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MPox-DenseConvNet: A Transfer Learning Based Convolutional Neural Network for Monkeypox Detection and Assessment using Color Models
No full textMonkeypox, a zoonotic orthopoxvirus, unintentionally
produces smallpox-like sickness in people, though with a
far lower death rate. Despite the fact that Deep Networks
have been extensively used for visual inspection of such
diesases, the majority of works have frequently relied their
analysis on the results produced by a particular network
without taking the response of the colour channels to
classification findings into account. Deep learning has
recently shown to have enormous potential for image based diagnosis, including the detection of skin cancer, the
identification of tumour cells, and the COVID-19 patient
diagnosis through chest radiography. As a result, a similar
application may be used to identify the sickness associated
with monkeypox as it impacted human skin. This image
can then be obtained and employed to identify the illness.
This work focused on investing the prominent color
channel for Convolution Neural Network (ConvNet) based
monkeypox classification using skin images. For this
purpose, a transfer lerning based classification architecture
named MPox-DenseConvNet with fine tuning is designed.
Three colour channels namely RGB, HSV and YCbCr are
analyzed using proposed MPox-DenseConvNet. The
outcomes demonstrated that the colour channel employed
had an impact on the performance of the classification. The
results also confirmed that the HSV color channel has
outperformed of all the colour channels taken into
consideration
Critical Legal Issues associated with Arbitration Agreement under the UAE Arbitration Law
No full textDespite its high cost and long procedures in some cases, arbitration may be perceived as a safe
dispute resolution mechanism, at least in complex and large disputes. This may be owed to the
customary unified standards internationally, the relatively high procedural flexibility, and reduced
uncertainty. As arbitration is an exception to litigation depriving parties of the default litigation
right; an arbitration agreement validity is key. The paper explores arbitration agreement forms
under the UAE laws and identifies critical matters affecting its validity
By nature, a social animal: an exploration of perceptions of online group work
No full textThis research, exploring the value of online group work through
postgraduate student perceptions of engagement, surveyed 71
students and interviewed 11, over three rounds of data collection.
Participants were taught postgraduate students in a higher educa
tion institution education faculty in the United Arab Emirates. The
f
indings are relevant for our understanding of online group work;
assessment design; communication; and community building.
Research took place over a 12-month period, beginning before
COVID-19, in February 2020 with face to face teaching, and ending
during the third term of fully online teaching in January 2021. This
phenomenological research charts student perception and attitude
changes. Social Cognitive Theory, the Technology Acceptance
Model and Social Constructivism form the theoretical framework
within which participant engagement, behaviour and perception
are explored. The findings provide a reflective analysis regarding
student perception, engagement and acceptance of online group
work as a valid approach to meeting learning outcomes
Agent-Based Modelling and Simulation of Crowd Evacuation: Case Study for Electric Train Cabin
No full textThe agent-based simulation is a cutting-edge
example of a fresh and clever technique intended to fulfil these
goals. Numerous academics and researchers investigated the
crucial merits, applicability, and contributions of this approach in
a range of extreme situations and catastrophic scenarios. Their
numerical analysis and mathematical simulations showed that the
agent-based simulation framework is essential for providing a
thorough knowledge of pedestrian behavior and human mobility
in difficult emergency conditions. This work uses egress modelling
to explore crew procedures' impact on evacuating train cabins
under different fire scenarios.
Based on the numerical simulations and analyses conducted
via the Netlogo software package, Author’s found that two
employees (contracted by the railroad company) in the lounge
coach and two train hosts in the first-class coaches under
emergencies achieve an efficient step toward evacuating a larger
number of passengers. Nonetheless, passengers should be aware
and familiar with the locations of these exit points, emergency
signs, and egress paths to avoid any congestion, stampedes, and
social attachment that may contribute to losses of life and delay
the evacuation process. Also, an agent-based simulation is
remarkably practical for determining intelligent practices and
effective methods that can be adopted and followed to accelerate
the evacuation process compared with other methods that are very
difficult or unethical to apply, such as subjecting a group of people
to a real fire event and predicting some methods to evacuate them
based on the results
The mediating role of technology orientation in the relationship between risk management and performance of Dubai smart infrastructure projects
No full textDubai's infrastructure has been ranked 7th globally due to its efficiency, effectiveness, and use of advanced technologies. The success of Dubai's infrastructure can be attributed to five major factors; firstly, the government's dedication to ensuring that Dubai's infrastructure is among the best in the world. Secondly, the availability of cheap and plentiful labor from South Asia, which reduces construction costs. Thirdly, the honest and diligent administration of the Road and Transportation Authority (RTA), which ensures timely project delivery within budgetary limits. Fourthly, the RTA's role in project allocation, design approval, and safety compliance. Finally, Dubai's strict traffic and vehicle laws, which ensure safety and penalize violators. Hence, primary research was designed to investigate if technological innovation is impacting positively on the performance of the projects of smart infrastructure but it also turned risk management further complicated. The research was conducted on a private construction agency in the United Arab Emirates. The survey tool used to collect data from its participants and 100 responses considered to analyses. The primary research findings are consistent with the literature review, indicating that risk management is crucial in optimizing smart infrastructure projects. The study revealed that respondents recognized the significance of all stages of risk management in the context of smart infrastructure. However, the research identified that organizations in Dubai need to improve their risk management practices as they struggle to effectively mitigate risks and implement risk mitigation plans. Despite this, respondents were content with the early warning practices and pre-monitoring measures in place to identify potential risks. Primary research recommending to cconduct a comprehensive risk assessment, implement robust security measures, develop a disaster recovery plan, conduct regular security audits, train employees on cyber security best practices, collaborate with cyber security experts, and stay up-to-date with cyber security trends to further enhance the efficiency and outcome of smart infrastructure and lower the risks
Exploiting Functional Discourse Grammar to Enhance Complex Arabic Relation Extraction using a Hybrid Semantic Knowledge Base - Machine Learning Approach
No full textRelation extraction from unstructured Arabic text is especially challenging due to the Arabic language com plex morphology and the variation in word semantics and lexical categories. The research documented in
this paper presents a hybrid Semantic Knowledge base - Machine Learning (SKML) approach for extracting
complex Arabic relations from unstructured Arabic documents; the proposed approach exploits the princi ples of Functional Discourse Grammar (FDG) to emphasise the semantic and pragmatic properties of the
language and facilitate the identification of relation elements. At the initial phase, the novel FDG-SKML re lation extraction approach deploys a lexical-based mechanism that utilises a purposely built domain-specific
Semantic Knowledge to encode the semantic association between the identified relations’ elements. The eval uation of the initial stage evidenced improved accuracy for extracting most complex Arabic relations. The
initial relation extraction mechanism was further extended by integrating its output into a Machine Learn ing classifier that facilitated extracting especially complex relations with significant disparity in the relation
elements’ presence, order, and correlation. Using Economics as the problem domain, experimental evalua tion evidenced the high accuracy of our FDG-SKML approach in complex Arabic relation extraction task and
demonstrated its further improvement upon integration with machine learning classifiers
The Impact of Teacher Leadership on Teacher’s Performance and Students’ Development for School Improvement: a case study of Dubai Private Kindergarten
No full textTeachers' leadership is essential to school success, since with an effective leadership style, a teacher will develop and perform well in both teaching and learning and as a result, students' achievement will automatically increase. This study examines the impact of teacher leadership practices on the performance and achievement of teachers and students. A case study was conducted using a mixed data collection approach. The first step was to complete a self-administered questionnaire among teachers in a Dubai private kindergarten. A non-probability sampling technique was then used to conduct semi-structured interviews with two head coordinators and two lead teachers. The study was guided by the following questions: to what extent do teachers practice teacher leadership, what characteristics or factors are involved in an effective teacher leadership style, how they influence school performance and evaluation, and what role teacher leadership plays in the overall performance of teachers and students, the collective performance of schools, and school management. The analysis of data showed that there is a positive relationship between effective lead teachers and the improvement of the teaching and learning process. This includes both teachers' performance and students' outcomes. The results of the quantitative analysis of the study indicated that teachers are often involved in certain leadership roles, as measured by questionnaire items. In contrast, other activities such as leading action research or participating in professional groups, are practiced infrequently. Data from interviews revealed that teachers perceive that school administrators generally encourage them to take on leadership roles. However, administrators also heavily depend on group-based teachers to lead. In addition, school contextual factors, such as lack of time, resource shortages, overload of work, and leadership style, as well as teachers' assumptions about and willingness to assume additional leadership responsibilities, are obstacles to maximizing the potential for teacher leadership in this kindergarten. This study added and narrowed the current research on teacher leadership's impact on both teachers' and students' development in the UAE to a private kindergarten in Dubai. It should be noted that the findings of this study cannot be generalized and are only applicable to certain contexts, which constitutes a limitation of the study. For this purpose, It is suggested that teacher leadership should be promoted on a broader scale in UAE schools. Further research can focus on what teacher leadership practices are most appropriate and how school leaders can deal with crises for school improvement
Understanding the Intention to Use the Metaverse in IT Companies Using a Hybrid SEM-ANN Approach.
Get PDFWhile embracing the metaverse within Information Technology (IT) companies could present unique opportunities, it also brings about challenges in adoption behavior. However, research on the factors influencing intentional behavior to use the metaverse in IT companies is scarce. To bridge this gap, this study develops a research model that integrates elements from the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), Task-Technology Fit (TTF), and awareness studies, and hypothesizes key variables such as performance expectancy, effort expectancy, and social influence. Through a comprehensive survey of 234 participants, the research model is evaluated employing a unique combination of Structural Equation Modeling (SEM) and Artificial Neural Network (ANN), which serve as advanced modeling techniques. The SEM and ANN analyses elucidate intricate relationships and make predictions about adoption behavior, while uncovering patterns and insights into metaverse adoption in IT companies. Although the primary focus is on SEM and ANN, this study also utilizes Partial Least Squares (PLS) in the research design. It identifies and discusses key findings from descriptive analysis, measurement model assessments, and structural model assessments. Furthermore, the ANN results and sensitivity analysis paint a more nuanced picture of metaverse adoption behavior in the IT sector, providing valuable predictions and insights. In addition to the theoretical contributions, the findings offer practical implications for IT companies and suggest future research directions to help them make informed decisions related to the implementation and use of the metaverse. Overall, this study contributes to the growing body of literature on the metaverse and its application in the business landscape, with specific emphasis on IT companies
Reusing Minarets as a Passive Cooling (Wind Catcher/Solar Chimney): A Case Study in the Emirate of Sharjah
Get PDFThe number of mosques in the United Arab Emirates exceeds 9,000 mosques, including approximately 3,000 mosques in the Emirate of Sharjah alone. The minaret accompanies the design of each mosque, which is equivalent to the number of mosques, and more, since some mosque designs have more than one minaret.
In this research, the idea of repurposing minarets or adding new uses to them is studied, such as using minarets as a passive cooling method, such as using them as wind catchers/solar chimneys that contribute to the process of directing the wind to the prayer hall and work to increase thermal comfort through environmentally friendly passive cooling methods.
The Luqman Mosque in the Al Tay area in Sharjah was studied as a model for a case study. It was drawn using the IESVE computer simulation program, and then different scenarios were created for the idea of creating a connection between the prayer hall and the minaret by making doors and windows. After that, the opening and closing of windows and doors in each case were studied. One side of the prayer hall and the minaret, in addition to scenarios for opening the windows of the dome and adding a divider in the minaret, divides it into two parts. It should be noted that the number of virtual scenarios reaches 34 designs. The results are then analyzed, conclusions are drawn, and the results are then evaluated.
The study revealed the possibility, benefit, and feasibility of the idea of repurposing the minaret in reducing overall energy consumption and the impact of thermal comfort elements such as air temperature, relative humidity, wind movement, mean radiant temperature and CFD in the process of repurposing the minaret
The Role of Artifical Intelligence in Enterprise Risk Managment
No full textIn the modern world, artificial intelligence is not a new concept. Companies, both large and small have incorporated artificial intelligence in risk management. AI can be an effective tool in business since it drives cost efficiencies and operational awareness. Businesses presently use artificial intelligence to achieve strategic transformation, including better risk management. Effective risk management is relatively considered far from becoming an innovation inhibitor, but it’s pivotal to the successful adoption of artificial intelligence. One the main challenges for organizations is less about dealing with new risks or existing risks, but getting the right framework to handle the risks in a timely manner. To avoid issues with risk management, organizations must learn how to reap the benefits of AI. This will make them prepared to handle future risks. Therefore, management and boards must develop a meaningful understanding of new risk management technologies, including the existing and potential uses within organizations. They also need to take a firm grip on the implications of artificial intelligence from a risk perspective. In this research, the aim is to evaluate the effectiveness of artificial intelligence in enterprise risk management, and especially on the context of increased accuracy, efficiency, and speed of decision-making. This research will uncover the biggest challenges that organizations experience when incorporating AI for enterprise risk management and discuss how organizational management can leverage AI to improve enterprise risk management. To complete the research, quantitative data will be collected from different sources, and then analyzed for implications in risk management