The Internet of Things (IoT) paradigm is a predominant research domain for smart cities, smart villages, society, and industry 4.0. The introduction of Unmanned Aircraft Systems (UAS) in an ultra-low latency network with fog, dews, and edge computing gives the researcher ample scope to establish a decentralized architecture for ultra-high-speed message exchange between IoT devices. This work mainly

Based on nationwide aircraft performance and scheduling gathered from Variflight.com, the work evaluates how the identified factors, such as aircraft taxi-in and taxi-out time, airborne time, Origin–destination Pair Herfindahl–Hirschman Index (OD-Pair HHI), hub airport, and flight distance, coexisted in order to organize aviation scheduling more effectively and appropriately in the air transportation

This paper presents robust fixed-time controllers for nonlinear discrete-time systems with time-varying delay and uncertain parameters. The nonlinear function has the Lipschitz condition, and the uncertain parameters are time-varying. Firstly, by selecting an appropriate Lyapunov–Krasovskii functional, sufficient conditions are extracted to guarantee the fixed-time boundedness in the presence of uncertain

The price demand relation is a fundamental concept that models how price affects the sale of a product. It is critical to have an accurate estimate of its parameters, as it will impact the company's revenue. The learning has to be performed very efficiently using a small window of a few test points, because of the rapid changes in price demand parameters due to seasonality and fluctuations. However

Nowadays, use of various types of hybrid metaheuristic algorithms attracts the researchers to optimize the average profit or cost of an inventory system to avoid the local optimality due to high nonlinearity of the corresponding optimization problem. This paper deals with an application of binary tournament-based quantum-behaved particle swarm optimization algorithms on an imperfect production inventory

This paper explores the suitability of space fractional-order reaction–diffusion scenarios to model some emergent pattern formation in predator–prey models. Such fractional reaction–diffusion equations are obtained on the basis of a continuous-time random walk approach with spatial memory and local kinetic reaction. The classical space second-order derivative is changed by the fractional Laplacian

The estimation of the energy performance of residential buildings has gained importance because of the significant consumption of electricity in housing estate areas. For this aim, different approaches were utilized for robust and accurate prediction of the energy load in buildings. The use of different kind of construction materials, timely change in building parameters lead to imprecise and vague

In project management, agility concept has emerged for overcoming the limitations of traditional methodologies that are sequential and linear. An agile project contains planned processes as well as iterations. In global competitive areas, achieving agility in outsourcing processes enables the companies to cope with changes and dynamic issues. This paper introduces an integrated cognitive map-based

The current world faces a considerable traffic rate on roads due to the increase in various types of vehicles. It caused emergency vehicles to delay and increasing the patients' health risk factor. Internet of vehicle-based artificial neural network (IoV-ANN) has been proposed for effective health autonomous system in medical things. The proposed IoV-ANN provides a secure network to monitor and track

Presently, novel coronavirus outbreak 2019 (COVID-19) is a major threat to public health. Mathematical epidemic models can be utilized to forecast the course of an epidemic and cultivate approaches for controlling it. This paper utilizes the real data of spreading COVID-19 in Saudi Arabia for mathematical modeling and complex analyses. This paper introduces the Susceptible, Exposed, Infectious, Recovered

We introduce so-called consistent posets which are bounded posets with an antitone involution \('\) where the lower cones of \(x,x'\) and of \(y,y'\) coincide provided that x, y are different from 0, 1 and, moreover, if x, y are different from 0, then their lower cone is different from 0, too. We show that these posets can be represented by means of commutative meet-directoids with an antitone involution

Multi-criteria decision-making (MCDM) methods deeply assist decision-makers in evaluating and analyzing input data as accurately as possible in the area of safety and reliability. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) can be used to rank a set of alternatives based on the different types of criteria. However, this method still needs to be improved; fuzzy set

In this paper, the prioritized muirhead mean aggregation operations are used to constructing some bipolar neutrosophic fuzzy (BNF) operators, i.e., BNF prioritized muirhead mean weighted averaging, BNF prioritized muirhead mean ordered weighted averaging, BNF prioritized muirhead mean hybrid weighted averaging, BNF prioritized muirhead mean weighted geometric, BNF prioritized muirhead mean ordered

In recent decades, hybridization of superior attributes of few algorithms was proposed to aid in covering more areas of complex application as well as improves performance. Condition monitoring is a major component in predictive maintenance which monitors the condition and identifies significant changes in the machinery parameter to perform early detection and prevent equipment defects that could cause

The idempotent graph I(R) of a ring R is a graph with nontrivial idempotents of R as vertices, and two vertices are adjacent in I(R) if and only if their product is zero. In the present paper, we prove that idempotent graphs are weakly perfect. We characterize the rings whose idempotent graphs have connected complements. As an application, the idempotent graph of an abelian Rickart ring R is used to

The theory of \(\sigma -\oplus \)-measure is a basic tool in soft computing. There are no studies on cumulative distribution function in pseudo-analysis. In this paper, we first introduce pseudo-cumulative distribution function. Then, some examples of this class are studied. Also, we analyze a real data set for the daily humidity of Basel’s city in period of 1985/01/01 to 2018/11/11 by the proposed

The COVID-19 pandemic enforced nationwide lockdown, which has restricted human activities from March 24 to May 3, 2020, resulted in an improved air quality across India. The present research investigates the connection between COVID-19 pandemic-imposed lockdown and its relation to the present air quality in India; besides, relationship between climate variables and daily new affected cases of Coronavirus

This paper presents a data-driven machine learning approach of support vector regression (SVR) with genetic algorithm (GA) optimization approach called SVR-GA for predicting the shear strength capacity of medium- to ultra-high strength concrete beams with longitudinal reinforcement and vertical stirrups. One hundred and forty eight experimental samples collected with different geometric, material and

Various methods have been proposed to diagnose renal failure based on data mining and artificial intelligence techniques. The use of data mining approaches, renal failure could be predicted based on several features and risk factors that exacerbate the condition. At the same time, each is associated with issues such as complex computation and a long implementation period. Moreover, these methods have

Real-world applications now deal with enormous amounts of data, especially in the area of high dimensional features. In the present study, we provide an approach for the rough set which is simply* alpha open set (briefly, \(\mathop S\limits^{M*} - \alpha\) open set). This approach was used to introduce a new concept of separation axioms, from which fundamental properties and theorems of preservation

The development of the Internet of Things (IoT) widened its definition to incorporate aquatic conditions. The submarine sensor structures and intelligent underwater linked devices have been built into the IoT environment as the Internet of Underwater Things. Energy-sensitive and accurate data collection is carried out using extremely secure communications in underwater sensor networks that face major

Mobile ad hoc networks include VANETs (vehicular ad hoc networks) characterized to enhance vehicles’ wireless connectivity. In intelligent transportation systems (ITS), information can be exchanged over long distances as long as a means of retransmission exists. ITS uses the broadcasting technique for message transmission, and the network should have characteristics to overwhelm duplicate packets.

Inflation forecasting has been and continues to be an important issue for the world’s economies. Governments, through their central banks, watch closely inflation indicators to make national decisions and policies. This study proposes to forecast the inflation rate in five Latin American emerging economies based on the commonly used seasonal autoregressive integrated moving average (SARIMA) approach

With the rise of the mobile Internet, the number of mobile applications (apps) has shown explosive growth, which directly leads to the apps data overload. Currently, the recommender system has become the most effective method to solve the app data overload. However, most of the existing recommended methods for apps ignore the app functional exclusiveness features, which makes it difficult to further

Surgical rescheduling is necessary for adjusting initial schedules on surgery day after emergency demand is realized. While people-oriented medical service has been emphasized these years, the traditional rescheduling scheme which is only in pursuit of a great cost-related performance is no longer desirable since patients and medical staff are also highly involved in rescheduling and their preferences

The bounded diameter minimum spanning tree (BD-MST) problem seeks a spanning tree (T) of minimum weight on a given connected, undirected and edge-weighted graph subject to the diameter of T does not exceed \(D \ge 2\), where D is a given positive integer. The BD-MST problem is \({\mathcal {N}}{\mathcal {P}}\)-hard problem and finds many real-world applications. In this paper, we propose an artificial

The world population continues to increase which imposes rising demand in agriculture production. How to improve crop breeding to feed the growing population is a significant challenge. The traditional crop breeding is resource-intensive and time-consuming. Predictive modeling on crop yield can speed up the breeding process and make it resource-efficient. In this paper, a genetic algorithm (GA)-assisted

In this paper, we focuses on the theoretical analysis on the convergence of the beetle antennae search (BAS) algorithm. For the first time, we prove that the BAS algorithm is convergent with probability 1, which provides some insights about why the BAS algorithm works and also brings us some ideas about how to improve the BAS algorithm in the future. We also test the performance of the BAS algorithm

A group communication needs high security in cloud due to the security issues like group forward and backward secrecy. Many works have addressed those problems, but still they have some lack in their solutions. To address this issue, we propose a new deep learning-based key transmission (DLKT) protocol. This protocol gives the secure group communication in cloud by using autoencoder-based generative

The notion of the (dual) hull-kernel topology on a collection of prime filters in a residuated lattice is introduced and investigated. It is observed that any collection of prime filters is a \(T_0\) topological space under the (dual) hull-kernel topology. It is proved that any collection of prime filters is a \(T_1\) space if and only if it is an antichain, and it is a Hausdorff space if and only

Sustainability and performance assessment are significant aspects for organizations such as healthcare systems in order to make sustainable decisions and to improve the quality. A sustainability framework usually addresses economic, social and environmental impacts. In many real applications, uncertainty and imprecise data are also perceived. Therefore, the current study proposes a novel approach based

Over the last several years, payment information management using blockchain technology has generated great interest and development. Companies and authorities may exchange state information in real-time concerning logistics. Whenever a stakeholder changes the state of one or more items, like offloading a container from a vessel, anyone who has access will know this immediately. Nowadays, edge computing

With the development of science and technology and the improvement of people's quality of life, film and television animation has gradually become an important means to enrich people's daily entertainment and cultural exchanges. The inertial motion capture technology developed on the basis of motion capture has accelerated the development process of film and television animation, making film and television

Vehicular fog computing (VFC), combining the vehicular ad hoc network with fog computing, is an efficient vehicle communication architecture. However, the user data is often threatened since VFC is an open environment. Attribute-based encryption (ABE) is suitable for open scenarios, such as cloud and Internet of Things, because of its confidentiality and access control characteristics. However, the

Crowd counting is one of the most challenging issues in the computer vision community for safety and security through surveillance systems. It has extensive range of applications, such as disaster management, surveillance event detection, intelligence gathering and analysis, public safety control, traffic monitoring, design of public spaces, anomaly detection and military. Early approaches still encounter

In this paper, we first introduce some inequalities related to Jensen type for \(\sigma \)-\(\oplus \)-measure. Then, the concept of f-divergence for \( \sigma \)-\(\oplus \)-measure is studied. Finally, for finding the lower bound of the generalized f-divergence, some new inequalities are studied in information theory.

It is possible in a stock exchange that some candidate securities possess sufficient transaction data, and some others are newly listed and lack enough data. If an investor wants to choose a portfolio that contains two types of securities mentioned, none of the probability theory and uncertainty theory, alone, can be applied. In this case, the chance theory can be useful. For this purpose, in this

Automated vulnerability detection has become a research hot spot because it is beneficial for improving software quality and security. The code metric (CM) is one class of important representations of vulnerability in source code. The implicit relationships among different metric attributes have not been sufficiently considered in traditional vulnerability detection based on CMs. In this paper, in

User-preference based multi-objective evolutionary algorithms (MOEAs) have attracted much attention recently because it helps save computational cost, make better use of the knowledge offered by the decision-maker, and offer more insight into solutions in the region of interest (ROI). Weight vectors based MOEAs can be converted to their user-preference based versions by offering a set of evenly distributed

The accurate detection and tracking of pupil is important to many applications such as human–computer interaction, driver’s fatigue detection and diagnosis of brain diseases. Existing approaches however face challenges in handing low quality of pupil images. In this paper, we propose an integrated pupil tracking framework, namely LVCF, based on deep learning. LVCF consists of the pupil detection model

The direct measurement of speed in induction motors is costly and requires maintenance. Thus, sensorless techniques for estimating or predicting the speed in three-phase induction motors represent a feasible and economical solution. This work considers a single time delay neural network as a speed estimator in two different strategies of stator field-oriented induction motor drive: direct current and

Recent increases in computational power and the development of specialized architecture led to the possibility to perform machine learning, especially inference, on the edge. OpenVINO is a toolkit based on convolutional neural networks that facilitates fast-track development of computer vision algorithms and deep learning neural networks into vision applications, and enables their easy heterogeneous

The coronavirus disease 2019 (COVID-19) was first reported in December 2019 in Wuhan, China, and then moved to almost every country showing an unprecedented outbreak. The world health organization declared COVID-19 a pandemic. Since then, millions of people were infected, and millions have lost their lives all around the globe. By the end of 2020, effective vaccines that could prevent the fast spread

The developments in telecommunication and online facility resolutions help to connect the digital divide among urban and rural healthcare services administrations, empowering arrangement of appropriate medicinal finding and treatment discussions. Mobile-healthcare (m-Healthcare) systems can be used for quality improvement of healthcare and monitoring individuals with chronic diseases like heart disease

The expanding approval of e-learning structure has made the need for the customized suggestion prototype which can be utilized to advance the successful learning condition for the learners. Customized suggestion model is a particular sort of data separating framework used to recognize a lot of articles that are applicable to a e-learners. In this paper, we mainly propose the efficient e-learning recommendation

Recently, gene-culture coevolutionary multitasking, i.e., the multifactorial evolutionary algorithm (MFEA and MFEA-II), has become increasingly popular in the area of evolutionary computation. One of the most fascinating aspects of the MFEA is that it can obtain better optimization performance by exploiting underlying complementarities and/or commonalities between different tasks synchronously. In

As a promising option, Hydrogen as a clean energy alternative has been acknowledged for emissions alleviation and environmental safety. Life cycle sustainability evaluation of hydrogen can help the experts choose the desirable sustainable methodology for hydrogen production in life cycle standard over various options. This paper proposes a sustainable approach for selecting apt hydrogen production

A correction to this paper has been published: https://doi.org/10.1007/s00500-021-05882-3

It is well known that it is very difficult to solve constrained multiobjective optimization problems. Such problems not only need to optimize the objective function but also need to consider the constraints. The epsilon constraint handling method is commonly used, which releases the degree of constraint violations by defining a gradually decayed epsilon. However, for the solutions whose overall constraint

We introduce the notion of \(q^\prime \)-compactness for Sheffer stroke basic algebras and Visser algebras. Our goal is to determine when induced lattice of a Sheffer stroke basic algebra and a Visser algebra is a strongly algebraically closed algebra, and we find the condition that the lattices of complete congruences relations on a Sheffer stroke basic algebra are weakly relatively pseudocomplemented

Some existing feature subset selection algorithms use only one metric, such as symmetric uncertainty, to evaluate redundant features. These algorithms have the problem that some relevant features are considered as redundant and removed. To solve the problem, this paper proposes a feature subset selection algorithm based on equal interval division and three-way interaction information. Symmetric uncertainty

Looking for offer, an approximate solution of the Riccati’s differential equations in this research work is based on a fuzzy linguistic model (FLM). It is shown by the FLM that it is possible to approximate continuous functions which are satisfied at the interpolation points. To obtain the function as the approximation of the solution of the RDEs, fuzzy linguistic model (FLM) was used. In numerical

\(Q\)-neutrosophic soft sets are essentially neutrosophic soft sets characterized by three independent two-dimensional membership functions which stand for uncertainty, indeterminacy and falsity. Thus, it can be applied to two-dimensional imprecise, indeterminate and inconsistent data which appear in most real-life problems. Graph theory has now become a major branch of applied mathematics, and it

This paper proposes a new effective tool to address complex multicriteria decision-making problems where all decision-making information is provided by decision makers in both the trapezoidal neutrosophic environment and the bipolar neutrosophic environment. Relatedly, the concepts and operating laws of the bipolar trapezoidal neutrosophic set are defined. Some priority aggregate operators for the

Cooperation between upstream suppliers and downstream manufacturers in technology investment is a popular way to improve production technology for reducing suppliers’ production costs of key components. The suppliers’ cooperation strategies are mainly influenced by manufacturers’ technology investments and wholesale price discount contracts provided by suppliers. This paper explores whether a supplier

The proliferation in population and industrial expansion leads to more coal consumption. Many environmental protection bodies raise environmental issues, governments, and health authorities, especially air pollution, land use, water management, and waste management. The utilization of machine vision for the control and monitoring of industrial systems has improved intensely. Hence, in this paper, machine

Together with J. Paseka we introduced so-called sectionally pseudocomplemented lattices and posets and illuminated their role in algebraic constructions. We believe that—similar to relatively pseudocomplemented lattices—these structures can serve as an algebraic semantics of certain intuitionistic logics. The aim of the present paper is to define congruences and filters in these structures, derive

Watershed as a complex and dynamic system is considered to be a functional unit for planning and management strategies. It is important to take all technical, social, economic, physical, ecological and administrative aspects in the process of watersheds planning and management into account. Deciding in the watershed management is quite intricate due to existence of diverse agents and indices there