ghanaopendata/ghanaian-research-english huggingface dataset:
Building a safe penetration testing environment for a computer security class at Ashesi UniversityTY CLASS AT ASHESI UNIVERSITY

Malicious cyberattacks are increasing, causing increasing damage and becoming a significant concern for companies and organizations. However, the shortage of cybersecurity professionals presents a considerable challenge. As a result, it is crucial to equip computing students with practical training in cybersecurity to address this issue. This project aims to provide an innovative solution by creating a distributable virtual lab environment with a set of labs that reinforce the concepts taught in the CS455 computer security course at Ashesi University. The labs will be designed to follow the methodology of a penetration tester, providing students with hands-on experience in exploiting various computer security flaws. The project's ultimate goal is to equip students with the understanding and practical skills in penetration testing, helping them develop their own personal and professional computer security awareness.

Source: Ashesi
Building a team-management and improved peer review platform for Ashesi University

PEGAR is a platform designed to streamline team interactions in Ashesi, improve the authenticity of peer reviews and strengthen the credibility of team dynamic grading. The system development methodology used was the SCRUM method as the team dynamic and user input was a continuous iterative process. Regarding this project's scope, PEGAR is a team management and peer review platform intended for the use and progressive exploration within the Ashesi University academic scene. It complements educational team projects by focusing on the team element of the project and not the submissions and direct project grading. The core functionalities include but are not limited to an object team selection algorithm, team task management and a peer review section that generates tailored reviews according to the user and user type. This project resulted in an 80% user acceptance rate for the platform and the revised peer review format. Considering that the primary users are both Ashesi students and teaching faculty, this high acceptance rate is indicative of future development and integration into the Ashesi curriculum.

Source: Ashesi
Building a web-based continuous sign language translation application for the deaf and hard-of-hearing (DHH)

Advancement in technology has brought about limitless possibilities. We have seen technology been applied to every aspect of our lives, from Medicine to the food we eat. This technology can also be applied to make life more comfortable for the Deaf and Hard-of Hearing (DHH) individuals. Assistive technologies have been built for individuals with various forms of disabilities. DHH individuals have seen assistive technologies in the form of mechanical hardware, and cybernetics that enables translation of sign language to verbal communication in various languages. However, these technologies are often expensive and difficult to afford. In this project, an automatic sign language translation model is implemented to help people without hearing impairment to communicate better with DHH individuals in order to better provide services for them.

Source: Ashesi
Building an e-commerce website for a traditional retail footwear shop (Es-Store)

The evolution of technology has impacted the world significantly; in government, industries, and sports. Business activities such as buying and selling have equally received their share of the technology boom. Despite the utility of technology in modern times, many traditional businesses have failed to incorporate technology in their daily activities. Es-Store is no exception. In the typical routine of Es-Store, people travel from the outskirt of Accra towards the central part to transact business with Es-Store. The uncertainties associated with the availability of the specific type of brands of footwear is a concern to potential customers, and often, customers are disappointed after traveling long distances without getting their desired footwear. Mr. Emmanuel Osei, the shop owner of Es-Store, spends huge part of their business capitals on stocking his shops with products customers sometimes do not need, leading to a slow market. Mr. Osei makes significant losses when the products in their heavily stocked shop begin to wear out. The benefits of online platforms in transacting businesses cannot be overemphasized considering the challenges above. People can obtain product information, availability, prices, and access delivery options. On the other hand, business owners can build a database of past and future customer details, preferences and trends in sales and shift supplies to respond to the shift in customer demands. In this project, I develop a web-based platform for Es-Store using technology tools such as HTML (Hypertext Markup Language), PHP (Hypertext Preprocessor), Javascript, Ajax, CSS (Cascading Style Sheet), and MySQL (Structured Query Language). I hope that Es-store and all other traditional retail shops will leverage this platform to enhance their operations and increase their profit margins.

Source: Ashesi
Building an Examination Scheduling System For Ashesi University

Every Ghanaian educational institution goes through the process of scheduling assessments at the end of the academic period. Unfortunately, this process can last anywhere from hours to weeks because of the many factors it is constrained by like the number of available classrooms, the duration of the examination period, the duration of individual papers and the flexibility of student schedules. Additionally, many of these factors are specific to the institution undergoing the scheduling and fluctuate across semesters. Consequently, institutions are not only prevented from sharing solutions but must create new solutions every academic period. To address these issues, this project leverages graph-coloring and breadth first search to design and implement a system that efficiently generates examination schedules that cater to Ashesi University

Source: Ashesi
Building An Inclusive Green Economy: Assessing The Perspectives Of Ghanaian Market Women.

The green economy is emerging as a central focus for economies worldwide, particularly in response to the growing risks associated with climate change. For developing nations like Ghana, a successful transition to a green economy must be inclusive of the informal sector, which accounts this sector, this study conducted interviews with 20 participants across Makola and Agbogbloshie participants largely associated the concepts of the green economy and sustainable development with basic sanitation practices, rather than broader development models. Contrary to the widespread view that the informal sector impedes sustainable development, the study identified notable green practices among market women, such as waste segregation, recycling, and waste monetization by informal waste collectors. And motivations for participating in the green economy included a desire to reduce pollution, improve health outcomes, and comply with government regulations. However, persistent barriers such as poor waste management by the Accra Metropolitan Assembly, limited access to sustainable packaging, economic hardships, and weak enforcement of environmental regulations hinder market women's full participation. Therefore, the study economy framework. Enhancing environmental education, investing in sustainable packaging solutions, and strengthening recycling initiatives are critical steps toward fostering greater inclusion of the informal sector. Ultimately, the paper advocates for an inclusive green economy transition in Ghana, one that leaves no one behind, particularly market women.

Source: Ashesi
Building the Thelpis Cryptocurrency Mobile Wallet on the Ethereum Blockchain.

What is the future of finance? This question is addressed through the focus on cryptocurrencies and decentralized finance. The purpose of this applied capstone project is to demonstrate the capabilities of cryptocurrencies and the potential to alleviate poverty in Africa through financial inclusion using cryptocurrencies. This project draws on interviews, observations, and conversations with users who are already in the crypto space and those who aspire to be. It also draws on personal experiences with existing wallets and the challenges faced in those spaces. The project scope is limited to the sending, receiving, and storing of cryptocurrencies and does not focus on buying and selling since implementing payment gateways in Web3 decentralized apps is complex and requires a lot of resources and funding. The result is a secure non-custodial cryptocurrency wallet named Thelpis that allows users to send, receive, and store cryptocurrencies. We conclude that the functional requirements for Thelpis are feasible within the scope of this applied capstone project, and we build the platform over the proposed project timeline.

Source: Ashesi
Can technology improve the development of club football in Ghana?

ootball is a global sport. It is the most-watched and most played sport in the world It is also capital-intensive. In recent times, with the influx of new technology, football has taken a giant leap globally into popularity and improved the standard of living of many of its stakeholders. It is also regarded as a lucrative business. This research investigates how technology can support or improve the development of club football in Ghana. This paper highlights the recent technological advancements in the world, how it can be applied to football, and more specifically how it can improve Ghana’s football especially at the club level. The objectives of this research are to highlight the state of football in Ghana, investigate how technology can improve club football in Ghana, and to recommend ways to increase the positive and decrease the negative impact(s) that technology has on club football in Ghana. The study involved research and intense analysis of the literature available on technology and how it has improved football, the reasons for technological advances in football, and how it can be applied to Ghana’s football. The absence of official websites of most local-based football clubs was also studied and it serves as the theoretical framework for this research. The research involved gathering data using quantitative methods. Data was collected from football stakeholders in Ghana, including footballers, administrators, coaches, football agents, and individuals in the media sector. This dissertation serves as the first major study on technology and how it can be used to improve club football in Ghana, though other studies have been conducted concerning football and national development, the rise of football agencies and its impact on football in Ghana and lastly improving the football industry in Ghana through franchising, licensing and merchandising. This study provides insights into the role of technology in football, the different ways it could be used to improve club football in Ghana, and which technological solution(s) could be proposed to effect some changes.

Source: Ashesi
Capstone management system

A Capstone is a project carried out by final year students usually before graduating or completing a course of study. In Ashesi University, a capstone project can either be a thesis, an applied, or an entrepreneurship project. The absence of a centralized system often results in a constant back and forth between students and faculty members. While the current method of operation works, it involves an appreciable amount of paperwork, which is an ineffective way to handle data. A possible solution presented in this paper is a capstone management system that holds the ability to streamline the entire capstone process between students and faculty members. An essential feature discussed is a feature that makes capstone-worthy projects available to all students. This is especially beneficial to students with little to no idea of projects to pursue.

Source: Ashesi
Car parking management system

Finding a vacant parking spot is important to individuals to save time which can be spent on other things. The increase in the number of cars in the country has led to a difficulty in locating vacant parking spots and the increase in importance of car parking lot and structure management. To make it easier for drivers to locate vacant parking spots within structures or parking lots, some of the most common technologies were explored and applied to come up with a solution to this growing problem. This project provides a solution to this problem using sensors for car detection and displaying the status of the parking slots to the driver.

Source: Ashesi
Career Buddy: A digital system to streamline career-related actions between students and the career centre

The fourth industrial revolution has had a significant impact on the global market, leading to increased competition among firms. Consequently, employers are seeking highly skilled employees who can provide substantial value to their organizations. In response, universities have established career services departments to prepare students for the job market. The primary objective of these departments is to assist students in discovering and defining their career paths and achieving their career goals. Ashesi University, like most institutions, has a career services department that requires digitalization to effectively streamline departmental activities and provide students with high-quality career guidance and services. This paper proposes a web application called Career Buddy to aid the Ashesi Career Services Department in enhancing its services. The proposed solution aims to facilitate departmental activities and ensure that students have easy access to career guidance and opportunities. The successful implementation of the proposed solution would enable the Ashesi Career Services Department to efficiently manage its resources and provide students with top-notch career guidance and services. By using Career Buddy, students would have access to a comprehensive suite of career resources and services, enabling them to make informed career decisions and achieve their career goals. Ultimately, this web application would be a valuable asset to the university's career services department and would contribute to the institution's efforts to prepare students for the job market.

Source: Ashesi
Cassava Plant Disease Detection on Low-End Mobile Devices Using Convolutional Neural Networks

Cassava is a staple crop used and consumed in predominantly Africa and other parts of the world. However, farmers lose significant portions of potential crop yield due to various cassava plant diseases. Although farmers use fertilisers and other preventive measures to mitigate these diseases, they are usually expensive and hence not very effective and predictive of future diseases. Convolutional Neural Networks(CNNs) provide an avenue to tackle this issue by providing a model that helps with predictive diagnosis of these diseases with near precise accuracy, even for low-income farmers. This project employed CNNs to build a classification model for cassava plant diseases with an accuracy of 89%. The model was then transformed to work with low-processor power devices and fed to the backend of an Android application. It demonstrated the efficacy of using Machine Learning techniques to develop applications for low-income farmers that can impact crop yield and agriculture in general.

Source: Ashesi
Cattle tracking with LoRa and machine learning

To curb the increase in livestock theft in Sub-saharan countries, this project looked at machine learning applications like cattle tracking on a farm. Received signal strength indicators from home available WiFis were utilized to fingerprint locations on the farm. Where WiFis were not available, ESP866 Node MCUs were used to deploy access points. These ESP8266 Node MCUs were also given SSIDs that could easily be used for classification using the SSIDs as labels in the program. Two classifiers were explored, the support vector machine (SVM) and the Decision Tree. A linear kernel with a very low gamma value of 0.001 was used for the SVM classifier. The decision tree classifier yielded an average accuracy of 0.89683659, while the support vector machine yielded an average accuracy of 0.915699. The SVM classifier emerged as a suitable classifier to use to achieve reliable accuracy in cattle tracking. Lora proved to be an essential tool in wireless communication of the prediction results from the pendant/transmitter designed to the receiver, hence enhancing mobility in tracking. Future works include incorporating distance calculation to make the tracking process more straightforward and efficient. Sensor nodes that will further provide the machine learning algorithm designed with unique data values will also be incorporated to compensate for longer farms that might need the deployment of more Node MCU access points. This is an effort to maintain low costs in tracking using the solution provided by this project. Therefore, the solution presented by this project proved to be feasible.

Source: Ashesi
Centralized patient health management system for hospitals and pharmacies in Ghana

This project aims to provide a centralized system where hospitals and pharmacies interact and share information to improve services and the health of patients. The application is developed in order to address the issue of hospitals and pharmacies not having updated records of patients. The system seeks to primarily help patients keep track of medications that were prescribed to them by the hospital and given to them by the pharmacy. The application will also allow the patient to check the times medications must be taken on the application. Moreover, hospitals and pharmacies, through a centralized, system can access patient information and details. Both hospital and pharmacy will have an updated version of a patient’s information whenever an update is made.

Source: Ashesi
Child welfare module for existing mHealth application, Yaresa

With Ghana striving to reach its Millennium Development Goals, the government has employed various tactics to improve healthcare delivery in Ghana. One of these strategies involves deploying Community Health Workers to rural areas to provide residents of such areas with good healthcare. As a result, various Community Health Centers have been set up in rural areas, and Community Health Workers have to attend to the healthcare needs of these communities. In recent past, mobile technology has been used to improve the efficiency of Community Health Workers in theses areas. As such, a group of Ashesi students and faculty developed an mHealth application to also help Community Health Workers in various ways. This project presents a Child Welfare Module to be integrated with the existing mHealth application, Yaresa.

Source: Ashesi
Circular economy in additive manufacturing: A study on the feasibility of building a 3d printer from repurposed electronic waste

In order to provide creative, cost-effective, and environmentally friendly 3D printing solutions, this study investigated the viability of building a 3D printer using salvaged electrical waste parts. The project required adapting and integrating abandoned electronic parts, including power supply, microcontrollers, and motion control systems. The control system used the Arduino Mega 2560 and Ramps 1.4 board, and the printer was programmed using Marlin firmware. A 20x20 aluminum v-slot profile was used to construct the mechanical framework. Testing of the printer's X and Y axes was conducted to evaluate the performance of the salvaged components. Upon completion of the testing procedure, the X and Y axes exhibited smooth, precise, and controlled movement, with functional endstops effectively preventing over-travel. This demonstrated that the project was feasible, as the successful operation of these axes substantiated the idea that constructing a 3D printer from repurposed parts is viable. This study adds to the increasing body of information on sustainable 3D printing methods and circular economy principles. The findings of this study have significance for the broader area of managing electronic waste, showing the possibilities for upcycling electronic waste and minimizing the harm e-waste causes to the environment.

Source: Ashesi
Classiﬁcation and quantiﬁcation of malaria parasites using convolutional neural networks

Malaria is currently one of the most deadly diseases in the world. While there are different treatment methods for the disease, the search for new drugs against malaria is still a very important area of research. One of the main challenges in manufacturing drugs against malaria is efﬁciently evaluating the performance of the drugs on the parasites since it requires, amongst others, precise measurements of the parasite growth-stages as well as their counts in blood smear images. The current gold-standard for making such detail diagnosis is manual microscopy which is tedious. This research showed that convolutional neural networks can be used to identify the different growth-cycle stages of Plasmodium parasites, even in situations where there is little data. Employing a variety of data augmentation techniques and transfer learning, a semantic segmentation model was built to discriminate between trophozoites, gametocytes and normal red blood cells with an accuracy of 85.86% in 353 Giemsa-stained thin blood smears. The results showed that it is possible to perform dense predictions on Giemsa-stained thin blood smears using convolutional neural networks.

Source: Ashesi
Classification and quantification of malaria parasites using convolutional neural networks.

Malaria is currently one of the most deadly diseases in the world. While there are different treatment methods for the disease, the search for new drugs against malaria is still a very important area of research. One of the main challenges in manufacturing drugs against malaria is efﬁciently evaluating the performance of the drugs on the parasites since it requires, amongst others, precise measurements of the parasite growth-stages as well as their counts in blood smear images. The current gold-standard for making such detail diagnosis is manual microscopy which is tedious. This research showed that convolutional neural networks can be used to identify the different growth-cycle stages of Plasmodium parasites, even in situations where there is little data. Employing a variety of data augmentation techniques and transfer learning, a semantic segmentation model was built to discriminate between trophozoites, gametocytes and normal red blood cells with an accuracy of 85.86% in 353 Giemsa-stained thin blood smears. The results showed that it is possible to perform densepredictionsonGiemsa-stained thin blood smears using convolutional neural networks.

Source: Ashesi