Middle East College

Monitoring and managing potential infected patients of COVID-19 is still a great challenge for the latest technologies. In this work, IoT based wearable monitoring device is designed to measure various vital signs related to COVID-19. Moreover, the system automatically alerts the concerned medical authorities about any violations of quarantine for potentially infected patients by monitoring their real time GPS data. The wearable sensor placed on the body is connected to edge node in IoT cloud where the data is processed and analyzed to define the state of health condition. The proposed system is implemented with three layered functionalities as wearable IoT sensor layer, cloud layer with Application Peripheral Interface (API) and Android web layer for mobile phones. Each layer has individual functionality, first the data is measured from IoT sensor layer to define the health symptoms. The next layer is used to store the information in the cloud database for preventive measures, alerts, and immediate actions. The Android mobile application layer is responsible for providing notifications and alerts for the potentially infected patient family respondents. The integrated system has both API and mobile application synchronized with each other for predicting and alarming the situation. The design serves as an essential platform that defines the measured readings of COVID-19 symptoms for monitoring, management, and analysis. Furthermore, the work disseminates how digital remote platform as wearable device can be used as a monitoring device to track the health and recovery of a COVID-19 patient.

Abstract Facial Detection and recognition research has been widely studied in recent years. The facial recognition applications plays an important role in many areas such as security, camera surveillance, identity verification in modern electronic devices, criminal investigations, database management systems and smart card applications etc. This work presents deep learning algorithms used in facial recognition for accurate identification and detection. The main objective of facial recognition is to authenticate and identify the facial features. However, the facial features are captured in real time and processed using haar cascade detection. The sequential process of the work is defined in three different phases where in the first phase human face is detected from the camera and in the second phase, the captured input is analyzed based on the features and database used with support of keras convolutional neural network model. In the last phase human face is authenticated to classify the emotions of human as happy, neutral, angry, sad, disgust and surprise. The proposed work presented is simplified in three objectives as face detection, recognition and emotion classification. In support of this work Open CV library, dataset and python programming is used for computer vision techniques involved. In order to prove real time efficacy, an experiment was conducted for multiple students to identify their inner emotions and find physiological changes for each face. The results of the experiments demonstrates the perfections in face analysis system. Finally, the performance of automatic face detection and recognition is measured with Accuracy.

The Internet of Things with its enormous growth widens its applications to the living environment of the people by changing a home to smart home. Smart home is a connected home that connects all type of digital devices to communicate each other through the internet. These devices form a home area network where communications are enabled by different protocols. As these devices are designed by different companies with different standards and technologies there is a problem exists in their connectivity. This paper aims at describing the wireless standards used in home network and how these protocols face the connectivity challenges in the smart home network.

Technology and innovation empower higher educational institutions (HEI) to use different types of learning systems—video learning is one such system. Analyzing the footprints left behind from these online interactions is useful for understanding the effectiveness of this kind of learning. Video-based learning with flipped teaching can help improve student’s academic performance. This study was carried out with 772 examples of students registered in e-commerce and e-commerce technologies modules at an HEI. The study aimed to predict student’s overall performance at the end of the semester using video learning analytics and data mining techniques. Data from the student information system, learning management system and mobile applications were analyzed using eight different classification algorithms. Furthermore, data transformation and preprocessing techniques were carried out to reduce the features. Moreover, genetic search and principle component analysis were carried out to further reduce the features. Additionally, the CN2 Rule Inducer and multivariate projection can be used to assist faculty in interpreting the rules to gain insights into student interactions. The results showed that Random Forest accurately predicted successful students at the end of the class with an accuracy of 88.3% with an equal width and information gain ratio.

The adverse environmental effects from fossil fuels and their depletion through time push the world to consider sustainable and environmentally friendly forms of energy sources. The advancement put forward to improve the performance of Solar energy has made it to be one of the potential alternative energy sources in the years ahead. This paper, therefore, assesses the strength, weakness, opportunities and threats (SWOT) of using solar energy. The suitability of solar energy to the environment, minimal cost in the long ran, and its versatility are few to mention among other significant advantages of this energy source to get noticeable attention in an effort to substitute fossil fuels. The expected cost reduction through time with the technology advancement is also taken as opportunity to use solar energy. However, using solar energy has also weaknesses and threats which yet require further attentions. The low efficiency, high initial cost, energy storage requirement are some of the challenges. In addition, shifting the energy source for industries from fossil fuel to solar energy remains as a challenge due to the utilities which are already in place and working with conventional fuels. Although some of the weaknesses and threats to solar energy application still exist, through technology advancement most of the problems would be addressed in the future.

Nanotechnology has been widely used in many fields including in soil and groundwater remediation. Nanoremediation has emerged as an effective, rapid, and efficient technology for soil and groundwater contaminated with petroleum pollutants and heavy metals. This review provides an overview of the application of nanomaterials for environmental cleanup, such as soil and groundwater remediation. Four types of nanomaterials, namely nanoscale zero-valent iron (nZVI), carbon nanotubes (CNTs), and metallic and magnetic nanoparticles (MNPs), are presented and discussed. In addition, the potential environmental risks of the nanomaterial application in soil remediation are highlighted. Moreover, this review provides insight into the combination of nanoremediation with other remediation technologies. The study demonstrates that nZVI had been widely studied for high-efficiency environmental remediation due to its high reactivity and excellent contaminant immobilization capability. CNTs have received more attention for remediation of organic and inorganic contaminants because of their unique adsorption characteristics. Environmental remediations using metal and MNPs are also favorable due to their facile magnetic separation and unique metal-ion adsorption. The modified nZVI showed less toxicity towards soil bacteria than bare nZVI; thus, modifying or coating nZVI could reduce its ecotoxicity. The combination of nanoremediation with other remediation technology is shown to be a valuable soil remediation technique as the synergetic effects may increase the sustainability of the applied process towards green technology for soil remediation.

Purpose Historically, investments in innovation are perceived as one of the paramount decisions businesses opt to thrive and the impact of such investments on businesses' market performance is well documented in the literature. However, the environmental aspects of making such investments are yet to be addressed by the firms, which in turn, present considerable damage to the environment. Coupling with the natural resource-based view (NRBV) and the stakeholder theory of the firm, this research builds on an earlier work of Khalil and Nimmanunta (2021) in an attempt to examine the link between innovation and firms' environmental and financial value. The authors extend their analysis and document a more consistent approach to measuring environmental innovation which allows the authors to investigate the firms from three additional economies with respect to firms' investments in both traditional and environmental innovations. Design/methodology/approach The underlying models are tested using the time fixed-effects panel regression by utilizing information from publicly traded companies of ten Asian economies, including Japan, Hong Kong, Taiwan, Thailand, Turkey, Malaysia, Singapore, India, Indonesia, and Saudi Arabia. The reported sample covers annual firm-level ESG data obtained from Thomson Reuters' Datastream and Refinitiv Eikon during the 2015–2019 period. Findings This research offers support to the conventional wisdom that innovation is advantageous to the firms' market value. The authors further decompose innovation into traditional innovation and environmental innovation. The findings of this research suggest that traditional innovation is favorable only for the firms' market valuation and traditional innovation is strongly ineffectual for the environment – traditional innovation produces sizeable environmental distress by contributing substantially to carbon emissions. In contrast, the resultant effects of investments in environmental innovation are evident to be instrumental for both firms' financial performance and the environment. Research limitations/implications This research has primarily focused on only two components of a company's environmental performance: reduction in carbon emissions (CO2) and corporate social responsibility (CSR). Given the complexity of firms' environmental strategies and the multidimensionality of the variable, which encompasses a wide range of corporate behavior in terms of relationships with communities, suppliers, consumers, and broader environmental responsibilities broadening the scope of the study by including other important aspects of environmental sustainability is, therefore, critical. Practical implications The findings of this research signify environmental innovation as one of the vital investment approaches as firms can exploit benefits related to the market from firms' sustainable practices, developing eco-friendly processes by introducing steady yet systematic chains of green products and services. Such products and services may have a feature of enhanced functionality with a better layout in terms of improved product life with better recycling options, and lower consumption and exploitation of energy and natural resources. These sustainable practices would be advantageous for the firms regarding the possibility of setting prices above the standard level through establishing green brands and gaining market share of environmentally anxious consumers. For those companies that are striving to take the leading role in the green industry and longing to seek superior returns on the companies' environmental investments, these benefits, in particular, are exceptionally critical to them. Originality/value The linkage between firms' financial and environmental performance in the context of simultaneous inclusion of both green and traditional innovations remains unclear and is yet to be investigated by researchers. Thus, this research shed light on the role of environmental innovation and traditional innovation on firms' environmental performance and financial performance. The authors utilize a novel dataset with a clear indication of measuring different elements of innovation that allows us to develop a more robust approach to corporates' environmental, social and governance (ESG) performance metrics having the slightest biases related to transparency and firm size.

This paper explores opinion mining using supervised learning algorithms to find the polarity of the student feedback based on pre-defined features of teaching and learning. The study conducted involves the application of a combination of machine learning and natural language processing techniques on student feedback data gathered from module evaluation survey results of Middle East College, Oman. In addition to providing a step by step explanation of the process of implementation of opinion mining from student comments using the open source data analytics tool Rapid Miner, this paper also presents a comparative performance study of the algorithms like SVM, Naïve Bayes, K Nearest Neighbor and Neural Network classifier. The data set extracted from the survey is subjected to data preprocessing which is then used to train the algorithms for binomial classification. The trained models are also capable of predicting the polarity of the student comments based on extracted features like examination, teaching etc. The results are compared to find the better performance with respect to various evaluation criteria for the different algorithms.

The desalination industry is increasingly growing in the Middle East and North Africa (MENA) due to the increase in water demand and reduction in desalination costs resulting from advances in desalination technologies. Within the next 20 years, it is estimated that the MENA region will become so dependent on desalination technology for sustainable water supply that a minimum of 50,000 additional technical experts of various professional levels will be needed to service the desalination industry. Over the last decade, desalination experts, industries and manufacturers have launched awareness programs for building capacity in the MENA where there is a greater need for human resources to cater to the needs of the huge water market. Only a few institutions have implemented some academic programs and provided short courses and workshops in desalination; other institutions developed web-based training to the desalination community. But these actions cannot compensate for the need of real institutional training and education as well as for research and development. Capacity-building is urgently needed at different levels: operators, educators, academics and management. Achieving this target requires more specific training efforts in desalination technologies to encompass the principles, practice, operation and maintenance, design, human resources management as well as research and development. A capacity-building program is necessary not only to operate and improve existing plants but also to develop new sustainable technologies. Wastewater treatment and water reuse technologies should also be included in capacity-building programs to achieve a better integration in water resources management. An overview of a capacity-building strategy and perspectives for desalination in MENA are presented. The Middle East Desalination Research Center’s approach to enhance human resources and expertise in the region via training, academic education and research and development is outlined.

The Sultanate of Oman faces challenges, like rapid growth of waste generation, which calls for an optimum waste management strategy. Oman has witnessed the production of 1.5m t of municipal solid waste in 2012, which is expected to elevate to 1.89m t in 2030. This rapid increase needs to be tackled to reduce the generation rates along with the environmental impacts. Currently, there are no treatment facilities in Oman other than limited recycling, and therefore dumping waste into the landfill is the only ultimate way to dispose solid waste. Hence, this study is an initiative to improve the waste managing system in Oman by proposing optimum waste-to-energy technology using an analytical hierarchy process, manually and through expect choice software as well. In the present study, the identified important parameters were considered in an analytical hierarchy process model to rank the waste-to-energy technology alternatives. Based on the survey conducted, the most important criteria were environmental and economic, with the local priority vector of 0.400 and 0.277, respectively. This research concludes that the most suitable waste-to-energy technology for Oman, on the basis of the identified criteria, is anaerobic digestion followed by fermentation and incineration, which will help to reduce the amount of waste, greenhouse gas emissions and developing and maintaining costs of landfills.

The Blockchain is a process which divide the data into blocks which are secured through unique cryptography algorithms to ensure privacy and security. The blocks are connected to each other in mesh topology which create a chain. Blockchain is start to be utilized through different domain such as banking, government, defense and educations. Today the higher education's institutions are grants to run campuses in different cities and different countries. Hence, securing the data transactions such as student profiles and certifications is considering significant concerns for security professions. Hence, this research is about highlighting the studies which cover the possibility of adopting Blockchain in education institutions. The concluded recommendation will be generated based on investigations running in the higher education field.

The role of international students as catalysts for internationalization and related reforms in the UK higher education sector is increasing. With the growing number of international students, administrators and academics are identifying ways to enable international students to adapt to the UK environment and enhance their experiences as students. This article examines the academic and other social problems that international students who pursue programmes offered by the universities in the UK encounter. It also suggests mechanisms that universities may adopt so that international students have a smooth academic progression and a comfortable social life. Describing the roles of different stakeholders in supporting international students, and the need to create a university-wide awareness of the importance of the presence of the international students in the university campus, the article suggests how universities may track the performance of drivers that foster the experiences of international students.

The purpose of this study is to examine the possibility of using plastic bottles in concrete block. The plastic bottles were used to create voids at equal distance between them in the masonry units. Concrete was placed around each bottle to encase it in the masonry units. The study utilized 500-mL plastic bottles placed inside concrete masonry units and analyzed the compressive strength. The testing for compressive strength was determined according to the ASTM C140 standard. Results from this study were deemed reasonable due to the testing of concrete cylinders as a control of compressive strength for the concrete blocks from Oman's market. This study shows 57% difference in the strength by using plastic bottles compared to local concrete blocks. This proves the necessity for further research regarding concrete mix design, amount of cement and properties of local concrete blocks as well as other technical and non-technical aspects to determine the appropriate mix design and feasibility in the production industry.

Very little is known about the impact of the different types of feedback on students’ academic performance. This article explores students’ preference in the use of audio and written feedback and how each type of feedback received by students impacts their academic performance in subsequent assignments. The study involved 68 students who were divided into two groups that received either audio or written feedback in their first assignment which was then recalled and applied into the second assignment. An analysis of results obtained in the second assignment was conducted and comparisons made between students in the audio and written feedback group. Students were also surveyed using an online questionnaire to ascertain their perceptions about the type of feedback they had received. The study established that the type of feedback received did not impact students’ grades in the subsequent assignment. In addition, while students were broadly positive about audio feedback, they indicated a strong preference for written feedback in future assignments. The study recommends, among other things, further investigation into the link between students’ learning styles and their preferences for different types of feedback.

IOT has proven to be the most emerging technology where millions of devices can connect to the internet which makes the life feasible without any human intervention. This paper has analysed the challenges associated with IOT technology. Two major issues security and privacy of data and user information has discussed in detail. In this research paper solution of major issue of security is also proposed. One of the important requirements of IOT is to have a quality of service where the data among the devices should be as high as possible without degrading the performance. In this paper, we have proposed a software model based on Software Defined Network (DTN). Software Defined Network is a technology that increases the performance of the network and reduces the hardware usage and also provides a better security and privacy compare to the traditional networks. Lastly, the paper has discussed about the architectural design of SDN and suitable for IoT and Ad-hoc networks.

With the rapid development of road infrastructure, the volume of vehicle on the road network increases which leads to traffic Congestion. The same scenario exists in the Sultanate of Oman. Traffic congestions are amongst the top list of the problems faced in Muscat and other cities in the Sultanate of Oman. This is mainly caused due to the rapid up rise in the number of vehicles in a short span of time. To overcome such impact of traffic congestions, it is required to develop an IoT Based traffic control system. The proposed system would be based on the measurement of the actual traffic density on the road. This would be achieved using a real time video and image processing techniques. Wherein the images captured and are stored in the server, which will be compared with the real time image captured via camera to identify the density. The theme is to control the traffic by determining the traffic density on each side of the road and enabling a controlling option of the traffic signal to the user through a software application.

Matrix representations of Maxwell's equations are very well-known. This is evident from the numerous studies on the close resemblance between the Maxwell equations in spinor form to the Dirac equation. However, all these matrix representations lack an exactness, as they assume the media to be homogeneous or/and time-independent. Moreover the final representation is given in terms of a pair of matrix equations. We present a matrix representation of Maxwell's equations in an inhomogeneous linear medium, in presence of sources. It is shown that such a representation necessarily requires 8 × 8 matrices and an explicit representation for them is presented.

Cloud computing is a new computing model which is based on the grid computing, distributed computing, parallel computing and virtualization technologies define the shape of a new technology. It is the core technology of the next generation of network computing platform, especially in the field of education, cloud computing is the basic environment and platform of the future E-learning. It provides secure data storage, convenient internet services and strong computing power. This article mainly focuses on the research of the application of cloud computing in E-learning environment. The research study shows that the cloud platform is valued for both students and instructors to achieve the course objective. The paper presents the nature, benefits and cloud computing services, as a platform for e-learning environment.

Soil is the most important source of natural radiation which can pass on to the food chain and the air, contributing to the internal dose received by the population. Human activities can modify the natural concentrations of radionuclides by the release of residues or effluents to the environment, which cause the accumulation of radioactive elements. In this study, the radiological hazard parameters due to the natural radioactivity, such as, Radium equivalent activity (Ra_eq), Representative level index (RLI), Activity utilization index (AUI), Absorbed dose (D), Annual Effective Dose equivalent (AEDE), Annual gonadal dose equivalent (AGDE), External hazard index (H ex ), Internal hazard index (H in ) and Excess lifetime cancer risk (ELCR) are assessed from the sugar industrial effluent disposed soil. The calculated radiological parameters are compared with that of soils around different industries across the world. The recorded average value of AUI and ADGE is 0.713 and 316.72 μSv/y, respectively, are higher than the globally approved values (0.07 and 300 μSv/y, respectively). Further, the average values of RLI and ELCR are closer to the world average values. The Pearson correlation analysis and cluster analysis are employed to analyse the data and identify the existing relationships between the radiological hazard parameters with the natural radionuclides.

Migration of methane ( $CH_4$ ) gas from landfills to the surrounding environment negatively affects both humankind and the environment. It is therefore essential to develop management techniques to reduce $CH_4$ emissions from landfills to minimize global warming and to reduce the human risks associated with $CH_4$ gas migration. Oxidation of $CH_4$ in landfill cover soil is the most important strategy for $CH_ 4$ emissions mitigation. $CH_4$ oxidation occurs naturally in landfill cover soils due to the abundance of methanotrophic bacteria. However, the activities of these bacteria are influenced by several controlling factors. This study attempts to review the important issues associated with the $CH_4$ oxidation process in landfill cover soils. The $CH_4$ oxidation process is highly sensitive to environmental factors and cover soil properties. The comparison of various biotic system techniques indicated that each technique has unique advantages and disadvantages, and the choice of the best technique for a specific application depends on economic constraints, treatment efficiency and landfill operations.