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The Influence of Ambient Weather Parameters on the Prediction of an Electrical Power Production of a Combined Cycle Power Plant in the UAE
No full textTo improve the utilisation of power plants and enhance production, this study is devoted to predicting the baseload electrical power production of a combined cycle power plant in the UAE. The data for this study was taken from plant sensors over a period of one month (September 2021) from specific sensors installed in the power plant, and provided the data for input features that correspond to affect and change the electrical power production. In the UAE, the hot summer climate and ambient weather conditions adversely affect the performance of gas turbines (GT) and have an influence on steam turbines too. Accordingly, this paper studies four input variables: ambient temperature (ranges from 25.29°C to 36.5°C), relative humidity (ranges from 35.47% to 90.28%), atmospheric pressure (ranges from 0.99 bar to 1.01 bar) and exhaust steam vacuum (ranges from 0.057 bar to 0.126 bar). All influence the target variable (power production), which ranges from 506.32MW to 864.44MW. The change in the exhaust vacuum pressure in the steam turbine is affected by the change in ambient temperature, relative humidity, and atmospheric pressure in the gas turbine.
The analysis includes applying machine learning methods such as linear regression and artificial neural networks (ANNs) to develop a predictive power production model using different interactive computer programs such as Minitab, RStudio and Microsoft Excel. The linear regression model R-sq value was found to be 53.49%. Consequently, Minitab software is found to be a slightly more accurate statistical package compared to RStudio. In addition, the best data subset is found to be for week 1, with R-sq value of 82.16%. Moreover, the power linear regression model is ascertained to be more accurate than the ANN power predictive model, with a mean absolute deviation of 46.385, symmetric mean absolute per cent error of 6.719 and residual standard error of 57.392 (Minitab outputs)
The Influence of Kanban Project Management Methodology Success Factors on Data Science Project Teams
No full textThe current study targeted the issue of Kanban methodology integration for the needs of effective management of Data Science project teams. The rapid growth in the number of Data Science projects that are being implemented in the contemporary world has increased the relevance of the study in this sphere. It is vital to develop effective and reliable project management methods that can enhance the productivity and quality of cooperation among members of a Data Science project team.
To address this question, the researcher reviewed the following key variables: Data Science project team challenges, and success factors of the Kanban methodology. It was important to estimate the potential influence of specific challenge factors on the performance of the Data Science project teams. In addition, the role of Kanban success factors as instruments of mitigating and preventing challenges was assessed. The results of the study were based on the collection of survey data from the target population of project managers and other members of the Data Science project teams.
The data analysis methods included descriptive statistics and regression analysis. The study outcomes demonstrated the effectiveness of the Kanban methodology in dealing with some pre-identified project management challenges in the field of Data Science. The study produced a significant premise. This suggests that the target population may not have the necessary knowledge and experience to effectively benefit from the Kanban project management techniques. Further research will be required to evaluate this premise
Exploring Authentic Leadership Theory in Practice: A Case Study about a School’s Leaders in a Private School in Sharjah, UAE
No full textDue to the economic, technical, and environmental problems that school leaders face in the twenty-first century, authentic leadership is crucial in today's society. This research investigates authentic leadership theory in practice through the eyes of successful leaders at a private school in Sharjah, with the goal of determining how authentic leadership theory is or might be applied by school leaders in the UAE. The theoretical basis for this research is informed by the genuine leadership theory. The research methodology is a qualitative exploratory case study using constructivism as the research paradigm. To collect data, semi-structured interviews were conducted, which included in-depth discussion with one school leader who was carefully chosen and a focus group interview with the middle leaders of the school to solidify the findings. The results indicate that the school leadership practice shows authentic leadership traits such as self-awareness, internalized moral viewpoint, and balanced thinking. However, data suggests that the leader's behavior lacks relational transparency, which might be challenging in particular settings. These findings might help practitioners add value to professional development programs by teaching how to use authentic leadership theory in the workplace
Organizational Culture Factors Affecting the Project Effectiveness in the Construction Industry of the UAE
No full textThe present research examined organizational culture factors that are associated with project success in the construction business in the UAE. The study investigates the influence of project coordination, trust, communication, shared experience, and alternate forms of cooperation on construction project success. The research study assisted in enhancing the understanding of the UAE construction industry in terms of the project manager’s perception of the core factors of project success. With the use of a quantitative research design, the researcher attempted to answer the research questions. A survey strategy was employed, with a questionnaire being the primary tool of data collection. The data was analyzed with the help of descriptive analysis and multiple regression analysis. The results of the study show that project managers perceive that project coordination, trust, and communication show a significant impact on construction project success. The findings of the study show that the perception of project managers about the role of shared experience and alternate forms of cooperation was favourable to project success. The findings of the research study have significant implications for project management in the construction industry. The researcher recommended future research studies based on the limitations of the present research
The Impact of Distance Learning on Identifying Primary Students with Specific Learning Disorder (SLD) during COVID-19 in Two Schools in Ajman City in the UAE
No full textAbstract
The purpose of this study is to highlight the impact of distance learning on identifying primary students with specific learning disorders (SLD) during the COVID-19 pandemic in two private schools in Ajman city in the UAE. The present paper is a small-scale study that employed the qualitative design method to gather responses to the research question, depending on semi-structured interviews. A thematic analysis was used to analyze data collected from 101 teachers, parents, special education teachers, and coordinators.
In light of the results, the study revealed that schools faced obstacles, which hindered the effective identification during distance learning. Findings referred these barriers to lack of knowledge and awareness about students with SLD, lack of instructions, resources, and data, as well as lack of assessment reliability and validity and poor student evaluation. In addition, there was lack of communication and coordination among teachers, special education teachers, coordinators, and parents. Lastly, the absence of a team of experts and trained teachers in the field played an important role.
The study wrapped up with a list of recommendations for effective identification in an online environment such as training teachers on inclusive education, establishing a well-articulated and efficient policy for identification methods in the schools, and raising awareness within the school community. Also, stakeholders and policymakers are urged to examine the problem from different perspectives to overcome all the barriers hindering effective identification. Finally, various factors posed limitations to the study, including restricted access to schools, restrictive rules of social interaction during the pandemic, and having to rely solely on semi-structured interviews.
The significance of this study arises from the sacristy of research, at least locally, and the increasing numbers of cases of learning difficulties, as well as the lack of awareness among all stakeholders on dealing with such cases.
Keywords: distance learning, identification, COVID-19, students with a specific learning disorder.BUI
The impact of using self-learning platforms on students' performance and motivating them to learn mathematics in Cycle/3 schools in the Emirate of Abu Dhabi.
No full textThe United Arab Emirates has worked for several years to consolidate the concept of self-learning among school students. The Ministry of Education (MOE) and the Emirates Schools Establishment (ESE) have provided schools with educational platforms based on artificial intelligence, giving students a greater opportunity for self-learning and making them more self-reliant. Alef Education platform started working in government schools in 2016 and is now considered the most important educational platform in schools because of the support it provides to students to develop their performance. This mixed study aims to identify the impact of self-learning platforms on students' performance and motivation towards learning mathematics in cycle/3 schools in the Emirate of Abu Dhabi. The study targeted 1042 students of both sexes from the Grade/10 and Grade/12 in its advanced and general streams belonging to four secondary schools in the Emirate of Abu Dhabi and 40 mathematics teachers from the same schools. 285 students and 19 teachers responded.
The current study revealed the important role of using self-learning platforms in improving students' performance in mathematics and motivating them to learn it. Analysis of students' responses indicated a relatively large influence of the role of self-learning; That is 79.8%. The impact of using these platforms varies with the level of students. Teacher and student responses were significantly correlated. Educators suggested updating the existing platforms to more interactive platforms with simpler and gradual curricula that are compatible with all levels of students and various assessment tools to improve student performance and motivation in mathematics, in addition to using only one platform to avoid student distraction.
This study will provide an opportunity for education decision-makers in the United Arab Emirates to develop a system of self-learning platforms to become more sophisticated and effective in improving students' learning opportunities in the future. On the other hand, this study opened the door for future researchers to expand the scope of research on these platforms to include other subjects such as languages and sciences
Arabic Sign Language Recognition: A Deep Learning Approach
No full textWith more than 300 sign languages across the world, sign interprets are not always available to translate spoken words into sign language and vice versa. As people with hearing and speech impairments rely on Sign Language for communication, this would limit their communication with others. A solution for this would be utilizing Sign Language Recognition systems, which allow for communication between users of the sign language and those who do not without the need for interpreters.
As we consider the success of Deep Learning for Computer Vision tasks, we observe the advantage it can provide for Arabic Sign Language Recognition. For this research, we have two aims. First, we would like to review the current status of research in Arabic Sign Language Recognition using Deep Learning and find research gaps. Second, we aim to build a Sign Language Recognition system that bridges the gap.
We achieve this through a systematic review that identifies primary studies using deep learning models for Arabic Sign Language Recognition. Out of 414 identified studies, 67 were deemed of relevance to our topic. Out of those, 32 studies passed our full selection procedure. We were able to discover patterns in research and find that the biggest issue is data collection as current datasets don’t offer enough variety and are not representative of real-life scenarios. Current methods are either too expensive, or easily affected by the surrounding environment.
Thus, for the second part, we offer a solution for data collection using MediaPipe, which allow us to collect data directly through the webcam. We are able to leverage this framework to build a recognition system for Emirati Sign Language that recognizes the signs for the seven Emirates. We used an LSTM model and achieve an accuracy of 100% in the testing dataset
Factors Influencing Students’ Achievements in the Content and Cognitive Domains in TIMSS 4th Grade Science and Mathematics in the United Arab Emirates
No full textTrends in International Mathematics and Science Study (TIMSS) is a comparative interna
tional assessment study conducted by the International Association for the Evaluation of Educational
Achievement (IEA). TIMSS aims to study how educational opportunities are provided for students
and what factors are associated with these opportunities. The purpose of this study was to examine
the student factors in the United Arab Emirates that have an association with grade 4 students’
TIMSS 2015 results in the content and cognitive domains in the subjects of mathematics and science.
The study adopted the quantitative research approach through the data analysis of TIMSS 2015
for grade 4 students in these subjects. The study sample consisted of 21,177 students enrolled in
372 UAEprivate schools and 186 public schools. The percentage of grade 4 girls who participated
in the study was 48%, while the percentage of boys was 52%. A multiple linear regression analysis
Citation: Balfaqeeh, A.; Mansour, N.;
Forawi, S. Factors Influencing
Students’ Achievements in the
Content and Cognitive Domains in
TIMSS 4th Grade Science and
Mathematics in the United Arab
Emirates. Educ. Sci. 2022, 12, 618.
https://doi.org/10.3390/
educsci12090618
Academic Editor: James Albright
Received: 23 June 2022
Accepted: 8 September 2022
Published: 13 September 2022
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Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
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conditions of the Creative Commons
Attribution (CC BY) license (https://
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4.0/).
was conducted to examine the most influential student factors that impact on science and maths
achievement. Structural equation modeling (SEM) was implemented to examine the relationships
between student factors and the content and cognitive domains of mathematics and science in the
TIMSS 2015 results. The findings showed that the student factors with a positive association with stu
dent achievement were having breakfast on school days, engaging teaching in mathematics lessons,
liking learning science, and confidence in mathematics and science. There was a non-significant
correlation between gender and mathematics and science achievement. A surprising finding was that
“liking learning mathematics” had a negative association with student performance in that subject.
There was a positive association between student engagement and mathematics achievement, while
the association between the engagement in science lessons and student performance was found to
be insignificant
Relational pre‑impact assessment of conventional housing features and carbon footprint for achieving sustainable built environment
No full textSustainable comfortable living requires comprehensive energy consumption planning for
the housing habitat. Besides other energy planning considerations, the variations in physi
cal features of built facilities, their environmental interaction, and resulting operational life
cycle carbon footprint are an important focus in contemporary research. Therefore, this
research aims to explore the relationship between the physical features of the built facil
ity and the resulting carbon footprint for conventional housing designs. A combination of
conventional Malaysian model housing units was developed in 3D virtual prototypes by
building information modeling, and regression analysis was used to investigate the envi
ronmental impact paradigm of the built facility. Correspondingly, an operational CO2 pre
assessment was also examined by the partial life cycle assessment technique during the
early stages of design and planning. The results of this study show a positive and statisti
cally significant linear relation of carbon footprint with the area, volume, and power rating
parameters. The outcome of this study is imperative for designing resource-efficient liv
ing facilities and achieving a sustainable built environment through a proactive life cycle
assessment of housing construction projects