This sub-community contains all Masters thesis of the five streams offered at AUST http://repository.aust.edu.ng/xmlui/handle/123456789/352 2026-08-26T00:59:19Z 2026-08-26T00:59:19Z Saddiq, Faisal http://repository.aust.edu.ng/xmlui/handle/123456789/5208 2026-08-19T21:00:45Z 2026-03-12T00:00:00Z

Gender-Based Violence Data Governance improving reporting mechanisms for effective policy interventions in Kaduna Public Secondary Schools Saddiq, Faisal This study investigates Gender-Based Violence (GBV) data governance and its implications for improving reporting mechanisms to support effective policy interventions in Kaduna public secondary schools. GBV remains a pervasive challenge in Nigeria, with Kaduna State recording a sharp rise in reported cases, highlighting the urgency of addressing structural and systemic barriers to reporting and response. The research adopts a quantitative paradigm with a descriptive correlational design to examine the effectiveness of reporting mechanisms, data governance structures, and policy frameworks in capturing, managing, and utilizing GBV-related data for evidence-based interventions. A sample of 400 respondents comprising students, teachers, administrators, and policymakers was drawn from urban and rural schools, with 390 valid responses retrieved. Data were collected using structured questionnaires and analyzed using descriptive and inferential statistics, complemented by thematic analysis of open-ended responses. Findings reveal that while counsellor/teacher reporting remains the most accessible mechanism, underreporting persists due to fear of stigma, lack of confidentiality, and weak institutional responses. The study also identifies poor data governance practices characterized by inadequate trained personnel, fragmented reporting systems, and limited use of collected data in shaping policies. Furthermore, analysis shows that existing policies are often poorly enforced, undermining their potential to protect students and address GBV effectively. However, respondents highlighted strategies such as training and awareness creation, adoption of digital reporting platforms, improved confidentiality measures, and regular policy reviews as essential to strengthening GBV data governance. The study concludes that effective data governance frameworks, coupled with survivor-cantered reporting mechanisms, are crucial for ensuring accurate, secure, and timely GBV data that can inform robust policy responses. It recommends a comprehensive approach integrating digital innovations, institutional reforms, and stakeholder collaboration to foster safer learning environments and enhance the accountability of schools and government institutions in addressing GBV.

2026-03-12T00:00:00Z Maduakor, Francis http://repository.aust.edu.ng/xmlui/handle/123456789/5206 2026-05-26T21:00:42Z 2019-06-20T00:00:00Z

Fast and Accurate Feature-based Region Identification Maduakor, Francis There have been several improvements in object detection and semantic segmentation results in recent years. Baseline systems that drive these advances are Fast/Faster R-CNN, Fully Convolutional Network and recently Mask R-CNN and its variant that has a weight transfer function. Mask R-CNN is the state-of-art. This research extends the application of the state-of-art in object detection and semantic segmentation in drone-based datasets. Existing drone datasets was used to learn semantic segmentation on drone images using Mask R-CNN. This work is the result of my own activity. I have neither given nor received unauthorized assistance on this work.

2019-06-20T00:00:00Z Adam, Saleh Adam http://repository.aust.edu.ng/xmlui/handle/123456789/5205 2026-05-26T21:00:56Z 2024-02-18T00:00:00Z

Multiple String-Matching Using Wavelet Matrix and Burrows-Wheeler Transform (Bwt) Adam, Saleh Adam The problem of multiple string matching is fundamental in computer science, with applications in bioinformatics, text mining, and information retrieval. Traditional methods struggle with large datasets due to high computational and memory requirements. This research proposes a novel algorithm that combines the Burrows-Wheeler Transform (BWT) for text compression and the Wavelet Matrix (WM) for efficient pattern search. The proposed method achieves faster search times, lower memory usage, and effective compression, particularly for repetitive datasets like DNA sequences. Experimental results demonstrate that the method performs better compared to existing algorithms. This work contributes to the advancement of efficient and scalable multiple string-matching techniques, with potential applications in large-scale text processing and bioinformatics. Keywords: Algorithms, Text Compression, Wavelet Matrix, Burrows-Wheeler transform, Multiple String matching

2024-02-18T00:00:00Z Abiola, Jimoh Ridwan http://repository.aust.edu.ng/xmlui/handle/123456789/5203 2026-05-25T21:01:28Z 2026-01-15T00:00:00Z

Technology Policy and Sustainable Start-Up Ecosystems: A Comparative Study of Nigeria and India Abiola, Jimoh Ridwan This study compares technology policies and sustainable start-up ecosystems in Nigeria and India. It examines legal frameworks, government initiatives, funding mechanisms, and implementation challenges in both countries. Nigeria relies mainly on the Nigeria Start-up Act 2022, the National Digital Economy Policy and Strategy, and the Companies and Allied Matters Act. India uses the Start-up India Action Plan 2016, the National Digital Communication Policy, and the Companies Act 2013, supported by a more mature and integrated system. The research uses a mixed-method approach: doctrinal legal analysis of 52 policy documents and a descriptive survey of 118 stakeholders from both countries. Findings show that India has a stronger, more sustainable ecosystem with better coordination, larger funding flows, and more supportive regulations. Nigeria faces major barriers including poor infrastructure, limited access to capital, bureaucratic delays, and low awareness of the Start-up Act. Stakeholders strongly support public-private partnerships, improved venture capital access, targeted policy reforms, and collaboration with research institutions to build a more sustainable ecosystem in Nigeria. Lessons from India highlight the value of long-term policy consistency, strong digital infrastructure, and effective funding structures. The study concludes that while Nigeria has progressive laws, faster implementation, better coordination, and infrastructure improvements are essential for a thriving and sustainable start-up ecosystem. Recommendations focus on central coordination, state-level adoption of the Start-up Act, expanded funding vehicles, and stronger public-private collaboration.

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