Computing and Information Technology
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- ItemThe Impact and Future of Teletherapy in Mental Health Support(Research Output Journal of Biological and Applied Science, 2024-11-19) Nalongo Bina K.Teletherapy, a digital form of mental health support, has become an essential aspect of psychological care, driven by technological advancements and evolving societal needs. This paper examines the evolution, benefits, and challenges of teletherapy, emphasizing its accessibility, especially for underserved populations. It highlights innovations such as artificial intelligence (AI) and secure messaging and discusses ethical considerations like confidentiality and informed consent. Despite limitations, such as technical barriers and reduced non-verbal communication, teletherapy is poised to grow, offering flexible, accessible mental health services. The future of teletherapy will likely see further integration with emerging technologies, potentially reshaping the landscape of mental health care.
- ItemImproving family planning through use of a mobile system:(Kampala International University, 2024-06) Jenkins, Twinomugisha E.L.The concerning trend of low utilization of family planning methods among the youth has led to increased risks of infectious diseases like human immunodeficiency virus, unintended pregnancies, abortions, maternal morbidity, and mortality. Despite advancements in healthcare and information dissemination, challenges in family planning uptake among young adults persist. The main objective of this study is to improve family planning uptake among Ugandan youth through the development and implementation of a mobile system. Specific objectives include gathering information on the requirements for the use of family planning methods by youth, developing a mobile system for enhancing access to and utilization of family planning methods among youth in Uganda, deploying and integrating the developed mobile system into existing infrastructure, and validating and testing the functionality and effectiveness of the implemented mobile system. This study addresses these issues by enhancing family planning practices through a mobile system, using the Design Science Methodology to investigate demographic characteristics, awareness, usage patterns, access to information, and perceptions regarding family planning among young adults aged 20-35. The findings show that many in this age group are familiar with modern family planning methods such as oral contraceptive pills, intra uterine devices, and emergency contraception pills, with intentions to use or prior utilization. Reasons for non-usage include lack of sexual activity, waiting until marriage, or concerns about side effects. Notably, 58% of respondents (214 out of 369) have used a mobile system for family planning information, primarily accessing it through the internet, healthcare facilities, and social media. Participants expressed a strong interest in mobile systems for family planning, desiring features like period tracking, detailed method information, and expert advice. The study highlights the potential of mobile apps to increase family planning uptake by providing personalized reminders, facilitating service access, and offering comprehensive information. Key factors for successful implementation include education, awareness campaigns, and improved method accessibility. Ultimately, leveraging technology through mobile systems can empower young adults to make informed reproductive health decisions, improving well-being and reducing unplanned pregnancies.
- ItemA block chain-based framework for records management in land registry system in Uganda:(Kampala International University, 2024-04) Keneth, NiyibiziBlockchain is rapidly becoming established as the core technology of the Fourth Industrial Revolution. By combining blockchain to improve processes in existing industries, innovative of new services will emerge, but services not effectively applied by blockchain will also develop. This study investigated the factors to be considered when applying the characteristics of blockchain technology to land records management (Security, Economic and Decentration ). I designed a blockchain-based framework for land records management using the Delphi and analytic hierarchy process methods. The Delphi method is used to identify highly effective blockchain application factors by applying the evaluation framework to actual adoption in the public sector. By proposing a blockchain-based framework for blockchain application services, this study provides a systematic foundation for blockchain business review. Blockchains are expected to become more active along with the full-scale digital transformation of industries, and thus, we must examine the ways to broadly use blockchain as a base technology in a form applicable to the diverse industries and societies constituting the digital economy. Accordingly, this study presents an blockchain-based framework for promoting transparency and a protected digital information for land records management systems.
- ItemDevelopment of an optimized multimedia compression model for improved quality of service in virtual learning environments(Kampala International University, 2024-06) Joshua, B. AlitwezaIn the rapidly evolving landscape of education, one of the most transformative advancements has been the advent of e-learning. This mode of education encompasses a wide range of activities, from online courses and virtual classrooms to interactive simulations and multimedia presentations, demanding substantial bandwidth. However, in low-developed countries, e-learning often relies on wireless and mobile networks with limited bandwidth, low computing devices, and poor network connectivity, thereby hindering the effectiveness of learning in virtual environments. This research aims to address this challenge by exploring data compression algorithms through a comprehensive comparative analysis and developing an optimized data compression model suitable for low-bandwidth networks. The goal is to achieve maximum reduction of data in transit, facilitating quicker and timelier transmissions, thereby enhancing virtual learning environments and ensuring an effective and improved learning experience in institutions of learning. The research objectives included establishing requirements for designing a multimedia compression model for optimal bandwidth utilization, developing a multimedia compression model with optimum bandwidth utilization, and evaluating the model through comparative performance analysis to attain more optimized results. This study employed the Design Science methodology, complemented by simulation and experimentation. Additionally, the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology was employed, involving problem understanding, data understanding, modeling, evaluation, and implementation phases. These methodologies guided the research process and facilitated the systematic development and assessment of the compression model. The approach allowed for concrete measurements and comparisons, providing robust evidence of the model's effectiveness. DCT, Huffman, and Fractural compression algorithms were studied, analyzed, and compared for use in the model design. All algorithms were applied to multimedia data, with a focus on images and videos. The best optimal results were obtained after combining DCT and Huffman, resulting in a compression ratio of 0.14745 compared to 0.148601 for DCT alone and 1.00330 for Fractural. Optimizing DCT with Huffman yielded superior compression ratio (CR) and peak signal-to-noise ratio (PSNR), making it best suited for use in low-computing devices and poor network environments, thereby providing optimal performance for improved quality of service in virtual learning environments.
- ItemIntegration and analysis of unstructured data towards database optimization and decision making using deep learning techniques(Kampala International University, 2024-06) Maxima, AinomugishaThis thesis addresses the challenge of integrating unstructured data into a Relational Database Management System (RDBMS). The increasing volume and variety of unstructured data pose significant challenges for organizations seeking to leverage such data for decision-making. Traditional RDBMS are not well-equipped to handle unstructured data due to their structured nature, leading to inefficiencies in data storage and analysis. To overcome these challenges, a model is developed to automatically integrate unstructured data into a Relational Database Management System (RDBMS). The objectives include designing a classification model, implementing it for data integration and analysis, optimizing it for database optimization and decision support, and validating its effectiveness. The model efficiently extracts relevant information from categorized unstructured documents, facilitating structured database construction. The study rigorously followed a data science research methodology, encompassing data collection, model development, implementation, testing, evaluation, and validation. Results show significant performance improvement with the incorporation of LSTM layers, notably achieving an accuracy boost from 83.2% to 94.6% in receipt image processing. Similar improvements were observed across precision, recall, and F1-Score metrics. This accomplishment substantially addressed the hurdles associated with processing and analyzing unstructured data. In conclusion, the researcher strongly recommends the adoption of this model for the analysis of unstructured data. Future research could focus on further optimizing the model's performance and scalability, exploring additional deep learning techniques, and extending its applicability to other domains.