Dissertations for IT Management (ITM)

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    Investigating the Effects of Cloud-Based Business Intelligence Adoption on Services Delivery Quality and Customers Participation in Private Sector Companies in UAE
    (The British University in Dubai (BUiD), 2023-06) ELSHABOURI, MOHAMED IBRAHIM HAMZAWI; Professor Khaled Shaalan
    Purpose: This dissertation aims to investigate the effects of cloud-based business intelligence (BI) adoption on service delivery quality and customer participation in private sector companies in the United Arab Emirates (UAE). The study seeks to address the research gap regarding the specific impacts of cloud-based BI in the UAE context and provide practical insights for organizations striving to improve operations and enhance customer experiences. Methodology: A mixed methods approach will be employed to collect quantitative and qualitative data from a sample of private sector companies in the UAE. The study will focus on two key areas: the impact of cloud-based BI adoption on service delivery quality and its influence on customer participation. The data will be gathered through interviews and surveys, allowing for a comprehensive analysis of the research questions. Findings: The findings from this study will shed light on the effects of cloud-based BI adoption on service delivery quality and customer participation in private sector companies in the UAE. The study will provide empirical evidence and insights into the specific benefits and challenges associated with adopting cloud-based BI in the UAE context. Implications: The results of this study will have practical implications for private sector companies in the UAE seeking to enhance their operations and improve customer experiences through cloud-based BI adoption. The findings will inform strategic decision-making processes and provide guidance for organizations looking to optimize service delivery quality and customer engagement. Originality/Value: This research contributes to the existing body of literature by addressing the research gap in understanding the effects of cloud-based BI adoption on service delivery quality and customer participation in private sector companies in the UAE. The study provides original insights and empirical evidence specific to the UAE context, offering valuable contributions to the field of cloud-based BI implementation and its impacts on organizational performance and customer engagement.
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    Students’ Intentions Towards the Adoption of the Metaverse in UAE Higher Education Using an Extended UTAUT2 Model: A Hybrid SEM-ANN Approach
    (The British University in Dubai (BUiD), 2023-06) DALLAH, SAMIA MOHAMMAD SABRI
    This research paper examines students’ intentions towards the metaverse technology acceptance in UAE’s higher education. However, limited research is available on the impact of using the metaverse technology for teaching and learning. The COVID-19 crisis had a great impact on the teaching and learning process. Thus, the use of the metaverse in education has the power to transform conventional approaches to instruction learning by giving students engaging, immersive experiences. The primary motivation behind this study was to understand students' intentions of accepting the implementation of this new technology in higher education. Because UAE always aims to improve its sectors by investing in technology usage, it has been chosen to conduct this study. The study aims to investigate learners’ intentions towards the metaverse in UAE’s higher education by applying a convenience sampling technique to collect 313 responses using an online survey. An extended UTAUT2 model is a useful framework integrated to comprehend the ten factors that affect the metaverse's effective adoption in educational contexts. The study identifies behavioral intentions (BI) as an essential factor to measure users’ intention of using the metaverse in higher education. Compared to other literatures, the study adopts a novel methodology by using artificial neural networks (ANN) and structural equation modelling (SEM) to test the hypotheses. The study findings revealed that perceived innovation had the most significant effect on the metaverse use in higher education, with an (87%) normalized importance score, followed by social influence (82%), performance expectancy (79%), habit (72%), satisfaction (62.4%), ubiquity (49%), and perceived risk (36%). Sensitivity analysis results further revealed that these factors play a crucial role in shaping students’ attitudes towards using the metaverse in education, as well as its impact on the learning process. The practical significance of the study enables the relevant educational stakeholders to consider the main factors that could affect students’ BI towards the use of the metaverse in learning. However, further research is needed to verify the findings and broaden the application of the suggested theoretical framework to other fields.
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    An Integrated Model For Examining The Intention To Use The Metaverse In Higher Education Through The SEM-ANN Approach
    (The British University in Dubai (BUiD), 2023-06) ABOUSHARKH, INAS WAHID
    With the emergence of the COVID-19 pandemic, online education has become the norm, posing challenges to academic effectiveness. This study examines the adoption of Metaverse in higher education. Using the Unified Theory of Acceptance and Use of Technology (UTAUT2) and the Protection Motivation Theory (PMT), a model was developed to assess the adoption of Metaverse technology in an educational setting from a student’s perspective. 368 undergraduate students in the United Arab Emirates participated in the survey. These students had extensive exposure to technology, particularly online learning tools. Structural equation modeling and deep learning analysis were used for data analysis. The results highlighted significant factors influencing the initial intention to adopt Metaverse technology in education. The most distinguishing success factors were identified as Habit, Self-Efficacy, Response-Efficacy, and Response-Cost. This research contributes to theory by presenting and empirically validating a novel model that investigates the factors influencing the initial intention to adopt Metaverse technology in higher education. The practical implications of the study's findings are that they inform the development of diffusion strategies and marketing techniques for the adoption of Metaverse technology in higher education. This is accomplished by evaluating the impact of diverse user requirements on the intention to use the Metaverse for educational purposes. The findings may also help Metaverse technology designers create platforms that are user-friendly to nurture self-efficacy, and successful in accomplishing learning outcomes i.e., increasing response-efficacy, and cost- and time-efficient (cutting response-cost).
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    Predicting Student Withdrawal from UAE CHEDS Repository using Data Mining Methodology
    (The British University in Dubai (BUiD), 2022-11) BINEID, AHMAD ABDULLA
    Early prediction of a student who is at risk of course dropout leads to student retention in the study course. The percentage of student dropout in higher education sector is high, and affects the students’ careers negatively and the institute’s program continuation. The purpose of this study is to predict and identify students who are likely to withdraw from an institute. This identification assists the institute’s advisor to take precautionary measures to retain this group of students. Also, the study aims to find the variable that is most efficient to lead to student dropout prediction. To fulfil the study’s aim, CRISP method was followed after reviewing research papers. A dataset of 1272 students’ data in size from Central Higher Education Data Store (CHEDS) has been fetched from Dubai’s governmental higher education institute. The demography of students is international background. Several model classifiers from Standard and ensemble were implemented to find the best answer to the research questions. Receiver Operator Characteristic (ROC) based on Area Under Curve (AUC) was used to assess the result plus other metrics. Research outcome, results showed that students who had low GPA, average register credit hours and fluctuating student’s enrollment status were more likely to withdraw from study course. Random Forest classifiers demonstrated the highest performance in prediction, and scored 87.8% in AUC with an accuracy of 84.82%. GPA and average register credit hours attributes were the most effective contributor in prediction.
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    The Development And Significance Of Business Intelligence (BI) Platforms In Facilitating The Decision-Making Process In Dubai Government Entities
    (The British University in Dubai (BUiD), 2022-05) ALMHEIRI, ABDULLA OBAID MOHAMMED
    Business Intelligence (BI) technologies provide a flexible platform for businesses to properly store, process, analyse and report data and processes. The use of BI technologies in handling critical data and facilitating data-driven decision making (DDD) has been realised by many literature studies. However, its application and benefits for the Dubai government entities for effective data management and decision making have not been investigated before. Thus, the current study has focused on analysing the significance of BI platforms in improving the decision-making process in the Dubai Statistics Center (DSC), a governmental entity in Dubai. Using secondary research design, the study determined factors that impact the decision-making process in Dubai government entities. Furthermore, the significance of using the BI platform for decision-making is established in the light of academic and empirical evidence. A BI platform using ArcGIS software is also developed demonstrating the visual and realistic application of interactive data in decision-making regarding different aspects of DSC such as population, marriages, education, etc. The recommendations are provided retarding the effective use of BI platforms in DSC and other government entities in Dubai. The current study will contribute to knowledge and practice to promote the use of BI platforms in making effective decisions. Future work includes integration with Artificial Intelligence (AI) for the AI-based BI platforms which would allow the translation of theoretical solutions into actionable tasks.
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    Information Security Management for Cyber Security Challenges in Smart Cities Security and Privacy
    (The British University in Dubai (BUiD), 2022-04) OTHMAN, AZZAM;
    Information security management universally needed and has become popular in our digital world. A growing proportion of human activities, such as social interactions, entertainment, shopping, and gathering information, are now mediated by digital services and devices that are needed to be protected 24/7 based on the information security triangle Confidentiality, Integrity, and Availability. Currently, there are more than 12.3 billion IoT devices connected to our digital world recording everything around us such as street cameras, smart security devices, smart refrigerators, smart watches, etc. These devices collect most of our daily time information as our health by smart watches, refrigerator needs, air condition status, GPS information, and so on. Much of our daily life activities and privacy collected by these digital devices connected to the Internet. The main objective of this research is to answer the question whether information security management can protect our daily life and privacy information to be able to live in safe life in our smart cities or not. The findings of this study suggest that lack of in-house expertise, insufficient funding, difficulty in locating right security talent, poor leadership and lack of accountability are the top cyber-security challenges. In addition, it was found that organizations are mediocrely prepared to detect, prevent and respond to cyber-threats. Furthermore, it was revealed that individuals have mediocre level of security awareness.
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    Developing a framework for network security behavior integrated with the organization data management system to predict the threats
    (The British University in Dubai (BUiD), 2022-03) ISMAIL, HANI ABDELHADI ABDULLAH
    Network security management becomes an essential task in all organizations to protect their information and communication. It became more critical, especially after the COVID 19 Pandemic, as most businesses and industries have moved to use more online technologies. This study aims to develop a framework for analyzing network security behavior integrated with the current data management system and to predict the threats for administrator remedial actions by using Machine-Learning techniques The primary objective of the study is to automatically provide an optimum set of rules that are summarized and generalized across various security devices for professionals to configure the best security solution with minimum configuration efforts. This is experimental analysis research method depends on collecting information from network security data flow based on selected events that matched with the actual organization's security rules and policies with a dataset of 123029 records collected from log files of the standard security system. Moreover, a framework is designed based on the network security events, including the threats prediction, which can be used to take proper actions by using the artificial intelligence method. The result of the studied framework showed that KNN and random forest models performed better with the precision of 91.84% and 91.48%, respectively, compared to the other models of SVM, decision tree, and Naïve Bayes. The future work of the study is to enhance the prediction of unknown threats and apply the model in the real world to establish a security baseline for similar organizations.
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    Predict Student Success and Performance factors by analyzing educational data using data mining techniques
    (The British University in Dubai (BUiD), 2022-03) ATIF, MUHAMMAD
    Academic institutions around the globe strive to become highly reputable and make continuous efforts to improve their students' ability to gain and apply knowledge concepts in the field. The primary outcome of the academic institutions is their student's quality of education. The academic institutions are known for their outcome product that are their students work in the practical field. The educational institutions desire to have beneficial insights to ensure the success of students and to enable them to acquire knowledge and improve their abilities. This enables the institutions to retain students, graduate students on time, make students’ workplace ready and improve the institution’s reputation. The primary aim of the study is to identify key attributes that contribute to the performance of the student. Past research has mainly focused on data related to student academic assessments grades, GPA, and student demographics. The research study includes more aspects like the number of students in class, attendance of the student in class, and due to the fact that the United Arab Emirates is a diversified multicultural country, English Language Proficiency, nationality and age of students and the instructor contributes towards student performance. The research study is performed as experimental analysis and develop models from nine machine learning algorithms including KNN, Naïve Bayes, SVM, Logistic regression, Decision Tree, Random forest, Adaboost, Bagging Classifier, and voting Classifier. The model is then applied to data collected from a reputable university that included 126,698 records with twenty-six (26) initial data attributes. The results show that the Random forest model performed better in terms of accuracy of 90.12% as compared to other models. The attendance in class attribute showed positive correlation while the number of students in class attribute showed negative correlation with the grades. The Future enhancement of the research study is to include more attributes from various aspects and also to further the study to provide recommendations for the students, instructor, and the educational institution.
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    Developing a framework for using face recognition in transit payment transactions
    (The British University in Dubai (BUiD), 2021-11) HABEH, ORABI MOHAMMAD ABDULLAH
    Nowadays, significant number of people relays on public transportation to commute to their final distention due to the increase of the private cars cost, traffic jam, toll gates, high petrol charges and other factors, which create a huge pressure on the public transportion infrastructure in general and the fare collection system in specific. Therefore, transit operators are continuously keen to identify different solutions to reduce that pressure and improve the travel experience by upgrading its fare collection system to the advanced state-of-the-art account based ticketing system in order to achieve better flexibility to offer smooth and convenient payment options for the passengers to choose. On the other hand, a tremendous advancement has been noticed in the human face detection and recognition technology which mainly used to authenticate and identify person face from a group of people through detecting a unique feature of the face and ignore the background image then compare the outcomes with the registered faces in the database to identify the person. This dissertation proposes a framework which aims to offer face recognition technology as a new payment option inside metro station. The proposed framework involves the hardware, software, algorithms, and system specification requirements. Further, it provides a detailed end-to-end systems integration and transaction flow between the account-based ticketing, face recognition, and banking systems. It’s worth to mention that the proposed framework is built based on the outcomes of three dimensions, including a systematic literature review, users’ surveys, and experts’ surveys. 84% of the users expecting an improvement to their travel experience if the face recognition access offered. In addition, the experts supported the users’ survey results by claiming the optimum technical feasibility to implement the face recognition access inside metro station. The framework offers two state-of-the-art solutions. The first solution is proposed based on integrating the existing surveillance camera systems with the recommended “Banking Payment Context- Account Based Ticketing System” to offer face recognition access entry to the passenger inside metro station. A number of combined algorithms and classifiers are proposed to use in this solution based on the encouraging outcomes observed from the systematic literature review and experts’ survey, including Local Binary Pattern descriptor, Haar-Like Descriptor, Ada Boost, Cascade classifiers, Affine Transformation, Histogram Equalization, Gaussian Filter, Principal Component Analysis which are embedded in OpenCV or MATLAB application. The argued face recognition accuracy between 98%-99.2% and average processing time including metro gate opening time ranges between 1114-1400 milliseconds. This solution considers an effective cost-based solution. The second solution is proposed based on implementing a dedicated full HD face recognition stereo camera system on top of each metro gate and integrate it with the recommended “Banking Payment Context- Account Based Ticketing System” by using the MFcoface face recognition method which results from the systematic literature review and experts’ outcomes. The argued face recognition accuracy ranges between 99.3%-100% and average processing time including metro gate opening time ranges between 200-400 milliseconds. This solution considers an efficient performance-based solution.
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    Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique
    (The British University in Dubai (BUiD), 2021-12) ALZAABI, HANADI OBAID
    Energy is an essential contribution for practically all exercises and is, in this way, imperative for development in personal satisfaction. Because of this explanation, valuable energy has turned into an expansion sought after for many years, particularly utilizations in smart homes and structures as individuals create quickly and improve their way of life dependent on current innovation. The energy requirement is higher than the production of energy, which makes a shortage of energy. Many new plans are being created to satisfy the energy consumer interest. Energy utilization in the housing area is 30-40% of the multitude of areas. A smart home's existence and growth has raised the need for more intelligence in applications such as resource management, energy efficiency, security, and health monitoring so that the home can learn about residents' activities and predict future needs. An energy management technique is being applied in this research work to overcome the challenges of energy consumption optimization. Data fusion has recently attracted much attention for energy efficiency in buildings, where numerous types of information may be processed. The proposed research developed a model by using the data fusion approach to predict energy consumption in terms of accuracy and miss rate. The proposed approach simulation results are being associated with the previously published techniques. Additionally, the prediction accuracy of the anticipated method attains 92%, which is higher than the previous published approaches.
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    Digital Transformation in Public Transportation: Investigate the impact of Digital Transformation in Public Transportation Business Model in UAE on Public Transportation Customer Relationship
    (The British University in Dubai (BUiD), 2021-11) THEKRALLAH, FIRAS FATHI
    Digital transformation become a major need, and for many businesses it’s not optional to speed up their digital transformation because of all the uncertainty about the future such as COVID-19 pandemic. Government agencies can enhance services, save money and the same time improve the quality of resident’s life by digitizing processes and making organizational changes, also many government entities have discovered that the digital transformation of a government is difficult however, it is extremely lucrative for residents and government officials. The United Arab Emirates is one of the most developed countries in the middle east and north africa for citizen-centric online public services, as multiple digital government strategies had been introduced such as the fourth industrial revolution strategy, the artificial intelligence strategy, the national innovation strategy, and the emirates blockchain strategy 2021, moreover UAE government achieved major digital accomplishments in a variety of fields, including education, health, cybersecurity, digital government, and smart cities. The aim of this research is to identify the impact of digital transformation of public transportation business model on customer relationship using a quantitative research methodology by utilizing a quantitative survey for collecting numerical data. Results indicates that there is a moderately positive association between the digital transformation of public transportation business model on customer relationship.
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    The Impact of Implementing Maturity Models on IT Project Performance
    (The British University in Dubai (BUiD), 2021-11) AL KAILANI, BARA’ RIYAD
    Recently, many models of maturity have emerged in IT sector, and there are few research studies on their benefits and impact on projects performance. The main aim is to study the impact of implementing project management maturity models on IT project performance. The quantitative approach was used by measuring the implementation of four basic principles shared by all maturity model. In addition, secondary research methods were used to collect data on the implementation of maturity models from academic journals, articles, and online books. A survey was conducted as a primary research method to collect data from employees of various job roles working in IT organisations. This survey is designed in three sections, the first for demographics, the second for measuring maturity models implementation, and the third for measuring project performance. Survey questionnaire was published by sending it electronically to 300 IT professionals representing the study population. 192 responses were received and therefore the participation response rate was 64%. Appropriate scientific analysis methods were used to analyze the data, including descriptive analysis, reliability, correlation, linear regression, and multiple regression. This research found that the implementation of maturity models have a significant relationship with the performance of IT projects, and plays an important role in influencing. The research offers a set of recommendations, including: To improve the performance of IT projects, it is recommended to implement the project management maturity models, with an emphasis on process improvement activities. It is recommended that IT organizations start spreading awareness of maturity models and adopt their own improvement policies.
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    Impact of strategic information systems To achieve the agility of administrative processes (An applied study on government institutions in the Emirate of Fujairah)
    (The British University in Dubai (BUiD), 2021-05) AlDhanhani, Aishah
    In light of the current situation in years 2020-2021 for the threat of the COVID-19 pandemic. The government organizations, see the importance of creating policies is to ensure the continuity of their work. The study will discuss the vision of the role played by strategic information systems (SIS) in enhancing the agility of administrative processes in government institutions in the Emirate of Fujairah. The study set three hypothesis to prove the SIS role and effect on the administrative processes according to different dimensions. Quantitative methods is used and the questionnaire tool is used to analyze the data. The results of the study can be summarized to, the study sample is aware of the SIS from its effects and not by its definition. Second result is the high positive relationship of the SIS characteristics to the agility of administrative processes. Third, the level of understanding the terms of SIS and agility in Fujairah government organizations is varies for variable (gender, years of experience, job position and academic qualification). The study finally presents recommendations for the results to improve Fujairah government organization.
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    Students behaviour toward voice assistant technology in the UAE
    (The British University in Dubai (BUiD), 2021-05) Al Shamsi, Jawaher
    Recently, voice assistant’s technology has become a universal learning assistant approach for students to such an extent that they can no longer use their hands to study. The aim of this research is to investigate higher education students’ behaviour towards artificial intelligence voice assistants in the United Arab Emirates, such as Siri, Alexa, Google and Cortana etc. This research has three main objectives. First, to review most commonly adopted external variables for adoption and acceptance of voice assistant studies in the TAM. In order to carry out a systematic analysis, the quantitative study technique is based of 42 papers published in the past 10 years. The independent variables of TAM, which includes: (Subjective norms (SN), Enjoyment (ENJ), Facilitating Conditions (FC), Trust (TR), and Security (SR)), were defined as the most commonly used. Second, to generate a conceptual framework by applying TAM model with most commonly adopted external variables. Third, to conduct a current conceptual framework by employing the PLS-SEM procedure, which is appropriate for the context of our research. A questionnaire survey was used to gather data from four universities in the United Arab Emirates which have adopted the voice assistant system. The overall number of students that were involved in this research were 300 students. Based on the study’s findings, the results indicate that there was a significant influence of enjoyment and trust on students' perceived usefulness of using voice assistant technology. In addition to that, trust and facilitating conditions have positively impacted the students' perceived ease of use of voice assistant systems. Moreover, perceived usefulness and perceived ease of use has contributed to grow the students' behavior intention to use voice assistant technology.
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    21st Century Warfare: How Information Technology Has Fundamentally Changed Global Warfare - An Analysis of Insurgencies’ Use of IT
    (The British University in Dubai (BUiD), 2018-11) FIKRI, MOHAMMAD NADER MOHAMMAD ABDULLAH
    This paper utilizes a qualitative approach to provide a case study analysis of the rising use of technology by insurgents. Examining the literature and making a comparative analysis of the trends of recent years allowed the researcher to come to the conclusion of the rising necessity of cybersecurity in contemporary warfare. A quantitative approach in such a case would have been limited due to the lack of reliable statistics available as well as the more sterile nature of results it would provide. The 21st century has seen a change in the type of warfare waged globally. Whereas the 20th century was characterized by decolonization and states warring against one another, the 21st century has witnessed a shift in global warfare where non-state actors such as radical groups are gaining momentum and causing significant mayhem. The accessibility of radical groups to wage war on a global level has been exacerbated in recent years by the widespread usage of information technology on an individual level and the resulting compression of time and space. Both these factors, the rise of non-state actors and the usage of information technology, has disrupted the way global warfare is waged. This dissertation focuses on examining the ways in which global security in the 21st century has changed due to insurgents’ access to information technology. By focusing heavily on the available literature and findings conducted of the insurgents in Iraq and Syria, this research aims to provide recommendations on the ways in which governments must now reassess their security needs by taking into account the changes in 21st century information technology. Information technology is a double-edged sword; the abuse of it by the wrong hands can cause global chaos, however, it is also a fundamentally important tool in the counterterrorism effort as well. As technology continues to advance and as social networks and IT equipment become more accessible to individuals, a major portion of global antiterrorism efforts will shift to the digital sphere. After reviewing the findings from literature and references of insurgents’ usage of IT, it became clear that social media was a catalyst for the rapid spread of their ideology and propaganda. Social media networks were used both to brainwash the public and recruit new members. Government websites and databases were hacked by cyberattacks and sensitive information made public. These findings from the literature review conducted; demonstrated that they had a well developed, deeply-strategized IT and media strategy and that when they emerged globally seemingly overnight, the world was taken aback and governments were unprepared with how to deal with their digital prowess. This has brought to light the importance of a globally concerted effort to give cyberterrorism the importance it deserves in counterterrorism efforts.
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    Social Commerce Trust Factors and Users' Perspectives: A Study in UAE Based on Trust-Extended Technology Acceptance Model
    (The British University in Dubai (BUiD), 2019-12) Abdulrazzaq, Reem
    Nowadays, social commerce has been turned into the most interactive and the most convenient way in online shopping. Despite having multiple risks when performing a purchase through social networks, yet it is becoming the trend of the era. For that, the significance of trust has arisen along with the need to recognize the elements that influence trust in social commerce. These basic elements were identified as familiarity, electronic word-of-mouth, high knowledge in internet and social networks and integration between ecommerce and social commerce. The aim of this research study is to investigate the factors affecting UAE people’s trust in social commerce and have a closer look on users’ points of view when making a purchase process over social networks marketplaces. In order to accomplish this goal, a quantitative survey was carried out and the results were analyzed which provided us with an extensive vision about the perspectives of the respondents and the socio-technical components that affect users trust in social commerce.
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    Government Data Governance and Management Frameworks Positive Collaborations, to Enhance Data Sharing and Efficiency of Government Services in Smart Cities
    (The British University in Dubai (BUiD), 2018-11) HAMDAN, DIMAH
    The conception of the word smart in smart cities; is often perceived, as cities that are aiming to improve its functions across various sectors, through the adoption of (smart) digital technologies. These cities value up the citizens prospective through services focused on innovation driven and data sharing; consequently, or in simple words embarking and enabling data sharing and offer smart services across the city. Smart Governments globally (including United Arab Emirates) built on complex and diverse systems; aiming to change the way services are delivered and consumed. Government entities will have access to and hold a significant variety of data, however, only a subset of this, will be made available to share with other authorized entities or with the public, either because the rest is not relevant, or due to security restrictions preventing further dissemination. Therefore, Governments need to outline common processes to follow when contributing data, This dissertation, through presenting a holistic review will cover three pillars, first pillar; is to highlight the gaps and challenges governments are facing on the backbone to a successful implementation for integration of government systems and services-, which is the Data. And that any data centric model strategy including the smart cities, should think of process not only technology when it comes to data. Second pillar in this paper will elaborate on the components of data governance and data management, and the human resources needed in every government entity to adopt the data governance and support the transformation. Third pillar; will demonstrate the United Arab Emirates best practice, regarding issuing the data management and governance framework. In addition to two, real use case of integrated services, to show the coloration between having the proper data governance and the success of integrated services, maximizing the utilization of the technology and reduce the cost and time of fixing the data to fit to purpose. I would like to focus that the smart/ digital cities need more integrated services; not more data.
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    The Impact of Privacy Laws on Social Media in the United Arab Emirates
    (The British University in Dubai (BUiD), 2018-11) ALHAMMADI, ABDELRAHMAN AHMED ALMULLA
    The purpose of this research is to perform a study on the impact of privacy laws on social media. This discussion demonstrates that there is no single definition of privacy that is applicable to all features of social media and that it is often necessary to combine perspectives to achieve a holistic framework that can guide research on issues of both information disclosure and privacy. This research is based on an Epistemology research methodology; as this methodology is focused on the facts that determine the acceptable knowledge about the concerned field of research as well as it also question the information known to be true on the basis of rigorously tested and treated facts. Furthermore, results examined that social networking privacy laws are followed by the UAE social networking websites but not by all. In the conclusion of this research, the measures to determine the privacy law’s impact on personal information policies, control and notification to measure the acceptance of social networking websites by users and risk awareness in determining social networking acceptance by users are discussed. And the results concluded that that privacy laws and concerns for control and notification affected the user's acceptable behavior and the UAE authorities must follow such measures that guarantee the protection of sensitive information and other personal details
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    Facilitating Decisions by Using a Data – Driven - Decision Making for Management Using Business Intelligence Case Study: Social-Services Departments in the Emirate of Sharjah
    (The British University in Dubai (BUiD), 2019-04) AL KETBI, WADHA RASHID
    Many governmental and private institutions have much data, which are not used properly. Therefore, they are stored for a long period and this leads to using all the servers found there. Modern technology can find links between such data and the way of getting benefit of it. Actually, this helps to get a quick and proper decision. This data is not only for storing but it is also for helping in taking the quick and proper decision based on numbers and statistics. Due to the care of our rulers, the strong base of data and the strategy of the UAE in predicting the future, the UAE can anticipate, analyze and plan the early opportunities and challenges on the long run at all levels to achieve qualitative achievements for serving the state’s interests. The new strategy of the UAE serves the vision of the president and vice-president of the UAE while forming the future government, which aims at getting all the global opportunities and anticipate ten future economic and social challenges. Providing social aids gets much care from our rulers either inside the state or outside it. This research sheds some lights on providing social aids for the UAE citizens in the emirate of Sharjah. It also helps people get familiar with the technique used to provide these aids, people deserving this aid, and the objectives of this department, which help in improving the way of providing these aids. Simply, the definition of the social aids means providing the financial, healthy and social aids. This research focuses on the improvement and acceleration of the technique of providing the financial social aids for three types of people; oldness, widows and handicapped. That is because these kinds of people have the priority in providing aids in the department and they get the ultimate care of our rulers. Data-Driven decision-making approach was used in this research. Data driven refers to activities driven by spurred on by data. However, it is totally different from the data driven by the personal attempts and experiences. This leads to a very strong decision based on proofs rather than feelings. This expression is used mainly in business, but it is also used in so many other fields. Business Intelligence solution was proposed to analyze (12272 records) for the three priority beneficiaries in the provision of cash social assistance, which are, Elderly, Widows and Disabled. The result was the highlight of the major challenges that hamper the delivery of cash social assistance as well as the ability to involve all decision-makers based on accurate data and demonstrate it in an easy to read and accessible manner. By using POWER BI tools which can visualize data and share it through dashboards, online (web view) and mobile applications.
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    Positive Unlabelled Learning to Recognize Dishes as Named Entity
    (The British University in Dubai (BUiD), 2019-04) TAREK, AIMAN
    With the growth of social media, there is a need to analyse the user-generated content; especially the text reviews. Online text reviews have a lot of potential and opportunities for both users and business owners. Many researches target analysing text reviews extracting useful info especially Named Entity Recognition. In this research, I focus on extracting food and dish names as a named entity. With the lack of labelled data, I try to overcome the cold start and avoid manual labelling by building a lookup table from a dictionary. I work with Yelp dataset, going through each text review, using each noun as a candidate, label the positive samples using the aforementioned lookup table, then using Positive Unlabelled learning techniques to recognise more entities within the unlabelled data, by predicting the probability for each candidate. I considered the surrounding words; preceding and following in building the model, as well as Part of Speech tag for each. To eliminate duplicates due to repeated candidates from different reviews or sentences, I calculate the average and represent each candidate entity only once. The results show how we can automate entity recognition process, using dictionaries and machine learning techniques and achieve an acceptable accuracy of 67% and boost the newly discovered entities by around 15% using Positive Unlabelled learning over automatically build lookup table. This research has the potential to be extended to other topics other than food and dish names, also it acts as a framework and algorithm independent.