Papers by Yusuf Musa Malgwi
Remote Sensing Data Analysis in Machine Learning and Proposed Quantum Computational Intelligence: A Meta-Analysis
Communications
Advances in Networks
Computer vision is a multidisciplinary field that cannot be separated with image processing techn... more Computer vision is a multidisciplinary field that cannot be separated with image processing techniques and Neuro-Computing specifically Deep Learning (DL) algorithms, in recent time DL techniques enable computer vision to understand the content of an image, moreover, it is working hand in hand with image processing techniques because image preprocessing are essential components in digital image analysis. Therefore, the remarkable advancement recorded by computer vision today such as in remote sensing, security, medical imaging and robotics etc. The aim of this research work was to explored the technical and theoretical contributions of image processing techniques and DL algorithms to computer vision. A systematic method of literature review was adapted. Basic image processing techniques such as standardization, denoising, filtering, and segmentation are clearly explored, concept of DL algorithms are briefly discussed, recent reviewed articles (from 2018 to date) are obtained from top journals in computer vision thus; IEEE, Elsevier and ISPR and tabulated as a major source of information for this work. We have shown some of the software's used for the implementation of deep learning researches in computer vision. Finally we concludes and give recommendations based on our findings.
Computer Science & IT Research Journal
Liver cirrhosis is the most common type of chronic liver disease in the globe. The ability to for... more Liver cirrhosis is the most common type of chronic liver disease in the globe. The ability to forecast the onset of liver cirrhosis sickness is critical for successful treatment and the prevention of catastrophic health implications. As a result, the researchers created a prediction model using machine learning techniques. This study was based on a dataset from the Federal Medical Centre, Yola, which included 583 patient instances and 11 attributes. The proposed model for the prediction of liver cirrhosis sickness employed Nave Bayes, Classification and Regression Tree (CART), and Support Vector Machine (SVM) with 10-fold cross-validation. Accuracy, precision, recall, and F1 Score were used to evaluate the model's performance. Among all the strategies used in this study, the Support Vector Machine (SVM) technique produces the best results, with accuracy of 73%, precision of 73%, recall of 100%, and F1 Score of 84%. Based on medical data from FMC, Yola, this study shows that mach...
Mediterranean Journal of Basic and Applied Sciences, 2022
Artificial Intelligence (AI) breakthroughs in the last few years have accelerated dramatically as... more Artificial Intelligence (AI) breakthroughs in the last few years have accelerated dramatically as a result of the industry's vast technological use. Neural Networks (NN) is one of the most vital areas of AI, as they allow for commercial use of features that were previously not accessible via the use of computers. The Intrusion Detection System (IDS) is one of the areas in which Neural Networks are being extensively investigated to provide comprehensive computer network security and data confidentiality. During the realization of this work Artificial Neural Network (ANN) were used to shape the proposed model using a realistic CICIDS2017 dataset retrieved from the Canadian Institute for Cyber-Security (CIC) website. Following implementation and testing, it was discovered that the new model performs exceptionally well, with an average. In addition, the receiver operator characteristic curve (ROC) has a 9.999 % area under the Receiver Operator Characteristic Curve (AUC). Finally, it...
Computer Science & IT Research Journal, 2021
The hepatitis B virus causes a liver infection called hepatitis B (HBV). It might be severe and g... more The hepatitis B virus causes a liver infection called hepatitis B (HBV). It might be severe and go away on its own. Some kinds, however, can be persistent, leading to cirrhosis and liver cancer. HBV can be transmitted to others without the individual being aware of it; some persons have no symptoms, while others only have the first infection, which later resolves. Others develop a chronic illness as a result of their condition. In chronic cases, the virus attacks the liver for an extended period of time without being detected, causing irreparable liver damage. The manual approach has a high number of errors due to human decision-making, and visual screening is time-consuming, tiresome, and costly in terms of manpower. To predict the occurrence of Hepatitis virus (HBV), this research project thesis suggested an algorithm; Artificial Neural Network (ANN), and genetic algorithm (GA). To develop, evaluate and validate the performance of the model developed using ANN. Medical records of ...
OIRT Journal of Information Technology, 2022
Background: The processor affinity library in Java can switch ON all the processing cores availa... more Background: The processor affinity library in Java can switch ON all the processing cores available in a multi-processing environment. Using this feature will enable concurrent programmers to fully utilize the benefits of processing power available in multi-core processors. Therefore, this study aims to use processor affinity to develop four different frameworks that could optimize the efficiency of quick sorting algorithms on multi-core platforms. Methods: Benchmarking is the method used to carry out all the experiments and test the developed algorithm's efficiencies using all four frameworks. An Octa-core machine with eight (8) processing cores was used to develop and run the algorithms to measure their running times and compare their performances. JDK 12.0 is the version of Java used for development. An array data structure containing One Million Elements (1,000,000) was used as the preferred data structure. Results: The results obtained show that processor affinity can...
Communications, 2021
The accurate multi-detection of objects in satellite images has become very essential due to the ... more The accurate multi-detection of objects in satellite images has become very essential due to the high criminal activities that posed security threat to humanity all over the world. However, there are significant limitations of traditional methods of multi-object detection such as matching based techniques and object based image analysis. Although Convolutional neural network and image processing techniques has been proved to be essential fields in so many applications of computer vision specifically multi-object detection, multi-object classification, object retrieval, object recognition and object segmentation in a digital image or video, however, multi-object detection especially in satellite images suffer from problems such as shadow, camouflage, and occlusion. The aim of this research work was to design a robust multi-class object detection model in satellite images using image processing techniques and convolutional neural network with a particular concern on image preprocessing, image denoising and image enhancement to enable address the issue of noise in satellite images. The Satellite image that are propose for this model is LandSat-8, because it is free access for research and have a tract record in terms of consistency. The proposed model applied supervised learning algorithm for training different samples of labeled data for the model to enable the system detect vegetation, water bodies, road networks and building. This research will enable the government to know the positions as well as the coordinates of every thick forest, drainage, road networks and buildings in the forest for security reasons. It is at the heart of this research to pave away for the full implementation of this model using either MATLAB or Python Programming.
Computer Science & IT Research Journal, 2022
The rate of mortality in the recent time because of tuberculosis disease is so alarming. Drug-Res... more The rate of mortality in the recent time because of tuberculosis disease is so alarming. Drug-Resistant Tuberculosis is a communicable disease very dangerous that attack lungs, many victims were not identified due to weak health systems facilities, poor doctor-patient relationship, and inefficient mechanisms for predicting of the disease. Data mining can be applied on medical data to foresee novel, useful and potential knowledge that can save a life, reduce treatment cost, increases diagnostic and prediction accuracy as well as delay taking during prediction which reduce the treatment cost of a patience. Several data mining technique such as classification, clustering, regression, and association rule were used to enhance the prediction of tuberculosis. In this project I used Naïve Bayes Classifier to design a model for predicting tuberculosis. I considered the following parameters; Gender, Chills, Fever, Night sweat, Fatigue, Cough with Blood, Weight loss, and Loss of Appetite for ...
Telah dihasilkan sebuah Sistem Informasi Manajemen (SIM) Nursery anggrek dengan pendekatan pengem... more Telah dihasilkan sebuah Sistem Informasi Manajemen (SIM) Nursery anggrek dengan pendekatan pengembangan yang hijau. Salah satu target konsep pengembangan perangkat lunak yang hijau, adalah menghasilkan sebuah perangkat lunak yang ketika digunakan tidak akan membutuhkan kinerja CPU yang besar, memerlukan bandwith dan memory yang kecil, serta ketika dipasang tidak berukuran besar. Pengujian aspek kehijauan dari SIM Nursery Anggrek yang dihasilkan perlu untuk dilakukan. Penelitian ini berupaya untuk memperlihatkan hasil pengujian terhadap penggunaan CPU, memory, dan waktu komputasi. Tahapan penelitian terdiri dari pengujian, analisis hasil, dan terakhir perbaikan sistem. Hasil pengujian menunjukkan bahwa SIM Nursery Anggrek Versi 1 masih relevan untuk digunakan dalam jumlah record 0-1500 data. Penggunaan library JavaScript dalam pagination menyebabkan SIM Nursery Anggrek membutuhkan waktu komputasi yang lama, menggunakan CPU yang besar, dan memory footprint yang tidak sedikit. SIM Nurs...
Computer Science & IT Research Journal, 2021
An expert system is a computer program designed to solve problems in a domain that has human expe... more An expert system is a computer program designed to solve problems in a domain that has human expertise. The knowledge built into the system is usually obtained from experts in the field. Based on this knowledge, an expert system can replicate the thinking process of the human experts and make logical deductions accordingly. Malaria and Typhoid are major health challenge in our society today (Nigeria), its symptoms can lead to other illness which include prolonged fever, fatigue, headaches, nausea, abdominal pain and constipation or diarrhea. People in endemic areas are at risk of contracting both infections concurrently. According to the world malaria report 2011, there were about 216 million cases of malaria and typhoid and estimated 655,000 deaths in 2010. (WHO report, 2011). The main challenging issue confronting the healthcare is lack of quality of service at minimal cost implying from diagnosing to predicting patients correctly. This issue can sometimes lead to an unfortunate c...
American Journal of Data Mining and Knowledge Discovery, 2019
Breast cancer is one of the most hazardous of all types of cancer affecting mainly women. It is t... more Breast cancer is one of the most hazardous of all types of cancer affecting mainly women. It is the second leading cause of death in Nigerian women. It is difficult to classify breast tumour. The diagnosis of breast cancer on patients in hospitals and clinics is highly subjective and it is reliant on the physician's expertise. This may often lead to incorrect diagnosis and long waiting time to diagnose breast tumour which may increase the possibility of Cancer metastasizing. This study focused on developing a multi-agent based model for diagnosis of breast tumours using the k-Nearest Neighbor (k-NN) algorithm by classifying the nature of the tumours based on their associated patterns of symptoms and other risk factors of Cancer diseases. A k-NN algorithm using Java and MYSQ was developed to extract and classify the symptoms associated with Breast Cancer. Java Agent Development Environment (JADE) was used for the modeling and simulation. The accuracy score was tested on a breast tumour clinical datasets which were gotten and formed from Federal Medical Centers (FMC) Yola and Gombe in Nigeria. The experimental result of the prediction model shows a percentage accuracy score of 98.9%.
International Journal of Database Theory and Application, 2017
Road traffic accidents, the inadvertent crash involving at least one motor vehicle, occurring on ... more Road traffic accidents, the inadvertent crash involving at least one motor vehicle, occurring on a road open to public circulation, in which at least one person is injured or killed; intentional acts (murder, suicide) and natural disasters excluded, is indisputably one of the most frequent and most damaging calamities bedeviling human societies, in particular, Nigeria, today. It is therefore, of paramount importance to seek to identify the root causes of road traffic accidents in order to proffer mitigating solutions to address the menace. This research, aimed at predicting the likely causes of road accidents, its prone locations and time along Kano-Wudil highway in order to take all necessary counter measures is a step forward in this direction. In this study data mining decision tree algorithm was used to predict the causes of the accidents, its prone locations and time along Kano-Wudil Highway that links Kano State to Wudil Local Government Area Kano State for effective decision making.
Chinese Physics Letters, 2003
The preparation and results of investigations of nonlinear optical properties of LiCaBO 3-Ag 2 O ... more The preparation and results of investigations of nonlinear optical properties of LiCaBO 3-Ag 2 O and LiCaBO 3-Gd 2 O 3-Ag 2 O glasses with Ag nanoparticles (Ag NPs) formed by thermal treatment in vacuum and in air are presented. The intensive plasmon absorption Ag NPs in optical transmission spectra were observed. Nonlinear optical properties of glasses by single-beam Z-scan technique were investigated: it was ascertained an influence of Ag NPs on their nonlinear optical properties, in particular, changes of nonlinear refractive index n 2 , and nonlinear absorption coefficient b.
Deep Learning Models for Predicting COVID-19 Using Chest X-Ray Images
Trends and Advancements of Image Processing and Its Applications, 2021
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Papers by Yusuf Musa Malgwi