Thermal properties of pineapple leaf fiber reinforced composites Mangal, Ravindra; Saxena, N.S.; Sreekala, M.S. ...
Materials science & engineering. A, Structural materials : properties, microstructure and processing,
01/2003, Letnik:
339, Številka:
1
Journal Article
Recenzirano
Simultaneous measurment of effective thermal conductivity (
λ) and effective thermal diffusivity (
κ) of pineapple leaf fiber reinforced phenolformaldehyde (PF) composites have been studied by ...transient plane source (TPS) technique. The samples of different weight percentage typically (15, 20, 30, 40 and 50%) have been taken. It is found that of effective thermal conductivity and effective thermal diffusivity of the composites decrease, as compared with pure PF as the fraction of fiber loading increases. Using Y. Agari, model thermal conductivity of pure fiber is evaluated and compared with the thermal conductivity of fiber determined by extrapolated experimental value of composite. Also, we have compared the results of thermal conductivity of composites with two models (Rayleigh–Maxwell and Meredith–Tobias model). Good agreement between theoretical and experimental result has been found.
Nowadays, there is an increasing tendency to upload images to online platforms acting as information carriers for various applications. Unfortunately, the unauthorized utilization of such images is a ...serious concern that has significantly impacted security and privacy. Although digital images are widely available, the storage of these images requires a large amount of data. This study aims to address these issues by developing an improved encryption–compression-based algorithm for securing digital images that reduces unnecessary hardware storage space, transmission time and bandwidth demand. First, the image is encrypted using chaotic encryption. Then the encrypted image is compressed using wavelet-based compression in order to make efficient use of resources without any information about the encryption key. On the other side, the image is decompressed and decrypted by the receiver. The security assessment of the proposed algorithm is performed in different ways, such as differential and statistical, key sensitivity, and execution time analysis. The experimental analysis proves the security of the method against various possible attacks. Furthermore, the extensive evaluations on a real dataset demonstrate that the proposed solution is secure and has a low encryption overhead compared to similar methods.
With the rapid advancement of the internet and the widespread application of information technology, a large amount of imaging data has been transmitted over the internet in the healthcare domain. ...The region of interest (ROI) portion of medical-imaging security is important not only for protecting individual privacy but also for accurate clinical diagnosis and treatment. Therefore, an effective security solution is required to prevent third parties from understanding the transmitted data. This paper proposes an efficient image encryption technique called DeepENC that uses multi-modal features to transfer data securely. The first stage performs ROI selection using UNet3+, a deep-learning model with high computational efficiency and fewer network parameters. Subsequently, fingerprint and iris features are extracted, fused and encoded in a deep learning network, and a highly secure encryption key is generated using a novel, 2D hybrid chaotic map. Lastly, the key is employed to encrypt only the ROI portion of the medical images, reducing the time cost. Through comprehensive experimental analysis, this study demonstrates the superiority of the DeepENC technique over other encryption approaches, establishing the validity of the technique for securely transmitting sensitive data.
As digital images become increasingly sophisticated, they raise significant security concerns, including the copyright violation, data leakage and identity theft. Deep learning-based data hiding ...techniques conceals mark within media carriers, enabling both error-free mark extraction and lossless carrier restoration. However, the challenge of enhancing watermark robustness data while ensuring imperceptibility, security, embedding capacity, and model security becomes increasingly pronounced in deep learning environment. In this paper, we present GANMarked, a robust watermarking method embedding a secure mark into the media carriers, based on a generative adversarial network (GAN). First, we utilize an improved autoencoder-based network for secure generation of encoded mark by encoding two individual watermarks into one. Second, the encoded mark imperceptibly embedding into the media carriers using GAN network. Third, the extraction network considers only the marked media as input and robustly recovers the hidden mark at the receiver side. In addition to media security, we fine-tuned the deep watermarking network using secret trigger key to verify the ownership of suspicious models if any piracy or infringements occur. Lastly, decoder network reconstructs the encoded media into the individual one. Our method has been empirically validated across multiple standard datasets, consistently maintaining high imperceptibility, robustness and security, even with variations in hybrid noise during mark extraction. Further, the results demonstrate that the proposed method significantly outperforms other existing methods in terms of imperceptibility and robustness while ensuring reversibility and security.
Recently, digital images are an essential source of data obtained from consumer devices, thus playing a crucial role in various important scenarios such as consumer apps, businesses, e-commerce, ...education, entertainment and healthcare. However, security and privacy are primarily concerned with the transmission and storage of these images. Therefore, there is an urgent demand to protect their copyright and prevent leakage. To address these concerns, this paper presents a novel multimodal biometric, encryption and watermarking-based method for digital image security. First, multimodal biometric features are extracted and fused using the customized deep learning model. Second, different secret keys are used to encrypt the fused features of the biometric images. Here, the fused features, considered as watermarks, are divided into sub-features before encrypting them with different keys. Third, to improve security while maintaining imperceptibility, the encoded sub-features are embedded into multiple cover media-based convolutional neural network (ConvNet). The experimental results demonstrate that the proposed system is highly secure and that it can recover complete marks under different attacks. Further, experiments illustrate the superior performance of our proposed system in terms of both imperceptibility and robustness compared with the competing schemes. It indicates a considerable improvement in imperceptibility and robustness of 62.83% and 25.16%, respectively over existing schemes.
In the category of 2D materials, MoS2 a transition metal dichalcogenide, is a novel and intriguing class of materials with interesting physicochemical properties, explored in applications ranging ...from cutting-edge optoelectronic to the frontiers of biomedical and biotechnology. MoS2 nanostructures an alternative to heavy toxic metals exhibit biocompatibility, low toxicity and high stability, and high binding affinity to biomolecules. MoS2 nanostructures provide a lot of opportunities for the advancement of novel biosensing, nanodrug delivery system, electrochemical detection, bioimaging, and photothermal therapy. Much efforts have been made in recent years to improve their physiochemical properties by developing a better synthesis approach, surface functionalization, and biocompatibility for their safe use in the advancement of biomedical applications. The understanding of parameters involved during the development of nanostructures for their safe utilization in biomedical applications has been discussed. Computational studies are included in this article to understand better the properties of MoS2 and the mechanism involved in their interaction with biomolecules. As a result, we anticipate that this combined experimental and computational studies of MoS2 will inspire the development of nanostructures with smart drug delivery systems, and add value to the understanding of two-dimensional smart nano-carriers.
Abstract
Data hiding has become a hot research topic in recent years due to increased attention placed on the copyright protection of ocean images and related digital records. Further, high image ...volumes put enormous pressure on transmission bandwidth and storage capabilities. This paper proposes an innovative deep learning‐based data‐hiding technique for ocean images. First, a down‐sampling scheme is applied to compress the secret mark before embedding it in the host media. Then, a convolutional neural network is used to embed and recover compressed marks into or from the host ocean image. Finally, a generative adversarial network‐based reconstruction network is used to reconstruct the high‐quality mark image. Our experiments show that the proposed work not only maintains high imperceptibility and robustness against many attacks but also provides better data‐hiding performance than related works.
This work reports a detailed study of reduced graphene oxide (rGO)-Fe3O4 nanoparticle composite as an excellent electromagnetic (EM) interference shielding material in GHz range. A rGO-Fe3O4 ...nanoparticle composite was synthesized using a facile, one step, and modified solvothermal method with the reaction of FeCl3, ethylenediamine and graphite oxide powder in the presence of ethylene glycol. Various structural, microstructural and optical characterization tools were used to determine its synthesis and various properties. Dielectric, magnetic and EM shielding parameters were also evaluated to estimate its performance as a shielding material for EM waves. X-ray diffraction patterns have provided information about the structural and crystallographic properties of the as-synthesized material. Scanning electron microscopy micrographs revealed the information regarding the exfoliation of graphite into rGO. Well-dispersed Fe3O4 nanoparticles over the surface of the graphene can easily be seen by employing transmission electron microscopy. For comparison, rGO nanosheets and Fe3O4 nanoparticles have also been synthesized and characterized in a similar fashion. A plot of the dielectric and magnetic characterizations provides some useful information related to various losses and the relaxation process. Shielding effectiveness due to reflection (SER), shielding effectiveness due to absorption (SEA), and total shielding effectiveness (SET) were also plotted against frequency over a broad range (8-12 GHz). A significant change in all parameters (SEA value from 5 dB to 35 dB for Fe3O4 nanoparticles to rGO-Fe3O4 nanoparticle composite) was found. An actual shielding effectiveness (SET) up to 55 dB was found in the rGO-Fe3O4 nanoparticle composite. These graphs give glimpses of how significantly this material shows shielding effectiveness over a broad range of frequency.
•Herein, a first report on the MoS2-rGO/ZnO nanocomposite by one-step hydrothermal synthesis method.•MoS2-rGO/ZnO nanocomposite shows higher electrical conductivity and dielectric loss parameter than ...pure MoS2-rGO nanocomposite.•Most of the electromagnetic energy attenuated by MoS2-rGO/ZnO nanocomposite due to the decrease in the transmittance value.•Synthesis is much simpler and safer, without any hazardous tail gas or reagents involved.
The tremendous development in electronic devices and their prolific implications have triggered a serious threat to our ambiance in form of electromagnetic interference (EMI) pollution. The present study manifests a feasible approach to design an alternative architecture of graphene-based material for improving the shielding performance through absorption in X-band frequency array. The MoS2-rGO/ZnO ternary nanostructure has been synthesized through a simplistic solvothermal approach. The studies suggest that the MoS2-rGO/ZnO ternary nanocomposite exhibits outstanding EM wave absorption and dissipation capabilities as compared to its constituent components. The average EMI SET (∼32 dB) of the studied MoS2-rGO/ZnO nanocomposite owes to the combined effects of various relaxations and polarizations of ZnO and MoS2-rGO. The synergic effect, as well as dielectric and magnetic losses, furnish the high shielding effectiveness. The incorporation of ZnO nanoparticles in MoS2-rGO nanocomposite results in a spectacular average value of EMI SET, making it appropriate for widespread applications.
Ferromagnetism in Cu-doped ZnSe semiconducting quantum dots Kumar, Pushpendra; Singh, Kedar
Journal of nanoparticle research : an interdisciplinary forum for nanoscale science and technology,
04/2011, Letnik:
13, Številka:
4
Journal Article
The projection of integrating optical, magnetic and electronic functionalities into a single material have aggravated passionate attention in mounting wide band gap diluted magnetic semiconductor ...(DMS) in the midst of room temperature ferromagnetism. We report the evidence of ferromagnetism in Cu-doped ZnSe quantum dots (QDs) below room temperature, grown from a single source precursor by lyothermal method with the sizes of approximately 3.2–5.14 nm. QDs mainly exhibit paramagnetic behavior between 80 and 300 K, with a weak ferromagnetic/anti-ferromagnetic exchange at lower temperature as observed by superconducting quantum interference device (SQUID) magnetometer. From the Curie–Weiss behavior of the susceptibility, Curie temperature (
T
c
) of Cu-doped ZnSe sample has been evaluated. From EPR, we obtain the
Lande
-
g
factor in the Zeeman interaction term as 2.060. Photoluminescence and EPR measurements support and confirm the view that Cu
2+
substitutes for Zn
2+
in Cu-doped ZnSe quantum dots.
