Engineering Commons^™

Developing An Energy Efficient Real-Time System, Aamir Aarif Khan

Masters Theses

"Increasing number of battery operated devices creates a need for energy-efficient real-time operating system for such devices. Designing a truly energy-efficient system is a multi-staged effort; this thesis consists of three main tasks that address different aspects of energy efficiency of a real-time system (RTS).

The first chapter introduces an energy-efficient algorithm that alternates processor frequency using DVFS to schedule tasks on cores. Speed profiles is calculated for every task that gives information about how long a task would run for and at what processor speed. We pair tasks with similar speed profiles to give us a resultant merged speed …

Precise Energy Efficient Scheduling Of Mixed-Criticality Tasks & Sustainable Mixed-Criticality Scheduling, Sai Sruti

Masters Theses

"In this thesis, the imprecise mixed-criticality model (IMC) is extended to precise scheduling of tasks, and integrated with the dynamic voltage and frequency scaling (DVFS) technique to enable energy minimization. The challenge in precise scheduling of MC systems is to simultaneously guarantee the timing correctness for all tasks, hi and lo, under both pessimistic and optimistic (less pessimistic) assumptions. To the best of knowledge this is the first work to address the integration of DVFS energy conserving techniques with precise scheduling of lo-tasks of the MC model.

In this thesis, the utilization based schedulability tests and sufficient conditions for such …

Epithelium Detection And Cervical Intraepithelial Neoplasia Classification In Digitized Histology Images, Sri Venkata Ravitej Addanki

Masters Theses

“Cervical cancer is one of the most deadly cancers faced by women. It is the second leading cause of cancer death in women aged 20 to 39 years. In order to detect cancer at early stages, pathologists analyze the epithelium region from the cervical histology images. These histology images have a pre-cervical cancer condition called cervical intraepithelial neoplasia (CIN) determined by pathologists. This study deals with automating the process of epithelium detection and epithelium CIN classification in digitized histology images. For epithelium detection, the objective is to detect epithelium regions in microscopy images from non-epithelium regions and background. convolutional neural …