Piezoelectric properties of zinc oxide/iron oxide filled polyvinylidene fluoride nanocomposite fibers

Piezoelectric nanogenerators (PENG) with flexible and simple design have pronounced significance in fabricating sustainable devices for self-powering electronics. This study demonstrates the fabrication of electrospun nanocomposite fibers from polyvinylidene fluoride (PVDF) filled zinc oxide (ZnO)/iron oxide (FeO) nanomaterials. The nanocomposite fiber based flexible PENG shows piezoelectric output voltage of 5.9 V when 3 wt% of ZnO/FeO hybrid nanomaterial is introduced, which is 29.5 times higher than the neat PVDF. No apparent decline in output voltage is observed for almost 2000 s attributed to the outstanding durability. This higher piezoelectric output performance is correlated with the β-phase transformation studies from the Fourier transformation infrared spectroscopy and the crystallinity studies from the differential scanning calorimetry. Both these studies show respective enhancement of 3.79 and 2.16% in the β-phase crystallinity values of PVDF-ZnO/FeO 3 wt% composite. Higher dielectric constant value obtained for the same composite (three times higher than the neat PVDF) confirms the increased energy storage efficiency as well. Thus the proposed soft and flexible PENG is a promising mechanical energy harvester, and its good dielectric properties reveals the ability to use this material as good power sources for wearable and flexible electronic devices.

     

Investigation of antimicrobial properties and in-vitro bioactivity of Ce3+-Sr2+dual-substituted nano hydroxyapatites

Dual doped calcium apatite has been widely focused as it enhances the osteoconductive property for the possible applications in orthopedic and dental implants. In this work, we investigate the antimicrobial and bioactive properties of cerium/strontium (Ce³⁺/Sr²⁺) co-substituted hydroxyapatite (HA) nanoparticles synthesized by sol-gel assisted precipitation method. The structure, morphology, functional groups, photoluminescence, and thermal stability of the developed systems are examined. The comparative studies performed among the pure HA, Sr²⁺, and Ce³⁺-substituted HA nanoparticles illustrate higher antibacterial activity with lowered apatite-forming ability and biocompatibility for the Ce³⁺-substituted HA. However, the Ce³⁺/Sr²⁺co-substituted HA exhibits better biocompatibility, apatite-forming ability, and good antimicrobial properties. Sr²⁺ ion inclusion leads to better biological properties and compromise the cytotoxic nature of the Ce³⁺-HA. In addition, the Ce³⁺/Sr²⁺-HA nanoparticles prevent thermal decomposition up to 700°C, pointing also toward the possibility of this co-substituted HA in bone implant applications.     

Vapor sensing performances of PVDF nanocomposites containing titanium dioxide nanotubes decorated multi-walled carbon nanotubes

Inorganic nanocarbon hybrid materials are good alternatives for superior electrochemical performance and specific capacitance to their traditional counterparts. Nanocarbons act as a good template for the growth of metal nanoparticles on it and their hybrid combinations enhance the charge transport and rate capability of electrochemical materials without sacrificing the specific capacity. In this study, titanium dioxide nanotubes (TNT) are synthesized hydrothermally in the presence of multi-walled carbon nanotubes (MWCNT) where the latter acts as base template material for the metal oxide nanotube growth. The MWCNT–TNT hybrid material possesses very high dielectric strength and this is used to enhance the dielectric property of the polymer polyvinyledene fluoride (PVDF). Solution mixing was used to prepare the PVDF/MWCNT–TNT nanocomposites by varying the filler concentrations from 0.5 to 2.5 wt%. Excellent vapor sensing was noticed for the PVDF nanocomposites with different rate of response towards commonly used laboratory solvents. The composites and the fillers were characterized for its morphology and structural properties using scanning and transmission electron microscopy, X-ray diffraction studies and infrared spectroscopy. Vapor sensing was measured as relative resistance variations against the solvent vapors, and the dielectric properties of the composites were measured at room temperature during the frequency 10²–10⁷ Hz. Experimental results revealed the influence of filler synergy on the properties of PVDF and the enhancement in the solvent vapor detectability and dielectric properties reflects the ability of these composite films in flexible vapor sensors and in energy storage.     

Novel geometric features for off-line writer identification

Writer identification is an important field in forensic document examination. Typically, a writer identification system consists of two main steps: feature extraction and matching and the performance depends significantly on the feature extraction step. In this paper, we propose a set of novel geometrical features that are able to characterize different writers. These features include direction, curvature, and tortuosity. We also propose an improvement of the edge-based directional and chain code-based features. The proposed methods are applicable to Arabic and English handwriting. We have also studied several methods for computing the distance between feature vectors when comparing two writers. Evaluation of the methods is performed using both the IAM handwriting database and the QUWI database for each individual feature reaching Top1 identification rates of 82 and 87 % in those two datasets, respectively. The accuracies achieved by Kernel Discriminant Analysis (KDA) are significantly higher than those observed before feature-level writer identification was implemented. The results demonstrate the effectiveness of the improved versions of both chain-code features and edge-based directional features.     

A image encryption algorithm based on chaotic Lorenz system and novel primitive polynomial S-boxes

We have proposed a robust, secure and efficient image encryption algorithm based on chaotic maps and algebraic structure. Nowadays, the chaotic cryptosystems gained more attention due to their efficiency, the assurance of robustness and high sensitivity corresponding to initial conditions. In literature, there are many encryption algorithms that can simply guarantees security while the schemes based on chaotic systems only promises the uncertainty, both of them can not encounter the needs of current scenario. To tackle this issue, this article proposed an image encryption algorithm based on Lorenz chaotic system and primitive irreducible polynomial substitution box. First, we have proposed 16 different S-boxes based on projective general linear group and 16 primitive irreducible polynomials of Galois field of order 256, and then utilized these S-boxes with combination of chaotic map in image encryption scheme. Three chaotic sequences can be produced by the disturbed of Lorenz chaotic system corresponding to variables x, y and z. We have constructed a new pseudo random chaotic sequence k_i based on x, y and z. The plain image is encrypted by the use of chaotic sequence k_i and XOR operation to get a ciphered image. To show the strength of presented image encryption, some renowned analyses are performed.

     

Gait recognition for person re-identification

The Journal of Supercomputing - Person re-identification across multiple cameras is an essential task in computer vision applications, particularly tracking the same person in different scenes....     

Round-Robin sequential forward selection algorithm for prostate cancer classification and diagnosis using multispectral imagery

This paper proposes an automatic classification system for the use in prostate cancer diagnosis. The system aims to detect and classify prostatic tissue textures captured from microscopic samples taken from needle biopsies. Biopsies are usually analyzed by a trained pathologist with different grades of malignancy typically corresponding to different structural patterns as well as apparent textures. In the context of prostate cancer diagnosis, four major groups have to be accurately recognized: stroma, benign prostatic hyperplasia, prostatic intraepithelial neoplasia, and prostatic carcinoma. Recently, multispectral imagery has been proposed as a new image acquisition modality which unlike conventional RGB-based light microscopy allows the acquisition of a large number of spectral bands within the visible spectrum, resulting in a large feature vector size. Many features in the initial feature set are irrelevant to the classification task and are correlated with each other, resulting in an increase in the computational complexity and a reduction in the recognition rate. In this paper, a Round-Robin (RR) sequential forward selection RR-SFS is used to address these problems. RR is a technique for handling multi-class problems with binary classifiers by training one classifier for each pair of classes. The experimental results demonstrate this finding when compared with classical method based on the multiclass SFS and other ensemble methods such as bagging/boosting with decision tree (C4.5) classifier where it is shown that RR-SFS method achieves the best results with a classification accuracy of 99.9%.     

A comprehensive overview of feature representation for biometric recognition

Multimedia Tools and Applications - The performance of any biometric recognition system heavily dependents on finding a good and suitable feature representation space where observations from...     

Designing dual phase sensing materials from polyaniline filled styrene–isoprene–styrene composites

The demand for developing oil detectors is ever increasing since the cleanup and recovery from oil spill usually take long time. Here we propose oil sensors made of polyaniline (PANI) filled poly(styrene–isoprene–styrene) (SIS) block copolymer composite films with good uniformity and dispersion. The changes in resistivity of the samples in presence of both oil and water media reveal the good sensing ability of SIS–PANI films towards oil in water (dual phase). The morphology and chemical composition of the developed products are characterized by scanning electron microscopy and Fourier transformation infrared spectroscopy. Swelling studies are performed to correlate the sensing response to the structural variations and based on it a mechanism is derived for the dual phase sensing. Contact angle measurements confirm the behavior further. The thermal properties and crystallinity of the composites are also addressed by the thermogravimetric and differential scanning calorimetric studies. The developed oil sensor material is able to withstand extreme temperature condition as well.