2022 July-2 - 185 articles
According to the World Energy Investment 2018 report, the global annual investment in renewable energy exceeded USD 200 billion for eight consecutive years until 2017. In this paper, a deep-learning-based time-series prediction method, namely a gated...
The paper presents a new hydrodynamical code, OMPEGAS, for the 3D simulation of astrophysical flows on shared memory architectures. It provides a numerical method for solving the three-dimensional equations of the gravitational hydrodynamics based on...
Missing link prediction technology (MLP) is always a hot research area in the field of complex networks, and it has been extensively utilized in UAV swarm network reconstruction recently. UAV swarm is an artificial network with strong randomness, in...
The authenticated key exchange (AKE) protocol can ensure secure communication between a client and a server in the electricity transaction of the Energy Internet of things (EIoT). Park proposed a two-factor authentication protocol 2PAKEP, whose compu...
A great challenge for intelligent transportation systems (ITS) is missing traffic data. Traffic data are input from various transportation applications. In the past few decades, several methods for traffic temporal data imputation have been proposed....
Nowadays, the trend of countries and their electrical sectors moves towards the inclusion of renewable distributed generators (RDGs) to diminish the use of the fossil fuel based DGs. The solar photovoltaic-based DG (PV-DG) is widely used as a clean a...
This study investigates the optimization of an integrated production–inventory system that consists of an original equipment manufacturer (OEM) supplier and an OEM brand company. The cognitive and skill learning effect, imperfect quality, and f...
We present an efficient and accurate computational algorithm for reconstructing a local volatility surface from given market option prices. The local volatility surface is dependent on the values of both the time and underlying asset. We use the gene...
The computerization of many everyday tasks generates vast amounts of data, and this has lead to the development of machine-learning methods which are capable of extracting useful information from the data so that the data can be used in future decisi...
We present a pursuit differential game for an infinite system of two-block differential equations in Hilbert space
In the context of a shortage of labor and objective patterns of the development of means of production in a number of sectors of agriculture, farmers are increasingly using robotics. Despite the presence of significant positive economic effects, the...
Masses are the early indicators of breast cancer, and distinguishing between benign and malignant masses is a challenging problem. Many machine learning- and deep learning-based methods have been proposed to distinguish benign masses from malignant o...
Data that have not been modeled cannot be correctly predicted. Under this assumption, this research studies how k-fold cross-validation can introduce dataset shift in regression problems. This fact implies data distributions in the training and test...
To provide a low-cost methodical way for inference-driven insight into the assessment of SDN operations, a behavioral study of key network parameters that predicate the proper functioning and performance of software-defined networks (SDNs) is present...
Eric Lord has observed: “In nature, helical structures arise when identical structural subunits combine sequentially, the orientational and translational relation between each unit and its predecessor remaining constant.” This paper prove...
In this paper, we assess sentiment and emotion regarding green energy through employing a social listening analysis on Twitter. Knowing the sentiment and attitude of the population is important because it will help to promote policies and actions tha...
Domain discrepancy is a key research problem in the field of deep domain adaptation. Two main strategies are used to reduce the discrepancy: the parametric method and the nonparametric method. Both methods have achieved good results in practical appl...
The present research paper consists of the study of an
This work objective is to generate an HJ-biplot representation for the content analysis obtained by latent Dirichlet assignment (LDA) of the headlines of three Spanish newspapers in their web versions referring to the topic of the pandemic caused by...
In this paper, we consider fully degenerate Daehee numbers and polynomials by using degenerate logarithm function. We investigate some properties of these numbers and polynomials. We also introduce higher-order multiple fully degenerate Daehee polyno...
Clustering algorithms and deep learning methods have been widely applied in the multimode process monitoring. However, for the process data with unknown mode, traditional clustering methods can hardly identify the number of modes automatically. Furth...
Heat exchangers are usually designed using a sophisticated process of trial-and-error to find proper values of unknown parameters which satisfy given requirements. Recently, the design of heat exchangers using evolutionary optimization algorithms has...
In recent years, reinforcement learning algorithms based on automatic curriculum learning have been increasingly applied to multi-agent system problems. However, in the sparse reward environment, the reinforcement learning agents get almost no feedba...
Scene graph generation is the basis of various computer vision applications, including image retrieval, visual question answering, and image captioning. Previous studies have relied on visual features or incorporated auxiliary information to predict...
In the paper, a new method was presented using queueing theory models in order to ensure an optimal production department size, optimized production costs and optimal provision. Queueing/waiting mathematical models represent the development matrix fo...
Betweenness centrality evaluates the importance of nodes and edges in networks and is one of the most pivotal indices in complex network analysis; for example, it is widely used in centrality ordering, failure cascading modeling, and path planning. E...
This paper is concerned with the output tracking control problem for random nonlinear systems with time-varying powers. A distinct feature of this paper is that we consider time-varying powers and the second-order moment process simultaneously, which...
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Distribution centers are quite important for logistics. In order to save costs, reduce energy consumption and deal with increasingly uncertain demand, it is necessary for distribution centers to select the location strategically. In this paper, a two...
I consider strategic-form games with transferable utility extended with a phase of negotiations before the actual play of the game, where players can exchange a series of alternating (turn-based) unilaterally binding offers to each other for incentiv...
In this paper, we would like to propose a (2+1)-dimensional fractional-order epidemic model with pulse jumps to describe the spread of the Omicron variant of COVID-19. The problem of identifying the involved parameters in the proposed model is reduce...
The Bessel–Struve kernel function defined in the unit disc is used in this study. The Bessel–Struve kernel functions are generalized in this article, and differential equations are derived. We found conditions under which the generalized...
With the rapid development and evolution of the Internet-of-Things (IoT) and big-data analysis technologies, faster and more accurate production data analysis and process capability evaluation models will bring industries closer to the goal of smart...
Aiming at providing a high-performance terrestrial network for edge computing in satellite networks, we experimentally demonstrate a high bandwidth and low latency decomposed optical computing architecture based on distributed Nanoseconds Optical Swi...
Computed tomography (CT) scans were performed on samples of an outburst-prone coal seam at different loading stages. The area and roundness of the CT images were used to quantify the degree of the coal macroscopic deformation under different loads. A...
In this work, we investigate the variant of the Internet Shopping Optimization Problem (ISHOP) that considers different item units. This variant is more challenging than the original problem. The original ISHOP is already known as a combinatorial NP-...
Problem: The leverage effect plays an important role in finance. However, the statistical test for the presence of the leverage effect is still lacking study. Approach: In this paper, by using high frequency data, we propose a novel procedure to test...
In recent years, the occurrence of cascading failures and blackouts arising from cyber intrusions in the underlying configuration of power systems has increasingly highlighted the need for effective power management that is able to handle this issue...
Much has been written on variable exponent spaces in recent years. Most of the literature deals with the normed space structure of such spaces. However, because of the variability of the exponent, the underlying modular structure of these spaces is r...
We consider a variant of group testing (GT) models called noisy threshold group testing (NTGT), in which when there is more than one defective sample in a pool, its test result is positive. We deal with a variant model of GT where, as in the diagnosi...
We investigate a nonparametric, varying coefficient regression approach for modeling and estimating the regression effects caused by two functionally correlated datasets. Due to modern biomedical technology to measure multiple patient features during...
Explaining all published articles on the typhoid disease transmission model was carried out. It has been conducted to understand how Salmonella is transmitted among humans and vectors with variation interventions to control the spread of the typhoid...
Laser powder bed fusion (LPBF) is an additive manufacturing technology which uses a heat source (laser) to sinter or fuse atomized powder particles together. A new layer of powder is spread over the previous layer using a roller, and then the laser p...
Consensus protocols are a fundamental part of any blockchain; although several protocols have been in operation for several years, they still have drawbacks. For instance, some may be susceptible to a 51% attack, also known as a majority attack, whic...
This paper considers what we propose to call multi-gear bandits, which are Markov decision processes modeling a generic dynamic and stochastic project fueled by a single resource and which admit multiple actions representing gears of operation natura...
Forecasting price changes is very important for the process of estimating and managing market risk in financial markets. Price changes in financial markets may also depend on non-market factors. Considering this situation, the study investigates the...
Numerous polynomial variations and their extensions have been explored extensively and found applications in a variety of research fields. The purpose of this research is to establish a unified class of Apostol–Genocchi polynomials based on pol...
The present paper explores the application of bootstrap methods in testing for serial dependence in observed driven Integer-AutoRegressive (models) considering Poisson arrivals (P-INAR). To this end, a new semiparametric and restricted bootstrap algo...
Fractals are already firmly rooted in modern science. Research continues on the fractal properties of objects in physics, chemistry, biology and many other scientific fields. Fractal graphs as a discrete representation are used to model and describe...
The evolution of some epidemics, such as influenza, demonstrates common patterns both in different regions and from year to year. On the contrary, epidemics such as the novel COVID-19 show quite heterogeneous dynamics and are extremely susceptible to...
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