In the COVID-19 era, people face situations that they have never experienced before, which alerted importance of ESG. Investors also consider ESG indexes as an essential factor for their investments, and some research yielded return on sustainable funds is more significant than non-sustainable ones. Nevertheless, a deficiency in exists about analyzing through artificial intelligence algorithms due to adversity collecting ESG-related datasets. Therefore, this paper suggests integrated AI...

In complex dynamical networks, the resilience of individual nodes against perturbation and their influence on network dynamics are great interest have been actively investigated. We consider situations where coupling separable, which arise in certain classes processes including epidemic spreading, population dynamics, regulatory processes, derive algebraic scaling relations characterizing nodal influence. Utilizing synthetic empirical networks different topologies, we numerically verify...

Linear regression without correspondences is the problem of performing a linear fit to dataset for which between independent samples and observations are unknown. Such naturally arises in diverse domains such as computer vision, data mining, communications biology. In its simplest form, it tantamount solving system equations, entries right hand side vector have been permuted. This type corruption renders task considerably harder, even absence other corruptions, noise, outliers or missing...

Massive access is a critical design challenge of Internet Things (IoT) networks. In this paper, we consider the grant-free uplink transmission an IoT network with multiple-antenna base station (BS) and large number single-antenna devices. Taking into account sporadic nature devices, formulate joint activity detection channel estimation (JADCE) problem as group-sparse matrix problem. This can be solved by applying existing compressed sensing techniques, which however either suffer from high...

Abstract Accurately capturing the stress distribution within complex structures is crucial for reliability and performance, particularly in high-stress environments. Traditional finite element analysis methods require a fine mesh to achieve highly accurate fields, which computationally expensive time-consuming. This paper presents novel neural network-based approach that learns mapping between global displacement values on coarse elements local von Mises elements. By training network dataset...

Abstract Key message The pepper mutants (‘221-2-1a’ and ‘1559-1-2h’) with very low pungency were genetically characterized. Pun4 locus, responsible for the reduced of mutant fruits, was localized to a 208 Mb region on chromosome 6. DEMF06G16460, encoding 3-ketoacyl-CoA synthase, proposed as strong candidate gene based genetic analyses bulked segregants, DEG, expression analyses. Capsaicinoids are unique alkaloids present in ( Capsicum spp.), synthesized through condensation by-products from...

Towards low-latency communication for short-packet transmission, this paper tackles the problem of shuffled linear regression large-scale wireless sensor networks with header-free by using results from algebraic geometry as well an alternating optimization scheme. The is to solve a system entries right hand side vector. However, solving requires high computational cost. key idea our approach eliminate structure via symmetric polynomials, which leads polynomial equations. Considering one...

Pepper (Capsicum spp.) is a vegetable and spice crop in the Solanaceae family with many nutritional benefits for human health. During several decades, horticultural traits, including disease resistance, yield, fruit quality, have been improved through conventional breeding methods. Nevertheless, cultivar development time-consuming process because of long generation time pepper. Recently, speed has introduced as solution shorting cycle long-day or day-neutral field crops, but there only few...

We present a linear model with an unknown permutation matrix for header-free communication in massive Internet-of-Things (IoT) networks, thereby supporting low-latency communication. Besides the application, permuted also has many applications matching and correspondence estimation problems. To solve this system, key idea is to convert it into system of polynomial equations via power sum symmetric polynomials. In our proposed method, specific assumptions (e.g., low-rankness sparsity) about...

Appropriate weight initialization settings, along with the ReLU activation function, have become cornerstones of modern deep learning, enabling training and deployment highly effective efficient neural network models across diverse areas artificial intelligence. The problem "dying ReLU," where neurons inactive yield zero output, presents a significant challenge in networks function. Theoretical research various methods been introduced to address problem. However, even these research, remains...

In this paper, we propose a generalized notion of distance function, called $g$-metric. The $g$-metric with degree $n$ is $n+1$ points, generalizing the ordinary between two points and $G$-metric three points. Indeed, it shown that 1 (resp. 2) equivalent to metric $G$-metric). Fundamental properties several examples for are also given. Moreover, topological on space including convergence sequences continuity mappings studied. Finally, generalize some well-known fixed point theorems Banach...

A proper initial guess is critical for implementing Newton's iteration to approximate an exact solution of a nonlinear differential equation like the Navier-Stokes equations or magnetohydrodynamic equations. In this article, we will provide theoretical criteria way choosing required approximating equation.

High-radix topologies in large-scale networks provide low network diameter and high path diversity, but the idle power from high-speed links results energy inefficiency, especially at traffic load. In this work, we exploit diversity non-minimal adaptive routing high-radix to consolidate a smaller number of enable more channels be power-gated. particular, propose TCEP (Traffic Consolidation for Energy-Proportional networks), distributed, proactive management mechanism that achieves...

It is well expected that a collection of smart objects such as IoT devices dynamically form an edge cloud allowing acquiring, storing, communicating, and processing information done at the network. Edge workers (i.e. devices) usually have service specific characteristics while legacy are more computing oriented. However, existing cloudlet architectures continue to take their allocation policy centered around computation resource virtualization without considering clouds. In order provide QoS...

Due to a rapid development in the field of information and communication, technologies yielded novel changes both individual organizational operations. Therefore, accessibility became easier more convenient than before, malicious approaches such as hacking or spying aimed at various kept increasing. With aim preventing approaches, classification detecting traffic are vital. our research utilized deep learning machine models for better classification. The given dataset consists normal data...

Abstract Moment methods to reconstruct images from their Radon transforms are both natural and useful. They can be used suppress noise or other spurious effects lead highly efficient reconstructions relatively few projections. We establish a modified transform (MRT) via convolution with mollifier obtain its inversion formula. The relationship of the moments is derived, MRT data provide uniform approximation original density function. reconstruction algorithm implemented, simple function...

The von Neumann graph entropy (VNGE) can be used as a measure of complexity, which the information divergence and distance between graphs. However, computing VNGE is extensively demanding for large-scale graph. We propose novel quadratic approximations fast VNGE. Various inequalities error exact are found. Our methods reduce cubic complexity to linear complexity. Computational simulations on random models various real network datasets demonstrate superior performance.