Advances in multimedia and interactive technologies book series, 2019
The internet of things (IoT) is a complex system of heterogeneous devices connected to a network.... more The internet of things (IoT) is a complex system of heterogeneous devices connected to a network. While IoT can significantly add value to people's everyday activities around the world, there are numerous security risks and privacy breaches imposed by the IoT landscape. Traditional security solutions are not applicable for the IoT as they require high-end processing capacity. The objective of this chapter is two-fold. Firstly, it provides a comprehensive summary of the recent advancements in the IoT and identifies their vulnerabilities. Secondly, it proposes the paradigm of self-learning as an intelligent and sustainable mechanism that is capable of automatically detecting suspicious activities in the IoT. Overall, this chapter presents a contemporary coverage of the recent developments in the IoT scene, the security and privacy challenges confronting the security experts, a proposal of a self-learning framework for performing health check of the IoT environment, and finally a set of high-level implementation guidelines and conclusions.
This paper describes the first steps in the development of a user ontology for a Smart Health Inf... more This paper describes the first steps in the development of a user ontology for a Smart Health Information Portal (SHIP) to provide collaborative health terms in holistic medicine. Recent trends in the increasing dissatisfaction with conventional medicine and towards embracing holistic model of health for improving quality of life is being witnessed worldwide, more importantly in the technologically advanced countries. Today, advancements in Internet technology and the vast as well as growing source of information available in World Wide Web have the vision to achieve patient education and empowerment of their own health conditions and well-being. Hence, holistic medicine with the theory that each individual has an immense potential for self-healing could be mobilised by harnessing information technology intelligently. To achieve this, it becomes imperative to provide health information specific to each patient's needs in a personalised way due to the diversity in the patient circumstances and the availability of vast and varied information in the Web. A Smart Health Information Portal (SHIP) could provide quality information that is most relevant to patients pursuing holistic treatments. In this paper, we describe the initial development of a user ontology for holistic medical information that integrates conventional medical terms related to cardiac conditions along with Homeopathy and Ayurvedic terms towards providing meaningful complementary heart health information within an existing SHIP.
Every day, big amounts of unstructured data is generated. This data is of the form of essays, res... more Every day, big amounts of unstructured data is generated. This data is of the form of essays, research papers, speeches, patents, scholastic articles, book chapters etc. In today’s world, it is very important to extract key patterns from huge text passages or verbal speeches. This paper proposes a novel method for summarizing multilingual vocal as well as written paragraphs and speeches, using semantic Knowledge Graphs. Using the proposed model, big text extracts or speeches can be summarized for better understanding and analysis. The method uses speech recognition as well as Named Entity Recognition to identify entities from spoken content to create optimized Knowledge Graphs in the English Language.
Affordable and expandable low power networks such as 5G and Low Power Wide Area Networks (LPWAN) ... more Affordable and expandable low power networks such as 5G and Low Power Wide Area Networks (LPWAN) in the public and private network areas have improved network bandwidth capacities and processing performance. Internet of Things (IoT) technologies are increasing in popularity with numerous applications and devices being developed for smart environments and health-related applications. This raises security concerns in these networks, as many IoT devices handle confidential information such as IP/MAC addresses, which could be used to identify a user's location. As a result, there is vulnerability to data tampering by man-in-the-middle (MITM) attacks, which feature two observable characteristics: (1) there is a measurable delay in the session and (2) has unusual travel times compared to prior normal transactions. To improve the detection of these attacks, this paper proposes a novel scheme using a hybrid routing mechanism, which involves appointing dedicated nodes for enforcing routing between IoT devices and users with minimal intervention and workload to the network. The function of dedicated devices with more computational and battery power can provide three advantages: (1) determine secured paths within the network by avoiding suspicious nodes and networks, (2) provide stable travel times (less fluctuations) for a trusted time server (TTS) to improve the accuracy of estimated travel times, and (3) provide packet inspection for security checks. This proposed solution contributes towards increasing the security of IoT networks by enabling the real-time detection of intruders.
Improving the efficiency, effectiveness, and quality of public services has become a growing conc... more Improving the efficiency, effectiveness, and quality of public services has become a growing concern for many governments across the world, and more so with recent popularity of online services, widely referred as e-government services. The application of quality approaches for measuring and improving e-government services has been the subject of much research within the academic world over the last two decades. This chapter discusses the use of key quality approaches to improve services in Jordan's e-government initiatives. As more and more developing countries are adopting e-services as a means of providing quality services to their community and people through the Web, the necessary benchmarking plays an important role. Many traditional quality benchmarking performance measurements have proved futile in improving e-government services due to their quantitative focus. Though qualitative frameworks and measurement approaches such as Six Sigma and Balanced Scorecard have found their success in certain industry sectors, their relevance in the service sector has drawn attention only recently. While some studies have employed such approaches for evaluating projects in information and communication technologies, literature lacks investigations in the e-government sector. To fill this gap, this chapter investigates the application of Six Sigma and Balanced Scorecard approaches to improve quality in Jordanian e-government services.
International Journal of Power Electronics and Drive Systems, Aug 1, 2023
With the increasing use of technologies and digitally driven healthcare systems worldwide, there ... more With the increasing use of technologies and digitally driven healthcare systems worldwide, there will be several opportunities for the use of big data in personalized healthcare. In addition, With the advancements and availability of internet of things (IoT) based point-of-care (POC) technologies, big data analytics and artificial intelligence (AI) can provide useful methods and solutions in monitoring, diagnosis, and self-management of health issues for a better personalized healthcare. In this paper, we identify the current personalized healthcare trends and challenges. Then, propose an architecture to support big data analytics using POC test results of an individual. The proposed architecture can facilitate an integrated and self-managed healthcare as well as remote patient care by adapting three popular machine learning algorithms to leverage the current trends in IoT, big data infrastructures and data analytics for advancing personalized healthcare of the future. This is an open access article under the CC BY-SA license.
2017 Cybersecurity and Cyberforensics Conference (CCC)
The Golden Ratio is the most irrational among irrational numbers. Its successive continued fracti... more The Golden Ratio is the most irrational among irrational numbers. Its successive continued fraction converges with the Fibonacci sequence F(n+1)/F(n) are the slowest to approximate to its actual value.This paper proposes a new method to determine the Golden Ratio with infinite precision and compares the new method with the well-known Fibonacci sequence method. The results show that our proposed method outperforms Fibonacci sequence method. Hence, cryptosystems that use Fibonacci numbers would be much faster using our new method of Golden Ratio computation. This paves way in improving counter measures from security attacks since higher precisions of the Golden Ratio method can take place in cryptographic operations very quickly when used in elliptic curve cryptosystems, power analysis security, and other applications.
Recent studies report doubling numbers of deaths due to dementia. With such an escalating mortali... more Recent studies report doubling numbers of deaths due to dementia. With such an escalating mortality rate related to cognitive decline diseases, like dementia, timely information on contributing factors and knowledge discovery from evidence-based repositories is warranted. A large amount of scholarly knowledge extracted from research findings on dementia can be understood only using human intelligence for arriving at quality inferences. Due to the unstructured data presented in such a massive dataset of scientific articles available online, gaining insights from the knowledge hidden in the literature is complex and time-consuming. Hence, there is a need for developing a knowledge management model to create, query and maintain a knowledge repository of key elements and their relationships extracted from scholarly articles in a structured manner. In this paper, an innovative knowledge discovery computing model to process key findings from unstructured data from scholarly articles by us...
Proceedings of the Australasian Computer Science Week Multiconference, 2018
Scoring systems such as the Glasgow-Coma scale used to assess consciousness AusDrisk to assess th... more Scoring systems such as the Glasgow-Coma scale used to assess consciousness AusDrisk to assess the risk of diabetes, are prevalent in clinical practice. Scoring systems typically include relevant variables with ordinal values where each value is assigned a weight. Weights for selected values are summed and compared to thresholds for health care professionals to rapidly generate a score. Scoring systems are prevalent in clinical practice because they are easy and quick to use. However, most scoring systems comprise many variables and require some time to calculate an final score. Further, expensive population-wide studies are required to validate a scoring system. In this article, we present a new approach for the generation of a scoring system. The approach uses a search procedure invoking iterative decision tree induction to identify a suite of scoring rules, each of which requires values on only two variables. Twelve scoring rules were discovered using the approach, from an Australian screening program for the assessment of Type 2 Diabetes risk. However, classifications from the 12 rules can conflict. In this paper we argue that a simple rule preference relation is sufficient for the resolution of rule conflicts.
Proceedings of the 2020 2nd International Conference on Big Data Engineering and Technology, 2020
Recently, two terms, namely Big Data and Internet of Things (IoT) have gained popularity individu... more Recently, two terms, namely Big Data and Internet of Things (IoT) have gained popularity individually. However, their interconnections are not fully explored and understood. It is expected that the fusion of Big Data and IoT would create many complex systems for smart cities. While the data from IoT lies in Big Data, the scale of operations are completely different in terms of providing the required real-time analytics for such smart systems. Even though NoSQL databases and other next generation solutions could be deployed to achieve real-time responses, the major security challenges need to be understood as mission critical and sensitive data intertwines Big Data and IoT. In this paper, we identify the security challenges shared by the closely-knit Big Data and IoT in three main risk areas: i) NoSQL security vulnerabilities, ii) mobile IoT (M-IoT) security and privacy constraints and iii) encryption key security threats. We perform a comparative study of security vulnerabilities of NoSQL databases and identify the security and privacy constraints of M-IoT networks. Encryption key attacks for resource constrained IoT devices are also illustrated mathematically. Overall, this paper explores new research directions in these prime areas of security and privacy that would result in solution opportunities for a meaningful fusion of Big Data and IoT for a smart environment.
2016 Computing in Cardiology Conference (CinC), 2016
Cardiac health screening standards require increasingly more clinical tests consisting of blood, ... more Cardiac health screening standards require increasingly more clinical tests consisting of blood, urine and anthropometric measures as well as an extensive clinical and medication history. To ensure optimal screening referrals, diagnostic determinants need to be highly accurate to reduce false positives and ensuing stress to individual patients. However, the data from individual patients partaking in population screening is often incomplete. The current study provides an imputation algorithm that has been applied to patientcentered cardiac health screening. Missing values are iteratively imputed in conjunction with combinations of values on subsets of selected features. The approach was evaluated on the DiabHealth dataset containing 2800 records with over 180 attributes. The results for predicting CVD after data completion showed sensitivity and specificity of 94% and 99% respectively. Removing variables that define cardiac events and associated conditions directly, left 'age' followed by 'use' of antihypertensive and anti-cholesterol medication, especially statins among the best predictors.
Recently, the field of machine learning (ML) has evolved and finds its application in higher educ... more Recently, the field of machine learning (ML) has evolved and finds its application in higher education (HE) for various data analysis. Studies have shown that such an emerging field in educational technology provides meaningful insights into several dimensions of educational quality. An in-depth analysis of the application of ML could have a positive impact on the HE sector. However, there is a scarcity of a systematic review of HE literature to gain from the overarching trends and patterns discovered using ML. This paper conducts a systematic review and meta-analyses of research studies that have reported on the application of ML in HE. The differentiating factors of this study are primarily vested in the meta-analyses including a specific focus on student academic performance, atrisk, and attrition in HE. Our detailed investigation adopts an evidence-based framework called PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) for reporting the findings of our systematic review and meta-analyses of literature on the use of ML models, algorithms, evaluation metrics, and other criteria including demographics for assessing student academic performance, at-risk and attrition in HE. After undergoing the PRISMA steps such as selection criteria and filtering, we arrive at a narrowed down dataset of 89 relevant studies published from 2010 to 2020 for an in-depth analysis. The results not only show the outcomes of the quantitative analysis of the application of ML types, models, evaluation metrics, and other related demographics but also provide quality insights of publication patterns and future trends towards predicting and monitoring student academic progress in HE.
The higher education (HE) system is witnessing immense transformations to keep pace with the rapi... more The higher education (HE) system is witnessing immense transformations to keep pace with the rapid advancements in digital technologies and due to the recent COVID-19 pandemic compelling educational institutions to completely switch to online teaching and assessments. Assessments are considered to play an important and powerful role in students’ educational experience and evaluation of their academic abilities. However, there are many stigmas associated with both “traditional” and alternative assessment methods. Rethinking assessments is increasingly happening worldwide to keep up with the shift in current teaching and learning paradigms due to new possibilities of using digital technologies and a continuous improvement of student engagement. Many educational decisions such as a change in assessment from traditional summative exams to alternate methods require appropriate rationale and justification. In this paper, we adopt data-driven decision-making (DDDM) as a process for rethink...
Tour planning has become both challenging and time-consuming due to the huge amount of informatio... more Tour planning has become both challenging and time-consuming due to the huge amount of information available online and the variety of options to choose from. This is more so as each traveler has unique set of interests and location preferences in addition to other tour-based constraints such as vaccination status and pandemic travel restrictions. Several travel planning companies and agencies have emerged with more sophisticated online services to capitalize on global tourism effectively by using technology for making suitable recommendations to travel seekers. However, such systems predominantly adopt a destination-based recommendation approach and often come as bundled packages with limited customization options for incorporating each traveler’s preferences. To address these limitations, “thematic travel planning” has emerged as a recent alternative with researchers adopting text-based data mining for achieving value-added online tourism services. Understanding the need for a mor...
Computer Science & Information Technology, 2018
With the exponential proliferation of mobile devices in the consumer market, wireless e-business ... more With the exponential proliferation of mobile devices in the consumer market, wireless e-business is emerging as a key area to revolutionise industries. In the past few years, industry has witnessed an increase in the adoption of mobile payment and billing methods that leverage on wireless technologies. Yet, the success of mobile payments in businesses much depends on many factors such as, type of wireless technologies used, security options available, the players involved and their influencing m-business models. This paper examines mobile payments in both technical as well as business perspectives. It identifies and analyses the influencing factors from multi-dimensions that would be useful for adopting mobile payments.
The development of Industry 4.0 revolutionising the concept of automation and digitisation in an ... more The development of Industry 4.0 revolutionising the concept of automation and digitisation in an organisation poses a huge challenge in employee knowledge and skills to cope with the huge leap from Industry 3.0. The high-level digitisation of an organisation requires the workforce to possess higher order thinking skills (HOTS) for the changing job roles matching the rapid technological advancements. The Education 4.0 framework is aimed at supporting the Industry 4.0 skills requirement not only in digital technologies but more towards soft skill development such as collaboration and lifelong learning. However, the education sector is also facing challenges in its transition from Education 3.0 to Education 4.0. The main purpose of the paper is to propose an Agile approach for developing smart classroom teaching strategies that foster employee adaptability with the new learning paradigm of upskilling in line with Industry 4.0. By adopting an exploratory research methodology, the pilot ...
Advances in multimedia and interactive technologies book series, 2019
The internet of things (IoT) is a complex system of heterogeneous devices connected to a network.... more The internet of things (IoT) is a complex system of heterogeneous devices connected to a network. While IoT can significantly add value to people's everyday activities around the world, there are numerous security risks and privacy breaches imposed by the IoT landscape. Traditional security solutions are not applicable for the IoT as they require high-end processing capacity. The objective of this chapter is two-fold. Firstly, it provides a comprehensive summary of the recent advancements in the IoT and identifies their vulnerabilities. Secondly, it proposes the paradigm of self-learning as an intelligent and sustainable mechanism that is capable of automatically detecting suspicious activities in the IoT. Overall, this chapter presents a contemporary coverage of the recent developments in the IoT scene, the security and privacy challenges confronting the security experts, a proposal of a self-learning framework for performing health check of the IoT environment, and finally a set of high-level implementation guidelines and conclusions.
This paper describes the first steps in the development of a user ontology for a Smart Health Inf... more This paper describes the first steps in the development of a user ontology for a Smart Health Information Portal (SHIP) to provide collaborative health terms in holistic medicine. Recent trends in the increasing dissatisfaction with conventional medicine and towards embracing holistic model of health for improving quality of life is being witnessed worldwide, more importantly in the technologically advanced countries. Today, advancements in Internet technology and the vast as well as growing source of information available in World Wide Web have the vision to achieve patient education and empowerment of their own health conditions and well-being. Hence, holistic medicine with the theory that each individual has an immense potential for self-healing could be mobilised by harnessing information technology intelligently. To achieve this, it becomes imperative to provide health information specific to each patient's needs in a personalised way due to the diversity in the patient circumstances and the availability of vast and varied information in the Web. A Smart Health Information Portal (SHIP) could provide quality information that is most relevant to patients pursuing holistic treatments. In this paper, we describe the initial development of a user ontology for holistic medical information that integrates conventional medical terms related to cardiac conditions along with Homeopathy and Ayurvedic terms towards providing meaningful complementary heart health information within an existing SHIP.
Every day, big amounts of unstructured data is generated. This data is of the form of essays, res... more Every day, big amounts of unstructured data is generated. This data is of the form of essays, research papers, speeches, patents, scholastic articles, book chapters etc. In today’s world, it is very important to extract key patterns from huge text passages or verbal speeches. This paper proposes a novel method for summarizing multilingual vocal as well as written paragraphs and speeches, using semantic Knowledge Graphs. Using the proposed model, big text extracts or speeches can be summarized for better understanding and analysis. The method uses speech recognition as well as Named Entity Recognition to identify entities from spoken content to create optimized Knowledge Graphs in the English Language.
Affordable and expandable low power networks such as 5G and Low Power Wide Area Networks (LPWAN) ... more Affordable and expandable low power networks such as 5G and Low Power Wide Area Networks (LPWAN) in the public and private network areas have improved network bandwidth capacities and processing performance. Internet of Things (IoT) technologies are increasing in popularity with numerous applications and devices being developed for smart environments and health-related applications. This raises security concerns in these networks, as many IoT devices handle confidential information such as IP/MAC addresses, which could be used to identify a user's location. As a result, there is vulnerability to data tampering by man-in-the-middle (MITM) attacks, which feature two observable characteristics: (1) there is a measurable delay in the session and (2) has unusual travel times compared to prior normal transactions. To improve the detection of these attacks, this paper proposes a novel scheme using a hybrid routing mechanism, which involves appointing dedicated nodes for enforcing routing between IoT devices and users with minimal intervention and workload to the network. The function of dedicated devices with more computational and battery power can provide three advantages: (1) determine secured paths within the network by avoiding suspicious nodes and networks, (2) provide stable travel times (less fluctuations) for a trusted time server (TTS) to improve the accuracy of estimated travel times, and (3) provide packet inspection for security checks. This proposed solution contributes towards increasing the security of IoT networks by enabling the real-time detection of intruders.
Improving the efficiency, effectiveness, and quality of public services has become a growing conc... more Improving the efficiency, effectiveness, and quality of public services has become a growing concern for many governments across the world, and more so with recent popularity of online services, widely referred as e-government services. The application of quality approaches for measuring and improving e-government services has been the subject of much research within the academic world over the last two decades. This chapter discusses the use of key quality approaches to improve services in Jordan's e-government initiatives. As more and more developing countries are adopting e-services as a means of providing quality services to their community and people through the Web, the necessary benchmarking plays an important role. Many traditional quality benchmarking performance measurements have proved futile in improving e-government services due to their quantitative focus. Though qualitative frameworks and measurement approaches such as Six Sigma and Balanced Scorecard have found their success in certain industry sectors, their relevance in the service sector has drawn attention only recently. While some studies have employed such approaches for evaluating projects in information and communication technologies, literature lacks investigations in the e-government sector. To fill this gap, this chapter investigates the application of Six Sigma and Balanced Scorecard approaches to improve quality in Jordanian e-government services.
International Journal of Power Electronics and Drive Systems, Aug 1, 2023
With the increasing use of technologies and digitally driven healthcare systems worldwide, there ... more With the increasing use of technologies and digitally driven healthcare systems worldwide, there will be several opportunities for the use of big data in personalized healthcare. In addition, With the advancements and availability of internet of things (IoT) based point-of-care (POC) technologies, big data analytics and artificial intelligence (AI) can provide useful methods and solutions in monitoring, diagnosis, and self-management of health issues for a better personalized healthcare. In this paper, we identify the current personalized healthcare trends and challenges. Then, propose an architecture to support big data analytics using POC test results of an individual. The proposed architecture can facilitate an integrated and self-managed healthcare as well as remote patient care by adapting three popular machine learning algorithms to leverage the current trends in IoT, big data infrastructures and data analytics for advancing personalized healthcare of the future. This is an open access article under the CC BY-SA license.
2017 Cybersecurity and Cyberforensics Conference (CCC)
The Golden Ratio is the most irrational among irrational numbers. Its successive continued fracti... more The Golden Ratio is the most irrational among irrational numbers. Its successive continued fraction converges with the Fibonacci sequence F(n+1)/F(n) are the slowest to approximate to its actual value.This paper proposes a new method to determine the Golden Ratio with infinite precision and compares the new method with the well-known Fibonacci sequence method. The results show that our proposed method outperforms Fibonacci sequence method. Hence, cryptosystems that use Fibonacci numbers would be much faster using our new method of Golden Ratio computation. This paves way in improving counter measures from security attacks since higher precisions of the Golden Ratio method can take place in cryptographic operations very quickly when used in elliptic curve cryptosystems, power analysis security, and other applications.
Recent studies report doubling numbers of deaths due to dementia. With such an escalating mortali... more Recent studies report doubling numbers of deaths due to dementia. With such an escalating mortality rate related to cognitive decline diseases, like dementia, timely information on contributing factors and knowledge discovery from evidence-based repositories is warranted. A large amount of scholarly knowledge extracted from research findings on dementia can be understood only using human intelligence for arriving at quality inferences. Due to the unstructured data presented in such a massive dataset of scientific articles available online, gaining insights from the knowledge hidden in the literature is complex and time-consuming. Hence, there is a need for developing a knowledge management model to create, query and maintain a knowledge repository of key elements and their relationships extracted from scholarly articles in a structured manner. In this paper, an innovative knowledge discovery computing model to process key findings from unstructured data from scholarly articles by us...
Proceedings of the Australasian Computer Science Week Multiconference, 2018
Scoring systems such as the Glasgow-Coma scale used to assess consciousness AusDrisk to assess th... more Scoring systems such as the Glasgow-Coma scale used to assess consciousness AusDrisk to assess the risk of diabetes, are prevalent in clinical practice. Scoring systems typically include relevant variables with ordinal values where each value is assigned a weight. Weights for selected values are summed and compared to thresholds for health care professionals to rapidly generate a score. Scoring systems are prevalent in clinical practice because they are easy and quick to use. However, most scoring systems comprise many variables and require some time to calculate an final score. Further, expensive population-wide studies are required to validate a scoring system. In this article, we present a new approach for the generation of a scoring system. The approach uses a search procedure invoking iterative decision tree induction to identify a suite of scoring rules, each of which requires values on only two variables. Twelve scoring rules were discovered using the approach, from an Australian screening program for the assessment of Type 2 Diabetes risk. However, classifications from the 12 rules can conflict. In this paper we argue that a simple rule preference relation is sufficient for the resolution of rule conflicts.
Proceedings of the 2020 2nd International Conference on Big Data Engineering and Technology, 2020
Recently, two terms, namely Big Data and Internet of Things (IoT) have gained popularity individu... more Recently, two terms, namely Big Data and Internet of Things (IoT) have gained popularity individually. However, their interconnections are not fully explored and understood. It is expected that the fusion of Big Data and IoT would create many complex systems for smart cities. While the data from IoT lies in Big Data, the scale of operations are completely different in terms of providing the required real-time analytics for such smart systems. Even though NoSQL databases and other next generation solutions could be deployed to achieve real-time responses, the major security challenges need to be understood as mission critical and sensitive data intertwines Big Data and IoT. In this paper, we identify the security challenges shared by the closely-knit Big Data and IoT in three main risk areas: i) NoSQL security vulnerabilities, ii) mobile IoT (M-IoT) security and privacy constraints and iii) encryption key security threats. We perform a comparative study of security vulnerabilities of NoSQL databases and identify the security and privacy constraints of M-IoT networks. Encryption key attacks for resource constrained IoT devices are also illustrated mathematically. Overall, this paper explores new research directions in these prime areas of security and privacy that would result in solution opportunities for a meaningful fusion of Big Data and IoT for a smart environment.
2016 Computing in Cardiology Conference (CinC), 2016
Cardiac health screening standards require increasingly more clinical tests consisting of blood, ... more Cardiac health screening standards require increasingly more clinical tests consisting of blood, urine and anthropometric measures as well as an extensive clinical and medication history. To ensure optimal screening referrals, diagnostic determinants need to be highly accurate to reduce false positives and ensuing stress to individual patients. However, the data from individual patients partaking in population screening is often incomplete. The current study provides an imputation algorithm that has been applied to patientcentered cardiac health screening. Missing values are iteratively imputed in conjunction with combinations of values on subsets of selected features. The approach was evaluated on the DiabHealth dataset containing 2800 records with over 180 attributes. The results for predicting CVD after data completion showed sensitivity and specificity of 94% and 99% respectively. Removing variables that define cardiac events and associated conditions directly, left 'age' followed by 'use' of antihypertensive and anti-cholesterol medication, especially statins among the best predictors.
Recently, the field of machine learning (ML) has evolved and finds its application in higher educ... more Recently, the field of machine learning (ML) has evolved and finds its application in higher education (HE) for various data analysis. Studies have shown that such an emerging field in educational technology provides meaningful insights into several dimensions of educational quality. An in-depth analysis of the application of ML could have a positive impact on the HE sector. However, there is a scarcity of a systematic review of HE literature to gain from the overarching trends and patterns discovered using ML. This paper conducts a systematic review and meta-analyses of research studies that have reported on the application of ML in HE. The differentiating factors of this study are primarily vested in the meta-analyses including a specific focus on student academic performance, atrisk, and attrition in HE. Our detailed investigation adopts an evidence-based framework called PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) for reporting the findings of our systematic review and meta-analyses of literature on the use of ML models, algorithms, evaluation metrics, and other criteria including demographics for assessing student academic performance, at-risk and attrition in HE. After undergoing the PRISMA steps such as selection criteria and filtering, we arrive at a narrowed down dataset of 89 relevant studies published from 2010 to 2020 for an in-depth analysis. The results not only show the outcomes of the quantitative analysis of the application of ML types, models, evaluation metrics, and other related demographics but also provide quality insights of publication patterns and future trends towards predicting and monitoring student academic progress in HE.
The higher education (HE) system is witnessing immense transformations to keep pace with the rapi... more The higher education (HE) system is witnessing immense transformations to keep pace with the rapid advancements in digital technologies and due to the recent COVID-19 pandemic compelling educational institutions to completely switch to online teaching and assessments. Assessments are considered to play an important and powerful role in students’ educational experience and evaluation of their academic abilities. However, there are many stigmas associated with both “traditional” and alternative assessment methods. Rethinking assessments is increasingly happening worldwide to keep up with the shift in current teaching and learning paradigms due to new possibilities of using digital technologies and a continuous improvement of student engagement. Many educational decisions such as a change in assessment from traditional summative exams to alternate methods require appropriate rationale and justification. In this paper, we adopt data-driven decision-making (DDDM) as a process for rethink...
Tour planning has become both challenging and time-consuming due to the huge amount of informatio... more Tour planning has become both challenging and time-consuming due to the huge amount of information available online and the variety of options to choose from. This is more so as each traveler has unique set of interests and location preferences in addition to other tour-based constraints such as vaccination status and pandemic travel restrictions. Several travel planning companies and agencies have emerged with more sophisticated online services to capitalize on global tourism effectively by using technology for making suitable recommendations to travel seekers. However, such systems predominantly adopt a destination-based recommendation approach and often come as bundled packages with limited customization options for incorporating each traveler’s preferences. To address these limitations, “thematic travel planning” has emerged as a recent alternative with researchers adopting text-based data mining for achieving value-added online tourism services. Understanding the need for a mor...
Computer Science & Information Technology, 2018
With the exponential proliferation of mobile devices in the consumer market, wireless e-business ... more With the exponential proliferation of mobile devices in the consumer market, wireless e-business is emerging as a key area to revolutionise industries. In the past few years, industry has witnessed an increase in the adoption of mobile payment and billing methods that leverage on wireless technologies. Yet, the success of mobile payments in businesses much depends on many factors such as, type of wireless technologies used, security options available, the players involved and their influencing m-business models. This paper examines mobile payments in both technical as well as business perspectives. It identifies and analyses the influencing factors from multi-dimensions that would be useful for adopting mobile payments.
The development of Industry 4.0 revolutionising the concept of automation and digitisation in an ... more The development of Industry 4.0 revolutionising the concept of automation and digitisation in an organisation poses a huge challenge in employee knowledge and skills to cope with the huge leap from Industry 3.0. The high-level digitisation of an organisation requires the workforce to possess higher order thinking skills (HOTS) for the changing job roles matching the rapid technological advancements. The Education 4.0 framework is aimed at supporting the Industry 4.0 skills requirement not only in digital technologies but more towards soft skill development such as collaboration and lifelong learning. However, the education sector is also facing challenges in its transition from Education 3.0 to Education 4.0. The main purpose of the paper is to propose an Agile approach for developing smart classroom teaching strategies that foster employee adaptability with the new learning paradigm of upskilling in line with Industry 4.0. By adopting an exploratory research methodology, the pilot ...
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Papers by Sitalakshmi Venkatraman