Shape memory alloys (SMAs) show a particular behavior that is the ability to recuperate the original shape while heating above specific critical temperatures (shape memory effect) or to withstand high deformations recoverable while unloading (pseudoelasticity). In many cases the SMAs play the actuator's role. Starting from the origin of the shape memory effect, the mechanical properties of these alloys are illustrated. This paper presents a review of SMAs applications in the aerospace field with particular emphasis on morphing wings (experimental and modeling), tailoring of the orientation and inlet geometry of many propulsion system, variable geometry chevron for thrust and noise optimization, and more in general reduction of power consumption. Space applications are described too: to isolate the micro-vibrations, for low-shock release devices and self-deployable solar sails. Novel configurations and devices are highlighted too.

https://www.mdpi.com/1996-1944/13/8/1856/pdf

Shape Memory Alloys for Aerospace, Recent Developments, and New Applications: A Short Review

Semi-quantum protocols that allow some of the users to remain classical are proposed for a large class of problems associated with secure communication and secure multiparty computation. Specifically, first-time semi-quantum protocols are proposed for key agreement, controlled deterministic secure communication and dialogue, and it is shown that the semi-quantum protocols for controlled deterministic secure communication and dialogue can be reduced to semi-quantum protocols for e-commerce and private comparison (socialist millionaire problem), respectively. Complementing with the earlier proposed semi-quantum schemes for key distribution, secret sharing and deterministic secure communication, set of schemes proposed here and subsequent discussions have established that almost every secure communication and computation tasks that can be performed using fully quantum protocols can also be performed in semi-quantum manner. Some of the proposed schemes are completely orthogonal-state-based, and thus, fundamentally different from the existing semi-quantum schemes that are conjugate coding-based. Security, efficiency and applicability of the proposed schemes have been discussed with appropriate importance.

Semi-quantum communication: protocols for key agreement, controlled secure direct communication and dialogue

The existing work on unsupervised segmentation frequently does not present any statistical extent to estimating and equating procedures, gratifying a qualitative calculation. Furthermore, regardless of the datum that enormous research is dedicated to the advancement of a novel segmentation approach and upgrading the deep learning techniques, there is an absence of research comprehending the assessment of eminent conventional segmentation methodologies for HSI. In this paper, to moderately fill this gap, we propose a direct method that diminishes the issues to some extent with the deep learning methods in the arena of a HSI space and evaluate the proposed segmentation techniques based on the method of the clustering-based profound iterating deep learning model for HSI segmentation termed as CPIDM. The proposed model is an unsupervised HSI clustering technique centered on the density of pixels in the spectral interplanetary space and the distance concerning the pixels. Furthermore, CPIDM is a fully convolutional neural network. In general, fully convolutional nets remain spatially invariant preventing them from modeling position-reliant outlines. The proposed network maneuvers this by encompassing an innovative position inclined convolutional stratum. The anticipated unique edifice of deep unsupervised segmentation deciphers the delinquency of oversegmentation and nonlinearity of data due to noise and outliers. The spectrum efficacy is erudite and incidental from united feedback via deep hierarchy with pooling and convolutional strata; as a consequence, it formulates an affiliation among class dissemination and spectra along with three-dimensional features. Moreover, the anticipated deep learning model has revealed that it is conceivable to expressively accelerate the segmentation process without substantive quality loss due to the existence of noise and outliers. The proposed CPIDM approach outperforms many state-of-the-art segmentation approaches that include watershed transform and neuro-fuzzy approach as validated by the experimental consequences.

/pdf/cpidm-a-clustering-based-profound-iterating-deep-learning-2qx765lw42.pdf

CPIDM: A Clustering-Based Profound Iterating Deep Learning Model for HSI Segmentation

Higher education in my country needs to focus on the cultivation of innovative talents, independent innovation, technological development, cultural innovation, and the promotion of scientific and technological knowledge. This paper proposes a performance index system for university social science research based on BP neural network and the relevant theoretical knowledge is utilized to construct a university social science research performance evaluation model. The results show that the difference between the predicted value of each sample and its expected output value is not large, and the value of the prediction error is also relatively small, all less than 1. In this paper, the performance evaluation method of social science research in colleges and universities based on BP neural network is an evaluation method with high efficiency, strong operability and high accuracy. Therefore, the BP neural network model is utilized to evaluate and optimize the performance of social science research in colleges and universities. The established BP neural network model has very low error value and good generalization ability, which effectively proves that the training sample data can fit the neural network simulation ideally. In the same way, it shows that the output value of BP neural network can be very close to the input vector.

Research on optimization of scientific research performance management based on BP neural network

The advancement of Internet technologies has led to the availability of audios, images, and videos in different forms. The unauthorized users are exploiting the use of multimedia by transmitting them on various Internet sites to earn money unethically without the intervention of the original copyright holder. Watermarking is a technique used to hide the signal known as watermark inside multimedia data that is not visible to the intruder to manipulate any information. In this paper, a secured watermarking approach is developed to tackle issues related to copyright protection and ownership identification. A Secured Graph Based Transform, Singular Valued Decomposition, and Hyperchaotic Encryption hybrid techniques are proposed. The watermark cannot be embedded in every frame of the video as it adds to the size of the video and watermark can be easily retrieved by an intruder. Therefore, the frame selection algorithm has been proposed in the given work. Adding watermark in the frame adds to the challenge of quality loss. The quality loss is addressed in this work. Various attacks have been applied on the watermarked frames to calculate the performance of the proposed technique using quality metrics: Peak Signal to Noise Ratio, Structural Similarity Index, Normalized Correlation, and Bit Error Rate. The results indicate that the proposed technique is effective against various attack scenarios.

/pdf/a-secured-frame-selection-based-video-watermarking-technique-2e5mmsj6k3.pdf

A Secured Frame Selection Based Video Watermarking Technique to Address Quality Loss of Data: Combining Graph Based Transform, Singular Valued Decomposition, and Hyperchaotic Encryption

The multimedia technologies are gaining a lot of popularity these days Many unauthorized persons are gaining the access of multimedia such as videos, audios, and images The transmission of multimedia across the Internet by unauthorized person has led to the problem of illegal distribution The problem arises when copyrighted data is getting accessed without the knowledge of copyright owner The videos are the most attacked data during COVID-19 pandemic In this paper, the frame selection video watermarking technique is proposed to tackle the issue The proposed work enlightens frame selection followed by watermarking embedding and testing of the technique against various attacks The embedding of the watermark is done on selected frames of the video The additional security feature Hyperchaotic Encryption is applied on watermark before embedding Watermark embedding is done using graph-based transform and singular-valued decomposition and the performance of the technique is further optimized using hybrid combination of grey wolf optimization and genetic algorithm Many researchers face the challenge of quality loss after embedding of watermark Proposed technique will aim to overcome those challenges A total of 6 videos (Akiyo, Coastguard, Foreman, News, Bowing, and Pure Storage) are used for carrying out research work The performance evaluation of the proposed technique has been carried out after processing it against practical video processing attacks Gaussian noise, sharpening, rotation, blurring, and JPEG compression [ABSTRACT FROM AUTHOR] Copyright of Mathematical Problems in Engineering is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission However, users may print, download, or email articles for individual use This abstract may be abridged No warranty is given about the accuracy of the copy Users should refer to the original published version of the material for the full abstract (Copyright applies to all Abstracts )

/pdf/a-novel-optimized-graph-based-transform-watermarking-5exjukj42v.pdf

A Novel Optimized Graph-Based Transform Watermarking Technique to Address Security Issues in Real-Time Application

The use of Internet technology has led to the availability of different multimedia data in various formats. The unapproved customers misuse multimedia information by conveying them on various web objections to acquire cash deceptively without the first copyright holder's intervention. Due to the rise in cases of COVID-19, lots of patient information are leaked without their knowledge, so an intelligent technique is required to protect the integrity of patient data by placing an invisible signal known as a watermark on the medical images. In this paper, a new method of watermarking is proposed on both standard and medical images. The paper addresses the use of digital rights management in medical field applications such as embedding the watermark in medical images related to neurodegenerative disorders, lung disorders, and heart issues. The various quality parameters are used to figure out the evaluation of the developed method. In addition, the testing of the watermarking scheme is done by applying various signal processing attacks.

/pdf/a-robust-image-encrypted-watermarking-technique-for-4thnffs771.pdf

A Robust Image Encrypted Watermarking Technique for Neurodegenerative Disorder Diagnosis and Its Applications.

Investigation of Smart Material Actuators & Aerodynamic optimization of Morphing Wing

The presented work presents an efficient watermarking technique based on Discrete Wavelet Transformation (DWT), Singular Value Decomposition (SVD) and Rail Fence methods that are applied on digital multimedia such as videos, images. The occurrences to abuse and copyright infringement of videos by some intrudes is increasing day by day. Video watermarking is technique to resolve the given problem .The proposed technique will embed a watermark in the frames of the video. The proposed scheme is applied to the frame on high frequency sub bands. Various attacks have been applied to watermarked video and input video to check robustness of the proposed scheme.

Chirag Sharma

Papers

A Secured Frame Selection Based Video Watermarking Technique to Address Quality Loss of Data: Combining Graph Based Transform, Singular Valued Decomposition, and Hyperchaotic Encryption

A Novel Optimized Graph-Based Transform Watermarking Technique to Address Security Issues in Real-Time Application

A Robust Image Encrypted Watermarking Technique for Neurodegenerative Disorder Diagnosis and Its Applications.

Investigation of Smart Material Actuators & Aerodynamic optimization of Morphing Wing

Efficient Video Watermarking Technique for Quality Loss of Data