• Title/Summary/Keyword: Qatar

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Prevalence of Oral Pre-malignant Lesions and its Risk Factors in an Indian Subcontinent Low Income Migrant Group in Qatar

  • Kavarodi, Abdul Majeed;Thomas, Mary;Kannampilly, Johnny
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.10
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    • pp.4325-4329
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    • 2014
  • Background: The expatriate population in Qatar largely comprises workers from the Indian subcontinent which has a very high rate of oral malignancy. Social and cultural habits and as well premalignant risk factors in this population remain prevalent even after migration. Materials and Methods: This cross sectional study assessed the prevalence of risk factors and occurrence of oral precancerous lesions in a low income group expatriate community from the Indian subcontinent residing in Qatar. Results: Among the 3,946 participants screened for oral premalignant lesions 24.3% (958) were smokers and 4.3 % (169) were pan chewers while 6.3% (248) were users of both smoked and smokeless forms of tobacco. Significantly higher proportion of industrial laborers (49.9%) followed by drivers (24.1%) were found to be smokers (p=0.001). The prevalence of white lesions was higher in smokers versus non-smokers 3.5% versus 2.3% (p=0.111), however this difference was statistically non-significant. Red and white lesions were highly significant (i.e. 1.2 % and 10.9% respectively) in the subjects with pan chewing and smoking habits (p=0.001). A significant proportion (8.9%) of the subjects with pan chewing habit showed evidence of oral precancerous lesions (p=0.001). Conclusions: Even though smoking and pan chewing were two significant risk factors detected in this population, their prevalence and occurrence of premalignant lesions are low as compared to the studies conducted in their home countries.

Analyzing exact nonlinear forced vibrations of two-phase magneto-electro-elastic nanobeams under an elliptic-type force

  • Mirjavadi, Seyed Sajad;Nikookar, Mohammad;Mollaee, Saeed;Forsat, Masoud;Barati, Mohammad Reza;Hamouda, A.M.S.
    • Advances in nano research
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    • v.9 no.1
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    • pp.47-58
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    • 2020
  • The present paper deals with analyzing nonlinear forced vibrational behaviors of nonlocal multi-phase piezo-magnetic beam rested on elastic substrate and subjected to an excitation of elliptic type. The applied elliptic force may be presented as a Fourier series expansion of Jacobi elliptic functions. The considered multi-phase smart material is based on a composition of piezoelectric and magnetic constituents with desirable percentages. Additionally, the equilibrium equations of nanobeam with piezo-magnetic properties are derived utilizing Hamilton's principle and von-Kármán geometric nonlinearity. Then, an exact solution based on Jacobi elliptic functions has been provided to obtain nonlinear vibrational frequencies. It is found that nonlinear vibrational behaviors of the nanobeam are dependent on the magnitudes of induced electrical voltages, magnetic field intensity, elliptic modulus, force magnitude and elastic substrate parameters.

Secure and Robust Clustering for Quantized Target Tracking in Wireless Sensor Networks

  • Mansouri, Majdi;Khoukhi, Lyes;Nounou, Hazem;Nounou, Mohamed
    • Journal of Communications and Networks
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    • v.15 no.2
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    • pp.164-172
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    • 2013
  • We consider the problem of secure and robust clustering for quantized target tracking in wireless sensor networks (WSN) where the observed system is assumed to evolve according to a probabilistic state space model. We propose a new method for jointly activating the best group of candidate sensors that participate in data aggregation, detecting the malicious sensors and estimating the target position. Firstly, we select the appropriate group in order to balance the energy dissipation and to provide the required data of the target in the WSN. This selection is also based on the transmission power between a sensor node and a cluster head. Secondly, we detect the malicious sensor nodes based on the information relevance of their measurements. Then, we estimate the target position using quantized variational filtering (QVF) algorithm. The selection of the candidate sensors group is based on multi-criteria function, which is computed by using the predicted target position provided by the QVF algorithm, while the malicious sensor nodes detection is based on Kullback-Leibler distance between the current target position distribution and the predicted sensor observation. The performance of the proposed method is validated by simulation results in target tracking for WSN.

Fundamental Output Voltage Enhancement of Half-Bridge Voltage Source Inverter with Low DC-link Capacitance

  • Elserougi, Ahmed;Massoud, Ahmed;Ahmed, Shehab
    • Journal of Power Electronics
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    • v.18 no.1
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    • pp.116-128
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    • 2018
  • Conventionally, in order to reduce the ac components of the dc-link capacitors of the two-level Half-Bridge Voltage Source Inverter (HB-VSI), high dc-link capacitances are required. This necessitates the employment of short-lifetime and bulky electrolytic capacitors. In this paper, an analysis for the performance of low dc-link capacitances-based HB-VSI is presented to elucidate its ability to generate an enhanced fundamental output voltage magnitude without increasing the voltage rating of the involved switches. This feature is constrained by the load displacement factor. The introduced enhancement is due to the ac components of the capacitors' voltages. The presented approach can be employed for multi-phase systems through using multi single-phase HB-VSI(s). Mathematical analysis of the proposed approach is presented in this paper. To ensure a successful operation of the proposed approach, a closed loop current controller is examined. An expression for the critical dc-link capacitance, which is the lowest dc-link capacitance that can be employed for unipolar capacitors' voltages, is derived. Finally, simulation and experimental results are presented to validate the proposed claims.

A Buck-Boost Converter-Based Bipolar Pulse Generator

  • Elserougi, Ahmed A.;Massoud, Ahmed M.;Ahmed, Shehab
    • Journal of Power Electronics
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    • v.17 no.6
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    • pp.1422-1432
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    • 2017
  • This paper presents a buck-boost converter-based bipolar pulse generator, which is able to generate bipolar exponential pulses across a resistive load. The concept of the proposed approach depends on operating the involved buck-boost converters in discontinuous current conduction mode with high-voltage gain and enhanced efficiency. A full design of the pulse generator and its passive components is presented to ensure generating the pulses with the desired specifications (rise time, pulse width, and pulse magnitude) for a given load resistance and input dc voltage. In case of moderate pulsed output voltages (i.e. few of kV), one module of the presented bipolar generator can be employed. While in case of high-voltage pulsed output, multi-module version can be employed, where each module is fed from an isolated dc source and their outputs are connected in series. Simulation models for the proposed approach are built to elucidate their performance in case of one-module as well as multi-module based generator. Finally, a scaled-down prototype for one-module of buck-boost converter-based bipolar pulse generator is implemented to validate the proposed concept.

Will You Buy It Now?: Predicting Passengers that Purchase Premium Promotions Using the PAX Model

  • Al Emadi, Noora;Thirumuruganathan, Saravanan;Robillos, Dianne Ramirez;Jansen, Bernard Jim
    • Journal of Smart Tourism
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    • v.1 no.1
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    • pp.53-64
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    • 2021
  • Upselling is often a critical factor in revenue generation for businesses in the tourism and travel industry. Utilizing passenger data from a major international airline company, we develop the PAX (Passenger, Airline, eXternal) model to predict passengers that are most likely to accept an upgrade offer from economy to premium. Formulating the problem as an extremely unbalanced, cost-sensitive, supervised binary classification, we predict if a customer will take an upgrade offer. We use a feature vector created from the historical data of 3 million passenger records from 2017 to 2019, in which passengers received approximately 635,000 upgrade offers worth more than $422,000,000 U.S. dollars. The model has an F1-score of 0.75, outperforming the airline's current rule-based approach. Findings have several practical applications, including identifying promising customers for upselling and minimizing the number of indiscriminate emails sent to customers. Accurately identifying the few customers who will react positively to upgrade offers is of paramount importance given the airline 'industry's razor-thin margins. Research results have significant real-world impacts because there is the potential to improve targeted upselling to customers in the airline and related industries.

Does Ramzan Effect the Returns and Volatility? Evidence from GCC Share Market

  • ABRO, Asif Ali;UL MUSTAFA, Ahmed Raza;ALI, Mumtaz;NAYYAR, Youaab
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.7
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    • pp.11-19
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    • 2021
  • The study aims to investigate the impact of seasonality in Gulf Cooperation Council (GCC) countries' share market during the month of Ramadan. It helps in finding the opportunities for stock market investors to earn abnormal (returns) gain by investing during Ramadan in GCC stock markets. This study uses stock returns data of GCC countries (Saudi Arabia, Bahrain, Qatar, Kuwait, Dubai, and UAE) from January 2004 to November 2019. Stock prices indexes of GCC stock markets have been obtained from Datastream. The ARCH-GARCH model is used to study the impact of the Ramadan month on the return and volatility of the stock market in GCC countries. The results showed that the Ramadan month has a significant impact on share market prices in Saudi Arabia and the United Arab Emirates. However, Ramadan has an insignificant impact on share market prices in Bahrain and Oman. The study found no evidence of serial correlational between residuals in Kuwait; meaning that stock return was not dependent on the prior stock returns in Kuwait, therefore, we cannot go for forecasting. The ARCH-LM test statistic for Qatar does not fulfill the requirement of a good regression model; therefore, we cannot go for forecasting or testing the hypothesis of Qatar.

Microstructure and mechanical behavior of cementitious composites with multi-scale additives

  • Irshidat, Mohammad R.;Al-Nuaimi, Nasser;Rabie, Mohamed
    • Advances in concrete construction
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    • v.11 no.2
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    • pp.163-171
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    • 2021
  • This paper studies the effect of using multi-scale reinforcement additives on mechanical strengths, damage performance, microstructure, and water absorption of cementitious composites. Small dosages of carbon nanotubes (CNTs) or polypropylene (PP) microfibers; 0.05%, 0.1%, and 0.2% by weight of cement; were added either separately or simultaneously into cement mortar. The experimental results show the ability of these additives to enhance the mechanical behavior of the mortar. The best improvement in compressive and flexural strengths of cement mortar reaches 28% in the case of adding a combination of 0.1% CNTs and 0.2% PP fibers for compression, and a combination of 0.2% CNTs and 0.2% PP fibers for flexure. Adding CNTs does not change the brittle mode of failure of plain mortar whereas the presence of PP fibers changes it into ductile failure and clearly enhances the fracture energy of the specimens. Scanning electron microscopic (SEM) images of the fracture surfaces highlights the role of CNTs in improving the adhesion between the PP fibers and the hydration products and thus enhance the ability of the fibers to mitigate cracks propagation and to enhance the mechanical performance of the mortar.