ghanaopendata/ghanaian-research-english huggingface dataset:
Autograding and detecting plagiarism in student programming assignments

In computer science, practical assignments ensure that students put the theory they learn in class into practice by writing computer programs to solve problems. Practical assignments also play a critical role in assessing students’ understanding of course materials. For course facilitators, grading programming assignments is a time-consuming task. The course facilitators must run each student’s submission. Moreover, some students copy the code from their friends and change the lexicon and structure. This makes it nearly impossible for the course facilitators to detect plagiarism. A possible solution to these problems is a system that allows course facilitators to write tests that apply automatically to all students’ submissions and consequently allocate grades based on test results. To curb the plagiarism issue, the system should have a component that calculates the peer plagiarism index and flags students’ submissions that may have plagiarism issues. This applied project is an attempt to develop, test and evaluate such a system. While designing the system, it became apparent that running students’ submission and instructors’ tests on the server would pose a security threat to the server. After evaluating possible workaround for the issue, we decided to run the submissions and tests on a docker sandbox within a virtual machine. The plagiarism index is calculated by quantifying the lexical and structural similarities. To integrate the two components, we developed an API. To test and demonstrate the workings of the system, we developed a frontend client to consume the critical endpoints of the API. This project is proof of concept that the solution for the problem can be developed and successfully deployed.

Source: Ashesi
Automated collection and visualization of road quality data to aid driver navigation

In nations worldwide, roads play a major part in the livelihood of individuals. They aid in the transport of both people and goods from one location to another. In developed countries, most roads are tarred making travel easier and quicker. In developing countries, this is not the case. Quite an amount of road work and development is still needed in these regions. These roads normally have different grades of road quality and have different effects on the individuals that use them. With the introduction of mapping applications such as Google Maps, individuals can place information about various locations on a mapping interface. In this project, an application is built to allow individuals collect data about the quality of roads around them. This data will be viewed on a map interface. With such data, drivers would be able to choose they type of roads they would want use.

Source: Ashesi
Automated course scheduler for Ashesi University College

Ashesi University College is faced with the challenge of effectively scheduling courses at the beginning of the semester so that there are no class clashes for both lecturers and students. In an attempt to solve the Course Timetabling Problem at Ashesi University College, five algorithms: Genetic Algorithm, Constraint Programing, Particle Swarm Optimization, Simulated Annealing and Tabu Search algorithm, which are known for their use in solving University Course Timetabling problems have been studied and based on their ease of implementation, their robustness in arriving at feasible solutions, their computational speed and whether an optimal solution is always guaranteed, Particle Swarm Optimization algorithm is chosen to implement a solution to the Ashesi University Course Timetabling problem. This project is focused on eliminating course conflicts and creating an optimal table based on teachers‟ preferences for certain timeslots to teach during the week. The paper outlines the assumptions and steps including explanations on Particle Swarm Optimization used in constructing the timetable base on teachers‟ preferences. Test conducted on the project proved that the use of Particle Swarm Optimization to solve the Ashesi Course Timetabling problems is in the right direction.Finally, the paper proposes a focus on other areas of the course timetabling problem at Ashesi University College, using the same Particle swarm optimization procedures described in the paper to help provide a complete solution to the timetabling problem of the school.

Source: Ashesi
Automated Detection of Faults in Overhead Transmission Lines

Electricity is a significant aspect of our daily lives. social activities and industries heavily depend on electricity to function. Transmission line protection is an essential issue in power system engineering because 85-87% of power system faults occur in transmission lines. Proper detection of various faults which do occur on transmission lines is very important. This project presents an impedance technique to detect and classify the different shunt faults on transmission lines for quick and reliable protection schemes. Discrimination among different types of faults on the transmission lines is achieved by applying evolutionary programming tools. MATLAB software is used to simulate operating and fault conditions on high voltage transmission line, namely single phase to ground fault, line to line fault, double line to ground and three-phase short circuit fault. These faults are isolated from the system using a designed impedance relay and the distance of the fault is calculated and provided. This research project successfully designed a functional and cost effective fault detection prototype and its simulation was also successful.

Source: Ashesi
Automated IoT-aided hydroponics systsm

Hydroponics is the sustainable and efficient method of growing plants without soil whereby nutrient-rich solution is used instead, which has proven to produce higher yield and make more efficient use of water and space as compared to traditional farming. The integration of Internet of Things to Hydroponics has the potential to revolutionize agriculture in Ghana by providing a more efficient way to grow crops in remote areas. Although IoT-aided Hydroponic systems are beneficial, they come with challenges such as the need for constant water and energy power supply, difficulty in scalability and overall efficiency. This paper is aimed at developing an automated IoT-aided hydroponics system which addresses these challenges. The development and implementation of this system ensured the use of scalable and energy efficient technologies which would create a full efficient hydroponic system capable of remote monitoring and control.

Source: Ashesi
Automated medication/drug dispensing machine

The Automated Medication Dispensing Machine (AMDM) is a solution to the challenge of obtaining medication in areas where access to medication is limited, especially during odd hours. The machine operates like a vending machine, offering only Over-the-Counter (OTC) drugs 24/7, allowing users to conveniently purchase medication without human intervention. The purpose of this project is to provide an in-depth analysis of the AMDM, including its design and implementation, potential benefits and limitations, and impact on the healthcare industry and society. Enhancements to the AMDM include providing access to drug dosages through QR code scanning, inventory count, and pill dispensation to prevent overdose. This project offers a novel solution to the challenge of accessing medication, especially in areas with limited pharmacy access.

Source: Ashesi
Automated plastic waste segregation system

The goal of this capstone project is to create a automated plastic waste segregator that uses artificial intelligence (AI) to distinguish plastic garbage from other types of trash. Inefficient waste segregation is a problem that has led to pollution and environmental damage in many metropolitan areas. This research offers an innovative approach to trash segregation by employing AI-powered sensors to identify and separate plastic waste from general particles, unlike standard waste segregation systems that rely on manual sorting and recycling.

Source: Ashesi
Automated Timetabling In Higher Education: The Case Of Ashesi University

Educational timetabling is a complex problem, often described as an NP-complete task, involving the allocation of courses to time slots while adhering to various constraints. This thesis explores the application of modern optimization algorithms; Greedy Algorithm, Genetic Algorithm, and Simulated Annealing, to improve the timetabling process at Ashesi University. The study evaluates these algorithms in terms of runtime, violation of constraints (such as room capacity, faculty availability, and student conflicts), and resource utilization. Simulated Annealing emerged as the most balanced approach, offering a compromise between computational efficiency and quality of results. The findings suggest that automated timetabling systems can significantly reduce the administrative burden, improve resource utilization, and optimize timetabling in higher education institutions, particularly in the context of African universities. This research also lays the groundwork for developing a modular, open-source timetabling framework applicable to other academic institutions in the developing world.

Source: Ashesi
Automatic car number plate recognition to improve driving safety at traffic lights in Ghana

Technology to identify the number plates of vehicles that jump traffic lights exists in many advanced countries. However, for developing economies, financial and technological constraints have been the major factor preventing them from acquiring technologies. For this project, a low-cost Automatic Number Plate Recognition (ANPR) system has been developed. With this system, drivers who jump traffic lights can easily be identified and fined with little to no manual work from the police or legal authorities. The system also provides a user-friendly administrator interface to relevant authorities giving them permission to access and monitor records of all incidences captured on the ANPR system. This documents also contains results from testing the system as well as future works.

Source: Ashesi
Automatic classification of news stories – A machine learning approach

Humans are good at classifying things because our brains are adept at understanding contextual nuances. Machines, however, need to be fed the right features to achieve reasonably good levels of classification. Classifying text manually is a time-consuming and expensive process especially in the information age where a combination of the success of cloud computing, big data and the resurgent trend of the internet of things as well as unprecedented population growth have led to an explosion in the amount of data that we have to deal with – approximately 2.5 quintillion bytes every 24 hours (Walker, 2015). This Thesis explores the efficiency of two well-known machine learning classification algorithms; Naïve Bayes and Support Vector Machines in classifying news stories - an important subset of the global repositories of information. The findings in this study report that using machine learning to classify news stories is not easy but is feasible and if done properly can yield accuracy rates of at least 70%. These results translate into significant time savings that cannot be achieved by manual classification and are a precursor to other machine learning techniques such as recommendation, clustering and sentiment analysis.

Source: Ashesi
Automatic license plate recognition for non commercial vehicles in Ghana to improve road safety

Vehicles are ingenuous contraptions that have significantly revolutionized how human beings move from one place to another. However, inasmuch as they have liberated man, they have also become a major cause of fatalities and injuries. Technologies such as Automatic License Plate Recognition (ALPR) have been utilized in advanced countries to make roads safer to use. However, they are not utilized in lesser developed countries such as Ghana to improve road safety. In this project, an ALPR system is implemented for the Ghanaian context. It is intended to recognize and detect number plates of non-commercial vehicles that jump the red light by using a mobile phone camera and Optical Character Recognition (OCR).

Source: Ashesi
Automatic license plate recognition system for traffic monitoring

In Ghana, road accidents are primarily caused by road traffic law violations. Technologies, such as Automatic License Plate Recognition(ALPR), have been implemented to help reduce road accidents in other countries. However, they are not utilized in less developed countries like Ghana. In this project, an ALPR is implemented using two approaches: computer vision algorithms and YOLOv4. The computer vision approach obtained a 71% ALPR accuracy at 3 meters distance and 60 degrees inclination between the license plate and camera at 7 pm night time. The YOLOv4 obtained a 99% ALPR accuracy at 6 meters distance and 60 degrees inclination between the license plate at 7 pm night time.The results of testing show that the YOLOv4 approach was more accurate than the one with computer vision.

Source: Ashesi
Automatic Retractable Raincoat for Drying Clothes

With the unpredictability and unforeseen weather changes, it is hard for people who are on busy schedules and want to include a washing day to decide which day is best to wash for their clothes to dry properly uninterrupted. This project used an ESP 32 microcontroller and Arduino IDE to install all the required programs that gave instructions for the effective functionality of the automated retractable raincoat system for drying clothes. When a raindrop (water) was sensed by the water sensor, the linear motion of the bearings was automatically initiated for the clothes to be covered by the raincoat and once the rain stopped, an opposite movement was automatically initiated to uncover the clothes for them to continue drying. The whole system required two DC motors to convert electrical energy into mechanical energy that initiated the linear movement. Water sensor and Ultra-sonic sensor with the Dual H-Bridge L298N motor driver technology was used. It was observed that the system was effective with the forward linear movement taking approximately the same time as the backward linear movement.

Source: Ashesi
Automating Chalkboard support processes using a chatbot

This project seeks to apply natural language processing techniques to automate the support processes of Chalkboard Education, a startup in Ghana. The company has many users but currently has only two operations personnel responsible for responding to customer queries. Their support processes can be made easier with the use of a chatbot. The project references work from early chatbots like ELIZA and Cleverbot as well as more recent ones like MOOCBuddy and SuperAgent. The chatbot is built on RASA Natural Language Interpreter and uses third party APIs like Twilio and Database connections to mirror human support processes. Upon implementation, the chatbot is suitably able to perform the repetitive human tasks the operations personnel were carrying out, successfully and in shorter time. In the event that the chatbot cannot handle a query, the problem is forwarded to the aforementioned operations personnel. Upon evaluation, it was discovered that the chatbot has could improve its accuracy and effectiveness with techniques such as adding more training data and using different language models for embeddings. In the future, the chatbot can be implemented via a USSD application to enable Chalkboard capitalize on the prevalence of USSD application in Africa.

Source: Ashesi
Automating The Verification Process Of Zeepay Wallets (Zeeverify)

The manual verification process for registering Zeepay wallets via the ZeeAgent platform presents significant inefficiencies, including time delays and a high potential for human error. This applied project aims to automate this verification system, which currently relies on manual checks of ID cards and registration forms by human agents to approve new wallets. The central research question driving this projectis: How can the wallet verification process on the ZeeAgent platform be automated to improve efficiency and accuracy? The proposed solution leverages Optical Character Recognition (OCR) to extract data from ID cards and facial recognition technologyto match user-submitted photos with their ID documents. This automated system will reduce the reliance on human intervention, significantly decreasing processing time and enhancing accuracy. By streamlining the verification process, this project seeks to improve the customer onboarding experience, maintain security standards, and provide a scalable solution as Zeepay

Source: Ashesi
Autonomous self-driving vehicle: Perception, supervised learning, control.

Road accidents are estimated to be the ninth leading cause of death across all age groups globally. 1.25 million people die annually from road accidents and Africa has the highest rate of road fatalities (WHO, 2015). Self-driving technology has the potential of saving over a million lives lost to preventable road accidents worldwide. Africa accounts for the majority of road fatalities and as such would benefit immensely from this technology. However, financial constraints prevent viable experimentation and research into self-driving technology in Africa. In this applied project I designed and implemented RollE to bridge this gap. RollE is an affordable modular autonomous vehicle development platform. It is capable of road data collection and autonomous driving using a convolutional neural network. This system is aimed at providing students and researchers with an affordable autonomous vehicle to develop self-driving car technology.

Source: Ashesi
Autonomous self-driving vehicle: Perception, supervised learning, control.

Road accidents are estimated to be the ninth leading cause of death across all age groups globally. 1.25 million people die annually from road accidents, and Africa has the highest rate of road fatalities (WHO, 2015). Self-driving technology has the potential of saving over a million lives lost to preventable road accidents worldwide. Africa accounts for the majority of road fatalities and as such would benefit immensely from this technology. However, financial constraints prevent viable experimentation and research into self-driving technology in Africa. In this applied project I designed and implemented RollE to bridge this gap. RollE is an affordable modular autonomous vehicle development platform. It is capable of road data collection and autonomous driving using a convolutional neural network. This system is aimed at providing students and researchers with an affordable autonomous vehicle to develop self-driving car technology.

Source: Ashesi
Axis Mobile: A mobile application to support the processes of Axis Human Capital Limited, a human resource management company in Ghana

The increasing accessibility to internet resources has made several companies adopt the use of such resources in their processes. Axis Human Capital Limited, a human capital management and development company in Ghana, needed a mobile application that mitigates the problems that their clients face when using their website and has other important features that successfully support their processes and improve them where necessary. This paper proposes a hybrid mobile application, Axis Mobile, and a web application, Axis Notification Center, that meet Axis’ needs. The proposed solutions address the limitations of Axis’s website and provides important features that complement it. Axis Mobile and Axis Notification Center make Axis’ clients much happier and Axis’ processes much faster.

Source: Ashesi
Badges, Points, and Leaderboards: Exploring the Potential Impact of Gamification on Adults’ Reading Habits

The decline in reading habits among adults, often attributed to the rise of digital media, has been a growing concern in recent years. Although existing digital reading platforms offer various features, they often fail to address the motivational barriers faced by infrequent readers. Inspired by the success of other learning platforms like Duolingo, this study explored the potential of gamification to revive adults’ reading habits. In line with the Octalysis framework, a gamified digital reading platform incorporating points, badges, leaderboards, streaks, and was developed and tested for three weeks with 19 participants. Qualitative analysis of pre-and post-study questionnaires and platform usage data revealed that gamification could positively influence the reading frequency, duration, and enjoyment, particularly for those reading for pleasure. The platform also helped address common barriers to reading, such as lack of time, interest, and focus. Additionally, some participants reported decreased social media usage during the study. These findings highlight the potential of gamified reading platforms to encourage and sustain reading habits in young adults, offering a viable approach to addressing declining literacy among the demographic in the digital age.

Source: Ashesi
Beauty With Integrity: Consumer Perceptions of Social Media Marketing Ethics in Ghana’s Cosmetics Industry

This thesis investigates consumer perceptions of marketing ethics in Ghana"intention-behaviour gap", showing that while ethical awareness is present, factors such as economic constraints, product necessity, and peer recommendations often override ethical concerns during purchasing decisions. Generational and cultural influences further shape consumer attitudes, with younger consumers demonstrating more relativistic ethical reasoning compared to older cohorts. Peer validation, particularly through social media platforms, and influencer authenticity emerged as critical determinants of brand trust. The findings underscore the need for more robust regulatory frameworks, transparent marketing practices, and consumer education in Ghana

Source: Ashesi
Billing and location tracking app for transportation

Most companies in Ghana provide their staff with buses to make transportation more accessible, but this transportation medium is not tracked, making its operations difficult for staff. Means of payment become a problem when the staff has a higher denomination. This project aims to solve these problems by adapting the tracking technology based on GPS and the cashless payment system based on RFID. Using these technologies, this project will make tracking and payment on these company buses easy. This project goes beyond tracking to estimating the arrival time of the bus and beyond RFID payment to tracking user pickup and endpoints. This system is flexible and allows users to make payments with cash and make payments by scanning a QR code.

Source: Ashesi
Billing and location tracking web and mobile system for the Ashesi school bus

Staff and faculty at Ashesi University face the problem of tracking the location of the school bus, know available seats on the bus and made COVID-19 free cashless payments. Research has show that, an individual waiting for a public transport without knowing its location increases one's fatigue. The staff and faculty are likely to miss the bus since they cannot track its location. They may end up being late to school after taking an alternative transport. With the development of a web and mobile application, staff and faculty will be able to track the location of the bus and know the number of available seats. They can also take trips and secure financial transactions free of health risks with this proposed solution. The web application will be for accountability, settling accounts and tracking.

Source: Ashesi