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Comparative analysis of routing techniques in chord overlay network Omoruyi Osemwegie; Samuel John; Adewale Adeyinka; Etinosa Noma-Osaghae; Kennedy Okokpujie
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4361-4372

Abstract

Overlay networks are not a new field or area of study. This domain of computing will someday drive P2P systems in various application areas such as block-chain, energy trading, video multicasting, and distributed file storage. This study highlights the two widely known methods of routing information employed in one of such overlay networks called chord. In this study, simulations of both routing modes (iterative and recursive) and their variations under no-churn (leaving and joining of nodes) and churn conditions was carried out. The routing parameter (successor list size) was varied for each of the routing techniques in a simulation study. The results obtained show that semi recursive routing gives a better routing performance under churn scenarios.
Performance Benchmarking of Key-Value Store NoSQL Databases Omoruyi Osemwegie; Kennedy Okokpujie; Nsikan Nkordeh; Charles Ndujiuba; Samuel John; Uzairue Stanley
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (941.893 KB) | DOI: 10.11591/ijece.v8i6.pp5333-5341

Abstract

Increasing requirements for scalability and elasticity of data storage for web applications has made Not Structured Query Language NoSQL databases more invaluable to web developers. One of such NoSQL Database solutions is Redis. A budding alternative to Redis database is the SSDB database, which is also a key-value store but is disk-based. The aim of this research work is to benchmark both databases (Redis and SSDB) using the Yahoo Cloud Serving Benchmark (YCSB). YCSB is a platform that has been used to compare and benchmark similar NoSQL database systems. Both databases were given variable workloads to identify the throughput of all given operations. The results obtained shows that SSDB gives a better throughput for majority of operations to Redis’s performance.
Epidemic Alert System: A Web-based Grassroots Model Etinosa Noma Osaghae; Kennedy Okokpujie; Charles Ndujiuba; Olatunji Okesola; Imhade P. Okokpujie
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (816.656 KB) | DOI: 10.11591/ijece.v8i5.pp3809-3828

Abstract

Most web-based disease surveillance systems that give epidemic alerts are based on very large and unstructured data from various news sources, social media and online queries that are parsed by complex algorithms. This has the tendency to generate results that are so diverse and non-specific. When considered along with the fact that there are no existing standards for mining and analyzing data from the internet, the results or decisions reached based on internet sources have been classified as low-quality. This paper proposes a web-based grassroots epidemic alert system that is based on data collected specifically from primary health centers, hospitals and registered laboratories. It takes a more traditional approach to indicator-based disease surveillance as a step towards standardizing web-based disease surveillance. It makes use of a threshold value that is based on the third quartile (75th percentile) to determine the need to trigger the alarm for the onset of an epidemic. It also includes, for deeper analysis, demographic information.
Development of alcohol triggered vehicle engine lock system Ighalo Joshua; Uzairue Stanley; Ochonogor Charles; Amaize Peter; Kennedy Okokpujie
IAES International Journal of Robotics and Automation (IJRA) Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (420.731 KB) | DOI: 10.11591/ijra.v8i1.pp68-76

Abstract

Drunk driving is a very dangerous behavior caused as a result of excessive consumption of alcohol therefore causing distortion in the thought pattern of its victims with a large percentage being drivers of vehicles of all forms. Most of the traffic accidents recorded in recent years are related to drunk driving. Solutions have been proposed, devices developed, all to the sole aim which is to reduce traffic accidents due to drunk driving but none has been quite cable of impairing the driver’s ability to drive. To this end, we model and design an alcohol triggered vehicle engine lock system. This project’s ability to impair the driver’s ability to drive makes it stand out from previous methods or devices developed to reduce road accidents due to drunk driving. The entire system is based on a microcontroller that is used to set an alcohol limit/ threshold which when reached or crossed upon sensing of alcohol in the air by the alcohol sensor, would trigger the buzzer alarm and warning LED of the circuit to alert the driver that his/her blood alcohol concentration at that moment in time wouldn’t be safe for driving. At this point the system automatically locks the ignition system of the vehicle within which it is embedded while an LCD displays information for the driver’s visuals incase the driver’s sight isn’t also impaired while in the drunk state. This project is a prototype to what is proposed with the vehicle’s engine system represented with a DC motor and its ignition system represented with a push button. The overall work was implemented with a constructed work, tested working and perfectly functional.
A secured automated bimodal biometric electronic voting system Kennedy Okokpujie; John Abubakar; Samuel John; Etinosa Noma-Osaghae; Charles Ndujiuba; Imhade Princess Okokpujie
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 1: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i1.pp1-8

Abstract

Insecurity, rigging and violence continue to mar electoral processes in developing nations. It has been difficult to enforce security and transparency in the voting process. This paper proposes a secure and automated bimodal voting system. The system uses three security layers, namely, a unique ID code, a token passcode that expires every five minutes and biometrics (iris and fingerprint). A scanner captures the fingerprint and iris of eligible voters. The fingerprint and iris images stored along with the corresponding particulars in a database. The software implemented is a .net managed code in C#. The result of this system shows the system is transparent, fast and fraud-free. The proposed method had a failure to enroll (FTE) and a failure to capture (FTC) of zero.
MIMO channels: optimizing throughput and reducing outage by increasing multiplexing gain Oboyerulu Agboje; Nsikan Nkordeh; Uzairue Stanley Idiake; Ololade Oladoyin; Kennedy Okokpujie; Ibinabo Bob-Manuel
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 1: February 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i1.8720

Abstract

The two main aims of deploying multiple input multiple out (MIMO) are to achieve spatial diversity (improves channel reliability) and spatial multiplexing (increase data throughput). Achieving both in a given system is impossible for now, and a trade-off has to be reached as they may be conflicting objectives. The basic concept of multiplexing: divide (multiplex) transmit a data stream several branches and transmit via several (independent) channels. In this paper, we focused mainly on achieving spatial multiplexing by modeling the channel using the diagonal Bell Labs space time scheme (D-BLAST) and the vertical Bell Labs space time architecture (V-BLAST) Matlab simulations results were a lso given to further compare the advantages of spatial multiplexing.
Performance of MPLS-based Virtual Private Networks and Classic Virtual Private Networks Using Advanced Metrics Kennedy Okokpujie; Olamilekan Shobayo; Etinosa Noma-Osaghae; Okokpujie Imhade; Obinna Okoyeigbo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 5: October 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i5.7326

Abstract

Multiprotocol Label Switching (MPLS) is effective in managing and utilizing available network bandwidth. It has advanced security features and a lower time delay. The existing literature has covered the performance of MPLS-based networks in relation to conventional Internet Protocol (IP) networks. But, too few literatures exist on the performance of MPLS-based Virtual Private Networks (VPN) in relation to traditional VPN networks. In this paper, a comparison is made between the effectiveness of the MPLS-VPN network and a classic VPN network using simulation studies done on OPNET®. The performance metrics used to carry out the comparison include; End to End Delay, Voice Packet Sent/Received and Label Switched Path’s Traffic. The simulation study was carried out with Voice over Internet Protocol (VoIP) as the test bed. The result of the study showed that MPLS-based VPN networks outperform classic VPN networks.
Comparative analysis of augmented datasets performances of age invariant face recognition models Kennedy Okokpujie; Etinosa Noma-Osaghae; Samuel Ndueso John; Charles Ndujiuba; Imhade Princess Okokpujie
Bulletin of Electrical Engineering and Informatics Vol 10, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i3.3020

Abstract

The popularity of face recognition systems has increased due to their non-invasive method of image acquisition, thus boasting the widespread applications. Face ageing is one major factor that influences the performance of face recognition algorithms. In this study, the authors present a comparative study of the two most accepted and experimented face ageing datasets (FG-Net and morph II). These datasets were used to simulate age invariant face recognition (AIFR) models. Four types of noises were added to the two face ageing datasets at the preprocessing stage. The addition of noise at the preprocessing stage served as a data augmentation technique that increased the number of sample images available for deep convolutional neural network (DCNN) experimentation, improved the proposed AIFR model and the trait aging features extraction process. The proposed AIFR models are developed with the pre-trained Inception-ResNet-v2 deep convolutional neural network architecture. On testing and comparing the models, the results revealed that FG-Net is more efficient over Morph with an accuracy of 0.15%, loss function of 71%, mean square error (MSE) of 39% and mean absolute error (MAE) of -0.63%.
An improved age invariant face recognition using data augmentation Kennedy Okokpujie; Samuel John; Charles Ndujiuba; Joke A. Badejo; Etinosa Noma- Osaghae
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.2356

Abstract

In spite of the significant advancement in face recognition expertise, accurately recognizing the face of the same individual across different ages still remains an open research question. Face aging causes intra-subject variations (such as geometric changes during childhood and adolescence, wrinkles and saggy skin in old age) which negatively affects the accuracy of face recognition systems. Over the years, researchers have devised different techniques to improve the accuracy of age invariant face recognition (AIFR) systems. In this paper, the face and gesture recognition network (FG-NET) aging dataset was adopted to enable the benchmarking of experimental results. The FG-Net dataset was augmented by adding four different types of noises at the preprocessing phase in order to improve the trait aging face features extraction and the training model used at the classification stages, thus addressing the problem of few available training aging for face recognition dataset. The developed model was an adaptation of a pre-trained convolution neural network architecture (Inception-ResNet-v2) which is a very robust noise. The proposed model on testing achieved a 99.94% recognition accuracy, a mean square error of 0.0158 and a mean absolute error of 0.0637. The results obtained are significant improvements in comparison with related works.