9,966 Results Found

In this article, we analyze the emergence of a global security norm of the COVID-19 epidemic as a threat to international security. This crisis is one of the gravest crises that humanity has experienced since the end of World War II in terms of the n...

In the presented article, we define the R-norm entropy and the conditional R-norm entropy of partitions of a given fuzzy probability space and study the properties of the suggested entropy measures. In addition, we introduce the concept of R-norm div...

This study employs the notions of t-norms and t-co-norms to define a group of $\mathcal{T}$-neutrosophic sub-groups and normal $\mathcal{T}$-neutrosophic subgroups. Furthermore, the different properties of these sub-groups have been investigated. After that, the t-norm and...

In compressed sensing, it is believed that the L₀ norm minimization is the best way to enforce a sparse solution. However, the L₀ norm is difficult to implement in a gradient-based iterative image reconstruction algorithm. The total variation (TV) no...

In this article, we explain and demonstrate how to model norm scores with the cNORM package in R. This package is designed specifically to determine norm scores when the latent ability to be measured covaries with age or other explanatory variables s...

Social norms have traditionally been difficult to quantify. In any particular society, their sheer number and complex interdependencies often limit a system-level analysis. One exception is that of the network of norms that sustain the online Wikiped...

We formally explore the idea that punishment of norm-breakers may be a vehicle for the older generation to teach youngsters about social norms. We show that this signaling role provides sufficient incentives to sustain costly punishing behavior. Peop...

In this article we highlight and discuss how norm-challenging pedagogy in music education can be encouraged and executed from three different angles. We primarily focus on activities such as democratic learning situations for pupils and teachers, to...

The Least Absolute Shrinkage and Selection Operator (LASSO) regression technique has proven to be a valuable tool for fitting and reducing linear models. The trend of applying LASSO to compositional data is growing, thereby expanding its applicabilit...

The Ulam stability of various equations (e.g., differential, difference, integral, and functional) concerns the following issue: how much does an approximate solution of an equation differ from its exact solutions? This paper presents methods that al...

We propose a framework that integrates norm entrepreneurship from human society into the dynamics of an agent society. Most work in agent coordination in a distributed environment studies norms that are provided to agents as part of their specificati...

Linguistic interval-valued intuitionistic fuzzy sets, as an extension of interval-valued intuitionistic fuzzy sets, have strong practical value in the management of complex uncertainty system with qualitative evaluation information. This study focuse...

In this paper, we introduce mixed-norm amalgam spaces ${(L^{\overrightarrow{p}},L^{\overrightarrow{s}})}^{\alpha }\left({\mathbb{R}}^n\right)$ and prove the boundedness of maximal function. Then, the dilation argument obtains the necessary and sufficient conditions of fractional integral operators’ bo...

The hyperspace consists of all subsets of a vector space. Owing to a lack of additive inverse elements, the hyperspace cannot form a vector space. In this paper, we shall consider a so-called informal norm to the hyperspace in which the axioms regard...

In this paper, we explore the least-norm solution to the classical matrix equation $AXB=C$ over the dual quaternion algebra, where A, B, and C are given matrices, while X remains the unknown matrix. We begin by transforming the definition of the Froben...

Low-rank tensor recovery has attracted much attention among various tensor recovery approaches. A tensor rank has several definitions, unlike the matrix rank—e.g., the CP rank and the Tucker rank. Many low-rank tensor recovery methods are focused on...

International norms do not diffuse linearly; they are localized, adapted and contested at every turn. Foster care systems have been enthusiastically promoted by international organizations to serve the best interests of children. This study explores...

We make a detailed study of norm retrieval. We give several classification theorems for norm retrieval and give a large number of examples to go with the theory. One consequence is a new result about Parseval frames: If a Parseval frame is divided in...

Norms have been effectively utilized to facilitate smooth interactions among agents. Norms are usually the global data that agents cannot directly access in complex environments; instead, norms can only be indirectly accessed by agents via maintainin...

It is the case that, in certain applications of fuzzy graphs, a t-norm, instead of a minimum, is more suitable. This requires the development of a new theory of fuzzy graphs involving an arbitrary t-norm in the basic definition of a fuzzy graph. Ther...

In this study, we obtain the ${\ell }_p$-norms of six classes of operators that commute with the infinite Hilbert operators.

Recent research in the US shows the potential of providing information about minority norms that are increasing on positively influencing interest and engagement in desired behaviours. Although these are promising findings, there is little published...

More recently, the ability of the coprime array to yield large array apertures and high degrees of freedom in comparison with the uniform linear array (ULA) has drawn an enormous amount of attention. In light of this, we propose a low-rank matrix com...

Setting up a contest is a popular means to promote pro-environmental behaviors. Yet, research on contest-based interventions is scarce while norm-based interventions have gained much attention. In two field experiments, we randomly assigned 79 apartm...

In this paper, we present some important approximation properties of Chebyshev polynomials in the Legendre norm. We mainly discuss the Chebyshev interpolation operator at the Chebyshev–Gauss–Lobatto points. The cases of single domain and...

We introduce a new tensor norm ( $\sigma$ -tensor norm) and show that it is associated with the ideal of $\sigma$ -nuclear operators. In this paper, we investigate the ideal of $\sigma$ -nuclear operators and the $\sigma$ -tensor norm.

The aim of this paper is to investigate when a linear normed space is an inner product space. Several conditions in a linear normed space are formulated with the help of inequalities. Some of them are from the literature and others are new. We prove...

Consumer attitudes toward consuming and buying locally produced food are well studied. By contrast, the topic of consumer preferences for local food, with a special emphasis on the role of norms, still lacks empirical evidence. To study the influence...

Projective Norms are a class of tensor norms that map from the input to the output spaces. These norms are useful for providing a measure of entanglement. Calculating the projective norms is an NP-hard problem, which creates challenges in computing d...

Recently, with the popularization of intelligent terminals, research on intelligent big data has been paid more attention. Among these data, a kind of intelligent big data with functional characteristics, which is called functional data, has attracte...

How can we curb the current norm of unsustainable levels of meat consumption? Research on dynamic norms finds that learning that others are starting to eat less meat can inspire people to follow suit. Across four field experiments, we test efforts to...

In this paper, we introduce and study the concept of the ingredient modulus of smoothness in component form in $L_{\overrightarrow{p}}\left({\mathbb{R}}^d\right)$ and a kind of mixed-norm Sobolev space. We obtain some new properties, inequalities, and auxiliary results in mixed-norm space...

Compressive sensing theory has attracted widespread attention in recent years and sparse signal reconstruction has been widely used in signal processing and communication. This paper addresses the problem of sparse signal recovery especially with non...

In this paper, we propose an algorithm based on the mathematical p-norm which has been applied to improve both the traction power and the trajectory smoothness of joystick-controlled two-wheeled vehicles. This algorithm can theoretically supply 100%...

The stability of deep neural networks during training is related to the structural symmetry between gradient dynamics and parameter updates. Existing Adam-type optimizers are prone to breaking this dynamic symmetry when the gradient scale changes dra...

In this paper, we introduce the property $(h)$ on Banach lattices and present its characterization in terms of disjoint sequences. Then, an example is given to show that an order-to-norm continuous operator may not be $\sigma$-order continuous. Suppose...

We prove the existence and uniqueness of the solution of the problem of the minimum norm function ${\parallel ·\parallel }_{\infty }$ with a given set of initial coefficients of the trigonometric Fourier series $c_j$ , $j=0,1,\dots ,2n$...

Assertion is the use of declarative sentences to convey information, which necessitates meeting the “justified-belief norm” as a prerequisite. However, a significant amount of misinformation that did not meet these conditions was spread d...

The aim of this article was to provide improved estimates for the $(\alpha ,\beta )$-norm of a bounded linear operator. In particular, our results enabled the determination of new upper bounds involving both the Berezin number and the Berezin norm of b...

We focus on the relationships among some consistency axioms in the framework of fuzzy choice functions. In order to help disclose the role of the t-norm in existing analyses, we start to study the situation that arises when we replace the standard t-...

The goal of sparse linear hyperspectral unmixing is to determine a scanty subset of spectral signatures of materials contained in each mixed pixel and to estimate their fractional abundances. This turns into an...

Blind image deblurring is a well-known ill-posed inverse problem in the computer vision field. To make the problem well-posed, this paper puts forward a plain but effective regularization method, namely spectral norm regularization (SN), which can be...

In this article, we introduce the ∗-fuzzy ${\left(L^{+}\right)}^p$ spaces for $1\le p<\infty$ on triangular norm-based ∗-fuzzy measure spaces and show that they are complete ∗-fuzzy normed space and investigate some properties in these space. Next, we prove Chebyshev’s inequa...

The l₂-norm minimization is a common means for the 3D inversion of gravity data. The unconstrained l₂-norm inversion will produce a smooth solution, which contains redundant structures and artifacts. Positivity-constrained l₂-norm inversion can elimi...

Recently, the sparse representation based classification methods have received particular attention in the classification of hyperspectral imagery. However, current sparse representation based classification models have not considered all the test pi...

Background: An innovative approach of Norm Balance is proposed under the Theory of Planned Behavior (TPB). In this approach, the measurement score of subjective norm is weighted by the relative importance of others, and the measurement score of self-...

In the reconstruction of sparse signals in compressed sensing, the reconstruction algorithm is required to reconstruct the sparsest form of signal. In order to minimize the objective function, minimal norm algorithm and greedy pursuit algorithm are m...

In the Compressed Sensing (CS) framework, the underdetermined system of linear equation (USLE) can have infinitely many possible solutions. However, we intend to find the sparsest possible solution, which is $l_0$-norm minimization. However, finding an...

Let $\overrightarrow{p}\in {(0,\infty )}^n$ be an exponent vector and A be a general expansive matrix on ${\mathbb{R}}^n$. Let $H_A^{\overrightarrow{p}}\left({\mathbb{R}}^n\right)$ be the anisotropic mixed-norm Hardy spaces associated with A defined via the non-tangential grand maximal function. In this article, using the known atomic ch...

In this paper, we present a Mirsky-type unitarily invariant norm inequality for dual quaternion matrices, which can be regarded as a singular value perturbation theorem for dual quaternion matrices. By using this unitarily invariant norm inequality,...