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Working stress is recognized as one of the major challenges faced by the working community around the world. Working Stress is the response of the people, when presented work demands are not matched to their knowledge and ability and which challenge their ability to cope. Increased stress at work cause depression and anxiety. Working stress cannot be avoided, so mechanism to cope with the stress positively...
We propose a new Non-Intrusive Load Monitoring (NILM) approach for appliances power profile/signal estimation at low sampling rate (1 s or greater). The proposed method relay on two main phases: identification of turned on appliance combination in a given time period and estimation of the active power consumption signal of each individual appliances in that combination. Unlike most existing NILM method...
A Non-Intrusive Load Monitoring (NILM) method for residential appliances based on uncorrelated spectral components of an active power signal is presented. This method utilizes the Karhunen Loéve (KL) expansion to breakdown the active power signal into subspace components so as to construct a unique information rich appliance signature. Unlike existing NILM techniques that rely on multiple measurements...
A real-time event tracking method is proposed that is immune to background variances. The proposed method models each pixel as a collection of Gaussian distributions to handle background variations and uses manipulations in the RGB space to mitigate the effects of foreground shadows. A two stepped connected component analysis method is also introduced in refining the estimated foreground and clustering...
This paper addresses the specific problem of human event detection from a video sequence in both indoor and outdoor environments. Foreground image pixels are identified through the principle of background subtraction by defining a reference background model using a mixture of time varying Gaussian distributions. Color filtering in the RGB space is then used to remove image distortions due to camera...
This paper addresses the generic object counting problem with object overlapping occurring at varied levels and degrees. The overall image containing the objects is segmented from the background. Thereafter a combination of parameters is extracted from each of the segments to construct a parameter space. The overall space formed by these vectors contains redundant dimensions due to the existence of...
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