Suleiman Aliyu - Academia.edu (original) (raw)

Papers by Suleiman Aliyu

In this paper we consider conditions for the existence and non-existence of a critical point in t... more In this paper we consider conditions for the existence and non-existence of a critical point in the first quadrant for a predator-prey system of Ivlev type. A geometrical interpretation of an existing theorem is then presented and a condition, which is necessary and sufficient, established by Sugie (1998) for a unique stable limit cycle is obtained through linearization and utilization of properties of the Jacobian matrix. Examples are also given to illustrate our results.

A thorough investigation of the electroencephalograph (EEG) information may support an enriched a... more A thorough investigation of the electroencephalograph (EEG) information may support an enriched awareness of the mechanism of understanding different learning styles patterns. Wavelet analysis is a powerful technique that uniquely permits the decomposition of complex information of trends, discontinuities, a repeated pattern. The purpose of such methods is to be able to assign simple segments at diverse locations and scales, to be remodelled afterward effectively. In this paper, we attempt to classify individual cognitive learning styles using artificial neural networks and unsupervised learning. First, we apply Independent component analysis (ICA) to extract relevant features (artefacts removal) of the EEG records. We analyse the ICA-based EEG channels data using inter-quartiles to show the degree of dispersion and skewness. Next, self-organising maps (SOM) are then created to characterise different cognitive learning styles from selected ICA-based channel data.

Journal of responsible technology, Dec 1, 2020

Artificial Intelligence (AI) is playing a crucial role in advancing efforts towards sustainable d... more Artificial Intelligence (AI) is playing a crucial role in advancing efforts towards sustainable development across the globe. AI has the potential to help address some of the biggest challenges that society faces including health and well-being. Thus, AI can be useful in addressing some health and well-being related challenges by accelerating the attainment of the UN's Sustainable Development Goal 3 (SDG3), namely Good health and well-being. This paper draws on the Organisation for Economic Cooperation and Development (OECD) Development Assistance Committee (DAC) list of Official Development Assistance (ODA) and the Price Waterhouse Coopers (PwC) SDG selector to identify the SDG that is prioritised in Least Developed Countries (LDCs). Out of 32 least developed African countries on the list, SDG3 was the most common SDG, suggesting that health and well-being is a priority for these countries. In order to understand the opportunities and challenges that might result in applying AI in the acceleration of SDG3, the paper uses a SWOT analysis to highlight some socio-ethical implications of using AI in advancing SDGS in the identified LDCs on the DAC list.

Previous work demonstrated that by adopting a semi-recursive contract net protocol (SR-CNP) equip... more Previous work demonstrated that by adopting a semi-recursive contract net protocol (SR-CNP) equipped with service capability tables (SCTs) for dynamically selecting recorded cloud agents, their services and states, Cloud agents can effectively integrate disparate Cloud resources into a unified Cloud service. However, the choice of SCT may result in large overheads with Cloud agents exchanging a considerably large number of messages to achieve high success rates in service composition. In this paper, a comprehensive set of mathematical analyses of message exchanges by Cloud agents (Broker agents, Consumer agents and Service provider agents) in cloud service composition are presented. Experiments were performed where cloud agents adopt Particle Swarm Optimization for evolving the best service composition outcomes with the aim of minimizing the average number of messages propagated while successfully composing cloud services using SR-CNP and SCTs. Empirical results obtained from an agent-based testbed reveal that agents successfully minimized the number of messages exchanged during cloud service composition. Index Terms-agent based cloud service composition, multiagent systems, Cloud computing, contract net protocol, Cloud service composition. I. INTRODUCTION LOUD computing pools a set of web-accessible resources, provisioned under service level agreements and established via negotiation. Furthermore, it should be dynamically composed and virtualized according to consumers' need on an on-demand basis [1]. Over the past few years, Cloud service providers (e.g. Microsoft [2], Amazon [3], Google [4], Go Grid [5], IBM [6] etc.) have continued to evolve and the Cloud services churned out by these providers have continued to increase proportionately. On the other hand, the complexity of Consumers (e.g. App developers) requirements have also changed over time. In order to satisfy these complex consumer requests as they emerge, there is need for a dynamic and automated service composition that can support everything as-a-service model [7]. Hence, cloud service composition in single or multi-cloud environments must support the coordination of independent and self-interested parties, efficient re-configuration of existent and permanent service compositions since consumer requirements can Manuscript

2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)

Software Defined Networking (SDN) paradigm is introducing new architectural approaches for many u... more Software Defined Networking (SDN) paradigm is introducing new architectural approaches for many unresolved issues of networking. These new approaches are imperative in emerging scenarios where user requirements keep growing, the required bandwidth keeps increasing, and so does the variety of applications (e.g. Big data analytics) that suggest the network plays a more prominent role. As such, our research aims to provide a novel self-tuning (adaptive) resource management technique in SDN-based InterCloud environments. Essentially, this workshop paper presents a policy-based quality of service (QoS) control framework described using principles in coalition games with externalities or partition form games (PFGs). More specifically, we model QoS-aware resource management in the SDN-based InterCloud platform as an adaptive control problem. This ongoing work outlines a proposed dynamic programming and anytime approach (Integer partition based) to solve the multicriteria optimisation problem of a Markov decision process (MDP) model for system dynamics in SDN-based InterClouds.

2019 International Conference on Computing, Electronics & Communications Engineering (iCCECE), 2019

Advanced Driving Assistance Systems (ADAS) has been a critical component in vehicles and vital to... more Advanced Driving Assistance Systems (ADAS) has been a critical component in vehicles and vital to the safety of vehicle drivers and public road transportation systems. In this paper, we present a deep learning technique that classifies drivers' distraction behaviour using three contextual awareness parameters: speed, manoeuver and event type. Using a video coding taxonomy, we study drivers' distractions based on events information from Regions of Interest (RoI) such as hand gestures, facial orientation and eye gaze estimation. Furthermore, a novel probabilistic (Bayesian) model based on the Long shortterm memory (LSTM) network is developed for classifying driver's distraction severity. This paper also proposes the use of frame-based contextual data from the multi-view TeleFOT naturalistic driving study (NDS) data monitoring to classify the severity of driver distractions. Our proposed methodology entails recurrent deep neural network layers trained to predict driver distraction severity from time series data.

Journal of Systems and Software, 2016

Software cybernetics research is to apply a variety of techniques from cybernetics research to so... more Software cybernetics research is to apply a variety of techniques from cybernetics research to software engineering research. For more than fifteen years since 2001, there has been a dramatic increase in work on software cybernetics. From cybernetics viewpoint, the work is mainly on the first-order level, namely, the software under observation and control. Beyond the first-order cybernetics, the software, developers/users, and running environments influence each other and thus create feedback to form a more complicated system. We classify software cybernetics as classical software cybernetics based on the first-order cybernetics, and as modern software cybernetics based on the higher order cybernetics (new cybernetics). This paper provides a review of literature on software cybernetics, especially focuses on the transition from classical software cybernetics to modern software cybernetics. The results of the survey indicate that some new research areas such as Internet of Things, big data, cloud computing, cyber-physical systems, and even creative computing are related to modern software cybernetics. The paper identifies the relationships between the techniques of new cybernetics applied and the new research areas to which they have been applied; formulates research problems and challenges of software cybernetics with the application of principles of new cybernetics; identifies and highlights new research trends of modern software cybernetic for further research.

ABSTRACT: Background: Male infertility is a worldwide problem. In Africa it assumes a bigger dime... more ABSTRACT: Background: Male infertility is a worldwide problem. In Africa it assumes a bigger dimension due to its psychosocial implications. We reviewed the magnitude of the problem and outcome of management. Aim to study the pattern of male infertility, and outcome of its management. Materials and Methods: Male infertility patients managed at University Teaching Hospital Maiduguri (UMTH) between January 2008 to December 2012 were reviewed. Results-There were 73 patients, age ranged from 25-52 years with a mean of 38.35years. The peak age group was 30-39years with 45.20 % of the patients.The duration of the problem varied from months to over 10 years. Twenty five(34.25%) patients had STD. Co-morbid medical conditions were hypertension in 18(24.66%), diabetes 9(12.33%). Abnormal findings in the testes were varicoceles in 51(34.93%) testes while 7(4.79%) were undescended testes. Seminal fluid analysis revealed azospermia in 44(60.27%), oligospermia in 26(35.62%). Sixty- seven patients...

2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), 2017

Software Defined Networking (SDN) paradigm is introducing novel approaches for many unresolved is... more Software Defined Networking (SDN) paradigm is introducing novel approaches for many unresolved issues of networking. These new outlooks are imperative in emerging scenarios where user requirements keep growing, the required bandwidth keeps increasing, and so does the variety of applications (e.g. Big data analytics) that suggest the network plays a more prominent role. As such, our research aims to provide a novel adaptive (self-tuning) resource management technique in SDN-based InterCloud environments. A quality of service (QoS) policy control framework is presented by modelling QoS-aware resource management as an adaptive control problem, and using principles in coalition games with externalities or partition form games (PFGs) as control mechanism. This on-going work outlines a proposed dynamic programming and anytime approach (Integer partition based) to solve the multi-criteria optimisation problem of a Markov decision process (MDP) model for system dynamics in SDN-based InterCl...

More and more real-time IoT applications such as smart cities or autonomous vehicles require big ... more More and more real-time IoT applications such as smart cities or autonomous vehicles require big data analytics with reduced latencies. However, data streams produced from distributed sensing devices may not suffice to be processed traditionally in the remote cloud due to: (i) longer Wide Area Network (WAN) latencies and (ii) limited resources held by a single Cloud. To solve this problem, a novel Software-Defined Network (SDN) based InterCloud architecture is presented for mobile edge computing environments, known as EdgeIoT. An adaptive resource capacity management approach is proposed to employ a policy-based QoS control framework using principles in coalition games with externalities. To optimise resource capacity policy, the proposed QoS management technique solves, adaptively, a lexicographic ordering bi-criteria Coalition Structure Generation (CSG) problem. It is an onerous task to guarantee in a deterministic way that a real-time EdgeIoT application satisfies low latency req...

IEEE Access

Detecting and classifying driver distractions is crucial in the prevention of road accidents. The... more Detecting and classifying driver distractions is crucial in the prevention of road accidents. These distractions impact both driver behavior and vehicle dynamics. Knowing the degree of driver distraction can aid in accident prevention techniques, including transitioning of control to a level 4 semi-autonomous vehicle, when a high distraction severity level is reached. Thus, enhancement of Advanced Driving Assistance Systems (ADAS) is a critical component in the safety of vehicle drivers and other road users. In this paper, a new methodology is introduced, using an expert knowledge rule system to predict the severity of distraction in a contiguous set of video frames using the Naturalistic Driving American University of Cairo (AUC) Distraction Dataset. A multi-class distraction system comprises the face orientation, drivers' activities, hands and previous driver distraction, a severity classification model is developed as a discrete dynamic Bayesian (DDB). Furthermore, a Mamdani-based fuzzy system was implemented to detect multi-class of distractions into a severity level of safe, careless or dangerous driving. Thus, if a high level of severity is reached the semi-autonomous vehicle will take control. The result further shows that some instances of driver's distraction may quickly transition from a careless to dangerous driving in a multi-class distraction context. INDEX TERMS Fuzzy logic systems, driver distraction, severity level, ADAS, image processing, dynamic Bayesian.

Journal of Systems and Software, 2016

Software cybernetics research is to apply a variety of techniques from cybernetics research to so... more Software cybernetics research is to apply a variety of techniques from cybernetics research to software engineering research. For more than fifteen years since 2001, there has been a dramatic increase in work relating to software cybernetics. From cybernetics viewpoint, the work is mainly on the first-order level, namely, the software under observation and control. Beyond the first-order cybernetics, the software, developers/users, and running environments influence each other and thus create feedback to form more complicated systems. We classify software cybernetics as Software Cybernetics I based on the first-order cybernetics, and as Software Cybernetics II based on the higher order cybernetics. This paper provides a review of the literature on software cybernetics, particularly focusing on the transition from Software Cybernetics I to Software Cybernetics II. The results of the survey indicate that some new research areas such as Internet of Things, big data, cloud computing, cyber-physical systems, and even creative computing are related to Software Cybernetics II. The paper identifies the relationships between the techniques of Software Cybernetics II applied and the new research areas to which they have been applied, formulates research problems and challenges of software cybernetics with the application of principles of Phase II of software cybernetics; identifies and highlights new research trends of software cybernetic for further research.

2016 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), 2016

InterCloud Computing is a new cloud paradigm designed to guarantee service quality or performance... more InterCloud Computing is a new cloud paradigm designed to guarantee service quality or performance and availability of on-demand resources. InterCloud enables Cloud interoperability by promoting the interworking of Cloud systems from different cloud providers using standard interfacing. Resource management in InterCloud, considered as an important functional requirement, has not attracted commensurate research attention. The focus of this paper is to propose a Software Cybernetic approach, in the form of an adaptive control framework, for efficient management of shared resources in peer-to-peer InterCloud computing. This research effort adopts cooperative game theory to model resource management in InterCloud. The space of cooperative arrangements (resource sharing) between the participant cloud systems is presented by using Integer Partitioning to characterise the worst case communication complexity in peer to peer InterCloud. Essentially, this paper presents an Integer partition based anytime algorithm as an optimal cost solution to the bi-objective optimisation problem in resource management; anchored principally on practical trade-off between the desired performance (quality of service) and communication complexity of collaborating resource clouds.

2016 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), 2016

InterCloud Computing is a new cloud paradigm designed to guarantee service quality or performance... more InterCloud Computing is a new cloud paradigm designed to guarantee service quality or performance and availability of on-demand resources. InterCloud enables Cloud interoperability by promoting the interworking of Cloud systems from different cloud providers using standard interfacing. Resource management in InterCloud, considered as an important functional requirement, has not attracted commensurate research attention. The focus of this paper is to propose a Software Cybernetic approach, in the form of an adaptive control framework, for efficient management of shared resources in peer-to-peer InterCloud computing. This research effort adopts cooperative game theory to model resource management in InterCloud. The space of cooperative arrangements (resource sharing) between the participant cloud systems is presented by using Integer Partitioning to characterise the worst case communication complexity in peer to peer InterCloud. Essentially, this paper presents an Integer partition based anytime algorithm as an optimal cost solution to the bi-objective optimisation problem in resource management; anchored principally on practical trade-off between the desired performance (quality of service) and communication complexity of collaborating resource clouds.

In this paper we consider conditions for the existence and non-existence of a critical point in t... more In this paper we consider conditions for the existence and non-existence of a critical point in the first quadrant for a predator-prey system of Ivlev type. A geometrical interpretation of an existing theorem is then presented and a condition, which is necessary and sufficient, established by Sugie (1998) for a unique stable limit cycle is obtained through linearization and utilization of properties of the Jacobian matrix. Examples are also given to illustrate our results.

A thorough investigation of the electroencephalograph (EEG) information may support an enriched a... more A thorough investigation of the electroencephalograph (EEG) information may support an enriched awareness of the mechanism of understanding different learning styles patterns. Wavelet analysis is a powerful technique that uniquely permits the decomposition of complex information of trends, discontinuities, a repeated pattern. The purpose of such methods is to be able to assign simple segments at diverse locations and scales, to be remodelled afterward effectively. In this paper, we attempt to classify individual cognitive learning styles using artificial neural networks and unsupervised learning. First, we apply Independent component analysis (ICA) to extract relevant features (artefacts removal) of the EEG records. We analyse the ICA-based EEG channels data using inter-quartiles to show the degree of dispersion and skewness. Next, self-organising maps (SOM) are then created to characterise different cognitive learning styles from selected ICA-based channel data.

Journal of responsible technology, Dec 1, 2020

Artificial Intelligence (AI) is playing a crucial role in advancing efforts towards sustainable d... more Artificial Intelligence (AI) is playing a crucial role in advancing efforts towards sustainable development across the globe. AI has the potential to help address some of the biggest challenges that society faces including health and well-being. Thus, AI can be useful in addressing some health and well-being related challenges by accelerating the attainment of the UN's Sustainable Development Goal 3 (SDG3), namely Good health and well-being. This paper draws on the Organisation for Economic Cooperation and Development (OECD) Development Assistance Committee (DAC) list of Official Development Assistance (ODA) and the Price Waterhouse Coopers (PwC) SDG selector to identify the SDG that is prioritised in Least Developed Countries (LDCs). Out of 32 least developed African countries on the list, SDG3 was the most common SDG, suggesting that health and well-being is a priority for these countries. In order to understand the opportunities and challenges that might result in applying AI in the acceleration of SDG3, the paper uses a SWOT analysis to highlight some socio-ethical implications of using AI in advancing SDGS in the identified LDCs on the DAC list.

Previous work demonstrated that by adopting a semi-recursive contract net protocol (SR-CNP) equip... more Previous work demonstrated that by adopting a semi-recursive contract net protocol (SR-CNP) equipped with service capability tables (SCTs) for dynamically selecting recorded cloud agents, their services and states, Cloud agents can effectively integrate disparate Cloud resources into a unified Cloud service. However, the choice of SCT may result in large overheads with Cloud agents exchanging a considerably large number of messages to achieve high success rates in service composition. In this paper, a comprehensive set of mathematical analyses of message exchanges by Cloud agents (Broker agents, Consumer agents and Service provider agents) in cloud service composition are presented. Experiments were performed where cloud agents adopt Particle Swarm Optimization for evolving the best service composition outcomes with the aim of minimizing the average number of messages propagated while successfully composing cloud services using SR-CNP and SCTs. Empirical results obtained from an agent-based testbed reveal that agents successfully minimized the number of messages exchanged during cloud service composition. Index Terms-agent based cloud service composition, multiagent systems, Cloud computing, contract net protocol, Cloud service composition. I. INTRODUCTION LOUD computing pools a set of web-accessible resources, provisioned under service level agreements and established via negotiation. Furthermore, it should be dynamically composed and virtualized according to consumers' need on an on-demand basis [1]. Over the past few years, Cloud service providers (e.g. Microsoft [2], Amazon [3], Google [4], Go Grid [5], IBM [6] etc.) have continued to evolve and the Cloud services churned out by these providers have continued to increase proportionately. On the other hand, the complexity of Consumers (e.g. App developers) requirements have also changed over time. In order to satisfy these complex consumer requests as they emerge, there is need for a dynamic and automated service composition that can support everything as-a-service model [7]. Hence, cloud service composition in single or multi-cloud environments must support the coordination of independent and self-interested parties, efficient re-configuration of existent and permanent service compositions since consumer requirements can Manuscript

2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)

Software Defined Networking (SDN) paradigm is introducing new architectural approaches for many u... more Software Defined Networking (SDN) paradigm is introducing new architectural approaches for many unresolved issues of networking. These new approaches are imperative in emerging scenarios where user requirements keep growing, the required bandwidth keeps increasing, and so does the variety of applications (e.g. Big data analytics) that suggest the network plays a more prominent role. As such, our research aims to provide a novel self-tuning (adaptive) resource management technique in SDN-based InterCloud environments. Essentially, this workshop paper presents a policy-based quality of service (QoS) control framework described using principles in coalition games with externalities or partition form games (PFGs). More specifically, we model QoS-aware resource management in the SDN-based InterCloud platform as an adaptive control problem. This ongoing work outlines a proposed dynamic programming and anytime approach (Integer partition based) to solve the multicriteria optimisation problem of a Markov decision process (MDP) model for system dynamics in SDN-based InterClouds.

2019 International Conference on Computing, Electronics & Communications Engineering (iCCECE), 2019

Advanced Driving Assistance Systems (ADAS) has been a critical component in vehicles and vital to... more Advanced Driving Assistance Systems (ADAS) has been a critical component in vehicles and vital to the safety of vehicle drivers and public road transportation systems. In this paper, we present a deep learning technique that classifies drivers' distraction behaviour using three contextual awareness parameters: speed, manoeuver and event type. Using a video coding taxonomy, we study drivers' distractions based on events information from Regions of Interest (RoI) such as hand gestures, facial orientation and eye gaze estimation. Furthermore, a novel probabilistic (Bayesian) model based on the Long shortterm memory (LSTM) network is developed for classifying driver's distraction severity. This paper also proposes the use of frame-based contextual data from the multi-view TeleFOT naturalistic driving study (NDS) data monitoring to classify the severity of driver distractions. Our proposed methodology entails recurrent deep neural network layers trained to predict driver distraction severity from time series data.

Journal of Systems and Software, 2016

Software cybernetics research is to apply a variety of techniques from cybernetics research to so... more Software cybernetics research is to apply a variety of techniques from cybernetics research to software engineering research. For more than fifteen years since 2001, there has been a dramatic increase in work on software cybernetics. From cybernetics viewpoint, the work is mainly on the first-order level, namely, the software under observation and control. Beyond the first-order cybernetics, the software, developers/users, and running environments influence each other and thus create feedback to form a more complicated system. We classify software cybernetics as classical software cybernetics based on the first-order cybernetics, and as modern software cybernetics based on the higher order cybernetics (new cybernetics). This paper provides a review of literature on software cybernetics, especially focuses on the transition from classical software cybernetics to modern software cybernetics. The results of the survey indicate that some new research areas such as Internet of Things, big data, cloud computing, cyber-physical systems, and even creative computing are related to modern software cybernetics. The paper identifies the relationships between the techniques of new cybernetics applied and the new research areas to which they have been applied; formulates research problems and challenges of software cybernetics with the application of principles of new cybernetics; identifies and highlights new research trends of modern software cybernetic for further research.

ABSTRACT: Background: Male infertility is a worldwide problem. In Africa it assumes a bigger dime... more ABSTRACT: Background: Male infertility is a worldwide problem. In Africa it assumes a bigger dimension due to its psychosocial implications. We reviewed the magnitude of the problem and outcome of management. Aim to study the pattern of male infertility, and outcome of its management. Materials and Methods: Male infertility patients managed at University Teaching Hospital Maiduguri (UMTH) between January 2008 to December 2012 were reviewed. Results-There were 73 patients, age ranged from 25-52 years with a mean of 38.35years. The peak age group was 30-39years with 45.20 % of the patients.The duration of the problem varied from months to over 10 years. Twenty five(34.25%) patients had STD. Co-morbid medical conditions were hypertension in 18(24.66%), diabetes 9(12.33%). Abnormal findings in the testes were varicoceles in 51(34.93%) testes while 7(4.79%) were undescended testes. Seminal fluid analysis revealed azospermia in 44(60.27%), oligospermia in 26(35.62%). Sixty- seven patients...

2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), 2017

Software Defined Networking (SDN) paradigm is introducing novel approaches for many unresolved is... more Software Defined Networking (SDN) paradigm is introducing novel approaches for many unresolved issues of networking. These new outlooks are imperative in emerging scenarios where user requirements keep growing, the required bandwidth keeps increasing, and so does the variety of applications (e.g. Big data analytics) that suggest the network plays a more prominent role. As such, our research aims to provide a novel adaptive (self-tuning) resource management technique in SDN-based InterCloud environments. A quality of service (QoS) policy control framework is presented by modelling QoS-aware resource management as an adaptive control problem, and using principles in coalition games with externalities or partition form games (PFGs) as control mechanism. This on-going work outlines a proposed dynamic programming and anytime approach (Integer partition based) to solve the multi-criteria optimisation problem of a Markov decision process (MDP) model for system dynamics in SDN-based InterCl...

More and more real-time IoT applications such as smart cities or autonomous vehicles require big ... more More and more real-time IoT applications such as smart cities or autonomous vehicles require big data analytics with reduced latencies. However, data streams produced from distributed sensing devices may not suffice to be processed traditionally in the remote cloud due to: (i) longer Wide Area Network (WAN) latencies and (ii) limited resources held by a single Cloud. To solve this problem, a novel Software-Defined Network (SDN) based InterCloud architecture is presented for mobile edge computing environments, known as EdgeIoT. An adaptive resource capacity management approach is proposed to employ a policy-based QoS control framework using principles in coalition games with externalities. To optimise resource capacity policy, the proposed QoS management technique solves, adaptively, a lexicographic ordering bi-criteria Coalition Structure Generation (CSG) problem. It is an onerous task to guarantee in a deterministic way that a real-time EdgeIoT application satisfies low latency req...

IEEE Access

Detecting and classifying driver distractions is crucial in the prevention of road accidents. The... more Detecting and classifying driver distractions is crucial in the prevention of road accidents. These distractions impact both driver behavior and vehicle dynamics. Knowing the degree of driver distraction can aid in accident prevention techniques, including transitioning of control to a level 4 semi-autonomous vehicle, when a high distraction severity level is reached. Thus, enhancement of Advanced Driving Assistance Systems (ADAS) is a critical component in the safety of vehicle drivers and other road users. In this paper, a new methodology is introduced, using an expert knowledge rule system to predict the severity of distraction in a contiguous set of video frames using the Naturalistic Driving American University of Cairo (AUC) Distraction Dataset. A multi-class distraction system comprises the face orientation, drivers' activities, hands and previous driver distraction, a severity classification model is developed as a discrete dynamic Bayesian (DDB). Furthermore, a Mamdani-based fuzzy system was implemented to detect multi-class of distractions into a severity level of safe, careless or dangerous driving. Thus, if a high level of severity is reached the semi-autonomous vehicle will take control. The result further shows that some instances of driver's distraction may quickly transition from a careless to dangerous driving in a multi-class distraction context. INDEX TERMS Fuzzy logic systems, driver distraction, severity level, ADAS, image processing, dynamic Bayesian.

Journal of Systems and Software, 2016

Software cybernetics research is to apply a variety of techniques from cybernetics research to so... more Software cybernetics research is to apply a variety of techniques from cybernetics research to software engineering research. For more than fifteen years since 2001, there has been a dramatic increase in work relating to software cybernetics. From cybernetics viewpoint, the work is mainly on the first-order level, namely, the software under observation and control. Beyond the first-order cybernetics, the software, developers/users, and running environments influence each other and thus create feedback to form more complicated systems. We classify software cybernetics as Software Cybernetics I based on the first-order cybernetics, and as Software Cybernetics II based on the higher order cybernetics. This paper provides a review of the literature on software cybernetics, particularly focusing on the transition from Software Cybernetics I to Software Cybernetics II. The results of the survey indicate that some new research areas such as Internet of Things, big data, cloud computing, cyber-physical systems, and even creative computing are related to Software Cybernetics II. The paper identifies the relationships between the techniques of Software Cybernetics II applied and the new research areas to which they have been applied, formulates research problems and challenges of software cybernetics with the application of principles of Phase II of software cybernetics; identifies and highlights new research trends of software cybernetic for further research.

2016 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), 2016

InterCloud Computing is a new cloud paradigm designed to guarantee service quality or performance... more InterCloud Computing is a new cloud paradigm designed to guarantee service quality or performance and availability of on-demand resources. InterCloud enables Cloud interoperability by promoting the interworking of Cloud systems from different cloud providers using standard interfacing. Resource management in InterCloud, considered as an important functional requirement, has not attracted commensurate research attention. The focus of this paper is to propose a Software Cybernetic approach, in the form of an adaptive control framework, for efficient management of shared resources in peer-to-peer InterCloud computing. This research effort adopts cooperative game theory to model resource management in InterCloud. The space of cooperative arrangements (resource sharing) between the participant cloud systems is presented by using Integer Partitioning to characterise the worst case communication complexity in peer to peer InterCloud. Essentially, this paper presents an Integer partition based anytime algorithm as an optimal cost solution to the bi-objective optimisation problem in resource management; anchored principally on practical trade-off between the desired performance (quality of service) and communication complexity of collaborating resource clouds.

2016 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), 2016

InterCloud Computing is a new cloud paradigm designed to guarantee service quality or performance... more InterCloud Computing is a new cloud paradigm designed to guarantee service quality or performance and availability of on-demand resources. InterCloud enables Cloud interoperability by promoting the interworking of Cloud systems from different cloud providers using standard interfacing. Resource management in InterCloud, considered as an important functional requirement, has not attracted commensurate research attention. The focus of this paper is to propose a Software Cybernetic approach, in the form of an adaptive control framework, for efficient management of shared resources in peer-to-peer InterCloud computing. This research effort adopts cooperative game theory to model resource management in InterCloud. The space of cooperative arrangements (resource sharing) between the participant cloud systems is presented by using Integer Partitioning to characterise the worst case communication complexity in peer to peer InterCloud. Essentially, this paper presents an Integer partition based anytime algorithm as an optimal cost solution to the bi-objective optimisation problem in resource management; anchored principally on practical trade-off between the desired performance (quality of service) and communication complexity of collaborating resource clouds.