopes 10B and 20Ne are calculated using plane-wave Born approximation with the charge density distributions obtained by SHF model to investigate the effect of the extended charge distributions of proton-rich nucl
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