Novel approaches for synthesizing video textures

Video texture, a novel type of medium, can produce a new video with a continuously varying stream of images from a recorded video. A classic approach to generate video textures is to apply principal components analysis (PCA) for dimensionality reduction (i.e. extraction of frame signatures) and autoregressive (AR) process for prediction purposes. In this paper we investigate the use of other dimensionality reduction techniques to generate accurate video textures. Based on our experiments, the quality of video textures can be improved further. We also propose a new approach for generating video textures using probabilistic principal components analysis (PPCA) and Gaussian process dynamical model (GPDM) to synthesize video textures which contain frames that never appeared before and with similar motions as original videos. Furthermore, we propose two ways of generating online video textures by applying the incremental Isomap and incremental Spatio-temporal Isomap (IST-Isomap). Both approaches can produce good online video texture results. In particular, IST-Isomap, that we propose, is more suitable for sparse video data (e.g. cartoon).     

A nonparametric Bayesian learning model using accelerated variational inference and feature selection

Pattern Analysis and Applications - Developing effective machine learning methods for multimedia data modeling continues to challenge computer vision scientists. The capability of providing...     

Role of Glycosylation in Vascular Calcification

Glycosylation is an important step in post-translational protein modification. Altered glycosylation results in an abnormality that causes diseases such as malignancy and cardiovascular diseases. Recent emerging evidence highlights the importance of glycosylation in vascular calcification. Two major types of glycosylation, N-glycosylation and O-glycosylation, are involved in vascular calcification. Other glycosylation mechanisms, which polymerize the glycosaminoglycan (GAG) chain onto protein, resulting in proteoglycan (PG), also have an impact on vascular calcification. This paper discusses the role of glycosylation in vascular calcification.     

Fly Ash-based Geopolymer Lightweight Concrete Using Foaming Agent

In this paper, we report the results of our investigation on the possibility of producing foam concrete by using a geopolymer system. Class C fly ash was mixed with an alkaline activator solution (a mixture of sodium silicate and NaOH), and foam was added to the geopolymeric mixture to produce lightweight concrete. The NaOH solution was prepared by dilute NaOH pellets with distilled water. The reactives were mixed to produce a homogeneous mixture, which was placed into a 50 mm mold and cured at two different curing temperatures (60 °C and room temperature), for 24 hours. After the curing process, the strengths of the samples were tested on days 1, 7, and 28. The water absorption, porosity, chemical composition, microstructure, XRD and FTIR analyses were studied. The results showed that the sample which was cured at 60 °C (LW2) produced the maximum compressive strength for all tests, (11.03 MPa, 17.59 MPa, and 18.19 MPa) for days 1, 7, and 28, respectively. Also, the water absorption and porosity of LW2 were reduced by 6.78% and 1.22% after 28 days, respectively. The SEM showed that the LW2 sample had a denser matrix than LW1. This was because LW2 was heat cured, which caused the geopolymerization rate to increase, producing a denser matrix. However for LW1, microcracks were present on the surface, which reduced the compressive strength and increased water absorption and porosity.     

Simple N‐Heterocyclic Carbenes as Ligands in Ullmann‐Type Ether and Thioether Formations

A simple N‐heterocyclic carbene (NHC) derived from 1‐methyl‐3‐ethylimidazolium tetrafluoroborate was found to be an efficient ligand for a range of copper‐catalyzed cross‐coupling reactions, leading to the formation of aromatic ethers and thioethers.

     

Feature selection using swarm-based relative reduct technique for fetal heart rate

Fetal heart rate helps in diagnosing the well-being and also the distress of fetal. Cardiotocograph (CTG) monitors the fetal heart activity to estimate the fetal tachogram based on the evaluation of ultrasound pulses reflected from the fetal heart. It consists in a simultaneous recording and analysis of fetal heart rate signal, uterine contraction activity and fetal movements. Generally CTG comprises more number of features. Feature selection also called as attribute selection is a process of selecting a subset of highly relevant features which is responsible for future analysis. In general, medical datasets require more number of features to predict an activity. This paper aims at identifying the relevant and ignores the redundant features, consequently reducing the number of features to assess the fetal heart rate. The features are selected by using unsupervised particle swarm optimization (PSO)-based relative reduct (US-PSO-RR) and compared with unsupervised relative reduct and principal component analysis. The proposed method is then tested by applying various classification algorithms such as single decision tree, multilayer perceptron neural network, probabilistic neural network and random forest for maximum number of classes and clustering accuracies like root mean square error, mean absolute error, Davies–Bouldin index and Xie–Beni index for minimum number of classes. Empirical results show that the US-PSO-RR feature selection technique outperforms the existing methods by producing sensitivity of 72.72 %, specificity of 97.66 %, F-measure of 74.19 % which is remarkable, and clustering results demonstrate error rate produced by US-PSO-RR is less as well.     

Background subtraction using finite mixtures of asymmetric Gaussian distributions and shadow detection

Foreground segmentation of moving regions in image sequences is a fundamental step in many vision systems including automated video surveillance, human-machine interface, and optical motion capture. Many models have been introduced to deal with the problems of modeling the background and detecting the moving objects in the scene. One of the successful solutions to these problems is the use of the well-known adaptive Gaussian mixture model. However, this method suffers from some drawbacks. Modeling the background using the Gaussian mixture implies the assumption that the background and foreground distributions are Gaussians which is not always the case for most environments. In addition, it is unable to distinguish between moving shadows and moving objects. In this paper, we try to overcome these problem using a mixture of asymmetric Gaussians to enhance the robustness and flexibility of mixture modeling, and a shadow detection scheme to remove unwanted shadows from the scene. Furthermore, we apply this method to real image sequences of both indoor and outdoor scenes. The results of comparing our method to different state of the art background subtraction methods show the efficiency of our model for real-time segmentation.     

Multilayered Cylindrical Triboelectric Nanogenerator to Harvest Kinetic Energy of Tree Branches for Monitoring Environment Condition and Forest Fire

Forest fires present a great threat as they can rapidly grow and become large, resulting in tragic loss of life and property when occurring near occupied land. Here a self‐powered fire alarm system based on a novel multilayered cylindrical triboelectric nanogenerator (MC‐TENG) that can produce electrical power for the detection sensors by harvesting the kinetic energy of moving tree branches in a forest is presented. The major parameters for harvesting the kinetic energy using the proposed MC‐TENG are investigated, including the number of triboelectric layers, the frequency, the amplitude of external excitation, and the orientation between motion direction and device configuration. The fabricated MC‐TENG results in a peak power of 2.9 mW and a maximum average power of 1.2 mW at a low frequency of 1.25 Hz. The integrated self‐powered forest fire alarm system, consisting of fire sensors, a carbon‐based micro‐supercapacitor, and the MC‐TENG, is demonstrated to be able to report fire risk or hazard efficiently, accurately, and robustly. This study provides a new solution to reduce the forest fire risk through a portable and sustainable alarm system by effectively harvesting kinetic energies in natural environment with TENG technology.     

Quantitative duplex real-time polymerase chain reaction assay with TaqMan probe detects and quantifies Crocodylus porosus in food chain and traditional medicines

Consumption and exploitation of crocodiles have been rampant for their exotic, nutritive and medicinal attributes. These depredations are alarming and although they have continued to be monitored by wildlife and conservation agencies, unlawful trading of crocodiles shows an increasing trend worldwide. Recently, conventional polymerase chain reaction (PCR) and PCR-restriction fragment length polymorphism (RFLP) assays for crocodile have been documented but they are only suitable for identification and cannot quantify adulterations. We described here a quantitative duplex real-time PCR assay with probes to quantify contributions from Crocodylus porosus materials simultaneously. A very short amplicon size of 127bp was used because longer targets could have been broken down in samples, bringing considerable uncertainty in molecular analysis. We have validated a TaqMan probe-based duplex real-time PCR (qPCR) assay for the detection of 0.004 ng DNA in pure state and 0.1% target meat in model chicken meatball. False negative detection was eliminated through an endogenous control (141-bp site of eukaryotic 18S rRNA). Analysis of 12 model chicken meatballs adulterated with C. porosus reflected 96.3?120.2% target recovery at 0.1?10% adulterations. A validation test of 21 commercial food and traditional medicine (TM) crocodile-based products showed 100% effectiveness. Short amplicon sizes, alternative complementary target, exceptional stability and superior sensitivity suggested the assay could be used for the identification and quantitative determination of C. porosus in any food or TM samples even under degraded conditions.