Combined experimental and TDDFT computational studies of the optical and electrical characteristic of luminol films-doped TiO2 with 9.027% power conversion efficiency

Journal of Materials Science: Materials in Electronics - In this study, the spectrophotometric analysis was applied to check the optical properties of undoped [LO]TF and doped Luminol films with...     

Dynamic mechanical analysis and non-isothermal kinetics of EVA/PPy carbon black nanocomposites

Pure ethylene-co-vinyl acetate (EVA) and its conductive blend-nanocomposite with polypyrrole (PPy)/carbon black (CB) were prepared using a melt mixing process. Dynamic mechanical analysis and non-isothermal thermal gravimetrical analysis were performed on the samples. The storage modulus, loss modulus, and damping factor of the EVA/PPy/CB nanocomposites were significantly affected by the incorporation of PPy/CB. Two thermal decomposition stages were detected for pure and blended nanocomposite samples. Peak analysis was used to deconvolve the first complex decomposition stage. The Coats-Redfern method was used to determine the kinetic parameters. Improving the thermal and mechanical properties of the EVA co-polymer will enable the three-phase blend/nanocomposites to be used in several industrial applications.     

Enhancement of Infrared Images Using Super Resolution Techniques Based on Big Data Processing

This paper presents a super-resolution (SR) technique for enhancement of infrared (IR) images. The suggested technique relies on the image acquisition model, which benefits from the sparse representations of low-resolution (LR) and high-resolution (HR) patches of the IR images. It uses bicubic interpolation and minimum mean square error (MMSE) estimation in the prediction of the HR image with a scheme that can be interpreted as a feed-forward neural network. The suggested algorithm to overcome the problem of having only LR images due to hardware limitations is represented with a big data processing model. The performance of the suggested technique is compared with that of the standard regularized image interpolation technique as well as an adaptive block-by-block least-squares (LS) interpolation technique from the peak signal-to-noise ratio (PSNR) perspective. Numerical results reveal the superiority of the proposed SR technique.

     

2D/3D Shaped Radiation Patterns of Sunflower and Conformal Antenna Arrays Using Phase Synthesis

2D and 3D beam synthesis from different antenna array arrangements are investigated in this paper. Planar sunflower, conformal cylinderical and spherical helical array arrangements are studied. The particle swarm optimization (PSO) technique is used to predict the phase distribution on the array elements. The beam synthesis is achieved by comparing the array factor with a predetermined mask with both upper and lower limits according to the intented application requirements. Different 2D and 3D masks are used in beam synthesis as pencil, flat-top, and cosecant single beam are predicted. The planar sunflower antenna array is investigated due to its high gain, low side-lobe level (SLL) below ??20 dB and its compact size. The phase distribution of sunflower array is estimated using PSO to radiate dual-beams in different planes. Dual-beam with pencil, flat-top, and cosecant beams are obtained with different half-power beam widths. 3D conformal antenna arrays of cylindrical and spherical helical arrangements are studied. Each 3D conformal array consists of four arms shifted in position by 90° orintation angle. Each arm is designed to radiate single beam in a specific direction. Four-beams are considered to radiate in the directions of θ_1,2,3,4?=?30°, and ?₁?=?0°, ?₂?=?90°, ?₃?=?180°, and ?₄?=?270° with SLL optimized below ??17 dB. The array arrangements analysis is based on the array theory formulation, through the implemention of the estimiated equation using a home programmed MATLAB code.

     

Encoder-independent decoder-dependent depth-assisted error concealment algorithm for wireless 3D video communication

Three-Dimensional Multi-View Video (3D MVV) contains diverse video streams taken by different cameras around an object. Thence, it is an imperative assignment to fulfill efficient compression to attain future resource bonds whilst preserving a decisive reception MVV quality. The extensive 3D MVV encoding and transmission over mobile or Internet are vulnerable to packet losses on account of the existence of severe channel faults and restricted bandwidth. In this work, we propose a new Encoder-Independent Decoder-Dependent Depth-Assisted Error Concealment (EIDD-DAEC) algorithm. It invests the depth correlations between the temporally, spatially, and inter-view adjoining Macro-Blocks (MBs) to conceal the erroneous streams. At the encoder, the existing inter-view, temporal, and spatial matching are exploited to efficiently compress the 3D MVV streams and to estimate the Disparity Vectors (DVs) and Motion Vectors (MVs). At the decoder, the gathered MVs and DVs from the received coded streams are used to calculate additional depth-assisted MVs and DVs, which are afterwards combined with the collected candidate texture color MVs and DVs groups for concealing the lost MBs of inter- and intra-encoded frames. Finally, the optimum DVs and MVs concealment candidates are selected by the Directional Interpolation Error Concealment Algorithm (DIECA) and Decoder Motion Vector Estimation Algorithm (DMVEA), respectively. Experimental results on several standardized 3D MVV sequences verified the efficacy of the proposed EIDD-DAEC algorithm by achieving ameliorated efficacious objective and subjective results without generating and transporting depth maps at the encoder. The proposed work achieves high 3D MVV quality performance with an improved average Peak Signal-to-Noise Ratio (PSNR) gain by up to 0.95 ~ 2.70 dBs compared to the state-of-the-art error concealment algorithms, which do not employ depth-assisted correlations at different Quantization Parameters (QPs) and Packet Loss Rates (PLRs) of 40%.     

Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm

In cloud computing, resources are dynamically provisioned and delivered to users in a transparent manner automatically on-demand. Task execution failure is no longer accidental but a common characteristic of cloud computing environment. In recent times, a number of intelligent scheduling techniques have been used to address task scheduling issues in cloud without much attention to fault tolerance. In this research article, we proposed a dynamic clustering league championship algorithm (DCLCA) scheduling technique for fault tolerance awareness to address cloud task execution which would reflect on the current available resources and reduce the untimely failure of autonomous tasks. Experimental results show that our proposed technique produces remarkable fault reduction in task failure as measured in terms of failure rate. It also shows that the DCLCA outperformed the MTCT, MAXMIN, ant colony optimization and genetic algorithm-based NSGA-II by producing lower makespan with improvement of 57.8, 53.6, 24.3 and 13.4 % in the first scenario and 60.0, 38.9, 31.5 and 31.2 % in the second scenario, respectively. Considering the experimental results, DCLCA provides better quality fault tolerance aware scheduling that will help to improve the overall performance of the cloud environment.

     

Optimal network restructure via improved whale optimization approach

Latterly, reduction of power loss in distribution system is the objective of many researches due to its impact on total costs and voltage profiles. It can be handled by optimal restructure of radial distribution system (RDS). This article introduces an innovative approach to restructure of RDS by electing the optimal switches combination subject to the system operating constraints, which is improved whale optimization approach (IWOA). The suggested approach combines exploitation of WOA with exploration of differential evolution (DE), and thus, it supplies a promising candidate solution. The suggested approach is tested on IEEE 33 and 69 bus RDS. The superiority of the suggested approach compared with other well‐known approaches is verified through simulation results by observation of total losses, cost, and saving. Also, the impact of alterable loading is investigated to prove the effectiveness of the suggested IWOA.     

Hilbert Transform and Statistical Analysis for Channel Selection and Epileptic Seizure Prediction

This paper is concerned with Electroencephalography (EEG) seizure prediction, which means the detection of the pre-ictal state prior to ictal activity occurrence. The basic idea of the proposed approach for EEG seizure prediction is to work on the signals in the Hilbert domain. The operation in the Hilbert domain guarantees working on the low-pass spectra of EEG signal segments to avoid artifacts. Signal attributes in the Hilbert domain including amplitude, derivative, local mean, local variance, and median are analyzed statistically to perform the channel selection and seizure prediction tasks. Pre-defined prediction and false-alarm probabilities are set to select the channels, the attributes, and bins of probability density functions (PDFs) that can be useful for seizure prediction. Due to the multi-channel nature of this process, there is a need for a majority voting strategy to take a decision for each signal segment. Simulation results reveal an average prediction rate of 96.46%, an average false-alarm rate of 0.028077/h and an average prediction time of 60.1595 min for a 90-min prediction horizon.

     

The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings

Field spectroscopy is a rapid and non-destructive analytical technique that may be used for assessing plant stress and disease. The objective of this study was to develop spectral indices for detection of Ganoderma disease in oil palm seedlings. The reflectance spectra of oil palm seedlings from three levels of Ganoderma disease severity were acquired using a spectroradiometer. Denoizing and data transformation using first derivative analysis was conducted on the original reflectance spectra. Then, comparative statistical analysis was used to select significant wavelength from transformed data. Wavelength pairs of spectral indices were selected using optimum index factor. The spectral indices were produced using the wavelength ratios and a modified simple ratio method. The relationship analysis between spectral indices and total leaf chlorophyll (TLC) was conducted using regression technique. The results suggested that six spectral indices are suitable for the early detection of Ganoderma disease in oil palm seedlings. Final results after regression with TLC showed that Ratio 3 is the best spectral index for the early detection of Ganoderma infection in oil palm seedlings. For future works, this can be used for the development of robust spectral indices for Ganoderma disease detection in young and mature oil palm using airborne hyperspectral imaging.     

Biologically active polymers. IV. Synthesis and antimicrobial activity of tartaric acid polyamides

New bactericidal polyamides with quaternary ammonium or phosphonium salts were prepared, and their antimicrobial activities were explored. The polyamides were synthesized by the polycondensation of diethyl‐l‐tartrate or chloromethylated diethyl‐l‐tartrate with ethylenediamine in dry absolute ethanol. The polyamides were modified to yield polymers with either quaternary ammonium or phosphonium salts. The polymers were characterized with elemental microanalysis and ¹H‐NMR and IR spectra. The antimicrobial activity of the polymers bearing onium salts was studied against Gram‐negative bacteria (Escherichia coli, Pseudomones aeruginosa, Shigella sp., and Salmonella typhae), Gram‐positive bacteria (Bacillus subtilis and Bacillus cereus), and a fungus (Trichophytum rubrum) by the cut‐plug and viable‐cell‐count methods. Although all the polymers showed high antibacterial activity, some had no antifungal activity. The tributyl phosphonium salt of the polyamide was more effective against both Gram‐negative and Gram‐positive bacteria than the triethyl ammonium and triphenyl phosphonium salts of the polyamide. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 4780–4790, 2006