Comparisons of the Microstructure and Magnetic Properties of Anisotropic NdFeB Magnets Prepared by Hot Pressing and Spark Plasma Sintering

Journal of Superconductivity and Novel Magnetism - NdFeB hot-pressed and hot-deformed magnets were prepared by hot-pressed (HP) sintering and spark plasma sintering (SPS). The effects of sintering...     

Magnetic Properties and Microstructural Modifications of Sm-Co-Hf Alloy Ribbons by B Addition

Journal of Superconductivity and Novel Magnetism - Microstructure optimization is highly desirable for improving the magnetic properties of permanent magnetic materials. To optimize the...     

An Efficient Digital Confidentiality Scheme Based on Commutative Chaotic Polynomial

Multimedia Tools and Applications - One of the most critical aspects of this technologically progressive era is the propagation of information through an unsecured communication channel. The...     

A Machine Learning-Assisted Approach to a Rapid and Reliable Screening for Mechanically Stable Perovskite-Based Materials

The present work is designed to discover new perovskite-based materials, which are expected to show high mechanical stability during their applications, using machine learning (ML) techniques, and based on the Pugh's criterion for distinguishing brittle and ductile behaviors. For this purpose, ML models to predict the moduli of materials, bulk (B) and shear (G), are built using their crystal structure and composition information. The ML process is initiated with the information of 5663 compounds, including composition, crystal structure and moduli, as listed in AFLOW database. Following a procedure of data characteristics, feature generation, feature processing, training, and testing, the ML models are constructed with acceptable accuracy (tenfold cross-validation R² score of 0.90 and 0.89 for B and G, respectively). The validation process of the models, which is conducted using the corresponding density functional theory calculations, reveals that these models are reliable to be employed in a large-scale screening process. Indeed, the B- and G-based ML models are incorporated in a screening process, and this is also conjugated with other screening criterions, to find out thermodynamically stable and formable perovskite-based materials with improved mechanical performance.     

Engineered Cobalt Single-Atoms@BiFeO3 Heteronanostructures for Highly Efficient Solar Water Oxidation

Efficient charge–carrier separation and their utilization are the key factors in overcoming sluggish four-electron reaction kinetics involved in photocatalytic oxygen evolution. Here, a novel study demonstrates the significance of Na₂S₂O₈ as a sacrificial agent in comparison to AgNO₃. Resultantly, BiFeO₃ (BFO) and titanium doped-oxygen deficient BiFeO₃ (Ti-BFO-R) nanostructures achieve ≈64 and 44.5 times higher O₂ evolution in the presence of Na₂S₂O₈ compared to AgNO₃ as a sacrificial agent, respectively. Furthermore, the presence of Co single atoms (Co-SAs) deposited via immersion method on BFO and Ti-BFO-R nanostructures led to achieving outstanding O₂ evolution at a rate of 16.11 and 23.89 mmol g⁻¹ h⁻¹, respectively, which is 153 and 227.5 times higher compared to BFO (in the presence of AgNO₃), the highest O₂ evolution observed for BFO-based materials to date. The successful deposition of Co-SAs is confirmed by aberration-corrected high-angle annular dark-field scanning transmission electron microscopy (AC HAADF-STEM) and X-ray absorption near-edge structure (XANES). The charge transfer investigations confirm the significance of Co-SAs on BFO-based photocatalysts for improved charge–carrier separation, transport, and utilization. This novel study validates the excellent role of Na₂S₂O₈ as a sacrificial agent and Co-SAs as a cocatalyst for BFO-based nanostructures for efficient O₂ evolution.     

Designing Pair of Nonlinear Components of a Block Cipher over Gaussian Integers

In block ciphers, the nonlinear components, also known as substitution boxes (S-boxes), are used with the purpose of inducing confusion in cryptosystems. For the last decade, most of the work on designing S-boxes over the points of elliptic curves has been published. The main purpose of these studies is to hide data and improve the security levels of crypto algorithms. In this work, we design pair of nonlinear components of a block cipher over the residue class of Gaussian integers (GI). The fascinating features of this structure provide S-boxes pair at a time by fixing three parameters. But the prime field dependent on the Elliptic curve (EC) provides one S-box at a time by fixing three parameters and . The newly designed pair of S-boxes are assessed by various tests like nonlinearity, bit independence criterion, strict avalanche criterion, linear approximation probability, and differential approximation probability.     

Enhanced dynamic credential generation scheme for protection of user identity in mobile-cloud computing

To improve the resource limitation of mobile devices, mobile users may utilize cloud-computational and storage services. Although the utilization of the cloud services improves the processing and storage capacity of mobile devices, the migration of confidential information on untrusted cloud raises security and privacy issues. Considering the security of mobile-cloud-computing subscribers’ information, a mechanism to authenticate legitimate mobile users in the cloud environment is sought. Usually, the mobile users are authenticated in the cloud environment through digital credential methods, such as password. Once the users’ credential information theft occurs, the adversary can use the hacked information for impersonating the mobile user later on. The alarming situation is that the mobile user is unaware about adversary’s malicious activities. In this paper, a light-weight security scheme is proposed for mobile user in cloud environment to protect the mobile user’s identity with dynamic credentials. The proposed scheme offloads the frequently occurring dynamic credential generation operations on a trusted entity to keep minimum processing burden on the mobile device. To enhance the security and reliability of the scheme, the credential information is updated frequently on the basis of mobile-cloud packets exchange. Furthermore, the proposed scheme is compared with the existing scheme on the basis of performance metrics i.e. turnaround time and energy consumption. The experimental results for the proposed scheme showed significant improvement in turnaround time and energy consumption as compared to the existing scheme.     

Minimum redundancy maximum relevance (mRMR) based feature selection from endoscopic images for automatic gastrointestinal polyp detection

Multimedia Tools and Applications - In this paper, a computer based system has been proposed as a support to gastrointestinal polyp detection. It can detect and classify gastrointestinal polyps...     

A new nonparametric double exponentially weighted moving average control chart

There are many practical situations where the underlying distribution of the quality characteristic either deviates from normality or it is unknown. In such cases, practitioners often make use of the nonparametric control charts. In this paper, a new nonparametric double exponentially weighted moving average control chart on the basis of the signed-rank statistic is proposed for monitoring the process location. Monte Carlo simulations are carried out to obtain the run length characteristics of the proposed chart. The performance comparison of the proposed chart with the existing parametric and nonparametric control charts is made by using various performance metrics of the run length distribution. The comparison showed the superiority of the suggested chart over its existing parametric and nonparametric counterparts. An illustrative example for the practical implementation of the proposed chart is also provided by using the industrial data set.     

A Coordinated Navigation Strategy for Multi-Robots to Capture a Target Moving with Unknown Speed

The paper proposes an algorithm for multi-robot coordination and navigation in order to intercept a target at a long distance. For this purpose, a limit cycle based algorithm using a neural oscillator with phase differences is proposed. The state of target is unknown, under the assumption that it is stationary or in motion with constant unknown speed along a straight line. Using the proposed algorithm, a group of robots is intended to move towards the target in such a way that the robots surround it. While moving to the target, self-collision between the robots is avoided. Moreover, a collision avoidance with static obstacles as well as dynamic target is realized. The robots reach the target at a desired distance, keeping uniformly distributed angles around the target. The algorithm is further extended so that a static interception point for the target can be estimated in place of pursuing a dynamic target, which is referred to as a virtual target in this paper. In other words, the robots move towards the virtual target instead of the actual target. The robots ultimately encircle the actual target when they arrive at the virtual target. The effectiveness of the proposed method is verified through simulation results.