Technologies for Oil Extraction: A Review

This paper is designed for people who have little or no technical background or earlier knowledge of oil extraction processing. It provides a vital introduction to both traditional and improved methods for the extraction of vegetable oil from oilseeds. Comparisons are made between different improved technologies aim to show under what circumstances they may be technically appropriate or inappropriate. The improved method include; Mechanical Extraction (oil expeller, motorized screw press) and solvent extraction (chemical extraction). Also problems associated with each method and the needs for more research for the improvement of the methods are analyzed. It has been shown that for any developing country to effectively adopt modern methods in the production of edible vegetable oils, improvement on the existing traditional methods, environmental factors need to be studied. This can be achieved through more research in the recommended area of need .Also oil expression technology in order to create an interest and awareness of the technology, which may help improving the rural development as wealth and self-employment

A reduced-reference perceptual image and video quality metric based on edge preservation

In image and video compression and transmission, it is important to rely on an objective image/video quality metric which accurately represents the subjective quality of processed images and video sequences. In some scenarios, it is also important to evaluate the quality of the received video sequence with minimal reference to the transmitted one. For instance, for quality improvement of video transmission through closed-loop optimisation, the video quality measure can be evaluated at the receiver and provided as feedback information to the system controller. The original image/video sequence-prior to compression and transmission-is not usually available at the receiver side, and it is important to rely at the receiver side on an objective video quality metric that does not need reference or needs minimal reference to the original video sequence. The observation that the human eye is very sensitive to edge and contour information of an image underpins the proposal of our reduced reference (RR) quality metric, which compares edge information between the distorted and the original image. Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art RR metric. © 2012 Martini et al

Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation

Image-to-image translation has been made much progress with embracing Generative Adversarial Networks (GANs). However, it's still very challenging for translation tasks that require high quality, especially at high-resolution and photorealism. In this paper, we present Discriminative Region Proposal Adversarial Networks (DRPAN) for high-quality image-to-image translation. We decompose the procedure of image-to-image translation task into three iterated steps, first is to generate an image with global structure but some local artifacts (via GAN), second is using our DRPnet to propose the most fake region from the generated image, and third is to implement "image inpainting" on the most fake region for more realistic result through a reviser, so that the system (DRPAN) can be gradually optimized to synthesize images with more attention on the most artifact local part. Experiments on a variety of image-to-image translation tasks and datasets validate that our method outperforms state-of-the-arts for producing high-quality translation results in terms of both human perceptual studies and automatic quantitative measures.Comment: ECCV 201

Why Are Deep Representations Good Perceptual Quality Features?

Recently, intermediate feature maps of pre-trained convolutional neural networks have shown significant perceptual quality improvements, when they are used in the loss function for training new networks. It is believed that these features are better at encoding the perceptual quality and provide more efficient representations of input images compared to other perceptual metrics such as SSIM and PSNR. However, there have been no systematic studies to determine the underlying reason. Due to the lack of such an analysis, it is not possible to evaluate the performance of a particular set of features or to improve the perceptual quality even more by carefully selecting a subset of features from a pre-trained CNN. This work shows that the capabilities of pre-trained deep CNN features in optimizing the perceptual quality are correlated with their success in capturing basic human visual perception characteristics. In particular, we focus our analysis on fundamental aspects of human perception, such as the contrast sensitivity and orientation selectivity. We introduce two new formulations to measure the frequency and orientation selectivity of the features learned by convolutional layers for evaluating deep features learned by widely-used deep CNNs such as VGG-16. We demonstrate that the pre-trained CNN features which receive higher scores are better at predicting human quality judgment. Furthermore, we show the possibility of using our method to select deep features to form a new loss function, which improves the image reconstruction quality for the well-known single-image super-resolution problem.Comment: To be presented at ECCV 202

Pathogenic variability in Exserohilum turcicum and identification of resistant sources to turcicum leaf blight of maize (Zea mays L.)

Turcicum leaf blight of maize incited by Exserohilum turcicum (Pass.) Leonard and Suggs is the major limiting factor of maize production in temperate agro-ecologies. Disease management through host plant resistance is the most effective strategy. In the present study among 26 maize genotypes which were initially screened for resistance against E. turcicum under field conditions, 8 genotypes viz., PS 39, CML 451, CML 470, CML 472, VL 1030, VL 1018140, VL1018527 and SMI178-1 were found resistant when screened against twelve isolates of E. turcicum under artificial epiphytotic conditions. Eight genotypes viz., PS45, CML165, CML459, VL1249, VL0536, SMC-5, SMC-3 and KDL 211 were found moderately resistant with disease grade ranged from 2.1-2.5. These maize genotypes possess resistance to turcicum leaf blight can be used successfully in developing high yielding early maturing varieties for high altitude temperate agro-ecologies. The fungus E. turcicum is highly variable in nature. Variability studies on pathogenicity were conducted on twelve isolates of E. turcicum on eleven putative differential maize lines. During the present study a wide pathogenic variation was observed among the twelve isolates of E. turcicum. Cluster analysis on the basis of similarity or dissimilarity in reaction types exhibited by the differential hosts, clustered the isolates into 6 pathogenic groups. The isolates belonged to higher altitudes (Kti 10, Kti11, Kti5) were found to be more aggressive as compared to the isolates of low altitude areas

Fourier Method for Approximating Eigenvalues of Indefinite Stekloff Operator

We introduce an efficient method for computing the Stekloff eigenvalues associated with the Helmholtz equation. In general, this eigenvalue problem requires solving the Helmholtz equation with Dirichlet and/or Neumann boundary condition repeatedly. We propose solving the related constant coefficient Helmholtz equation with Fast Fourier Transform (FFT) based on carefully designed extensions and restrictions of the equation. The proposed Fourier method, combined with proper eigensolver, results in an efficient and clear approach for computing the Stekloff eigenvalues.Comment: 12 pages, 4 figure

Classification of All 1/2 BPS Solutions of the Tiny Graviton Matrix Theory

The tiny graviton matrix theory [hep-th/0406214] is proposed to describe DLCQ of type IIB string theory on the maximally supersymmetric plane-wave or AdS_5xS^5 background. In this paper we provide further evidence in support of the tiny graviton conjecture by focusing on the zero energy, half BPS configurations of this matrix theory and classify all of them. These vacua are generically of the form of various three sphere giant gravitons. We clarify the connection between our solutions and the half BPS configuration in N=4 SYM theory and their gravity duals. Moreover, using our half BPS solutions, we show how the tiny graviton Matrix theory and the mass deformed D=3, N=8 superconformal field theories are related to each other.Comment: 40 pages, 12 figures, v

Phylogenic analysis of serotype Asia1 foot-and-mouth disease virus from Sulaimani/Iraq using VP1 protein: heterogeneity with vaccine strain As1/Shamir/89

Foot-and-mouth disease virus (FMDV) serotypes O, A and Asia1 are responsible for a significant number of disease outbreaks in Iraq. The current study can be considered as the first molecular characterization of serotype Asia1 in Iraq. The present investigation reports the detection of serotype FMDV Asia1 from local farms in Sulaimani districts in 2012 and 2014 outbreaks. Phylogenetic analysis of the complete VP1 gene has shown that FMDV Asia1 field isolates were under genetic novel variant Sindh-08 (group VII) including PAK/iso/11 and TUR/13 strains. The VP1 protein sequence of circulatory FMDV Asia1 genotype showed heterogeneity of nine amino acid substitutions within the G-H loop with the vaccine strain As1/Shamir/89 (JF739177) that is currently used in vaccination program in Iraq. Our result indicated that differences in VP1 protein at G-H loop of the locally circulated FMDV serotype Asia1 strain may be a reason for current vaccination failure