Spin-Cherenkov effect in a magnetic nanostrip with interfacial Dzyaloshinskii-Moriya interaction

Spin-Cherenkov effect enables strong excitations of spin waves (SWs) with nonlinear wave dispersions. The Dzyaloshinskii-Moriya interaction (DMI) results in anisotropy and nonreciprocity of SWs propagation. In this work, we study the effect of the interfacial DMI on SW Cherenkov excitations in permalloy thin-film strips within the framework of micromagnetism. By performing micromagnetic simulations, it is shown that coherent SWs are excited when the velocity of a moving magnetic source exceeds the propagation velocity of the SWs. Moreover, the threshold velocity of the moving magnetic source with finite DMI can be reduced compared to the case of zero DMI. It thereby provides a promising route towards efficient SW generation and propagation, with potential applications in spintronic and magnonic devices.Comment: 6 pages, 5 figures. To be published in Scientific Report

Magnetic Skyrmion Transport in a Nanotrack With Spatially Varying Damping and Non-adiabatic Torque

Reliable transport of magnetic skyrmions is required for any future skyrmion-based information processing devices. Here we present a micromagnetic study of the in-plane current-driven motion of a skyrmion in a ferromagnetic nanotrack with spatially sinusoidally varying Gilbert damping and/or non-adiabatic spin-transfer torque coefficients. It is found that the skyrmion moves in a sinusoidal pattern as a result of the spatially varying Gilbert damping and/or non-adiabatic spin-transfer torque in the nanotrack, which could prevent the destruction of the skyrmion caused by the skyrmion Hall effect. The results provide a guide for designing and developing the skyrmion transport channel in skyrmion-based spintronic applications.Comment: 5 pages, 6 figure

Supervised cross-modal factor analysis for multiple modal data classification

In this paper we study the problem of learning from multiple modal data for purpose of document classification. In this problem, each document is composed two different modals of data, i.e., an image and a text. Cross-modal factor analysis (CFA) has been proposed to project the two different modals of data to a shared data space, so that the classification of a image or a text can be performed directly in this space. A disadvantage of CFA is that it has ignored the supervision information. In this paper, we improve CFA by incorporating the supervision information to represent and classify both image and text modals of documents. We project both image and text data to a shared data space by factor analysis, and then train a class label predictor in the shared space to use the class label information. The factor analysis parameter and the predictor parameter are learned jointly by solving one single objective function. With this objective function, we minimize the distance between the projections of image and text of the same document, and the classification error of the projection measured by hinge loss function. The objective function is optimized by an alternate optimization strategy in an iterative algorithm. Experiments in two different multiple modal document data sets show the advantage of the proposed algorithm over other CFA methods

A New Transparent and Secured Transmission Routing Method for Blockchain Data in Management Systems

A significant quantity of information, particularly financial data, has now been growing in accordance with the advancement of information technologies. Due to the prevalence of fraud, it is impossible to identify the data sources for corporate financial data and the applicable employees. There are substantial issues with nonstandard behavior and a lack of critical financial data of these firms, as evidenced by the fact that the majority of employees are not capable of perform appropriate queries on the needed financial statements. It has consistently created financial information management for companies more difficult, posed a risk to the entire company's ecosystem, and hurt the interests of several parties, among other concerns, because many analogous concerns were not satisfactorily addressed. Blockchain has garnered a great deal of attention recently, and Crypto currency and other crypto currencies have gained popularity as a result. This is because of the characteristics of blockchain, like centralized control, confidentiality, truthfulness, and lack of courage, which make data difficult to predict and tamper with. According to current implementation and exploration, blockchain has emerged as a novel solution to issues relating to company financial information management since these features are connected to the data storage privacy and data transfer speed required by this type of management. In order to construct a transparent and secured transmission method for blockchain data, the study deployed blockchain for managing the financial management framework and information processing strategy. In terms of security level, throughput, run time, and scalability, the suggested Blockchain solution is contrasted with existing approaches