Manual analysis of thermal image for detecting defects and classifying of condition of surge arrester take a long time. Artificial neural network is good tool for predict and classify data. This study applied neural network for classify the degree of degradation of surge arrester. Thermal image as input of neural network was segmented using Otsu’s segmentation and histogram method to get featur...

It is essential to have a reliable system to detect humans in forestry environments in close range of forestry machines to stop cutting or carrying operations to prohibit any harm to humans. We use a thermal camera due to its advantages over RGB cameras by considering different lighting and occlusion conditions. This paper introduces a novel shape-independent feature called brightness-histogram...

In this paper, we investigate the dynamics of the Bloch vector of a single two-level atom which interacts with a single quantized electromagnetic field mode according to the Jaynes-Cummings model, where the field is initially prepared in a thermal state. The time evolution of the Bloch vector S(t) seems to be in complete disorder because of the thermal distribution of the initial state of the f...

In this paper, an experimentation to enhance the visibility of hot objects in a thermal image acquired with ordinary digital camera is reported, after the applications of lowpass and median filters to suppress the distracting granular noises. The common thresholding and slicing techniques were used on the histogram at different gray levels, followed by a subjective comparative evaluation. The b...

This paper presents column parallel signal processing techniques for reducing thermal and RTS noises of in-pixel source followers. Noise reduction methods of correlated multiple sampling differential averaging (CMSDA) and histogram-based RTS-noise suppression and averaging (HRNSA) are applied and their effectiveness for RTS noise reduction is demonstrated for large sampling number.

The numerical simulation of strongly first-order phase transitions has remained a notoriously difficult problem even for classical systems due to the exponentially suppressed (thermal) equilibration in the vicinity of such a transition. In the absence of efficient update techniques, a common approach to improve equilibration in Monte Carlo simulations is to broaden the sampled statistical ensem...

Using the random-cluster representation of the q-state Potts models we consider the pooling of data from cluster-update Monte Carlo simulations for different thermal couplings K and number of states per spin q. Proper combination of histograms allows for the evaluation of thermal averages in a broad range of K and q values, including noninteger values of q. Due to restrictions in the sampling p...

We propose a new Monte Carlo technique in which the de-generacy of energy states is obtained with a Markovian process analogous to that of Metropolis used currently in canonical simulations. The obtained histograms are much broader than those of the canonical histogram technique studied by Ferrenberg and Swendsen. Thus we can reliably reconstruct ther-modynamic functions over a much larger temp...

We studied thermal turbulence in a low Prandtl number, Pr, fluid using liquid Hg (Pr ­ 0.024). For Rayleigh numbers (106 , Ra , 108), the histogram of temperature fluctuations at the center of the cell (aspect ratio 1), and the scaling laws for the Nusselt number and the large scale flow, all showed He-like hard turbulence. However, the cascade range of the frequency spectrum of the temperature...