Perceptually motivated Rated Controller for Video coding

Rate control regulates the instantaneous video bit -rate to maximize a picture quality metric while satisfying channel constraints. Typically, a quality metric such as Peak Signalto-Noise ratio (PSNR) or weighted signal -to-noise ratio(WSNR) is chosen out of convenience. However this metric is not always truly representative of perceptual video quality.Attempts to use perceptual metrics in rate control have been limited by the accuracy of the video quality metrics chosen.Recently, new and improved metrics of subjective quality such as the Video quality experts group's (VQEG) NTIA1 General Video Quality Model (VQM) have been proven to have strong correlation with subjective quality. Here, we apply the key principles of the NTIA -VQM model to rate control in order to maximize perceptual video quality. Our experiments demonstrate that applying NTIA -VQM motivated metrics to standard TMN8 rate control in an H.263 encoder results in perceivable quality improvements over a baseline TMN8 / MSE based implementation.

Systematic study on crystal-contact engineering of diphthine synthase: influence of mutations at crystal-packing regions on X-ray diffraction quality

It is well known that protein crystallizability can be influenced by site-directed mutagenesis of residues on the molecular surface of proteins, indicating that the intermolecular interactions in crystal-packing regions may play a crucial role in the structural regularity at atomic resolution of protein crystals. Here, a systematic examination was made of the improvement in the diffraction resolution of protein crystals on introducing a single mutation of a crystal-packing residue in order to provide more favourable packing interactions, using diphthine synthase from Pyrococcus horikoshii OT3 as a model system. All of a total of 21 designed mutants at 13 different crystal-packing residues yielded almost isomorphous crystals from the same crystallization conditions as those used for the wild-type crystals, which diffracted X-rays to 2.1 angstrom resolution. Of the 21 mutants, eight provided crystals with an improved resolution of 1.8 angstrom or better. Thus, it has been clarified that crystal quality can be improved by introducing a suitable single mutation of a crystal-packing residue. In the improved crystals, more intimate crystal-packing interactions than those in the wild-type crystal are observed. Notably, the mutants K49R and T146R yielded crystals with outstandingly improved resolutions of 1.5 and 1.6 angstrom, respectively, in which a large-scale rearrangement of packing interactions was unexpectedly observed despite the retention of the same isomorphous crystal form. In contrast, the mutants that provided results that were in good agreement with the designed putative structures tended to achieve only moderate improvements in resolution of up to 1.75 angstrom. These results suggest a difficulty in the rational prediction of highly effective mutations in crystal engineering.

No-reference image quality assessment using modified extreme learning machine classifier

In this paper, we present a machine learning approach to measure the visual quality of JPEG-coded images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity (HVS) factors such as edge amplitude, edge length, background activity and background luminance. Image quality assessment involves estimating the functional relationship between HVS features and subjective test scores. The quality of the compressed images are obtained without referring to their original images ('No Reference' metric). Here, the problem of quality estimation is transformed to a classification problem and solved using extreme learning machine (ELM) algorithm. In ELM, the input weights and the bias values are randomly chosen and the output weights are analytically calculated. The generalization performance of the ELM algorithm for classification problems with imbalance in the number of samples per quality class depends critically on the input weights and the bias values. Hence, we propose two schemes, namely the k-fold selection scheme (KS-ELM) and the real-coded genetic algorithm (RCGA-ELM) to select the input weights and the bias values such that the generalization performance of the classifier is a maximum. Results indicate that the proposed schemes significantly improve the performance of ELM classifier under imbalance condition for image quality assessment. The experimental results prove that the estimated visual quality of the proposed RCGA-ELM emulates the mean opinion score very well. The experimental results are compared with the existing JPEG no-reference image quality metric and full-reference structural similarity image quality metric.

Fuzzy optimization model for water quality management of a river system - Closure

A fuzzy waste-load allocation model, FWLAM, is developed for water quality management of a river system using fuzzy multiple-objective optimization. An important feature of this model is its capability to incorporate the aspirations and conflicting objectives of the pollution control agency and dischargers. The vagueness associated with specifying the water quality criteria and fraction removal levels is modeled in a fuzzy framework. The goals related to the pollution control agency and dischargers are expressed as fuzzy sets. The membership functions of these fuzzy sets are considered to represent the variation of satisfaction levels of the pollution control agency and dischargers in attaining their respective goals. Two formulations—namely, the MAX-MIN and MAX-BIAS formulations—are proposed for FWLAM. The MAX-MIN formulation maximizes the minimum satisfaction level in the system. The MAX-BIAS formulation maximizes a bias measure, giving a solution that favors the dischargers. Maximization of the bias measure attempts to keep the satisfaction levels of the dischargers away from the minimum satisfaction level and that of the pollution control agency close to the minimum satisfaction level. Most of the conventional water quality management models use waste treatment cost curves that are uncertain and nonlinear. Unlike such models, FWLAM avoids the use of cost curves. Further, the model provides the flexibility for the pollution control agency and dischargers to specify their aspirations independently.

Basic Needs and Much More With One Kilowatt Per Capita

Conventional thinkin g holds that increased energy consumption is a prerequisite for economic and social development. This belief, together With the prospect of dwindling global petroleum supplies and the high costs of expanding energy supply generally, lead many to believe that it is not feasible to improve living standards substantially in the developing countries. But by shifting to high-quality energy carriers and by exploiting cost-effective opportunities for more efficient energy use, it would be possible to satisfy basic human needs and to provide considerable further improvements in living standards without significantly increasing per-capita energy use above the present level.