Soft chemistry synthesis and crystal structure of MgxCu3−xV2O6(OH)4·2H2O

Mg_xCu_3−xV₂O₆(OH)₄·2H₂O (x ∼ 1), with similar crystal structure as volborthite Cu₃V₂O₇(OH)₂·2H₂O, was successfully prepared by a soft chemistry technique. The method consists of mixing magnesium nitrate and copper nitrate with a boiling solution of vanadium oxide (obtained by reacting V₂O₅ with few mL of 30 vol.% H₂O₂ followed by addition of distilled water). When ammonium hydroxide NH₄OH 10% was added (pH 7.8), a green yellowish precipitate was obtained. Using X-ray powder diffraction data, its crystal structure has been determined by Rietveld refinement. Compared to volborthite, the vanadium coordination changes from tetrahedral VO₄ to trigonal bipyramidal VO₅, and magnesium replaces copper, preferably, in the less distorted octahedron. At 300 °C, the phase formed is similar to the high pressure (HP) monoclinic Cu₃V₂O₈ phase. However at higher temperature, 600 °C, the phase obtained is different from known Cu₃V₂O₈ phases.     

A Simple Quasi-2D Numerical Model of a Thermogage Furnace

A simple quasi-2D model for the temperature distribution in a graphite tube furnace is presented. The model is used to estimate the temperature gradients in the furnace at temperatures above which contact sensors can be used, and to assist in the redesign of the furnace heater element to improve the temperature gradients. The Thermogage graphite tube furnace is commonly used in many NMIs as a blackbody source for radiation thermometer calibration and as a spectral irradiance standard. Although the design is robust, easy to operate and can change temperature rapidly, it is limited by its effective emissivity of typically 99.5–99.8%. At NMIA, the temperature gradient along the tube is assessed using thermocouples up to about 1,500°C, and the blackbody emissivity is calculated from this. However, at higher operating temperatures (up to 2,900°C), it is impractical to measure the gradient, and we propose to numerically model the temperature distributions used to calculate emissivity. In another paper at this conference, the model is used to design an optimized heater tube with improved temperature gradients. In the model presented here, the 2-D temperature distribution is simplified to separate the axial and radial temperature distributions within the heater tube and the surrounding insulation. Literature data for the temperature dependence of the electrical and thermal conductivities of the graphite tube were coupled to models for the thermal conductivity of the felt insulation, particularly including the effects of allowing for a gas mixture in the insulation. Experimental measurements of the temperature profile up to 1,500°C and radial heat fluxes up to 2,200°C were compared to the theoretical predictions of the model and good agreement was obtained.     

Kinetic investigation of C38 steel corrosion in concentrated perchloric acid solutions

The corrosion behaviour of steel at various concentrations of perchloric acid was studied by weight loss method in temperature range from 298 to 323 K. Results obtained show that corrosiveness of acid increases with its concentration and temperature. The logarithm of corrosion rate was plotted against the acid concentration and values of Hammett H_o and Strehlow R_o(H) acidity functions. The activation energies, enthalpies and entropies of the corrosion process of steel were also determined and fitted against R_o(H).     

Plasma myeloperoxidase,NT‐proBNP,and troponin‐I in patients on CAPD compared with those on regular hemodialysis

Myeloperoxidase (MPO) is a hemoprotein that is released during inflammation and may lead to irreversible protein and lipid modification, increasing levels of oxidized low density lipoprotein, and promoting athrogenesis. Recently, it has been considered as a risk factor for cardiovascular diseases. Similarly, the measurement of carotid intima‐media thickness gives an indication about the degree of atherosclerosis and prediction of clinical cardiovascular events. Elevated white blood cells counts may indicate a state of acute inflammation and follow its progression. Dialysis patients are at a high risk of developing cardiovascular disease compared with healthy subjects. The role of N‐terminal pro‐brain natriuretic peptide and increased cardiac troponin in identification and prognostication of cardiovascular diseases in end‐stage renal disease patients has been investigated. The current study aimed to evaluate plasma MPO and its possible relationship with carotid intima‐media thickness, troponin I, N‐terminal pro‐brain natriuretic peptide (NT‐proBNP), and insulin resistance as measured by homeostatic model assessment (HOMA index) in a cohort of Saudi patients who are undergoing hemodialysis (HD) vs. continuous ambulatory peritoneal dialysis for end‐stage renal disease. Plasma MPO was significantly higher in patients on continuous ambulatory peritoneal dialysis (CAPD) than in those on HD and in normal subjects (P<0.001). Conversely, NT‐proBNP plasma levels were significantly higher in patients on HD (both predialysis and postdialysis) than in those on CAPD (P<0.01) and than normal subjects. Similarly, plasma troponin‐I levels were significantly higher in patients on HD compared with those of CAPD and than normal subjects (P<0.001). Plasma troponin‐I and NT‐proBNP levels were positively correlated in the 3 groups namely those on CAPD, Pre‐HD, and post‐HD (r: 0.464 and P=0.047; r: 0.330 and P=0.013; and r: 0.452 and P=0.024), respectively. There was no correlation between the MPO level and carotid intima‐media thickness (P>0.05). However, plasma MPO level correlated positively with the white blood cell count in patients on CAPD and in those on HD (P<0.05). Our findings suggest an increased oxidative stress in CAPD patients compared with HD patients, while the reported difference in plasma NT‐proBNP and troponin‐I may be related to the rapid decline of residual renal function in HD and type of membrane used in the HD dialysis procedure itself.     

Dejittering in the transport of MPEG-2 and MPEG-4 video

When multimedia information is transported over a packet-switched network, the quality of presentation can be degraded due to network delay variation or jitter. This paper presents a dejittering scheme that can be used in the transport of MPEG-4 and MPEG-2 video to absorb any introduced network jitter, thus preserving the presentation quality of transported media streams. The dejittering scheme is based on the statistical approximation of delay variation in the arrival times of video packets carrying encoded clock reference values and a filtering and re-stamping mechanism. In addition, a brief overview of the MPEG-4 system is presented.     

Speech emotion recognition using optimized genetic algorithm-extreme learning machine

Multimedia Tools and Applications - Automatic Emotion Speech Recognition (ESR) is considered as an active research field in the Human-Computer Interface (HCI). Typically, the ESR system is...     

Improved Approximations for Guarding 1.5-Dimensional Terrains

We present a 4-approximation algorithm for the problem of placing the fewest guards on a 1.5D terrain so that every point of the terrain is seen by at least one guard. This improves on the previous best approximation factor of 5 (see King in Proceedings of the 13th Latin American Symposium on Theoretical Informatics, pp. 629–640, 2006). Unlike most of the previous techniques, our method is based on rounding the linear programming relaxation of the corresponding covering problem. Besides the simplicity of the analysis, which mainly relies on decomposing the constraint matrix of the LP into totally balanced matrices, our algorithm, unlike previous work, generalizes to the weighted and partial versions of the basic problem.     

Convolutional neural networks for the classification of chest X-rays in the IoT era

Multimedia Tools and Applications - Chest X-ray medical imaging technology allows the diagnosis of many lung diseases. It is known that this technology is frequently used in hospitals, and it is...     

Recognizing arabic handwritten characters using deep learning and genetic algorithms

Automated techniques for Arabic content recognition are at a beginning period contrasted with their partners for the Latin and Chinese contents recognition. There is a bulk of handwritten Arabic archives available in libraries, data centers, historical centers, and workplaces. Digitization of these documents facilitates (1) to preserve and transfer the country’s history electronically, (2) to save the physical storage space, (3) to proper handling of the documents, and (4) to enhance the retrieval of information through the Internet and other mediums. Arabic handwritten character recognition (AHCR) systems face several challenges including the unlimited variations in human handwriting and the leakage of large and public databases. In the current study, the segmentation and recognition phases are addressed. The text segmentation challenges and a set of solutions for each challenge are presented. The convolutional neural network (CNN), deep learning approach, is used in the recognition phase. The usage of CNN leads to significant improvements across different machine learning classification algorithms. It facilitates the automatic feature extraction of images. 14 different native CNN architectures are proposed after a set of try-and-error trials. They are trained and tested on the HMBD database that contains 54,115 of the handwritten Arabic characters. Experiments are performed on the native CNN architectures and the best-reported testing accuracy is 91.96%. A transfer learning (TF) and genetic algorithm (GA) approach named “HMB-AHCR-DLGA” is suggested to optimize the training parameters and hyperparameters in the recognition phase. The pre-trained CNN models (VGG16, VGG19, and MobileNetV2) are used in the later approach. Five optimization experiments are performed and the best combinations are reported. The highest reported testing accuracy is 92.88%.

     

An optimal deployable bandwidth aggregation system

The explosive increase in data demand coupled with the rapid deployment of various wireless access technologies have led to the increase of number of multi-homed or multi-interface enabled devices. Fully exploiting these interfaces has motivated researchers to propose numerous solutions that aggregate their available bandwidths to increase overall throughput and satisfy the end-user’s growing data demand. These solutions, however, do not utilize their interfaces to the maximum without network support, and more importantly, have faced a steep deployment barrier. In this paper, we propose an optimal deployable bandwidth aggregation system (DBAS) for multi-interface enabled devices. We present the DBAS architecture that does not introduce any intermediate hardware, modify current operating systems, modify socket implementations, nor require changes to current applications or legacy servers. The DBAS architecture is designed to automatically estimate the characteristics of applications and dynamically schedule various connections and/or packets to different interfaces. We also formulate our optimal scheduler as a mixed integer programming problem yielding an efficient solution. We evaluate DBAS via implementation on the Windows OS and further verify our results with simulations on NS2. Our evaluation shows that, with current Internet characteristics, DBAS reaches the throughput upper bound with no modifications to legacy servers. It also highlights the significant enhancements in the response time introduced by DBAS, which directly enhances the user experience.