European Journal of Computer Science and Information Technology
Most disease that affects the heart or blood vessels is referred to as cardiovascular disease(CVD... more Most disease that affects the heart or blood vessels is referred to as cardiovascular disease(CVD). The main aim of this work is to build a system capable of modeling and predicting early syndromic cardiovascular diseases (CVD) based on electrocardiogram (ECG). The study considers the implementation of computationally intelligent system for detecting and classifying early syndromic assessment of CVD. The clinical and ECG recordings of patients diagnosed with pulmonary hypertension at the University of Uyo Teaching Hospital (UUTH) were obtained. The datasets were segmented into Demographic and ECG datasets. A quantitative research approach was used for the study with examination of several segments based on recommended framework. Three (3) classifier models were adopted to detect cardiac related problems using specified datasets. The classifiers such as; Random Forest Ensemble (RFE), Support Vector (SVM) Classifier and Artificial Neural Network (ANN) was employed for Machine Learning...
Global Journal of Engineering and Technology Advances
Deep learning-based face recognition system have produced high accuracy and better performance wh... more Deep learning-based face recognition system have produced high accuracy and better performance when compared to other methods of face recognition like the eigen faces. Modern face recognition systems consist of different phases such as face detection, face alignment, feature extraction, face representation and face recognition. This paper proposes a deep learning approach in developing a face recognition-based class attendance system. The Multitask Convolutional Neural Network (MTCNN) is used for the face detection and alignment phase and a lightweight hybrid high performance Deepface Python framework based on the ‘Deepface’ Deep Convolutional Neural Network is employed for the feature extraction, face representation and face recognition phases with FaceNet-512 pretrained model. Because Convolutional Neural Networks (CNNs) perform better with larger datasets, image augmentation will be used on the original photos to enlarge the tiny dataset. The attendance record is stored in a MySQ...
A Delay/Disruption Tolerant Network (DTN) is an overlay on top of a number of diverse networks su... more A Delay/Disruption Tolerant Network (DTN) is an overlay on top of a number of diverse networks such as mobile ad hoc networks, wireless sensor networks, satellite networks, vehicular networks and the Internet. In terrestrial DTNs, the effectiveness of data dissemination is greatly affected by node mobility and end-to-end disconnections. The inherent mobility of nodes is exploited to forward data opportunistically when a contact arises through the store-carry-and-forward technique. Thus a DTN is characterized by limited bandwidth, long queuing delays, low data rate, low power and intermittent connectivity. The real challenge is how to make DTN resilient against Denial of Service (DoS) attacks. In this thesis, we have investigated several DoS mitigating schemes for wired and wireless networks and found most of them to be highly interactive requiring several protocol rounds, resource-consuming, complex, assume persistent connectivity and hence not suitable for DTN. This thesis proposes three variants of DTN-Cookies of which any is selected as the light-weight authenticator based on the perceived Network Threat Level. For the intra-region scenario, it proposes a DoS-Resilient Authentication Mechanism to mitigate the effect of resource exhaustion DoS attacks. For the inter-region scenario, it proposes an enhanced version of the DoS-Resilient Authentication Mechanism. The proposed mechanism exploits the loose time-synchronization property of DTN, dividing communication contact time into timeslots. The mechanism uses variable seed values in different time slots for the computation and verification of DTN-Cookies, incorporates an ingress filter at the region gateways and uses the HMAC variant of DTN-Cookie. This work also proposes a comprehensive defence mechanism against flooding DoS attacks. The aim of the proposed mechanism is to restrict the volume of malicious traffic during an attack. The rate limiting component monitors the number of bundles per traffic flow and different nodes are assigned different threshold values based on their capability and role in the network. The results show that the proposed DTN-Cookies accurately detect DoS attacks and outperform RSA-1024 digital signatures in terms of energy and bandwidth efficiency. The proposed mechanisms have been verified through simulations and their superior performance is established over solutions which are based purely on Public-Key Cryptography
Performance evaluation based on some cognitive factors especially Students’ Intelligent Quotient ... more Performance evaluation based on some cognitive factors especially Students’ Intelligent Quotient rating (IQR), Confidence Level (CoL) and Time Management ability gives an equal platform for better evaluation of students’ performance using Artificial Neural Network. Artificial Neural Networks (ANN) models, which has the advantage of being trained, offers a more robust methodology and tool for predicting, forecasting and modeling phenomena to ascertain conformance to desired standards as well as assist in decision making. This work employs Machine Learning and cognitive science which uses Artificial Neural networks (ANNs) to evaluated students’ academic performance in the Department of Computer Science, Akwa Ibom State University. It presents a survey of the design, building and functionalities of Artificial Neural Network for the evaluation of students’ academic performance using cognitive factors that could affect student’s performances. Keywords : Cognitive, Intelligent Quotient Ra...
A Delay/Disruption Tolerant Network (DTN) is an overlay on top of a number of diverse networks su... more A Delay/Disruption Tolerant Network (DTN) is an overlay on top of a number of diverse networks such as mobile ad hoc networks, wireless sensor networks, satellite networks, vehicular networks and the Internet. In terrestrial DTNs, the effectiveness of data dissemination is greatly affected by node mobility and end-to-end disconnections. The inherent mobility of nodes is exploited to forward data opportunistically when a contact arises through the store-carry-and-forward technique. Thus a DTN is characterized by limited bandwidth, long queuing delays, low data rate, low power and intermittent connectivity. The real challenge is how to make DTN resilient against Denial of Service (DoS) attacks. In this thesis, we have investigated several DoS mitigating schemes for wired and wireless networks and found most of them to be highly interactive requiring several protocol rounds, resource-consuming, complex, assume persistent connectivity and hence not suitable for DTN. This thesis proposes...
Denial of Service (DoS) attacks have been amajor threat in the Internet and in other emerging net... more Denial of Service (DoS) attacks have been amajor threat in the Internet and in other emerging networks including DelayTolerant Networks (DTNs). A DTN is characterized by limited bandwidth, longqueuing delays, low data rate, low power and intermittent connectivity. Most ofthe proposed DoS mitigation schemes for wired and wireless networks are highlyinteractive requiring several protocol rounds. They are also resourceconsuming, complex and assume intermittent connectivity. These features makethe applicability of proposed schemes unsuitable in a DTN scenario. An attackercan exploit the DTN message forwarding mechanism to inject fake bundles intothe network. The attacker’s overall objective is to deplete node and linkresources such as CPU processing cycles, battery power, memory and bandwidth.In this paper, we propose a proactive DoS-Resilient Authentication Mechanism(DoSRAM). The proposed mechanism uses three message authenticator variantscalled DTN-Cookies to minimize computational an...
European Journal of Computer Science and Information Technology
Most disease that affects the heart or blood vessels is referred to as cardiovascular disease(CVD... more Most disease that affects the heart or blood vessels is referred to as cardiovascular disease(CVD). The main aim of this work is to build a system capable of modeling and predicting early syndromic cardiovascular diseases (CVD) based on electrocardiogram (ECG). The study considers the implementation of computationally intelligent system for detecting and classifying early syndromic assessment of CVD. The clinical and ECG recordings of patients diagnosed with pulmonary hypertension at the University of Uyo Teaching Hospital (UUTH) were obtained. The datasets were segmented into Demographic and ECG datasets. A quantitative research approach was used for the study with examination of several segments based on recommended framework. Three (3) classifier models were adopted to detect cardiac related problems using specified datasets. The classifiers such as; Random Forest Ensemble (RFE), Support Vector (SVM) Classifier and Artificial Neural Network (ANN) was employed for Machine Learning...
Global Journal of Engineering and Technology Advances
Deep learning-based face recognition system have produced high accuracy and better performance wh... more Deep learning-based face recognition system have produced high accuracy and better performance when compared to other methods of face recognition like the eigen faces. Modern face recognition systems consist of different phases such as face detection, face alignment, feature extraction, face representation and face recognition. This paper proposes a deep learning approach in developing a face recognition-based class attendance system. The Multitask Convolutional Neural Network (MTCNN) is used for the face detection and alignment phase and a lightweight hybrid high performance Deepface Python framework based on the ‘Deepface’ Deep Convolutional Neural Network is employed for the feature extraction, face representation and face recognition phases with FaceNet-512 pretrained model. Because Convolutional Neural Networks (CNNs) perform better with larger datasets, image augmentation will be used on the original photos to enlarge the tiny dataset. The attendance record is stored in a MySQ...
A Delay/Disruption Tolerant Network (DTN) is an overlay on top of a number of diverse networks su... more A Delay/Disruption Tolerant Network (DTN) is an overlay on top of a number of diverse networks such as mobile ad hoc networks, wireless sensor networks, satellite networks, vehicular networks and the Internet. In terrestrial DTNs, the effectiveness of data dissemination is greatly affected by node mobility and end-to-end disconnections. The inherent mobility of nodes is exploited to forward data opportunistically when a contact arises through the store-carry-and-forward technique. Thus a DTN is characterized by limited bandwidth, long queuing delays, low data rate, low power and intermittent connectivity. The real challenge is how to make DTN resilient against Denial of Service (DoS) attacks. In this thesis, we have investigated several DoS mitigating schemes for wired and wireless networks and found most of them to be highly interactive requiring several protocol rounds, resource-consuming, complex, assume persistent connectivity and hence not suitable for DTN. This thesis proposes three variants of DTN-Cookies of which any is selected as the light-weight authenticator based on the perceived Network Threat Level. For the intra-region scenario, it proposes a DoS-Resilient Authentication Mechanism to mitigate the effect of resource exhaustion DoS attacks. For the inter-region scenario, it proposes an enhanced version of the DoS-Resilient Authentication Mechanism. The proposed mechanism exploits the loose time-synchronization property of DTN, dividing communication contact time into timeslots. The mechanism uses variable seed values in different time slots for the computation and verification of DTN-Cookies, incorporates an ingress filter at the region gateways and uses the HMAC variant of DTN-Cookie. This work also proposes a comprehensive defence mechanism against flooding DoS attacks. The aim of the proposed mechanism is to restrict the volume of malicious traffic during an attack. The rate limiting component monitors the number of bundles per traffic flow and different nodes are assigned different threshold values based on their capability and role in the network. The results show that the proposed DTN-Cookies accurately detect DoS attacks and outperform RSA-1024 digital signatures in terms of energy and bandwidth efficiency. The proposed mechanisms have been verified through simulations and their superior performance is established over solutions which are based purely on Public-Key Cryptography
Performance evaluation based on some cognitive factors especially Students’ Intelligent Quotient ... more Performance evaluation based on some cognitive factors especially Students’ Intelligent Quotient rating (IQR), Confidence Level (CoL) and Time Management ability gives an equal platform for better evaluation of students’ performance using Artificial Neural Network. Artificial Neural Networks (ANN) models, which has the advantage of being trained, offers a more robust methodology and tool for predicting, forecasting and modeling phenomena to ascertain conformance to desired standards as well as assist in decision making. This work employs Machine Learning and cognitive science which uses Artificial Neural networks (ANNs) to evaluated students’ academic performance in the Department of Computer Science, Akwa Ibom State University. It presents a survey of the design, building and functionalities of Artificial Neural Network for the evaluation of students’ academic performance using cognitive factors that could affect student’s performances. Keywords : Cognitive, Intelligent Quotient Ra...
A Delay/Disruption Tolerant Network (DTN) is an overlay on top of a number of diverse networks su... more A Delay/Disruption Tolerant Network (DTN) is an overlay on top of a number of diverse networks such as mobile ad hoc networks, wireless sensor networks, satellite networks, vehicular networks and the Internet. In terrestrial DTNs, the effectiveness of data dissemination is greatly affected by node mobility and end-to-end disconnections. The inherent mobility of nodes is exploited to forward data opportunistically when a contact arises through the store-carry-and-forward technique. Thus a DTN is characterized by limited bandwidth, long queuing delays, low data rate, low power and intermittent connectivity. The real challenge is how to make DTN resilient against Denial of Service (DoS) attacks. In this thesis, we have investigated several DoS mitigating schemes for wired and wireless networks and found most of them to be highly interactive requiring several protocol rounds, resource-consuming, complex, assume persistent connectivity and hence not suitable for DTN. This thesis proposes...
Denial of Service (DoS) attacks have been amajor threat in the Internet and in other emerging net... more Denial of Service (DoS) attacks have been amajor threat in the Internet and in other emerging networks including DelayTolerant Networks (DTNs). A DTN is characterized by limited bandwidth, longqueuing delays, low data rate, low power and intermittent connectivity. Most ofthe proposed DoS mitigation schemes for wired and wireless networks are highlyinteractive requiring several protocol rounds. They are also resourceconsuming, complex and assume intermittent connectivity. These features makethe applicability of proposed schemes unsuitable in a DTN scenario. An attackercan exploit the DTN message forwarding mechanism to inject fake bundles intothe network. The attacker’s overall objective is to deplete node and linkresources such as CPU processing cycles, battery power, memory and bandwidth.In this paper, we propose a proactive DoS-Resilient Authentication Mechanism(DoSRAM). The proposed mechanism uses three message authenticator variantscalled DTN-Cookies to minimize computational an...
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Papers by Godwin Ansa