IGI Global.

 Journal

 Artificial Intelligence In Agriculture: The Potential For Efficiency And Sustainability, With Ethical Considerations

 Peace Busola Falola, Abidemi Emmanuel Adeniyi, Olugbenga Ayomide Madamidola, Joseph Bamidele Awotunde, Oyenike Adunni Olukiran, Solomon Olalekan Akinola

 2024

AI and sustainable agriculture have emerged as two intersecting fields with the potential to revolutionize food production and address pressing environmental challenges. This chapter explores the integration of AI technologies into agricultural practices to enhance efficiency and productivity while considering the ethical implications associated with this transformation. The application of AI in sustainable agriculture offers numerous benefits, including improved crop yield, resource optimization, and enhanced pest and disease management. Nevertheless, there are also moral issues with the use of AI in agriculture. Data privacy, security, and equitable access to AI technologies are essential to prevent data exploitation and uphold an equitable agricultural environment. The ethical concerns brought up by the application of AI in agriculture must be addressed in order to create an equitable, inclusive, and ecologically responsible agricultural system 

  IEEE

 Conference

 Development Of An Android-based Reminder System For The Covid-19 Management

 Adigun Jinmisayo Awokola, Busola Peace Falola, Abidemi Emmanuel Adeniyi, Moses Kazeem Abiodun, Ayomide Oluwagbenga Madamidola, Joseph Bamidele Awotunde, Mukaila Olagunju, Oladayo Gbenga Atanda, Peter Omolehin

 2023

The COVID-19 pandemic that affected the entire world in the year 2020 sparked interest in research aimed at reducing the mortality rate of patients who contracted the virus. According to research, the majority of these fatalities are brought on by carelessness and negligence toward their health. Recent technological advancements have made it possible to overcome these kinds of issues by creating a reminder application that can operate on smartphones which is convenient for patients to carry around. In this study, a CO-MINDER system was developed for the management of covid-19. The CO-MINDER system comprises real-time monitoring and awareness, patients' ability to take necessary safeguards against minor symptoms, and better preventive treatment. Additionally, the reminder system assists medical personnel and the COVID-19 management team by reminding patients and users at large of the precautions they must take to avoid contracting the feared virus. The CO-MINDER also offers certain features such as the covid-19 helpline which is the co-minder application help page that provides helpline service to speak with a health specialist or to report an infection in the area in emergencies and also a safety test that offers a safety check by analyzing the user's current symptoms, travel history, and interactions with other covid-19 patients. Its sole purpose is to raise users' awareness of the covid-19 virus and guarantee that they are always in a safe environment and mindful of their health. The Flutter Framework, Dart programming language, and Firebase, which served as the back-end to handle a variety of user information requests, from authentication to data storage, were utilized in the design and development of the mobile application. 

 Springer Singapore

 Conference

 A Model For Network Virtualization With OpenFlow Protocol In Software-Defined Network

 Oluwashola David Adeniji, Madamidola O. Ayom?de, And Sunday Adeola Ajagbe

 2022

The implementation of network functions is based on the separately configured devices. This implementation has a significant effect on the operational expenses and capital expenses. This separation will also reduce and facilitate the deployment of new services with better overhead and faster time. The developed IPv6 experimental testbed was modeled using Mininet network simulation version 2.2.2170321. The Mininet software was installed and configured on Ubuntu Linux version 14.04.4–server-i386 simulator operating system environment. The flow-visor protocol was used to create the network slices in the topology while the floodlight protocol is used to create the controller, virtual switches and virtual hosts within the Mininet network emulator. The prime focus of this study is to develop a mechanism for network function virtualization in an IPV6-enabled SDN. The analysis of the percentage line rate for IPv4 was 95.27% as compared to the developed model of IPv6 with a line rate of 54.55% for each network slice. 

 Journal Of Next Generation Sequencing & Applications

 Journal

 A Computational Technique For Eliminating Low Complexity Regions In DNA Sequences

 OA Madamidola, TJ Adedeji, OL Osajiuba

 2021

Low complexity regions (LCRs) are short sequence repeats in DNA sequences. These repeats can cause high alignment scores with unrelated sequences in sequence databases and therefore need to be eliminated to enhance homology search. In this study, a computational approach was developed to eliminate low complexity regions in “real” DNA sequences, thereby classifying nucleotides into Significant Region (SR) and Non-Significant Region (NSR) which depicts the positive and negative classes respectively. Support Vector Machine was used for the classification task which employs training and testing datasets. The DNA sequences of Plasmodium falciparum were encoded using the positional information and density information techniques, which resulted into having two training and two testing datasets. The SVM model in this case was able to eliminate low complexity regions in “real” DNA sequences with a promising result. 

 International Journal Of Computer (IJC)

 Journal

 Metadata Extraction From References Of Different Styles

 Olugbenga A Madamidola, Olatunde, Ibikunle, Olawale T Adeboje, Promise I Ayansola

 2021

Metadata extraction is the process of describing extrinsic and intrinsic qualities of the resource such as document, image, video, including getting data from references. References form an essential part of electronic scholarly publications. A reference is the way of giving acknowledgment to individuals for their creative and intellectual works that one utilized in his or her research work. It can also be used to locate particular sources and combat plagiarism. A reference style dictates the information necessary for a reference and how the information is ordered. Accurate and automatic reference metadata generation provides scalability, interoperability and usability for digital libraries of both public and private institution and their collections. Accurate reference metadata extraction becomes an intriguing task to researchers who want to collect data of scientific publications; therefore, this research work proposes a metadata extraction from references of different styles with the use of regular expression. This work accurately extract metadata such as author, title of article, volume, year of publication and institution from references of different styles limiting it to six referencing style. 

 International Journal Of Computer (IJC)

 Journal

 Predictive System For Heart Disease Using A Machine Learning Trained Model

 Ozichi N Emuoyibofarhe, Segun Adebayo, Ayodeji Ibitoye, Madamidola O Ayomide, Aderibigbe Taye

 2019

Heart as one of the essential organ of the human body and with its related disease such as cardiovascular diseases accounts for the death of many in our society over the last decades, and also regarded as one of the most life-threatening diseases in the world. Hence we seek to predict a system for Heart disease using a supervised Machine Learning (ML) trained model in MATLAB2018 workflow in a real-time environment. To develop the system, 299 heart sounds from patients were obtained and labeled as normal and abnormal heart sound. Features were extracted and labeled as dataset; K Nearest Neighbour (KNN), Support Vector Machine (SVM) and Decision Tree (DT) algorithm were used as the training platform. From the classification analysis developed using the supervised ML trained model in MATLAB2018 in conjunction with system software features for the prediction of the heartbeat for both current and predefined of a heart condition algorithms used in training the dataset for the prediction when principle component analysis was enabled, the result shows that KNN algorithm has the highest and best accuracy of 94.4%, followed by the SVM with 84.4% and DT had 81.1%. while from the evaluation analysis, KNN on Receive Operation Characteristic Curve (ROC) with 90% variance and training time of 12.88 seconds on positive class of abnormal over false classes of normal heart sound has AUC as 0.94 and on ROC curve with PCA 90% variance and training time of 1.7119 seconds on positive class of normal over negative classes of abnormal heart sound has AUC as 0.89 efficiency 

 International Journal Of Trend In Scientific Research And Development - IJTSRD

 Journal

 Enhancement Of Cloud Resources Security Using Verification Code

 Madamidola Olugbenga, Abimbola Tolulope, Afolabi Gboyega

 2017

Cloud computing security or simply cloud security refers to a broad set of policies, technologies and controls deployed to protect data application and the associated infrastructure of cloud computing. The aim of this work was to address and minimize the problem of unauthorized access to information and applications on the cloud with the use of verification code, this project is targeted towards protecting user’s privacy and also preserving the integrity of their information and also the integrity of the Cloud Environment. The work was accomplished with the creation of user registration phase, user login and authentication phase and password change and verification code change phase, this was accomplished with the use of certain tools such as PHP, JQuery, MySQL Database, Ajax, HTML5 and CSS. A system using an integrated development environment was developed and security was installed in the system using htdocs and htaccess which helps to prevent against IP address filtering, URL address switching and removes the channel of SQL injection. 

 

 Conferenceproceeding

 Typhoid Patients Temperature Monitoring System

 O.N. Emuoyinbofarhe, Adebayo S, O.A. Madamidola

 2017

NILL 

 International Journal Of Trend In Scientific Research And Development,

 Journal

 Web–based Intelligent Inventory Management System

 Olugbenga Ayomide Madamidola, OA Daramola, KG Akintola

 2017

All around the world, inventory managers are faced with the complexities of simultaneously striving to retain constant manufacturing operation, render quality and adequate services to customer and keep goods at optimum level as well as having proper inventory management policy in place. As company grows a number of problem also arises first, a varieties of item are needed to be maintained in the inventory making it difficult to for managers to keep track, therefore a formal record keeping will have to evolve, besides that as quantities in inventory grows more space is required to do business. Due to local and global competition any company that must survive in the competitive world must take an advantage of effective management of its inventory seriously therefore the use of intelligent approach for effective and efficient inventory management system has become indispensable. This work developed an intelligent system implemented in a web based environment to integrate multiple stores also providing an effective coordination of all of the stores, intelligently determining the different reorder points of all the disparate stores in the systems and communicating the information back to the centralized store using Java Remote Method Invocation (RMI) with a secure socket layer (SSL), implemented using My Structured Query Language (MySQL), Database Management System, Hypertext Markup Language (HTML), JavaScript, Hypertext Preprocessor (PHP) and Xampp (Apache). The work optimized the performance of inventory management integrating multiple systems and providing an efficient coordination and monitoring moving away from single store into distributed system relating real time status of supplies at the different stores