Cuckoo search algorithm based satellite image contrast and brightness enhancement using DWT–SVD

This paper presents a new contrast enhancement approach which is based on Cuckoo Search (CS) algorithm and DWT-SVD for quality improvement of the low contrast satellite images. The input image is decomposed into the four frequency subbands through Discrete Wavelet Transform (DWT), and CS algorithm used to optimize each subband of DWT and then obtains the singular value matrix of the low-low thresholded subband image and finally, it reconstructs the enhanced image by applying IDWT. The singular value matrix employed intensity information of the particular image, and any modification in the singular values changes the intensity of the given image. The experimental results show superiority of the proposed method performance in terms of PSNR, MSE, Mean and Standard Deviation over conventional and state-of-the-art techniques.     

Accurate predictive modeling of response variables under dynamic condition without the use of past response data

One promising attribute of the dynamic predictive modeling method introduced by Rollins et al. [D.K. Rollins, J. Liang, P. Smith, Accurate simplistic predictive modeling of nonlinear dynamic processes, ISA Transactions 37(4) (1998) 193-203] is its ability to accurately predict output response without the use of online output data. The proposed method only needs online input data to accurately predict output behavior once the semi-empirical model has been identified using offline data. This ability is critical to chemical processes because many output variables (such as chemical composition) are often measured infrequently, inaccurately, or not at all. In addition, in the presence of extremely high measurement noise of the output variable, this work will demonstrate very accurate predictive performance. Finally, this article will show that the method of Rollins et al. can predict better without the use of output data than with the use of output data in the case of large measurement variance. Thus, the proposed method is being recommended for its accuracy, especially in situations where online output response data is limited or inaccurate.     

Theoretical thermoelectric figure of merit of highly disordered lead telluride type materials

A quantitative estimate is made of the reduction in lattice thermal conductivity (λ_L) of lead telluride type material as a function of doping level, grain size, alloying and temperature. The effect of this reduction in λ_L on the thermoelectric figure of merit is explored by considering a two band multivalleyed model. It is concluded that, in highly disordered, alloyed material, moderately doped and with a mean grain size of 1μm the figure of meritis increased by about 10% at 300K and about 6% at 800K compared with “single crystal” or large grain size material.     

Advanced Scout: Data Mining and Knowledge Discovery in NBA Data

Advanced Scout is a PC-based data mining application used by National Basketball Association (NBA)coaching staffs to discover interesting patterns in basketball game data. We describe Advanced Scout software from the perspective of data mining and knowledge discovery. This paper highlights the pre-processing of raw data that the program performs, describes the data mining aspects of the software and how the interpretation of patterns supports the processof knowledge discovery. The underlying technique of attribute focusing asthe basis of the algorithm is also described. The process of pattern interpretation is facilitated by allowing the user to relate patterns to video tape.     

Investigation of CTARA wood-burning stove. Part I. Experimental investigation

This paper describes experimental investigation of a single pot wood-burning stove developed atCtara. The stove incorporates features such as a converging combustion space, a grate, preheated secondary air and a swirling-device. Using chipped wood and a large diameter vessel (30 cm), efficiencies in excess of 40% have been measured. An electric stove, having a geometry similar to that of the woodburning stove, has also been experimented with to obtain magnitudes of heat transfer coefficient at the vessel bottom, to estimate relative contributions of convection and radiation heat transfer to the vessel bottom, to study the effect of flame to grate heat release ratios and to study the effect of depth of insertion of the vessel into the stove. Finally, a 3-pot mud stove used in the Konkan region is investigated and it is shown that provision of a grate improves the efficiency of the stove.     

Constrained MIMO dynamic discrete-time modeling exploiting optimal experimental design

This article presents a new multiple input, multiple output (MIMO) constrained discrete-time modeling (DTM) approach for dynamic block-oriented processes that does not require the nonlinear steady state characteristics to be known prior to model development. This approach uses an efficient statistical experimental design to provide design points for sequential step tests. The DTM is developed from this data in two stages. In the first stage, the ultimate response (steady state) model is determined from just the ultimate response data of the sequential step tests. In the second stage, the dynamic parameters are estimated under the constraint of the fitted ultimate response model obtained in the first stage. The constrained formulation is given for MIMO Hammerstein and Wiener block-oriented systems. Comparison of the proposed constrained DTM method is made with unconstrained DTM and constrained continuous-time modeling (CTM). Prediction accuracy of the proposed method is significantly better than unconstrained DTM and comparable to constrained CTM for the process studied.     

Halfwave retarder for all polarization states

We show that a device consisting of an optical rotator placed between two identically oriented quarter-wave plates always acts as a halfwave retarder for some pair of orthogonal elliptically polarized states that can be selected by linear adjustment of the optical rotation and orientation of the quarter-wave plates.     

Spatial context-based optimal multilevel energy curve thresholding for image segmentation using soft computing techniques

Neural Computing and Applications - Image segmentation using multilevel thresholding (MT) is one of the leading methods. Although, as most techniques are based on the image histogram to be...