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  <title>UDSspace Collection:</title>
  <link rel="alternate" href="http://hdl.handle.net/123456789/11" />
  <subtitle />
  <id>http://hdl.handle.net/123456789/11</id>
  <updated>2026-05-03T01:01:15Z</updated>
  <dc:date>2026-05-03T01:01:15Z</dc:date>
  <entry>
    <title>FORECASTING URINARY TRACT INFECTION (UTI) CASES IN NORTHERN  REGION USING MACHINE LEARNING APPROACHES</title>
    <link rel="alternate" href="http://hdl.handle.net/123456789/4621" />
    <author>
      <name>MOHAMMED FUSEINI DOKURGU, B. E.</name>
    </author>
    <id>http://hdl.handle.net/123456789/4621</id>
    <updated>2026-04-24T10:13:12Z</updated>
    <published>2025-01-01T00:00:00Z</published>
    <summary type="text">Title: FORECASTING URINARY TRACT INFECTION (UTI) CASES IN NORTHERN  REGION USING MACHINE LEARNING APPROACHES
Authors: MOHAMMED FUSEINI DOKURGU, B. E.
Abstract: Urinary Tract Infections (UTIs) continue to be a significant public health concern, with &#xD;
fluctuating incidence rates influenced by factors such as environmental conditions, healthcare &#xD;
accessibility, population diversity, and the rise in antimicrobial resistance. Accurate prediction &#xD;
of UTI trends is essential for health professionals and policymakers to implement timely &#xD;
interventions, optimize healthcare delivery, and develop effective disease prevention strategies. &#xD;
This study considers the modeling of UTI counts trend through the use of machine learning &#xD;
classification algorithms such as K-Nearest Neighbors (K-NN), Support Vector Classification &#xD;
(SVC), Decision Trees, and Random Forest Classification. These algorithms are best-suited &#xD;
for structured health data and can help uncover unique undiscovered patterns and relationships &#xD;
between multiple variables influencing UTIs.
Description: REQUIREMENTS FOR THE AWARD OF MASTER OF PHILOSOPHY  IN STATISTICS</summary>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>A TWO- PARAMETER GENERALISATION OF THE GAMMA FUNCTION AND ITS PROPERTIES</title>
    <link rel="alternate" href="http://hdl.handle.net/123456789/4599" />
    <author>
      <name>HASHIMU, M.</name>
    </author>
    <id>http://hdl.handle.net/123456789/4599</id>
    <updated>2026-04-22T14:47:40Z</updated>
    <published>2026-01-01T00:00:00Z</published>
    <summary type="text">Title: A TWO- PARAMETER GENERALISATION OF THE GAMMA FUNCTION AND ITS PROPERTIES
Authors: HASHIMU, M.
Abstract: This thesis presents a significant contribution to the field of special functions by&#xD;
introducing and thoroughly analyzing a novel two-parameter generalization of the&#xD;
Gamma function: the ( ,v)-generalizedGammafunction.Theresearchsuccess&#xD;
fully addressed a critical gap in the literature by unifying previously disparate&#xD;
generalizations, such as the-analogue and v-analogue Gamma functions. The&#xD;
thesis meticulously presented the ( , v)-generalizedGamma function through&#xD;
amodified integral representationandderivedseveral keyproperties, including&#xD;
recurrence relations and integral representations. A core strength of the work&#xD;
lies in its exploration of the properties and associated inequalities of the ( ,v)&#xD;
generalized Gamma function. Key analytical tools employed include H¨older’s&#xD;
inequality and Young’s inequality, alongwith techniques of integrationand&#xD;
di↵erentiation. The proofs provided are rigorous and clearly presented.
Description: REQUIREMENTS FOR THE AWARD OF MASTER OF PHILOSOPHY IN MATHEMATICS</summary>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>THE FLOW OF CASSON FLUIDS THROUGH POROUS MEDIA</title>
    <link rel="alternate" href="http://hdl.handle.net/123456789/4598" />
    <author>
      <name>ISSAH, A.</name>
    </author>
    <id>http://hdl.handle.net/123456789/4598</id>
    <updated>2026-04-22T14:44:28Z</updated>
    <published>2025-01-01T00:00:00Z</published>
    <summary type="text">Title: THE FLOW OF CASSON FLUIDS THROUGH POROUS MEDIA
Authors: ISSAH, A.
Abstract: This research presents an investigation of a two-dimensional steady flow of an incompressible &#xD;
Casson fluid. The flow is assumed to be in a porous medium with a chemical process and a &#xD;
magnetic field transversely acting on an exponentially stretched surface. The study is significant &#xD;
as the majority of the flow industry exhibits behaviors of a non-Newtonian in nature. The &#xD;
governing equations of the model were derived in the form of partial differential equations, and &#xD;
suitable similarity variables were employed to model the transformation. These produced a &#xD;
coupled form of nonlinear higher-order ordinary differential equations, which were then reduced &#xD;
to a system of first-order ordinary differential equations. The fourth-order Runge–Kutta–Fehlberg &#xD;
method, along with the shooting techniques, was used to obtain numerical solutions using the &#xD;
Maple Software package. Numerical results for the skin friction coefficient, the Nusselt number, &#xD;
and the Sherwood number, which are the most important quantities of interest in engineering &#xD;
practice and give insights into the flow dynamics, were computed and displayed in tables. &#xD;
Graphical results have also been displayed for the model to depict the effects of the controlling &#xD;
parameters on the flow. It was noticed that increases in the Casson parameter caused the skin&#xD;
friction coefficient to rise, which was accompanied by a decline in the speed of heat and mass &#xD;
transfers. This further resulted in a lower speed of flow along with an enhancement of the thermal &#xD;
boundary layer thickness. The study, therefore, concludes that the use of Casson fluids is crucial &#xD;
in controlling flow kinematics, which are important in achieving desired product characteristics
Description: REQUIREMENTS FOR THE AWARD OF MASTERS OF PHILOSOPHY DEGREE IN MATHEMATICS</summary>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>MULTI-OBJECTIVE OPTIMIZATION MODEL FOR FARM PLANNING IN  SOME SELECTED SMALL-SCALE FARMS IN NAVRONGO, GHANA</title>
    <link rel="alternate" href="http://hdl.handle.net/123456789/4527" />
    <author>
      <name>JOSHUA, M. B.</name>
    </author>
    <id>http://hdl.handle.net/123456789/4527</id>
    <updated>2025-11-24T11:39:53Z</updated>
    <published>2025-01-01T00:00:00Z</published>
    <summary type="text">Title: MULTI-OBJECTIVE OPTIMIZATION MODEL FOR FARM PLANNING IN  SOME SELECTED SMALL-SCALE FARMS IN NAVRONGO, GHANA
Authors: JOSHUA, M. B.
Abstract: The small-scale agricultural sector makes a substantial contribution to a country's &#xD;
economic growth. The goal of this research is to create a multi-objective optimization &#xD;
model for farm planning that maximize returns whilst minimizing labour cost for optimal &#xD;
land use.  To do this, three optimization models were developed using the weighted sum &#xD;
and epsilon-constraint method for multi-objective programming and solved by &#xD;
optimization techniques, using a management scientist software version 6.0. These three &#xD;
models were discussed in detailed and tested using data collected from some selected &#xD;
small-scale vegetables, cereals and legume farmers in some parts of Navrongo in the &#xD;
Kesena Nankana Municipality of the Upper East region of Ghana. Model 1 suggested an &#xD;
optimal land use and an increased in returns for all the test it was employed on. Also &#xD;
model 2 showed an increased in returns in all test cases while suggesting an optimal land &#xD;
use as well. Furthermore, model 3 showed a decreased in cost of employing labour whiles &#xD;
suggesting an optimal land usage. In all cases, the models were found to be robust for &#xD;
both the vegetables, cereal and legume farming through the sensitivity analysis done for &#xD;
the range of values for the coefficients of the decision variables and the constraints. In &#xD;
general, the developed models helped the small-scale farmers to maximize returns as well &#xD;
as minimizing the cost of labour whilst proposing optimal use of the farm land. &#xD;
Consequently, it is recommended that future works could consider adding other &#xD;
parameters like fertilizers application or type of fertilizer used, soil type, water &#xD;
requirements, etc. to see how the model will work.
Description: AWARD OF MASTER OF PHILOSOPHY  IN MATHEMATICS</summary>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </entry>
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