Browsing by Author "Omwenga, Vincent"

Now showing 1 - 3 of 3
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    Glucose-Insulin Dynamics: a grey-box analogy
    (Strathmore University, 2019-08) Omwenga, Vincent; Madhumati, Vaishnav; Vinay, Chauhan; Krishnaswamy, Patnam; Srikanta, Sathyanarayan; Navakant, Bhat
    Regulating plasma glucose levels for both type I and type Il diabetic patients is a challenging task. Understanding the effects of meals taken, the physical exercises and stress levels will contribute significantly to the overall management of the plasma glucose levels. This paper provides an extension of the Bergman Minimal model to represent twelve-compartmental models associated with meals taken, physical exercises and stress levels interactions within a semi-closed loop system using Stochastic Differential Equations (SDE). The mathematical modelling is constructed following the Grey-box model analogy as applied on an identifiable patient. Obtained results from the study demonstrates the predictive capability of the model to be good and its sensitivity is enhanced with increased dataset.
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    Implementing enterprise systems for management: a case of Kenyan Universities
    Nyandiere Clement M,; Kamuzora, Faustin; Lukandu, Ismail Ateya; Omwenga, Vincent
    Kenyan universities, as other business entities, are implementing various information systems to facilitate their operations. The systems include enterprise systems which are implemented to enhance institutional management given their emphasis on standardisation, streamlining, and integration of business operations. In this study, the authors have established that Kenyan universities have mainly implemented systems for finance and accounting, student admissions, examinations management, and library services. The authors have also established that there are no significant differences in information systems needs among Kenyan universities, but there are significant differences in strengths and weaknesses among the private and public universities in the capabilities of systems they have implemented. The authors have further established that despite fears especially on delays in projects implementation and system costs, Kenyan universities are in a position to implement enterprise systems to facilitate their operations. However, the universities need to allocate more funds to systems implementation if they have to successfully implement enterprise systems which generally require more resources than ordinary software applications.
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    Statistical techniques for characterizing cloud workloads: a survey
    (Strathmore University, 2017) Kenga, Derdus; Omwenga, Vincent; Ogao, Patrick
    Cloud computing infrastructure is becoming indispensable in modern IT. Understanding the behavior and resource demands of cloud application workloads is key in data center capacity planning, cloud infrastructure testing, performance tuning and cloud computing research. Additionally, cloud providers want to ensure Quality of Service (QoS), reduce Service Level Agreement (SLA) violations and minimize energy consumption. To achieve this, cloud workload analysis is critical. However, scanty information is known about the characteristics of these workloads because cloud providers are not willing to share such information for confidentiality and business reasons. Besides, there is lack of documented techniques for workload characterization. To alleviate this situation, in this paper we perform the first meticulous study on statistical techniques that can be used to characterize cloud workloads. Through this review, we identify a statistical technique and its role in understanding cloud workload characteristics and its weakness. Throughout the review, we point out relevant examples where and how (particularly workload prediction), such techniques have been applied by pointing out to Google Cluster Trace (GCT) and Bitbrain’s Grid Workload Archive Trace (GWA-T-12).