Umair Ali Khan

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Dynamic power management (DPM) refers to strategies which selectively change the operational states of a device during runtime to reduce the power consumption based on the past usage pattern, the current workload, and the given performance constraint. The power management problem becomes more challenging when the workload exhibits nonstationary behavior(More)
Dynamic Power Management (DPM) refers to a set of strategies that achieves efficient power consumption by selectively turning off (or reducing the performance of) a system components when they are idle or are serving light workloads. This paper presents a Reinforcement Learning (RL) based DPM technique for a portable, multi-camera traffic monitoring system.(More)
A simulator is developed for training and optimizing the templates for cellular neural networks for obstacle detection. The simulator uses the Genetic Algorithm (GA) for training the cellular neural network. The traditional method of genetic algorithm involves creating an initial population of random solutions (chromosomes) in binary format, the so called(More)
The biggest challenges faced by intelligent traffic monitoring systems are mobility, compactness and energy-efficiency. Current traffic monitoring systems are based on fixed installations and thus have no or least portability. Also, they use many sensors (e.g, cameras, induction loops, radar or laser), utilize little or no image processing capabilities, and(More)
— This research paper presents a system for vehicles collision avoidance using zigbee sensors. The system developed provides timely safety information for drivers who do not have any idea of happening collision. This system calculates the distance covered by vehicle from the moment brakes are applied till it stops and the time taken by it, at variable(More)
BACKGROUND Recent studies have identified the diagnostic challenge of low-grade infections after shoulder arthroplasty surgery. Infections after nonarthroplasty procedures have not been reported. This study assessed patient-related risk factors, outcomes, and clinical presentation of low-grade infection after open and arthroscopic nonarthroplasty shoulder(More)
– In this paper we describe an efficient method for traffic light controllers. This method is based on enhanced reinforcement learning with local states around each traffic light on crossings. It uses many independent controllers depending upon the number of crossings. Each controller can learn the best actions by a supervised method that is based on reward(More)
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