The breakthrough of blockchain technology has facilitated the emergence and deployment of a wide ... more The breakthrough of blockchain technology has facilitated the emergence and deployment of a wide range of Unmanned Aerial Vehicles (UAV) networks-based applications. Yet, the full utilization of these applications is still limited due to the fact that each application is operating on an isolated blockchain. Thus, it is inevitable to orchestrate these blockchain fragments by introducing a cross-blockchain platform that governs the inter-communication and transfer of assets in the UAV networks context. In this paper, we provide an up-to-date survey of blockchain-based UAV networks applications. We also survey the literature on the state-of-the-art cross blockchain frameworks to highlight the latest advances in the field. Based on the outcomes of our survey, we introduce a spectrum of scenarios related to UAV networks that may leverage the potentials of the currently available cross-blockchain solutions. Finally, we identify open issues and potential challenges associated with the appl...
Proceedings of the 18th Annual Conference on Information Technology Education, 2017
As major product of information technology, YouTube is a ubiquitous source for education, also in... more As major product of information technology, YouTube is a ubiquitous source for education, also in the field of information technology. Learners, however, are facing the increasing problem of finding appropriate videos on YouTube efficiently. Users' rating in terms of Likes and Dislikes could provide a starting point. However, it is unclear what the number of Likes and Dislikes reveal about the video. This paper tries to create links between different video features and users' rating of YouTube's educational content. For this purpose, 300 educational videos were collected and analyzed and regression models were established that describe the number of Likes per view and the number of Dislikes per view as functions of different video features and production styles. Results show that the number of Likes per view can be predicted more reliably than the number of Dislikes per view. The number of Likes per view increases with higher video resolution and higher talking rate (words per second), and when the instructor or tutor speaks English as a native language. Videos using explanations on paper or whiteboard as well as videos that use more than one style attract more Likes per view. In contrast, the model that describes the number of Dislikes per view has a low adjusted R-squared and the contribution of its significant variables is rather difficult to interpret. This suggests that further research is required to understand users' behavior in terms of disliking an educational video.
2018 IEEE Global Engineering Education Conference (EDUCON), 2018
The design of combinatorial and sequential circuits relies on multiple logical transformations th... more The design of combinatorial and sequential circuits relies on multiple logical transformations that can show different levels of complexity. This paper investigates the intrinsic complexity of eight logical transformation problems: (1)-from human-language statement into formal function, (2)-from formal function into truth table, (3)-from truth table into formal function, (4)-from formal function into k-map, (5)-from truth table into k-map, (6)-from k-map into minimized formal function, (7)-from formal function into minimized formal function using Boolean algebra, and (8)-from formal function into digital circuit. 27 potential complexity variables were first identified and specified and a total of 303 test items/problems were generated and solved by up to 43 students each with time recording. The level of intrinsic complexity was defined based on average solving time and error ratio. Regression models were generated to establish a predictive relationship between the intrinsic complexity level and the complexity variables for each transformation problem. Apart from Transformation 7, the regression models showed adjusted R-square values between 81% and 94%. These models can be used to predict the solving time of new problems towards more reliable test design.
2017 IEEE International Symposium on Circuits and Systems (ISCAS), 2017
Any exam problem shows a specific level of intrinsic complexity that affects its solving time. Th... more Any exam problem shows a specific level of intrinsic complexity that affects its solving time. This paper investigates the factors that affect the intrinsic complexity of determining the total resistance of a resistive circuit. A sample of 46 circuits was generated and solved by 27 students with time recording. Regression analysis showed that the solving time is significantly affected by the number of arithmetic operations required to solve the problem, by the value range of the resistors, as well as by the inconsistency of the given resistor units. Other factors that reflect the circuit topology including the number of circuit nodes and branches are either correlated with the number of arithmetic operations or insignificant in the regression analysis. The outcome of the study is a complexity model that can be used to predict the solving time of new problems of the same class which allows to develop more reliable exam problems. Different ways to control the complexity level are disc...
Background: You Tube is a valuable source of health-related educational material which can have a... more Background: You Tube is a valuable source of health-related educational material which can have a profound impact on people's health-related behaviors and decisions. However, YouTube contains a wide variety of unverified content that may promote unhealthy behaviors and activities. We aim in this systematic review to provide insight into the published literature concerning the quality of health information and educational videos found on YouTube.Methods: A search of peer-reviewed original articles was conducted regarding the educational value of YouTube medical videos which were published in English. We searched Google Scholar, Medline (through PubMed), EMBASE, Scopus, Direct Science, Web of Science, and ProQuest databases. A literature search was conducted between April 1 and April 31 of 2021. Based on the eligibility criteria, 202 artilces covering 30 medical categories were included in the qualitative synthesis.Results: We reviewed approximately 22,300 videos in all of the stu...
Unmanned aerial vehicles (UAVs) are gaining immense attention due to their potential to revolutio... more Unmanned aerial vehicles (UAVs) are gaining immense attention due to their potential to revolutionize various businesses and industries. However, the adoption of UAV-assisted applications will strongly rely on the provision of reliable systems that allow managing UAV operations at high levels of safety and security. Recently, the concept of UAV traffic management (UTM) has been introduced to support safe, efficient, and fair access to low-altitude airspace for commercial UAVs. A UTM system identifies multiple cooperating parties with different roles and levels of authority to provide real-time services to airspace users. However, current UTM systems are centralized and lack a clear definition of protocols that govern a secure interaction between authorities, service providers, and end-users. The lack of such protocols renders the UTM system unscalable and prone to various cyber attacks. Another limitation of the currently proposed UTM architecture is the absence of an efficient mech...
Drone flight controls and ground stations are known to be vulnerable to attacks. Besides posing a... more Drone flight controls and ground stations are known to be vulnerable to attacks. Besides posing a threat to integrity and confidentiality of drone data, their vulnerabilities endanger safety. Onboard continuous authentication is a vital countermeasure to hijacking attempts. Motivated by the success of Machine Learning (ML) techniques in the field of behavioral biometrics, this paper investigates the use of sensor readings generated onboard drones and of control data reaching them from the ground to feed an onboard ML model continuously authenticating pilots. We analyze fifteen inertial measurement units (IMU) and four radio control signals obtained from the drone's onboard sensors or coming from its remote controller, to identify the controlling pilot. We investigate three sequence classification schemes. In the first scheme, raw sensor sequences are directly fed to a deep Long/Short-Term Memory (LSTM) learner. In the second scheme, frequency-domain features are extracted from the data sequences and interpreted by an ensemble of random trees. In the third scheme, instantaneous sensor readings are classified using the same ensemble learning technique as in the second scheme, yet a final decision fusion method is adopted to provide a sequence-based decision. We compare the three schemes in terms of accuracy, complexity, and delay. The winning scheme is validated and tested against an unseen intruder scenario. Our tests show that an LSTM model trained with data from 19 users is able to identify the operating user at a 97% accuracy, while it can identify an unknown intruder at an average accuracy of 73%.
The breakthrough of blockchain technology has facilitated the emergence and deployment of a wide ... more The breakthrough of blockchain technology has facilitated the emergence and deployment of a wide range of Unmanned Aerial Vehicles (UAV) networks-based applications. Yet, the full utilization of these applications is still limited due to the fact that each application is operating on an isolated blockchain. Thus, it is inevitable to orchestrate these blockchain fragments by introducing a cross-blockchain platform that governs the inter-communication and transfer of assets in the UAV networks context. In this paper, we provide an up-to-date survey of blockchain-based UAV networks applications. We also survey the literature on the state-of-the-art cross blockchain frameworks to highlight the latest advances in the field. Based on the outcomes of our survey, we introduce a spectrum of scenarios related to UAV networks that may leverage the potentials of the currently available cross-blockchain solutions. Finally, we identify open issues and potential challenges associated with the appl...
Proceedings of the 18th Annual Conference on Information Technology Education, 2017
As major product of information technology, YouTube is a ubiquitous source for education, also in... more As major product of information technology, YouTube is a ubiquitous source for education, also in the field of information technology. Learners, however, are facing the increasing problem of finding appropriate videos on YouTube efficiently. Users' rating in terms of Likes and Dislikes could provide a starting point. However, it is unclear what the number of Likes and Dislikes reveal about the video. This paper tries to create links between different video features and users' rating of YouTube's educational content. For this purpose, 300 educational videos were collected and analyzed and regression models were established that describe the number of Likes per view and the number of Dislikes per view as functions of different video features and production styles. Results show that the number of Likes per view can be predicted more reliably than the number of Dislikes per view. The number of Likes per view increases with higher video resolution and higher talking rate (words per second), and when the instructor or tutor speaks English as a native language. Videos using explanations on paper or whiteboard as well as videos that use more than one style attract more Likes per view. In contrast, the model that describes the number of Dislikes per view has a low adjusted R-squared and the contribution of its significant variables is rather difficult to interpret. This suggests that further research is required to understand users' behavior in terms of disliking an educational video.
2018 IEEE Global Engineering Education Conference (EDUCON), 2018
The design of combinatorial and sequential circuits relies on multiple logical transformations th... more The design of combinatorial and sequential circuits relies on multiple logical transformations that can show different levels of complexity. This paper investigates the intrinsic complexity of eight logical transformation problems: (1)-from human-language statement into formal function, (2)-from formal function into truth table, (3)-from truth table into formal function, (4)-from formal function into k-map, (5)-from truth table into k-map, (6)-from k-map into minimized formal function, (7)-from formal function into minimized formal function using Boolean algebra, and (8)-from formal function into digital circuit. 27 potential complexity variables were first identified and specified and a total of 303 test items/problems were generated and solved by up to 43 students each with time recording. The level of intrinsic complexity was defined based on average solving time and error ratio. Regression models were generated to establish a predictive relationship between the intrinsic complexity level and the complexity variables for each transformation problem. Apart from Transformation 7, the regression models showed adjusted R-square values between 81% and 94%. These models can be used to predict the solving time of new problems towards more reliable test design.
2017 IEEE International Symposium on Circuits and Systems (ISCAS), 2017
Any exam problem shows a specific level of intrinsic complexity that affects its solving time. Th... more Any exam problem shows a specific level of intrinsic complexity that affects its solving time. This paper investigates the factors that affect the intrinsic complexity of determining the total resistance of a resistive circuit. A sample of 46 circuits was generated and solved by 27 students with time recording. Regression analysis showed that the solving time is significantly affected by the number of arithmetic operations required to solve the problem, by the value range of the resistors, as well as by the inconsistency of the given resistor units. Other factors that reflect the circuit topology including the number of circuit nodes and branches are either correlated with the number of arithmetic operations or insignificant in the regression analysis. The outcome of the study is a complexity model that can be used to predict the solving time of new problems of the same class which allows to develop more reliable exam problems. Different ways to control the complexity level are disc...
Background: You Tube is a valuable source of health-related educational material which can have a... more Background: You Tube is a valuable source of health-related educational material which can have a profound impact on people's health-related behaviors and decisions. However, YouTube contains a wide variety of unverified content that may promote unhealthy behaviors and activities. We aim in this systematic review to provide insight into the published literature concerning the quality of health information and educational videos found on YouTube.Methods: A search of peer-reviewed original articles was conducted regarding the educational value of YouTube medical videos which were published in English. We searched Google Scholar, Medline (through PubMed), EMBASE, Scopus, Direct Science, Web of Science, and ProQuest databases. A literature search was conducted between April 1 and April 31 of 2021. Based on the eligibility criteria, 202 artilces covering 30 medical categories were included in the qualitative synthesis.Results: We reviewed approximately 22,300 videos in all of the stu...
Unmanned aerial vehicles (UAVs) are gaining immense attention due to their potential to revolutio... more Unmanned aerial vehicles (UAVs) are gaining immense attention due to their potential to revolutionize various businesses and industries. However, the adoption of UAV-assisted applications will strongly rely on the provision of reliable systems that allow managing UAV operations at high levels of safety and security. Recently, the concept of UAV traffic management (UTM) has been introduced to support safe, efficient, and fair access to low-altitude airspace for commercial UAVs. A UTM system identifies multiple cooperating parties with different roles and levels of authority to provide real-time services to airspace users. However, current UTM systems are centralized and lack a clear definition of protocols that govern a secure interaction between authorities, service providers, and end-users. The lack of such protocols renders the UTM system unscalable and prone to various cyber attacks. Another limitation of the currently proposed UTM architecture is the absence of an efficient mech...
Drone flight controls and ground stations are known to be vulnerable to attacks. Besides posing a... more Drone flight controls and ground stations are known to be vulnerable to attacks. Besides posing a threat to integrity and confidentiality of drone data, their vulnerabilities endanger safety. Onboard continuous authentication is a vital countermeasure to hijacking attempts. Motivated by the success of Machine Learning (ML) techniques in the field of behavioral biometrics, this paper investigates the use of sensor readings generated onboard drones and of control data reaching them from the ground to feed an onboard ML model continuously authenticating pilots. We analyze fifteen inertial measurement units (IMU) and four radio control signals obtained from the drone's onboard sensors or coming from its remote controller, to identify the controlling pilot. We investigate three sequence classification schemes. In the first scheme, raw sensor sequences are directly fed to a deep Long/Short-Term Memory (LSTM) learner. In the second scheme, frequency-domain features are extracted from the data sequences and interpreted by an ensemble of random trees. In the third scheme, instantaneous sensor readings are classified using the same ensemble learning technique as in the second scheme, yet a final decision fusion method is adopted to provide a sequence-based decision. We compare the three schemes in terms of accuracy, complexity, and delay. The winning scheme is validated and tested against an unseen intruder scenario. Our tests show that an LSTM model trained with data from 19 users is able to identify the operating user at a 97% accuracy, while it can identify an unknown intruder at an average accuracy of 73%.
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Papers by Abdulhadi Shoufan