 Subjects -> SCIENCES: COMPREHENSIVE WORKS (Total: 374 journals)
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- Processing and Characterization of UAE Clay Ceramic Membranes for Water
Treatment Applications-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Abdelrahman Khalil Abdelrazek Khalil, Abdelaziz Elgamouz, Muataz Ali Atieh, Abdallah Shanableh, Tahar Laoui
The scarcity of drinking water is currently a critical issue in many parts of the world. Providing clean/urgent longer limited to natural sources. Wastewater treatment has become an urgent necessity in many countries, particularly in the Middle East and North African regions characterized by a desert climate. Hence, the development of effective methods for wastewater treatment is vital to overcome this water shortage. The present study attempts to explore the use of local clay from the United Arab Emirates (UAE) to prepare porous ceramic membranes (flat disk shape) for the purpose of removing toxic heavy metals from contaminated water. Two types of ceramic membranes were prepared by powder metallurgy method; the first type was prepared by uniaxial compression of the clay powder with particle size ≤ 250 μm, followed by sintering. The second type of membrane was composed of an activated carbon/clay powder mixture at different ratios (0.5%, 3% w/w). The activated carbon was used as an agent to form porosity in the plain clay membrane. The activated carbon was found to affect the final characteristics of the flat disk membranes sintered at 1000°C. 3% w/w activated carbon/clay powder was found to induce 19% porosity in the flat disc. The flat disc membranes were also characterized by X-ray diffraction, and scanning electron microscopy, X-ray fluorescence. The plain clay and 3% w/w activated carbon membranes were tested for their efficiency for water permeation. The results proved that the UAE clay could be considered as a promising material for the fabrication of ceramic membranes for prospective use in the removal of water contaminated with heavy metals.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Processing of Carbon Nanofibers with Graphene Oxide and Carbon Nanotubes
Additives and its Application in CDI Electrode Material-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Farah Anwar Abumadi, Moumena Koujan, Tahar Laoui, Muataz Ali Atieh, Khalil Abdelrazek Khalil
Water shortage has been a severe problem affecting the globe for the past decade. Therefore, appropriate and efficient technologies should be implemented to tackle the water shortage dilemma and to acquire clean water. Several desalination techniques are implemented across the world; among them is capacitive deionization (CDI). CDI is an energy-efficient and cost-effective electrochemical process employed for extracting charged ions from aqueous solutions using a pair of electrodes. Electrode materials strongly influence the CDI's desalination efficiency and conductivity. The CDI electrodes are composed of carbon materials such as activated carbon, carbon aerogel, carbon nanofibers, and porous carbon. However, in this study, carbon nanofibers that possess several advantages and properties over the existing materials have been examined to be used as CDI electrode material due to their high electrical conductivity, large surface area, dimensional stability, and low production cost. Furthermore, different conductive additives could be added to the carbon nanofibers to increase the electrical conductivity and capacitance. In particular, this paper discusses the effect of adding graphene oxide (GO) and carbon nanotubes (CNT) as additives to carbon nanofibers.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Capacitive Deionization Water Desalination Technology, Process
Optimization and Cost Analysis - A Review-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Farah Anwar Abumadi, Moumena Koujan, Tahar Laoui, Muataz Ali Atieh, Khalil Abdelrazek Khalil
Capacitive deionization is an emerging electrochemical technology employed in water desalination applications. Multiple water desalination technologies include reverse osmosis, multi-stage flash, humidification-dehumidification, and nanofiltration. Capacitive deionization is appreciably increased the desalination efficiency compared to other technologies while promising energy-efficient and cost-effective operation. In the CDI system, the charged ions are extracted from feedwater by applying an electrical voltage across electrodes, in which the charged ions are attracted to the oppositely charged electrodes. This paper demonstrates the concept of capacitive deionization (CDI), the components of CDI cell, working principal, and performance metrics for the CDI system. Furthermore, the paper reviews the state of technology of the CDI cell and the development of the system since the mid-1960, including the concepts of membrane and flow electrode CDI. Finally, a cost analysis framework of CDI, MCDI, and FCDI is demonstrated based on the Levelized cost of water.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Prediction of Concrete Modulus of Elasticity Using Deep Learning
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Emran Alotaibi, Mohamad Alhalabi, Omar Mostafa, Samer Barakat
Modulus of Elasticity (Ec’) is a key parameter in structural engineering concrete designs. In concrete as a composite material, Ec’ is a function of compressive strength and the proportions of components in the concrete matrix (percentages of aggregates and cement). The inaccuracy and dispersity in estimating Ec’ from models provided by the existing codes of practice strongly affect the performance and design of the concrete structures. In this study, a dataset of 189 experimental concrete compressive strength results were collected from the available literature. The data set includes curing time (in days) for the concrete specimens, concrete density, experimental compressive strength (fc’), experimental Ec’ and several additives (e.g., slag, gypsum…etc.) with a total of 13 variables. Deep artificial neural networks (DANN) were used to model and analyze the effects of these variables on Ec’. A grid search over 2 hidden layers of DANNs was conducted to compute the best performed DANN. A total of 49 DANN models were developed in this study to predict concrete Ec’. The best performed DANN had a coefficient of determination (R2) of 0.81 and was selected for further analysis. Importance scoring was performed on the best DANN and results revealed that compressive strength had the highest importance score followed by water/cement ratio (w/c). Interestingly, the specimen sizes and curing days had the 6th and 8th scoring respectively from the 13 investigated variables. Ground pumice had the highest scoring compared to other additives. Sensitivity analyses were conducted revealing that at low specimen sizes of 10 mm, the Ec’ may vary by ~50%, while at higher size (150 mm), the Ec’ had less scatter and more reliable values.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Termite as Biomimicry Solution for Enhancing Building Envelope: A
Comparative Model Case Study in the UAE-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Khalid AlShuhail, Abdelsalam Aldawoud, Syarif Junaidi
The building envelope is considered the boundary in which a building interacts with the surrounding environment. This paper aims to enhance building envelope design by biomimicry of the termite mound shape for reducing the energy demand as well as maintaining comfortable indoor temperatures. In this paper, two models with the same internal dimensions, cross-sectional area, and block material were constructed. The first model is a regular block model (RB) that represents a typical house construction. The second model (TM) development including the form and the envelope design is inspired by the termite mounds. The building model used the same principles of ventilation and thermoregulation in the same way as termite responds to extremely hot and humid conditions. Infrared thermography (IR) was carried out to measure the thermal performance of building envelopes throughout a full year. The influence of the termite model on the thermal properties such as the Decrement Factor (DF), Temperature Difference Ratio (TDR), and Time lag (Tlg) was investigated. The results suggest that the termite model (TM) can accumulate time lag for up to three hours on average. Investigation results indicated that the termite model improved for thermal repletion, unlike the regular model. The termite model absorbed more heat while the regular block model (RB) was thermally reflective.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- 3D Finite Element Modeling of Suction Caissons Used as Foundations for
Offshore Wind Turbines in Clayey Soils-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Omar Mostafa, Mohamed G. Arab, Maher Omar
In this study, three-dimensional finite element modeling is utilized to simulate suction caisson foundations used for offshore wind turbines. The behavior of suction caissons in normally consolidated clayey soil subjected to lateral loading is investigated. A numerical model is calibrated and validated using experimental laboratory physical model. A parametric study is conducted to evaluate the effect of suction caisson diameter (D) and the ratio of skirt length (L) to caisson diameter (L/D) on the load-deflection response of a full-scale suction caisson. Several caisson diameters and length to diameter ratios were considered. The results of numerical analysis modeling demonstrated that the caisson ultimate load capacity and displacement are significantly affected by caisson geometry. Generally, increasing both the caisson diameter and length has substantially increased both caisson’s ultimate load capacity and displacement at failure. However, the increase in ultimate capacity and displacement reaches a threshold after which the increase in these values is less pronounced as D and L/D are further increased. Additionally, the effect of caisson geometry on relative stiffness is investigated. The relative stiffness of the suction caisson was found to increase proportionally with the increase of both diameter and length of the modeled caissons.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Sustainable Performance Measurement: An Application to the U.S. Car
Industry-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Syed Faisal Shah, Panagiotis D. Zervopoulos, Mohamed Aboelmaged
This study measures the sustainable performance of ten car manufacturers operating in the U.S. We took into account three dimensions of sustainability: (a) economic, (b) environmental, and (c) social. Our methodology drew on the generalized directional distance function data envelopment analysis in conjunction with the multi-parametric method for bias correction of efficiency estimators. The combination of the two methods reduced the bias of efficiency estimators, which was sourced from the dimensionality of the production set and the sample size. Our analysis revealed that Chrysler-Fiat, GM, and Ford have the worst sustainable performance among firms under review over the years 2014–2018.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- The Effect of Mergers and Acquisitions on Efficiency: Evidence from the
Pharmaceutical Industry-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Sheikha Ishaq Abdallah Gholoom, Panagiotis D. Zervopoulos
This study emphasizes the assessment of efficiency and the degree of operating efficiency of mergers and acquisitions in the pharmaceutical industry worldwide. This industry encounters various challenges such as expiring patents, the rise of genetics pharmaceuticals, the entrance of biotechnology companies in the pharmaceutical market, the increasing research and development expenses, government regulations of the pharmaceutical industry, distribution channels, and drug prices. All these challenges result in an intensely competitive environment in which pharmaceuticals suffering from shortcomings (e.g., operational and/or financial inefficiencies) are not easy to catch up with the competition. Mergers and acquisitions are major activities to overcome shortcomings and achieve growth. Mergers and acquisitions have been widely used in the pharmaceutical industry for many years and are expected to accelerate. The objective of this work is to identify whether mergers and acquisitions between pharmaceutical companies can be successful and to highlight the most favourable consolidations. The assessment of mergers and acquisitions is realized through conventional and stochastic data envelopment analysis approaches. The empirical analysis draws on a sample of 371 pharmaceutical companies. The original sample was extended by 870 possible combinations between firms. Our empirical analysis reveals a positive impact of mergers and acquisitions on the efficiency of pharmaceutical companies.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Performance Measurement of Airports Incorporating Employees’ and
Customers’ Perspectives-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Ebtisam Abdallah Alhammadi, Panagiotis D. Zervopoulos
The purpose of this study was to explore airport performance and its impact on customers’ and employees’ satisfaction. This study applied a slacks-based measure network DEA (NSBM) model to evaluate the performance of sixteen international airports. Ten variables were incorporated in the two-stage NSBM model. Specifically, five inputs (i.e., number of employees, number of terminals, number of runways, airport area, and capacity) and three outputs (i.e., number of passengers, number of aircraft movements, and cargo) were used for the first stage. In the second stage, all outputs from the previous stage served as inputs (linking activities), while the outputs of this stage are the perceptions of employees and customers about the work environment and the quality of outputs produced by the first stage, respectively. Drawing on our empirical analysis findings, smaller airports perform better than larger counterparts. In particular, the airports that achieved satisfactory employees’ and customers’ satisfaction scores were those operating a comparatively high number of small-size terminals and have a relatively small number of employees.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Predicting Employee Voice Behavior: Exploring the Roles of Empowering
Leadership, LMX and the Mediation Effect of Psychological Empowerment-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Safeya Almazrouei, Shaker Bani-Melhem
When employees consciously suppress important information, suggestions or concerns from their managers, negative implications for organizational performance can emerge. Some studies suggested that employees often choose to remain silent when faced with the choice of whether or not to raise an issue. Therefore, the main objective of this research is to examine the factors that impact employee voice behavior (VB). The research theorizes that empowering leadership and Leader-Member Exchange (LMX) significantly and positively impacts employee voice behavior in UAE public sector (N=146). Moreover, this study broadens the previous research on the empowering leadership, LMX and employee voice relationship by introducing employee psychological empowerment as a mediator. The data was gathered using the online survey. The results of the statistical analysis using structural equation modeling with Smart-Partial Least Squares (PLS).3 showed that empowering leadership directly and indirectly (through psychological empowerment) impact on employee voice behavior. Surprisingly, the results presented no significant relationships between LMX and voice behavior. However, the relationships only exist through the psychological empowerment (fully mediate). Implications of the study model for management or human resource management as well as for future research are discussed. Keywords: Empowering leadership, Leader-member exchange, psychological empowerment, employee voice behavior
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Religiosity, Brand Image, and Behavioral Intention: An Investigation for
Halal Restaurant-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Sulaiman En, Mohamed Battour, Ririn Tri Ratnasari
Aim - This study aims to reveal the effect of religiosity and brand image on the behavioral intention with trust and satisfaction as mediating variables at the Larazeta halal restaurant. Design/Method/Approach - Data were collected through a questionnaire with a total sample of 100 customers of the Larazeta halal restaurant. The respondents were customers of the Larazeta halal restaurant who had visited the restaurant that has many branches in Indonesia at least once. The sampling technique used is convenience sampling. This study used a quantitative approach with the Structural Equation Modelling-Partial Least Squares Analysis. The exogenous variables in this study include religiosity and brand image, the mediating variables consisted of trust and satisfaction, while the endogenous variable was the behavioral intention. Results - The results indicate that the variables of religiosity and brand image had a significant effect on the behavioral intention, trust, and satisfaction variables of Larazeta halal restaurant customers. Practical Implications – This study provides an understanding of how religiosity, brand image, trust, and satisfaction can influence the behavioral intention of halal food consumers. Originality– There is a little research investigating the relationship between religiosity and marketing in Islam in Indonesia with unique demographic conditions. Research gaps are found in the previous studies, namely the broad scope of research so that they were not effective in explaining areas that have unique demographic characteristics. Therefore, for the first time, the present study aims to analyze specifically the relationship of religiosity and brand image on behavioral intention, with trust and satisfaction as mediating variables in discussing halal food as a healthy lifestyle in Indonesia. Keywords : Healthy Lifestyle, Religiosity, Brand Image, Trust, Satisfaction, Behavioral Intention, Halal Food
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Determinants of Employee Creativity: The Mediating Role of Employee
Happiness-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Khawla Abdel Aziz Al Serkal
Purpose - The current study integrated number of research fields to develop and test a model on the determinants of employees’ happiness and creativity. Hypothesizing that quality of work life, perceived training intensity and job security affect employees’ happiness and creativity in in the United Arab Emirates (UAE) Public sector. Design - The study uses survey data from 120 employees from public sector companies in United Arab Emirates (UAE). Based on an extensive literature review, eight hypotheses were formulated and explored. These were tested through multiple regression analysis using smart PLS Partial Least Squares. Findings – Work life balance, perceived training intensity and job security showed no significant relationship. However, the relationships only exist through the feeling of happiness. Research limitation – The sample is from a single sector (public) in a single country. Future research would benefit from examining the above relationships in privet sector in the UAE. It could also explore the validity of these relationships in the public sector of other countries in the Middle East and Gulf regions. Originality/value –few studies have adequately examined their determinants particularly in UAE. Although research examining the employee creativity in public sector is limited, it is clear that public sector stands to gain from creative employees because employee creativity and innovation will contribute to the attainment of organizational goals. KEY WORDS-Employee creativity, Employee happiness, Job security, Training, Work-life balance, Human resources, UAE, Public sector Paper Type –Research paper
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- A Methodology for Safety Inspection Analysis Based on Risk Insight and
Defense-in-Depth Concept for APR1400 Nuclear Power Plant-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Saud Bin Khadim, Muhammad Zubair
To confirm the safety of Nuclear Power Plants (NPP) several regulatory safety inspections based on defense in depth criteria were conducted. However, once the plant is put into service the regulatory safety inspection must be focused on whether to minimize the risk of accident using defense-in-depth concept and risk insight obtained from probabilistic safety analysis. The regulatory oversight of accident prevention can be strengthened by requiring that safety improvements be considered through the use of deterministic and probabilistic approaches (such as probabilistic risk assessments (PRA). Hence, the incorporation of DID concept and risk insight into deterministic-based safety inspection has not been well studied so far since the regulatory safety inspection was developed depending on each country’s specific regulation. The aim of this study is to propose a methodology using APR1400 Large LOCA as a case study to develop Safety Inspection Methodology using AIMS-PSA as an analysis platform to develop Event tree and fault trees and analyze how to secure the success path and how to block the failure path in a specific event tree. This study will help to improve accident anticipation, high reliability, and risk assessments to maintain the operability of all safety systems and to ensure the long-term ability to mitigate any extreme accident scenarios
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Assessment of Drowsy Driving Associated Characteristics Using Deep
Learning-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Marwan Naeem, Emran Alotaibi, Yousef Elbaz, Muamer Abuzwidah, Samer Barakat
The presence of road traffic accidents is subjected to various contributing factors including drowsy driving. The occurrence of drowsy driving has been a major cause of road accidents globally. Therefore, this study aims to analyze demographic, socio-economic, daily habits and drowsy-related characteristics associated with fatigued or drowsy driving in the United Arab Emirates (UAE). The data were gathered upon a questionnaire-based survey among a sample size of 525 drivers in the UAE. Inputs were given weights upon consulting experts in the field of transportation. Data were analyzed using artificial neural networks (ANN). Daily habits significantly affect the driver’s risk to experience fatigued driving. Socio-economic, drowsy-related, and demographic characteristics followed sequentially. Time of day to experience drowsy driving has the largest importance. Moreover, daily habits such as driving durations, distance driven, and sleeping hours demanded the importance of drowsy driving risk next. Socio-economic characteristic such as the average monthly income was the least significant. Prevalence of sleep-related accidents in the UAE is a fact, where drivers are less concerned about fatigue driving than other traffic safety issues. Raising awareness of drowsy driving among society is a need since people tend to see other factors to be riskier than drowsy driving. The results highlight the need to counteract drowsy driving with treatments on-road and more education to the public.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Modeling Crash Frequency Using Crash and Geometric Data at Freeways
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Abdulrauf Khetrish, Muamer Abuzwidah, Samer Barakat
Road crashes are one of the leading causes of death and injuries in many countries around the world, which leads to enormous losses in terms of health, social, and economic aspects. Researchers are using different tools to locate, assess, and treat hazard spots in the road network. this paper aims to investigate and understand the important variables that contribute to road crashes using different crash frequency modeling techniques. Negative Binomial and Poisson regression models were used to identify the most significant variables that increase the crash frequency on the roads. The study was conducted on data obtained from the Highway Safety Information System database for a 5-years crash period in the state of North Carolina. The results of these models showed that for the Poisson model, the p-value was significant for the segment length, AADT, speed limit, right shoulder width, and median width while the left shoulder width and number of lanes weren’t significant. The coefficient estimate B sign could be used to indicate the type of contribution to the independent variable, all the dependent variables were positive signs except for speed and median width. Therefore, the increase in speed limit will decree the number of crashes. In contrast to the Poisson model, the negative binomial model showed significance only in three variables segment length, AADT, and the speed limit, the rest are not significant based on p-value, similar to Poisson the coefficient estimate B sign for the speed was negative. As expected, the increase of exposure increases the likelihood of being in a crash, therefore countermeasures are urgently needed to manage the speed, improve traffic operation, and enhance traffic safety.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Predicting Traffic Accidents Severity Using Multiple Analytical Techniques
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Ahmed Elawady, Muamer Abuzwidah, Samer Barakat, Jae Young Lee
Road accidents are a major world economic and social problem, as shown by the report of loss of lives and properties in many countries worldwide. Reporting indicated the number of fatalities from road accidents per year of about 1.35 million and 50 million injuries was recorded or an average of 3000 deaths/day and 30,000 injuries/ day. Furthermore, its consequences have an impact on economic and social conditions in terms of health care costs of injuries and disabilities. The objectives of this paper are to implement four modeling techniques, Logistic Regression, Naïve Bayes, Support Vector Machine (SVM), and Artificial Neural Networks (ANN), to predict accident severity and compare the performance of these models in terms of their prediction accuracy. More than 117,000 accident records with over 32 variables were retrieved from London. The results showed that the nonlinear SVM model outperformed other techniques in terms of performance with an accuracy of 78.32%. On the other hand, the linear SVM was the worst overall model with an accuracy of 69.27%. In terms of training time, a considerable difference was found between two groups of models: Logistic Regression, Naïve Bayes on one hand, and SVM and ANN on the other group. The former required a shorter training time (less than 10 min for each model), while the latter had training times between 20 to 70 min per model. Overall, the nonlinear SVM seems to perform the best in terms of accuracy, while Naïve Bayes is the best for fast prediction. This result can be beneficial for researchers and practitioners to predict accident severity levels and suggest improvements to traffic safety.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
- Modeling Lane-Choice Behavior and Public Willingness to Pay for HOT Lanes:
A Neural Network Approach-
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Abstract: Publication date: 30 August 2023
Source: Advances in Science and Technology Vol. 129
Author(s): Mahmoud Khalil, Ahmad Shabib, Sainab Feroz, Muamer Abuzwidah
This paper focuses on investigating public perception in the United Arab Emirates (UAE) towards the implementation of High-Occupancy Toll (HOT) lanes in major freeways. HOT lanes provide the UAE government with significant potential to enhance the transportation network through decline in motorway accidents, procuring additional revenues, decreasing the overall sector costs, as well as lessening the carbon footprint ensuing from this sector. However, the primary challenge encountered during the implementation of HOT lanes in the UAE is public perception and Willingness to Pay (WTP). A questionnaire-based survey was developed and circulated among the public in the UAE to deduce the public’s attitude towards the utilization of HOT lanes. The survey intended to capture the socio-economic, demographic, and commute-related characteristics of respondents, as well as their current knowledge of HOT lanes. The survey data were collected and processed to identify the features of the obtained sample. Comparative statistical and advanced numerical analyses, in the form of Linear Regression (LR) and Artificial Neural Networks (ANN) were conducted to model the relationships between different characteristics and the public’s WTP. Additionally, the significance of the factors affecting the WTP were ranked using Bayesian Networks. The results showed that monthly income was the most significant factor affecting public WTP followed by age, frequency of trips, employment status, peak hour traffic, and emirate of residence. Prediction equations generated from ANN and LR, utilizing the most significant factors, indicated that ANN had significantly higher accuracy and lower MSE compared to linear regression. Overall, this study could significantly help decision-makers for future transportation systems improvement.
PubDate: Wed, 30 Aug 2023 00:00:00 +020
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