Indonesian Journal of Electrical Engineering and Computer Science, Dec 31, 2023
Encryption methods had been widely used for secure data transmission and communication in both pu... more Encryption methods had been widely used for secure data transmission and communication in both public and private organizations against intruders. Rivest-shamir-adleman (RSA) encryption algorithm is one of the most popular and efficient encryption schemes that has been in used for decades. Due to technological advancement and innovation, there is a threat to this algorithm. It is believed that introduction of quantum computer will break RSA algorithm easily. In view of this, it is pertinent to research into how RSA algorithm could be strengthened against all adversaries. This research aim at protecting client/server communication and file sharing by generating dynamic public and private keys. The proposed method was implemented in visual basic.net 2008. The result shows that dynamic keys do not affect the performance of the system and it is capable of protecting communication and file sharing between client/server. As the key generated keeps changing at an interval, it will difficult for most advance computer to factor any of the keys before another key is generated. This is the basis of the security of the proposed system.
The portfolio selection of assets for an investment by investors has remain a challenge in buildi... more The portfolio selection of assets for an investment by investors has remain a challenge in building appropriate portfolio of assets when investing hard earned money into different assets in order to maximize returns and minimize associated risk. Different models have been used to resolve the portfolio selection problem but with some limitations due to the complexity and instantaneity of the portfolio optimization model, however, particle swarm optimization (PSO) algorithm is a good alternative to meet the challenge. This study applied cardinality and bounding constraints to portfolio selection model using a meta-heuristic technique of particle swarm optimization. The implementation of the developed model was done with python programming language. The results of this study were compared with that of the genetic algorithms technique as found in extant literature. The results obtained with the model developed shows that particle swarm optimization approach gives a better result than genetic algorithm in solving portfolio selection problem.
International journal of engineering research and technology, Jan 30, 2020
Malaria parasites adopt outstanding variation of life phases as they evolve through manifold mosq... more Malaria parasites adopt outstanding variation of life phases as they evolve through manifold mosquito vector atmospheres. Transcriptomes of thousands of individual parasites exists. Ribonucleic acid sequencing (RNA-seq) is a widespread method for gene expression which has resulted into improved understandings of genetical queries. RNA-seq compute transcripts of gene expressions. RNA-seq data necessitates analytical improvements of machine learning techniques. Several learning approached have been proposed by researchers for analysing biological data. In this study, PCA feature extraction algorithm is used to fetch latent components out of a high dimensional malaria vector RNA-seq dataset, and evaluates it classification performance using an Ensemble classification algorithm. The effectiveness of this experiment is validated on aa mosquito anopheles gambiae RNA-Seq dataset. The experiment result achieved a relevant performance metrics with a classification accuracy of 93.3%.
Business-to-business electronic procurement success in business organizations (private sectors) h... more Business-to-business electronic procurement success in business organizations (private sectors) has been a major driving force for government organizations (public sectors) in developed nations to adopt electronic government procurement in order to reduce cost and improve administrative efficiency. Eprocurement within the government is recognized to be the main area of government-to-business that needs to be exploited by government of developing nations. In this paper, we examined the drawbacks of existing procurement process in Nigeria with a view to offering an improved approach. A prototype e-GP system was designed and developed to eliminate the associated bottlenecks with existing system and showcase the attendant benefits of the proposed system which can lead to an improved procurement cycle process flow.
RNA-Seq data are utilized for biological applications and decision making for the classification ... more RNA-Seq data are utilized for biological applications and decision making for the classification of genes. A lot of works in recent time are focused on reducing the dimension of RNA-Seq data. Dimensionality reduction approaches have been proposed in the transformation of these data. In this study, a novel optimized hybrid investigative approach is proposed. It combines an optimized genetic algorithm with Principal Component Analysis and Independent Component Analysis (GA-O-PCA and GAO-ICA), which are used to identify an optimum subset and latent correlated features, respectively. The classifier uses KNN on the reduced mosquito Anopheles gambiae dataset, to enhance the accuracy and scalability in the gene expression analysis. The proposed algorithm is used to fetch relevant features based on the high-dimensional input feature space. A fast algorithm for feature ranking is used to select relevant features. The performances of the model are evaluated and validated using the classificat...
The detection of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), which is responsib... more The detection of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), which is responsible for coronavirus disease 2019 (COVID-19), using chest X-ray images has life-saving importance for both patients and doctors. In addition, in countries that are unable to purchase laboratory kits for testing, this becomes even more vital. In this study, we aimed to present the use of deep learning for the high-accuracy detection of COVID-19 using chest X-ray images. Publicly available X-ray images (1583 healthy, 4292 pneumonia, and 225 confirmed COVID-19) were used in the experiments, which involved the training of deep learning and machine learning classifiers. Thirty-eight experiments were performed using convolutional neural networks, 10 experiments were performed using five machine learning models, and 14 experiments were performed using the state-of-the-art pre-trained networks for transfer learning. Images and statistical data were considered separately in the experiments to evalu...
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Breast Cancer Detection Using a PSO-ANN Machine Learning Technique
Advances in medical technologies and clinical practice book series, Oct 14, 2022
Machine learning is employed in all facets of life. Breast cancer has been known to be the second... more Machine learning is employed in all facets of life. Breast cancer has been known to be the second most severe cancer that leads to death among women globally. The use of dimensionality reduction to reduce noise and eliminate irrelevant features from dataset is of enormous significant on breast cancer detection. In this study, particle swarm optimization (PSO) algorithm was employed to select relevant features from the data with artificial neural network for classification purpose on a University of California Irvine machine learning database dataset. The study was evaluated with the findings revealing the performance of the study at 97.13% accuracy. Conclusively, the aim of this study is to improve machine learning approach for breast cancer detection. This paper will be of help to radiologists in taking accurate results and making proper decisions regarding breast cancer early diagnosis based on machine learning.
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