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Polycystic Ovarian Syndrome Identification through Self-Attention Guided Convolutional Neural Network
No full textPolycystic Ovarian Syndrome (PCOS) is a hormonal
disorder that impacts women during their reproductive
years, marked by indicators like multiple ovarian
follicles or cysts that can be visualized through
ultrasound imaging. Convolution Neural Networks
(ConvNets) have been enhanced with self-attention
mechanisms to improve their efficacy across a variety
of computer vision applications, according to
researchers. This study uses self-attention to improve
the effectiveness of a ConvNet classifier in classifying
PCOS, yielding a superior 99% accuracy, exceeding
the 96% accuracy of a regular ConvNet classifier
Ensemble Stacking Model for Sentiment Analysis of Emirati and Arabic Dialects
No full textSentiment analysis is the process of examining people’s opinions and emotions towards goods, services,
organizations, individuals, and other things, through the use of textual data. It involves categorizing text
as positive, negative, or neutral to quantify people’s beliefs. Social media platforms have become an
important source of sentiment analysis data due to their widespread use for sharing opinions and infor mation. As the number of social media users continues to grow, the amount of data generated for senti ment analysis also increases. Previous research on sentiment analysis for the Arabic language has mostly
focused on Modern Standard Arabic and various dialects such as Egyptian, Saudi, Algerian, Jordanian,
Tunisian, and Levantine. However, there has been no research on the utilization of deep-learning
approaches for sentiment analysis of the Emirati dialect, which is an informal form of the Arabic language
spoken in the United Arab Emirates. It’s important to note that each country in the Arab world has its
dialect, and some dialects may even have several sub-dialects.
The primary aim of this research is to create a highly advanced deep-learning model that can effectively
perform sentiment analysis on the Emirati dialect. To achieve this objective, the authors have proposed
and utilized seven different deep-learning models for sentiment analysis of the Emirati dialect. Then, an
ensemble stacking model was introduced to combine the best-performing deep learning models used in
this study. The ensemble stacking deep learning model consisted of deep learning models with a meta learner layer of classifiers. The first model combined the two best-performing deep learning models,
the second combined the four best-performing models, and the final model combined all seven trained
deep learning models in this research. The proposed ensemble stacking deep learning model was
assessed on four datasets, three versions of the ESAAD Emirati Sentiment Analysis Annotated Dataset,
two versions of Twitter-based Benchmark Arabic Sentiment Analysis Dataset (ASAD), an Arabic
Company Reviews dataset, and an English dataset known as a Preprocessed Sentiment Analysis
Dataset PSAD. The results of the experiments demonstrated that the proposed ensemble stacking model
presented an outstanding performance in terms of accuracy and achieved an accuracy of 95.54% for the
ESAAD dataset, 96.71% for the ASAD benchmark dataset, 96.65% for the Arabic Company Reviews Dataset,
and 98.53% for the Preprocessed Sentiment Analysis Dataset PSAD
Factors Affecting Autonomous Vehicles Adoption: A Systematic Review, Proposed Framework, and Future Roadmap
No full textAutonomous vehicles (AVs) offer several benefits, such as improving road safety, mitigating traffic
congestion, and reducing fuel consumption and gas emissions. Despite these benefits, their adop tion rate remains limited due to various factors influencing users’ decisions. While previous studies
have identified numerous factors influencing AV adoption using various adoption frameworks, the
factors have not been comprehensively analyzed and synthesized. Thus, this systematic review
aims to bridge this gap by identifying and classifying the factors influencing the adoption of AVs.
Out of 3,532 collected research papers, 71 empirical studies were analyzed thoroughly. The find ings demonstrated that the technology acceptance model (TAM) was the most widely used model
for investigating AV adoption. The identified factors in the analyzed studies were classified into
distinct categories: psychological and behavioral factors, technological factors, social factors, envir onmental factors, security and privacy factors, AV-related factors, risky and negative factors, condi tional factors, and monetary factors. We have proposed an AV adoption framework grounded in
this taxonomy to direct subsequent empirical research. We have also highlighted numerous agen das to serve as a blueprint for future AV adoption studies. This review offers various theoretical
insights and actionable recommendations for multiple AV research, development, and implemen tation stakeholders
Analyzing the efficiency of intellectual capital: anewapproach based on DEA-MPI technology
No full textPurpose–Thisstudydevelopsarobustmodeltomeasureintellectualcapitalefficiency (ICE). It also analyzes
ICE across Gulf companies, sectors and countries.
Design/methodology/approach– This study uses data envelopment analysis (DEA), the Malmquist
productivity index (MPI), difference tests and additional analyses on a dataset consisting of 276 firm-year
observations.
Findings– The findings indicate that the study model is robust to additional analysis. The results show
significant differences in ICE between firms during the study period and noteworthy differences between
countries, where the Qatari and Bahraini firms achieved the best ICE compared to other countries.
Practicalimplications–Theresultsofthisstudyhavesignificantramificationsforincreasingknowledgeof
ICE analysis models among relevant parties. In addition, the findings may affect trading strategies because
investors and financiers are motivated by the potential for lucrative financial returns on their investments in
companies that prioritize ICE strategies.
Originality/value–Thisresearchcontributestotheliteraturebyproposingarobustmodelforestimatingthe
ICE. It also comparesICEacrossGulfcompanies,industriesandcountriestoshedlightontheirICEchallenges.
Keywords Intellectual capital, Efficiency, DEA, Data envelopment analysis, Malmquist productivity index
Paper type Research pape
An Investigation into the Impact of School Leadership Practices and School Policies on Abu Dhabi (UAE) Governmental School Inspection Outcomes
No full textThis thesis focuses on how schools implement three of six standards in the UAE inspection framework which are: Standard 3, teaching and assessment based on teaching for effective learning; Standard 5, how protection, care, guidance, and support of students has been implemented; and Standard 6, leadership, and management, which illustrates gaps in educational leadership due to differences in the direction, vision, and communication.
The study’s significance is that it will help determine how school leadership practices influence governmental school inspection outcomes in the UAE. School leadership must have supporting standards that schools should implement to improve their performance. There is a gap on the impact of leadership practices on school performance management and inspection outcomes in the UAE. Although the UAE school inspection framework emphasizes a visionary education system that is knowledge-based and drives innovation through research, it provides standards to ensure comprehensive performance to achieve quality education (Ministry of Education, 2017). It clearly defines the specific governance systems that should aid schools in implementing the framework.
This research is expected to provide details about new leadership practices that should be developed to help school principals identify and implement good educational and learning practices and offer recommendations on how to implement the inspection framework to improve performance. The research also provides a distinctive recommendation for school principals to develop their performance using the government excellence system in the United Arab Emirates GEM 2
Effect of Customer Service Modernization on Customer Satisfaction in Shell Petrol Stations in Oman
No full textCustomer service modernization is a critical success factor for energy service sector companies. Influencing positive customer experience is essential for enterprises operating in this area since energy sector depends on high quality customer service delivery to influence competitive market advantage. The study determines the effect of customer service modernization on customer satisfaction in Shell petrol stations in Oman to examine the effect of service visibility, service reliability, service effectiveness and efficiency, and service customization on customer satisfaction. The research adopted a descriptive research design and a population of customers who fuel at Shell petrol stations in Oman. A sample comprising 196 customers were recruited using simple random sampling. Online semi-structured questionnaires were used to collect the primary data. Multiple regression and correlation tests were inferential statistics reported. The results reveal service visibility positively and significantly affects customer satisfaction (β1 = 0.40; p < 0.05). Service reliability positively and significantly affects customer satisfaction (β2 = 0.267; p < 0.05). Service effectiveness and efficiency positively and significantly affects customer satisfaction (β3 = 0.169; p < 0.05). Service customization positively and significantly affects customer satisfaction (β4 = 0.124; p < 0.05). Shell stations to promote customer satisfaction through quality service delivery
Failures Root Cause Analysis for Sewer Pipeline Network System
No full textWastewater System is one of the most critical infrastructure systems. It is known that there are several types of Wastewater, and this dissertation is concerned with the Sewer type of Wastewater in particular. In addition, there are several systems of Sewer Wastewater as the dissertation is centered around Sewer Wastewater Pipeline Systems. Furthermore, there are two types of Sewer Wastewater Pipeline Systems: the gravity and pressure systems, and both systems will be discussed in this dissertation.
The Sewer Wastewater Pipeline System was chosen for several reasons, the most important of which is finding Sewer Wastewater Pipeline System failures that affect the Sewer Wastewater as a whole System. In addition, to the danger effects of Sewer Wastewater Pipeline System failures. These effects may reach the residents of the area where the Sewer Wastewater Pipeline System failures occur. Furthermore, there are very harmful environmental effects.
This dissertation aims to study the Sewer Pipelines system failures in an infrastructure organization in one of the Middle East countries. The period of data collected from 2014-2022. For studying and analyzing this topic, some techniques will be used Failure Rate, Pareto Chart, FMEA, and Fishbone Diagram.
The research findings are summarized as the failure rate of the Gravity Pipeline system is higher than the Pressure Pipeline system. Also, the most frequent system failures are Pipeline broken, joint dislocation, connection broken, and damage. In addition, the most important consequences of the sewage pipeline system effects are the health, environmental impact, and road collapse in some failure cases. Furthermore, the most critical root cause is Third Party, Water Hammer, and Groundwater movement
Utilizing Blockchain Technology in the UAE’s Construction Industry: Contract Administration and Management of Disputes and Claims
No full textOne of the main challenges faced by economies around the world is digital transformation. However, due to the large number of participants in single construction projects, the centralisation of authority, poor contract administration, lack of database and system interoperability, the construction industry has been unable to digitise, leading to delays and cost overruns, and disputes. The dissertation aims to explore and investigate the benefits of utilizing blockchain technology in construction contract administration, claim, and dispute management processes in depth, to decrease the number of disputes and claims, and to improve the efficiency, and overall productivity of the UAE construction industry. Further, the dissertation provides common causes of construction claims, and disputes, opportunities in implementation, functionalities of blockchain and smart contracts, adoption and adaptation guide, while observing other industries’ applications. Blockchain distributed structure provides a transparent, secure, and a private communication channel, thus establishing trust among contracting parties. Decentralisation supports document management, claim submissions, and automation of payments. Self-execution and enforcement of blockchain based smart contracts ensures compliance with contract provisions, claim process, procedure, and dispute mechanism. Through utilizing blockchain technology, most processes can be streamlined and automated, thereby ensuring compliance and reducing causes of dispute. In order to develop the dissertation, and answer the research questions, a qualitative research approach is employed, associated with literature from different sources. A thematic analysis strategy has been used combined with deductive reasoning of secondary data to validate or reject the hypothesis
Investigating Senior and Middle Level Leaders’ Perceptions of the Implementation of School Inspection Models in Selected Dubai and Northern Emirates Private Schools
No full textResearch has shown that school inspection is one of the most important tools that can be used to track and ensure the quality of education provided to students is at the expected level. The United Arab Emirates (UAE) has, in the past few years, initiated several policies to raise the quality of education. The UAE Vision 2030 lays specific attention on raising the educational quality of its residents, hence raising the human productivity and efficiency of the future workforce. As a result, several initiatives and projects have been implemented to monitor the quality of education in schools. One of them is the foundation of quality assurance entities that supervise and oversee the educational process through different inspection models. However, different stakeholders have various perceptions of the effectiveness of these initiatives to achieve quality education. In view of this, the main aim of this study is to investigate senior and middle leaders’ perceptions of the implementation of the school inspection models in selected private schools. The theoretical framework of the thesis is based on the following theories: Taylors’ Scientific Management Theory; School Inspection Effects and Causal Mechanism Model; School Inspection Effects and Effectiveness Model; and School Inspection Outcome Model. A sequential mixed method is used to facilitate the research process. Document analysis, questionnaires, and interviews were used to collect data from senior and middle leaders in the selected private schools. The research findings identify and classify the models of school inspection that are implemented. The findings also show that school inspection models have a significant role in supporting school leadership in school improvement and continuous development; however, the findings also show that school inspection could lead to some unintended consequences, such as some schools showing activities they have never done before or focusing on the quantity of policies and practices more than their quality. The study provides a set of recommendations about how to improve school inspection models based on the best practices implemented that led to the desired outcomes such as the implementation of monitoring and development visits that guide schools on how to address the recommendations received from full inspections