Welcome to Ashesi Institutional Repository

Welcome to the Ashesi Institutional Repository (AIR), an archive for preserving and sharing scholarly work at Ashesi University. Contributors to the repository ensure that their scholarly and creative work is preserved, indexed and showcased for a global audience. Students who produce strong research work have the privilege of getting their work published on AIR. Ashesi Community members can make submissions through warrenlibrary@ashesi.edu.gh.

The repository is organized in "Communities" that group publications by department and/or subject. You can browse the "Community" by Collection, Author, Title, or Issue Date. Alternatively, a search function enables easy access to information.

Communities

Select a community to browse its collections.

Recently Added

  • Improving customer satisfaction at Mahorgany Health Foods Ltd 
    Benson, Keshia (2020-05)
    Mahorgany Health Foods Ltd is an organic health food store and restaurant that specializes in freshly made vegan foods, with strengths such as cleanliness and good presentation, a convenient location, and considering ...
  • Crescendo: Developing a smartphone based hearing system 
    Tagboto, Zoe (2020)
    The ability to hear is an integral part of being a human being. It plays a vital role in various facets of the human experience, communication, listening to music and even being aware of one’s environment. Unfortunately, ...
  • Reflect: Teaching machine learning models to reconsider their biases 
    Osei, Maame Yaa (2020)
    Machine learning models have gained prevalence in the world we live in today. Currently, they are employed in different fields to automate the decision-making process of various institutions. With the increasing availability ...
  • Scalable automated machine learning 
    Dovonon, Gbetondji Jean-Sebastien (2020)
    Automated machine learning holds a lot of promise to revolutionize and democratize the field of artificial intelligence. Neural architecture search is one of the main components of AutoML and is usually very computationally ...
  • Using geospatial analytics to find prospective locations for water harvesting in Northern Ghana 
    Boye, Naa Lamle (2020-05)
    Access to potable water is a difficulty for about a quarter of the world’s population. The people living in the northern regions of Ghana, which have arid to semi-arid vegetation cover, form a significantly large percentage ...

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