1. DESIGN AND IMPLEMENTATION OF A MEDICAL DIAGNOSTIC SYSTEM
BACKGROUND OF STUDY
Medical diagnosis, (often simply termed diagnosis) refers both to the process of attempting to determine or identifying a possible disease or disorder to the opinion reached by this process. A diagnosis in the sense of diagnostic procedure can be re...
2. DESIGN AND IMPLEMENTATION OF A MEDICAL DIAGNOSTIC SYSTEM
BACKGROUND OF STUDY
Medical diagnosis, (often simply termed diagnosis) refers both to the process of attempting to determine or identifying a possible disease or disorder to the opinion reached by this process. A diagnosis in the sense of diagnostic procedure can be re...
3. SMART TRAFFIC CONTROL SYSTEM USING YOLO-MODEL
Background of the study
Traffic congestion is a major problem in many cities, and the fixed-cycle light signal controllers are not resolving the high waiting time in the intersection. We see often a policeman managing the movements instead of the traffi...
4. DEVELOPMENT OF A DEEP LEARNING BASED VEHICLE LICENSE PLATE DETECTION SCHEME
ABSTRACT
This research developed a license plate and classification scheme using deep learning architecture which utilized transfer learning using pre-trained Convolutional Neural Network (CNN). The developed scheme used images obtained from Caltech dataset, Peking University VehicleID...
5. DEVELOPMENT OF AN IMPROVED SHORT-TERM PEAK LOAD FORECASTING MODEL BASED ON SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE AND NONLINEAR AUTOREGRESSIVE NEURAL NETWORK FOR NIGERIA POWER SYSTEM GRID
ABSTRACT
Electricity demand forecasting is a central and integral process for planning periodical operations and facility expansion in the electricity sector. Demand pattern is very complex due to the highly unpredictable behavior of consumers load consumption. Therefore, finding an app...
6. HARMONICS MITIGATION ON VARIABLE FREQUENCY DRIVE USING SINGLE PHASE SHUNT ACTIVE POWER FILTER CONTROLLED BY ARTIFICIAL NEURAL NETWORK
ABSTRACT
This research presents effect of harmonic generated by variable frequency drives (VFD).In the past, electrical power system equipment and devices were designed to produce nearly sinusoidal voltage and current waveforms. However, nowadays, with much interest and wide spreads of...
7. PREDICTING STUDENTS ACADEMIC PERFORMANCE USING ARTIFICIAL NEURAL NETWORK
BACKGROUND TO THE STUDY
Predicting student academic performance has long been an important research topic. Among the issues of education system, questions concerning admissions into academic institutions (secondary and tertiary level) remain important (Ting, 2008). The...
8. Improving Deep Representations by Incorporating Domain Knowledge and Modularization for Synthetic Aperture Radar and Physiological Data
Abstract
Machine Learning (ML) using Artificial Neural Networks (ANNs), referred to as Deep Learning (DL), is a very popular and powerful method of statistical inference. A primary advantage of deep-learning has been the automatic learning of informative features (that encodes the data...
9. LEARNING FROM NATURAL HUMAN INTERACTIONS FOR ASSISTIVE ROBOTS
ABSTRACT.
In our everyday lives, we interact with agents like personal computers, search engines, cars, etc., and reveal many of our personal choices, biases, and preferences. Improving agents by analyzing their interactions with humans is an active area of research. However, the algori...
10. Predicting High Stress Regions in a Microstructure using Convolutional Neural Networks
Abstract
Origins of failure are often driven by localizations in material response due to the applied stress/strain state. These stress “hot spots” intuitively represent regions that accumulate higher damage than their surroundings, serving as prime locations for crack nucle...
11. DESIGN & IMPLEMENTATION OF A NEURAL MACHINE TRANSLATION SYSTEM (LET’S TALK) FOR THE TRANSLATION OF HYAM TO ENGLISH
ABSTRACT
In Southern Kaduna, the Hyam Community always welcome foreigners every year, due to their friendliness and hospitable nature. They have even welcomed Igbos in the past and when the Hausas wanted to kill them, they hid them and gave them a safe route back to the east. Now with t...
12. DESIGN AND IMPLEMENTATIONOF A MEDICAL DIAGNOSTIC SYSTEM
BACKGROUND OF STUDY
Medical diagnosis, (often simply termed diagnosis) refers both to the process of attempting to determine or identifying a possible disease or disorder to the opinion reached by this process. A diagnosis in the sense of diagnostic procedure can be regarded as an attem...
13. DEVELOPMENT OF AN INTERNET OF THINGS BASED WATER MANAGEMENT SYSTEM USING DECISION TREE AND DEEP NEURAL NETWORK ALGORITHMS
ABSTRACT
Distribution of Water has been a major source of concern all over the world. Despite the fact that water is a scarce commodity, a lot of human activities in terms of poor management such as opening taps when not needed and careless attitudes towards broken pipes contribute to p...
14. APPLICATION OF GEOGRAPHIC INFORMATION SYSTEM TECHNOLOGY IN ANALYSING URBAN DENSIFICATION AND HOUSING MARKET IN BIDA, NIGERIA
ABSTRACT
Urban densification is as a result of increase in the level of urbanisation of a limited area which causes challenges in the housing affordability due to the increase in price of houses, high rental values, high demand and shortage in supply to meet the need of the urban reside...
15. ARTIFICIAL NEURAL NETWORK BASED PREDICTION AND COOLING ENRGY OPTIMIZATION OF DATA CENTERS
ABSTRACT
Thermal management of data centers remains a challenge because of their everincreasing power densities and decreasing server footprints. Current lack of dynamic control over global provisioning and local distribution of cooling resources often result in wasteful overcooling. Th...
16. RAINFALL PREDICTION FOR MINNA METROPOLIS USING ARTIFICIAL NEURAL NETWORK
ABSTRACT
The effect of rainfall in our society today is stupendous. Rainfall is seen as a benefit to crops and lives. Accurate and timely rainfall prediction can be very helpful for effective security measures for planning water resources management, transportation activities, agricultu...
17. INHIBITION OF PLANT LEAF EXTRACTS ON ALUMINUM AND MILD STEEL IN ACIDIC AND ALKALINE MEDIA USING DIFFERENT TECHNIQUES
Statement of the Problem
The obnoxious state of the Nigerian manufacturing sector has created a dire need for accurate bankruptcy prediction models about the overall outlook of companies. This is precipitated on the overbearing consequences of corporate bankruptcy on key stakeholders. P...
18. KINETICS AND ENGINE PERFORMANCE OF BIODIESEL PRODUCED FROM SELECTED NON EDIBLESEEDSOILS USING ACTIVATED CLAY CATALYSTS
ABSTRACT
The kinetics and engine performance of biodiesel from African pear seed oil (APO) and Gmelina seed oil (GSO) by modified clay catalysts were carried out. The catalyst was synthesized by activating it with heat, phosphoric acid and sodium hydroxide. They were characterized using...
19. KINETICS AND OPTIMIZATION OF PHENOL UPTAKE FROM AQUEOUS SOLUTION USING AGRICULTURAL WASTES
ABSTRACT The uptake of phenol from simulated aqueous solution using agricultural wastes as adsorbents is the focus of this research work. The agricultural wastes used were corn cob and rice husk which were modified with tetraoxophosphate V acid (H3PO4) and carbonized to give corn cob activated ca...
20. DEEP LEARNING BASED CERVICAL CANCER DISEASE DETECTION AND CLASSIFICATION MODEL
Abstract
Cervical cancer is the second most common and second most deadly cancer in Ethiopia. The disease's incidence and prevalence are increasing over time due to population growth and aging, as well as an...
21. The Impact of Artificial Intelligence Tools in Medical Imaging and Disease Prediction: A Case Study of General Hospital, Nasarawa State.
1.1 Background of the Study
Artificial Intelligence (AI) has emerged as a transformative force in healthcare, particularly in medical imaging and disease prediction. By leveraging machine learning algorithms and deep neural networks, AI systems can analyze complex medical data, enabling...
22. THE EFFECT OF ARTIFICIAL INTELLIGENCE IN PREDICTING RAINFALL PATTERNS: A CASE STUDY OF NIGERIAN METEOROLOGICAL AGENCY, KANO STATE
Background of the Study
Accurate rainfall prediction is essential for agriculture, water resource management, and disaster preparedness. In Nigeria, unpredictable rainfall patterns have led to challenges in agricultural planning, flooding, and water scarcity. The Nigeri...
23. The Role of Artificial Intelligence Applications in Climate Modeling for Northern Nigeria: A Case Study of Nigerian Meteorological Agency, Bauchi State
1.1 Background of the Study
Climate modeling plays a crucial role in understanding and mitigating the impacts of climate change. Northern Nigeria faces significant environmental challenges, including desertification, erratic rainfall patterns, and rising temperatures, which threaten agr...
24. A Review of the Role of Machine Learning in Demand Forecasting: A Case Study of Guinness Nigeria in Kwara State
Background of the Study
Demand forecasting plays a critical role in supply chain management by predicting future customer demands, optimizing inventory levels, and reducing costs. Traditional forecasting methods, such as time series analysis and regression models, often fa...
25. An Assessment of the Impact of Machine Learning in Fraud Detection: A Study of Fintech Firms in Kwara State
Background of the Study
Machine learning (ML) has become an integral tool in fraud detection, enabling organizations to analyze vast datasets and identify anomalous patterns indicative of fraudulent activities. ML algorithms such as decision trees, neural networks, and...
26. An Assessment of Deep Learning Algorithms for Customer Behavior Forecasting: A Case Study of Online Shopping Platforms in Taraba State
Background of the Study
Deep learning algorithms, a subset of machine learning, have shown considerable promise in transforming industries by enabling more accurate predictions and automating complex tasks. In the context of online retail, deep learning...
27. An Appraisal of AI-Driven Fraud Detection Models in Nigerian Banks: A Case Study in Yobe State
Background of the Study
Fraud detection is a critical component of the banking sector’s operational framework, with artificial intelligence (AI) playing a transformative role. AI-driven models, such as neural networks and machine learning algorith...
28. The Effect of Data Mining on Credit Risk Assessment: A Study of Microfinance Institutions in Taraba State
Background of the Study
Credit risk assessment is a critical process for financial institutions, particularly microfinance institutions (MFIs), which often cater to clients with limited credit histories. Data mining, a technique for extracting patterns...
29. An Assessment of Deep Learning Models for Demand Forecasting: A Case Study of FMCG Companies in Kano State
Background of the Study
Demand forecasting is a critical function for fast-moving consumer goods (FMCG) companies, enabling them to predict future customer demand and make informed decisions about inventory, production, and supply chain management. Traditional forecasti...
30. An Examination of Statistical Models in Predicting Tuberculosis Prevalence in Kano State
Background of the Study
Tuberculosis (TB) remains a major public health concern in Nigeria, ranking among the top 10 causes of mortality and morbidity in the country (WHO, 2024). Kano State, located in northern Nigeria, has one of the highest TB prevalence rates due to factors such as p...
31. Comparative Study of Machine Learning Techniques for Predicting Student Dropout in Bayero University, Kano, Kano State
Background of the Study
Student dropout is a significant issue in higher education institutions, affecting both students’ academic success and the overall performance of universities. Bayero University, Kano, faces challenges related to student retention, with many s...
32. Comparative Study of AI-Based Versus Traditional Student Performance Prediction Models in Federal University, Wukari, Taraba State
Background of the study
Predicting student performance is a critical aspect of educational management, enabling institutions to provide targeted support and improve overall academic outcomes. Traditionally, student performance prediction has been based on historical data such as grades...
33. Evaluation of AI-Based University Email Spam Detection Models in Federal Polytechnic, Mubi, Adamawa State
Background of the Study
In today’s digital age, university email systems serve as a primary mode of communication between students, faculty, and administrative staff. However, with the increased use of email comes the challenge of spam, which can clutter inboxes, reduce productivi...
34. Exploring the Role of Deep Learning in Detecting Academic Fraud in University Portals: A Case Study of Federal University, Dutsin-Ma (Dutsin-Ma LGA, Katsina State)
Background of the Study
The increasing use of digital systems in educational institutions has revolutionized the way academic operations are conducted, from registration to the submission of assignments and examination results. However, the widespread use of university portals has also led...
35. Analysis of the Effectiveness of Neural Networks in Academic Fraud Detection: A Case Study of Federal University, Lokoja (Lokoja LGA, Kogi State)
Background of the Study
Academic fraud, which includes the use of false credentials, plagiarism, and misrepresentation of academic records, is a growing concern in higher education. This type of fraud not only compromises the integrity of academic institutions but also undermines the credi...
36. Comparative Study of Neural Networks and Decision Trees in Student Dropout Prediction: A Case Study of Kaduna State University (Kaduna North LGA, Kaduna State)
Background of the Study
Student dropout is a major issue facing many universities, including Kaduna State University in Kaduna North LGA, Kaduna State. The persistence of high dropout rates often reflects deeper issues, such as academic underperformance, financial difficulties, and lack of...
37. Development of a Deep Learning Model for Early Detection of Academic Struggles: A Case Study of University of Maiduguri (Maiduguri LGA, Borno State)
Background of the Study
The success of students in higher education is often linked to early intervention when academic struggles are detected. At the University of Maiduguri, located in Maiduguri LGA, Borno State, the university has a diverse student body with varying learning needs. Iden...
38. Exploring the Use of Deep Learning in Automated Lecture Video Summarization: A Case Study of University of Jos (Jos North LGA, Plateau State)
Background of the Study
With the increasing use of video-based learning materials, universities like the University of Jos are faced with the challenge of making vast amounts of video content accessible and easily digestible for students. Lecture videos, while valuable, can be lengthy and...
39. Development of a Deep Learning-Based System for Detecting Malpractice in Online Examinations: A Case Study of Federal University, Lokoja (Lokoja LGA, Kogi State)
Background of the Study
The advent of online examinations has transformed the way educational institutions assess students. However, the shift to digital platforms for assessments has raised concerns regarding academic malpractice, such as cheating, impersonation, and plagiarism. At Federa...
40. Evaluation of Machine Learning-Based Intrusion Detection Systems in University Networks: A Case Study of Taraba State University (Jalingo LGA, Taraba State)
Background of the Study
As universities increasingly rely on digital platforms and online learning systems, the security of their networks has become a critical concern. Taraba State University, located in Jalingo LGA, Taraba State, faces the growing challenge of protecting its network inf...
41. Enhancing the Accuracy of Optical Character Recognition (OCR) in Digitizing Old Academic Records: A Case Study of Ibrahim Badamasi Babangida University, Lapai (Lapai LGA, Niger State)
Background of the Study
Optical Character Recognition (OCR) technology has become a vital tool for digitizing printed materials and transforming them into editable text. Ibrahim Badamasi Babangida University, Lapai, located in Lapai LGA, Niger State, faces challenges in digitizing its old...
42. Design of an AI-Powered Plagiarism Detection System for University Research Papers: A Case Study of Benue State University, Makurdi (Makurdi LGA, Benue State)
Background of the Study
Plagiarism in academic research is a serious issue that undermines the integrity of academic institutions. Benue State University, Makurdi, located in Makurdi LGA, Benue State, has witnessed increasing concerns over plagiarism in student research papers and publicat...
43. An Investigation of Deep Learning Approaches for Early Detection of Student Dropout: A Case Study of Federal University, Gusau (Gusau LGA, Zamfara State)
Background of the Study
Student dropout rates are a significant concern for higher education institutions, especially in developing countries like Nigeria. Dropping out of university not only affects the students' future career prospects but also contributes to a loss of institutional...
44. Evaluation of Neural Network Models for Automated Lecture Timetabling: A Case Study of Federal University, Lokoja (Lokoja LGA, Kogi State)
Background of the Study
Automated lecture timetabling has long been a challenge for university administrators, who are tasked with ensuring efficient scheduling of classes, optimizing room usage, and managing faculty and student availability (Zhou et al., 2024). The comple...
45. Evaluation of Machine Learning Algorithms for Predicting University Graduation Rates: A Case Study of Kaduna State University (Kaduna North LGA, Kaduna State)
Background of the Study
Predicting student graduation rates is an essential task for universities, as it helps to identify at-risk students and implement early intervention strategies. Traditional methods of predicting graduation rates often rely on demographic factors and historical trend...
46. Comparative Study of Machine Learning Algorithms for Student Dropout Prediction: A Case Study of Federal University, Birnin Kebbi (Birnin Kebbi LGA, Kebbi State)
Background of the Study
Student dropout remains a significant challenge in higher education institutions worldwide, including Nigeria. Federal University, Birnin Kebbi, located in Birnin Kebbi LGA, Kebbi State, experiences a considerable number of student dropouts, which n...
47. Development of an Algorithm for Predicting Student Academic Performance: A Case Study of Federal University, Gusau (Gusau LGA, Zamfara State)
Background of the Study
In higher education institutions, predicting student academic performance is crucial for early interventions, personalized learning strategies, and resource allocation. Federal University, Gusau, located in Gusau LGA, Zamfara State, faces challenges...
48. Implementation of a Neural Network-Based Fraud Detection System for University Transactions: A Case Study of Bayero University, Kano (Gwale LGA, Kano State)
Background of the Study
Fraud in university transactions, including fee payments, scholarship disbursements, and financial aid processes, poses a significant risk to both students and university administration. Bayero University, Kano, like many academic institutions, hand...
49. Evaluation of Deep Learning Approaches for Automatic Student Feedback Analysis: A Case Study of Kaduna Polytechnic (Kaduna South LGA, Kaduna State)
Background of the Study
Student feedback plays a crucial role in evaluating the effectiveness of teaching methods, course content, and overall student satisfaction. Traditionally, feedback collection and analysis at Kaduna Polytechnic, like many educational institutions, r...
50. Comparative Study of Bayesian Networks and Neural Networks in Predicting Student Performance: A Case Study of University of Maiduguri (Maiduguri LGA, Borno State)
Background of the Study
Predicting student performance is a crucial aspect of academic planning and decision-making in universities. It allows institutions to identify students at risk of academic failure and provide timely interventions to improve their chances of success...
