Using blockchain technology to handle the entire chain of digital copyrights in digital libraries not only helps to improve the economy, validity, and fairness of the libraries’ digital resource offerings, but it also increases the revenue of digital copyright subjects in a sustainable manner. In this work, a decentralized, secure, and traceable digital copyright transaction system is designed and implemented using blockchain technology. The system serves creators, administrators, and subscribers through its user layer, business model layer, and Fabric network layer. To guarantee the accuracy and integrity of transaction data, smart contracts are used for the registration of digital works, transaction supervision, and smart contract execution. Fabric Composer is used in the development of the system and offers good scalability. The system still has issues with privacy protection, increasing performance, and complying with laws and regulations. It is anticipated that the digital copyright transaction system will advance in the area of digital copyright protection as blockchain technology develops.

As computer and mechanical automation technologies advance, machine vision-based non-destructive testing technology finds use in a multitude of domains. Non-destructive testing technologies can be used on apple sorting equipment to decrease apple damage while simultaneously increasing sorting efficiency. As a result, the apple sorting machine’s image identification system now incorporates machine vision technology. The automatic classification of apple grades is accomplished by gathering, processing, extracting, and computing the contour features of apple photographs using preset sorting levels. The automatic control system then sorts apples of different grades to designated locations, thus achieving the automation of apple sorting. Tests were run on the sorting machine’s image recognition system to confirm the solution’s viability. The outcomes demonstrate that the sorting machine can effectively classify fruit automatically based on their perimeter, which is important for fruit sorting automation.

The gearbox gearbox transmission system, which is the foundation of a new energy vehicle, is responsible for the crucial duty of power transmission. In reality, the reducer gearbox system is the primary source of noise inside cars because of the design of the system, mistakes made during manufacturing and assembly, and gear engagement impulses. The research target is the second-stage retarder gearbox system of a new energy vehicle. A three-dimensional model of the retarder gearbox system is created using the Romax software.Static and dynamic analyses were carried out in Romax software based on the five typical conditions of start, acceleration, equal speed, deceleration, and stop in order to derive performance data such as maximum contact and bending stresses of the gears, single-position length load distribution, gearbox error, etc. In the NVH analysis, the system’s vibration acceleration was ascertained using the findings of the gearbox error analysis. In order to provide comparative data for vibration and noise reduction of gear modification, the comparative study analyses the data output results under various working conditions and analyses the relationship between gear engagement force and gear vibration.

Let \(G\) be a connected graph. A pebbling move is defined as taking two pebbles from one vertex and the placing one pebble to an adjacent vertex and throwing away the another pebble. A dominating set \(D\) of a graph \(G=(V,E)\) is a non-split dominating set if the induced graph \(\) is connected. The Non-split Domination Cover(NDC) pebbling number, \(\psi_{ns}(G)\), of a graph $G$ is the minimum of pebbles that must be placed on \(V(G)\) such that after a sequence of pebbling moves, the set of vertices with a pebble forms a non-split dominating set of \(G\), regardless of the initial configuration of pebbles. We discuss some basic results and determine \(\psi_{ns}\) for some families of standard graphs.

Graph theory is playing vital role in almost every field of our routine life. You make a conference call with your friends by using vertices (yourself and your friends) and edges (network connection). You construct a printed grid floor with different faces in your home by the help of graph theory. Authors in this study are using labelling of graphs and applying it in choosing best friends around you. The helping graphs in this article will be plane graphs which will be labelling under \(\Bbbk-\)labelling \(\mathrm{M}\) of kind \((\lambda,\mu,\nu)\). This study can be applied in many fields of everyday life.

A complex Hadamard matrix is a matrix \(H_n \in {\{\omega^i | 1\leq i \leq m \}}^{n\times n}\) of order \(n\), where \(\omega\) is a primitive \(m^{th}\) root of unity, that satisfies \(H_n{H}^{*}_n=n{I_{n}}\), where \(H_n^{*}\) denotes the complex conjugate transpose of \(H_n\). We show that the Scarpis technique for constructing classic Hadamard matrices generalizes to Butson-type complex Hadamard matrices.

With the rapid development of the country’s economy, politics, and culture, China has swiftly ascended to the ranks of global powers. Its participation in international organizations, including the WTO, has significantly bolstered its global standing and diplomatic ties, making it an indispensable player in international politics. Meanwhile, domestically, China has implemented numerous initiatives aimed at improving the lives of its citizens, such as anti-corruption campaigns, efforts to uphold integrity, crackdowns on criminal organizations, and poverty alleviation programs. As a result, the well-being of the populace has seen a steady increase. Furthermore, China has embarked on a new era of education characterized by its unique attributes, with civic education platforms experiencing comprehensive development. This paper examines these developments through text and knowledge mapping, assessing the efficacy of this approach within the framework of course ideology and politics.

This work suggests predicting student performance using a Gaussian process model classification in order to address the issue that the prediction approach is too complex and the data set involved is too huge in the process of predicting students’ performance. In order to prevent overfitting, a sample set consisting of the three typical test outcomes from 465 undergraduate College English students is divided into training and test sets. The cross-validation technique is used in this study. According to the findings, Gaussian process model classification can accurately predict 92\% of the test set with a prediction model, and it can also forecast students’ final exam marks based on their typical quiz scores. Furthermore, it is discovered that the prediction accuracy increases with the sample set’s distance from the normal distribution; this prediction accuracy rises to 96\% when test scores with less than 60 points are taken out of the analysis.

Let \(\varepsilon_{0}\), \(\varepsilon_{1}\) be two linear homogenous equations, each with at least three variables and coefficients not all the same sign. Define the \(2\)-color off-diagonal Rado number \(R_2(\varepsilon_{0},\varepsilon_{1})\) to be the smallest \(N\) such that for any 2-coloring of \([1,N]\), it must admit a monochromatic solution to \(\varepsilon_{0}\) of the first color or a monochromatic solution to \(\varepsilon_{1}\) of the second color. Mayers and Robertson gave the exact \(2\)-color off-diagonal Rado numbers \(R_2(x+qy=z,x+sy=z). \) Xia and Yao established the formulas for \(R_2(3x+3y=z,3x+qy=z) \) and \(R_2(2x+3y=z,2x+2qy=z) \). In this paper, we determine the exact numbers \(R_2(2x+qy=2z,2x+sy=2z)\), where \(q, s\) are odd integers with \(q>s\geq1\).

Let \(X\) be bipartite mixed graph and for a unit complex number \(\alpha\), \(H_\alpha\) be its \(\alpha\)-hermitian adjacency matrix. If \(X\) has a unique perfect matching, then \(H_\alpha\) has a hermitian inverse \(H_\alpha^{-1}\). In this paper we give a full description of the entries of \(H_\alpha^{-1}\) in terms of the paths between the vertices. Furthermore, for \(\alpha\) equals the primitive third root of unity \(\gamma\) and for a unicyclic bipartite graph \(X\) with unique perfect matching, we characterize when \(H_\gamma^{-1}\) is \(\pm 1\) diagonally similar to \(\gamma\)-hermitian adjacency matrix of a mixed graph. Through our work, we have provided a new construction for the \(\pm 1\) diagonal matrix.